code
stringlengths 13
6.09M
| order_type
stringclasses 2
values | original_example
dict | step_ids
listlengths 1
5
|
|---|---|---|---|
# Parsing the raw.csv generated by running lis2dh_cluster.py
g = 9.806
def twos_complement(lsb, msb):
signBit = (msb & 0b10000000) >> 7
msb &= 0x7F # Strip off sign bit
if signBit:
x = (msb << 8) + lsb
x ^= 0x7FFF
x = -1 - x
else:
x = (msb << 8) + lsb
x = x>>6 # Remove left justification of data
return x
offset = 'not_set'
with open('raw.csv', 'r') as infile:
with open('parsed.csv', 'a') as outfile:
# Read the first line (the column headers)
headers = infile.readline().strip('\n\r')
headers = headers.split(';')
newheaders = []
for header in headers:
if header == 't': newheaders += ['t']
else: newheaders += [header+'x', header+'y', header+'z']
newheaders = ','.join(newheaders)
outfile.write(newheaders + '\n')
# Read and parse all sequential lines
line_in = infile.readline().strip('\n\r')
while line_in:
line_out = ''
data = line_in.split(';')
timestamp = eval(data[0])
if offset == 'not_set':
offset = timestamp
line_out += str(timestamp - offset)
for accel in data[1:]:
array = eval(accel) # Quick and dirty way of converting string to array
line_out += ','
line_out += str(twos_complement(array[0], array[1]))
line_out += ','
line_out += str(twos_complement(array[2], array[3]))
line_out += ','
line_out += str(twos_complement(array[4], array[5]))
line_out += '\n'
outfile.write(line_out)
try:
line_in = infile.readline().strip('\n\r')
except:
pass
|
normal
|
{
"blob_id": "a1b579494d20e8b8a26f7636ebd444252d2aa250",
"index": 4824,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef twos_complement(lsb, msb):\n signBit = (msb & 128) >> 7\n msb &= 127\n if signBit:\n x = (msb << 8) + lsb\n x ^= 32767\n x = -1 - x\n else:\n x = (msb << 8) + lsb\n x = x >> 6\n return x\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef twos_complement(lsb, msb):\n signBit = (msb & 128) >> 7\n msb &= 127\n if signBit:\n x = (msb << 8) + lsb\n x ^= 32767\n x = -1 - x\n else:\n x = (msb << 8) + lsb\n x = x >> 6\n return x\n\n\n<mask token>\nwith open('raw.csv', 'r') as infile:\n with open('parsed.csv', 'a') as outfile:\n headers = infile.readline().strip('\\n\\r')\n headers = headers.split(';')\n newheaders = []\n for header in headers:\n if header == 't':\n newheaders += ['t']\n else:\n newheaders += [header + 'x', header + 'y', header + 'z']\n newheaders = ','.join(newheaders)\n outfile.write(newheaders + '\\n')\n line_in = infile.readline().strip('\\n\\r')\n while line_in:\n line_out = ''\n data = line_in.split(';')\n timestamp = eval(data[0])\n if offset == 'not_set':\n offset = timestamp\n line_out += str(timestamp - offset)\n for accel in data[1:]:\n array = eval(accel)\n line_out += ','\n line_out += str(twos_complement(array[0], array[1]))\n line_out += ','\n line_out += str(twos_complement(array[2], array[3]))\n line_out += ','\n line_out += str(twos_complement(array[4], array[5]))\n line_out += '\\n'\n outfile.write(line_out)\n try:\n line_in = infile.readline().strip('\\n\\r')\n except:\n pass\n",
"step-4": "g = 9.806\n\n\ndef twos_complement(lsb, msb):\n signBit = (msb & 128) >> 7\n msb &= 127\n if signBit:\n x = (msb << 8) + lsb\n x ^= 32767\n x = -1 - x\n else:\n x = (msb << 8) + lsb\n x = x >> 6\n return x\n\n\noffset = 'not_set'\nwith open('raw.csv', 'r') as infile:\n with open('parsed.csv', 'a') as outfile:\n headers = infile.readline().strip('\\n\\r')\n headers = headers.split(';')\n newheaders = []\n for header in headers:\n if header == 't':\n newheaders += ['t']\n else:\n newheaders += [header + 'x', header + 'y', header + 'z']\n newheaders = ','.join(newheaders)\n outfile.write(newheaders + '\\n')\n line_in = infile.readline().strip('\\n\\r')\n while line_in:\n line_out = ''\n data = line_in.split(';')\n timestamp = eval(data[0])\n if offset == 'not_set':\n offset = timestamp\n line_out += str(timestamp - offset)\n for accel in data[1:]:\n array = eval(accel)\n line_out += ','\n line_out += str(twos_complement(array[0], array[1]))\n line_out += ','\n line_out += str(twos_complement(array[2], array[3]))\n line_out += ','\n line_out += str(twos_complement(array[4], array[5]))\n line_out += '\\n'\n outfile.write(line_out)\n try:\n line_in = infile.readline().strip('\\n\\r')\n except:\n pass\n",
"step-5": "# Parsing the raw.csv generated by running lis2dh_cluster.py\ng = 9.806\n\ndef twos_complement(lsb, msb):\n signBit = (msb & 0b10000000) >> 7\n msb &= 0x7F # Strip off sign bit\n if signBit:\n x = (msb << 8) + lsb\n x ^= 0x7FFF\n x = -1 - x\n else:\n x = (msb << 8) + lsb\n x = x>>6 # Remove left justification of data\n return x\n\n\noffset = 'not_set'\nwith open('raw.csv', 'r') as infile:\n with open('parsed.csv', 'a') as outfile:\n \n # Read the first line (the column headers)\n headers = infile.readline().strip('\\n\\r')\n headers = headers.split(';')\n newheaders = []\n for header in headers:\n if header == 't': newheaders += ['t']\n else: newheaders += [header+'x', header+'y', header+'z']\n newheaders = ','.join(newheaders)\n outfile.write(newheaders + '\\n')\n \n # Read and parse all sequential lines\n line_in = infile.readline().strip('\\n\\r')\n while line_in:\n line_out = ''\n data = line_in.split(';')\n timestamp = eval(data[0])\n if offset == 'not_set':\n offset = timestamp\n line_out += str(timestamp - offset)\n for accel in data[1:]:\n array = eval(accel) # Quick and dirty way of converting string to array\n line_out += ','\n line_out += str(twos_complement(array[0], array[1]))\n line_out += ','\n line_out += str(twos_complement(array[2], array[3]))\n line_out += ','\n line_out += str(twos_complement(array[4], array[5]))\n line_out += '\\n'\n outfile.write(line_out)\n try:\n line_in = infile.readline().strip('\\n\\r')\n except:\n pass",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
def upgrade():
op.drop_constraint('component_files_component_id_fkey', 'component_files')
op.drop_constraint('components_topic_id_fkey', 'components')
op.drop_constraint('files_job_id_fkey', 'files')
op.drop_constraint('files_jobstate_id_fkey', 'files')
op.drop_constraint('files_team_id_fkey', 'files')
op.drop_constraint('files_test_id_fkey', 'files')
op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')
op.drop_constraint('jobs_team_id_fkey', 'jobs')
op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')
op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')
op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')
op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')
op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')
op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')
op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')
op.drop_constraint('jobstates_team_id_fkey', 'jobstates')
op.drop_constraint('jobstates_job_id_fkey', 'jobstates')
op.drop_constraint('logs_team_id_fkey', 'logs')
op.drop_constraint('logs_user_id_fkey', 'logs')
op.drop_constraint('metas_job_id_fkey', 'metas')
op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')
op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')
op.drop_constraint('remotecis_team_id_fkey', 'remotecis')
op.drop_constraint('tests_team_id_fkey', 'tests')
op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')
op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')
op.drop_constraint('topics_next_topic_fkey', 'topics')
op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')
op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')
op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')
op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')
op.drop_constraint('users_team_id_fkey', 'users')
op.execute(
'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.create_foreign_key('component_files_component_id_fkey',
'component_files', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('components_topic_id_fkey', 'components',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [
'jobstate_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [
'test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [
'id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'
)
op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',
'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [
'remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [
'previous_job_id'], ['id'])
op.create_foreign_key('jobs_components_component_id_fkey',
'jobs_components', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',
'jobs', ['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',
'issues', ['issue_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [
'job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_remoteci_id_fkey',
'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [
'next_topic'], ['id'])
op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',
'teams', ['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',
'users', ['user_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_remoteci_id_fkey',
'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def upgrade():
op.drop_constraint('component_files_component_id_fkey', 'component_files')
op.drop_constraint('components_topic_id_fkey', 'components')
op.drop_constraint('files_job_id_fkey', 'files')
op.drop_constraint('files_jobstate_id_fkey', 'files')
op.drop_constraint('files_team_id_fkey', 'files')
op.drop_constraint('files_test_id_fkey', 'files')
op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')
op.drop_constraint('jobs_team_id_fkey', 'jobs')
op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')
op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')
op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')
op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')
op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')
op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')
op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')
op.drop_constraint('jobstates_team_id_fkey', 'jobstates')
op.drop_constraint('jobstates_job_id_fkey', 'jobstates')
op.drop_constraint('logs_team_id_fkey', 'logs')
op.drop_constraint('logs_user_id_fkey', 'logs')
op.drop_constraint('metas_job_id_fkey', 'metas')
op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')
op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')
op.drop_constraint('remotecis_team_id_fkey', 'remotecis')
op.drop_constraint('tests_team_id_fkey', 'tests')
op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')
op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')
op.drop_constraint('topics_next_topic_fkey', 'topics')
op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')
op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')
op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')
op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')
op.drop_constraint('users_team_id_fkey', 'users')
op.execute(
'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.create_foreign_key('component_files_component_id_fkey',
'component_files', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('components_topic_id_fkey', 'components',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [
'jobstate_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [
'test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [
'id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'
)
op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',
'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [
'remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [
'previous_job_id'], ['id'])
op.create_foreign_key('jobs_components_component_id_fkey',
'jobs_components', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',
'jobs', ['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',
'issues', ['issue_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [
'job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_remoteci_id_fkey',
'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [
'next_topic'], ['id'])
op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',
'teams', ['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',
'users', ['user_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_remoteci_id_fkey',
'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
def downgrade():
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
revision = '1bb42ff54435'
down_revision = '6bbbf58ed9de'
branch_labels = None
depends_on = None
<|reserved_special_token_0|>
def upgrade():
op.drop_constraint('component_files_component_id_fkey', 'component_files')
op.drop_constraint('components_topic_id_fkey', 'components')
op.drop_constraint('files_job_id_fkey', 'files')
op.drop_constraint('files_jobstate_id_fkey', 'files')
op.drop_constraint('files_team_id_fkey', 'files')
op.drop_constraint('files_test_id_fkey', 'files')
op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')
op.drop_constraint('jobs_team_id_fkey', 'jobs')
op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')
op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')
op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')
op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')
op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')
op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')
op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')
op.drop_constraint('jobstates_team_id_fkey', 'jobstates')
op.drop_constraint('jobstates_job_id_fkey', 'jobstates')
op.drop_constraint('logs_team_id_fkey', 'logs')
op.drop_constraint('logs_user_id_fkey', 'logs')
op.drop_constraint('metas_job_id_fkey', 'metas')
op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')
op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')
op.drop_constraint('remotecis_team_id_fkey', 'remotecis')
op.drop_constraint('tests_team_id_fkey', 'tests')
op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')
op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')
op.drop_constraint('topics_next_topic_fkey', 'topics')
op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')
op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')
op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')
op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')
op.drop_constraint('users_team_id_fkey', 'users')
op.execute(
'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.create_foreign_key('component_files_component_id_fkey',
'component_files', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('components_topic_id_fkey', 'components',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [
'jobstate_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [
'test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [
'id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'
)
op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',
'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [
'remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [
'previous_job_id'], ['id'])
op.create_foreign_key('jobs_components_component_id_fkey',
'jobs_components', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',
'jobs', ['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',
'issues', ['issue_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [
'job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_remoteci_id_fkey',
'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [
'next_topic'], ['id'])
op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',
'teams', ['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',
'users', ['user_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_remoteci_id_fkey',
'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
def downgrade():
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
revision = '1bb42ff54435'
down_revision = '6bbbf58ed9de'
branch_labels = None
depends_on = None
from alembic import op
def upgrade():
op.drop_constraint('component_files_component_id_fkey', 'component_files')
op.drop_constraint('components_topic_id_fkey', 'components')
op.drop_constraint('files_job_id_fkey', 'files')
op.drop_constraint('files_jobstate_id_fkey', 'files')
op.drop_constraint('files_team_id_fkey', 'files')
op.drop_constraint('files_test_id_fkey', 'files')
op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')
op.drop_constraint('jobs_team_id_fkey', 'jobs')
op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')
op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')
op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')
op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')
op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')
op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')
op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')
op.drop_constraint('jobstates_team_id_fkey', 'jobstates')
op.drop_constraint('jobstates_job_id_fkey', 'jobstates')
op.drop_constraint('logs_team_id_fkey', 'logs')
op.drop_constraint('logs_user_id_fkey', 'logs')
op.drop_constraint('metas_job_id_fkey', 'metas')
op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')
op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')
op.drop_constraint('remotecis_team_id_fkey', 'remotecis')
op.drop_constraint('tests_team_id_fkey', 'tests')
op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')
op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')
op.drop_constraint('topics_next_topic_fkey', 'topics')
op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')
op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')
op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')
op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')
op.drop_constraint('users_team_id_fkey', 'users')
op.execute(
'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'
)
op.execute(
'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'
)
op.execute(
'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'
)
op.execute(
'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'
)
op.execute(
'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'
)
op.create_foreign_key('component_files_component_id_fkey',
'component_files', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('components_topic_id_fkey', 'components',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [
'jobstate_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [
'test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [
'id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'
)
op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',
'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [
'remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [
'previous_job_id'], ['id'])
op.create_foreign_key('jobs_components_component_id_fkey',
'jobs_components', 'components', ['component_id'], ['id'], ondelete
='CASCADE')
op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',
'jobs', ['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',
'issues', ['issue_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [
'job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],
['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_remoteci_id_fkey',
'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',
'tests', ['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [
'next_topic'], ['id'])
op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',
'topics', ['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',
'teams', ['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',
'users', ['user_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_remoteci_id_fkey',
'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=
'CASCADE')
op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [
'team_id'], ['id'], ondelete='CASCADE')
def downgrade():
pass
<|reserved_special_token_1|>
#
# Copyright (C) 2017 Red Hat, Inc
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
"""Change varchar ID to UUID
Revision ID: 1bb42ff54435
Revises: 6bbbf58ed9de
Create Date: 2017-02-07 09:28:37.493302
"""
# revision identifiers, used by Alembic.
revision = '1bb42ff54435'
down_revision = '6bbbf58ed9de'
branch_labels = None
depends_on = None
from alembic import op
def upgrade():
# Drop constraint
op.drop_constraint('component_files_component_id_fkey', 'component_files')
op.drop_constraint('components_topic_id_fkey', 'components')
op.drop_constraint('files_job_id_fkey', 'files')
op.drop_constraint('files_jobstate_id_fkey', 'files')
op.drop_constraint('files_team_id_fkey', 'files')
op.drop_constraint('files_test_id_fkey', 'files')
op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests')
op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')
op.drop_constraint('jobs_team_id_fkey', 'jobs')
op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')
op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')
op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')
op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')
op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')
op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')
op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')
op.drop_constraint('jobstates_team_id_fkey', 'jobstates')
op.drop_constraint('jobstates_job_id_fkey', 'jobstates')
op.drop_constraint('logs_team_id_fkey', 'logs')
op.drop_constraint('logs_user_id_fkey', 'logs')
op.drop_constraint('metas_job_id_fkey', 'metas')
op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')
op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')
op.drop_constraint('remotecis_team_id_fkey', 'remotecis')
op.drop_constraint('tests_team_id_fkey', 'tests')
op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')
op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')
op.drop_constraint('topics_next_topic_fkey', 'topics')
op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')
op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')
op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')
op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')
op.drop_constraint('users_team_id_fkey', 'users')
# Change type
# Table component_files
op.execute("ALTER TABLE component_files ALTER COLUMN component_id TYPE \
UUID USING component_id::uuid")
op.execute("ALTER TABLE component_files ALTER COLUMN id TYPE \
UUID USING id::uuid")
# Table components
op.execute("ALTER TABLE components ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE components ALTER COLUMN topic_id TYPE \
UUID USING topic_id::uuid")
# Table files
op.execute("ALTER TABLE files ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE files ALTER COLUMN jobstate_id TYPE \
UUID USING jobstate_id::uuid")
op.execute("ALTER TABLE files ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
op.execute("ALTER TABLE files ALTER COLUMN job_id TYPE \
UUID USING job_id::uuid")
op.execute("ALTER TABLE files ALTER COLUMN test_id TYPE \
UUID USING test_id::uuid")
# Table issues
op.execute("ALTER TABLE issues ALTER COLUMN id TYPE \
UUID USING id::uuid")
# Table jobdefinition_tests
op.execute("ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id \
TYPE UUID USING jobdefinition_id::uuid")
op.execute("ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE \
UUID USING test_id::uuid")
# Table jobdefinitions
op.execute("ALTER TABLE jobdefinitions ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE \
UUID USING topic_id::uuid")
# Table jobs
op.execute("ALTER TABLE jobs ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE \
UUID USING jobdefinition_id::uuid")
op.execute("ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE \
UUID USING remoteci_id::uuid")
op.execute("ALTER TABLE jobs ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
op.execute("ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE \
UUID USING previous_job_id::uuid")
# Table jobs_components
op.execute("ALTER TABLE jobs_components ALTER COLUMN component_id TYPE \
UUID USING component_id::uuid")
op.execute("ALTER TABLE jobs_components ALTER COLUMN job_id TYPE \
UUID USING job_id::uuid")
# Table jobs_issues
op.execute("ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE \
UUID USING job_id::uuid")
op.execute("ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE \
UUID USING issue_id::uuid")
# Table jobstates
op.execute("ALTER TABLE jobstates ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE jobstates ALTER COLUMN job_id TYPE \
UUID USING job_id::uuid")
op.execute("ALTER TABLE jobstates ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
# Table logs
op.execute("ALTER TABLE logs ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE logs ALTER COLUMN user_id TYPE \
UUID USING user_id::uuid")
op.execute("ALTER TABLE logs ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
# Table metas
op.execute("ALTER TABLE metas ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE metas ALTER COLUMN job_id TYPE \
UUID USING job_id::uuid")
# Table remoteci_tests
op.execute("ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE \
UUID USING remoteci_id::uuid")
op.execute("ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE \
UUID USING test_id::uuid")
# Table remotecis
op.execute("ALTER TABLE remotecis ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE remotecis ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
# Table teams
op.execute("ALTER TABLE teams ALTER COLUMN id TYPE \
UUID USING id::uuid")
# Table tests
op.execute("ALTER TABLE tests ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE tests ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
# Table topic_tests
op.execute("ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE \
UUID USING topic_id::uuid")
op.execute("ALTER TABLE topic_tests ALTER COLUMN test_id TYPE \
UUID USING test_id::uuid")
# Table topics
op.execute("ALTER TABLE topics ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE topics ALTER COLUMN next_topic TYPE \
UUID USING next_topic::uuid")
# Table topics_teams
op.execute("ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE \
UUID USING topic_id::uuid")
op.execute("ALTER TABLE topics_teams ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
# Table user_remotecis
op.execute("ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE \
UUID USING user_id::uuid")
op.execute("ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE \
UUID USING remoteci_id::uuid")
# Table users
op.execute("ALTER TABLE users ALTER COLUMN id TYPE \
UUID USING id::uuid")
op.execute("ALTER TABLE users ALTER COLUMN team_id TYPE \
UUID USING team_id::uuid")
# Re-Create constraint
op.create_foreign_key('component_files_component_id_fkey',
'component_files', 'components',
['component_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('components_topic_id_fkey',
'components', 'topics',
['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_job_id_fkey',
'files', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_jobstate_id_fkey',
'files', 'jobstates',
['jobstate_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_team_id_fkey',
'files', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('files_test_id_fkey',
'files', 'tests',
['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',
'jobdefinition_tests', 'jobdefinitions',
['jobdefinition_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinition_tests_test_id_fkey',
'jobdefinition_tests', 'tests',
['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobdefinitions_topic_id_fkey',
'jobdefinitions', 'topics',
['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_team_id_fkey',
'jobs', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_jobdefinition_id_fkey',
'jobs', 'jobdefinitions',
['jobdefinition_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_remoteci_id_fkey',
'jobs', 'remotecis',
['remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_previous_job_id_fkey',
'jobs', 'jobs',
['previous_job_id'], ['id'])
op.create_foreign_key('jobs_components_component_id_fkey',
'jobs_components', 'components',
['component_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_components_job_id_fkey',
'jobs_components', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_issue_id_fkey',
'jobs_issues', 'issues',
['issue_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobs_issues_job_id_fkey',
'jobs_issues', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_team_id_fkey',
'jobstates', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('jobstates_job_id_fkey',
'jobstates', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('logs_team_id_fkey',
'logs', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('logs_user_id_fkey',
'logs', 'users',
['user_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('metas_job_id_fkey',
'metas', 'jobs',
['job_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_test_id_fkey',
'remoteci_tests', 'tests',
['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remoteci_tests_remoteci_id_fkey',
'remoteci_tests', 'remotecis',
['remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('remotecis_team_id_fkey',
'remotecis', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('tests_team_id_fkey',
'tests', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_test_id_fkey',
'topic_tests', 'tests',
['test_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topic_tests_topic_id_fkey',
'topic_tests', 'topics',
['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_next_topic_fkey',
'topics', 'topics',
['next_topic'], ['id'])
op.create_foreign_key('topics_teams_topic_id_fkey',
'topics_teams', 'topics',
['topic_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('topics_teams_team_id_fkey',
'topics_teams', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_user_id_fkey',
'user_remotecis', 'users',
['user_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('user_remotecis_remoteci_id_fkey',
'user_remotecis', 'remotecis',
['remoteci_id'], ['id'], ondelete='CASCADE')
op.create_foreign_key('users_team_id_fkey',
'users', 'teams',
['team_id'], ['id'], ondelete='CASCADE')
def downgrade():
pass
|
flexible
|
{
"blob_id": "a34584a71fdff65e5b1bb15a6304af79774dac2c",
"index": 1315,
"step-1": "<mask token>\n\n\ndef upgrade():\n op.drop_constraint('component_files_component_id_fkey', 'component_files')\n op.drop_constraint('components_topic_id_fkey', 'components')\n op.drop_constraint('files_job_id_fkey', 'files')\n op.drop_constraint('files_jobstate_id_fkey', 'files')\n op.drop_constraint('files_team_id_fkey', 'files')\n op.drop_constraint('files_test_id_fkey', 'files')\n op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')\n op.drop_constraint('jobs_team_id_fkey', 'jobs')\n op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')\n op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')\n op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')\n op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')\n op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')\n op.drop_constraint('jobstates_team_id_fkey', 'jobstates')\n op.drop_constraint('jobstates_job_id_fkey', 'jobstates')\n op.drop_constraint('logs_team_id_fkey', 'logs')\n op.drop_constraint('logs_user_id_fkey', 'logs')\n op.drop_constraint('metas_job_id_fkey', 'metas')\n op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')\n op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')\n op.drop_constraint('remotecis_team_id_fkey', 'remotecis')\n op.drop_constraint('tests_team_id_fkey', 'tests')\n op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')\n op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')\n op.drop_constraint('topics_next_topic_fkey', 'topics')\n op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')\n op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')\n op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')\n op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')\n op.drop_constraint('users_team_id_fkey', 'users')\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.create_foreign_key('component_files_component_id_fkey',\n 'component_files', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('components_topic_id_fkey', 'components',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [\n 'jobstate_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [\n 'test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [\n 'id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'\n )\n op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',\n 'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [\n 'remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [\n 'previous_job_id'], ['id'])\n op.create_foreign_key('jobs_components_component_id_fkey',\n 'jobs_components', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',\n 'jobs', ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',\n 'issues', ['issue_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [\n 'job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_remoteci_id_fkey',\n 'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [\n 'next_topic'], ['id'])\n op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',\n 'teams', ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',\n 'users', ['user_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_remoteci_id_fkey',\n 'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef upgrade():\n op.drop_constraint('component_files_component_id_fkey', 'component_files')\n op.drop_constraint('components_topic_id_fkey', 'components')\n op.drop_constraint('files_job_id_fkey', 'files')\n op.drop_constraint('files_jobstate_id_fkey', 'files')\n op.drop_constraint('files_team_id_fkey', 'files')\n op.drop_constraint('files_test_id_fkey', 'files')\n op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')\n op.drop_constraint('jobs_team_id_fkey', 'jobs')\n op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')\n op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')\n op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')\n op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')\n op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')\n op.drop_constraint('jobstates_team_id_fkey', 'jobstates')\n op.drop_constraint('jobstates_job_id_fkey', 'jobstates')\n op.drop_constraint('logs_team_id_fkey', 'logs')\n op.drop_constraint('logs_user_id_fkey', 'logs')\n op.drop_constraint('metas_job_id_fkey', 'metas')\n op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')\n op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')\n op.drop_constraint('remotecis_team_id_fkey', 'remotecis')\n op.drop_constraint('tests_team_id_fkey', 'tests')\n op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')\n op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')\n op.drop_constraint('topics_next_topic_fkey', 'topics')\n op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')\n op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')\n op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')\n op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')\n op.drop_constraint('users_team_id_fkey', 'users')\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.create_foreign_key('component_files_component_id_fkey',\n 'component_files', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('components_topic_id_fkey', 'components',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [\n 'jobstate_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [\n 'test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [\n 'id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'\n )\n op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',\n 'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [\n 'remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [\n 'previous_job_id'], ['id'])\n op.create_foreign_key('jobs_components_component_id_fkey',\n 'jobs_components', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',\n 'jobs', ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',\n 'issues', ['issue_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [\n 'job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_remoteci_id_fkey',\n 'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [\n 'next_topic'], ['id'])\n op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',\n 'teams', ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',\n 'users', ['user_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_remoteci_id_fkey',\n 'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n\n\ndef downgrade():\n pass\n",
"step-3": "<mask token>\nrevision = '1bb42ff54435'\ndown_revision = '6bbbf58ed9de'\nbranch_labels = None\ndepends_on = None\n<mask token>\n\n\ndef upgrade():\n op.drop_constraint('component_files_component_id_fkey', 'component_files')\n op.drop_constraint('components_topic_id_fkey', 'components')\n op.drop_constraint('files_job_id_fkey', 'files')\n op.drop_constraint('files_jobstate_id_fkey', 'files')\n op.drop_constraint('files_team_id_fkey', 'files')\n op.drop_constraint('files_test_id_fkey', 'files')\n op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')\n op.drop_constraint('jobs_team_id_fkey', 'jobs')\n op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')\n op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')\n op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')\n op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')\n op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')\n op.drop_constraint('jobstates_team_id_fkey', 'jobstates')\n op.drop_constraint('jobstates_job_id_fkey', 'jobstates')\n op.drop_constraint('logs_team_id_fkey', 'logs')\n op.drop_constraint('logs_user_id_fkey', 'logs')\n op.drop_constraint('metas_job_id_fkey', 'metas')\n op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')\n op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')\n op.drop_constraint('remotecis_team_id_fkey', 'remotecis')\n op.drop_constraint('tests_team_id_fkey', 'tests')\n op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')\n op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')\n op.drop_constraint('topics_next_topic_fkey', 'topics')\n op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')\n op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')\n op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')\n op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')\n op.drop_constraint('users_team_id_fkey', 'users')\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.create_foreign_key('component_files_component_id_fkey',\n 'component_files', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('components_topic_id_fkey', 'components',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [\n 'jobstate_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [\n 'test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [\n 'id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'\n )\n op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',\n 'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [\n 'remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [\n 'previous_job_id'], ['id'])\n op.create_foreign_key('jobs_components_component_id_fkey',\n 'jobs_components', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',\n 'jobs', ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',\n 'issues', ['issue_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [\n 'job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_remoteci_id_fkey',\n 'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [\n 'next_topic'], ['id'])\n op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',\n 'teams', ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',\n 'users', ['user_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_remoteci_id_fkey',\n 'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n\n\ndef downgrade():\n pass\n",
"step-4": "<mask token>\nrevision = '1bb42ff54435'\ndown_revision = '6bbbf58ed9de'\nbranch_labels = None\ndepends_on = None\nfrom alembic import op\n\n\ndef upgrade():\n op.drop_constraint('component_files_component_id_fkey', 'component_files')\n op.drop_constraint('components_topic_id_fkey', 'components')\n op.drop_constraint('files_job_id_fkey', 'files')\n op.drop_constraint('files_jobstate_id_fkey', 'files')\n op.drop_constraint('files_team_id_fkey', 'files')\n op.drop_constraint('files_test_id_fkey', 'files')\n op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')\n op.drop_constraint('jobs_team_id_fkey', 'jobs')\n op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')\n op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')\n op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')\n op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')\n op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')\n op.drop_constraint('jobstates_team_id_fkey', 'jobstates')\n op.drop_constraint('jobstates_job_id_fkey', 'jobstates')\n op.drop_constraint('logs_team_id_fkey', 'logs')\n op.drop_constraint('logs_user_id_fkey', 'logs')\n op.drop_constraint('metas_job_id_fkey', 'metas')\n op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')\n op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')\n op.drop_constraint('remotecis_team_id_fkey', 'remotecis')\n op.drop_constraint('tests_team_id_fkey', 'tests')\n op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')\n op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')\n op.drop_constraint('topics_next_topic_fkey', 'topics')\n op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')\n op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')\n op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')\n op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')\n op.drop_constraint('users_team_id_fkey', 'users')\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE component_files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE components ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN jobstate_id TYPE UUID USING jobstate_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE files ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE issues ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE UUID USING jobdefinition_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE UUID USING previous_job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN component_id TYPE UUID USING component_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_components ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE UUID USING issue_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE jobstates ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE logs ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE metas ALTER COLUMN job_id TYPE UUID USING job_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE remotecis ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE teams ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE tests ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topic_tests ALTER COLUMN test_id TYPE UUID USING test_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics ALTER COLUMN next_topic TYPE UUID USING next_topic::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE UUID USING topic_id::uuid'\n )\n op.execute(\n 'ALTER TABLE topics_teams ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE UUID USING user_id::uuid'\n )\n op.execute(\n 'ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE UUID USING remoteci_id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN id TYPE UUID USING id::uuid'\n )\n op.execute(\n 'ALTER TABLE users ALTER COLUMN team_id TYPE UUID USING team_id::uuid'\n )\n op.create_foreign_key('component_files_component_id_fkey',\n 'component_files', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('components_topic_id_fkey', 'components',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_job_id_fkey', 'files', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_jobstate_id_fkey', 'files', 'jobstates', [\n 'jobstate_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_team_id_fkey', 'files', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_test_id_fkey', 'files', 'tests', [\n 'test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests', 'jobdefinitions', ['jobdefinition_id'], [\n 'id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests', 'tests', ['test_id'], ['id'], ondelete='CASCADE'\n )\n op.create_foreign_key('jobdefinitions_topic_id_fkey', 'jobdefinitions',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_team_id_fkey', 'jobs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_jobdefinition_id_fkey', 'jobs',\n 'jobdefinitions', ['jobdefinition_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_remoteci_id_fkey', 'jobs', 'remotecis', [\n 'remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_previous_job_id_fkey', 'jobs', 'jobs', [\n 'previous_job_id'], ['id'])\n op.create_foreign_key('jobs_components_component_id_fkey',\n 'jobs_components', 'components', ['component_id'], ['id'], ondelete\n ='CASCADE')\n op.create_foreign_key('jobs_components_job_id_fkey', 'jobs_components',\n 'jobs', ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_issue_id_fkey', 'jobs_issues',\n 'issues', ['issue_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_job_id_fkey', 'jobs_issues', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_team_id_fkey', 'jobstates', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_job_id_fkey', 'jobstates', 'jobs', [\n 'job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_team_id_fkey', 'logs', 'teams', ['team_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_user_id_fkey', 'logs', 'users', ['user_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('metas_job_id_fkey', 'metas', 'jobs', ['job_id'],\n ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_test_id_fkey', 'remoteci_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_remoteci_id_fkey',\n 'remoteci_tests', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('remotecis_team_id_fkey', 'remotecis', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('tests_team_id_fkey', 'tests', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_test_id_fkey', 'topic_tests',\n 'tests', ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_topic_id_fkey', 'topic_tests',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_next_topic_fkey', 'topics', 'topics', [\n 'next_topic'], ['id'])\n op.create_foreign_key('topics_teams_topic_id_fkey', 'topics_teams',\n 'topics', ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_teams_team_id_fkey', 'topics_teams',\n 'teams', ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_user_id_fkey', 'user_remotecis',\n 'users', ['user_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_remoteci_id_fkey',\n 'user_remotecis', 'remotecis', ['remoteci_id'], ['id'], ondelete=\n 'CASCADE')\n op.create_foreign_key('users_team_id_fkey', 'users', 'teams', [\n 'team_id'], ['id'], ondelete='CASCADE')\n\n\ndef downgrade():\n pass\n",
"step-5": "#\n# Copyright (C) 2017 Red Hat, Inc\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\n\"\"\"Change varchar ID to UUID\n\nRevision ID: 1bb42ff54435\nRevises: 6bbbf58ed9de\nCreate Date: 2017-02-07 09:28:37.493302\n\n\"\"\"\n\n# revision identifiers, used by Alembic.\nrevision = '1bb42ff54435'\ndown_revision = '6bbbf58ed9de'\nbranch_labels = None\ndepends_on = None\n\nfrom alembic import op\n\n\ndef upgrade():\n # Drop constraint\n op.drop_constraint('component_files_component_id_fkey', 'component_files')\n op.drop_constraint('components_topic_id_fkey', 'components')\n op.drop_constraint('files_job_id_fkey', 'files')\n op.drop_constraint('files_jobstate_id_fkey', 'files')\n op.drop_constraint('files_team_id_fkey', 'files')\n op.drop_constraint('files_test_id_fkey', 'files')\n op.drop_constraint('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests')\n op.drop_constraint('jobdefinitions_topic_id_fkey', 'jobdefinitions')\n op.drop_constraint('jobs_team_id_fkey', 'jobs')\n op.drop_constraint('jobs_jobdefinition_id_fkey', 'jobs')\n op.drop_constraint('jobs_remoteci_id_fkey', 'jobs')\n op.drop_constraint('jobs_previous_job_id_fkey', 'jobs')\n op.drop_constraint('jobs_components_component_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_components_job_id_fkey', 'jobs_components')\n op.drop_constraint('jobs_issues_issue_id_fkey', 'jobs_issues')\n op.drop_constraint('jobs_issues_job_id_fkey', 'jobs_issues')\n op.drop_constraint('jobstates_team_id_fkey', 'jobstates')\n op.drop_constraint('jobstates_job_id_fkey', 'jobstates')\n op.drop_constraint('logs_team_id_fkey', 'logs')\n op.drop_constraint('logs_user_id_fkey', 'logs')\n op.drop_constraint('metas_job_id_fkey', 'metas')\n op.drop_constraint('remoteci_tests_test_id_fkey', 'remoteci_tests')\n op.drop_constraint('remoteci_tests_remoteci_id_fkey', 'remoteci_tests')\n op.drop_constraint('remotecis_team_id_fkey', 'remotecis')\n op.drop_constraint('tests_team_id_fkey', 'tests')\n op.drop_constraint('topic_tests_test_id_fkey', 'topic_tests')\n op.drop_constraint('topic_tests_topic_id_fkey', 'topic_tests')\n op.drop_constraint('topics_next_topic_fkey', 'topics')\n op.drop_constraint('topics_teams_topic_id_fkey', 'topics_teams')\n op.drop_constraint('topics_teams_team_id_fkey', 'topics_teams')\n op.drop_constraint('user_remotecis_user_id_fkey', 'user_remotecis')\n op.drop_constraint('user_remotecis_remoteci_id_fkey', 'user_remotecis')\n op.drop_constraint('users_team_id_fkey', 'users')\n\n # Change type\n # Table component_files\n op.execute(\"ALTER TABLE component_files ALTER COLUMN component_id TYPE \\\n UUID USING component_id::uuid\")\n op.execute(\"ALTER TABLE component_files ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n\n # Table components\n op.execute(\"ALTER TABLE components ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE components ALTER COLUMN topic_id TYPE \\\n UUID USING topic_id::uuid\")\n\n # Table files\n op.execute(\"ALTER TABLE files ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE files ALTER COLUMN jobstate_id TYPE \\\n UUID USING jobstate_id::uuid\")\n op.execute(\"ALTER TABLE files ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n op.execute(\"ALTER TABLE files ALTER COLUMN job_id TYPE \\\n UUID USING job_id::uuid\")\n op.execute(\"ALTER TABLE files ALTER COLUMN test_id TYPE \\\n UUID USING test_id::uuid\")\n\n # Table issues\n op.execute(\"ALTER TABLE issues ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n\n # Table jobdefinition_tests\n op.execute(\"ALTER TABLE jobdefinition_tests ALTER COLUMN jobdefinition_id \\\n TYPE UUID USING jobdefinition_id::uuid\")\n op.execute(\"ALTER TABLE jobdefinition_tests ALTER COLUMN test_id TYPE \\\n UUID USING test_id::uuid\")\n\n # Table jobdefinitions\n op.execute(\"ALTER TABLE jobdefinitions ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE jobdefinitions ALTER COLUMN topic_id TYPE \\\n UUID USING topic_id::uuid\")\n\n # Table jobs\n op.execute(\"ALTER TABLE jobs ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE jobs ALTER COLUMN jobdefinition_id TYPE \\\n UUID USING jobdefinition_id::uuid\")\n op.execute(\"ALTER TABLE jobs ALTER COLUMN remoteci_id TYPE \\\n UUID USING remoteci_id::uuid\")\n op.execute(\"ALTER TABLE jobs ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n op.execute(\"ALTER TABLE jobs ALTER COLUMN previous_job_id TYPE \\\n UUID USING previous_job_id::uuid\")\n\n # Table jobs_components\n op.execute(\"ALTER TABLE jobs_components ALTER COLUMN component_id TYPE \\\n UUID USING component_id::uuid\")\n op.execute(\"ALTER TABLE jobs_components ALTER COLUMN job_id TYPE \\\n UUID USING job_id::uuid\")\n\n # Table jobs_issues\n op.execute(\"ALTER TABLE jobs_issues ALTER COLUMN job_id TYPE \\\n UUID USING job_id::uuid\")\n op.execute(\"ALTER TABLE jobs_issues ALTER COLUMN issue_id TYPE \\\n UUID USING issue_id::uuid\")\n\n # Table jobstates\n op.execute(\"ALTER TABLE jobstates ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE jobstates ALTER COLUMN job_id TYPE \\\n UUID USING job_id::uuid\")\n op.execute(\"ALTER TABLE jobstates ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n\n # Table logs\n op.execute(\"ALTER TABLE logs ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE logs ALTER COLUMN user_id TYPE \\\n UUID USING user_id::uuid\")\n op.execute(\"ALTER TABLE logs ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n\n # Table metas\n op.execute(\"ALTER TABLE metas ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE metas ALTER COLUMN job_id TYPE \\\n UUID USING job_id::uuid\")\n\n # Table remoteci_tests\n op.execute(\"ALTER TABLE remoteci_tests ALTER COLUMN remoteci_id TYPE \\\n UUID USING remoteci_id::uuid\")\n op.execute(\"ALTER TABLE remoteci_tests ALTER COLUMN test_id TYPE \\\n UUID USING test_id::uuid\")\n\n # Table remotecis\n op.execute(\"ALTER TABLE remotecis ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE remotecis ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n\n # Table teams\n op.execute(\"ALTER TABLE teams ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n\n # Table tests\n op.execute(\"ALTER TABLE tests ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE tests ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n\n # Table topic_tests\n op.execute(\"ALTER TABLE topic_tests ALTER COLUMN topic_id TYPE \\\n UUID USING topic_id::uuid\")\n op.execute(\"ALTER TABLE topic_tests ALTER COLUMN test_id TYPE \\\n UUID USING test_id::uuid\")\n\n # Table topics\n op.execute(\"ALTER TABLE topics ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE topics ALTER COLUMN next_topic TYPE \\\n UUID USING next_topic::uuid\")\n\n # Table topics_teams\n op.execute(\"ALTER TABLE topics_teams ALTER COLUMN topic_id TYPE \\\n UUID USING topic_id::uuid\")\n op.execute(\"ALTER TABLE topics_teams ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n\n # Table user_remotecis\n op.execute(\"ALTER TABLE user_remotecis ALTER COLUMN user_id TYPE \\\n UUID USING user_id::uuid\")\n op.execute(\"ALTER TABLE user_remotecis ALTER COLUMN remoteci_id TYPE \\\n UUID USING remoteci_id::uuid\")\n\n # Table users\n op.execute(\"ALTER TABLE users ALTER COLUMN id TYPE \\\n UUID USING id::uuid\")\n op.execute(\"ALTER TABLE users ALTER COLUMN team_id TYPE \\\n UUID USING team_id::uuid\")\n\n # Re-Create constraint\n op.create_foreign_key('component_files_component_id_fkey',\n 'component_files', 'components',\n ['component_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('components_topic_id_fkey',\n 'components', 'topics',\n ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_job_id_fkey',\n 'files', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_jobstate_id_fkey',\n 'files', 'jobstates',\n ['jobstate_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_team_id_fkey',\n 'files', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('files_test_id_fkey',\n 'files', 'tests',\n ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_jobdefinition_id_fkey',\n 'jobdefinition_tests', 'jobdefinitions',\n ['jobdefinition_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinition_tests_test_id_fkey',\n 'jobdefinition_tests', 'tests',\n ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobdefinitions_topic_id_fkey',\n 'jobdefinitions', 'topics',\n ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_team_id_fkey',\n 'jobs', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_jobdefinition_id_fkey',\n 'jobs', 'jobdefinitions',\n ['jobdefinition_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_remoteci_id_fkey',\n 'jobs', 'remotecis',\n ['remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_previous_job_id_fkey',\n 'jobs', 'jobs',\n ['previous_job_id'], ['id'])\n op.create_foreign_key('jobs_components_component_id_fkey',\n 'jobs_components', 'components',\n ['component_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_components_job_id_fkey',\n 'jobs_components', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_issue_id_fkey',\n 'jobs_issues', 'issues',\n ['issue_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobs_issues_job_id_fkey',\n 'jobs_issues', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_team_id_fkey',\n 'jobstates', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('jobstates_job_id_fkey',\n 'jobstates', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_team_id_fkey',\n 'logs', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('logs_user_id_fkey',\n 'logs', 'users',\n ['user_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('metas_job_id_fkey',\n 'metas', 'jobs',\n ['job_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_test_id_fkey',\n 'remoteci_tests', 'tests',\n ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remoteci_tests_remoteci_id_fkey',\n 'remoteci_tests', 'remotecis',\n ['remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('remotecis_team_id_fkey',\n 'remotecis', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('tests_team_id_fkey',\n 'tests', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_test_id_fkey',\n 'topic_tests', 'tests',\n ['test_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topic_tests_topic_id_fkey',\n 'topic_tests', 'topics',\n ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_next_topic_fkey',\n 'topics', 'topics',\n ['next_topic'], ['id'])\n op.create_foreign_key('topics_teams_topic_id_fkey',\n 'topics_teams', 'topics',\n ['topic_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('topics_teams_team_id_fkey',\n 'topics_teams', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_user_id_fkey',\n 'user_remotecis', 'users',\n ['user_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('user_remotecis_remoteci_id_fkey',\n 'user_remotecis', 'remotecis',\n ['remoteci_id'], ['id'], ondelete='CASCADE')\n op.create_foreign_key('users_team_id_fkey',\n 'users', 'teams',\n ['team_id'], ['id'], ondelete='CASCADE')\n\n\ndef downgrade():\n pass\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
reload(plib)
reload(rdl)
<|reserved_special_token_0|>
plt.rcParams.update(params)
<|reserved_special_token_0|>
if not os.path.exists(outpath):
os.mkdir(outpath)
plt.close('all')
<|reserved_special_token_0|>
if config['plot_param_space']:
for desc in search_res:
fig = plt.figure()
plib.plot_search_matrix(fig, search_res[desc], config['fselection'],
config['method'], config.get('glomeruli', []))
fig.savefig(os.path.join(outpath, config['method'] + '_' + desc +
'.' + config['format']))
<|reserved_special_token_0|>
plib.new_descriptor_performance_plot(fig, max_overview, config['fselection'
], config['method'], config.get('glomeruli', []), ptype)
fig.subplots_adjust(bottom=0.25)
fig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config[
'format']), dpi=600)
<|reserved_special_token_0|>
for i, desc in enumerate(desc2comp):
desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)
desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)
desc1_collect.extend(max_overview['svr']['linear']['p_selection'][
desc_idx1, :])
desc2_collect.extend(max_overview['forest']['forest']['p_selection'][
desc_idx2, :])
ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],
max_overview['forest']['forest']['p_selection'][desc_idx2, :], 'o',
mfc=markers[i], label=desc, markersize=5)
ax.plot([0, 0.8], [0, 0.8], color='0.5')
plt.axis('scaled')
ax.set_xlim([0, 0.9])
ax.set_ylim([0, 0.9])
ax.set_xlabel('SVR (q2)')
ax.set_ylabel('RFR (q2)')
utils.simple_axis(ax)
ax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size':
'small'}, bbox_to_anchor=(0.01, 1))
<|reserved_special_token_0|>
ax.set_yticks(ticks)
ax.set_yticklabels(ticklabels)
ax.set_xticks(ticks)
ax.set_xticklabels(ticklabels)
fig.subplots_adjust(bottom=0.2)
fig.tight_layout()
fig.savefig(os.path.join(outpath, 'best_method_comparison.' + config[
'format']), dpi=600)
assert len(desc1_collect) == len(desc2_collect)
<|reserved_special_token_0|>
print('svr better than rfr in {:.2f} \\% of the cases'.format(ratio))
if utils.run_from_ipython():
plt.show()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
reload(plib)
reload(rdl)
params = {'axes.labelsize': 6, 'font.size': 6, 'legend.fontsize': 7,
'xtick.labelsize': 6, 'ytick.labelsize': 6}
plt.rcParams.update(params)
config = json.load(open(sys.argv[1]))
outpath = os.path.join(config['inpath'], 'plots')
if not os.path.exists(outpath):
os.mkdir(outpath)
plt.close('all')
search_res, max_overview, sc, _ = rdl.read_paramsearch_results(config[
'inpath'], p_selection=config.get('selection', {}))
if config['plot_param_space']:
for desc in search_res:
fig = plt.figure()
plib.plot_search_matrix(fig, search_res[desc], config['fselection'],
config['method'], config.get('glomeruli', []))
fig.savefig(os.path.join(outpath, config['method'] + '_' + desc +
'.' + config['format']))
fig = plt.figure(figsize=(3.35, 2))
ptype = config['descriptor_plot_type']
plib.new_descriptor_performance_plot(fig, max_overview, config['fselection'
], config['method'], config.get('glomeruli', []), ptype)
fig.subplots_adjust(bottom=0.25)
fig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config[
'format']), dpi=600)
markers = ['1', '0']
desc2comp = ['EVA_100', 'all']
fig = plt.figure(figsize=(3.35, 1.8))
ax = fig.add_subplot(111)
desc1_collect, desc2_collect = [], []
for i, desc in enumerate(desc2comp):
desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)
desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)
desc1_collect.extend(max_overview['svr']['linear']['p_selection'][
desc_idx1, :])
desc2_collect.extend(max_overview['forest']['forest']['p_selection'][
desc_idx2, :])
ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],
max_overview['forest']['forest']['p_selection'][desc_idx2, :], 'o',
mfc=markers[i], label=desc, markersize=5)
ax.plot([0, 0.8], [0, 0.8], color='0.5')
plt.axis('scaled')
ax.set_xlim([0, 0.9])
ax.set_ylim([0, 0.9])
ax.set_xlabel('SVR (q2)')
ax.set_ylabel('RFR (q2)')
utils.simple_axis(ax)
ax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size':
'small'}, bbox_to_anchor=(0.01, 1))
ticks = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
ticklabels = ['0', '', '.2', '', '.4', '', '.6', '', '.8', '']
ax.set_yticks(ticks)
ax.set_yticklabels(ticklabels)
ax.set_xticks(ticks)
ax.set_xticklabels(ticklabels)
fig.subplots_adjust(bottom=0.2)
fig.tight_layout()
fig.savefig(os.path.join(outpath, 'best_method_comparison.' + config[
'format']), dpi=600)
assert len(desc1_collect) == len(desc2_collect)
svr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if
d1 > d2])
rfr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if
d1 < d2])
ratio = float(svr_better) / (np.sum(rfr_better) + np.sum(svr_better))
print('svr better than rfr in {:.2f} \\% of the cases'.format(ratio))
if utils.run_from_ipython():
plt.show()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
import sys
import os
import json
import numpy as np
import pylab as plt
import itertools as it
from master.libs import plot_lib as plib
from master.libs import read_data_lib as rdl
from master.libs import utils
import matplotlib.gridspec as gridspec
reload(plib)
reload(rdl)
params = {'axes.labelsize': 6, 'font.size': 6, 'legend.fontsize': 7,
'xtick.labelsize': 6, 'ytick.labelsize': 6}
plt.rcParams.update(params)
config = json.load(open(sys.argv[1]))
outpath = os.path.join(config['inpath'], 'plots')
if not os.path.exists(outpath):
os.mkdir(outpath)
plt.close('all')
search_res, max_overview, sc, _ = rdl.read_paramsearch_results(config[
'inpath'], p_selection=config.get('selection', {}))
if config['plot_param_space']:
for desc in search_res:
fig = plt.figure()
plib.plot_search_matrix(fig, search_res[desc], config['fselection'],
config['method'], config.get('glomeruli', []))
fig.savefig(os.path.join(outpath, config['method'] + '_' + desc +
'.' + config['format']))
fig = plt.figure(figsize=(3.35, 2))
ptype = config['descriptor_plot_type']
plib.new_descriptor_performance_plot(fig, max_overview, config['fselection'
], config['method'], config.get('glomeruli', []), ptype)
fig.subplots_adjust(bottom=0.25)
fig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config[
'format']), dpi=600)
markers = ['1', '0']
desc2comp = ['EVA_100', 'all']
fig = plt.figure(figsize=(3.35, 1.8))
ax = fig.add_subplot(111)
desc1_collect, desc2_collect = [], []
for i, desc in enumerate(desc2comp):
desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)
desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)
desc1_collect.extend(max_overview['svr']['linear']['p_selection'][
desc_idx1, :])
desc2_collect.extend(max_overview['forest']['forest']['p_selection'][
desc_idx2, :])
ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],
max_overview['forest']['forest']['p_selection'][desc_idx2, :], 'o',
mfc=markers[i], label=desc, markersize=5)
ax.plot([0, 0.8], [0, 0.8], color='0.5')
plt.axis('scaled')
ax.set_xlim([0, 0.9])
ax.set_ylim([0, 0.9])
ax.set_xlabel('SVR (q2)')
ax.set_ylabel('RFR (q2)')
utils.simple_axis(ax)
ax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size':
'small'}, bbox_to_anchor=(0.01, 1))
ticks = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
ticklabels = ['0', '', '.2', '', '.4', '', '.6', '', '.8', '']
ax.set_yticks(ticks)
ax.set_yticklabels(ticklabels)
ax.set_xticks(ticks)
ax.set_xticklabels(ticklabels)
fig.subplots_adjust(bottom=0.2)
fig.tight_layout()
fig.savefig(os.path.join(outpath, 'best_method_comparison.' + config[
'format']), dpi=600)
assert len(desc1_collect) == len(desc2_collect)
svr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if
d1 > d2])
rfr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if
d1 < d2])
ratio = float(svr_better) / (np.sum(rfr_better) + np.sum(svr_better))
print('svr better than rfr in {:.2f} \\% of the cases'.format(ratio))
if utils.run_from_ipython():
plt.show()
<|reserved_special_token_1|>
#!/usr/bin/env python
# encoding: utf-8
"""
plot: regularization on x axis, number of k_best features on y
Created by on 2012-01-27.
Copyright (c) 2012. All rights reserved.
"""
import sys
import os
import json
import numpy as np
import pylab as plt
import itertools as it
from master.libs import plot_lib as plib
from master.libs import read_data_lib as rdl
from master.libs import utils
import matplotlib.gridspec as gridspec
reload(plib)
reload(rdl)
params = {'axes.labelsize': 6,
'font.size': 6,
'legend.fontsize': 7,
'xtick.labelsize':6,
'ytick.labelsize': 6}
plt.rcParams.update(params)
config = json.load(open(sys.argv[1]))
outpath = os.path.join(config['inpath'], 'plots')
if not os.path.exists(outpath):
os.mkdir(outpath)
# variables for results
plt.close('all')
search_res, max_overview, sc, _ = rdl.read_paramsearch_results(config['inpath'],
p_selection=config.get('selection', {}))
if config['plot_param_space']:
for desc in search_res:
fig = plt.figure()
plib.plot_search_matrix(fig, search_res[desc], config['fselection'],
config['method'], config.get('glomeruli', []))
fig.savefig(os.path.join(outpath, config['method'] + '_' + desc + '.' + config['format']))
# descriptor method performance plots
fig = plt.figure(figsize=(3.35, 2))
ptype = config['descriptor_plot_type']
plib.new_descriptor_performance_plot(fig, max_overview, config['fselection'],
config['method'],
config.get('glomeruli', []),
ptype)
fig.subplots_adjust(bottom=0.25)
fig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config['format']), dpi=600)
# ML method comparison plot
markers = ['1', '0']
desc2comp = ['EVA_100', 'all']
fig = plt.figure(figsize=(3.35, 1.8))
ax = fig.add_subplot(111)
desc1_collect, desc2_collect = [], []
for i, desc in enumerate(desc2comp):
desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)
desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)
desc1_collect.extend(max_overview['svr']['linear']['p_selection'][desc_idx1, :])
desc2_collect.extend(max_overview['forest']['forest']['p_selection'][desc_idx2, :])
ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],
max_overview['forest']['forest']['p_selection'][desc_idx2, :],
'o', mfc=markers[i],
label=desc,
markersize=5)
ax.plot([0, 0.8], [0, 0.8], color='0.5')
plt.axis('scaled')
ax.set_xlim([0, .9])
ax.set_ylim([0, .9])
ax.set_xlabel('SVR (q2)')
ax.set_ylabel('RFR (q2)')
utils.simple_axis(ax)
ax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size': 'small'}, bbox_to_anchor=(0.01, 1))
ticks = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
ticklabels = ['0', '', '.2', '', '.4', '', '.6', '', '.8', '']
ax.set_yticks(ticks)
ax.set_yticklabels(ticklabels)
ax.set_xticks(ticks)
ax.set_xticklabels(ticklabels)
fig.subplots_adjust(bottom=0.2)
fig.tight_layout()
fig.savefig(os.path.join(outpath, 'best_method_comparison.' + config['format']), dpi=600)
assert len(desc1_collect) == len(desc2_collect)
svr_better = np.sum([1 for d1, d2 in zip(desc1_collect, desc2_collect) if d1 > d2])
rfr_better = np.sum([1 for d1, d2 in zip(desc1_collect, desc2_collect) if d1 < d2])
ratio = float(svr_better) / (np.sum(rfr_better) + np.sum(svr_better))
print('svr better than rfr in {:.2f} \% of the cases'.format(ratio))
if utils.run_from_ipython():
plt.show()
|
flexible
|
{
"blob_id": "c5bbfa1a86dbbd431566205ff7d7b941bdceff58",
"index": 1233,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nreload(plib)\nreload(rdl)\n<mask token>\nplt.rcParams.update(params)\n<mask token>\nif not os.path.exists(outpath):\n os.mkdir(outpath)\nplt.close('all')\n<mask token>\nif config['plot_param_space']:\n for desc in search_res:\n fig = plt.figure()\n plib.plot_search_matrix(fig, search_res[desc], config['fselection'],\n config['method'], config.get('glomeruli', []))\n fig.savefig(os.path.join(outpath, config['method'] + '_' + desc +\n '.' + config['format']))\n<mask token>\nplib.new_descriptor_performance_plot(fig, max_overview, config['fselection'\n ], config['method'], config.get('glomeruli', []), ptype)\nfig.subplots_adjust(bottom=0.25)\nfig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config[\n 'format']), dpi=600)\n<mask token>\nfor i, desc in enumerate(desc2comp):\n desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)\n desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)\n desc1_collect.extend(max_overview['svr']['linear']['p_selection'][\n desc_idx1, :])\n desc2_collect.extend(max_overview['forest']['forest']['p_selection'][\n desc_idx2, :])\n ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],\n max_overview['forest']['forest']['p_selection'][desc_idx2, :], 'o',\n mfc=markers[i], label=desc, markersize=5)\nax.plot([0, 0.8], [0, 0.8], color='0.5')\nplt.axis('scaled')\nax.set_xlim([0, 0.9])\nax.set_ylim([0, 0.9])\nax.set_xlabel('SVR (q2)')\nax.set_ylabel('RFR (q2)')\nutils.simple_axis(ax)\nax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size':\n 'small'}, bbox_to_anchor=(0.01, 1))\n<mask token>\nax.set_yticks(ticks)\nax.set_yticklabels(ticklabels)\nax.set_xticks(ticks)\nax.set_xticklabels(ticklabels)\nfig.subplots_adjust(bottom=0.2)\nfig.tight_layout()\nfig.savefig(os.path.join(outpath, 'best_method_comparison.' + config[\n 'format']), dpi=600)\nassert len(desc1_collect) == len(desc2_collect)\n<mask token>\nprint('svr better than rfr in {:.2f} \\\\% of the cases'.format(ratio))\nif utils.run_from_ipython():\n plt.show()\n",
"step-3": "<mask token>\nreload(plib)\nreload(rdl)\nparams = {'axes.labelsize': 6, 'font.size': 6, 'legend.fontsize': 7,\n 'xtick.labelsize': 6, 'ytick.labelsize': 6}\nplt.rcParams.update(params)\nconfig = json.load(open(sys.argv[1]))\noutpath = os.path.join(config['inpath'], 'plots')\nif not os.path.exists(outpath):\n os.mkdir(outpath)\nplt.close('all')\nsearch_res, max_overview, sc, _ = rdl.read_paramsearch_results(config[\n 'inpath'], p_selection=config.get('selection', {}))\nif config['plot_param_space']:\n for desc in search_res:\n fig = plt.figure()\n plib.plot_search_matrix(fig, search_res[desc], config['fselection'],\n config['method'], config.get('glomeruli', []))\n fig.savefig(os.path.join(outpath, config['method'] + '_' + desc +\n '.' + config['format']))\nfig = plt.figure(figsize=(3.35, 2))\nptype = config['descriptor_plot_type']\nplib.new_descriptor_performance_plot(fig, max_overview, config['fselection'\n ], config['method'], config.get('glomeruli', []), ptype)\nfig.subplots_adjust(bottom=0.25)\nfig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config[\n 'format']), dpi=600)\nmarkers = ['1', '0']\ndesc2comp = ['EVA_100', 'all']\nfig = plt.figure(figsize=(3.35, 1.8))\nax = fig.add_subplot(111)\ndesc1_collect, desc2_collect = [], []\nfor i, desc in enumerate(desc2comp):\n desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)\n desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)\n desc1_collect.extend(max_overview['svr']['linear']['p_selection'][\n desc_idx1, :])\n desc2_collect.extend(max_overview['forest']['forest']['p_selection'][\n desc_idx2, :])\n ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],\n max_overview['forest']['forest']['p_selection'][desc_idx2, :], 'o',\n mfc=markers[i], label=desc, markersize=5)\nax.plot([0, 0.8], [0, 0.8], color='0.5')\nplt.axis('scaled')\nax.set_xlim([0, 0.9])\nax.set_ylim([0, 0.9])\nax.set_xlabel('SVR (q2)')\nax.set_ylabel('RFR (q2)')\nutils.simple_axis(ax)\nax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size':\n 'small'}, bbox_to_anchor=(0.01, 1))\nticks = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]\nticklabels = ['0', '', '.2', '', '.4', '', '.6', '', '.8', '']\nax.set_yticks(ticks)\nax.set_yticklabels(ticklabels)\nax.set_xticks(ticks)\nax.set_xticklabels(ticklabels)\nfig.subplots_adjust(bottom=0.2)\nfig.tight_layout()\nfig.savefig(os.path.join(outpath, 'best_method_comparison.' + config[\n 'format']), dpi=600)\nassert len(desc1_collect) == len(desc2_collect)\nsvr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if\n d1 > d2])\nrfr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if\n d1 < d2])\nratio = float(svr_better) / (np.sum(rfr_better) + np.sum(svr_better))\nprint('svr better than rfr in {:.2f} \\\\% of the cases'.format(ratio))\nif utils.run_from_ipython():\n plt.show()\n",
"step-4": "<mask token>\nimport sys\nimport os\nimport json\nimport numpy as np\nimport pylab as plt\nimport itertools as it\nfrom master.libs import plot_lib as plib\nfrom master.libs import read_data_lib as rdl\nfrom master.libs import utils\nimport matplotlib.gridspec as gridspec\nreload(plib)\nreload(rdl)\nparams = {'axes.labelsize': 6, 'font.size': 6, 'legend.fontsize': 7,\n 'xtick.labelsize': 6, 'ytick.labelsize': 6}\nplt.rcParams.update(params)\nconfig = json.load(open(sys.argv[1]))\noutpath = os.path.join(config['inpath'], 'plots')\nif not os.path.exists(outpath):\n os.mkdir(outpath)\nplt.close('all')\nsearch_res, max_overview, sc, _ = rdl.read_paramsearch_results(config[\n 'inpath'], p_selection=config.get('selection', {}))\nif config['plot_param_space']:\n for desc in search_res:\n fig = plt.figure()\n plib.plot_search_matrix(fig, search_res[desc], config['fselection'],\n config['method'], config.get('glomeruli', []))\n fig.savefig(os.path.join(outpath, config['method'] + '_' + desc +\n '.' + config['format']))\nfig = plt.figure(figsize=(3.35, 2))\nptype = config['descriptor_plot_type']\nplib.new_descriptor_performance_plot(fig, max_overview, config['fselection'\n ], config['method'], config.get('glomeruli', []), ptype)\nfig.subplots_adjust(bottom=0.25)\nfig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config[\n 'format']), dpi=600)\nmarkers = ['1', '0']\ndesc2comp = ['EVA_100', 'all']\nfig = plt.figure(figsize=(3.35, 1.8))\nax = fig.add_subplot(111)\ndesc1_collect, desc2_collect = [], []\nfor i, desc in enumerate(desc2comp):\n desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)\n desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)\n desc1_collect.extend(max_overview['svr']['linear']['p_selection'][\n desc_idx1, :])\n desc2_collect.extend(max_overview['forest']['forest']['p_selection'][\n desc_idx2, :])\n ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],\n max_overview['forest']['forest']['p_selection'][desc_idx2, :], 'o',\n mfc=markers[i], label=desc, markersize=5)\nax.plot([0, 0.8], [0, 0.8], color='0.5')\nplt.axis('scaled')\nax.set_xlim([0, 0.9])\nax.set_ylim([0, 0.9])\nax.set_xlabel('SVR (q2)')\nax.set_ylabel('RFR (q2)')\nutils.simple_axis(ax)\nax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size':\n 'small'}, bbox_to_anchor=(0.01, 1))\nticks = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]\nticklabels = ['0', '', '.2', '', '.4', '', '.6', '', '.8', '']\nax.set_yticks(ticks)\nax.set_yticklabels(ticklabels)\nax.set_xticks(ticks)\nax.set_xticklabels(ticklabels)\nfig.subplots_adjust(bottom=0.2)\nfig.tight_layout()\nfig.savefig(os.path.join(outpath, 'best_method_comparison.' + config[\n 'format']), dpi=600)\nassert len(desc1_collect) == len(desc2_collect)\nsvr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if\n d1 > d2])\nrfr_better = np.sum([(1) for d1, d2 in zip(desc1_collect, desc2_collect) if\n d1 < d2])\nratio = float(svr_better) / (np.sum(rfr_better) + np.sum(svr_better))\nprint('svr better than rfr in {:.2f} \\\\% of the cases'.format(ratio))\nif utils.run_from_ipython():\n plt.show()\n",
"step-5": "#!/usr/bin/env python\n# encoding: utf-8\n\"\"\"\n plot: regularization on x axis, number of k_best features on y\n\nCreated by on 2012-01-27.\nCopyright (c) 2012. All rights reserved.\n\"\"\"\nimport sys\nimport os\nimport json\nimport numpy as np\nimport pylab as plt\nimport itertools as it\nfrom master.libs import plot_lib as plib\nfrom master.libs import read_data_lib as rdl\nfrom master.libs import utils\nimport matplotlib.gridspec as gridspec\nreload(plib)\nreload(rdl)\n\n\nparams = {'axes.labelsize': 6,\n 'font.size': 6,\n 'legend.fontsize': 7,\n 'xtick.labelsize':6,\n 'ytick.labelsize': 6}\nplt.rcParams.update(params)\n\nconfig = json.load(open(sys.argv[1]))\noutpath = os.path.join(config['inpath'], 'plots')\nif not os.path.exists(outpath):\n os.mkdir(outpath)\n\n# variables for results\nplt.close('all')\nsearch_res, max_overview, sc, _ = rdl.read_paramsearch_results(config['inpath'],\n p_selection=config.get('selection', {}))\n\nif config['plot_param_space']:\n for desc in search_res:\n fig = plt.figure()\n plib.plot_search_matrix(fig, search_res[desc], config['fselection'],\n config['method'], config.get('glomeruli', []))\n fig.savefig(os.path.join(outpath, config['method'] + '_' + desc + '.' + config['format']))\n\n# descriptor method performance plots\nfig = plt.figure(figsize=(3.35, 2))\nptype = config['descriptor_plot_type']\nplib.new_descriptor_performance_plot(fig, max_overview, config['fselection'],\n config['method'],\n config.get('glomeruli', []),\n ptype)\nfig.subplots_adjust(bottom=0.25)\nfig.savefig(os.path.join(outpath, ptype + '_desc_comparison.' + config['format']), dpi=600)\n\n\n# ML method comparison plot\nmarkers = ['1', '0']\ndesc2comp = ['EVA_100', 'all']\nfig = plt.figure(figsize=(3.35, 1.8))\nax = fig.add_subplot(111)\ndesc1_collect, desc2_collect = [], []\nfor i, desc in enumerate(desc2comp):\n desc_idx1 = max_overview['svr']['linear']['desc_names'].index(desc)\n desc_idx2 = max_overview['forest']['forest']['desc_names'].index(desc)\n desc1_collect.extend(max_overview['svr']['linear']['p_selection'][desc_idx1, :])\n desc2_collect.extend(max_overview['forest']['forest']['p_selection'][desc_idx2, :])\n ax.plot(max_overview['svr']['linear']['p_selection'][desc_idx1, :],\n max_overview['forest']['forest']['p_selection'][desc_idx2, :],\n 'o', mfc=markers[i],\n label=desc,\n markersize=5)\nax.plot([0, 0.8], [0, 0.8], color='0.5')\nplt.axis('scaled')\nax.set_xlim([0, .9])\nax.set_ylim([0, .9])\nax.set_xlabel('SVR (q2)')\nax.set_ylabel('RFR (q2)')\nutils.simple_axis(ax)\nax.legend(loc='upper left', numpoints=1, frameon=False, prop={'size': 'small'}, bbox_to_anchor=(0.01, 1))\nticks = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]\nticklabels = ['0', '', '.2', '', '.4', '', '.6', '', '.8', '']\nax.set_yticks(ticks)\nax.set_yticklabels(ticklabels)\nax.set_xticks(ticks)\nax.set_xticklabels(ticklabels)\nfig.subplots_adjust(bottom=0.2)\nfig.tight_layout()\nfig.savefig(os.path.join(outpath, 'best_method_comparison.' + config['format']), dpi=600)\n\nassert len(desc1_collect) == len(desc2_collect)\nsvr_better = np.sum([1 for d1, d2 in zip(desc1_collect, desc2_collect) if d1 > d2])\nrfr_better = np.sum([1 for d1, d2 in zip(desc1_collect, desc2_collect) if d1 < d2])\nratio = float(svr_better) / (np.sum(rfr_better) + np.sum(svr_better))\nprint('svr better than rfr in {:.2f} \\% of the cases'.format(ratio))\n\nif utils.run_from_ipython():\n plt.show()\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import web
import datetime
# run with sudo to run on port 80 and use GPIO
urls = ('/', 'index', '/survey', 'survey')
render = web.template.render('templates/')
class survey:
def GET(self):
return render.survey()
class index:
def GET(self):
i = web.input(enter=None)
#if i.enter=='allow':
# do something
#elif i.enter=='deny':
# do something else
date = datetime.datetime.now().ctime()
hour = datetime.datetime.now().hour
return render.index(i.enter, date, hour)
if __name__ == "__main__":
app = web.application(urls, globals())
app.run()
|
normal
|
{
"blob_id": "07a0ba3ded8a2d4a980cfb8e3dbd6fd491ea24b0",
"index": 1842,
"step-1": "<mask token>\n\n\nclass survey:\n <mask token>\n\n\nclass index:\n\n def GET(self):\n i = web.input(enter=None)\n date = datetime.datetime.now().ctime()\n hour = datetime.datetime.now().hour\n return render.index(i.enter, date, hour)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass survey:\n\n def GET(self):\n return render.survey()\n\n\nclass index:\n\n def GET(self):\n i = web.input(enter=None)\n date = datetime.datetime.now().ctime()\n hour = datetime.datetime.now().hour\n return render.index(i.enter, date, hour)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass survey:\n\n def GET(self):\n return render.survey()\n\n\nclass index:\n\n def GET(self):\n i = web.input(enter=None)\n date = datetime.datetime.now().ctime()\n hour = datetime.datetime.now().hour\n return render.index(i.enter, date, hour)\n\n\nif __name__ == '__main__':\n app = web.application(urls, globals())\n app.run()\n",
"step-4": "import web\nimport datetime\nurls = '/', 'index', '/survey', 'survey'\nrender = web.template.render('templates/')\n\n\nclass survey:\n\n def GET(self):\n return render.survey()\n\n\nclass index:\n\n def GET(self):\n i = web.input(enter=None)\n date = datetime.datetime.now().ctime()\n hour = datetime.datetime.now().hour\n return render.index(i.enter, date, hour)\n\n\nif __name__ == '__main__':\n app = web.application(urls, globals())\n app.run()\n",
"step-5": "import web\nimport datetime\n\n# run with sudo to run on port 80 and use GPIO\n\nurls = ('/', 'index', '/survey', 'survey')\nrender = web.template.render('templates/')\n\nclass survey:\n def GET(self):\n return render.survey()\n\nclass index:\n def GET(self):\n i = web.input(enter=None)\n #if i.enter=='allow':\n # do something\n #elif i.enter=='deny':\n # do something else\n\n date = datetime.datetime.now().ctime()\n hour = datetime.datetime.now().hour\n \n return render.index(i.enter, date, hour)\n\nif __name__ == \"__main__\": \n app = web.application(urls, globals())\n app.run()\n",
"step-ids": [
3,
4,
5,
7,
8
]
}
|
[
3,
4,
5,
7,
8
] |
/Applications/anaconda2/lib/python2.7/warnings.py
|
normal
|
{
"blob_id": "cd2062055e30fc37a5f00f4bce6ffd9ea5eda860",
"index": 4134,
"step-1": "/Applications/anaconda2/lib/python2.7/warnings.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def test_preprocessor():
"""
"""
nb = nbformat.v4.new_notebook()
nb.cells.append(nbformat.v4.new_code_cell(dedent(
""" a = True
b = False
f = lambda x: not x
g = f(a) + f(b)
if f(a) and f(b):
print("hi")
if f(a) or f(b):
print("hi")
if a or b:
print("bye")
l = [f(i) for i in [a, b]]
f = lambda x: [not i for i in l]
l = [a, b]
if all(f(l)):
print("ok")
else:
l = any(f(l))
"""
)))
ivp = IntermediateVariablePreprocessor()
random.seed(42)
nb = ivp.preprocess(nb)
print(nb.cells[0].source)
assert len(nb.cells) == 1
assert nb.cells[0].source.strip() == dedent(
""" a = True
b = False
f = (lambda x: (not x))
var_HBRPOI = f(a)
var_G8F1CB = f(b)
g = (var_HBRPOI + var_G8F1CB)
var_FNO6B9 = f(a)
if (var_FNO6B9):
var_M80O2R = f(b)
if (var_FNO6B9 and var_M80O2R):
var_AK1VRJ = print('hi')
var_AK1VRJ
var_NVGFYG = f(a)
if (not (var_NVGFYG)):
var_WWQC38 = f(b)
if (var_NVGFYG or var_WWQC38):
var_HYF9SX = print('hi')
var_HYF9SX
if (a or b):
var_MECOSF = print('bye')
var_MECOSF
l = [f(i) for i in [a, b]]
f = (lambda x: [(not i) for i in l])
l = [a, b]
var_KXWNRE = f(l)
var_K8PK3Y = all(var_KXWNRE)
if var_K8PK3Y:
var_R9OUDO = print('ok')
var_R9OUDO
else:
var_CUZREN = f(l)
l = any(var_CUZREN)
"""
).strip()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
import random
import nbformat
from textwrap import dedent
from pybryt.preprocessors import IntermediateVariablePreprocessor
def test_preprocessor():
"""
"""
nb = nbformat.v4.new_notebook()
nb.cells.append(nbformat.v4.new_code_cell(dedent(
""" a = True
b = False
f = lambda x: not x
g = f(a) + f(b)
if f(a) and f(b):
print("hi")
if f(a) or f(b):
print("hi")
if a or b:
print("bye")
l = [f(i) for i in [a, b]]
f = lambda x: [not i for i in l]
l = [a, b]
if all(f(l)):
print("ok")
else:
l = any(f(l))
"""
)))
ivp = IntermediateVariablePreprocessor()
random.seed(42)
nb = ivp.preprocess(nb)
print(nb.cells[0].source)
assert len(nb.cells) == 1
assert nb.cells[0].source.strip() == dedent(
""" a = True
b = False
f = (lambda x: (not x))
var_HBRPOI = f(a)
var_G8F1CB = f(b)
g = (var_HBRPOI + var_G8F1CB)
var_FNO6B9 = f(a)
if (var_FNO6B9):
var_M80O2R = f(b)
if (var_FNO6B9 and var_M80O2R):
var_AK1VRJ = print('hi')
var_AK1VRJ
var_NVGFYG = f(a)
if (not (var_NVGFYG)):
var_WWQC38 = f(b)
if (var_NVGFYG or var_WWQC38):
var_HYF9SX = print('hi')
var_HYF9SX
if (a or b):
var_MECOSF = print('bye')
var_MECOSF
l = [f(i) for i in [a, b]]
f = (lambda x: [(not i) for i in l])
l = [a, b]
var_KXWNRE = f(l)
var_K8PK3Y = all(var_KXWNRE)
if var_K8PK3Y:
var_R9OUDO = print('ok')
var_R9OUDO
else:
var_CUZREN = f(l)
l = any(var_CUZREN)
"""
).strip()
<|reserved_special_token_1|>
""""""
import random
import nbformat
from textwrap import dedent
from pybryt.preprocessors import IntermediateVariablePreprocessor
def test_preprocessor():
"""
"""
nb = nbformat.v4.new_notebook()
nb.cells.append(nbformat.v4.new_code_cell(dedent("""\
a = True
b = False
f = lambda x: not x
g = f(a) + f(b)
if f(a) and f(b):
print("hi")
if f(a) or f(b):
print("hi")
if a or b:
print("bye")
l = [f(i) for i in [a, b]]
f = lambda x: [not i for i in l]
l = [a, b]
if all(f(l)):
print("ok")
else:
l = any(f(l))
""")))
ivp = IntermediateVariablePreprocessor()
random.seed(42)
nb = ivp.preprocess(nb)
print(nb.cells[0].source)
assert len(nb.cells) == 1
assert nb.cells[0].source.strip() == dedent("""\
a = True
b = False
f = (lambda x: (not x))
var_HBRPOI = f(a)
var_G8F1CB = f(b)
g = (var_HBRPOI + var_G8F1CB)
var_FNO6B9 = f(a)
if (var_FNO6B9):
var_M80O2R = f(b)
if (var_FNO6B9 and var_M80O2R):
var_AK1VRJ = print('hi')
var_AK1VRJ
var_NVGFYG = f(a)
if (not (var_NVGFYG)):
var_WWQC38 = f(b)
if (var_NVGFYG or var_WWQC38):
var_HYF9SX = print('hi')
var_HYF9SX
if (a or b):
var_MECOSF = print('bye')
var_MECOSF
l = [f(i) for i in [a, b]]
f = (lambda x: [(not i) for i in l])
l = [a, b]
var_KXWNRE = f(l)
var_K8PK3Y = all(var_KXWNRE)
if var_K8PK3Y:
var_R9OUDO = print('ok')
var_R9OUDO
else:
var_CUZREN = f(l)
l = any(var_CUZREN)
""").strip()
|
flexible
|
{
"blob_id": "d9f08e770dacaa86a03d553afd78fdcd725efb62",
"index": 5204,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_preprocessor():\n \"\"\"\n \"\"\"\n nb = nbformat.v4.new_notebook()\n nb.cells.append(nbformat.v4.new_code_cell(dedent(\n \"\"\" a = True\n b = False\n f = lambda x: not x\n\n g = f(a) + f(b)\n\n if f(a) and f(b):\n print(\"hi\")\n\n if f(a) or f(b):\n print(\"hi\")\n \n if a or b:\n print(\"bye\")\n\n l = [f(i) for i in [a, b]]\n\n f = lambda x: [not i for i in l]\n l = [a, b]\n if all(f(l)):\n print(\"ok\")\n else:\n l = any(f(l))\n \"\"\"\n )))\n ivp = IntermediateVariablePreprocessor()\n random.seed(42)\n nb = ivp.preprocess(nb)\n print(nb.cells[0].source)\n assert len(nb.cells) == 1\n assert nb.cells[0].source.strip() == dedent(\n \"\"\" a = True\n b = False\n f = (lambda x: (not x))\n var_HBRPOI = f(a)\n var_G8F1CB = f(b)\n g = (var_HBRPOI + var_G8F1CB)\n var_FNO6B9 = f(a)\n if (var_FNO6B9):\n var_M80O2R = f(b)\n if (var_FNO6B9 and var_M80O2R):\n var_AK1VRJ = print('hi')\n var_AK1VRJ\n var_NVGFYG = f(a)\n if (not (var_NVGFYG)):\n var_WWQC38 = f(b)\n if (var_NVGFYG or var_WWQC38):\n var_HYF9SX = print('hi')\n var_HYF9SX\n if (a or b):\n var_MECOSF = print('bye')\n var_MECOSF\n l = [f(i) for i in [a, b]]\n f = (lambda x: [(not i) for i in l])\n l = [a, b]\n var_KXWNRE = f(l)\n var_K8PK3Y = all(var_KXWNRE)\n if var_K8PK3Y:\n var_R9OUDO = print('ok')\n var_R9OUDO\n else:\n var_CUZREN = f(l)\n l = any(var_CUZREN)\n \"\"\"\n ).strip()\n",
"step-3": "<mask token>\nimport random\nimport nbformat\nfrom textwrap import dedent\nfrom pybryt.preprocessors import IntermediateVariablePreprocessor\n\n\ndef test_preprocessor():\n \"\"\"\n \"\"\"\n nb = nbformat.v4.new_notebook()\n nb.cells.append(nbformat.v4.new_code_cell(dedent(\n \"\"\" a = True\n b = False\n f = lambda x: not x\n\n g = f(a) + f(b)\n\n if f(a) and f(b):\n print(\"hi\")\n\n if f(a) or f(b):\n print(\"hi\")\n \n if a or b:\n print(\"bye\")\n\n l = [f(i) for i in [a, b]]\n\n f = lambda x: [not i for i in l]\n l = [a, b]\n if all(f(l)):\n print(\"ok\")\n else:\n l = any(f(l))\n \"\"\"\n )))\n ivp = IntermediateVariablePreprocessor()\n random.seed(42)\n nb = ivp.preprocess(nb)\n print(nb.cells[0].source)\n assert len(nb.cells) == 1\n assert nb.cells[0].source.strip() == dedent(\n \"\"\" a = True\n b = False\n f = (lambda x: (not x))\n var_HBRPOI = f(a)\n var_G8F1CB = f(b)\n g = (var_HBRPOI + var_G8F1CB)\n var_FNO6B9 = f(a)\n if (var_FNO6B9):\n var_M80O2R = f(b)\n if (var_FNO6B9 and var_M80O2R):\n var_AK1VRJ = print('hi')\n var_AK1VRJ\n var_NVGFYG = f(a)\n if (not (var_NVGFYG)):\n var_WWQC38 = f(b)\n if (var_NVGFYG or var_WWQC38):\n var_HYF9SX = print('hi')\n var_HYF9SX\n if (a or b):\n var_MECOSF = print('bye')\n var_MECOSF\n l = [f(i) for i in [a, b]]\n f = (lambda x: [(not i) for i in l])\n l = [a, b]\n var_KXWNRE = f(l)\n var_K8PK3Y = all(var_KXWNRE)\n if var_K8PK3Y:\n var_R9OUDO = print('ok')\n var_R9OUDO\n else:\n var_CUZREN = f(l)\n l = any(var_CUZREN)\n \"\"\"\n ).strip()\n",
"step-4": "\"\"\"\"\"\"\n\nimport random\nimport nbformat\n\nfrom textwrap import dedent\n\nfrom pybryt.preprocessors import IntermediateVariablePreprocessor\n\n\ndef test_preprocessor():\n \"\"\"\n \"\"\"\n nb = nbformat.v4.new_notebook()\n nb.cells.append(nbformat.v4.new_code_cell(dedent(\"\"\"\\\n a = True\n b = False\n f = lambda x: not x\n\n g = f(a) + f(b)\n\n if f(a) and f(b):\n print(\"hi\")\n\n if f(a) or f(b):\n print(\"hi\")\n \n if a or b:\n print(\"bye\")\n\n l = [f(i) for i in [a, b]]\n\n f = lambda x: [not i for i in l]\n l = [a, b]\n if all(f(l)):\n print(\"ok\")\n else:\n l = any(f(l))\n \"\"\")))\n\n ivp = IntermediateVariablePreprocessor()\n\n random.seed(42)\n nb = ivp.preprocess(nb)\n print(nb.cells[0].source)\n assert len(nb.cells) == 1\n assert nb.cells[0].source.strip() == dedent(\"\"\"\\\n a = True\n b = False\n f = (lambda x: (not x))\n var_HBRPOI = f(a)\n var_G8F1CB = f(b)\n g = (var_HBRPOI + var_G8F1CB)\n var_FNO6B9 = f(a)\n if (var_FNO6B9):\n var_M80O2R = f(b)\n if (var_FNO6B9 and var_M80O2R):\n var_AK1VRJ = print('hi')\n var_AK1VRJ\n var_NVGFYG = f(a)\n if (not (var_NVGFYG)):\n var_WWQC38 = f(b)\n if (var_NVGFYG or var_WWQC38):\n var_HYF9SX = print('hi')\n var_HYF9SX\n if (a or b):\n var_MECOSF = print('bye')\n var_MECOSF\n l = [f(i) for i in [a, b]]\n f = (lambda x: [(not i) for i in l])\n l = [a, b]\n var_KXWNRE = f(l)\n var_K8PK3Y = all(var_KXWNRE)\n if var_K8PK3Y:\n var_R9OUDO = print('ok')\n var_R9OUDO\n else:\n var_CUZREN = f(l)\n l = any(var_CUZREN)\n \"\"\").strip()\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import stats
import datetime
#takes in a sorted data frame holding the actuals, the predicted values (sorted descending) and the percentile of each obsevation
#and returns a new dataframe with all of the appropriate calculations
def lift_calculations(df):
#adding a sample counter variable
df['sample_num'] = range(len(df))
#adding cumulative sum of actual target
df['actual_sum'] = df['actual'].cumsum()
#column tracking the percentage of samples of total covered
df['per_sample_covered'] = ((df['sample_num']+1)*100)/len(df)
#percentage of all positives captured
df['per_pos_captured'] = (df['actual_sum']/(len(df[df['actual']==1])))*100
#proportion of positives captured from total
df['prop_pos_captured_from_all'] = df['per_pos_captured']/df['per_sample_covered']
return df
#creates a plot of cumulative positive gain
#takes in a dataframe with all of the relevant statistics already calculated
def gain_plot(df,figsize=None,x_range=None,y_range=None,legend='on'):
#Plot of the cumulative capture of positives as we go across the deciles
if figsize:
fig = plt.figure(figsize=figsize)
plt.plot(pd.Series([0]).append(df['per_sample_covered']),
pd.Series([0]).append(df['per_pos_captured'])) #pre-pending zeos to the front of the series for polotting purposes
plt.plot([0,100],[0,100])
plt.title('Cumulative True Positives Captured vs Random (Gain Curve)',fontsize=20)
plt.xlabel('% of Sample Covered',fontsize=15)
plt.ylabel('% of True Positives Captured',fontsize=15)
if x_range:
plt.xlim(x_range[0],x_range[1])
if y_range:
plt.ylim(y_range[0],y_range[1])
if legend=='on':
plt.legend(['Predictive Targeting','Random Targeting'],fontsize=12,loc=2)
def lift_plot(df,figsize=None,x_range=None,y_range=None,legend='on'):
#Lift Curve Plot(at whatever percent of customers cutoff, the model is targeting X times better than random)
#i.e. at the XX percentile, the response rate is Y times as good as it would be if targeting at random at the XX percentile
if figsize:
fig = plt.figure(figsize=figsize)
plt.plot(df['per_sample_covered'],df['prop_pos_captured_from_all'])
plt.plot([df['per_sample_covered'].min(),100],[1,1])
plt.title('Lift Curve',fontsize=20)
plt.xlabel('% of Customers',fontsize=15)
plt.ylabel('Lift',fontsize=15)
if x_range:
plt.xlim(x_range[0],x_range[1])
if y_range:
plt.ylim(y_range[0],y_range[1])
if legend=='on':
plt.legend(['Predictive Targeting','Random Targeting'],fontsize=12)
#a function which takes in an array of predicted values and returns the percentile associated with each one
def percentile_gen(arr_y_pred):
return np.array(pd.qcut(pd.Series(arr_y_pred).rank(method='first'),100,labels=range(1,101))) #method = first is used in the case when there are a lot of 0s and overlapping of labels
#a function which takes in an array of actual test values and the model predicted values and stacks them together
#then sorts them and puts them into a dataframe
def data_prep(arr_y_test,arr_y_pred):
#assigning each observation into a percentile
percentiles = percentile_gen(arr_y_pred)
#print(percentiles.shape)
#joining all the pieces together
data = np.hstack((arr_y_test.reshape((len(arr_y_test),1)),
arr_y_pred.reshape((len(arr_y_pred),1)),
percentiles.reshape((len(percentiles),1))))
#converting to a data frame
data_df = pd.DataFrame(data)
data_df.columns = ['actual','prob','percentile']
data_df.actual = data_df.actual.astype(int)
data_df.prob = data_df.prob.astype('float64')
#sorting by the probability
data_df = data_df.sort_values(by='prob',ascending=False)
#calculating lift metrics
data_df = lift_calculations(data_df)
return data_df
#a function which plots the lift curve for the model
def lift_curve(arr_y_test,arr_y_pred,figsize=None,x_range=None,y_range=None,legend='on'):
data_df = data_prep(arr_y_test,arr_y_pred)
#print(data_df.groupby('percentile').size())
#lift curve plot
lift_plot(data_df,figsize=figsize,x_range=x_range,y_range=y_range,legend=legend)
plt.show()
#a function which plots the gain curve for the model
def gain_curve(arr_y_test,arr_y_pred,figsize=None,x_range=None,y_range=None,legend='on'):
data_df = data_prep(arr_y_test,arr_y_pred)
#gain curve plot
gain_plot(data_df,figsize=figsize,x_range=x_range,y_range=y_range,legend=legend)
plt.show()
#a function which returns two numpy arrays:
#the first one is the percent of samples covered (X-value)
#the second being the lift values for the correponding the sample (Y-value)
def lift_values_generator(arr_y_test,arr_y_pred):
data_df = data_prep(arr_y_test,arr_y_pred)
return data_df.per_sample_covered, data_df.prop_pos_captured_from_all
#a function which plots multiple lift curves all on the same graph
#the first parameter is the x axis which represents %of the sample covered
#the second parameter is a list of lists, where each one presents the lift
#curve for a particular model, the last parameter holds the labels for the lift
#curves in the corresponding order
def plot_lift_curves(percent_sample_covered,list_of_lift_metrics,labels,figsize=None,x_range=None,y_range=None,legend='on'):
if figsize:
plt.figure(figsize=figsize)
#plotting the various model lift curves
for i,lift_scores in enumerate(list_of_lift_metrics):
plt.plot(percent_sample_covered,lift_scores)
#base line plot for random guessing
plt.plot([percent_sample_covered.min(),100],[1,1])
#formats and labels
plt.title('Lift Curves Comparison',fontsize=20)
plt.xlabel('% of Customers',fontsize=15)
plt.ylabel('Lift',fontsize=15)
if x_range:
plt.xlim(x_range[0],x_range[1])
if y_range:
plt.ylim(y_range[0],y_range[1])
model_labels = labels + ['Random Guessing']
if legend == 'on':
plt.legend(model_labels,fontsize=12,loc='best')
|
normal
|
{
"blob_id": "8e71ea23d04199e8fb54099c404c5a4e9af6c4b1",
"index": 9336,
"step-1": "<mask token>\n\n\ndef lift_calculations(df):\n df['sample_num'] = range(len(df))\n df['actual_sum'] = df['actual'].cumsum()\n df['per_sample_covered'] = (df['sample_num'] + 1) * 100 / len(df)\n df['per_pos_captured'] = df['actual_sum'] / len(df[df['actual'] == 1]\n ) * 100\n df['prop_pos_captured_from_all'] = df['per_pos_captured'] / df[\n 'per_sample_covered']\n return df\n\n\ndef gain_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(pd.Series([0]).append(df['per_sample_covered']), pd.Series([0]\n ).append(df['per_pos_captured']))\n plt.plot([0, 100], [0, 100])\n plt.title('Cumulative True Positives Captured vs Random (Gain Curve)',\n fontsize=20)\n plt.xlabel('% of Sample Covered', fontsize=15)\n plt.ylabel('% of True Positives Captured', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=\n 12, loc=2)\n\n\ndef lift_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(df['per_sample_covered'], df['prop_pos_captured_from_all'])\n plt.plot([df['per_sample_covered'].min(), 100], [1, 1])\n plt.title('Lift Curve', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=12)\n\n\n<mask token>\n\n\ndef data_prep(arr_y_test, arr_y_pred):\n percentiles = percentile_gen(arr_y_pred)\n data = np.hstack((arr_y_test.reshape((len(arr_y_test), 1)), arr_y_pred.\n reshape((len(arr_y_pred), 1)), percentiles.reshape((len(percentiles\n ), 1))))\n data_df = pd.DataFrame(data)\n data_df.columns = ['actual', 'prob', 'percentile']\n data_df.actual = data_df.actual.astype(int)\n data_df.prob = data_df.prob.astype('float64')\n data_df = data_df.sort_values(by='prob', ascending=False)\n data_df = lift_calculations(data_df)\n return data_df\n\n\ndef lift_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n lift_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef lift_calculations(df):\n df['sample_num'] = range(len(df))\n df['actual_sum'] = df['actual'].cumsum()\n df['per_sample_covered'] = (df['sample_num'] + 1) * 100 / len(df)\n df['per_pos_captured'] = df['actual_sum'] / len(df[df['actual'] == 1]\n ) * 100\n df['prop_pos_captured_from_all'] = df['per_pos_captured'] / df[\n 'per_sample_covered']\n return df\n\n\ndef gain_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(pd.Series([0]).append(df['per_sample_covered']), pd.Series([0]\n ).append(df['per_pos_captured']))\n plt.plot([0, 100], [0, 100])\n plt.title('Cumulative True Positives Captured vs Random (Gain Curve)',\n fontsize=20)\n plt.xlabel('% of Sample Covered', fontsize=15)\n plt.ylabel('% of True Positives Captured', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=\n 12, loc=2)\n\n\ndef lift_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(df['per_sample_covered'], df['prop_pos_captured_from_all'])\n plt.plot([df['per_sample_covered'].min(), 100], [1, 1])\n plt.title('Lift Curve', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=12)\n\n\n<mask token>\n\n\ndef data_prep(arr_y_test, arr_y_pred):\n percentiles = percentile_gen(arr_y_pred)\n data = np.hstack((arr_y_test.reshape((len(arr_y_test), 1)), arr_y_pred.\n reshape((len(arr_y_pred), 1)), percentiles.reshape((len(percentiles\n ), 1))))\n data_df = pd.DataFrame(data)\n data_df.columns = ['actual', 'prob', 'percentile']\n data_df.actual = data_df.actual.astype(int)\n data_df.prob = data_df.prob.astype('float64')\n data_df = data_df.sort_values(by='prob', ascending=False)\n data_df = lift_calculations(data_df)\n return data_df\n\n\ndef lift_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n lift_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\ndef gain_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n gain_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\n<mask token>\n\n\ndef plot_lift_curves(percent_sample_covered, list_of_lift_metrics, labels,\n figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n plt.figure(figsize=figsize)\n for i, lift_scores in enumerate(list_of_lift_metrics):\n plt.plot(percent_sample_covered, lift_scores)\n plt.plot([percent_sample_covered.min(), 100], [1, 1])\n plt.title('Lift Curves Comparison', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n model_labels = labels + ['Random Guessing']\n if legend == 'on':\n plt.legend(model_labels, fontsize=12, loc='best')\n",
"step-3": "<mask token>\n\n\ndef lift_calculations(df):\n df['sample_num'] = range(len(df))\n df['actual_sum'] = df['actual'].cumsum()\n df['per_sample_covered'] = (df['sample_num'] + 1) * 100 / len(df)\n df['per_pos_captured'] = df['actual_sum'] / len(df[df['actual'] == 1]\n ) * 100\n df['prop_pos_captured_from_all'] = df['per_pos_captured'] / df[\n 'per_sample_covered']\n return df\n\n\ndef gain_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(pd.Series([0]).append(df['per_sample_covered']), pd.Series([0]\n ).append(df['per_pos_captured']))\n plt.plot([0, 100], [0, 100])\n plt.title('Cumulative True Positives Captured vs Random (Gain Curve)',\n fontsize=20)\n plt.xlabel('% of Sample Covered', fontsize=15)\n plt.ylabel('% of True Positives Captured', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=\n 12, loc=2)\n\n\ndef lift_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(df['per_sample_covered'], df['prop_pos_captured_from_all'])\n plt.plot([df['per_sample_covered'].min(), 100], [1, 1])\n plt.title('Lift Curve', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=12)\n\n\ndef percentile_gen(arr_y_pred):\n return np.array(pd.qcut(pd.Series(arr_y_pred).rank(method='first'), 100,\n labels=range(1, 101)))\n\n\ndef data_prep(arr_y_test, arr_y_pred):\n percentiles = percentile_gen(arr_y_pred)\n data = np.hstack((arr_y_test.reshape((len(arr_y_test), 1)), arr_y_pred.\n reshape((len(arr_y_pred), 1)), percentiles.reshape((len(percentiles\n ), 1))))\n data_df = pd.DataFrame(data)\n data_df.columns = ['actual', 'prob', 'percentile']\n data_df.actual = data_df.actual.astype(int)\n data_df.prob = data_df.prob.astype('float64')\n data_df = data_df.sort_values(by='prob', ascending=False)\n data_df = lift_calculations(data_df)\n return data_df\n\n\ndef lift_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n lift_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\ndef gain_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n gain_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\n<mask token>\n\n\ndef plot_lift_curves(percent_sample_covered, list_of_lift_metrics, labels,\n figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n plt.figure(figsize=figsize)\n for i, lift_scores in enumerate(list_of_lift_metrics):\n plt.plot(percent_sample_covered, lift_scores)\n plt.plot([percent_sample_covered.min(), 100], [1, 1])\n plt.title('Lift Curves Comparison', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n model_labels = labels + ['Random Guessing']\n if legend == 'on':\n plt.legend(model_labels, fontsize=12, loc='best')\n",
"step-4": "import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom scipy import stats\nimport datetime\n\n\ndef lift_calculations(df):\n df['sample_num'] = range(len(df))\n df['actual_sum'] = df['actual'].cumsum()\n df['per_sample_covered'] = (df['sample_num'] + 1) * 100 / len(df)\n df['per_pos_captured'] = df['actual_sum'] / len(df[df['actual'] == 1]\n ) * 100\n df['prop_pos_captured_from_all'] = df['per_pos_captured'] / df[\n 'per_sample_covered']\n return df\n\n\ndef gain_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(pd.Series([0]).append(df['per_sample_covered']), pd.Series([0]\n ).append(df['per_pos_captured']))\n plt.plot([0, 100], [0, 100])\n plt.title('Cumulative True Positives Captured vs Random (Gain Curve)',\n fontsize=20)\n plt.xlabel('% of Sample Covered', fontsize=15)\n plt.ylabel('% of True Positives Captured', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=\n 12, loc=2)\n\n\ndef lift_plot(df, figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n fig = plt.figure(figsize=figsize)\n plt.plot(df['per_sample_covered'], df['prop_pos_captured_from_all'])\n plt.plot([df['per_sample_covered'].min(), 100], [1, 1])\n plt.title('Lift Curve', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n if legend == 'on':\n plt.legend(['Predictive Targeting', 'Random Targeting'], fontsize=12)\n\n\ndef percentile_gen(arr_y_pred):\n return np.array(pd.qcut(pd.Series(arr_y_pred).rank(method='first'), 100,\n labels=range(1, 101)))\n\n\ndef data_prep(arr_y_test, arr_y_pred):\n percentiles = percentile_gen(arr_y_pred)\n data = np.hstack((arr_y_test.reshape((len(arr_y_test), 1)), arr_y_pred.\n reshape((len(arr_y_pred), 1)), percentiles.reshape((len(percentiles\n ), 1))))\n data_df = pd.DataFrame(data)\n data_df.columns = ['actual', 'prob', 'percentile']\n data_df.actual = data_df.actual.astype(int)\n data_df.prob = data_df.prob.astype('float64')\n data_df = data_df.sort_values(by='prob', ascending=False)\n data_df = lift_calculations(data_df)\n return data_df\n\n\ndef lift_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n lift_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\ndef gain_curve(arr_y_test, arr_y_pred, figsize=None, x_range=None, y_range=\n None, legend='on'):\n data_df = data_prep(arr_y_test, arr_y_pred)\n gain_plot(data_df, figsize=figsize, x_range=x_range, y_range=y_range,\n legend=legend)\n plt.show()\n\n\ndef lift_values_generator(arr_y_test, arr_y_pred):\n data_df = data_prep(arr_y_test, arr_y_pred)\n return data_df.per_sample_covered, data_df.prop_pos_captured_from_all\n\n\ndef plot_lift_curves(percent_sample_covered, list_of_lift_metrics, labels,\n figsize=None, x_range=None, y_range=None, legend='on'):\n if figsize:\n plt.figure(figsize=figsize)\n for i, lift_scores in enumerate(list_of_lift_metrics):\n plt.plot(percent_sample_covered, lift_scores)\n plt.plot([percent_sample_covered.min(), 100], [1, 1])\n plt.title('Lift Curves Comparison', fontsize=20)\n plt.xlabel('% of Customers', fontsize=15)\n plt.ylabel('Lift', fontsize=15)\n if x_range:\n plt.xlim(x_range[0], x_range[1])\n if y_range:\n plt.ylim(y_range[0], y_range[1])\n model_labels = labels + ['Random Guessing']\n if legend == 'on':\n plt.legend(model_labels, fontsize=12, loc='best')\n",
"step-5": "import numpy as np\r\nimport pandas as pd\r\nimport matplotlib.pyplot as plt\r\nfrom scipy import stats\r\nimport datetime\r\n\r\n#takes in a sorted data frame holding the actuals, the predicted values (sorted descending) and the percentile of each obsevation\r\n#and returns a new dataframe with all of the appropriate calculations\r\ndef lift_calculations(df):\r\n\r\n\t#adding a sample counter variable\r\n df['sample_num'] = range(len(df)) \r\n \r\n #adding cumulative sum of actual target\r\n df['actual_sum'] = df['actual'].cumsum()\r\n \r\n #column tracking the percentage of samples of total covered\r\n df['per_sample_covered'] = ((df['sample_num']+1)*100)/len(df)\r\n \r\n #percentage of all positives captured\r\n df['per_pos_captured'] = (df['actual_sum']/(len(df[df['actual']==1])))*100\r\n \r\n #proportion of positives captured from total\r\n df['prop_pos_captured_from_all'] = df['per_pos_captured']/df['per_sample_covered']\r\n\r\n return df\r\n\r\n#creates a plot of cumulative positive gain \r\n#takes in a dataframe with all of the relevant statistics already calculated\r\ndef gain_plot(df,figsize=None,x_range=None,y_range=None,legend='on'):\r\n\r\n\t #Plot of the cumulative capture of positives as we go across the deciles\r\n if figsize:\r\n \tfig = plt.figure(figsize=figsize)\r\n plt.plot(pd.Series([0]).append(df['per_sample_covered']),\r\n pd.Series([0]).append(df['per_pos_captured'])) #pre-pending zeos to the front of the series for polotting purposes\r\n plt.plot([0,100],[0,100])\r\n plt.title('Cumulative True Positives Captured vs Random (Gain Curve)',fontsize=20) \r\n plt.xlabel('% of Sample Covered',fontsize=15)\r\n plt.ylabel('% of True Positives Captured',fontsize=15)\r\n if x_range:\r\n \tplt.xlim(x_range[0],x_range[1])\r\n if y_range:\r\n \tplt.ylim(y_range[0],y_range[1])\r\n if legend=='on':\r\n \tplt.legend(['Predictive Targeting','Random Targeting'],fontsize=12,loc=2)\r\n\r\ndef lift_plot(df,figsize=None,x_range=None,y_range=None,legend='on'):\r\n\r\n\t#Lift Curve Plot(at whatever percent of customers cutoff, the model is targeting X times better than random)\r\n #i.e. at the XX percentile, the response rate is Y times as good as it would be if targeting at random at the XX percentile\r\n if figsize:\r\n \tfig = plt.figure(figsize=figsize)\r\n plt.plot(df['per_sample_covered'],df['prop_pos_captured_from_all'])\r\n plt.plot([df['per_sample_covered'].min(),100],[1,1])\r\n plt.title('Lift Curve',fontsize=20)\r\n plt.xlabel('% of Customers',fontsize=15)\r\n plt.ylabel('Lift',fontsize=15)\r\n if x_range:\r\n \tplt.xlim(x_range[0],x_range[1])\r\n if y_range:\r\n \tplt.ylim(y_range[0],y_range[1])\r\n if legend=='on':\r\n \tplt.legend(['Predictive Targeting','Random Targeting'],fontsize=12)\r\n\r\n#a function which takes in an array of predicted values and returns the percentile associated with each one\r\ndef percentile_gen(arr_y_pred):\r\n\treturn np.array(pd.qcut(pd.Series(arr_y_pred).rank(method='first'),100,labels=range(1,101))) #method = first is used in the case when there are a lot of 0s and overlapping of labels\r\n\r\n#a function which takes in an array of actual test values and the model predicted values and stacks them together\r\n#then sorts them and puts them into a dataframe\r\ndef data_prep(arr_y_test,arr_y_pred):\r\n\r\n\t#assigning each observation into a percentile\r\n\tpercentiles = percentile_gen(arr_y_pred)\r\n\r\n\t#print(percentiles.shape)\r\n\r\n\t#joining all the pieces together\r\n\tdata = np.hstack((arr_y_test.reshape((len(arr_y_test),1)),\r\n\t\t\t\t\t arr_y_pred.reshape((len(arr_y_pred),1)),\r\n\t\t\t\t\t percentiles.reshape((len(percentiles),1))))\r\n\t\r\n\t#converting to a data frame\r\n\tdata_df = pd.DataFrame(data)\r\n\tdata_df.columns = ['actual','prob','percentile']\r\n\tdata_df.actual = data_df.actual.astype(int)\r\n\tdata_df.prob = data_df.prob.astype('float64')\r\n\t\r\n\t#sorting by the probability\r\n\tdata_df = data_df.sort_values(by='prob',ascending=False)\r\n\r\n\t#calculating lift metrics\r\n\tdata_df = lift_calculations(data_df)\r\n\r\n\treturn data_df\r\n\r\n#a function which plots the lift curve for the model\r\ndef lift_curve(arr_y_test,arr_y_pred,figsize=None,x_range=None,y_range=None,legend='on'):\r\n\r\n\tdata_df = data_prep(arr_y_test,arr_y_pred)\r\n\r\n\t#print(data_df.groupby('percentile').size())\r\n\r\n\t#lift curve plot\r\n\tlift_plot(data_df,figsize=figsize,x_range=x_range,y_range=y_range,legend=legend)\r\n\tplt.show()\r\n\r\n#a function which plots the gain curve for the model\r\ndef gain_curve(arr_y_test,arr_y_pred,figsize=None,x_range=None,y_range=None,legend='on'):\r\n\r\n\tdata_df = data_prep(arr_y_test,arr_y_pred)\r\n\r\n\t#gain curve plot\r\n\tgain_plot(data_df,figsize=figsize,x_range=x_range,y_range=y_range,legend=legend)\r\n\tplt.show()\r\n\r\n#a function which returns two numpy arrays:\r\n#the first one is the percent of samples covered (X-value)\r\n#the second being the lift values for the correponding the sample (Y-value)\r\ndef lift_values_generator(arr_y_test,arr_y_pred):\r\n\r\n\tdata_df = data_prep(arr_y_test,arr_y_pred)\r\n\r\n\treturn data_df.per_sample_covered, data_df.prop_pos_captured_from_all\r\n\r\n#a function which plots multiple lift curves all on the same graph\r\n#the first parameter is the x axis which represents %of the sample covered\r\n#the second parameter is a list of lists, where each one presents the lift\r\n#curve for a particular model, the last parameter holds the labels for the lift\r\n#curves in the corresponding order\r\n\r\ndef plot_lift_curves(percent_sample_covered,list_of_lift_metrics,labels,figsize=None,x_range=None,y_range=None,legend='on'):\r\n\r\n\tif figsize:\r\n\t\tplt.figure(figsize=figsize)\r\n\r\n\t#plotting the various model lift curves\r\n\tfor i,lift_scores in enumerate(list_of_lift_metrics):\r\n\t\tplt.plot(percent_sample_covered,lift_scores)\r\n\t#base line plot for random guessing\r\n\tplt.plot([percent_sample_covered.min(),100],[1,1])\r\n\t\r\n\t#formats and labels\r\n\tplt.title('Lift Curves Comparison',fontsize=20)\r\n\tplt.xlabel('% of Customers',fontsize=15)\r\n\tplt.ylabel('Lift',fontsize=15)\r\n\tif x_range:\r\n\t\tplt.xlim(x_range[0],x_range[1])\r\n\tif y_range:\r\n\t\tplt.ylim(y_range[0],y_range[1])\r\n\tmodel_labels = labels + ['Random Guessing']\r\n\tif legend == 'on':\r\n\t\tplt.legend(model_labels,fontsize=12,loc='best')\r\n",
"step-ids": [
5,
7,
8,
10,
11
]
}
|
[
5,
7,
8,
10,
11
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for i in range(nodes):
r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)
R, G, B = int(255 * r), int(255 * g), int(255 * b)
color = [R, G, B]
print(color)
img[markers == i + 2] = list(color)
<|reserved_special_token_0|>
cv2.putText(img, text, (160, 20), font, 0.5, (0, 0, 0), 1, cv2.LINE_AA)
plt.subplot(321), plt.imshow(rgb_img)
plt.title('Input image'), plt.xticks([]), plt.yticks([])
plt.subplot(322), plt.imshow(thresh, 'gray')
plt.title('Binary threshold'), plt.xticks([]), plt.yticks([])
plt.subplot(323), plt.imshow(sure_bg, 'gray')
plt.title('Sure background'), plt.xticks([]), plt.yticks([])
plt.subplot(324), plt.imshow(sure_fg, 'gray')
plt.title('Sure foreground'), plt.xticks([]), plt.yticks([])
plt.subplot(325), plt.imshow(dist_transform, 'gray')
plt.title('Distance transform'), plt.xticks([]), plt.yticks([])
plt.subplot(326), plt.imshow(img, 'gray')
plt.title('Result from watershed'), plt.xticks([]), plt.yticks([])
plt.tight_layout()
plt.show()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
img = cv2.imread('coins.jpg')
b, g, r = cv2.split(img)
rgb_img = cv2.merge([r, g, b])
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
grayBlur = cv2.medianBlur(gray, 3)
ret, thresh = cv2.threshold(grayBlur, 200, 255, cv2.THRESH_BINARY_INV)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
sure_bg = cv2.dilate(opening, kernel, iterations=1)
dist_transform = cv2.distanceTransform(opening, cv2.DIST_L2, 5)
ret, sure_fg = cv2.threshold(dist_transform, 0.6 * dist_transform.max(), 255, 0
)
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg, sure_fg)
ret, markers = cv2.connectedComponents(sure_fg)
markers = markers + 1
markers[unknown == 255] = 0
markers = cv2.watershed(img, markers)
img[markers == -1] = [0, 0, 0]
img[markers == 1] = [255, 255, 255]
nodes = np.amax(markers)
for i in range(nodes):
r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)
R, G, B = int(255 * r), int(255 * g), int(255 * b)
color = [R, G, B]
print(color)
img[markers == i + 2] = list(color)
text = 'Coins: ' + str(np.amax(markers - 1))
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, text, (160, 20), font, 0.5, (0, 0, 0), 1, cv2.LINE_AA)
plt.subplot(321), plt.imshow(rgb_img)
plt.title('Input image'), plt.xticks([]), plt.yticks([])
plt.subplot(322), plt.imshow(thresh, 'gray')
plt.title('Binary threshold'), plt.xticks([]), plt.yticks([])
plt.subplot(323), plt.imshow(sure_bg, 'gray')
plt.title('Sure background'), plt.xticks([]), plt.yticks([])
plt.subplot(324), plt.imshow(sure_fg, 'gray')
plt.title('Sure foreground'), plt.xticks([]), plt.yticks([])
plt.subplot(325), plt.imshow(dist_transform, 'gray')
plt.title('Distance transform'), plt.xticks([]), plt.yticks([])
plt.subplot(326), plt.imshow(img, 'gray')
plt.title('Result from watershed'), plt.xticks([]), plt.yticks([])
plt.tight_layout()
plt.show()
<|reserved_special_token_1|>
import numpy as np
import cv2
import colorsys
from matplotlib import pyplot as plt
img = cv2.imread('coins.jpg')
b, g, r = cv2.split(img)
rgb_img = cv2.merge([r, g, b])
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
grayBlur = cv2.medianBlur(gray, 3)
ret, thresh = cv2.threshold(grayBlur, 200, 255, cv2.THRESH_BINARY_INV)
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
sure_bg = cv2.dilate(opening, kernel, iterations=1)
dist_transform = cv2.distanceTransform(opening, cv2.DIST_L2, 5)
ret, sure_fg = cv2.threshold(dist_transform, 0.6 * dist_transform.max(), 255, 0
)
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg, sure_fg)
ret, markers = cv2.connectedComponents(sure_fg)
markers = markers + 1
markers[unknown == 255] = 0
markers = cv2.watershed(img, markers)
img[markers == -1] = [0, 0, 0]
img[markers == 1] = [255, 255, 255]
nodes = np.amax(markers)
for i in range(nodes):
r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)
R, G, B = int(255 * r), int(255 * g), int(255 * b)
color = [R, G, B]
print(color)
img[markers == i + 2] = list(color)
text = 'Coins: ' + str(np.amax(markers - 1))
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, text, (160, 20), font, 0.5, (0, 0, 0), 1, cv2.LINE_AA)
plt.subplot(321), plt.imshow(rgb_img)
plt.title('Input image'), plt.xticks([]), plt.yticks([])
plt.subplot(322), plt.imshow(thresh, 'gray')
plt.title('Binary threshold'), plt.xticks([]), plt.yticks([])
plt.subplot(323), plt.imshow(sure_bg, 'gray')
plt.title('Sure background'), plt.xticks([]), plt.yticks([])
plt.subplot(324), plt.imshow(sure_fg, 'gray')
plt.title('Sure foreground'), plt.xticks([]), plt.yticks([])
plt.subplot(325), plt.imshow(dist_transform, 'gray')
plt.title('Distance transform'), plt.xticks([]), plt.yticks([])
plt.subplot(326), plt.imshow(img, 'gray')
plt.title('Result from watershed'), plt.xticks([]), plt.yticks([])
plt.tight_layout()
plt.show()
<|reserved_special_token_1|>
import numpy as np
import cv2
import colorsys
from matplotlib import pyplot as plt
img = cv2.imread('coins.jpg')
b,g,r = cv2.split(img)
rgb_img = cv2.merge([r,g,b])
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
# Blurring image
grayBlur = cv2.medianBlur(gray, 3)
# Binary threshold
ret, thresh = cv2.threshold(grayBlur, 200,255, cv2.THRESH_BINARY_INV)
# Noise removal
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))
opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel,iterations=2)
# Sure background area
sure_bg = cv2.dilate(opening, kernel, iterations=1)
# Finding sure foreground area
dist_transform = cv2.distanceTransform(opening, cv2.DIST_L2,5)
ret, sure_fg = cv2.threshold(dist_transform,0.6*dist_transform.max(),255,0)
# Finding unknown region
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg,sure_fg)
# Marker labelling
ret, markers = cv2.connectedComponents(sure_fg)
# Add one to all labels so that sure background is not 0, but 1
markers = markers+1
# Now, mark the region of unknown with zero
markers[unknown==255] = 0
markers = cv2.watershed(img,markers)
# Coloring borders black
img[markers == -1] = [0,0,0]
#Color background white
img[markers == 1] = [255, 255, 255]
# Color nodes
nodes = np.amax(markers)
for i in range(nodes):
(r, g, b) = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)
R, G, B = int(255 * r), int(255 * g), int(255 * b)
color = [R,G,B]
print(color)
img[markers == i+2] = list(color)
# Add text with coin count
text = 'Coins: ' + (str)(np.amax(markers-1))
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,text,(160,20), font, 0.5,(0,0,0),1,cv2.LINE_AA)
# Plotting
plt.subplot(321), plt.imshow(rgb_img )
plt.title('Input image'), plt.xticks([]), plt.yticks([])
plt.subplot(322),plt.imshow(thresh, 'gray')
plt.title("Binary threshold"), plt.xticks([]), plt.yticks([])
plt.subplot(323),plt.imshow(sure_bg, 'gray')
plt.title("Sure background"), plt.xticks([]), plt.yticks([])
plt.subplot(324),plt.imshow(sure_fg, 'gray')
plt.title("Sure foreground"), plt.xticks([]), plt.yticks([])
plt.subplot(325),plt.imshow(dist_transform, 'gray')
plt.title("Distance transform"), plt.xticks([]), plt.yticks([])
plt.subplot(326),plt.imshow(img, 'gray')
plt.title("Result from watershed"), plt.xticks([]), plt.yticks([])
plt.tight_layout()
plt.show()
|
flexible
|
{
"blob_id": "39dda191ab2137b5f5538660f17e39b0a1358bf4",
"index": 206,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(nodes):\n r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)\n R, G, B = int(255 * r), int(255 * g), int(255 * b)\n color = [R, G, B]\n print(color)\n img[markers == i + 2] = list(color)\n<mask token>\ncv2.putText(img, text, (160, 20), font, 0.5, (0, 0, 0), 1, cv2.LINE_AA)\nplt.subplot(321), plt.imshow(rgb_img)\nplt.title('Input image'), plt.xticks([]), plt.yticks([])\nplt.subplot(322), plt.imshow(thresh, 'gray')\nplt.title('Binary threshold'), plt.xticks([]), plt.yticks([])\nplt.subplot(323), plt.imshow(sure_bg, 'gray')\nplt.title('Sure background'), plt.xticks([]), plt.yticks([])\nplt.subplot(324), plt.imshow(sure_fg, 'gray')\nplt.title('Sure foreground'), plt.xticks([]), plt.yticks([])\nplt.subplot(325), plt.imshow(dist_transform, 'gray')\nplt.title('Distance transform'), plt.xticks([]), plt.yticks([])\nplt.subplot(326), plt.imshow(img, 'gray')\nplt.title('Result from watershed'), plt.xticks([]), plt.yticks([])\nplt.tight_layout()\nplt.show()\n",
"step-3": "<mask token>\nimg = cv2.imread('coins.jpg')\nb, g, r = cv2.split(img)\nrgb_img = cv2.merge([r, g, b])\ngray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\ngrayBlur = cv2.medianBlur(gray, 3)\nret, thresh = cv2.threshold(grayBlur, 200, 255, cv2.THRESH_BINARY_INV)\nkernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))\nopening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)\nsure_bg = cv2.dilate(opening, kernel, iterations=1)\ndist_transform = cv2.distanceTransform(opening, cv2.DIST_L2, 5)\nret, sure_fg = cv2.threshold(dist_transform, 0.6 * dist_transform.max(), 255, 0\n )\nsure_fg = np.uint8(sure_fg)\nunknown = cv2.subtract(sure_bg, sure_fg)\nret, markers = cv2.connectedComponents(sure_fg)\nmarkers = markers + 1\nmarkers[unknown == 255] = 0\nmarkers = cv2.watershed(img, markers)\nimg[markers == -1] = [0, 0, 0]\nimg[markers == 1] = [255, 255, 255]\nnodes = np.amax(markers)\nfor i in range(nodes):\n r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)\n R, G, B = int(255 * r), int(255 * g), int(255 * b)\n color = [R, G, B]\n print(color)\n img[markers == i + 2] = list(color)\ntext = 'Coins: ' + str(np.amax(markers - 1))\nfont = cv2.FONT_HERSHEY_SIMPLEX\ncv2.putText(img, text, (160, 20), font, 0.5, (0, 0, 0), 1, cv2.LINE_AA)\nplt.subplot(321), plt.imshow(rgb_img)\nplt.title('Input image'), plt.xticks([]), plt.yticks([])\nplt.subplot(322), plt.imshow(thresh, 'gray')\nplt.title('Binary threshold'), plt.xticks([]), plt.yticks([])\nplt.subplot(323), plt.imshow(sure_bg, 'gray')\nplt.title('Sure background'), plt.xticks([]), plt.yticks([])\nplt.subplot(324), plt.imshow(sure_fg, 'gray')\nplt.title('Sure foreground'), plt.xticks([]), plt.yticks([])\nplt.subplot(325), plt.imshow(dist_transform, 'gray')\nplt.title('Distance transform'), plt.xticks([]), plt.yticks([])\nplt.subplot(326), plt.imshow(img, 'gray')\nplt.title('Result from watershed'), plt.xticks([]), plt.yticks([])\nplt.tight_layout()\nplt.show()\n",
"step-4": "import numpy as np\nimport cv2\nimport colorsys\nfrom matplotlib import pyplot as plt\nimg = cv2.imread('coins.jpg')\nb, g, r = cv2.split(img)\nrgb_img = cv2.merge([r, g, b])\ngray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\ngrayBlur = cv2.medianBlur(gray, 3)\nret, thresh = cv2.threshold(grayBlur, 200, 255, cv2.THRESH_BINARY_INV)\nkernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))\nopening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)\nsure_bg = cv2.dilate(opening, kernel, iterations=1)\ndist_transform = cv2.distanceTransform(opening, cv2.DIST_L2, 5)\nret, sure_fg = cv2.threshold(dist_transform, 0.6 * dist_transform.max(), 255, 0\n )\nsure_fg = np.uint8(sure_fg)\nunknown = cv2.subtract(sure_bg, sure_fg)\nret, markers = cv2.connectedComponents(sure_fg)\nmarkers = markers + 1\nmarkers[unknown == 255] = 0\nmarkers = cv2.watershed(img, markers)\nimg[markers == -1] = [0, 0, 0]\nimg[markers == 1] = [255, 255, 255]\nnodes = np.amax(markers)\nfor i in range(nodes):\n r, g, b = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)\n R, G, B = int(255 * r), int(255 * g), int(255 * b)\n color = [R, G, B]\n print(color)\n img[markers == i + 2] = list(color)\ntext = 'Coins: ' + str(np.amax(markers - 1))\nfont = cv2.FONT_HERSHEY_SIMPLEX\ncv2.putText(img, text, (160, 20), font, 0.5, (0, 0, 0), 1, cv2.LINE_AA)\nplt.subplot(321), plt.imshow(rgb_img)\nplt.title('Input image'), plt.xticks([]), plt.yticks([])\nplt.subplot(322), plt.imshow(thresh, 'gray')\nplt.title('Binary threshold'), plt.xticks([]), plt.yticks([])\nplt.subplot(323), plt.imshow(sure_bg, 'gray')\nplt.title('Sure background'), plt.xticks([]), plt.yticks([])\nplt.subplot(324), plt.imshow(sure_fg, 'gray')\nplt.title('Sure foreground'), plt.xticks([]), plt.yticks([])\nplt.subplot(325), plt.imshow(dist_transform, 'gray')\nplt.title('Distance transform'), plt.xticks([]), plt.yticks([])\nplt.subplot(326), plt.imshow(img, 'gray')\nplt.title('Result from watershed'), plt.xticks([]), plt.yticks([])\nplt.tight_layout()\nplt.show()\n",
"step-5": "import numpy as np\nimport cv2\nimport colorsys\nfrom matplotlib import pyplot as plt\n\nimg = cv2.imread('coins.jpg')\n\nb,g,r = cv2.split(img)\nrgb_img = cv2.merge([r,g,b])\n\ngray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n\n# Blurring image\ngrayBlur = cv2.medianBlur(gray, 3)\n\n# Binary threshold\nret, thresh = cv2.threshold(grayBlur, 200,255, cv2.THRESH_BINARY_INV)\n\n# Noise removal\nkernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE,(5,5))\nopening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel,iterations=2)\n\n# Sure background area\nsure_bg = cv2.dilate(opening, kernel, iterations=1)\n\n# Finding sure foreground area\ndist_transform = cv2.distanceTransform(opening, cv2.DIST_L2,5)\nret, sure_fg = cv2.threshold(dist_transform,0.6*dist_transform.max(),255,0)\n\n# Finding unknown region\nsure_fg = np.uint8(sure_fg)\nunknown = cv2.subtract(sure_bg,sure_fg)\n\n# Marker labelling\nret, markers = cv2.connectedComponents(sure_fg)\n\n# Add one to all labels so that sure background is not 0, but 1\nmarkers = markers+1\n\n# Now, mark the region of unknown with zero\nmarkers[unknown==255] = 0\n\nmarkers = cv2.watershed(img,markers)\n\n# Coloring borders black\nimg[markers == -1] = [0,0,0]\n\n#Color background white\nimg[markers == 1] = [255, 255, 255]\n\n# Color nodes\nnodes = np.amax(markers)\nfor i in range(nodes):\n (r, g, b) = colorsys.hsv_to_rgb(float(i) / nodes, 1.0, 1.0)\n R, G, B = int(255 * r), int(255 * g), int(255 * b)\n color = [R,G,B]\n print(color)\n img[markers == i+2] = list(color)\n\n# Add text with coin count\ntext = 'Coins: ' + (str)(np.amax(markers-1))\nfont = cv2.FONT_HERSHEY_SIMPLEX\ncv2.putText(img,text,(160,20), font, 0.5,(0,0,0),1,cv2.LINE_AA)\n\n\n# Plotting\nplt.subplot(321), plt.imshow(rgb_img )\nplt.title('Input image'), plt.xticks([]), plt.yticks([])\nplt.subplot(322),plt.imshow(thresh, 'gray')\nplt.title(\"Binary threshold\"), plt.xticks([]), plt.yticks([])\n\nplt.subplot(323),plt.imshow(sure_bg, 'gray')\nplt.title(\"Sure background\"), plt.xticks([]), plt.yticks([])\n\nplt.subplot(324),plt.imshow(sure_fg, 'gray')\nplt.title(\"Sure foreground\"), plt.xticks([]), plt.yticks([])\n\nplt.subplot(325),plt.imshow(dist_transform, 'gray')\nplt.title(\"Distance transform\"), plt.xticks([]), plt.yticks([])\nplt.subplot(326),plt.imshow(img, 'gray')\nplt.title(\"Result from watershed\"), plt.xticks([]), plt.yticks([])\n\nplt.tight_layout()\nplt.show()\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class ReinforcementLearner:
def __init__(self, clf=None, load=False, clfName=None):
"""
Initialise the Classifier, either from the provided model or from the stored classifier
:param clf: The current classifier, not yet fitted to the data
:param load: Set to True in order to load a previously saved model
"""
if load:
self.clf = joblib.load('model.pkl')
self.reTrain = True
else:
self.clf = clf
self.reTrain = False
if clfName == None:
self.name = self.clf.__class__.__name__
else:
self.name = clfName
<|reserved_special_token_0|>
<|reserved_special_token_0|>
def __exit__(self, exc_type, exc_val, exc_tb):
sqlManager.close()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ReinforcementLearner:
def __init__(self, clf=None, load=False, clfName=None):
"""
Initialise the Classifier, either from the provided model or from the stored classifier
:param clf: The current classifier, not yet fitted to the data
:param load: Set to True in order to load a previously saved model
"""
if load:
self.clf = joblib.load('model.pkl')
self.reTrain = True
else:
self.clf = clf
self.reTrain = False
if clfName == None:
self.name = self.clf.__class__.__name__
else:
self.name = clfName
<|reserved_special_token_0|>
def predict(self, X):
return self.clf.predict(X)
def __exit__(self, exc_type, exc_val, exc_tb):
sqlManager.close()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ReinforcementLearner:
def __init__(self, clf=None, load=False, clfName=None):
"""
Initialise the Classifier, either from the provided model or from the stored classifier
:param clf: The current classifier, not yet fitted to the data
:param load: Set to True in order to load a previously saved model
"""
if load:
self.clf = joblib.load('model.pkl')
self.reTrain = True
else:
self.clf = clf
self.reTrain = False
if clfName == None:
self.name = self.clf.__class__.__name__
else:
self.name = clfName
def fit(self, X, y, scoring='accuracy', crossval=5):
"""
Fit the Reinforcement classifier with data, either adding to previous previous data or learning for first time.
:param X: Input Features
:param y: Class Labels
:param scoring: Scoring used for cross validation
:param crossval: Cross Validation number of folds
:return: True if a new model is fit to the data, or a previous model is updated
False if old model when fit to new data performs poorly in comparison to
earlier data
"""
if not self.reTrain:
score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)
sqlManager.insertValue(self.name, 0.0, score.mean(), 0, len(y), 1)
self.clf.fit(X, y)
joblib.dump(self.clf, 'model.pkl')
print('Data Fit')
return True
else:
previousData = sqlManager.selectNewestRecord(self.name)
if len(previousData) > 0:
oldSize = previousData[5]
newSize = len(y)
accScore = previousData[3]
score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval
)
newAccScore = score.mean()
print('Old Accuracy Score : ', accScore)
print('New Accuracy Score : ', newAccScore)
if accScore <= newAccScore:
print(
'Reinforcement Learning : Newer model is superior. Saving Model.'
)
self.clf.fit(X, y)
sqlManager.insertValue(self.name, accScore, newAccScore,
oldSize, newSize, 1)
joblib.dump(self.clf, 'model.pkl')
return True
else:
print(
'Reinforcement Learning : Newer model is inferior. Not saving model.'
)
return False
def predict(self, X):
return self.clf.predict(X)
def __exit__(self, exc_type, exc_val, exc_tb):
sqlManager.close()
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class ReinforcementLearner:
def __init__(self, clf=None, load=False, clfName=None):
"""
Initialise the Classifier, either from the provided model or from the stored classifier
:param clf: The current classifier, not yet fitted to the data
:param load: Set to True in order to load a previously saved model
"""
if load:
self.clf = joblib.load('model.pkl')
self.reTrain = True
else:
self.clf = clf
self.reTrain = False
if clfName == None:
self.name = self.clf.__class__.__name__
else:
self.name = clfName
def fit(self, X, y, scoring='accuracy', crossval=5):
"""
Fit the Reinforcement classifier with data, either adding to previous previous data or learning for first time.
:param X: Input Features
:param y: Class Labels
:param scoring: Scoring used for cross validation
:param crossval: Cross Validation number of folds
:return: True if a new model is fit to the data, or a previous model is updated
False if old model when fit to new data performs poorly in comparison to
earlier data
"""
if not self.reTrain:
score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)
sqlManager.insertValue(self.name, 0.0, score.mean(), 0, len(y), 1)
self.clf.fit(X, y)
joblib.dump(self.clf, 'model.pkl')
print('Data Fit')
return True
else:
previousData = sqlManager.selectNewestRecord(self.name)
if len(previousData) > 0:
oldSize = previousData[5]
newSize = len(y)
accScore = previousData[3]
score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval
)
newAccScore = score.mean()
print('Old Accuracy Score : ', accScore)
print('New Accuracy Score : ', newAccScore)
if accScore <= newAccScore:
print(
'Reinforcement Learning : Newer model is superior. Saving Model.'
)
self.clf.fit(X, y)
sqlManager.insertValue(self.name, accScore, newAccScore,
oldSize, newSize, 1)
joblib.dump(self.clf, 'model.pkl')
return True
else:
print(
'Reinforcement Learning : Newer model is inferior. Not saving model.'
)
return False
def predict(self, X):
return self.clf.predict(X)
def __exit__(self, exc_type, exc_val, exc_tb):
sqlManager.close()
if __name__ == '__main__':
pass
<|reserved_special_token_1|>
import sklearn.metrics as metrics
import sklearn.cross_validation as cv
from sklearn.externals import joblib
import MachineLearning.Reinforcement.InternalSQLManager as sqlManager
class ReinforcementLearner:
def __init__(self, clf=None, load=False, clfName=None):
"""
Initialise the Classifier, either from the provided model or from the stored classifier
:param clf: The current classifier, not yet fitted to the data
:param load: Set to True in order to load a previously saved model
"""
if load:
self.clf = joblib.load("model.pkl")
self.reTrain = True
else:
self.clf = clf
self.reTrain = False
if clfName == None:
self.name = self.clf.__class__.__name__
else:
self.name = clfName
def fit(self, X, y, scoring="accuracy", crossval=5):
"""
Fit the Reinforcement classifier with data, either adding to previous previous data or learning for first time.
:param X: Input Features
:param y: Class Labels
:param scoring: Scoring used for cross validation
:param crossval: Cross Validation number of folds
:return: True if a new model is fit to the data, or a previous model is updated
False if old model when fit to new data performs poorly in comparison to
earlier data
"""
if not self.reTrain: # Train first time
score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)
sqlManager.insertValue(self.name, 0.0, score.mean(), 0, len(y), 1) # Store the first result of clf
self.clf.fit(X, y)
joblib.dump(self.clf, "model.pkl") # Store the CLF
print("Data Fit")
return True
else:
previousData = sqlManager.selectNewestRecord(self.name) # Check the last entry of CLF
if len(previousData) > 0:
oldSize = previousData[5]
newSize = len(y)
accScore = previousData[3]
score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)
newAccScore = score.mean()
print("Old Accuracy Score : ", accScore)
print("New Accuracy Score : ", newAccScore)
if accScore <= newAccScore: # If new data is benefitial, increases accuracy
print("Reinforcement Learning : Newer model is superior. Saving Model.")
self.clf.fit(X, y)
sqlManager.insertValue(self.name, accScore, newAccScore, oldSize, newSize, 1)
joblib.dump(self.clf, "model.pkl")
return True
else:
print("Reinforcement Learning : Newer model is inferior. Not saving model.")
return False
def predict(self, X):
return self.clf.predict(X)
def __exit__(self, exc_type, exc_val, exc_tb):
sqlManager.close()
if __name__ == "__main__":
pass
|
flexible
|
{
"blob_id": "c9be3d25824093528e2bee51c045d05e036daa67",
"index": 9715,
"step-1": "<mask token>\n\n\nclass ReinforcementLearner:\n\n def __init__(self, clf=None, load=False, clfName=None):\n \"\"\"\n Initialise the Classifier, either from the provided model or from the stored classifier\n\n :param clf: The current classifier, not yet fitted to the data\n :param load: Set to True in order to load a previously saved model\n \"\"\"\n if load:\n self.clf = joblib.load('model.pkl')\n self.reTrain = True\n else:\n self.clf = clf\n self.reTrain = False\n if clfName == None:\n self.name = self.clf.__class__.__name__\n else:\n self.name = clfName\n <mask token>\n <mask token>\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n sqlManager.close()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass ReinforcementLearner:\n\n def __init__(self, clf=None, load=False, clfName=None):\n \"\"\"\n Initialise the Classifier, either from the provided model or from the stored classifier\n\n :param clf: The current classifier, not yet fitted to the data\n :param load: Set to True in order to load a previously saved model\n \"\"\"\n if load:\n self.clf = joblib.load('model.pkl')\n self.reTrain = True\n else:\n self.clf = clf\n self.reTrain = False\n if clfName == None:\n self.name = self.clf.__class__.__name__\n else:\n self.name = clfName\n <mask token>\n\n def predict(self, X):\n return self.clf.predict(X)\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n sqlManager.close()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass ReinforcementLearner:\n\n def __init__(self, clf=None, load=False, clfName=None):\n \"\"\"\n Initialise the Classifier, either from the provided model or from the stored classifier\n\n :param clf: The current classifier, not yet fitted to the data\n :param load: Set to True in order to load a previously saved model\n \"\"\"\n if load:\n self.clf = joblib.load('model.pkl')\n self.reTrain = True\n else:\n self.clf = clf\n self.reTrain = False\n if clfName == None:\n self.name = self.clf.__class__.__name__\n else:\n self.name = clfName\n\n def fit(self, X, y, scoring='accuracy', crossval=5):\n \"\"\"\n Fit the Reinforcement classifier with data, either adding to previous previous data or learning for first time.\n\n :param X: Input Features\n :param y: Class Labels\n :param scoring: Scoring used for cross validation\n :param crossval: Cross Validation number of folds\n :return: True if a new model is fit to the data, or a previous model is updated\n False if old model when fit to new data performs poorly in comparison to\n earlier data\n \"\"\"\n if not self.reTrain:\n score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)\n sqlManager.insertValue(self.name, 0.0, score.mean(), 0, len(y), 1)\n self.clf.fit(X, y)\n joblib.dump(self.clf, 'model.pkl')\n print('Data Fit')\n return True\n else:\n previousData = sqlManager.selectNewestRecord(self.name)\n if len(previousData) > 0:\n oldSize = previousData[5]\n newSize = len(y)\n accScore = previousData[3]\n score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval\n )\n newAccScore = score.mean()\n print('Old Accuracy Score : ', accScore)\n print('New Accuracy Score : ', newAccScore)\n if accScore <= newAccScore:\n print(\n 'Reinforcement Learning : Newer model is superior. Saving Model.'\n )\n self.clf.fit(X, y)\n sqlManager.insertValue(self.name, accScore, newAccScore,\n oldSize, newSize, 1)\n joblib.dump(self.clf, 'model.pkl')\n return True\n else:\n print(\n 'Reinforcement Learning : Newer model is inferior. Not saving model.'\n )\n return False\n\n def predict(self, X):\n return self.clf.predict(X)\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n sqlManager.close()\n\n\n<mask token>\n",
"step-4": "<mask token>\n\n\nclass ReinforcementLearner:\n\n def __init__(self, clf=None, load=False, clfName=None):\n \"\"\"\n Initialise the Classifier, either from the provided model or from the stored classifier\n\n :param clf: The current classifier, not yet fitted to the data\n :param load: Set to True in order to load a previously saved model\n \"\"\"\n if load:\n self.clf = joblib.load('model.pkl')\n self.reTrain = True\n else:\n self.clf = clf\n self.reTrain = False\n if clfName == None:\n self.name = self.clf.__class__.__name__\n else:\n self.name = clfName\n\n def fit(self, X, y, scoring='accuracy', crossval=5):\n \"\"\"\n Fit the Reinforcement classifier with data, either adding to previous previous data or learning for first time.\n\n :param X: Input Features\n :param y: Class Labels\n :param scoring: Scoring used for cross validation\n :param crossval: Cross Validation number of folds\n :return: True if a new model is fit to the data, or a previous model is updated\n False if old model when fit to new data performs poorly in comparison to\n earlier data\n \"\"\"\n if not self.reTrain:\n score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)\n sqlManager.insertValue(self.name, 0.0, score.mean(), 0, len(y), 1)\n self.clf.fit(X, y)\n joblib.dump(self.clf, 'model.pkl')\n print('Data Fit')\n return True\n else:\n previousData = sqlManager.selectNewestRecord(self.name)\n if len(previousData) > 0:\n oldSize = previousData[5]\n newSize = len(y)\n accScore = previousData[3]\n score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval\n )\n newAccScore = score.mean()\n print('Old Accuracy Score : ', accScore)\n print('New Accuracy Score : ', newAccScore)\n if accScore <= newAccScore:\n print(\n 'Reinforcement Learning : Newer model is superior. Saving Model.'\n )\n self.clf.fit(X, y)\n sqlManager.insertValue(self.name, accScore, newAccScore,\n oldSize, newSize, 1)\n joblib.dump(self.clf, 'model.pkl')\n return True\n else:\n print(\n 'Reinforcement Learning : Newer model is inferior. Not saving model.'\n )\n return False\n\n def predict(self, X):\n return self.clf.predict(X)\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n sqlManager.close()\n\n\nif __name__ == '__main__':\n pass\n",
"step-5": "import sklearn.metrics as metrics\nimport sklearn.cross_validation as cv\nfrom sklearn.externals import joblib\nimport MachineLearning.Reinforcement.InternalSQLManager as sqlManager\n\nclass ReinforcementLearner:\n\n def __init__(self, clf=None, load=False, clfName=None):\n \"\"\"\n Initialise the Classifier, either from the provided model or from the stored classifier\n\n :param clf: The current classifier, not yet fitted to the data\n :param load: Set to True in order to load a previously saved model\n \"\"\"\n\n if load:\n self.clf = joblib.load(\"model.pkl\")\n self.reTrain = True\n else:\n self.clf = clf\n self.reTrain = False\n\n if clfName == None:\n self.name = self.clf.__class__.__name__\n else:\n self.name = clfName\n\n def fit(self, X, y, scoring=\"accuracy\", crossval=5):\n \"\"\"\n Fit the Reinforcement classifier with data, either adding to previous previous data or learning for first time.\n\n :param X: Input Features\n :param y: Class Labels\n :param scoring: Scoring used for cross validation\n :param crossval: Cross Validation number of folds\n :return: True if a new model is fit to the data, or a previous model is updated\n False if old model when fit to new data performs poorly in comparison to\n earlier data\n \"\"\"\n if not self.reTrain: # Train first time\n score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)\n\n sqlManager.insertValue(self.name, 0.0, score.mean(), 0, len(y), 1) # Store the first result of clf\n self.clf.fit(X, y)\n\n joblib.dump(self.clf, \"model.pkl\") # Store the CLF\n print(\"Data Fit\")\n return True\n else:\n previousData = sqlManager.selectNewestRecord(self.name) # Check the last entry of CLF\n if len(previousData) > 0:\n oldSize = previousData[5]\n newSize = len(y)\n\n accScore = previousData[3]\n\n score = cv.cross_val_score(self.clf, X, y, scoring, cv=crossval)\n newAccScore = score.mean()\n print(\"Old Accuracy Score : \", accScore)\n print(\"New Accuracy Score : \", newAccScore)\n\n if accScore <= newAccScore: # If new data is benefitial, increases accuracy\n print(\"Reinforcement Learning : Newer model is superior. Saving Model.\")\n self.clf.fit(X, y)\n\n sqlManager.insertValue(self.name, accScore, newAccScore, oldSize, newSize, 1)\n joblib.dump(self.clf, \"model.pkl\")\n return True\n else:\n print(\"Reinforcement Learning : Newer model is inferior. Not saving model.\")\n return False\n\n def predict(self, X):\n return self.clf.predict(X)\n\n def __exit__(self, exc_type, exc_val, exc_tb):\n sqlManager.close()\n\nif __name__ == \"__main__\":\n pass\n\n",
"step-ids": [
3,
4,
5,
6,
8
]
}
|
[
3,
4,
5,
6,
8
] |
<|reserved_special_token_0|>
def calcularHipotenusa(catA, catB):
hipotenusa = catA ** 2 + catB ** 2
hipotenusa = math.sqrt(hipotenusa)
hipotenusa = float(hipotenusa)
print('la hipotenusa es: ', hipotenusa)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(
'programa que calcula hipotenusa tomando el valor de los catetos en tipo double---'
)
print(
'------------------------------------------------------------------------')
print(' ')
<|reserved_special_token_0|>
def calcularHipotenusa(catA, catB):
hipotenusa = catA ** 2 + catB ** 2
hipotenusa = math.sqrt(hipotenusa)
hipotenusa = float(hipotenusa)
print('la hipotenusa es: ', hipotenusa)
calcularHipotenusa(catA, catB)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(
'programa que calcula hipotenusa tomando el valor de los catetos en tipo double---'
)
print(
'------------------------------------------------------------------------')
print(' ')
catA = float(input('igrese el valor del cateto A'))
catB = float(input('ingrese el valor del catebo B'))
def calcularHipotenusa(catA, catB):
hipotenusa = catA ** 2 + catB ** 2
hipotenusa = math.sqrt(hipotenusa)
hipotenusa = float(hipotenusa)
print('la hipotenusa es: ', hipotenusa)
calcularHipotenusa(catA, catB)
<|reserved_special_token_1|>
import math
print(
'programa que calcula hipotenusa tomando el valor de los catetos en tipo double---'
)
print(
'------------------------------------------------------------------------')
print(' ')
catA = float(input('igrese el valor del cateto A'))
catB = float(input('ingrese el valor del catebo B'))
def calcularHipotenusa(catA, catB):
hipotenusa = catA ** 2 + catB ** 2
hipotenusa = math.sqrt(hipotenusa)
hipotenusa = float(hipotenusa)
print('la hipotenusa es: ', hipotenusa)
calcularHipotenusa(catA, catB)
<|reserved_special_token_1|>
import math
print ("programa que calcula hipotenusa tomando el valor de los catetos en tipo double---")
print ("------------------------------------------------------------------------")
print (" ")
catA = float(input("igrese el valor del cateto A"))
catB = float(input("ingrese el valor del catebo B"))
def calcularHipotenusa(catA,catB):
hipotenusa=(catA**2)+(catB**2)
hipotenusa=math.sqrt(hipotenusa)
hipotenusa=float(hipotenusa)
print ("la hipotenusa es: " , hipotenusa)
calcularHipotenusa(catA,catB)
|
flexible
|
{
"blob_id": "af217d0cc111f425282ee21bd47d9007a69a6239",
"index": 6297,
"step-1": "<mask token>\n\n\ndef calcularHipotenusa(catA, catB):\n hipotenusa = catA ** 2 + catB ** 2\n hipotenusa = math.sqrt(hipotenusa)\n hipotenusa = float(hipotenusa)\n print('la hipotenusa es: ', hipotenusa)\n\n\n<mask token>\n",
"step-2": "<mask token>\nprint(\n 'programa que calcula hipotenusa tomando el valor de los catetos en tipo double---'\n )\nprint(\n '------------------------------------------------------------------------')\nprint(' ')\n<mask token>\n\n\ndef calcularHipotenusa(catA, catB):\n hipotenusa = catA ** 2 + catB ** 2\n hipotenusa = math.sqrt(hipotenusa)\n hipotenusa = float(hipotenusa)\n print('la hipotenusa es: ', hipotenusa)\n\n\ncalcularHipotenusa(catA, catB)\n",
"step-3": "<mask token>\nprint(\n 'programa que calcula hipotenusa tomando el valor de los catetos en tipo double---'\n )\nprint(\n '------------------------------------------------------------------------')\nprint(' ')\ncatA = float(input('igrese el valor del cateto A'))\ncatB = float(input('ingrese el valor del catebo B'))\n\n\ndef calcularHipotenusa(catA, catB):\n hipotenusa = catA ** 2 + catB ** 2\n hipotenusa = math.sqrt(hipotenusa)\n hipotenusa = float(hipotenusa)\n print('la hipotenusa es: ', hipotenusa)\n\n\ncalcularHipotenusa(catA, catB)\n",
"step-4": "import math\nprint(\n 'programa que calcula hipotenusa tomando el valor de los catetos en tipo double---'\n )\nprint(\n '------------------------------------------------------------------------')\nprint(' ')\ncatA = float(input('igrese el valor del cateto A'))\ncatB = float(input('ingrese el valor del catebo B'))\n\n\ndef calcularHipotenusa(catA, catB):\n hipotenusa = catA ** 2 + catB ** 2\n hipotenusa = math.sqrt(hipotenusa)\n hipotenusa = float(hipotenusa)\n print('la hipotenusa es: ', hipotenusa)\n\n\ncalcularHipotenusa(catA, catB)\n",
"step-5": "import math\nprint (\"programa que calcula hipotenusa tomando el valor de los catetos en tipo double---\")\nprint (\"------------------------------------------------------------------------\")\nprint (\" \")\n\ncatA = float(input(\"igrese el valor del cateto A\"))\ncatB = float(input(\"ingrese el valor del catebo B\"))\n\ndef calcularHipotenusa(catA,catB):\n\thipotenusa=(catA**2)+(catB**2)\n\thipotenusa=math.sqrt(hipotenusa)\n\thipotenusa=float(hipotenusa)\n\tprint (\"la hipotenusa es: \" , hipotenusa)\n\ncalcularHipotenusa(catA,catB)\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
import proactive
import unittest
import numbers
import os
import pytest
class RestApiTestSuite(unittest.TestCase):
"""Advanced test cases."""
gateway = None
username = ""
password = ""
@pytest.fixture(autouse=True)
def setup_gateway(self, metadata):
self.gateway = proactive.ProActiveGateway(metadata['proactive_url'], debug=True)
self.username = metadata['username']
self.password = metadata['password']
def test_rm_model_hosts(self):
self.gateway.connect(self.username, self.password)
restapi = self.gateway.getProactiveRestApi()
hosts = restapi.get_rm_model_hosts()
self.assertIsNotNone(hosts)
self.assertTrue(isinstance(hosts, list))
self.gateway.disconnect()
def test_rm_model_nodesources(self):
self.gateway.connect(self.username, self.password)
restapi = self.gateway.getProactiveRestApi()
nodesources = restapi.get_rm_model_nodesources()
self.assertIsNotNone(nodesources)
self.assertTrue(isinstance(nodesources, list))
self.gateway.disconnect()
def test_rm_model_tokens(self):
self.gateway.connect(self.username, self.password)
restapi = self.gateway.getProactiveRestApi()
tokens = restapi.get_rm_model_tokens()
self.assertIsNotNone(tokens)
self.assertTrue(isinstance(tokens, list))
self.gateway.disconnect()
if __name__ == '__main__':
unittest.main()
|
normal
|
{
"blob_id": "da2c615b8fab8de6bd63864508da254a46e65bb8",
"index": 4543,
"step-1": "<mask token>\n\n\nclass RestApiTestSuite(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @pytest.fixture(autouse=True)\n def setup_gateway(self, metadata):\n self.gateway = proactive.ProActiveGateway(metadata['proactive_url'],\n debug=True)\n self.username = metadata['username']\n self.password = metadata['password']\n <mask token>\n\n def test_rm_model_nodesources(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n nodesources = restapi.get_rm_model_nodesources()\n self.assertIsNotNone(nodesources)\n self.assertTrue(isinstance(nodesources, list))\n self.gateway.disconnect()\n\n def test_rm_model_tokens(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n tokens = restapi.get_rm_model_tokens()\n self.assertIsNotNone(tokens)\n self.assertTrue(isinstance(tokens, list))\n self.gateway.disconnect()\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass RestApiTestSuite(unittest.TestCase):\n \"\"\"Advanced test cases.\"\"\"\n gateway = None\n username = ''\n password = ''\n\n @pytest.fixture(autouse=True)\n def setup_gateway(self, metadata):\n self.gateway = proactive.ProActiveGateway(metadata['proactive_url'],\n debug=True)\n self.username = metadata['username']\n self.password = metadata['password']\n\n def test_rm_model_hosts(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n hosts = restapi.get_rm_model_hosts()\n self.assertIsNotNone(hosts)\n self.assertTrue(isinstance(hosts, list))\n self.gateway.disconnect()\n\n def test_rm_model_nodesources(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n nodesources = restapi.get_rm_model_nodesources()\n self.assertIsNotNone(nodesources)\n self.assertTrue(isinstance(nodesources, list))\n self.gateway.disconnect()\n\n def test_rm_model_tokens(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n tokens = restapi.get_rm_model_tokens()\n self.assertIsNotNone(tokens)\n self.assertTrue(isinstance(tokens, list))\n self.gateway.disconnect()\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass RestApiTestSuite(unittest.TestCase):\n \"\"\"Advanced test cases.\"\"\"\n gateway = None\n username = ''\n password = ''\n\n @pytest.fixture(autouse=True)\n def setup_gateway(self, metadata):\n self.gateway = proactive.ProActiveGateway(metadata['proactive_url'],\n debug=True)\n self.username = metadata['username']\n self.password = metadata['password']\n\n def test_rm_model_hosts(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n hosts = restapi.get_rm_model_hosts()\n self.assertIsNotNone(hosts)\n self.assertTrue(isinstance(hosts, list))\n self.gateway.disconnect()\n\n def test_rm_model_nodesources(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n nodesources = restapi.get_rm_model_nodesources()\n self.assertIsNotNone(nodesources)\n self.assertTrue(isinstance(nodesources, list))\n self.gateway.disconnect()\n\n def test_rm_model_tokens(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n tokens = restapi.get_rm_model_tokens()\n self.assertIsNotNone(tokens)\n self.assertTrue(isinstance(tokens, list))\n self.gateway.disconnect()\n\n\nif __name__ == '__main__':\n unittest.main()\n",
"step-4": "import proactive\nimport unittest\nimport numbers\nimport os\nimport pytest\n\n\nclass RestApiTestSuite(unittest.TestCase):\n \"\"\"Advanced test cases.\"\"\"\n gateway = None\n username = ''\n password = ''\n\n @pytest.fixture(autouse=True)\n def setup_gateway(self, metadata):\n self.gateway = proactive.ProActiveGateway(metadata['proactive_url'],\n debug=True)\n self.username = metadata['username']\n self.password = metadata['password']\n\n def test_rm_model_hosts(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n hosts = restapi.get_rm_model_hosts()\n self.assertIsNotNone(hosts)\n self.assertTrue(isinstance(hosts, list))\n self.gateway.disconnect()\n\n def test_rm_model_nodesources(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n nodesources = restapi.get_rm_model_nodesources()\n self.assertIsNotNone(nodesources)\n self.assertTrue(isinstance(nodesources, list))\n self.gateway.disconnect()\n\n def test_rm_model_tokens(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n tokens = restapi.get_rm_model_tokens()\n self.assertIsNotNone(tokens)\n self.assertTrue(isinstance(tokens, list))\n self.gateway.disconnect()\n\n\nif __name__ == '__main__':\n unittest.main()\n",
"step-5": "import proactive\nimport unittest\nimport numbers\nimport os\nimport pytest\n\n\nclass RestApiTestSuite(unittest.TestCase):\n \"\"\"Advanced test cases.\"\"\"\n\n gateway = None\n username = \"\"\n password = \"\"\n\n @pytest.fixture(autouse=True)\n def setup_gateway(self, metadata):\n self.gateway = proactive.ProActiveGateway(metadata['proactive_url'], debug=True)\n self.username = metadata['username']\n self.password = metadata['password']\n\n def test_rm_model_hosts(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n hosts = restapi.get_rm_model_hosts()\n self.assertIsNotNone(hosts)\n self.assertTrue(isinstance(hosts, list))\n self.gateway.disconnect()\n\n def test_rm_model_nodesources(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n nodesources = restapi.get_rm_model_nodesources()\n self.assertIsNotNone(nodesources)\n self.assertTrue(isinstance(nodesources, list))\n self.gateway.disconnect()\n\n def test_rm_model_tokens(self):\n self.gateway.connect(self.username, self.password)\n restapi = self.gateway.getProactiveRestApi()\n tokens = restapi.get_rm_model_tokens()\n self.assertIsNotNone(tokens)\n self.assertTrue(isinstance(tokens, list))\n self.gateway.disconnect()\n\n\nif __name__ == '__main__':\n unittest.main()\n",
"step-ids": [
4,
7,
8,
9,
10
]
}
|
[
4,
7,
8,
9,
10
] |
<|reserved_special_token_0|>
class TailwindTraders:
def __init__(self, req):
self._settings = Settings()
self._cs = CognitiveServices()
self._storage = BlobStorageService(self._settings.
get_storage_connection_string())
self._reqbody = req.get_json()
<|reserved_special_token_0|>
def getBlobUrlById(self, image_id):
image = list(self._storage.list_blobs(self._settings.
get_storage_container_name(), prefix=f'{image_id}.jpg'))
image_url = self._storage.make_blob_url(self._settings.
get_storage_container_name(), image[0].name)
return image_url
def getVisualFeaturesByImage(self, image_url):
response_analyze = self._cs.getVisualFeaturesByImage(image_url,
'analyze', {'visualFeatures': 'Description, Tags'})
response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')
return {'analyze': response_analyze, 'ocr': response_ocr}
def updateItemField(self, item, content):
item['Tags'] = content['analyze']['tags']
item['VisualDetail'] = content['analyze']['description']
recognition_result = content['ocr']['recognitionResult']
item['OCRText'] = [line['text'] for line in recognition_result['lines']
]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TailwindTraders:
def __init__(self, req):
self._settings = Settings()
self._cs = CognitiveServices()
self._storage = BlobStorageService(self._settings.
get_storage_connection_string())
self._reqbody = req.get_json()
def readRequest(self):
content = self._reqbody['values'][0]['data']['content']
return content
def getBlobUrlById(self, image_id):
image = list(self._storage.list_blobs(self._settings.
get_storage_container_name(), prefix=f'{image_id}.jpg'))
image_url = self._storage.make_blob_url(self._settings.
get_storage_container_name(), image[0].name)
return image_url
def getVisualFeaturesByImage(self, image_url):
response_analyze = self._cs.getVisualFeaturesByImage(image_url,
'analyze', {'visualFeatures': 'Description, Tags'})
response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')
return {'analyze': response_analyze, 'ocr': response_ocr}
def updateItemField(self, item, content):
item['Tags'] = content['analyze']['tags']
item['VisualDetail'] = content['analyze']['description']
recognition_result = content['ocr']['recognitionResult']
item['OCRText'] = [line['text'] for line in recognition_result['lines']
]
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class TailwindTraders:
def __init__(self, req):
self._settings = Settings()
self._cs = CognitiveServices()
self._storage = BlobStorageService(self._settings.
get_storage_connection_string())
self._reqbody = req.get_json()
def readRequest(self):
content = self._reqbody['values'][0]['data']['content']
return content
def getBlobUrlById(self, image_id):
image = list(self._storage.list_blobs(self._settings.
get_storage_container_name(), prefix=f'{image_id}.jpg'))
image_url = self._storage.make_blob_url(self._settings.
get_storage_container_name(), image[0].name)
return image_url
def getVisualFeaturesByImage(self, image_url):
response_analyze = self._cs.getVisualFeaturesByImage(image_url,
'analyze', {'visualFeatures': 'Description, Tags'})
response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')
return {'analyze': response_analyze, 'ocr': response_ocr}
def updateItemField(self, item, content):
item['Tags'] = content['analyze']['tags']
item['VisualDetail'] = content['analyze']['description']
recognition_result = content['ocr']['recognitionResult']
item['OCRText'] = [line['text'] for line in recognition_result['lines']
]
def generateResult(self, content):
result = {'values': [{'recordId': self._reqbody['values'][0][
'recordId'], 'data': {'Items': content['Items']}}]}
result = json.dumps(result, sort_keys=True, indent=4, separators=(
',', ': '))
return result
<|reserved_special_token_1|>
import json
import requests
import itertools
import logging
from shared_code.config.setting import Settings
from TailwindTraderFunc.cognitiveservices import CognitiveServices
from shared_code.storage.storage import BlobStorageService
class TailwindTraders:
def __init__(self, req):
self._settings = Settings()
self._cs = CognitiveServices()
self._storage = BlobStorageService(self._settings.
get_storage_connection_string())
self._reqbody = req.get_json()
def readRequest(self):
content = self._reqbody['values'][0]['data']['content']
return content
def getBlobUrlById(self, image_id):
image = list(self._storage.list_blobs(self._settings.
get_storage_container_name(), prefix=f'{image_id}.jpg'))
image_url = self._storage.make_blob_url(self._settings.
get_storage_container_name(), image[0].name)
return image_url
def getVisualFeaturesByImage(self, image_url):
response_analyze = self._cs.getVisualFeaturesByImage(image_url,
'analyze', {'visualFeatures': 'Description, Tags'})
response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')
return {'analyze': response_analyze, 'ocr': response_ocr}
def updateItemField(self, item, content):
item['Tags'] = content['analyze']['tags']
item['VisualDetail'] = content['analyze']['description']
recognition_result = content['ocr']['recognitionResult']
item['OCRText'] = [line['text'] for line in recognition_result['lines']
]
def generateResult(self, content):
result = {'values': [{'recordId': self._reqbody['values'][0][
'recordId'], 'data': {'Items': content['Items']}}]}
result = json.dumps(result, sort_keys=True, indent=4, separators=(
',', ': '))
return result
<|reserved_special_token_1|>
import json
import requests
import itertools
import logging
from shared_code.config.setting import Settings
from TailwindTraderFunc.cognitiveservices import CognitiveServices
from shared_code.storage.storage import BlobStorageService
class TailwindTraders():
def __init__(self, req):
self._settings = Settings()
self._cs = CognitiveServices()
self._storage = BlobStorageService(self._settings.get_storage_connection_string())
self._reqbody = req.get_json()
def readRequest(self):
content = self._reqbody["values"][0]["data"]["content"]
return content
def getBlobUrlById(self, image_id):
image = list(self._storage.list_blobs(self._settings.get_storage_container_name(),
prefix=f'{image_id}.jpg'))
image_url = self._storage.make_blob_url(self._settings.get_storage_container_name(),
image[0].name)
return image_url
def getVisualFeaturesByImage(self, image_url):
response_analyze = self._cs.getVisualFeaturesByImage(image_url, "analyze", {'visualFeatures': 'Description, Tags'})
response_ocr = self._cs.getOCRByImage(image_url, "recognizeText")
return {"analyze":response_analyze, "ocr":response_ocr}
def updateItemField(self, item, content):
item["Tags"] = content["analyze"]["tags"]
item["VisualDetail"] = content["analyze"]["description"]
recognition_result = content["ocr"]["recognitionResult"]
item["OCRText"] = [line["text"] for line in recognition_result["lines"]]
def generateResult(self, content):
result = {"values": [{"recordId": self._reqbody["values"][0]["recordId"],
"data" : {"Items": content["Items"]}}]}
result = json.dumps(result, sort_keys=True, indent=4, separators=(',', ': '))
return result
|
flexible
|
{
"blob_id": "75ba2448897bed8388a7b8d876827461e1bc9dd7",
"index": 2809,
"step-1": "<mask token>\n\n\nclass TailwindTraders:\n\n def __init__(self, req):\n self._settings = Settings()\n self._cs = CognitiveServices()\n self._storage = BlobStorageService(self._settings.\n get_storage_connection_string())\n self._reqbody = req.get_json()\n <mask token>\n\n def getBlobUrlById(self, image_id):\n image = list(self._storage.list_blobs(self._settings.\n get_storage_container_name(), prefix=f'{image_id}.jpg'))\n image_url = self._storage.make_blob_url(self._settings.\n get_storage_container_name(), image[0].name)\n return image_url\n\n def getVisualFeaturesByImage(self, image_url):\n response_analyze = self._cs.getVisualFeaturesByImage(image_url,\n 'analyze', {'visualFeatures': 'Description, Tags'})\n response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')\n return {'analyze': response_analyze, 'ocr': response_ocr}\n\n def updateItemField(self, item, content):\n item['Tags'] = content['analyze']['tags']\n item['VisualDetail'] = content['analyze']['description']\n recognition_result = content['ocr']['recognitionResult']\n item['OCRText'] = [line['text'] for line in recognition_result['lines']\n ]\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass TailwindTraders:\n\n def __init__(self, req):\n self._settings = Settings()\n self._cs = CognitiveServices()\n self._storage = BlobStorageService(self._settings.\n get_storage_connection_string())\n self._reqbody = req.get_json()\n\n def readRequest(self):\n content = self._reqbody['values'][0]['data']['content']\n return content\n\n def getBlobUrlById(self, image_id):\n image = list(self._storage.list_blobs(self._settings.\n get_storage_container_name(), prefix=f'{image_id}.jpg'))\n image_url = self._storage.make_blob_url(self._settings.\n get_storage_container_name(), image[0].name)\n return image_url\n\n def getVisualFeaturesByImage(self, image_url):\n response_analyze = self._cs.getVisualFeaturesByImage(image_url,\n 'analyze', {'visualFeatures': 'Description, Tags'})\n response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')\n return {'analyze': response_analyze, 'ocr': response_ocr}\n\n def updateItemField(self, item, content):\n item['Tags'] = content['analyze']['tags']\n item['VisualDetail'] = content['analyze']['description']\n recognition_result = content['ocr']['recognitionResult']\n item['OCRText'] = [line['text'] for line in recognition_result['lines']\n ]\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass TailwindTraders:\n\n def __init__(self, req):\n self._settings = Settings()\n self._cs = CognitiveServices()\n self._storage = BlobStorageService(self._settings.\n get_storage_connection_string())\n self._reqbody = req.get_json()\n\n def readRequest(self):\n content = self._reqbody['values'][0]['data']['content']\n return content\n\n def getBlobUrlById(self, image_id):\n image = list(self._storage.list_blobs(self._settings.\n get_storage_container_name(), prefix=f'{image_id}.jpg'))\n image_url = self._storage.make_blob_url(self._settings.\n get_storage_container_name(), image[0].name)\n return image_url\n\n def getVisualFeaturesByImage(self, image_url):\n response_analyze = self._cs.getVisualFeaturesByImage(image_url,\n 'analyze', {'visualFeatures': 'Description, Tags'})\n response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')\n return {'analyze': response_analyze, 'ocr': response_ocr}\n\n def updateItemField(self, item, content):\n item['Tags'] = content['analyze']['tags']\n item['VisualDetail'] = content['analyze']['description']\n recognition_result = content['ocr']['recognitionResult']\n item['OCRText'] = [line['text'] for line in recognition_result['lines']\n ]\n\n def generateResult(self, content):\n result = {'values': [{'recordId': self._reqbody['values'][0][\n 'recordId'], 'data': {'Items': content['Items']}}]}\n result = json.dumps(result, sort_keys=True, indent=4, separators=(\n ',', ': '))\n return result\n",
"step-4": "import json\nimport requests\nimport itertools\nimport logging\nfrom shared_code.config.setting import Settings\nfrom TailwindTraderFunc.cognitiveservices import CognitiveServices\nfrom shared_code.storage.storage import BlobStorageService\n\n\nclass TailwindTraders:\n\n def __init__(self, req):\n self._settings = Settings()\n self._cs = CognitiveServices()\n self._storage = BlobStorageService(self._settings.\n get_storage_connection_string())\n self._reqbody = req.get_json()\n\n def readRequest(self):\n content = self._reqbody['values'][0]['data']['content']\n return content\n\n def getBlobUrlById(self, image_id):\n image = list(self._storage.list_blobs(self._settings.\n get_storage_container_name(), prefix=f'{image_id}.jpg'))\n image_url = self._storage.make_blob_url(self._settings.\n get_storage_container_name(), image[0].name)\n return image_url\n\n def getVisualFeaturesByImage(self, image_url):\n response_analyze = self._cs.getVisualFeaturesByImage(image_url,\n 'analyze', {'visualFeatures': 'Description, Tags'})\n response_ocr = self._cs.getOCRByImage(image_url, 'recognizeText')\n return {'analyze': response_analyze, 'ocr': response_ocr}\n\n def updateItemField(self, item, content):\n item['Tags'] = content['analyze']['tags']\n item['VisualDetail'] = content['analyze']['description']\n recognition_result = content['ocr']['recognitionResult']\n item['OCRText'] = [line['text'] for line in recognition_result['lines']\n ]\n\n def generateResult(self, content):\n result = {'values': [{'recordId': self._reqbody['values'][0][\n 'recordId'], 'data': {'Items': content['Items']}}]}\n result = json.dumps(result, sort_keys=True, indent=4, separators=(\n ',', ': '))\n return result\n",
"step-5": "import json\nimport requests\nimport itertools\nimport logging\nfrom shared_code.config.setting import Settings\nfrom TailwindTraderFunc.cognitiveservices import CognitiveServices\nfrom shared_code.storage.storage import BlobStorageService\n\n\nclass TailwindTraders():\n\n def __init__(self, req):\n self._settings = Settings()\n self._cs = CognitiveServices()\n self._storage = BlobStorageService(self._settings.get_storage_connection_string())\n self._reqbody = req.get_json()\n\n def readRequest(self):\n content = self._reqbody[\"values\"][0][\"data\"][\"content\"]\n return content\n\n def getBlobUrlById(self, image_id):\n image = list(self._storage.list_blobs(self._settings.get_storage_container_name(),\n prefix=f'{image_id}.jpg'))\n image_url = self._storage.make_blob_url(self._settings.get_storage_container_name(),\n image[0].name)\n return image_url\n\n def getVisualFeaturesByImage(self, image_url):\n response_analyze = self._cs.getVisualFeaturesByImage(image_url, \"analyze\", {'visualFeatures': 'Description, Tags'})\n response_ocr = self._cs.getOCRByImage(image_url, \"recognizeText\")\n return {\"analyze\":response_analyze, \"ocr\":response_ocr}\n \n def updateItemField(self, item, content):\n item[\"Tags\"] = content[\"analyze\"][\"tags\"]\n item[\"VisualDetail\"] = content[\"analyze\"][\"description\"]\n recognition_result = content[\"ocr\"][\"recognitionResult\"]\n item[\"OCRText\"] = [line[\"text\"] for line in recognition_result[\"lines\"]]\n\n def generateResult(self, content):\n result = {\"values\": [{\"recordId\": self._reqbody[\"values\"][0][\"recordId\"],\n \"data\" : {\"Items\": content[\"Items\"]}}]}\n result = json.dumps(result, sort_keys=True, indent=4, separators=(',', ': '))\n return result",
"step-ids": [
5,
6,
7,
8,
9
]
}
|
[
5,
6,
7,
8,
9
] |
#!/usr/bin/env python
import sys
import requests
import numpy as np
import astropy.table as at
if __name__=='__main__':
targets = at.Table.read('targets_LCO2018A_002.txt', format='ascii')
headers={'Authorization': 'Token {}'.format(sys.argv[1])}
for x in targets['targetname']:
obs = requests.get('https://observe.lco.global/api/userrequests/?proposal=LCO2018A-002&title={}'.format(x.split('.')[0]),headers=headers).json()
for y in obs['results']:
print(y['group_id'])
|
normal
|
{
"blob_id": "705bc651e7d12769bcf5994168fe6685a6bae05d",
"index": 5983,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n targets = at.Table.read('targets_LCO2018A_002.txt', format='ascii')\n headers = {'Authorization': 'Token {}'.format(sys.argv[1])}\n for x in targets['targetname']:\n obs = requests.get(\n 'https://observe.lco.global/api/userrequests/?proposal=LCO2018A-002&title={}'\n .format(x.split('.')[0]), headers=headers).json()\n for y in obs['results']:\n print(y['group_id'])\n",
"step-3": "import sys\nimport requests\nimport numpy as np\nimport astropy.table as at\nif __name__ == '__main__':\n targets = at.Table.read('targets_LCO2018A_002.txt', format='ascii')\n headers = {'Authorization': 'Token {}'.format(sys.argv[1])}\n for x in targets['targetname']:\n obs = requests.get(\n 'https://observe.lco.global/api/userrequests/?proposal=LCO2018A-002&title={}'\n .format(x.split('.')[0]), headers=headers).json()\n for y in obs['results']:\n print(y['group_id'])\n",
"step-4": "#!/usr/bin/env python\nimport sys\nimport requests\nimport numpy as np\nimport astropy.table as at\n\nif __name__=='__main__':\n targets = at.Table.read('targets_LCO2018A_002.txt', format='ascii')\n headers={'Authorization': 'Token {}'.format(sys.argv[1])}\n for x in targets['targetname']:\n obs = requests.get('https://observe.lco.global/api/userrequests/?proposal=LCO2018A-002&title={}'.format(x.split('.')[0]),headers=headers).json()\n for y in obs['results']:\n print(y['group_id'])\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
__title__ = 'FUCKTHEINTRUDERS'
__description__ = 'Checking for Intruders in my locality'
__version__ = '0.0.1'
__author__ = 'Shivam Jalotra'
__email__ = 'shivam_11710495@nitkkr.ac.in'
__license__ = 'MIT 1.0'
|
normal
|
{
"blob_id": "ba94a69ac356969ab593afc922a2517f4713771f",
"index": 5536,
"step-1": "<mask token>\n",
"step-2": "__title__ = 'FUCKTHEINTRUDERS'\n__description__ = 'Checking for Intruders in my locality'\n__version__ = '0.0.1'\n__author__ = 'Shivam Jalotra'\n__email__ = 'shivam_11710495@nitkkr.ac.in'\n__license__ = 'MIT 1.0'\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(x[8])
<|reserved_special_token_0|>
print(x[14:17])
<|reserved_special_token_0|>
print(greet.upper())
print(len('banana') * 7)
<|reserved_special_token_0|>
print(data[pos:pos + 3])
<|reserved_special_token_0|>
print(stuff.get('candy', -1))
<|reserved_special_token_1|>
x = 'From marquard@uct.ac.za'
print(x[8])
x = 'From marquard@uct.ac.za'
print(x[14:17])
greet = 'Hello Bob'
xa = 'aaa'
print(greet.upper())
print(len('banana') * 7)
data = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'
pos = data.find('.')
print(data[pos:pos + 3])
stuff = dict()
print(stuff.get('candy', -1))
<|reserved_special_token_1|>
x = 'From marquard@uct.ac.za'
print(x[8])
x = 'From marquard@uct.ac.za'
print(x[14:17])
greet = 'Hello Bob'
xa = "aaa"
print(greet.upper())
print(len('banana')*7)
data = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'
pos = data.find('.')
print(data[pos:pos+3])
stuff = dict()
print(stuff.get('candy',-1))
|
flexible
|
{
"blob_id": "e26f673dfae38148a56927ce82d5ea7ea2545e12",
"index": 8540,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(x[8])\n<mask token>\nprint(x[14:17])\n<mask token>\nprint(greet.upper())\nprint(len('banana') * 7)\n<mask token>\nprint(data[pos:pos + 3])\n<mask token>\nprint(stuff.get('candy', -1))\n",
"step-3": "x = 'From marquard@uct.ac.za'\nprint(x[8])\nx = 'From marquard@uct.ac.za'\nprint(x[14:17])\ngreet = 'Hello Bob'\nxa = 'aaa'\nprint(greet.upper())\nprint(len('banana') * 7)\ndata = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'\npos = data.find('.')\nprint(data[pos:pos + 3])\nstuff = dict()\nprint(stuff.get('candy', -1))\n",
"step-4": "x = 'From marquard@uct.ac.za'\nprint(x[8])\n\nx = 'From marquard@uct.ac.za'\nprint(x[14:17])\n\ngreet = 'Hello Bob'\nxa = \"aaa\"\nprint(greet.upper())\n\n\nprint(len('banana')*7)\n\ndata = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'\npos = data.find('.')\nprint(data[pos:pos+3])\n\nstuff = dict()\nprint(stuff.get('candy',-1))\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
# Copyright 2018 The Cornac Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
# Copyright 2022 Huawei Technologies Co., Ltd
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Module containing functions for negative item sampling.
"""
import numpy as np
def sample_items(num_items, shape, random_state=None):
"""
Randomly sample a number of items.
Parameters
----------
num_items: int
Total number of items from which we should sample:
the maximum value of a sampled item id will be smaller
than this.
shape: int or tuple of ints
Shape of the sampled array.
random_state: np.random.RandomState instance, optional
Random state to use for sampling.
Returns
-------
items: np.array of shape [shape]
Sampled item ids.
"""
if random_state is None:
random_state = np.random.RandomState()
items = random_state.randint(0, num_items, shape, dtype=np.int64)
return items
|
normal
|
{
"blob_id": "d414e4497bae23e4273526c0bbdecd23ed665cac",
"index": 4857,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef sample_items(num_items, shape, random_state=None):\n \"\"\"\n Randomly sample a number of items.\n\n Parameters\n ----------\n\n num_items: int\n Total number of items from which we should sample:\n the maximum value of a sampled item id will be smaller\n than this.\n shape: int or tuple of ints\n Shape of the sampled array.\n random_state: np.random.RandomState instance, optional\n Random state to use for sampling.\n\n Returns\n -------\n\n items: np.array of shape [shape]\n Sampled item ids.\n \"\"\"\n if random_state is None:\n random_state = np.random.RandomState()\n items = random_state.randint(0, num_items, shape, dtype=np.int64)\n return items\n",
"step-3": "<mask token>\nimport numpy as np\n\n\ndef sample_items(num_items, shape, random_state=None):\n \"\"\"\n Randomly sample a number of items.\n\n Parameters\n ----------\n\n num_items: int\n Total number of items from which we should sample:\n the maximum value of a sampled item id will be smaller\n than this.\n shape: int or tuple of ints\n Shape of the sampled array.\n random_state: np.random.RandomState instance, optional\n Random state to use for sampling.\n\n Returns\n -------\n\n items: np.array of shape [shape]\n Sampled item ids.\n \"\"\"\n if random_state is None:\n random_state = np.random.RandomState()\n items = random_state.randint(0, num_items, shape, dtype=np.int64)\n return items\n",
"step-4": "# Copyright 2018 The Cornac Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n# ============================================================================\n# Copyright 2022 Huawei Technologies Co., Ltd\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\"\"\"\nModule containing functions for negative item sampling.\n\"\"\"\n\nimport numpy as np\n\n\ndef sample_items(num_items, shape, random_state=None):\n \"\"\"\n Randomly sample a number of items.\n\n Parameters\n ----------\n\n num_items: int\n Total number of items from which we should sample:\n the maximum value of a sampled item id will be smaller\n than this.\n shape: int or tuple of ints\n Shape of the sampled array.\n random_state: np.random.RandomState instance, optional\n Random state to use for sampling.\n\n Returns\n -------\n\n items: np.array of shape [shape]\n Sampled item ids.\n \"\"\"\n\n if random_state is None:\n random_state = np.random.RandomState()\n\n items = random_state.randint(0, num_items, shape, dtype=np.int64)\n\n return items\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for line in in_file:
data = line.strip().split(': ')
eng_word = data[0]
kor_word = data[1]
voca_dic[eng_word] = kor_word
while True:
keys = list(voca_dic.keys())
index = randint(1, len(keys) - 1)
input_val = input('%s: ' % voca_dic[keys[index]])
if input_val == 'q':
break
if input_val == keys[index]:
print('맞았습니다!')
else:
print('틀렸습니다. 정답은 %s입니다.' % keys[index])
<|reserved_special_token_1|>
<|reserved_special_token_0|>
in_file = open('vocabulary.txt', 'r')
voca_dic = {}
for line in in_file:
data = line.strip().split(': ')
eng_word = data[0]
kor_word = data[1]
voca_dic[eng_word] = kor_word
while True:
keys = list(voca_dic.keys())
index = randint(1, len(keys) - 1)
input_val = input('%s: ' % voca_dic[keys[index]])
if input_val == 'q':
break
if input_val == keys[index]:
print('맞았습니다!')
else:
print('틀렸습니다. 정답은 %s입니다.' % keys[index])
<|reserved_special_token_1|>
from random import randint
in_file = open('vocabulary.txt', 'r')
voca_dic = {}
for line in in_file:
data = line.strip().split(': ')
eng_word = data[0]
kor_word = data[1]
voca_dic[eng_word] = kor_word
while True:
keys = list(voca_dic.keys())
index = randint(1, len(keys) - 1)
input_val = input('%s: ' % voca_dic[keys[index]])
if input_val == 'q':
break
if input_val == keys[index]:
print('맞았습니다!')
else:
print('틀렸습니다. 정답은 %s입니다.' % keys[index])
<|reserved_special_token_1|>
from random import randint
in_file = open("vocabulary.txt", "r")
voca_dic = {}
for line in in_file:
data = line.strip().split(": ")
eng_word = data[0]
kor_word = data[1]
voca_dic[eng_word] = kor_word
while True:
keys = list(voca_dic.keys())
index = randint(1, len(keys) - 1)
input_val = input("%s: " % voca_dic[keys[index]])
if input_val == "q":
break
if input_val == keys[index]:
print("맞았습니다!")
else:
print("틀렸습니다. 정답은 %s입니다." % keys[index])
|
flexible
|
{
"blob_id": "be64c981e7ea70dfcbd840988a633b4a71a43783",
"index": 9814,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor line in in_file:\n data = line.strip().split(': ')\n eng_word = data[0]\n kor_word = data[1]\n voca_dic[eng_word] = kor_word\nwhile True:\n keys = list(voca_dic.keys())\n index = randint(1, len(keys) - 1)\n input_val = input('%s: ' % voca_dic[keys[index]])\n if input_val == 'q':\n break\n if input_val == keys[index]:\n print('맞았습니다!')\n else:\n print('틀렸습니다. 정답은 %s입니다.' % keys[index])\n",
"step-3": "<mask token>\nin_file = open('vocabulary.txt', 'r')\nvoca_dic = {}\nfor line in in_file:\n data = line.strip().split(': ')\n eng_word = data[0]\n kor_word = data[1]\n voca_dic[eng_word] = kor_word\nwhile True:\n keys = list(voca_dic.keys())\n index = randint(1, len(keys) - 1)\n input_val = input('%s: ' % voca_dic[keys[index]])\n if input_val == 'q':\n break\n if input_val == keys[index]:\n print('맞았습니다!')\n else:\n print('틀렸습니다. 정답은 %s입니다.' % keys[index])\n",
"step-4": "from random import randint\nin_file = open('vocabulary.txt', 'r')\nvoca_dic = {}\nfor line in in_file:\n data = line.strip().split(': ')\n eng_word = data[0]\n kor_word = data[1]\n voca_dic[eng_word] = kor_word\nwhile True:\n keys = list(voca_dic.keys())\n index = randint(1, len(keys) - 1)\n input_val = input('%s: ' % voca_dic[keys[index]])\n if input_val == 'q':\n break\n if input_val == keys[index]:\n print('맞았습니다!')\n else:\n print('틀렸습니다. 정답은 %s입니다.' % keys[index])\n",
"step-5": "from random import randint\n\nin_file = open(\"vocabulary.txt\", \"r\")\n\nvoca_dic = {}\n\nfor line in in_file:\n data = line.strip().split(\": \")\n eng_word = data[0]\n kor_word = data[1]\n\n voca_dic[eng_word] = kor_word\n\nwhile True:\n keys = list(voca_dic.keys())\n\n index = randint(1, len(keys) - 1)\n\n input_val = input(\"%s: \" % voca_dic[keys[index]])\n\n if input_val == \"q\":\n break\n\n if input_val == keys[index]:\n print(\"맞았습니다!\")\n else:\n print(\"틀렸습니다. 정답은 %s입니다.\" % keys[index])",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SurveyFeedback(forms.Form):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class SurveyFeedback(forms.Form):
CHOICES = [('Very Satisfied', 'Very Satisfied'), ('Satisfied',
'Satisfied'), ('Neither', 'Neither'), ('Dissatisfied',
'Dissatisfied'), ('Very Dissatisfied', 'Very Dissatisfied')]
radioFeedback = forms.ChoiceField(label=
'How satisfied were you with the service you just received?',
choices=CHOICES, widget=forms.RadioSelect(), required=False)
textFeedback = forms.CharField(label='Survey Feedback', max_length=
settings.MAX_CHARS, required=False, widget=forms.Textarea(attrs={
'rows': 10, 'cols': 80, 'onKeyDown':
'return setTimeout(remainingChars(' + str(settings.MAX_CHARS) +
'), 100);'}))
<|reserved_special_token_1|>
from django import forms
from django.conf import settings
class SurveyFeedback(forms.Form):
CHOICES = [('Very Satisfied', 'Very Satisfied'), ('Satisfied',
'Satisfied'), ('Neither', 'Neither'), ('Dissatisfied',
'Dissatisfied'), ('Very Dissatisfied', 'Very Dissatisfied')]
radioFeedback = forms.ChoiceField(label=
'How satisfied were you with the service you just received?',
choices=CHOICES, widget=forms.RadioSelect(), required=False)
textFeedback = forms.CharField(label='Survey Feedback', max_length=
settings.MAX_CHARS, required=False, widget=forms.Textarea(attrs={
'rows': 10, 'cols': 80, 'onKeyDown':
'return setTimeout(remainingChars(' + str(settings.MAX_CHARS) +
'), 100);'}))
|
flexible
|
{
"blob_id": "a9b7abaaaa811cf12a15def1f2dd21f95bac3d62",
"index": 6310,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass SurveyFeedback(forms.Form):\n <mask token>\n <mask token>\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass SurveyFeedback(forms.Form):\n CHOICES = [('Very Satisfied', 'Very Satisfied'), ('Satisfied',\n 'Satisfied'), ('Neither', 'Neither'), ('Dissatisfied',\n 'Dissatisfied'), ('Very Dissatisfied', 'Very Dissatisfied')]\n radioFeedback = forms.ChoiceField(label=\n 'How satisfied were you with the service you just received?',\n choices=CHOICES, widget=forms.RadioSelect(), required=False)\n textFeedback = forms.CharField(label='Survey Feedback', max_length=\n settings.MAX_CHARS, required=False, widget=forms.Textarea(attrs={\n 'rows': 10, 'cols': 80, 'onKeyDown': \n 'return setTimeout(remainingChars(' + str(settings.MAX_CHARS) +\n '), 100);'}))\n",
"step-4": "from django import forms\nfrom django.conf import settings\n\n\nclass SurveyFeedback(forms.Form):\n CHOICES = [('Very Satisfied', 'Very Satisfied'), ('Satisfied',\n 'Satisfied'), ('Neither', 'Neither'), ('Dissatisfied',\n 'Dissatisfied'), ('Very Dissatisfied', 'Very Dissatisfied')]\n radioFeedback = forms.ChoiceField(label=\n 'How satisfied were you with the service you just received?',\n choices=CHOICES, widget=forms.RadioSelect(), required=False)\n textFeedback = forms.CharField(label='Survey Feedback', max_length=\n settings.MAX_CHARS, required=False, widget=forms.Textarea(attrs={\n 'rows': 10, 'cols': 80, 'onKeyDown': \n 'return setTimeout(remainingChars(' + str(settings.MAX_CHARS) +\n '), 100);'}))\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def module_scope_prefix(request, session_scope_prefix):
"""
Generate a name prefix to be shared by objects created during this pytest module
Relies on pytest's builtin fixture "request"
https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request
"""
return session_scope_prefix + _del_test_prefix(request.module.__name__.
split('.')[-1]) + '-'
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def long_vo():
from rucio.tests.common import get_long_vo
return get_long_vo()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rucio_client():
from rucio.client import Client
return Client()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rse_client():
from rucio.client.rseclient import RSEClient
return RSEClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def dirac_client():
from rucio.client.diracclient import DiracClient
return DiracClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def mock_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('mock', vo=vo)
@pytest.fixture(scope='module')
def test_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('test', vo=vo)
<|reserved_special_token_0|>
@pytest.fixture
def rse_factory(request, vo, function_scope_prefix):
from .temp_factories import TemporaryRSEFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,
db_session=session) as factory:
yield factory
<|reserved_special_token_0|>
@pytest.fixture
def scope_factory():
from rucio.common.utils import generate_uuid
from rucio.core.scope import add_scope
from rucio.common.types import InternalAccount, InternalScope
def create_scopes(vos, account_name=None):
scope_uuid = str(generate_uuid()).lower()[:16]
scope_name = 'shr_%s' % scope_uuid
created_scopes = []
for vo in vos:
scope = InternalScope(scope_name, vo=vo)
add_scope(scope, InternalAccount(account_name if account_name else
'root', vo=vo))
created_scopes.append(scope)
return scope_name, created_scopes
return create_scopes
class _TagFactory:
def __init__(self, prefix):
self.prefix = prefix
self.index = 0
def new_tag(self):
self.index += 1
return f'{self.prefix}-{self.index}'
<|reserved_special_token_0|>
@pytest.fixture(scope='class')
def tag_factory_class(class_scope_prefix):
return _TagFactory(prefix=
f"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}"
.replace('_', '-'))
<|reserved_special_token_0|>
def __get_fixture_param(request):
fixture_param = getattr(request, 'param', None)
if not fixture_param:
mark = next(iter(filter(lambda m: m.name == 'parametrize', request.
instance.pytestmark)), None)
if mark:
fixture_param = mark.args[1][0]
return fixture_param
<|reserved_special_token_0|>
@pytest.fixture
def core_config_mock(request):
"""
Fixture to allow having per-test core.config tables without affecting the other parallel tests.
This override works only in tests which use core function calls directly, not in the ones working
via the API, because the normal config table is not touched and the rucio instance answering API
calls is not aware of this mock.
This fixture acts by creating a new copy of the "config" sql table using the :memory: sqlite engine.
Accesses to the "models.Config" table are then redirected to this temporary table via mock.patch().
"""
from unittest import mock
from sqlalchemy import Column
from rucio.common.utils import generate_uuid
from rucio.db.sqla.models import String, PrimaryKeyConstraint
from rucio.db.sqla.session import get_session
table_content = []
params = __get_fixture_param(request)
if params:
table_content = params.get('table_content', table_content)
InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid
(), Column('section', String(128)), Column('opt', String(128)),
Column('value', String(4000)), table_args=(PrimaryKeyConstraint(
'section', 'opt', name='CONFIGS_PK'),))
session = get_session()()
for section, option, value in (table_content or []):
InMemoryConfig(section=section, opt=option, value=value).save(flush
=True, session=session)
session.commit()
with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):
yield
<|reserved_special_token_0|>
@pytest.fixture
def caches_mock(request):
"""
Fixture which overrides the different internal caches with in-memory ones for the duration
of a particular test.
This override works only in tests which use core function calls directly, not in the ones
working via API.
The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.
"""
from unittest import mock
from contextlib import ExitStack
from dogpile.cache import make_region
caches_to_mock = []
expiration_time = 600
params = __get_fixture_param(request)
if params:
caches_to_mock = params.get('caches_to_mock', caches_to_mock)
expiration_time = params.get('expiration_time', expiration_time)
with ExitStack() as stack:
mocked_caches = []
for module in caches_to_mock:
region = make_region().configure('dogpile.cache.memory',
expiration_time=expiration_time)
stack.enter_context(mock.patch(module, new=region))
mocked_caches.append(region)
yield mocked_caches
@pytest.fixture
def metrics_mock():
"""
Overrides the prometheus metric registry and allows to verify if the desired
prometheus metrics were correctly recorded.
"""
from unittest import mock
from prometheus_client import CollectorRegistry, values
with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()
) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}
), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(
'rucio.core.monitor.TIMINGS', new={}), mock.patch(
'prometheus_client.values.ValueClass', new=values.MutexValue):
yield registry
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def module_scope_prefix(request, session_scope_prefix):
"""
Generate a name prefix to be shared by objects created during this pytest module
Relies on pytest's builtin fixture "request"
https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request
"""
return session_scope_prefix + _del_test_prefix(request.module.__name__.
split('.')[-1]) + '-'
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def long_vo():
from rucio.tests.common import get_long_vo
return get_long_vo()
@pytest.fixture(scope='module')
def account_client():
from rucio.client.accountclient import AccountClient
return AccountClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rucio_client():
from rucio.client import Client
return Client()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rse_client():
from rucio.client.rseclient import RSEClient
return RSEClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def dirac_client():
from rucio.client.diracclient import DiracClient
return DiracClient()
<|reserved_special_token_0|>
@pytest.fixture
def auth_token(rest_client, long_vo):
from rucio.tests.common import vohdr, headers, loginhdr
auth_response = rest_client.get('/auth/userpass', headers=headers(
loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))
assert auth_response.status_code == 200
token = auth_response.headers.get('X-Rucio-Auth-Token')
assert token
return str(token)
@pytest.fixture(scope='module')
def mock_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('mock', vo=vo)
@pytest.fixture(scope='module')
def test_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('test', vo=vo)
<|reserved_special_token_0|>
@pytest.fixture
def rse_factory(request, vo, function_scope_prefix):
from .temp_factories import TemporaryRSEFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,
db_session=session) as factory:
yield factory
<|reserved_special_token_0|>
@pytest.fixture
def scope_factory():
from rucio.common.utils import generate_uuid
from rucio.core.scope import add_scope
from rucio.common.types import InternalAccount, InternalScope
def create_scopes(vos, account_name=None):
scope_uuid = str(generate_uuid()).lower()[:16]
scope_name = 'shr_%s' % scope_uuid
created_scopes = []
for vo in vos:
scope = InternalScope(scope_name, vo=vo)
add_scope(scope, InternalAccount(account_name if account_name else
'root', vo=vo))
created_scopes.append(scope)
return scope_name, created_scopes
return create_scopes
class _TagFactory:
def __init__(self, prefix):
self.prefix = prefix
self.index = 0
def new_tag(self):
self.index += 1
return f'{self.prefix}-{self.index}'
<|reserved_special_token_0|>
@pytest.fixture(scope='class')
def tag_factory_class(class_scope_prefix):
return _TagFactory(prefix=
f"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}"
.replace('_', '-'))
<|reserved_special_token_0|>
def __get_fixture_param(request):
fixture_param = getattr(request, 'param', None)
if not fixture_param:
mark = next(iter(filter(lambda m: m.name == 'parametrize', request.
instance.pytestmark)), None)
if mark:
fixture_param = mark.args[1][0]
return fixture_param
<|reserved_special_token_0|>
@pytest.fixture
def core_config_mock(request):
"""
Fixture to allow having per-test core.config tables without affecting the other parallel tests.
This override works only in tests which use core function calls directly, not in the ones working
via the API, because the normal config table is not touched and the rucio instance answering API
calls is not aware of this mock.
This fixture acts by creating a new copy of the "config" sql table using the :memory: sqlite engine.
Accesses to the "models.Config" table are then redirected to this temporary table via mock.patch().
"""
from unittest import mock
from sqlalchemy import Column
from rucio.common.utils import generate_uuid
from rucio.db.sqla.models import String, PrimaryKeyConstraint
from rucio.db.sqla.session import get_session
table_content = []
params = __get_fixture_param(request)
if params:
table_content = params.get('table_content', table_content)
InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid
(), Column('section', String(128)), Column('opt', String(128)),
Column('value', String(4000)), table_args=(PrimaryKeyConstraint(
'section', 'opt', name='CONFIGS_PK'),))
session = get_session()()
for section, option, value in (table_content or []):
InMemoryConfig(section=section, opt=option, value=value).save(flush
=True, session=session)
session.commit()
with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):
yield
@pytest.fixture
def file_config_mock(request):
"""
Fixture which allows to have an isolated in-memory configuration file instance which
is not persisted after exiting the fixture.
This override works only in tests which use config calls directly, not in the ones working
via the API, as the server config is not changed.
"""
from unittest import mock
from rucio.common.config import Config, config_set, config_has_section, config_add_section
overrides = []
params = __get_fixture_param(request)
if params:
overrides = params.get('overrides', overrides)
parser = Config().parser
with mock.patch('rucio.common.config.get_config', side_effect=lambda :
parser):
for section, option, value in (overrides or []):
if not config_has_section(section):
config_add_section(section)
config_set(section, option, value)
yield
@pytest.fixture
def caches_mock(request):
"""
Fixture which overrides the different internal caches with in-memory ones for the duration
of a particular test.
This override works only in tests which use core function calls directly, not in the ones
working via API.
The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.
"""
from unittest import mock
from contextlib import ExitStack
from dogpile.cache import make_region
caches_to_mock = []
expiration_time = 600
params = __get_fixture_param(request)
if params:
caches_to_mock = params.get('caches_to_mock', caches_to_mock)
expiration_time = params.get('expiration_time', expiration_time)
with ExitStack() as stack:
mocked_caches = []
for module in caches_to_mock:
region = make_region().configure('dogpile.cache.memory',
expiration_time=expiration_time)
stack.enter_context(mock.patch(module, new=region))
mocked_caches.append(region)
yield mocked_caches
@pytest.fixture
def metrics_mock():
"""
Overrides the prometheus metric registry and allows to verify if the desired
prometheus metrics were correctly recorded.
"""
from unittest import mock
from prometheus_client import CollectorRegistry, values
with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()
) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}
), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(
'rucio.core.monitor.TIMINGS', new={}), mock.patch(
'prometheus_client.values.ValueClass', new=values.MutexValue):
yield registry
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def session_scope_prefix():
"""
Generate a name prefix to be shared by objects created during this pytest session
"""
return ''.join(choice(ascii_uppercase) for _ in range(6)) + '-'
@pytest.fixture(scope='module')
def module_scope_prefix(request, session_scope_prefix):
"""
Generate a name prefix to be shared by objects created during this pytest module
Relies on pytest's builtin fixture "request"
https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request
"""
return session_scope_prefix + _del_test_prefix(request.module.__name__.
split('.')[-1]) + '-'
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def long_vo():
from rucio.tests.common import get_long_vo
return get_long_vo()
@pytest.fixture(scope='module')
def account_client():
from rucio.client.accountclient import AccountClient
return AccountClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rucio_client():
from rucio.client import Client
return Client()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rse_client():
from rucio.client.rseclient import RSEClient
return RSEClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def dirac_client():
from rucio.client.diracclient import DiracClient
return DiracClient()
<|reserved_special_token_0|>
@pytest.fixture
def auth_token(rest_client, long_vo):
from rucio.tests.common import vohdr, headers, loginhdr
auth_response = rest_client.get('/auth/userpass', headers=headers(
loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))
assert auth_response.status_code == 200
token = auth_response.headers.get('X-Rucio-Auth-Token')
assert token
return str(token)
@pytest.fixture(scope='module')
def mock_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('mock', vo=vo)
@pytest.fixture(scope='module')
def test_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('test', vo=vo)
<|reserved_special_token_0|>
@pytest.fixture
def rse_factory(request, vo, function_scope_prefix):
from .temp_factories import TemporaryRSEFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,
db_session=session) as factory:
yield factory
<|reserved_special_token_0|>
@pytest.fixture
def scope_factory():
from rucio.common.utils import generate_uuid
from rucio.core.scope import add_scope
from rucio.common.types import InternalAccount, InternalScope
def create_scopes(vos, account_name=None):
scope_uuid = str(generate_uuid()).lower()[:16]
scope_name = 'shr_%s' % scope_uuid
created_scopes = []
for vo in vos:
scope = InternalScope(scope_name, vo=vo)
add_scope(scope, InternalAccount(account_name if account_name else
'root', vo=vo))
created_scopes.append(scope)
return scope_name, created_scopes
return create_scopes
class _TagFactory:
def __init__(self, prefix):
self.prefix = prefix
self.index = 0
def new_tag(self):
self.index += 1
return f'{self.prefix}-{self.index}'
<|reserved_special_token_0|>
@pytest.fixture(scope='class')
def tag_factory_class(class_scope_prefix):
return _TagFactory(prefix=
f"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}"
.replace('_', '-'))
<|reserved_special_token_0|>
def __get_fixture_param(request):
fixture_param = getattr(request, 'param', None)
if not fixture_param:
mark = next(iter(filter(lambda m: m.name == 'parametrize', request.
instance.pytestmark)), None)
if mark:
fixture_param = mark.args[1][0]
return fixture_param
<|reserved_special_token_0|>
@pytest.fixture
def core_config_mock(request):
"""
Fixture to allow having per-test core.config tables without affecting the other parallel tests.
This override works only in tests which use core function calls directly, not in the ones working
via the API, because the normal config table is not touched and the rucio instance answering API
calls is not aware of this mock.
This fixture acts by creating a new copy of the "config" sql table using the :memory: sqlite engine.
Accesses to the "models.Config" table are then redirected to this temporary table via mock.patch().
"""
from unittest import mock
from sqlalchemy import Column
from rucio.common.utils import generate_uuid
from rucio.db.sqla.models import String, PrimaryKeyConstraint
from rucio.db.sqla.session import get_session
table_content = []
params = __get_fixture_param(request)
if params:
table_content = params.get('table_content', table_content)
InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid
(), Column('section', String(128)), Column('opt', String(128)),
Column('value', String(4000)), table_args=(PrimaryKeyConstraint(
'section', 'opt', name='CONFIGS_PK'),))
session = get_session()()
for section, option, value in (table_content or []):
InMemoryConfig(section=section, opt=option, value=value).save(flush
=True, session=session)
session.commit()
with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):
yield
@pytest.fixture
def file_config_mock(request):
"""
Fixture which allows to have an isolated in-memory configuration file instance which
is not persisted after exiting the fixture.
This override works only in tests which use config calls directly, not in the ones working
via the API, as the server config is not changed.
"""
from unittest import mock
from rucio.common.config import Config, config_set, config_has_section, config_add_section
overrides = []
params = __get_fixture_param(request)
if params:
overrides = params.get('overrides', overrides)
parser = Config().parser
with mock.patch('rucio.common.config.get_config', side_effect=lambda :
parser):
for section, option, value in (overrides or []):
if not config_has_section(section):
config_add_section(section)
config_set(section, option, value)
yield
@pytest.fixture
def caches_mock(request):
"""
Fixture which overrides the different internal caches with in-memory ones for the duration
of a particular test.
This override works only in tests which use core function calls directly, not in the ones
working via API.
The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.
"""
from unittest import mock
from contextlib import ExitStack
from dogpile.cache import make_region
caches_to_mock = []
expiration_time = 600
params = __get_fixture_param(request)
if params:
caches_to_mock = params.get('caches_to_mock', caches_to_mock)
expiration_time = params.get('expiration_time', expiration_time)
with ExitStack() as stack:
mocked_caches = []
for module in caches_to_mock:
region = make_region().configure('dogpile.cache.memory',
expiration_time=expiration_time)
stack.enter_context(mock.patch(module, new=region))
mocked_caches.append(region)
yield mocked_caches
@pytest.fixture
def metrics_mock():
"""
Overrides the prometheus metric registry and allows to verify if the desired
prometheus metrics were correctly recorded.
"""
from unittest import mock
from prometheus_client import CollectorRegistry, values
with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()
) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}
), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(
'rucio.core.monitor.TIMINGS', new={}), mock.patch(
'prometheus_client.values.ValueClass', new=values.MutexValue):
yield registry
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def session_scope_prefix():
"""
Generate a name prefix to be shared by objects created during this pytest session
"""
return ''.join(choice(ascii_uppercase) for _ in range(6)) + '-'
@pytest.fixture(scope='module')
def module_scope_prefix(request, session_scope_prefix):
"""
Generate a name prefix to be shared by objects created during this pytest module
Relies on pytest's builtin fixture "request"
https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request
"""
return session_scope_prefix + _del_test_prefix(request.module.__name__.
split('.')[-1]) + '-'
<|reserved_special_token_0|>
@pytest.fixture(scope='session')
def long_vo():
from rucio.tests.common import get_long_vo
return get_long_vo()
@pytest.fixture(scope='module')
def account_client():
from rucio.client.accountclient import AccountClient
return AccountClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rucio_client():
from rucio.client import Client
return Client()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def rse_client():
from rucio.client.rseclient import RSEClient
return RSEClient()
<|reserved_special_token_0|>
@pytest.fixture(scope='module')
def dirac_client():
from rucio.client.diracclient import DiracClient
return DiracClient()
@pytest.fixture
def rest_client():
from rucio.tests.common import print_response
from flask.testing import FlaskClient
from rucio.web.rest.flaskapi.v1.main import application
class WrappedFlaskClient(FlaskClient):
def __init__(self, *args, **kwargs):
super(WrappedFlaskClient, self).__init__(*args, **kwargs)
def open(self, path='/', *args, **kwargs):
print(kwargs.get('method', 'GET'), path)
response = super(WrappedFlaskClient, self).open(path, *args, **
kwargs)
try:
print_response(response)
except Exception:
traceback.print_exc()
return response
_testing = application.testing
application.testing = True
application.test_client_class = WrappedFlaskClient
with application.test_client() as client:
yield client
application.test_client_class = None
application.testing = _testing
@pytest.fixture
def auth_token(rest_client, long_vo):
from rucio.tests.common import vohdr, headers, loginhdr
auth_response = rest_client.get('/auth/userpass', headers=headers(
loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))
assert auth_response.status_code == 200
token = auth_response.headers.get('X-Rucio-Auth-Token')
assert token
return str(token)
@pytest.fixture(scope='module')
def mock_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('mock', vo=vo)
@pytest.fixture(scope='module')
def test_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('test', vo=vo)
<|reserved_special_token_0|>
@pytest.fixture
def rse_factory(request, vo, function_scope_prefix):
from .temp_factories import TemporaryRSEFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,
db_session=session) as factory:
yield factory
<|reserved_special_token_0|>
@pytest.fixture
def did_factory(request, vo, mock_scope, function_scope_prefix,
file_factory, root_account):
from .temp_factories import TemporaryDidFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryDidFactory(vo=vo, default_scope=mock_scope, name_prefix=
function_scope_prefix, file_factory=file_factory, default_account=
root_account, db_session=session) as factory:
yield factory
<|reserved_special_token_0|>
@pytest.fixture
def scope_factory():
from rucio.common.utils import generate_uuid
from rucio.core.scope import add_scope
from rucio.common.types import InternalAccount, InternalScope
def create_scopes(vos, account_name=None):
scope_uuid = str(generate_uuid()).lower()[:16]
scope_name = 'shr_%s' % scope_uuid
created_scopes = []
for vo in vos:
scope = InternalScope(scope_name, vo=vo)
add_scope(scope, InternalAccount(account_name if account_name else
'root', vo=vo))
created_scopes.append(scope)
return scope_name, created_scopes
return create_scopes
class _TagFactory:
def __init__(self, prefix):
self.prefix = prefix
self.index = 0
def new_tag(self):
self.index += 1
return f'{self.prefix}-{self.index}'
<|reserved_special_token_0|>
@pytest.fixture(scope='class')
def tag_factory_class(class_scope_prefix):
return _TagFactory(prefix=
f"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}"
.replace('_', '-'))
<|reserved_special_token_0|>
def __get_fixture_param(request):
fixture_param = getattr(request, 'param', None)
if not fixture_param:
mark = next(iter(filter(lambda m: m.name == 'parametrize', request.
instance.pytestmark)), None)
if mark:
fixture_param = mark.args[1][0]
return fixture_param
<|reserved_special_token_0|>
@pytest.fixture
def core_config_mock(request):
"""
Fixture to allow having per-test core.config tables without affecting the other parallel tests.
This override works only in tests which use core function calls directly, not in the ones working
via the API, because the normal config table is not touched and the rucio instance answering API
calls is not aware of this mock.
This fixture acts by creating a new copy of the "config" sql table using the :memory: sqlite engine.
Accesses to the "models.Config" table are then redirected to this temporary table via mock.patch().
"""
from unittest import mock
from sqlalchemy import Column
from rucio.common.utils import generate_uuid
from rucio.db.sqla.models import String, PrimaryKeyConstraint
from rucio.db.sqla.session import get_session
table_content = []
params = __get_fixture_param(request)
if params:
table_content = params.get('table_content', table_content)
InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid
(), Column('section', String(128)), Column('opt', String(128)),
Column('value', String(4000)), table_args=(PrimaryKeyConstraint(
'section', 'opt', name='CONFIGS_PK'),))
session = get_session()()
for section, option, value in (table_content or []):
InMemoryConfig(section=section, opt=option, value=value).save(flush
=True, session=session)
session.commit()
with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):
yield
@pytest.fixture
def file_config_mock(request):
"""
Fixture which allows to have an isolated in-memory configuration file instance which
is not persisted after exiting the fixture.
This override works only in tests which use config calls directly, not in the ones working
via the API, as the server config is not changed.
"""
from unittest import mock
from rucio.common.config import Config, config_set, config_has_section, config_add_section
overrides = []
params = __get_fixture_param(request)
if params:
overrides = params.get('overrides', overrides)
parser = Config().parser
with mock.patch('rucio.common.config.get_config', side_effect=lambda :
parser):
for section, option, value in (overrides or []):
if not config_has_section(section):
config_add_section(section)
config_set(section, option, value)
yield
@pytest.fixture
def caches_mock(request):
"""
Fixture which overrides the different internal caches with in-memory ones for the duration
of a particular test.
This override works only in tests which use core function calls directly, not in the ones
working via API.
The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.
"""
from unittest import mock
from contextlib import ExitStack
from dogpile.cache import make_region
caches_to_mock = []
expiration_time = 600
params = __get_fixture_param(request)
if params:
caches_to_mock = params.get('caches_to_mock', caches_to_mock)
expiration_time = params.get('expiration_time', expiration_time)
with ExitStack() as stack:
mocked_caches = []
for module in caches_to_mock:
region = make_region().configure('dogpile.cache.memory',
expiration_time=expiration_time)
stack.enter_context(mock.patch(module, new=region))
mocked_caches.append(region)
yield mocked_caches
@pytest.fixture
def metrics_mock():
"""
Overrides the prometheus metric registry and allows to verify if the desired
prometheus metrics were correctly recorded.
"""
from unittest import mock
from prometheus_client import CollectorRegistry, values
with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()
) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}
), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(
'rucio.core.monitor.TIMINGS', new={}), mock.patch(
'prometheus_client.values.ValueClass', new=values.MutexValue):
yield registry
<|reserved_special_token_1|>
# -*- coding: utf-8 -*-
# Copyright European Organization for Nuclear Research (CERN) since 2012
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import traceback
import re
import functools
from os import environ
from random import choice
from string import ascii_uppercase
import pytest
_del_test_prefix = functools.partial(re.compile(r'^[Tt][Ee][Ss][Tt]_?').sub, '')
# local imports in the fixtures to make this file loadable in e.g. client tests
pytest_plugins = ('tests.ruciopytest.artifacts_plugin', )
def pytest_configure(config):
config.addinivalue_line('markers', 'dirty: marks test as dirty, i.e. tests are leaving structures behind')
config.addinivalue_line('markers', 'noparallel(reason, groups): marks test being unable to run in parallel to other tests' )
if config.pluginmanager.hasplugin("xdist"):
from .ruciopytest import xdist_noparallel_scheduler
config.pluginmanager.register(xdist_noparallel_scheduler)
def pytest_make_parametrize_id(config, val, argname):
if argname == 'file_config_mock':
cfg = {}
for section, option, value in val['overrides']:
cfg.setdefault(section, {})[option] = value
return argname + str(cfg)
if argname == 'core_config_mock':
cfg = {}
for section, option, value in val['table_content']:
cfg.setdefault(section, {})[option] = value
return argname + str(cfg)
# return None to let pytest handle the formatting
return None
@pytest.fixture(scope='session')
def session_scope_prefix():
"""
Generate a name prefix to be shared by objects created during this pytest session
"""
return ''.join(choice(ascii_uppercase) for _ in range(6)) + '-'
@pytest.fixture(scope='module')
def module_scope_prefix(request, session_scope_prefix):
"""
Generate a name prefix to be shared by objects created during this pytest module
Relies on pytest's builtin fixture "request"
https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request
"""
return session_scope_prefix + _del_test_prefix(request.module.__name__.split('.')[-1]) + '-'
@pytest.fixture(scope='class')
def class_scope_prefix(request, module_scope_prefix):
if not request.cls:
return module_scope_prefix
return module_scope_prefix + _del_test_prefix(request.cls.__name__) + '-'
@pytest.fixture(scope='function')
def function_scope_prefix(request, class_scope_prefix):
return class_scope_prefix + _del_test_prefix(request.node.originalname) + '-'
@pytest.fixture(scope='session')
def vo():
if environ.get('SUITE', 'remote_dbs') != 'client':
# Server test, we can use short VO via DB for internal tests
from rucio.tests.common_server import get_vo
return get_vo()
else:
# Client-only test, only use config with no DB config
from rucio.tests.common import get_long_vo
return get_long_vo()
@pytest.fixture(scope='session')
def second_vo():
from rucio.common.config import config_get_bool
from rucio.core.vo import vo_exists, add_vo
multi_vo = config_get_bool('common', 'multi_vo', raise_exception=False, default=False)
if not multi_vo:
pytest.skip('multi_vo mode is not enabled. Running multi_vo tests in single_vo mode would result in failures.')
new_vo = 'new'
if not vo_exists(vo=new_vo):
add_vo(vo=new_vo, description='Test', email='rucio@email.com')
return new_vo
@pytest.fixture(scope='session')
def long_vo():
from rucio.tests.common import get_long_vo
return get_long_vo()
@pytest.fixture(scope='module')
def account_client():
from rucio.client.accountclient import AccountClient
return AccountClient()
@pytest.fixture(scope='module')
def replica_client():
from rucio.client.replicaclient import ReplicaClient
return ReplicaClient()
@pytest.fixture(scope='module')
def rucio_client():
from rucio.client import Client
return Client()
@pytest.fixture(scope='module')
def did_client():
from rucio.client.didclient import DIDClient
return DIDClient()
@pytest.fixture(scope='module')
def rse_client():
from rucio.client.rseclient import RSEClient
return RSEClient()
@pytest.fixture(scope='module')
def scope_client():
from rucio.client.scopeclient import ScopeClient
return ScopeClient()
@pytest.fixture(scope='module')
def dirac_client():
from rucio.client.diracclient import DiracClient
return DiracClient()
@pytest.fixture
def rest_client():
from rucio.tests.common import print_response
from flask.testing import FlaskClient
from rucio.web.rest.flaskapi.v1.main import application
class WrappedFlaskClient(FlaskClient):
def __init__(self, *args, **kwargs):
super(WrappedFlaskClient, self).__init__(*args, **kwargs)
def open(self, path='/', *args, **kwargs):
print(kwargs.get('method', 'GET'), path)
response = super(WrappedFlaskClient, self).open(path, *args, **kwargs)
try:
print_response(response)
except Exception:
traceback.print_exc()
return response
_testing = application.testing
application.testing = True
application.test_client_class = WrappedFlaskClient
with application.test_client() as client:
yield client
application.test_client_class = None
application.testing = _testing
@pytest.fixture
def auth_token(rest_client, long_vo):
from rucio.tests.common import vohdr, headers, loginhdr
auth_response = rest_client.get('/auth/userpass', headers=headers(loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))
assert auth_response.status_code == 200
token = auth_response.headers.get('X-Rucio-Auth-Token')
assert token
return str(token)
@pytest.fixture(scope='module')
def mock_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('mock', vo=vo)
@pytest.fixture(scope='module')
def test_scope(vo):
from rucio.common.types import InternalScope
return InternalScope('test', vo=vo)
@pytest.fixture(scope='module')
def root_account(vo):
from rucio.common.types import InternalAccount
return InternalAccount('root', vo=vo)
@pytest.fixture(scope='module')
def jdoe_account(vo):
from rucio.common.types import InternalAccount
return InternalAccount('jdoe', vo=vo)
@pytest.fixture
def random_account(vo):
import random
import string
from rucio.common.types import InternalAccount
from rucio.core.account import add_account, del_account
from rucio.db.sqla import models
from rucio.db.sqla.constants import AccountType
from rucio.tests.common_server import cleanup_db_deps
account = InternalAccount(''.join(random.choice(string.ascii_uppercase) for _ in range(10)), vo=vo)
add_account(account=account, type_=AccountType.USER, email=f'{account.external}@email.com')
yield account
cleanup_db_deps(model=models.Account, select_rows_stmt=models.Account.account == account)
del_account(account)
@pytest.fixture(scope="module")
def containerized_rses(rucio_client):
"""
Detects if containerized rses for xrootd & ssh are available in the testing environment.
:return: A list of (rse_name, rse_id) tuples.
"""
from rucio.common.exception import InvalidRSEExpression
rses = []
try:
xrd_rses = [x['rse'] for x in rucio_client.list_rses(rse_expression='test_container_xrd=True')]
xrd_rses = [rucio_client.get_rse(rse) for rse in xrd_rses]
xrd_containerized_rses = [(rse_obj['rse'], rse_obj['id']) for rse_obj in xrd_rses if "xrd" in rse_obj['rse'].lower()]
xrd_containerized_rses.sort()
rses.extend(xrd_containerized_rses)
ssh_rses = [x['rse'] for x in rucio_client.list_rses(rse_expression='test_container_ssh=True')]
ssh_rses = [rucio_client.get_rse(rse) for rse in ssh_rses]
ssh_containerized_rses = [(rse_obj['rse'], rse_obj['id']) for rse_obj in ssh_rses if "ssh" in rse_obj['rse'].lower()]
ssh_containerized_rses.sort()
rses.extend(ssh_containerized_rses)
except InvalidRSEExpression as invalid_rse_expression:
print("{ex}. Note that containerized RSEs will not be available in non-containerized test environments"
.format(ex=invalid_rse_expression))
traceback.print_exc()
return rses
@pytest.fixture
def rse_factory(request, vo, function_scope_prefix):
from .temp_factories import TemporaryRSEFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix, db_session=session) as factory:
yield factory
@pytest.fixture(scope="class")
def rse_factory_unittest(request, vo, class_scope_prefix):
"""
unittest classes can get access to rse_factory fixture via this fixture
"""
from .temp_factories import TemporaryRSEFactory
with TemporaryRSEFactory(vo=vo, name_prefix=class_scope_prefix) as factory:
request.cls.rse_factory = factory
yield factory
@pytest.fixture
def did_factory(request, vo, mock_scope, function_scope_prefix, file_factory, root_account):
from .temp_factories import TemporaryDidFactory
session = None
if 'db_session' in request.fixturenames:
session = request.getfixturevalue('db_session')
with TemporaryDidFactory(vo=vo, default_scope=mock_scope, name_prefix=function_scope_prefix, file_factory=file_factory,
default_account=root_account, db_session=session) as factory:
yield factory
@pytest.fixture
def file_factory(tmp_path_factory):
from .temp_factories import TemporaryFileFactory
with TemporaryFileFactory(pytest_path_factory=tmp_path_factory) as factory:
yield factory
@pytest.fixture
def scope_factory():
from rucio.common.utils import generate_uuid
from rucio.core.scope import add_scope
from rucio.common.types import InternalAccount, InternalScope
def create_scopes(vos, account_name=None):
scope_uuid = str(generate_uuid()).lower()[:16]
scope_name = 'shr_%s' % scope_uuid
created_scopes = []
for vo in vos:
scope = InternalScope(scope_name, vo=vo)
add_scope(scope, InternalAccount(account_name if account_name else 'root', vo=vo))
created_scopes.append(scope)
return scope_name, created_scopes
return create_scopes
class _TagFactory:
def __init__(self, prefix):
self.prefix = prefix
self.index = 0
def new_tag(self):
self.index += 1
return f'{self.prefix}-{self.index}'
@pytest.fixture
def tag_factory(function_scope_prefix):
return _TagFactory(prefix=f'{function_scope_prefix}{"".join(choice(ascii_uppercase) for _ in range(6))}'.replace('_', '-'))
@pytest.fixture(scope='class')
def tag_factory_class(class_scope_prefix):
return _TagFactory(prefix=f'{class_scope_prefix}{"".join(choice(ascii_uppercase) for _ in range(6))}'.replace('_', '-'))
@pytest.fixture
def db_session():
from rucio.db.sqla import session
db_session = session.get_session()
yield db_session
db_session.commit()
db_session.close()
def __get_fixture_param(request):
fixture_param = getattr(request, "param", None)
if not fixture_param:
# Parametrize support is incomplete for legacy unittest test cases
# Manually retrieve the parameters from the list of marks:
mark = next(iter(filter(lambda m: m.name == 'parametrize', request.instance.pytestmark)), None)
if mark:
fixture_param = mark.args[1][0]
return fixture_param
def __create_in_memory_db_table(name, *columns, **kwargs):
"""
Create an in-memory temporary table using the sqlite memory driver.
Make sqlalchemy aware of that table by registering it via a
declarative base.
"""
import datetime
from sqlalchemy import Column, DateTime, CheckConstraint
from sqlalchemy.pool import StaticPool
from sqlalchemy.schema import Table
from sqlalchemy.orm import registry
from rucio.db.sqla.models import ModelBase
from rucio.db.sqla.session import get_maker, create_engine
engine = create_engine('sqlite://', connect_args={'check_same_thread': False}, poolclass=StaticPool)
# Create a class which inherits from ModelBase. This will allow us to use the rucio-specific methods like .save()
DeclarativeObj = type('DeclarativeObj{}'.format(name), (ModelBase,), {})
# Create a new declarative base and map the previously created object into the base
mapper_registry = registry()
InMemoryBase = mapper_registry.generate_base(name='InMemoryBase{}'.format(name))
table_args = tuple(columns) + tuple(kwargs.get('table_args', ())) + (
Column("created_at", DateTime, default=datetime.datetime.utcnow),
Column("updated_at", DateTime, default=datetime.datetime.utcnow, onupdate=datetime.datetime.utcnow),
CheckConstraint('CREATED_AT IS NOT NULL', name=name.upper() + '_CREATED_NN'),
CheckConstraint('UPDATED_AT IS NOT NULL', name=name.upper() + '_UPDATED_NN'),
)
table = Table(
name,
InMemoryBase.metadata,
*table_args
)
mapper_registry.map_imperatively(DeclarativeObj, table)
# Performa actual creation of the in-memory table
InMemoryBase.metadata.create_all(engine)
# Register the new table with the associated engine into the sqlalchemy sessionmaker
# In theory, this code must be protected by rucio.db.scla.session._LOCK, but this code will be executed
# during test case initialization, so there is no risk here to have concurrent calls from within the
# same process
senssionmaker = get_maker()
senssionmaker.kw.setdefault('binds', {}).update({DeclarativeObj: engine})
return DeclarativeObj
@pytest.fixture
def message_mock():
"""
Fixture which overrides the Message table with a private instance
"""
from unittest import mock
from sqlalchemy import Column
from rucio.common.utils import generate_uuid
from rucio.db.sqla.models import String, PrimaryKeyConstraint, CheckConstraint, Text, Index, GUID
InMemoryMessage = __create_in_memory_db_table(
'message_' + generate_uuid(),
Column('id', GUID(), default=generate_uuid),
Column('event_type', String(256)),
Column('payload', String(4000)),
Column('payload_nolimit', Text),
Column('services', String(256)),
table_args=(PrimaryKeyConstraint('id', name='MESSAGES_ID_PK'),
CheckConstraint('EVENT_TYPE IS NOT NULL', name='MESSAGES_EVENT_TYPE_NN'),
CheckConstraint('PAYLOAD IS NOT NULL', name='MESSAGES_PAYLOAD_NN'),
Index('MESSAGES_SERVICES_IDX', 'services', 'event_type'))
)
with mock.patch('rucio.core.message.Message', new=InMemoryMessage):
yield
@pytest.fixture
def core_config_mock(request):
"""
Fixture to allow having per-test core.config tables without affecting the other parallel tests.
This override works only in tests which use core function calls directly, not in the ones working
via the API, because the normal config table is not touched and the rucio instance answering API
calls is not aware of this mock.
This fixture acts by creating a new copy of the "config" sql table using the :memory: sqlite engine.
Accesses to the "models.Config" table are then redirected to this temporary table via mock.patch().
"""
from unittest import mock
from sqlalchemy import Column
from rucio.common.utils import generate_uuid
from rucio.db.sqla.models import String, PrimaryKeyConstraint
from rucio.db.sqla.session import get_session
# Get the fixture parameters
table_content = []
params = __get_fixture_param(request)
if params:
table_content = params.get("table_content", table_content)
InMemoryConfig = __create_in_memory_db_table(
'configs_' + generate_uuid(),
Column('section', String(128)),
Column('opt', String(128)),
Column('value', String(4000)),
table_args=(PrimaryKeyConstraint('section', 'opt', name='CONFIGS_PK'),),
)
# Fill the table with the requested mock data
session = get_session()()
for section, option, value in (table_content or []):
InMemoryConfig(section=section, opt=option, value=value).save(flush=True, session=session)
session.commit()
with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):
yield
@pytest.fixture
def file_config_mock(request):
"""
Fixture which allows to have an isolated in-memory configuration file instance which
is not persisted after exiting the fixture.
This override works only in tests which use config calls directly, not in the ones working
via the API, as the server config is not changed.
"""
from unittest import mock
from rucio.common.config import Config, config_set, config_has_section, config_add_section
# Get the fixture parameters
overrides = []
params = __get_fixture_param(request)
if params:
overrides = params.get("overrides", overrides)
parser = Config().parser
with mock.patch('rucio.common.config.get_config', side_effect=lambda: parser):
for section, option, value in (overrides or []):
if not config_has_section(section):
config_add_section(section)
config_set(section, option, value)
yield
@pytest.fixture
def caches_mock(request):
"""
Fixture which overrides the different internal caches with in-memory ones for the duration
of a particular test.
This override works only in tests which use core function calls directly, not in the ones
working via API.
The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.
"""
from unittest import mock
from contextlib import ExitStack
from dogpile.cache import make_region
caches_to_mock = []
expiration_time = 600
params = __get_fixture_param(request)
if params:
caches_to_mock = params.get("caches_to_mock", caches_to_mock)
expiration_time = params.get("expiration_time", expiration_time)
with ExitStack() as stack:
mocked_caches = []
for module in caches_to_mock:
region = make_region().configure('dogpile.cache.memory', expiration_time=expiration_time)
stack.enter_context(mock.patch(module, new=region))
mocked_caches.append(region)
yield mocked_caches
@pytest.fixture
def metrics_mock():
"""
Overrides the prometheus metric registry and allows to verify if the desired
prometheus metrics were correctly recorded.
"""
from unittest import mock
from prometheus_client import CollectorRegistry, values
with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()) as registry, \
mock.patch('rucio.core.monitor.COUNTERS', new={}), \
mock.patch('rucio.core.monitor.GAUGES', new={}), \
mock.patch('rucio.core.monitor.TIMINGS', new={}), \
mock.patch('prometheus_client.values.ValueClass', new=values.MutexValue):
yield registry
|
flexible
|
{
"blob_id": "eb1737ac671129ed3459ce4feacb81d414eef371",
"index": 5667,
"step-1": "<mask token>\n\n\n@pytest.fixture(scope='module')\ndef module_scope_prefix(request, session_scope_prefix):\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest module\n Relies on pytest's builtin fixture \"request\"\n https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request\n \"\"\"\n return session_scope_prefix + _del_test_prefix(request.module.__name__.\n split('.')[-1]) + '-'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='session')\ndef long_vo():\n from rucio.tests.common import get_long_vo\n return get_long_vo()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rucio_client():\n from rucio.client import Client\n return Client()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rse_client():\n from rucio.client.rseclient import RSEClient\n return RSEClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef dirac_client():\n from rucio.client.diracclient import DiracClient\n return DiracClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef mock_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('mock', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef test_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('test', vo=vo)\n\n\n<mask token>\n\n\n@pytest.fixture\ndef rse_factory(request, vo, function_scope_prefix):\n from .temp_factories import TemporaryRSEFactory\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,\n db_session=session) as factory:\n yield factory\n\n\n<mask token>\n\n\n@pytest.fixture\ndef scope_factory():\n from rucio.common.utils import generate_uuid\n from rucio.core.scope import add_scope\n from rucio.common.types import InternalAccount, InternalScope\n\n def create_scopes(vos, account_name=None):\n scope_uuid = str(generate_uuid()).lower()[:16]\n scope_name = 'shr_%s' % scope_uuid\n created_scopes = []\n for vo in vos:\n scope = InternalScope(scope_name, vo=vo)\n add_scope(scope, InternalAccount(account_name if account_name else\n 'root', vo=vo))\n created_scopes.append(scope)\n return scope_name, created_scopes\n return create_scopes\n\n\nclass _TagFactory:\n\n def __init__(self, prefix):\n self.prefix = prefix\n self.index = 0\n\n def new_tag(self):\n self.index += 1\n return f'{self.prefix}-{self.index}'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='class')\ndef tag_factory_class(class_scope_prefix):\n return _TagFactory(prefix=\n f\"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}\"\n .replace('_', '-'))\n\n\n<mask token>\n\n\ndef __get_fixture_param(request):\n fixture_param = getattr(request, 'param', None)\n if not fixture_param:\n mark = next(iter(filter(lambda m: m.name == 'parametrize', request.\n instance.pytestmark)), None)\n if mark:\n fixture_param = mark.args[1][0]\n return fixture_param\n\n\n<mask token>\n\n\n@pytest.fixture\ndef core_config_mock(request):\n \"\"\"\n Fixture to allow having per-test core.config tables without affecting the other parallel tests.\n\n This override works only in tests which use core function calls directly, not in the ones working\n via the API, because the normal config table is not touched and the rucio instance answering API\n calls is not aware of this mock.\n\n This fixture acts by creating a new copy of the \"config\" sql table using the :memory: sqlite engine.\n Accesses to the \"models.Config\" table are then redirected to this temporary table via mock.patch().\n \"\"\"\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint\n from rucio.db.sqla.session import get_session\n table_content = []\n params = __get_fixture_param(request)\n if params:\n table_content = params.get('table_content', table_content)\n InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid\n (), Column('section', String(128)), Column('opt', String(128)),\n Column('value', String(4000)), table_args=(PrimaryKeyConstraint(\n 'section', 'opt', name='CONFIGS_PK'),))\n session = get_session()()\n for section, option, value in (table_content or []):\n InMemoryConfig(section=section, opt=option, value=value).save(flush\n =True, session=session)\n session.commit()\n with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):\n yield\n\n\n<mask token>\n\n\n@pytest.fixture\ndef caches_mock(request):\n \"\"\"\n Fixture which overrides the different internal caches with in-memory ones for the duration\n of a particular test.\n\n This override works only in tests which use core function calls directly, not in the ones\n working via API.\n\n The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.\n \"\"\"\n from unittest import mock\n from contextlib import ExitStack\n from dogpile.cache import make_region\n caches_to_mock = []\n expiration_time = 600\n params = __get_fixture_param(request)\n if params:\n caches_to_mock = params.get('caches_to_mock', caches_to_mock)\n expiration_time = params.get('expiration_time', expiration_time)\n with ExitStack() as stack:\n mocked_caches = []\n for module in caches_to_mock:\n region = make_region().configure('dogpile.cache.memory',\n expiration_time=expiration_time)\n stack.enter_context(mock.patch(module, new=region))\n mocked_caches.append(region)\n yield mocked_caches\n\n\n@pytest.fixture\ndef metrics_mock():\n \"\"\"\n Overrides the prometheus metric registry and allows to verify if the desired\n prometheus metrics were correctly recorded.\n \"\"\"\n from unittest import mock\n from prometheus_client import CollectorRegistry, values\n with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()\n ) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}\n ), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(\n 'rucio.core.monitor.TIMINGS', new={}), mock.patch(\n 'prometheus_client.values.ValueClass', new=values.MutexValue):\n yield registry\n",
"step-2": "<mask token>\n\n\n@pytest.fixture(scope='module')\ndef module_scope_prefix(request, session_scope_prefix):\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest module\n Relies on pytest's builtin fixture \"request\"\n https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request\n \"\"\"\n return session_scope_prefix + _del_test_prefix(request.module.__name__.\n split('.')[-1]) + '-'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='session')\ndef long_vo():\n from rucio.tests.common import get_long_vo\n return get_long_vo()\n\n\n@pytest.fixture(scope='module')\ndef account_client():\n from rucio.client.accountclient import AccountClient\n return AccountClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rucio_client():\n from rucio.client import Client\n return Client()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rse_client():\n from rucio.client.rseclient import RSEClient\n return RSEClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef dirac_client():\n from rucio.client.diracclient import DiracClient\n return DiracClient()\n\n\n<mask token>\n\n\n@pytest.fixture\ndef auth_token(rest_client, long_vo):\n from rucio.tests.common import vohdr, headers, loginhdr\n auth_response = rest_client.get('/auth/userpass', headers=headers(\n loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))\n assert auth_response.status_code == 200\n token = auth_response.headers.get('X-Rucio-Auth-Token')\n assert token\n return str(token)\n\n\n@pytest.fixture(scope='module')\ndef mock_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('mock', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef test_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('test', vo=vo)\n\n\n<mask token>\n\n\n@pytest.fixture\ndef rse_factory(request, vo, function_scope_prefix):\n from .temp_factories import TemporaryRSEFactory\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,\n db_session=session) as factory:\n yield factory\n\n\n<mask token>\n\n\n@pytest.fixture\ndef scope_factory():\n from rucio.common.utils import generate_uuid\n from rucio.core.scope import add_scope\n from rucio.common.types import InternalAccount, InternalScope\n\n def create_scopes(vos, account_name=None):\n scope_uuid = str(generate_uuid()).lower()[:16]\n scope_name = 'shr_%s' % scope_uuid\n created_scopes = []\n for vo in vos:\n scope = InternalScope(scope_name, vo=vo)\n add_scope(scope, InternalAccount(account_name if account_name else\n 'root', vo=vo))\n created_scopes.append(scope)\n return scope_name, created_scopes\n return create_scopes\n\n\nclass _TagFactory:\n\n def __init__(self, prefix):\n self.prefix = prefix\n self.index = 0\n\n def new_tag(self):\n self.index += 1\n return f'{self.prefix}-{self.index}'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='class')\ndef tag_factory_class(class_scope_prefix):\n return _TagFactory(prefix=\n f\"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}\"\n .replace('_', '-'))\n\n\n<mask token>\n\n\ndef __get_fixture_param(request):\n fixture_param = getattr(request, 'param', None)\n if not fixture_param:\n mark = next(iter(filter(lambda m: m.name == 'parametrize', request.\n instance.pytestmark)), None)\n if mark:\n fixture_param = mark.args[1][0]\n return fixture_param\n\n\n<mask token>\n\n\n@pytest.fixture\ndef core_config_mock(request):\n \"\"\"\n Fixture to allow having per-test core.config tables without affecting the other parallel tests.\n\n This override works only in tests which use core function calls directly, not in the ones working\n via the API, because the normal config table is not touched and the rucio instance answering API\n calls is not aware of this mock.\n\n This fixture acts by creating a new copy of the \"config\" sql table using the :memory: sqlite engine.\n Accesses to the \"models.Config\" table are then redirected to this temporary table via mock.patch().\n \"\"\"\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint\n from rucio.db.sqla.session import get_session\n table_content = []\n params = __get_fixture_param(request)\n if params:\n table_content = params.get('table_content', table_content)\n InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid\n (), Column('section', String(128)), Column('opt', String(128)),\n Column('value', String(4000)), table_args=(PrimaryKeyConstraint(\n 'section', 'opt', name='CONFIGS_PK'),))\n session = get_session()()\n for section, option, value in (table_content or []):\n InMemoryConfig(section=section, opt=option, value=value).save(flush\n =True, session=session)\n session.commit()\n with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):\n yield\n\n\n@pytest.fixture\ndef file_config_mock(request):\n \"\"\"\n Fixture which allows to have an isolated in-memory configuration file instance which\n is not persisted after exiting the fixture.\n\n This override works only in tests which use config calls directly, not in the ones working\n via the API, as the server config is not changed.\n \"\"\"\n from unittest import mock\n from rucio.common.config import Config, config_set, config_has_section, config_add_section\n overrides = []\n params = __get_fixture_param(request)\n if params:\n overrides = params.get('overrides', overrides)\n parser = Config().parser\n with mock.patch('rucio.common.config.get_config', side_effect=lambda :\n parser):\n for section, option, value in (overrides or []):\n if not config_has_section(section):\n config_add_section(section)\n config_set(section, option, value)\n yield\n\n\n@pytest.fixture\ndef caches_mock(request):\n \"\"\"\n Fixture which overrides the different internal caches with in-memory ones for the duration\n of a particular test.\n\n This override works only in tests which use core function calls directly, not in the ones\n working via API.\n\n The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.\n \"\"\"\n from unittest import mock\n from contextlib import ExitStack\n from dogpile.cache import make_region\n caches_to_mock = []\n expiration_time = 600\n params = __get_fixture_param(request)\n if params:\n caches_to_mock = params.get('caches_to_mock', caches_to_mock)\n expiration_time = params.get('expiration_time', expiration_time)\n with ExitStack() as stack:\n mocked_caches = []\n for module in caches_to_mock:\n region = make_region().configure('dogpile.cache.memory',\n expiration_time=expiration_time)\n stack.enter_context(mock.patch(module, new=region))\n mocked_caches.append(region)\n yield mocked_caches\n\n\n@pytest.fixture\ndef metrics_mock():\n \"\"\"\n Overrides the prometheus metric registry and allows to verify if the desired\n prometheus metrics were correctly recorded.\n \"\"\"\n from unittest import mock\n from prometheus_client import CollectorRegistry, values\n with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()\n ) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}\n ), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(\n 'rucio.core.monitor.TIMINGS', new={}), mock.patch(\n 'prometheus_client.values.ValueClass', new=values.MutexValue):\n yield registry\n",
"step-3": "<mask token>\n\n\n@pytest.fixture(scope='session')\ndef session_scope_prefix():\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest session\n \"\"\"\n return ''.join(choice(ascii_uppercase) for _ in range(6)) + '-'\n\n\n@pytest.fixture(scope='module')\ndef module_scope_prefix(request, session_scope_prefix):\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest module\n Relies on pytest's builtin fixture \"request\"\n https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request\n \"\"\"\n return session_scope_prefix + _del_test_prefix(request.module.__name__.\n split('.')[-1]) + '-'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='session')\ndef long_vo():\n from rucio.tests.common import get_long_vo\n return get_long_vo()\n\n\n@pytest.fixture(scope='module')\ndef account_client():\n from rucio.client.accountclient import AccountClient\n return AccountClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rucio_client():\n from rucio.client import Client\n return Client()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rse_client():\n from rucio.client.rseclient import RSEClient\n return RSEClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef dirac_client():\n from rucio.client.diracclient import DiracClient\n return DiracClient()\n\n\n<mask token>\n\n\n@pytest.fixture\ndef auth_token(rest_client, long_vo):\n from rucio.tests.common import vohdr, headers, loginhdr\n auth_response = rest_client.get('/auth/userpass', headers=headers(\n loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))\n assert auth_response.status_code == 200\n token = auth_response.headers.get('X-Rucio-Auth-Token')\n assert token\n return str(token)\n\n\n@pytest.fixture(scope='module')\ndef mock_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('mock', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef test_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('test', vo=vo)\n\n\n<mask token>\n\n\n@pytest.fixture\ndef rse_factory(request, vo, function_scope_prefix):\n from .temp_factories import TemporaryRSEFactory\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,\n db_session=session) as factory:\n yield factory\n\n\n<mask token>\n\n\n@pytest.fixture\ndef scope_factory():\n from rucio.common.utils import generate_uuid\n from rucio.core.scope import add_scope\n from rucio.common.types import InternalAccount, InternalScope\n\n def create_scopes(vos, account_name=None):\n scope_uuid = str(generate_uuid()).lower()[:16]\n scope_name = 'shr_%s' % scope_uuid\n created_scopes = []\n for vo in vos:\n scope = InternalScope(scope_name, vo=vo)\n add_scope(scope, InternalAccount(account_name if account_name else\n 'root', vo=vo))\n created_scopes.append(scope)\n return scope_name, created_scopes\n return create_scopes\n\n\nclass _TagFactory:\n\n def __init__(self, prefix):\n self.prefix = prefix\n self.index = 0\n\n def new_tag(self):\n self.index += 1\n return f'{self.prefix}-{self.index}'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='class')\ndef tag_factory_class(class_scope_prefix):\n return _TagFactory(prefix=\n f\"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}\"\n .replace('_', '-'))\n\n\n<mask token>\n\n\ndef __get_fixture_param(request):\n fixture_param = getattr(request, 'param', None)\n if not fixture_param:\n mark = next(iter(filter(lambda m: m.name == 'parametrize', request.\n instance.pytestmark)), None)\n if mark:\n fixture_param = mark.args[1][0]\n return fixture_param\n\n\n<mask token>\n\n\n@pytest.fixture\ndef core_config_mock(request):\n \"\"\"\n Fixture to allow having per-test core.config tables without affecting the other parallel tests.\n\n This override works only in tests which use core function calls directly, not in the ones working\n via the API, because the normal config table is not touched and the rucio instance answering API\n calls is not aware of this mock.\n\n This fixture acts by creating a new copy of the \"config\" sql table using the :memory: sqlite engine.\n Accesses to the \"models.Config\" table are then redirected to this temporary table via mock.patch().\n \"\"\"\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint\n from rucio.db.sqla.session import get_session\n table_content = []\n params = __get_fixture_param(request)\n if params:\n table_content = params.get('table_content', table_content)\n InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid\n (), Column('section', String(128)), Column('opt', String(128)),\n Column('value', String(4000)), table_args=(PrimaryKeyConstraint(\n 'section', 'opt', name='CONFIGS_PK'),))\n session = get_session()()\n for section, option, value in (table_content or []):\n InMemoryConfig(section=section, opt=option, value=value).save(flush\n =True, session=session)\n session.commit()\n with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):\n yield\n\n\n@pytest.fixture\ndef file_config_mock(request):\n \"\"\"\n Fixture which allows to have an isolated in-memory configuration file instance which\n is not persisted after exiting the fixture.\n\n This override works only in tests which use config calls directly, not in the ones working\n via the API, as the server config is not changed.\n \"\"\"\n from unittest import mock\n from rucio.common.config import Config, config_set, config_has_section, config_add_section\n overrides = []\n params = __get_fixture_param(request)\n if params:\n overrides = params.get('overrides', overrides)\n parser = Config().parser\n with mock.patch('rucio.common.config.get_config', side_effect=lambda :\n parser):\n for section, option, value in (overrides or []):\n if not config_has_section(section):\n config_add_section(section)\n config_set(section, option, value)\n yield\n\n\n@pytest.fixture\ndef caches_mock(request):\n \"\"\"\n Fixture which overrides the different internal caches with in-memory ones for the duration\n of a particular test.\n\n This override works only in tests which use core function calls directly, not in the ones\n working via API.\n\n The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.\n \"\"\"\n from unittest import mock\n from contextlib import ExitStack\n from dogpile.cache import make_region\n caches_to_mock = []\n expiration_time = 600\n params = __get_fixture_param(request)\n if params:\n caches_to_mock = params.get('caches_to_mock', caches_to_mock)\n expiration_time = params.get('expiration_time', expiration_time)\n with ExitStack() as stack:\n mocked_caches = []\n for module in caches_to_mock:\n region = make_region().configure('dogpile.cache.memory',\n expiration_time=expiration_time)\n stack.enter_context(mock.patch(module, new=region))\n mocked_caches.append(region)\n yield mocked_caches\n\n\n@pytest.fixture\ndef metrics_mock():\n \"\"\"\n Overrides the prometheus metric registry and allows to verify if the desired\n prometheus metrics were correctly recorded.\n \"\"\"\n from unittest import mock\n from prometheus_client import CollectorRegistry, values\n with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()\n ) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}\n ), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(\n 'rucio.core.monitor.TIMINGS', new={}), mock.patch(\n 'prometheus_client.values.ValueClass', new=values.MutexValue):\n yield registry\n",
"step-4": "<mask token>\n\n\n@pytest.fixture(scope='session')\ndef session_scope_prefix():\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest session\n \"\"\"\n return ''.join(choice(ascii_uppercase) for _ in range(6)) + '-'\n\n\n@pytest.fixture(scope='module')\ndef module_scope_prefix(request, session_scope_prefix):\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest module\n Relies on pytest's builtin fixture \"request\"\n https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request\n \"\"\"\n return session_scope_prefix + _del_test_prefix(request.module.__name__.\n split('.')[-1]) + '-'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='session')\ndef long_vo():\n from rucio.tests.common import get_long_vo\n return get_long_vo()\n\n\n@pytest.fixture(scope='module')\ndef account_client():\n from rucio.client.accountclient import AccountClient\n return AccountClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rucio_client():\n from rucio.client import Client\n return Client()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef rse_client():\n from rucio.client.rseclient import RSEClient\n return RSEClient()\n\n\n<mask token>\n\n\n@pytest.fixture(scope='module')\ndef dirac_client():\n from rucio.client.diracclient import DiracClient\n return DiracClient()\n\n\n@pytest.fixture\ndef rest_client():\n from rucio.tests.common import print_response\n from flask.testing import FlaskClient\n from rucio.web.rest.flaskapi.v1.main import application\n\n\n class WrappedFlaskClient(FlaskClient):\n\n def __init__(self, *args, **kwargs):\n super(WrappedFlaskClient, self).__init__(*args, **kwargs)\n\n def open(self, path='/', *args, **kwargs):\n print(kwargs.get('method', 'GET'), path)\n response = super(WrappedFlaskClient, self).open(path, *args, **\n kwargs)\n try:\n print_response(response)\n except Exception:\n traceback.print_exc()\n return response\n _testing = application.testing\n application.testing = True\n application.test_client_class = WrappedFlaskClient\n with application.test_client() as client:\n yield client\n application.test_client_class = None\n application.testing = _testing\n\n\n@pytest.fixture\ndef auth_token(rest_client, long_vo):\n from rucio.tests.common import vohdr, headers, loginhdr\n auth_response = rest_client.get('/auth/userpass', headers=headers(\n loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))\n assert auth_response.status_code == 200\n token = auth_response.headers.get('X-Rucio-Auth-Token')\n assert token\n return str(token)\n\n\n@pytest.fixture(scope='module')\ndef mock_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('mock', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef test_scope(vo):\n from rucio.common.types import InternalScope\n return InternalScope('test', vo=vo)\n\n\n<mask token>\n\n\n@pytest.fixture\ndef rse_factory(request, vo, function_scope_prefix):\n from .temp_factories import TemporaryRSEFactory\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix,\n db_session=session) as factory:\n yield factory\n\n\n<mask token>\n\n\n@pytest.fixture\ndef did_factory(request, vo, mock_scope, function_scope_prefix,\n file_factory, root_account):\n from .temp_factories import TemporaryDidFactory\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n with TemporaryDidFactory(vo=vo, default_scope=mock_scope, name_prefix=\n function_scope_prefix, file_factory=file_factory, default_account=\n root_account, db_session=session) as factory:\n yield factory\n\n\n<mask token>\n\n\n@pytest.fixture\ndef scope_factory():\n from rucio.common.utils import generate_uuid\n from rucio.core.scope import add_scope\n from rucio.common.types import InternalAccount, InternalScope\n\n def create_scopes(vos, account_name=None):\n scope_uuid = str(generate_uuid()).lower()[:16]\n scope_name = 'shr_%s' % scope_uuid\n created_scopes = []\n for vo in vos:\n scope = InternalScope(scope_name, vo=vo)\n add_scope(scope, InternalAccount(account_name if account_name else\n 'root', vo=vo))\n created_scopes.append(scope)\n return scope_name, created_scopes\n return create_scopes\n\n\nclass _TagFactory:\n\n def __init__(self, prefix):\n self.prefix = prefix\n self.index = 0\n\n def new_tag(self):\n self.index += 1\n return f'{self.prefix}-{self.index}'\n\n\n<mask token>\n\n\n@pytest.fixture(scope='class')\ndef tag_factory_class(class_scope_prefix):\n return _TagFactory(prefix=\n f\"{class_scope_prefix}{''.join(choice(ascii_uppercase) for _ in range(6))}\"\n .replace('_', '-'))\n\n\n<mask token>\n\n\ndef __get_fixture_param(request):\n fixture_param = getattr(request, 'param', None)\n if not fixture_param:\n mark = next(iter(filter(lambda m: m.name == 'parametrize', request.\n instance.pytestmark)), None)\n if mark:\n fixture_param = mark.args[1][0]\n return fixture_param\n\n\n<mask token>\n\n\n@pytest.fixture\ndef core_config_mock(request):\n \"\"\"\n Fixture to allow having per-test core.config tables without affecting the other parallel tests.\n\n This override works only in tests which use core function calls directly, not in the ones working\n via the API, because the normal config table is not touched and the rucio instance answering API\n calls is not aware of this mock.\n\n This fixture acts by creating a new copy of the \"config\" sql table using the :memory: sqlite engine.\n Accesses to the \"models.Config\" table are then redirected to this temporary table via mock.patch().\n \"\"\"\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint\n from rucio.db.sqla.session import get_session\n table_content = []\n params = __get_fixture_param(request)\n if params:\n table_content = params.get('table_content', table_content)\n InMemoryConfig = __create_in_memory_db_table('configs_' + generate_uuid\n (), Column('section', String(128)), Column('opt', String(128)),\n Column('value', String(4000)), table_args=(PrimaryKeyConstraint(\n 'section', 'opt', name='CONFIGS_PK'),))\n session = get_session()()\n for section, option, value in (table_content or []):\n InMemoryConfig(section=section, opt=option, value=value).save(flush\n =True, session=session)\n session.commit()\n with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):\n yield\n\n\n@pytest.fixture\ndef file_config_mock(request):\n \"\"\"\n Fixture which allows to have an isolated in-memory configuration file instance which\n is not persisted after exiting the fixture.\n\n This override works only in tests which use config calls directly, not in the ones working\n via the API, as the server config is not changed.\n \"\"\"\n from unittest import mock\n from rucio.common.config import Config, config_set, config_has_section, config_add_section\n overrides = []\n params = __get_fixture_param(request)\n if params:\n overrides = params.get('overrides', overrides)\n parser = Config().parser\n with mock.patch('rucio.common.config.get_config', side_effect=lambda :\n parser):\n for section, option, value in (overrides or []):\n if not config_has_section(section):\n config_add_section(section)\n config_set(section, option, value)\n yield\n\n\n@pytest.fixture\ndef caches_mock(request):\n \"\"\"\n Fixture which overrides the different internal caches with in-memory ones for the duration\n of a particular test.\n\n This override works only in tests which use core function calls directly, not in the ones\n working via API.\n\n The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.\n \"\"\"\n from unittest import mock\n from contextlib import ExitStack\n from dogpile.cache import make_region\n caches_to_mock = []\n expiration_time = 600\n params = __get_fixture_param(request)\n if params:\n caches_to_mock = params.get('caches_to_mock', caches_to_mock)\n expiration_time = params.get('expiration_time', expiration_time)\n with ExitStack() as stack:\n mocked_caches = []\n for module in caches_to_mock:\n region = make_region().configure('dogpile.cache.memory',\n expiration_time=expiration_time)\n stack.enter_context(mock.patch(module, new=region))\n mocked_caches.append(region)\n yield mocked_caches\n\n\n@pytest.fixture\ndef metrics_mock():\n \"\"\"\n Overrides the prometheus metric registry and allows to verify if the desired\n prometheus metrics were correctly recorded.\n \"\"\"\n from unittest import mock\n from prometheus_client import CollectorRegistry, values\n with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()\n ) as registry, mock.patch('rucio.core.monitor.COUNTERS', new={}\n ), mock.patch('rucio.core.monitor.GAUGES', new={}), mock.patch(\n 'rucio.core.monitor.TIMINGS', new={}), mock.patch(\n 'prometheus_client.values.ValueClass', new=values.MutexValue):\n yield registry\n",
"step-5": "# -*- coding: utf-8 -*-\n# Copyright European Organization for Nuclear Research (CERN) since 2012\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\nimport traceback\nimport re\nimport functools\nfrom os import environ\nfrom random import choice\nfrom string import ascii_uppercase\n\nimport pytest\n\n\n_del_test_prefix = functools.partial(re.compile(r'^[Tt][Ee][Ss][Tt]_?').sub, '')\n# local imports in the fixtures to make this file loadable in e.g. client tests\n\npytest_plugins = ('tests.ruciopytest.artifacts_plugin', )\n\n\ndef pytest_configure(config):\n config.addinivalue_line('markers', 'dirty: marks test as dirty, i.e. tests are leaving structures behind')\n config.addinivalue_line('markers', 'noparallel(reason, groups): marks test being unable to run in parallel to other tests' )\n\n if config.pluginmanager.hasplugin(\"xdist\"):\n from .ruciopytest import xdist_noparallel_scheduler\n config.pluginmanager.register(xdist_noparallel_scheduler)\n\n\ndef pytest_make_parametrize_id(config, val, argname):\n if argname == 'file_config_mock':\n cfg = {}\n for section, option, value in val['overrides']:\n cfg.setdefault(section, {})[option] = value\n return argname + str(cfg)\n if argname == 'core_config_mock':\n cfg = {}\n for section, option, value in val['table_content']:\n cfg.setdefault(section, {})[option] = value\n return argname + str(cfg)\n # return None to let pytest handle the formatting\n return None\n\n\n@pytest.fixture(scope='session')\ndef session_scope_prefix():\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest session\n \"\"\"\n return ''.join(choice(ascii_uppercase) for _ in range(6)) + '-'\n\n\n@pytest.fixture(scope='module')\ndef module_scope_prefix(request, session_scope_prefix):\n \"\"\"\n Generate a name prefix to be shared by objects created during this pytest module\n Relies on pytest's builtin fixture \"request\"\n https://docs.pytest.org/en/6.2.x/reference.html#std-fixture-request\n \"\"\"\n return session_scope_prefix + _del_test_prefix(request.module.__name__.split('.')[-1]) + '-'\n\n\n@pytest.fixture(scope='class')\ndef class_scope_prefix(request, module_scope_prefix):\n if not request.cls:\n return module_scope_prefix\n return module_scope_prefix + _del_test_prefix(request.cls.__name__) + '-'\n\n\n@pytest.fixture(scope='function')\ndef function_scope_prefix(request, class_scope_prefix):\n return class_scope_prefix + _del_test_prefix(request.node.originalname) + '-'\n\n\n@pytest.fixture(scope='session')\ndef vo():\n if environ.get('SUITE', 'remote_dbs') != 'client':\n # Server test, we can use short VO via DB for internal tests\n from rucio.tests.common_server import get_vo\n return get_vo()\n else:\n # Client-only test, only use config with no DB config\n from rucio.tests.common import get_long_vo\n return get_long_vo()\n\n\n@pytest.fixture(scope='session')\ndef second_vo():\n from rucio.common.config import config_get_bool\n from rucio.core.vo import vo_exists, add_vo\n multi_vo = config_get_bool('common', 'multi_vo', raise_exception=False, default=False)\n if not multi_vo:\n pytest.skip('multi_vo mode is not enabled. Running multi_vo tests in single_vo mode would result in failures.')\n\n new_vo = 'new'\n if not vo_exists(vo=new_vo):\n add_vo(vo=new_vo, description='Test', email='rucio@email.com')\n return new_vo\n\n\n@pytest.fixture(scope='session')\ndef long_vo():\n from rucio.tests.common import get_long_vo\n return get_long_vo()\n\n\n@pytest.fixture(scope='module')\ndef account_client():\n from rucio.client.accountclient import AccountClient\n\n return AccountClient()\n\n\n@pytest.fixture(scope='module')\ndef replica_client():\n from rucio.client.replicaclient import ReplicaClient\n\n return ReplicaClient()\n\n\n@pytest.fixture(scope='module')\ndef rucio_client():\n from rucio.client import Client\n return Client()\n\n\n@pytest.fixture(scope='module')\ndef did_client():\n from rucio.client.didclient import DIDClient\n\n return DIDClient()\n\n\n@pytest.fixture(scope='module')\ndef rse_client():\n from rucio.client.rseclient import RSEClient\n\n return RSEClient()\n\n\n@pytest.fixture(scope='module')\ndef scope_client():\n from rucio.client.scopeclient import ScopeClient\n\n return ScopeClient()\n\n\n@pytest.fixture(scope='module')\ndef dirac_client():\n from rucio.client.diracclient import DiracClient\n\n return DiracClient()\n\n\n@pytest.fixture\ndef rest_client():\n from rucio.tests.common import print_response\n\n from flask.testing import FlaskClient\n from rucio.web.rest.flaskapi.v1.main import application\n\n class WrappedFlaskClient(FlaskClient):\n def __init__(self, *args, **kwargs):\n super(WrappedFlaskClient, self).__init__(*args, **kwargs)\n\n def open(self, path='/', *args, **kwargs):\n print(kwargs.get('method', 'GET'), path)\n response = super(WrappedFlaskClient, self).open(path, *args, **kwargs)\n try:\n print_response(response)\n except Exception:\n traceback.print_exc()\n return response\n\n _testing = application.testing\n application.testing = True\n application.test_client_class = WrappedFlaskClient\n with application.test_client() as client:\n yield client\n application.test_client_class = None\n application.testing = _testing\n\n\n@pytest.fixture\ndef auth_token(rest_client, long_vo):\n from rucio.tests.common import vohdr, headers, loginhdr\n\n auth_response = rest_client.get('/auth/userpass', headers=headers(loginhdr('root', 'ddmlab', 'secret'), vohdr(long_vo)))\n assert auth_response.status_code == 200\n token = auth_response.headers.get('X-Rucio-Auth-Token')\n assert token\n return str(token)\n\n\n@pytest.fixture(scope='module')\ndef mock_scope(vo):\n from rucio.common.types import InternalScope\n\n return InternalScope('mock', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef test_scope(vo):\n from rucio.common.types import InternalScope\n\n return InternalScope('test', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef root_account(vo):\n from rucio.common.types import InternalAccount\n\n return InternalAccount('root', vo=vo)\n\n\n@pytest.fixture(scope='module')\ndef jdoe_account(vo):\n from rucio.common.types import InternalAccount\n\n return InternalAccount('jdoe', vo=vo)\n\n\n@pytest.fixture\ndef random_account(vo):\n import random\n import string\n\n from rucio.common.types import InternalAccount\n from rucio.core.account import add_account, del_account\n from rucio.db.sqla import models\n from rucio.db.sqla.constants import AccountType\n from rucio.tests.common_server import cleanup_db_deps\n\n account = InternalAccount(''.join(random.choice(string.ascii_uppercase) for _ in range(10)), vo=vo)\n add_account(account=account, type_=AccountType.USER, email=f'{account.external}@email.com')\n yield account\n cleanup_db_deps(model=models.Account, select_rows_stmt=models.Account.account == account)\n del_account(account)\n\n\n@pytest.fixture(scope=\"module\")\ndef containerized_rses(rucio_client):\n \"\"\"\n Detects if containerized rses for xrootd & ssh are available in the testing environment.\n :return: A list of (rse_name, rse_id) tuples.\n \"\"\"\n from rucio.common.exception import InvalidRSEExpression\n\n rses = []\n try:\n xrd_rses = [x['rse'] for x in rucio_client.list_rses(rse_expression='test_container_xrd=True')]\n xrd_rses = [rucio_client.get_rse(rse) for rse in xrd_rses]\n xrd_containerized_rses = [(rse_obj['rse'], rse_obj['id']) for rse_obj in xrd_rses if \"xrd\" in rse_obj['rse'].lower()]\n xrd_containerized_rses.sort()\n rses.extend(xrd_containerized_rses)\n ssh_rses = [x['rse'] for x in rucio_client.list_rses(rse_expression='test_container_ssh=True')]\n ssh_rses = [rucio_client.get_rse(rse) for rse in ssh_rses]\n ssh_containerized_rses = [(rse_obj['rse'], rse_obj['id']) for rse_obj in ssh_rses if \"ssh\" in rse_obj['rse'].lower()]\n ssh_containerized_rses.sort()\n rses.extend(ssh_containerized_rses)\n except InvalidRSEExpression as invalid_rse_expression:\n print(\"{ex}. Note that containerized RSEs will not be available in non-containerized test environments\"\n .format(ex=invalid_rse_expression))\n traceback.print_exc()\n return rses\n\n\n@pytest.fixture\ndef rse_factory(request, vo, function_scope_prefix):\n from .temp_factories import TemporaryRSEFactory\n\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n\n with TemporaryRSEFactory(vo=vo, name_prefix=function_scope_prefix, db_session=session) as factory:\n yield factory\n\n\n@pytest.fixture(scope=\"class\")\ndef rse_factory_unittest(request, vo, class_scope_prefix):\n \"\"\"\n unittest classes can get access to rse_factory fixture via this fixture\n \"\"\"\n from .temp_factories import TemporaryRSEFactory\n\n with TemporaryRSEFactory(vo=vo, name_prefix=class_scope_prefix) as factory:\n request.cls.rse_factory = factory\n yield factory\n\n\n@pytest.fixture\ndef did_factory(request, vo, mock_scope, function_scope_prefix, file_factory, root_account):\n from .temp_factories import TemporaryDidFactory\n\n session = None\n if 'db_session' in request.fixturenames:\n session = request.getfixturevalue('db_session')\n\n with TemporaryDidFactory(vo=vo, default_scope=mock_scope, name_prefix=function_scope_prefix, file_factory=file_factory,\n default_account=root_account, db_session=session) as factory:\n yield factory\n\n\n@pytest.fixture\ndef file_factory(tmp_path_factory):\n from .temp_factories import TemporaryFileFactory\n\n with TemporaryFileFactory(pytest_path_factory=tmp_path_factory) as factory:\n yield factory\n\n\n@pytest.fixture\ndef scope_factory():\n from rucio.common.utils import generate_uuid\n from rucio.core.scope import add_scope\n from rucio.common.types import InternalAccount, InternalScope\n\n def create_scopes(vos, account_name=None):\n scope_uuid = str(generate_uuid()).lower()[:16]\n scope_name = 'shr_%s' % scope_uuid\n created_scopes = []\n for vo in vos:\n scope = InternalScope(scope_name, vo=vo)\n add_scope(scope, InternalAccount(account_name if account_name else 'root', vo=vo))\n created_scopes.append(scope)\n return scope_name, created_scopes\n\n return create_scopes\n\n\nclass _TagFactory:\n def __init__(self, prefix):\n self.prefix = prefix\n self.index = 0\n\n def new_tag(self):\n self.index += 1\n return f'{self.prefix}-{self.index}'\n\n\n@pytest.fixture\ndef tag_factory(function_scope_prefix):\n return _TagFactory(prefix=f'{function_scope_prefix}{\"\".join(choice(ascii_uppercase) for _ in range(6))}'.replace('_', '-'))\n\n\n@pytest.fixture(scope='class')\ndef tag_factory_class(class_scope_prefix):\n return _TagFactory(prefix=f'{class_scope_prefix}{\"\".join(choice(ascii_uppercase) for _ in range(6))}'.replace('_', '-'))\n\n\n@pytest.fixture\ndef db_session():\n from rucio.db.sqla import session\n\n db_session = session.get_session()\n yield db_session\n db_session.commit()\n db_session.close()\n\n\ndef __get_fixture_param(request):\n fixture_param = getattr(request, \"param\", None)\n if not fixture_param:\n # Parametrize support is incomplete for legacy unittest test cases\n # Manually retrieve the parameters from the list of marks:\n mark = next(iter(filter(lambda m: m.name == 'parametrize', request.instance.pytestmark)), None)\n if mark:\n fixture_param = mark.args[1][0]\n return fixture_param\n\n\ndef __create_in_memory_db_table(name, *columns, **kwargs):\n \"\"\"\n Create an in-memory temporary table using the sqlite memory driver.\n Make sqlalchemy aware of that table by registering it via a\n declarative base.\n \"\"\"\n import datetime\n from sqlalchemy import Column, DateTime, CheckConstraint\n from sqlalchemy.pool import StaticPool\n from sqlalchemy.schema import Table\n from sqlalchemy.orm import registry\n from rucio.db.sqla.models import ModelBase\n from rucio.db.sqla.session import get_maker, create_engine\n\n engine = create_engine('sqlite://', connect_args={'check_same_thread': False}, poolclass=StaticPool)\n\n # Create a class which inherits from ModelBase. This will allow us to use the rucio-specific methods like .save()\n DeclarativeObj = type('DeclarativeObj{}'.format(name), (ModelBase,), {})\n # Create a new declarative base and map the previously created object into the base\n mapper_registry = registry()\n InMemoryBase = mapper_registry.generate_base(name='InMemoryBase{}'.format(name))\n table_args = tuple(columns) + tuple(kwargs.get('table_args', ())) + (\n Column(\"created_at\", DateTime, default=datetime.datetime.utcnow),\n Column(\"updated_at\", DateTime, default=datetime.datetime.utcnow, onupdate=datetime.datetime.utcnow),\n CheckConstraint('CREATED_AT IS NOT NULL', name=name.upper() + '_CREATED_NN'),\n CheckConstraint('UPDATED_AT IS NOT NULL', name=name.upper() + '_UPDATED_NN'),\n )\n table = Table(\n name,\n InMemoryBase.metadata,\n *table_args\n )\n mapper_registry.map_imperatively(DeclarativeObj, table)\n # Performa actual creation of the in-memory table\n InMemoryBase.metadata.create_all(engine)\n\n # Register the new table with the associated engine into the sqlalchemy sessionmaker\n # In theory, this code must be protected by rucio.db.scla.session._LOCK, but this code will be executed\n # during test case initialization, so there is no risk here to have concurrent calls from within the\n # same process\n senssionmaker = get_maker()\n senssionmaker.kw.setdefault('binds', {}).update({DeclarativeObj: engine})\n return DeclarativeObj\n\n\n@pytest.fixture\ndef message_mock():\n \"\"\"\n Fixture which overrides the Message table with a private instance\n \"\"\"\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint, CheckConstraint, Text, Index, GUID\n\n InMemoryMessage = __create_in_memory_db_table(\n 'message_' + generate_uuid(),\n Column('id', GUID(), default=generate_uuid),\n Column('event_type', String(256)),\n Column('payload', String(4000)),\n Column('payload_nolimit', Text),\n Column('services', String(256)),\n table_args=(PrimaryKeyConstraint('id', name='MESSAGES_ID_PK'),\n CheckConstraint('EVENT_TYPE IS NOT NULL', name='MESSAGES_EVENT_TYPE_NN'),\n CheckConstraint('PAYLOAD IS NOT NULL', name='MESSAGES_PAYLOAD_NN'),\n Index('MESSAGES_SERVICES_IDX', 'services', 'event_type'))\n )\n\n with mock.patch('rucio.core.message.Message', new=InMemoryMessage):\n yield\n\n\n@pytest.fixture\ndef core_config_mock(request):\n \"\"\"\n Fixture to allow having per-test core.config tables without affecting the other parallel tests.\n\n This override works only in tests which use core function calls directly, not in the ones working\n via the API, because the normal config table is not touched and the rucio instance answering API\n calls is not aware of this mock.\n\n This fixture acts by creating a new copy of the \"config\" sql table using the :memory: sqlite engine.\n Accesses to the \"models.Config\" table are then redirected to this temporary table via mock.patch().\n \"\"\"\n from unittest import mock\n from sqlalchemy import Column\n from rucio.common.utils import generate_uuid\n from rucio.db.sqla.models import String, PrimaryKeyConstraint\n from rucio.db.sqla.session import get_session\n\n # Get the fixture parameters\n table_content = []\n params = __get_fixture_param(request)\n if params:\n table_content = params.get(\"table_content\", table_content)\n\n InMemoryConfig = __create_in_memory_db_table(\n 'configs_' + generate_uuid(),\n Column('section', String(128)),\n Column('opt', String(128)),\n Column('value', String(4000)),\n table_args=(PrimaryKeyConstraint('section', 'opt', name='CONFIGS_PK'),),\n )\n\n # Fill the table with the requested mock data\n session = get_session()()\n for section, option, value in (table_content or []):\n InMemoryConfig(section=section, opt=option, value=value).save(flush=True, session=session)\n session.commit()\n\n with mock.patch('rucio.core.config.models.Config', new=InMemoryConfig):\n yield\n\n\n@pytest.fixture\ndef file_config_mock(request):\n \"\"\"\n Fixture which allows to have an isolated in-memory configuration file instance which\n is not persisted after exiting the fixture.\n\n This override works only in tests which use config calls directly, not in the ones working\n via the API, as the server config is not changed.\n \"\"\"\n from unittest import mock\n from rucio.common.config import Config, config_set, config_has_section, config_add_section\n\n # Get the fixture parameters\n overrides = []\n params = __get_fixture_param(request)\n if params:\n overrides = params.get(\"overrides\", overrides)\n\n parser = Config().parser\n with mock.patch('rucio.common.config.get_config', side_effect=lambda: parser):\n for section, option, value in (overrides or []):\n if not config_has_section(section):\n config_add_section(section)\n config_set(section, option, value)\n yield\n\n\n@pytest.fixture\ndef caches_mock(request):\n \"\"\"\n Fixture which overrides the different internal caches with in-memory ones for the duration\n of a particular test.\n\n This override works only in tests which use core function calls directly, not in the ones\n working via API.\n\n The fixture acts by by mock.patch the REGION object in the provided list of modules to mock.\n \"\"\"\n\n from unittest import mock\n from contextlib import ExitStack\n from dogpile.cache import make_region\n\n caches_to_mock = []\n expiration_time = 600\n\n params = __get_fixture_param(request)\n if params:\n caches_to_mock = params.get(\"caches_to_mock\", caches_to_mock)\n expiration_time = params.get(\"expiration_time\", expiration_time)\n\n with ExitStack() as stack:\n mocked_caches = []\n for module in caches_to_mock:\n region = make_region().configure('dogpile.cache.memory', expiration_time=expiration_time)\n stack.enter_context(mock.patch(module, new=region))\n mocked_caches.append(region)\n\n yield mocked_caches\n\n\n@pytest.fixture\ndef metrics_mock():\n \"\"\"\n Overrides the prometheus metric registry and allows to verify if the desired\n prometheus metrics were correctly recorded.\n \"\"\"\n\n from unittest import mock\n from prometheus_client import CollectorRegistry, values\n\n with mock.patch('rucio.core.monitor.REGISTRY', new=CollectorRegistry()) as registry, \\\n mock.patch('rucio.core.monitor.COUNTERS', new={}), \\\n mock.patch('rucio.core.monitor.GAUGES', new={}), \\\n mock.patch('rucio.core.monitor.TIMINGS', new={}), \\\n mock.patch('prometheus_client.values.ValueClass', new=values.MutexValue):\n yield registry\n",
"step-ids": [
17,
20,
21,
23,
45
]
}
|
[
17,
20,
21,
23,
45
] |
<|reserved_special_token_0|>
class PersonView(TemplateView):
def get(self, request):
persons = Person.objects.all()
context = {'persons': persons}
return render(request, 'budget/person.html', context)
class AddView(TemplateView):
template = 'budget/add.html'
def get(self, request):
form = NameForm
context = {'form': form}
return render(request, self.template, context)
def post(self, request):
form = NameForm(request.POST)
if form.is_valid():
text = form.cleaned_data
form = NameForm()
p = Person(first_name=text['first_name'], last_name=text[
'last_name'], income=text['income'])
p.save()
context = {'form': form, 'text': text}
return render(request, self.template, context)
class UploadView(TemplateView):
template_name = 'budget/upload.html'
def get(self, request):
form = UploadFileForm()
return render(request, self.template_name, {'form': form})
def post(self, request):
if request.method == 'POST':
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
handle_uploaded_file(request.FILES['file'])
read_file(request.FILES['file'])
return HttpResponseRedirect('/upload')
return render(request, self.template_name, {'form': form})
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class DetailView(TemplateView):
<|reserved_special_token_0|>
class PersonView(TemplateView):
def get(self, request):
persons = Person.objects.all()
context = {'persons': persons}
return render(request, 'budget/person.html', context)
class AddView(TemplateView):
template = 'budget/add.html'
def get(self, request):
form = NameForm
context = {'form': form}
return render(request, self.template, context)
def post(self, request):
form = NameForm(request.POST)
if form.is_valid():
text = form.cleaned_data
form = NameForm()
p = Person(first_name=text['first_name'], last_name=text[
'last_name'], income=text['income'])
p.save()
context = {'form': form, 'text': text}
return render(request, self.template, context)
class UploadView(TemplateView):
template_name = 'budget/upload.html'
def get(self, request):
form = UploadFileForm()
return render(request, self.template_name, {'form': form})
def post(self, request):
if request.method == 'POST':
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
handle_uploaded_file(request.FILES['file'])
read_file(request.FILES['file'])
return HttpResponseRedirect('/upload')
return render(request, self.template_name, {'form': form})
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class IndexView(TemplateView):
<|reserved_special_token_0|>
class DetailView(TemplateView):
def get(self, request, person_id):
try:
persons = Person.objects.all()
person = Person.objects.get(id=person_id)
except Person.DoesNotExist:
raise Http404('Person does not exist')
context = {'persons': persons, 'person': person, 'first_name':
person.first_name, 'last_name': person.last_name, 'income':
person.income}
return render(request, 'budget/detail.html', context)
class PersonView(TemplateView):
def get(self, request):
persons = Person.objects.all()
context = {'persons': persons}
return render(request, 'budget/person.html', context)
class AddView(TemplateView):
template = 'budget/add.html'
def get(self, request):
form = NameForm
context = {'form': form}
return render(request, self.template, context)
def post(self, request):
form = NameForm(request.POST)
if form.is_valid():
text = form.cleaned_data
form = NameForm()
p = Person(first_name=text['first_name'], last_name=text[
'last_name'], income=text['income'])
p.save()
context = {'form': form, 'text': text}
return render(request, self.template, context)
class UploadView(TemplateView):
template_name = 'budget/upload.html'
def get(self, request):
form = UploadFileForm()
return render(request, self.template_name, {'form': form})
def post(self, request):
if request.method == 'POST':
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
handle_uploaded_file(request.FILES['file'])
read_file(request.FILES['file'])
return HttpResponseRedirect('/upload')
return render(request, self.template_name, {'form': form})
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class IndexView(TemplateView):
def get(self, request):
price_history = Stock_history.objects.all()
context = {'entry': price_history}
return render(request, 'budget/index.html', context)
class DetailView(TemplateView):
def get(self, request, person_id):
try:
persons = Person.objects.all()
person = Person.objects.get(id=person_id)
except Person.DoesNotExist:
raise Http404('Person does not exist')
context = {'persons': persons, 'person': person, 'first_name':
person.first_name, 'last_name': person.last_name, 'income':
person.income}
return render(request, 'budget/detail.html', context)
class PersonView(TemplateView):
def get(self, request):
persons = Person.objects.all()
context = {'persons': persons}
return render(request, 'budget/person.html', context)
class AddView(TemplateView):
template = 'budget/add.html'
def get(self, request):
form = NameForm
context = {'form': form}
return render(request, self.template, context)
def post(self, request):
form = NameForm(request.POST)
if form.is_valid():
text = form.cleaned_data
form = NameForm()
p = Person(first_name=text['first_name'], last_name=text[
'last_name'], income=text['income'])
p.save()
context = {'form': form, 'text': text}
return render(request, self.template, context)
class UploadView(TemplateView):
template_name = 'budget/upload.html'
def get(self, request):
form = UploadFileForm()
return render(request, self.template_name, {'form': form})
def post(self, request):
if request.method == 'POST':
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
handle_uploaded_file(request.FILES['file'])
read_file(request.FILES['file'])
return HttpResponseRedirect('/upload')
return render(request, self.template_name, {'form': form})
<|reserved_special_token_1|>
from django.shortcuts import render, HttpResponse
from django.views.generic import TemplateView
from .models import Person, Stock_history
from django.http import Http404, HttpResponseRedirect
from .forms import NameForm, UploadFileForm
from .back import handle_uploaded_file, read_file
class IndexView(TemplateView):
def get(self, request):
price_history = Stock_history.objects.all()
context = {
'entry': price_history
}
return render(request, 'budget/index.html', context)
class DetailView(TemplateView):
def get(self, request, person_id):
try:
persons = Person.objects.all()
person = Person.objects.get(id=person_id)
except Person.DoesNotExist:
raise Http404("Person does not exist")
context = {
'persons': persons,
'person': person,
'first_name': person.first_name,
'last_name': person.last_name,
'income': person.income,
}
return render(request, 'budget/detail.html', context)
class PersonView(TemplateView):
def get(self, request):
persons = Person.objects.all()
context = {
'persons': persons,
}
return render(request, 'budget/person.html', context)
class AddView(TemplateView):
template = 'budget/add.html'
def get(self, request):
form = NameForm
context = {'form': form}
return render(request, self.template, context)
def post(self, request):
form = NameForm(request.POST)
if form.is_valid():
text = form.cleaned_data
form = NameForm()
p = Person(first_name=text['first_name'], last_name=text['last_name'], income = text['income'])
p.save()
context = {
'form': form,
'text': text,
}
return render(request, self.template, context)
class UploadView(TemplateView):
template_name = 'budget/upload.html'
def get(self, request):
form = UploadFileForm()
return render(request, self.template_name, {'form': form})
def post(self, request):
if request.method == 'POST':
form = UploadFileForm(request.POST, request.FILES)
if form.is_valid():
handle_uploaded_file(request.FILES['file'])
read_file(request.FILES['file'])
return HttpResponseRedirect('/upload')
#else:
# form = UploadFileForm()
return render(request, self.template_name, {'form': form})
|
flexible
|
{
"blob_id": "2d65ffa3fc8a5360702337d749884903b2cb0423",
"index": 2353,
"step-1": "<mask token>\n\n\nclass PersonView(TemplateView):\n\n def get(self, request):\n persons = Person.objects.all()\n context = {'persons': persons}\n return render(request, 'budget/person.html', context)\n\n\nclass AddView(TemplateView):\n template = 'budget/add.html'\n\n def get(self, request):\n form = NameForm\n context = {'form': form}\n return render(request, self.template, context)\n\n def post(self, request):\n form = NameForm(request.POST)\n if form.is_valid():\n text = form.cleaned_data\n form = NameForm()\n p = Person(first_name=text['first_name'], last_name=text[\n 'last_name'], income=text['income'])\n p.save()\n context = {'form': form, 'text': text}\n return render(request, self.template, context)\n\n\nclass UploadView(TemplateView):\n template_name = 'budget/upload.html'\n\n def get(self, request):\n form = UploadFileForm()\n return render(request, self.template_name, {'form': form})\n\n def post(self, request):\n if request.method == 'POST':\n form = UploadFileForm(request.POST, request.FILES)\n if form.is_valid():\n handle_uploaded_file(request.FILES['file'])\n read_file(request.FILES['file'])\n return HttpResponseRedirect('/upload')\n return render(request, self.template_name, {'form': form})\n",
"step-2": "<mask token>\n\n\nclass DetailView(TemplateView):\n <mask token>\n\n\nclass PersonView(TemplateView):\n\n def get(self, request):\n persons = Person.objects.all()\n context = {'persons': persons}\n return render(request, 'budget/person.html', context)\n\n\nclass AddView(TemplateView):\n template = 'budget/add.html'\n\n def get(self, request):\n form = NameForm\n context = {'form': form}\n return render(request, self.template, context)\n\n def post(self, request):\n form = NameForm(request.POST)\n if form.is_valid():\n text = form.cleaned_data\n form = NameForm()\n p = Person(first_name=text['first_name'], last_name=text[\n 'last_name'], income=text['income'])\n p.save()\n context = {'form': form, 'text': text}\n return render(request, self.template, context)\n\n\nclass UploadView(TemplateView):\n template_name = 'budget/upload.html'\n\n def get(self, request):\n form = UploadFileForm()\n return render(request, self.template_name, {'form': form})\n\n def post(self, request):\n if request.method == 'POST':\n form = UploadFileForm(request.POST, request.FILES)\n if form.is_valid():\n handle_uploaded_file(request.FILES['file'])\n read_file(request.FILES['file'])\n return HttpResponseRedirect('/upload')\n return render(request, self.template_name, {'form': form})\n",
"step-3": "<mask token>\n\n\nclass IndexView(TemplateView):\n <mask token>\n\n\nclass DetailView(TemplateView):\n\n def get(self, request, person_id):\n try:\n persons = Person.objects.all()\n person = Person.objects.get(id=person_id)\n except Person.DoesNotExist:\n raise Http404('Person does not exist')\n context = {'persons': persons, 'person': person, 'first_name':\n person.first_name, 'last_name': person.last_name, 'income':\n person.income}\n return render(request, 'budget/detail.html', context)\n\n\nclass PersonView(TemplateView):\n\n def get(self, request):\n persons = Person.objects.all()\n context = {'persons': persons}\n return render(request, 'budget/person.html', context)\n\n\nclass AddView(TemplateView):\n template = 'budget/add.html'\n\n def get(self, request):\n form = NameForm\n context = {'form': form}\n return render(request, self.template, context)\n\n def post(self, request):\n form = NameForm(request.POST)\n if form.is_valid():\n text = form.cleaned_data\n form = NameForm()\n p = Person(first_name=text['first_name'], last_name=text[\n 'last_name'], income=text['income'])\n p.save()\n context = {'form': form, 'text': text}\n return render(request, self.template, context)\n\n\nclass UploadView(TemplateView):\n template_name = 'budget/upload.html'\n\n def get(self, request):\n form = UploadFileForm()\n return render(request, self.template_name, {'form': form})\n\n def post(self, request):\n if request.method == 'POST':\n form = UploadFileForm(request.POST, request.FILES)\n if form.is_valid():\n handle_uploaded_file(request.FILES['file'])\n read_file(request.FILES['file'])\n return HttpResponseRedirect('/upload')\n return render(request, self.template_name, {'form': form})\n",
"step-4": "<mask token>\n\n\nclass IndexView(TemplateView):\n\n def get(self, request):\n price_history = Stock_history.objects.all()\n context = {'entry': price_history}\n return render(request, 'budget/index.html', context)\n\n\nclass DetailView(TemplateView):\n\n def get(self, request, person_id):\n try:\n persons = Person.objects.all()\n person = Person.objects.get(id=person_id)\n except Person.DoesNotExist:\n raise Http404('Person does not exist')\n context = {'persons': persons, 'person': person, 'first_name':\n person.first_name, 'last_name': person.last_name, 'income':\n person.income}\n return render(request, 'budget/detail.html', context)\n\n\nclass PersonView(TemplateView):\n\n def get(self, request):\n persons = Person.objects.all()\n context = {'persons': persons}\n return render(request, 'budget/person.html', context)\n\n\nclass AddView(TemplateView):\n template = 'budget/add.html'\n\n def get(self, request):\n form = NameForm\n context = {'form': form}\n return render(request, self.template, context)\n\n def post(self, request):\n form = NameForm(request.POST)\n if form.is_valid():\n text = form.cleaned_data\n form = NameForm()\n p = Person(first_name=text['first_name'], last_name=text[\n 'last_name'], income=text['income'])\n p.save()\n context = {'form': form, 'text': text}\n return render(request, self.template, context)\n\n\nclass UploadView(TemplateView):\n template_name = 'budget/upload.html'\n\n def get(self, request):\n form = UploadFileForm()\n return render(request, self.template_name, {'form': form})\n\n def post(self, request):\n if request.method == 'POST':\n form = UploadFileForm(request.POST, request.FILES)\n if form.is_valid():\n handle_uploaded_file(request.FILES['file'])\n read_file(request.FILES['file'])\n return HttpResponseRedirect('/upload')\n return render(request, self.template_name, {'form': form})\n",
"step-5": "from django.shortcuts import render, HttpResponse\nfrom django.views.generic import TemplateView\nfrom .models import Person, Stock_history\nfrom django.http import Http404, HttpResponseRedirect\nfrom .forms import NameForm, UploadFileForm\n\nfrom .back import handle_uploaded_file, read_file\n\nclass IndexView(TemplateView):\n def get(self, request):\n price_history = Stock_history.objects.all()\n context = {\n 'entry': price_history\n }\n return render(request, 'budget/index.html', context)\n\nclass DetailView(TemplateView):\n def get(self, request, person_id):\n try:\n persons = Person.objects.all()\n person = Person.objects.get(id=person_id)\n except Person.DoesNotExist:\n raise Http404(\"Person does not exist\")\n \n context = {\n 'persons': persons,\n 'person': person,\n 'first_name': person.first_name, \n 'last_name': person.last_name,\n 'income': person.income,\n\n }\n return render(request, 'budget/detail.html', context)\n\n\nclass PersonView(TemplateView):\n def get(self, request):\n persons = Person.objects.all()\n\n context = {\n 'persons': persons,\n }\n return render(request, 'budget/person.html', context)\n\nclass AddView(TemplateView):\n template = 'budget/add.html'\n\n def get(self, request):\n form = NameForm\n context = {'form': form}\n return render(request, self.template, context)\n\n\n def post(self, request):\n form = NameForm(request.POST)\n if form.is_valid():\n text = form.cleaned_data\n form = NameForm()\n p = Person(first_name=text['first_name'], last_name=text['last_name'], income = text['income'])\n p.save()\n context = {\n 'form': form,\n 'text': text,\n }\n\n return render(request, self.template, context)\n\n\nclass UploadView(TemplateView):\n template_name = 'budget/upload.html'\n\n def get(self, request):\n form = UploadFileForm()\n return render(request, self.template_name, {'form': form})\n\n def post(self, request):\n if request.method == 'POST':\n form = UploadFileForm(request.POST, request.FILES)\n if form.is_valid():\n handle_uploaded_file(request.FILES['file'])\n read_file(request.FILES['file'])\n return HttpResponseRedirect('/upload')\n #else:\n # form = UploadFileForm()\n return render(request, self.template_name, {'form': form})\n",
"step-ids": [
10,
11,
13,
14,
16
]
}
|
[
10,
11,
13,
14,
16
] |
PROJECT_ID = "aaet-geoscience-dev"
# The tmp folder is for lasio I/O purposes
DATA_PATH = "/home/airflow/gcs/data/tmp"
# Credential JSON key for accessing other projects
# CREDENTIALS_JSON = "gs://aaet_zexuan/flow/keys/composer_las_merge.json"
CREDENTIALS_JSON = "keys/composer_las_merge.json"
# Bucket name for merged las files and spliced las files
BUCKET_LAS_MERGE = "las_merged"
BUCKET_LAS_SPLICE = "us-central1-lithos-dev-94beb3d4-bucket"
# las_splice.py output to the composer data folder, as input of logqc
COMPOSER_FOLDER = "data/logqc_landing"
TMP_FOLDER = "data/tmp"
# for GCP web UI and Big Query Job Status Report
BUCKET_JOB = "log_splice_tool_jobs"
BIGQUERY_DATASET_ID = "urc_jobs"
BIGQUERY_TABLE_ID = "jobs"
# Workflow type
tpt_workflow_type = "tpt"
logsplice_workflow_type = "logsplice"
logqc_workflow_type = "logqc"
geomech_workflow_type = "geomech"
# Number of processors for las_merge_MP (multiprocessing).
N_PROCESSORS = 16
# The window size for moving average, e.g. 11 means the window covers a
# point and 5 adjacent points on both sides
MOVING_AVG_WINDOW_SIZE = 11
# Default value for missing data, usually it is either -999.25 or -999.0
MISSING = -999.0
# COL_DICT: a dictionary of aliased curve names for log splicing. keys correspond to measurements
# (e.g., 'density', 'gamma', 'resistivity', etc.),
# and each value is a list of aliased column names that could potentially correspond
# to those measurements. Each key is the aliased curve name before splicing,
# each key's value is the standard curve name after splicing.
COL_DICT = {
# Caliper
"cal": ["CAL", "CALI", "CALX", "HCAL", "TGS_CALX", "RAW_CALX"],
# Compressional Sonic Slowness
"dtc": ["DT", "DT24", "DTC", 'TGS_DT', "TGS_DTC", "RAW_DT", "RAW_DTC"],
# Deep Resistivity
# 'rdeep' includes 'rdeep_ltrl' (laterolog), 'rdeep_indct' (induction), 'rdeep_unknown'.
# A final 'rdeep' will be generated
# with an additional 'rdeep_type' curve to denote the log type.
"rdeep": ['ILT90', 'LLD', 'RDEEP', 'RES', 'RES_DEEP', 'AHT90', 'AT90', 'ILD', 'ILT90', 'LLD', 'ILO90', 'ILF90', 'LLMD'],
# Density (Bulk)
"rhob": ["DEN", "RHOB", "RHOZ", "ZDEN", "ZDNC", "TGS_RHOB", 'RAW_RHOB'],
# Density (Correction)
"drho": ["DRHO", "HDRA", "ZCOR"],
# Gamma Ray
"gr": ["APC_GR_NRM", "GAMM", "GR", "GR_R", "GRR", 'SGR', 'SGRR', 'CGR'],
# Neutron Porosity
"nphil": ["CNCF", "NEU", "NPOR", "NPHI", "NPHIL", "TNPH", 'TGS_NPHI', 'NPHI_LS', 'TNPH_LS', 'RAW_NPHI'],
# Photoelectric effect
"pe": ["PE", "PEF", "PEFZ", 'TGS_PE', 'RAW_PE'],
}
# LDD is laterolog
# The rest are inductions
# RDEEP, RES, RES_DEEP are of unknown origin
# __log_type_rdeep = [log_type_enum.induction, #AHT90
# log_type_enum.induction, #AT90
# log_type_enum.induction, #ILD
# log_type_enum.induction, #ILT90
# log_type_enum.laterolog, #LLD
# log_type_enum.induction, #M2R9
# log_type_enum.unknown, #RDEEP
# log_type_enum.unknown, #RES
# log_type_enum.unknown] #RES_DEEP
RDEEP_TYPE_LIST = ["rdeep_ltrl", "rdeep_indct", "rdeep_unknown"]
RDEEP_TYPE_DICT = {"rdeep_ltrl": 1, "rdeep_indct": 2, "rdeep_unknown": 3}
# curve description dictionary
CURVE_DESC = {
"DEPT": "Depth",
"CAL": "Caliper",
"DRHO": "Density Correction",
"DTC": "Compressional Wave Slowness",
"DTS": "Shear Wave Slowness",
"GR": "Gamma Ray",
"NPHI": "Neutron Porosity",
"NPHIL": "Neutron Porosity",
"PE": "Photoelectric Effect",
"RDEEP": "Deep Resistivity",
"RDEEP_LTRL": "Laterolog Resistivity",
"RDEEP_INDCT": "Induction Resistivity",
"RDEEP_UNKNOWN": "Unknown Resistivity (Laterolog or Induction)",
"RDEEP_TYPE": "RDEEP Type 1:Laterolog 2:Induction 3:Unknown",
"RHOB": "Bulk Density",
"RUGOSITY": "Borehole Rugosity",
"RUGOSITY_BHF": "Rugosity Bad Hole Flag",
"DRHO_BHF": "Density Correction Bad Hole Flag",
"DTC_BHF": "Sonic Bad Hole Flag",
"GR_BHF": "Gamma Ray Bad Hole Flag",
"NPHIL_BHF": "Neutron Bad Hole Flag",
"RHOB_BHF": "Density Bad Hole Flag",
"LOG_RDEEP_BHF": "Resistivity Bad Hole Flag",
"PE_BHF": "PE Bad Hole Flag",
"RHOB_MCF": "Density Corrected from Multiwell Flag",
"RHOB_SYN": "Density Estimation from Ensemble of Learners",
"NPHI_MCF": "Neutron Corrected from Multiwell Flag",
"NPHI_SYN": "Neutron Estimation from Ensemble of Learners",
"DTC_MCF": "Sonic Corrected from Multiwell Flag",
"DTC_SYN": "Sonic Estimation from Ensemble of Learners",
"PE_MCF": "PE Corrected from Multiwell Flag",
"PE_SYN": "PE Estimation from Ensemble of Learners",
"RHOB_NCF": "Density No Correction Flag",
"RHOB_CORR": "Density Corrected",
"NPHI_NCF": "Neutron No Correction Flag",
"NPHI_CORR": "Neutron Corrected",
"DTC_NCF": "Sonic No Correction Flag",
"DTC_CORR": "Sonic Corrected",
"PE_NCF": "PE No Correction Flag",
"PE_CORR": "PE Corrected"
}
|
normal
|
{
"blob_id": "0b2a036b806cca6e7f58008040b3a261a8bc844d",
"index": 4092,
"step-1": "<mask token>\n",
"step-2": "PROJECT_ID = 'aaet-geoscience-dev'\nDATA_PATH = '/home/airflow/gcs/data/tmp'\nCREDENTIALS_JSON = 'keys/composer_las_merge.json'\nBUCKET_LAS_MERGE = 'las_merged'\nBUCKET_LAS_SPLICE = 'us-central1-lithos-dev-94beb3d4-bucket'\nCOMPOSER_FOLDER = 'data/logqc_landing'\nTMP_FOLDER = 'data/tmp'\nBUCKET_JOB = 'log_splice_tool_jobs'\nBIGQUERY_DATASET_ID = 'urc_jobs'\nBIGQUERY_TABLE_ID = 'jobs'\ntpt_workflow_type = 'tpt'\nlogsplice_workflow_type = 'logsplice'\nlogqc_workflow_type = 'logqc'\ngeomech_workflow_type = 'geomech'\nN_PROCESSORS = 16\nMOVING_AVG_WINDOW_SIZE = 11\nMISSING = -999.0\nCOL_DICT = {'cal': ['CAL', 'CALI', 'CALX', 'HCAL', 'TGS_CALX', 'RAW_CALX'],\n 'dtc': ['DT', 'DT24', 'DTC', 'TGS_DT', 'TGS_DTC', 'RAW_DT', 'RAW_DTC'],\n 'rdeep': ['ILT90', 'LLD', 'RDEEP', 'RES', 'RES_DEEP', 'AHT90', 'AT90',\n 'ILD', 'ILT90', 'LLD', 'ILO90', 'ILF90', 'LLMD'], 'rhob': ['DEN',\n 'RHOB', 'RHOZ', 'ZDEN', 'ZDNC', 'TGS_RHOB', 'RAW_RHOB'], 'drho': [\n 'DRHO', 'HDRA', 'ZCOR'], 'gr': ['APC_GR_NRM', 'GAMM', 'GR', 'GR_R',\n 'GRR', 'SGR', 'SGRR', 'CGR'], 'nphil': ['CNCF', 'NEU', 'NPOR', 'NPHI',\n 'NPHIL', 'TNPH', 'TGS_NPHI', 'NPHI_LS', 'TNPH_LS', 'RAW_NPHI'], 'pe': [\n 'PE', 'PEF', 'PEFZ', 'TGS_PE', 'RAW_PE']}\nRDEEP_TYPE_LIST = ['rdeep_ltrl', 'rdeep_indct', 'rdeep_unknown']\nRDEEP_TYPE_DICT = {'rdeep_ltrl': 1, 'rdeep_indct': 2, 'rdeep_unknown': 3}\nCURVE_DESC = {'DEPT': 'Depth', 'CAL': 'Caliper', 'DRHO':\n 'Density Correction', 'DTC': 'Compressional Wave Slowness', 'DTS':\n 'Shear Wave Slowness', 'GR': 'Gamma Ray', 'NPHI': 'Neutron Porosity',\n 'NPHIL': 'Neutron Porosity', 'PE': 'Photoelectric Effect', 'RDEEP':\n 'Deep Resistivity', 'RDEEP_LTRL': 'Laterolog Resistivity',\n 'RDEEP_INDCT': 'Induction Resistivity', 'RDEEP_UNKNOWN':\n 'Unknown Resistivity (Laterolog or Induction)', 'RDEEP_TYPE':\n 'RDEEP Type 1:Laterolog 2:Induction 3:Unknown', 'RHOB': 'Bulk Density',\n 'RUGOSITY': 'Borehole Rugosity', 'RUGOSITY_BHF':\n 'Rugosity Bad Hole Flag', 'DRHO_BHF':\n 'Density Correction Bad Hole Flag', 'DTC_BHF': 'Sonic Bad Hole Flag',\n 'GR_BHF': 'Gamma Ray Bad Hole Flag', 'NPHIL_BHF':\n 'Neutron Bad Hole Flag', 'RHOB_BHF': 'Density Bad Hole Flag',\n 'LOG_RDEEP_BHF': 'Resistivity Bad Hole Flag', 'PE_BHF':\n 'PE Bad Hole Flag', 'RHOB_MCF': 'Density Corrected from Multiwell Flag',\n 'RHOB_SYN': 'Density Estimation from Ensemble of Learners', 'NPHI_MCF':\n 'Neutron Corrected from Multiwell Flag', 'NPHI_SYN':\n 'Neutron Estimation from Ensemble of Learners', 'DTC_MCF':\n 'Sonic Corrected from Multiwell Flag', 'DTC_SYN':\n 'Sonic Estimation from Ensemble of Learners', 'PE_MCF':\n 'PE Corrected from Multiwell Flag', 'PE_SYN':\n 'PE Estimation from Ensemble of Learners', 'RHOB_NCF':\n 'Density No Correction Flag', 'RHOB_CORR': 'Density Corrected',\n 'NPHI_NCF': 'Neutron No Correction Flag', 'NPHI_CORR':\n 'Neutron Corrected', 'DTC_NCF': 'Sonic No Correction Flag', 'DTC_CORR':\n 'Sonic Corrected', 'PE_NCF': 'PE No Correction Flag', 'PE_CORR':\n 'PE Corrected'}\n",
"step-3": "PROJECT_ID = \"aaet-geoscience-dev\"\r\n# The tmp folder is for lasio I/O purposes\r\nDATA_PATH = \"/home/airflow/gcs/data/tmp\"\r\n\r\n# Credential JSON key for accessing other projects\r\n# CREDENTIALS_JSON = \"gs://aaet_zexuan/flow/keys/composer_las_merge.json\"\r\nCREDENTIALS_JSON = \"keys/composer_las_merge.json\"\r\n\r\n# Bucket name for merged las files and spliced las files\r\nBUCKET_LAS_MERGE = \"las_merged\"\r\nBUCKET_LAS_SPLICE = \"us-central1-lithos-dev-94beb3d4-bucket\"\r\n\r\n# las_splice.py output to the composer data folder, as input of logqc\r\nCOMPOSER_FOLDER = \"data/logqc_landing\"\r\nTMP_FOLDER = \"data/tmp\"\r\n# for GCP web UI and Big Query Job Status Report\r\nBUCKET_JOB = \"log_splice_tool_jobs\"\r\nBIGQUERY_DATASET_ID = \"urc_jobs\"\r\nBIGQUERY_TABLE_ID = \"jobs\"\r\n\r\n# Workflow type\r\ntpt_workflow_type = \"tpt\"\r\nlogsplice_workflow_type = \"logsplice\"\r\nlogqc_workflow_type = \"logqc\"\r\ngeomech_workflow_type = \"geomech\"\r\n\r\n# Number of processors for las_merge_MP (multiprocessing).\r\nN_PROCESSORS = 16\r\n\r\n# The window size for moving average, e.g. 11 means the window covers a\r\n# point and 5 adjacent points on both sides\r\nMOVING_AVG_WINDOW_SIZE = 11\r\n\r\n# Default value for missing data, usually it is either -999.25 or -999.0\r\nMISSING = -999.0\r\n\r\n# COL_DICT: a dictionary of aliased curve names for log splicing. keys correspond to measurements\r\n# (e.g., 'density', 'gamma', 'resistivity', etc.),\r\n# and each value is a list of aliased column names that could potentially correspond\r\n# to those measurements. Each key is the aliased curve name before splicing,\r\n# each key's value is the standard curve name after splicing.\r\nCOL_DICT = {\r\n # Caliper\r\n \"cal\": [\"CAL\", \"CALI\", \"CALX\", \"HCAL\", \"TGS_CALX\", \"RAW_CALX\"],\r\n # Compressional Sonic Slowness\r\n \"dtc\": [\"DT\", \"DT24\", \"DTC\", 'TGS_DT', \"TGS_DTC\", \"RAW_DT\", \"RAW_DTC\"],\r\n # Deep Resistivity\r\n # 'rdeep' includes 'rdeep_ltrl' (laterolog), 'rdeep_indct' (induction), 'rdeep_unknown'.\r\n # A final 'rdeep' will be generated\r\n # with an additional 'rdeep_type' curve to denote the log type.\r\n \"rdeep\": ['ILT90', 'LLD', 'RDEEP', 'RES', 'RES_DEEP', 'AHT90', 'AT90', 'ILD', 'ILT90', 'LLD', 'ILO90', 'ILF90', 'LLMD'],\r\n # Density (Bulk)\r\n \"rhob\": [\"DEN\", \"RHOB\", \"RHOZ\", \"ZDEN\", \"ZDNC\", \"TGS_RHOB\", 'RAW_RHOB'],\r\n # Density (Correction)\r\n \"drho\": [\"DRHO\", \"HDRA\", \"ZCOR\"],\r\n # Gamma Ray\r\n \"gr\": [\"APC_GR_NRM\", \"GAMM\", \"GR\", \"GR_R\", \"GRR\", 'SGR', 'SGRR', 'CGR'],\r\n # Neutron Porosity\r\n \"nphil\": [\"CNCF\", \"NEU\", \"NPOR\", \"NPHI\", \"NPHIL\", \"TNPH\", 'TGS_NPHI', 'NPHI_LS', 'TNPH_LS', 'RAW_NPHI'],\r\n # Photoelectric effect\r\n \"pe\": [\"PE\", \"PEF\", \"PEFZ\", 'TGS_PE', 'RAW_PE'],\r\n}\r\n\r\n# LDD is laterolog\r\n# The rest are inductions\r\n# RDEEP, RES, RES_DEEP are of unknown origin\r\n# __log_type_rdeep = [log_type_enum.induction, #AHT90\r\n# log_type_enum.induction, #AT90\r\n# log_type_enum.induction, #ILD\r\n# log_type_enum.induction, #ILT90\r\n# log_type_enum.laterolog, #LLD\r\n# log_type_enum.induction, #M2R9\r\n# log_type_enum.unknown, #RDEEP\r\n# log_type_enum.unknown, #RES\r\n# log_type_enum.unknown] #RES_DEEP\r\n\r\nRDEEP_TYPE_LIST = [\"rdeep_ltrl\", \"rdeep_indct\", \"rdeep_unknown\"]\r\nRDEEP_TYPE_DICT = {\"rdeep_ltrl\": 1, \"rdeep_indct\": 2, \"rdeep_unknown\": 3}\r\n\r\n# curve description dictionary\r\nCURVE_DESC = {\r\n \"DEPT\": \"Depth\",\r\n \"CAL\": \"Caliper\",\r\n \"DRHO\": \"Density Correction\",\r\n \"DTC\": \"Compressional Wave Slowness\",\r\n \"DTS\": \"Shear Wave Slowness\",\r\n \"GR\": \"Gamma Ray\",\r\n \"NPHI\": \"Neutron Porosity\",\r\n \"NPHIL\": \"Neutron Porosity\",\r\n \"PE\": \"Photoelectric Effect\",\r\n \"RDEEP\": \"Deep Resistivity\",\r\n \"RDEEP_LTRL\": \"Laterolog Resistivity\",\r\n \"RDEEP_INDCT\": \"Induction Resistivity\",\r\n \"RDEEP_UNKNOWN\": \"Unknown Resistivity (Laterolog or Induction)\",\r\n \"RDEEP_TYPE\": \"RDEEP Type 1:Laterolog 2:Induction 3:Unknown\",\r\n \"RHOB\": \"Bulk Density\",\r\n \"RUGOSITY\": \"Borehole Rugosity\",\r\n \"RUGOSITY_BHF\": \"Rugosity Bad Hole Flag\",\r\n \"DRHO_BHF\": \"Density Correction Bad Hole Flag\",\r\n \"DTC_BHF\": \"Sonic Bad Hole Flag\",\r\n \"GR_BHF\": \"Gamma Ray Bad Hole Flag\",\r\n \"NPHIL_BHF\": \"Neutron Bad Hole Flag\",\r\n \"RHOB_BHF\": \"Density Bad Hole Flag\",\r\n \"LOG_RDEEP_BHF\": \"Resistivity Bad Hole Flag\",\r\n \"PE_BHF\": \"PE Bad Hole Flag\",\r\n \"RHOB_MCF\": \"Density Corrected from Multiwell Flag\",\r\n \"RHOB_SYN\": \"Density Estimation from Ensemble of Learners\",\r\n \"NPHI_MCF\": \"Neutron Corrected from Multiwell Flag\",\r\n \"NPHI_SYN\": \"Neutron Estimation from Ensemble of Learners\",\r\n \"DTC_MCF\": \"Sonic Corrected from Multiwell Flag\",\r\n \"DTC_SYN\": \"Sonic Estimation from Ensemble of Learners\",\r\n \"PE_MCF\": \"PE Corrected from Multiwell Flag\",\r\n \"PE_SYN\": \"PE Estimation from Ensemble of Learners\",\r\n \"RHOB_NCF\": \"Density No Correction Flag\",\r\n \"RHOB_CORR\": \"Density Corrected\",\r\n \"NPHI_NCF\": \"Neutron No Correction Flag\",\r\n \"NPHI_CORR\": \"Neutron Corrected\",\r\n \"DTC_NCF\": \"Sonic No Correction Flag\",\r\n \"DTC_CORR\": \"Sonic Corrected\",\r\n \"PE_NCF\": \"PE No Correction Flag\",\r\n \"PE_CORR\": \"PE Corrected\"\r\n}\r\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
import numpy as np
from sklearn import model_selection
from iterstrat.ml_stratifiers import MultilabelStratifiedKFold
"""
- binary cross-validate
- multi-class cross-validate
- multi-label cross-validate
- holdout
- regression
"""
class CrossValidate(object):
def __init__(self, df,
target_cols,
problem_type,
num_folds = 3,
shuffle = False,
random_state = 0):
"""
df - pandas dataframe
target_cols - list of targets
problem_type - ["binary", "multiclass", holdout_n, multilabel]
"""
self.dataframe = df
self.target_cols = target_cols
self.num_targets = len(target_cols)
self.problem_type = problem_type
self.shuffle = shuffle
self.num_folds = num_folds
self.random_state = random_state
if self.shuffle:
self.dataframe = self.dataframe.sample(frac = 1,
random_state = self.random_state).reset_index(drop = True)
self.dataframe["kfold"] = -1
def split(self):
if self.problem_type in ("binary", "multiclass"):
"""
target_cols - ['target_1']
unique_values - eg, [0, 1] for binary, [0, 1, 2,...] for multiclass
"""
if self.num_targets != 1:
raise Exception("Invalid number of targets for this problem type. \
Needed number of targets = 1")
target = self.target_cols[0]
unique_values = self.dataframe[target].nunique()
if unique_values == 1:
raise Exception("Only one unique value found! \
Must be two for Binary and Multiclass cross validation")
elif unique_values > 1:
kf = model_selection.StratifiedKFold(n_splits=self.num_folds,
shuffle = False)
for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.dataframe,
y=self.dataframe[target].values)):
self.dataframe.loc[val_idx, 'kfold'] = fold
elif self.problem_type == "multilabel":
"""
target_cols - ['target_1', 'target_2', 'target_3',....]
"""
if self.num_targets < 1:
raise Exception("Invalid number of targets for this problem type. \
Must be greater than 1.")
kf = MultilabelStratifiedKFold(n_splits=self.num_folds,
shuffle = False)
for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.dataframe,
y=self.dataframe[self.target_cols].values)):
self.dataframe.loc[val_idx, 'kfold'] = fold
elif self.problem_type in ("regression"):
kf = model_selection.KFold(n_splits=self.num_folds)
for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.dataframe)):
self.dataframe.loc[val_idx, 'kfold'] = fold
elif self.problem_type.startswith("holdout_"):
"""
1 : Training Set
0 : Validation Set
holdout_n : n% to holdout
"""
holdout_percentage = int(self.problem_type.split("_")[1])
num_holdout_samples = int(len(self.dataframe) * holdout_percentage / 100)
self.dataframe.loc[:len(self.dataframe) - num_holdout_samples, "kfold"] = 0
self.dataframe.loc[len(self.dataframe) - num_holdout_samples:, "kfold"] = 1
else:
raise Exception("Problem type not understood!")
return self.dataframe
|
normal
|
{
"blob_id": "0dad1937df39c012f7991c3897f27964bed1d5a0",
"index": 1533,
"step-1": "<mask token>\n\n\nclass CrossValidate(object):\n <mask token>\n <mask token>\n",
"step-2": "<mask token>\n\n\nclass CrossValidate(object):\n\n def __init__(self, df, target_cols, problem_type, num_folds=3, shuffle=\n False, random_state=0):\n \"\"\"\n df - pandas dataframe\n target_cols - list of targets\n problem_type - [\"binary\", \"multiclass\", holdout_n, multilabel]\n \"\"\"\n self.dataframe = df\n self.target_cols = target_cols\n self.num_targets = len(target_cols)\n self.problem_type = problem_type\n self.shuffle = shuffle\n self.num_folds = num_folds\n self.random_state = random_state\n if self.shuffle:\n self.dataframe = self.dataframe.sample(frac=1, random_state=\n self.random_state).reset_index(drop=True)\n self.dataframe['kfold'] = -1\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass CrossValidate(object):\n\n def __init__(self, df, target_cols, problem_type, num_folds=3, shuffle=\n False, random_state=0):\n \"\"\"\n df - pandas dataframe\n target_cols - list of targets\n problem_type - [\"binary\", \"multiclass\", holdout_n, multilabel]\n \"\"\"\n self.dataframe = df\n self.target_cols = target_cols\n self.num_targets = len(target_cols)\n self.problem_type = problem_type\n self.shuffle = shuffle\n self.num_folds = num_folds\n self.random_state = random_state\n if self.shuffle:\n self.dataframe = self.dataframe.sample(frac=1, random_state=\n self.random_state).reset_index(drop=True)\n self.dataframe['kfold'] = -1\n\n def split(self):\n if self.problem_type in ('binary', 'multiclass'):\n \"\"\"\n target_cols - ['target_1']\n unique_values - eg, [0, 1] for binary, [0, 1, 2,...] for multiclass\n \"\"\"\n if self.num_targets != 1:\n raise Exception(\n 'Invalid number of targets for this problem type. Needed number of targets = 1'\n )\n target = self.target_cols[0]\n unique_values = self.dataframe[target].nunique()\n if unique_values == 1:\n raise Exception(\n 'Only one unique value found! Must be two for Binary and Multiclass cross validation'\n )\n elif unique_values > 1:\n kf = model_selection.StratifiedKFold(n_splits=self.\n num_folds, shuffle=False)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self\n .dataframe, y=self.dataframe[target].values)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n elif self.problem_type == 'multilabel':\n \"\"\"\n target_cols - ['target_1', 'target_2', 'target_3',....]\n \"\"\"\n if self.num_targets < 1:\n raise Exception(\n 'Invalid number of targets for this problem type. Must be greater than 1.'\n )\n kf = MultilabelStratifiedKFold(n_splits=self.num_folds, shuffle\n =False)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.\n dataframe, y=self.dataframe[self.target_cols].values)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n elif self.problem_type in 'regression':\n kf = model_selection.KFold(n_splits=self.num_folds)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.\n dataframe)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n elif self.problem_type.startswith('holdout_'):\n \"\"\"\n 1 : Training Set\n 0 : Validation Set\n holdout_n : n% to holdout\n \"\"\"\n holdout_percentage = int(self.problem_type.split('_')[1])\n num_holdout_samples = int(len(self.dataframe) *\n holdout_percentage / 100)\n self.dataframe.loc[:len(self.dataframe) - num_holdout_samples,\n 'kfold'] = 0\n self.dataframe.loc[len(self.dataframe) - num_holdout_samples:,\n 'kfold'] = 1\n else:\n raise Exception('Problem type not understood!')\n return self.dataframe\n",
"step-4": "import numpy as np\nfrom sklearn import model_selection\nfrom iterstrat.ml_stratifiers import MultilabelStratifiedKFold\n<mask token>\n\n\nclass CrossValidate(object):\n\n def __init__(self, df, target_cols, problem_type, num_folds=3, shuffle=\n False, random_state=0):\n \"\"\"\n df - pandas dataframe\n target_cols - list of targets\n problem_type - [\"binary\", \"multiclass\", holdout_n, multilabel]\n \"\"\"\n self.dataframe = df\n self.target_cols = target_cols\n self.num_targets = len(target_cols)\n self.problem_type = problem_type\n self.shuffle = shuffle\n self.num_folds = num_folds\n self.random_state = random_state\n if self.shuffle:\n self.dataframe = self.dataframe.sample(frac=1, random_state=\n self.random_state).reset_index(drop=True)\n self.dataframe['kfold'] = -1\n\n def split(self):\n if self.problem_type in ('binary', 'multiclass'):\n \"\"\"\n target_cols - ['target_1']\n unique_values - eg, [0, 1] for binary, [0, 1, 2,...] for multiclass\n \"\"\"\n if self.num_targets != 1:\n raise Exception(\n 'Invalid number of targets for this problem type. Needed number of targets = 1'\n )\n target = self.target_cols[0]\n unique_values = self.dataframe[target].nunique()\n if unique_values == 1:\n raise Exception(\n 'Only one unique value found! Must be two for Binary and Multiclass cross validation'\n )\n elif unique_values > 1:\n kf = model_selection.StratifiedKFold(n_splits=self.\n num_folds, shuffle=False)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self\n .dataframe, y=self.dataframe[target].values)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n elif self.problem_type == 'multilabel':\n \"\"\"\n target_cols - ['target_1', 'target_2', 'target_3',....]\n \"\"\"\n if self.num_targets < 1:\n raise Exception(\n 'Invalid number of targets for this problem type. Must be greater than 1.'\n )\n kf = MultilabelStratifiedKFold(n_splits=self.num_folds, shuffle\n =False)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.\n dataframe, y=self.dataframe[self.target_cols].values)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n elif self.problem_type in 'regression':\n kf = model_selection.KFold(n_splits=self.num_folds)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.\n dataframe)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n elif self.problem_type.startswith('holdout_'):\n \"\"\"\n 1 : Training Set\n 0 : Validation Set\n holdout_n : n% to holdout\n \"\"\"\n holdout_percentage = int(self.problem_type.split('_')[1])\n num_holdout_samples = int(len(self.dataframe) *\n holdout_percentage / 100)\n self.dataframe.loc[:len(self.dataframe) - num_holdout_samples,\n 'kfold'] = 0\n self.dataframe.loc[len(self.dataframe) - num_holdout_samples:,\n 'kfold'] = 1\n else:\n raise Exception('Problem type not understood!')\n return self.dataframe\n",
"step-5": "import numpy as np\nfrom sklearn import model_selection\nfrom iterstrat.ml_stratifiers import MultilabelStratifiedKFold\n\n\"\"\"\n- binary cross-validate\n- multi-class cross-validate\n- multi-label cross-validate\n- holdout\n- regression\n\"\"\"\n\nclass CrossValidate(object):\n def __init__(self, df,\n target_cols,\n problem_type,\n num_folds = 3,\n shuffle = False,\n random_state = 0):\n \"\"\"\n df - pandas dataframe\n target_cols - list of targets\n problem_type - [\"binary\", \"multiclass\", holdout_n, multilabel]\n \"\"\"\n\n self.dataframe = df\n self.target_cols = target_cols\n self.num_targets = len(target_cols)\n self.problem_type = problem_type\n self.shuffle = shuffle\n self.num_folds = num_folds\n self.random_state = random_state\n\n if self.shuffle:\n self.dataframe = self.dataframe.sample(frac = 1,\n random_state = self.random_state).reset_index(drop = True)\n\n self.dataframe[\"kfold\"] = -1\n\n def split(self):\n if self.problem_type in (\"binary\", \"multiclass\"):\n \"\"\"\n target_cols - ['target_1']\n unique_values - eg, [0, 1] for binary, [0, 1, 2,...] for multiclass\n \"\"\"\n if self.num_targets != 1:\n raise Exception(\"Invalid number of targets for this problem type. \\\n Needed number of targets = 1\")\n target = self.target_cols[0]\n unique_values = self.dataframe[target].nunique()\n\n if unique_values == 1:\n raise Exception(\"Only one unique value found! \\\n Must be two for Binary and Multiclass cross validation\")\n elif unique_values > 1:\n kf = model_selection.StratifiedKFold(n_splits=self.num_folds,\n shuffle = False)\n\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.dataframe,\n y=self.dataframe[target].values)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n\n elif self.problem_type == \"multilabel\":\n \"\"\"\n target_cols - ['target_1', 'target_2', 'target_3',....]\n \"\"\"\n if self.num_targets < 1:\n raise Exception(\"Invalid number of targets for this problem type. \\\n Must be greater than 1.\")\n\n kf = MultilabelStratifiedKFold(n_splits=self.num_folds,\n shuffle = False)\n\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.dataframe,\n y=self.dataframe[self.target_cols].values)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n\n elif self.problem_type in (\"regression\"):\n kf = model_selection.KFold(n_splits=self.num_folds)\n for fold, (train_idx, val_idx) in enumerate(kf.split(X=self.dataframe)):\n self.dataframe.loc[val_idx, 'kfold'] = fold\n\n elif self.problem_type.startswith(\"holdout_\"):\n \"\"\"\n 1 : Training Set\n 0 : Validation Set\n holdout_n : n% to holdout\n \"\"\"\n holdout_percentage = int(self.problem_type.split(\"_\")[1])\n num_holdout_samples = int(len(self.dataframe) * holdout_percentage / 100)\n self.dataframe.loc[:len(self.dataframe) - num_holdout_samples, \"kfold\"] = 0\n self.dataframe.loc[len(self.dataframe) - num_holdout_samples:, \"kfold\"] = 1\n\n else:\n raise Exception(\"Problem type not understood!\")\n\n return self.dataframe\n",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
import pandas as pd
# read the data
df = pd.read_csv("data/lottery.csv")
# extract needed column
df1 = df[['1','2','3','4','5','6','bonus']]
# translate dataframe to list for convenience
df2 = df1.values.tolist()
# cnt_number is each number's apearance times
cnt_number = []
for i in range(0, 46):
cnt_number.append(0)
# count the appearnce times
for i in range(0, len(df2)):
for j in range(0, 7):
cnt_index = df2[i][j]
cnt_number[int(cnt_index)] += 1
# print the appearance times
for k in range(1, 46):
print('%5d -> %3d times'%(k, cnt_number[k]))
|
normal
|
{
"blob_id": "b257e36b3cb4bda28cf18e192aa95598105f5ae9",
"index": 2705,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(0, 46):\n cnt_number.append(0)\nfor i in range(0, len(df2)):\n for j in range(0, 7):\n cnt_index = df2[i][j]\n cnt_number[int(cnt_index)] += 1\nfor k in range(1, 46):\n print('%5d -> %3d times' % (k, cnt_number[k]))\n",
"step-3": "<mask token>\ndf = pd.read_csv('data/lottery.csv')\ndf1 = df[['1', '2', '3', '4', '5', '6', 'bonus']]\ndf2 = df1.values.tolist()\ncnt_number = []\nfor i in range(0, 46):\n cnt_number.append(0)\nfor i in range(0, len(df2)):\n for j in range(0, 7):\n cnt_index = df2[i][j]\n cnt_number[int(cnt_index)] += 1\nfor k in range(1, 46):\n print('%5d -> %3d times' % (k, cnt_number[k]))\n",
"step-4": "import pandas as pd\ndf = pd.read_csv('data/lottery.csv')\ndf1 = df[['1', '2', '3', '4', '5', '6', 'bonus']]\ndf2 = df1.values.tolist()\ncnt_number = []\nfor i in range(0, 46):\n cnt_number.append(0)\nfor i in range(0, len(df2)):\n for j in range(0, 7):\n cnt_index = df2[i][j]\n cnt_number[int(cnt_index)] += 1\nfor k in range(1, 46):\n print('%5d -> %3d times' % (k, cnt_number[k]))\n",
"step-5": "import pandas as pd\n\n# read the data\ndf = pd.read_csv(\"data/lottery.csv\")\n\n# extract needed column\ndf1 = df[['1','2','3','4','5','6','bonus']]\n\n# translate dataframe to list for convenience\ndf2 = df1.values.tolist()\n\n# cnt_number is each number's apearance times\ncnt_number = []\nfor i in range(0, 46):\n cnt_number.append(0)\n\n# count the appearnce times\nfor i in range(0, len(df2)):\n for j in range(0, 7):\n cnt_index = df2[i][j]\n cnt_number[int(cnt_index)] += 1\n\n# print the appearance times\nfor k in range(1, 46):\n print('%5d -> %3d times'%(k, cnt_number[k]))",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
'''a,b = input().split()
a, b = [int(a),int(b)]
List = set()
ArrayA = list(map(int, input().split()))
temp = 1
ArrayB = list(map(int, input().split()))
for i in range(max(ArrayA), min(ArrayB)+1):
for j in ArrayA:
if i%j is 1:
temp += 1
if temp is len(ArrayA):
List.add(i)
temp=1
newList = list(List)
temp = 1
newSet = set()
for i in newList:
for j in ArrayB:
if j%i==1:
temp+=1
if temp is len(ArrayB):
newSet.add(i)
temp=1
print(len(list(newSet)))
'''
'''nm = input().split( "-" )
a = (nm[1])
b = (nm[1])
print(nm)'''
'''x1, v1, x2, v2 = input().split()
x1, v1, x2, v2 = [int(x1),int(v1),int(x2),int(v2)]
if (x1<x2 and v1<v2) or (x2>x1 and v2>v1) or v1 is v2:
print("NO")
exit(1)
diff = 1
while True:
x1 += v1
x2 += v2
diff = x2 - x1
if diff < 1:
print("NO")
break
elif diff is 1:
print("YES")
break'''
#Graph Explaorartion
'''
import numpy as np
import matplotlib.pyplot as plt
N = 5
menMeans = (20, 35, 30, 35, 27)
menStd = (2, 3, 4, 1, 2)
ind = np.arange(N) # the x locations for the groups
width = 1.35 # the width of the bars
fig = plt.figure()
ax = fig.add_subplot(111)
rects1 = ax.bar(ind, menMeans, width, color='royalblue', yerr=menStd)
womenMeans = (25, 32, 34, 20, 25)
womenStd = (3, 5, 2, 3, 3)
rects2 = ax.bar(ind+width, womenMeans, width, color='seagreen', yerr=womenStd)
# add some
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind + width / 2)
ax.set_xticklabels( ('G1', 'G2', 'G3', 'G4', 'G5') )
ax.legend( (rects1[1], rects2[1]), ('Men', 'Women') )
plt.show()
'''
from math import gcd
# from functools import reduce
# for _ in range(int(input())):
# N = int(input())
# print(reduce(lambda x,y: x*y//gcd(x,y), range(1,N+1)))
import numpy as np
nk = input().split()
board = int(nk[0])
numberOfObs = int(nk[1])
roco = input().split()
obstacle = []
row = int(roco[0])
col = int(roco[1])
for _ in range(numberOfObs):
obs = input().split()
obstacle.append((int(obs[0]), int((obs[1]))))
#up
q = row
r = col
#down
s = row
t = col
#left
u = row
v = col
#right
w = row
x = col
#upper right
k = row
l = col
#lower left
i = row
j = col
#upperleft
m = row
n = col
#lower right
o = row
p = col
boxes = 0
while (1 <= q <= board) and (1 <= r <= board):
if (q, r) in obstacle:
break
else:
boxes += 1
q -= 1
while (1 <= s <= board) and (1 <= t <= board):
if (s, t) in obstacle:
break
else:
boxes += 1
s += 1
while (1 <= u <= board) and (1 <= v <= board):
if (u, v) in obstacle:
break
else:
boxes += 1
v -= 1
while (1 <= w <= board) and (1 <= x <= board):
if (w, x) in obstacle:
break
else:
boxes += 1
x += 1
while (1 <= o <= board) and (1 <= p <= board):
if (o, p) in obstacle:
break
else:
boxes += 1
o += 1
p += 1
while (1 <= m <= board) and (1 <= n <= board):
if (m, n) in obstacle:
break
else:
boxes += 1
m -= 1
n -= 1
while (1 <= k <= board) and (1 <= l <= board):
if (k, l) in obstacle:
break
else:
boxes += 1
k -= 1
l += 1
while (1 <= i <=board) and (1 <= j <= board):
if (i,j) in obstacle:
break
else:
boxes += 1
i += 1
j -= 1
print(boxes - 8)
|
normal
|
{
"blob_id": "73d02615863826d77d65fbf0314dc71acb97ef28",
"index": 4035,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor _ in range(numberOfObs):\n obs = input().split()\n obstacle.append((int(obs[0]), int(obs[1])))\n<mask token>\nwhile 1 <= q <= board and 1 <= r <= board:\n if (q, r) in obstacle:\n break\n else:\n boxes += 1\n q -= 1\nwhile 1 <= s <= board and 1 <= t <= board:\n if (s, t) in obstacle:\n break\n else:\n boxes += 1\n s += 1\nwhile 1 <= u <= board and 1 <= v <= board:\n if (u, v) in obstacle:\n break\n else:\n boxes += 1\n v -= 1\nwhile 1 <= w <= board and 1 <= x <= board:\n if (w, x) in obstacle:\n break\n else:\n boxes += 1\n x += 1\nwhile 1 <= o <= board and 1 <= p <= board:\n if (o, p) in obstacle:\n break\n else:\n boxes += 1\n o += 1\n p += 1\nwhile 1 <= m <= board and 1 <= n <= board:\n if (m, n) in obstacle:\n break\n else:\n boxes += 1\n m -= 1\n n -= 1\nwhile 1 <= k <= board and 1 <= l <= board:\n if (k, l) in obstacle:\n break\n else:\n boxes += 1\n k -= 1\n l += 1\nwhile 1 <= i <= board and 1 <= j <= board:\n if (i, j) in obstacle:\n break\n else:\n boxes += 1\n i += 1\n j -= 1\nprint(boxes - 8)\n",
"step-3": "<mask token>\nnk = input().split()\nboard = int(nk[0])\nnumberOfObs = int(nk[1])\nroco = input().split()\nobstacle = []\nrow = int(roco[0])\ncol = int(roco[1])\nfor _ in range(numberOfObs):\n obs = input().split()\n obstacle.append((int(obs[0]), int(obs[1])))\nq = row\nr = col\ns = row\nt = col\nu = row\nv = col\nw = row\nx = col\nk = row\nl = col\ni = row\nj = col\nm = row\nn = col\no = row\np = col\nboxes = 0\nwhile 1 <= q <= board and 1 <= r <= board:\n if (q, r) in obstacle:\n break\n else:\n boxes += 1\n q -= 1\nwhile 1 <= s <= board and 1 <= t <= board:\n if (s, t) in obstacle:\n break\n else:\n boxes += 1\n s += 1\nwhile 1 <= u <= board and 1 <= v <= board:\n if (u, v) in obstacle:\n break\n else:\n boxes += 1\n v -= 1\nwhile 1 <= w <= board and 1 <= x <= board:\n if (w, x) in obstacle:\n break\n else:\n boxes += 1\n x += 1\nwhile 1 <= o <= board and 1 <= p <= board:\n if (o, p) in obstacle:\n break\n else:\n boxes += 1\n o += 1\n p += 1\nwhile 1 <= m <= board and 1 <= n <= board:\n if (m, n) in obstacle:\n break\n else:\n boxes += 1\n m -= 1\n n -= 1\nwhile 1 <= k <= board and 1 <= l <= board:\n if (k, l) in obstacle:\n break\n else:\n boxes += 1\n k -= 1\n l += 1\nwhile 1 <= i <= board and 1 <= j <= board:\n if (i, j) in obstacle:\n break\n else:\n boxes += 1\n i += 1\n j -= 1\nprint(boxes - 8)\n",
"step-4": "<mask token>\nfrom math import gcd\nimport numpy as np\nnk = input().split()\nboard = int(nk[0])\nnumberOfObs = int(nk[1])\nroco = input().split()\nobstacle = []\nrow = int(roco[0])\ncol = int(roco[1])\nfor _ in range(numberOfObs):\n obs = input().split()\n obstacle.append((int(obs[0]), int(obs[1])))\nq = row\nr = col\ns = row\nt = col\nu = row\nv = col\nw = row\nx = col\nk = row\nl = col\ni = row\nj = col\nm = row\nn = col\no = row\np = col\nboxes = 0\nwhile 1 <= q <= board and 1 <= r <= board:\n if (q, r) in obstacle:\n break\n else:\n boxes += 1\n q -= 1\nwhile 1 <= s <= board and 1 <= t <= board:\n if (s, t) in obstacle:\n break\n else:\n boxes += 1\n s += 1\nwhile 1 <= u <= board and 1 <= v <= board:\n if (u, v) in obstacle:\n break\n else:\n boxes += 1\n v -= 1\nwhile 1 <= w <= board and 1 <= x <= board:\n if (w, x) in obstacle:\n break\n else:\n boxes += 1\n x += 1\nwhile 1 <= o <= board and 1 <= p <= board:\n if (o, p) in obstacle:\n break\n else:\n boxes += 1\n o += 1\n p += 1\nwhile 1 <= m <= board and 1 <= n <= board:\n if (m, n) in obstacle:\n break\n else:\n boxes += 1\n m -= 1\n n -= 1\nwhile 1 <= k <= board and 1 <= l <= board:\n if (k, l) in obstacle:\n break\n else:\n boxes += 1\n k -= 1\n l += 1\nwhile 1 <= i <= board and 1 <= j <= board:\n if (i, j) in obstacle:\n break\n else:\n boxes += 1\n i += 1\n j -= 1\nprint(boxes - 8)\n",
"step-5": "'''a,b = input().split()\na, b = [int(a),int(b)]\nList = set()\nArrayA = list(map(int, input().split()))\ntemp = 1\nArrayB = list(map(int, input().split()))\nfor i in range(max(ArrayA), min(ArrayB)+1):\n for j in ArrayA:\n if i%j is 1:\n temp += 1\n\n if temp is len(ArrayA):\n List.add(i)\n temp=1\nnewList = list(List)\ntemp = 1\nnewSet = set()\nfor i in newList:\n for j in ArrayB:\n if j%i==1:\n temp+=1\n if temp is len(ArrayB):\n newSet.add(i)\n temp=1\n\nprint(len(list(newSet)))\n'''\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n'''nm = input().split( \"-\" )\na = (nm[1])\nb = (nm[1])\nprint(nm)'''\n\n\n\n\n\n\n\n'''x1, v1, x2, v2 = input().split()\nx1, v1, x2, v2 = [int(x1),int(v1),int(x2),int(v2)]\nif (x1<x2 and v1<v2) or (x2>x1 and v2>v1) or v1 is v2:\n print(\"NO\")\n exit(1)\ndiff = 1\nwhile True:\n x1 += v1\n x2 += v2\n diff = x2 - x1\n if diff < 1:\n print(\"NO\")\n break\n elif diff is 1:\n print(\"YES\")\n break'''\n#Graph Explaorartion\n'''\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nN = 5\nmenMeans = (20, 35, 30, 35, 27)\nmenStd = (2, 3, 4, 1, 2)\n\nind = np.arange(N) # the x locations for the groups\nwidth = 1.35 # the width of the bars\n\nfig = plt.figure()\nax = fig.add_subplot(111)\nrects1 = ax.bar(ind, menMeans, width, color='royalblue', yerr=menStd)\n\nwomenMeans = (25, 32, 34, 20, 25)\nwomenStd = (3, 5, 2, 3, 3)\nrects2 = ax.bar(ind+width, womenMeans, width, color='seagreen', yerr=womenStd)\n\n# add some\nax.set_ylabel('Scores')\nax.set_title('Scores by group and gender')\nax.set_xticks(ind + width / 2)\nax.set_xticklabels( ('G1', 'G2', 'G3', 'G4', 'G5') )\n\nax.legend( (rects1[1], rects2[1]), ('Men', 'Women') )\n\nplt.show()\n'''\nfrom math import gcd\n# from functools import reduce\n\n# for _ in range(int(input())):\n# N = int(input())\n# print(reduce(lambda x,y: x*y//gcd(x,y), range(1,N+1)))\nimport numpy as np\nnk = input().split()\nboard = int(nk[0])\nnumberOfObs = int(nk[1])\nroco = input().split()\nobstacle = []\nrow = int(roco[0])\ncol = int(roco[1])\nfor _ in range(numberOfObs):\n obs = input().split()\n obstacle.append((int(obs[0]), int((obs[1]))))\n#up\nq = row\nr = col\n#down\ns = row\nt = col\n#left\nu = row\nv = col\n#right\nw = row\nx = col\n#upper right\nk = row\nl = col\n#lower left\ni = row\nj = col\n#upperleft\nm = row\nn = col\n#lower right\no = row\np = col\nboxes = 0\nwhile (1 <= q <= board) and (1 <= r <= board):\n if (q, r) in obstacle:\n break\n else:\n boxes += 1\n q -= 1\nwhile (1 <= s <= board) and (1 <= t <= board):\n if (s, t) in obstacle:\n break\n else:\n\n\n boxes += 1\n s += 1\nwhile (1 <= u <= board) and (1 <= v <= board):\n if (u, v) in obstacle:\n break\n else:\n\n boxes += 1\n v -= 1\nwhile (1 <= w <= board) and (1 <= x <= board):\n if (w, x) in obstacle:\n break\n else:\n\n boxes += 1\n x += 1\nwhile (1 <= o <= board) and (1 <= p <= board):\n if (o, p) in obstacle:\n break\n else:\n\n boxes += 1\n o += 1\n p += 1\nwhile (1 <= m <= board) and (1 <= n <= board):\n if (m, n) in obstacle:\n break\n else:\n\n boxes += 1\n m -= 1\n n -= 1\nwhile (1 <= k <= board) and (1 <= l <= board):\n if (k, l) in obstacle:\n break\n else:\n\n boxes += 1\n k -= 1\n l += 1\nwhile (1 <= i <=board) and (1 <= j <= board):\n if (i,j) in obstacle:\n break\n else:\n boxes += 1\n i += 1\n j -= 1\nprint(boxes - 8)\n\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
from setuptools import Command
class decl_cmd1(Command):
user_options = []
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
pass
class decl_cmd2(Command):
user_options = []
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
pass
|
normal
|
{
"blob_id": "70b8efa844395592131382d1d1e2c39150804f99",
"index": 4111,
"step-1": "<mask token>\n\n\nclass decl_cmd1(Command):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass decl_cmd2(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n",
"step-2": "<mask token>\n\n\nclass decl_cmd1(Command):\n <mask token>\n <mask token>\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n\n\nclass decl_cmd2(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n",
"step-3": "<mask token>\n\n\nclass decl_cmd1(Command):\n <mask token>\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n\n\nclass decl_cmd2(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n",
"step-4": "<mask token>\n\n\nclass decl_cmd1(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n\n\nclass decl_cmd2(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n",
"step-5": "from setuptools import Command\n\n\nclass decl_cmd1(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n\n\nclass decl_cmd2(Command):\n user_options = []\n\n def initialize_options(self):\n pass\n\n def finalize_options(self):\n pass\n\n def run(self):\n pass\n",
"step-ids": [
6,
8,
9,
10,
11
]
}
|
[
6,
8,
9,
10,
11
] |
from django.contrib import admin
from employees.models import Leave,EmployeeProfile
admin.site.register(Leave)
admin.site.register(EmployeeProfile)
# Register your models here.
|
normal
|
{
"blob_id": "77ea670b537e9ff7082aeb9ed54b011fa8e3a035",
"index": 6328,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nadmin.site.register(Leave)\nadmin.site.register(EmployeeProfile)\n",
"step-3": "from django.contrib import admin\nfrom employees.models import Leave, EmployeeProfile\nadmin.site.register(Leave)\nadmin.site.register(EmployeeProfile)\n",
"step-4": "from django.contrib import admin\r\nfrom employees.models import Leave,EmployeeProfile\r\n\r\nadmin.site.register(Leave)\r\nadmin.site.register(EmployeeProfile)\r\n# Register your models here.\r\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Matching:
<|reserved_special_token_0|>
<|reserved_special_token_0|>
@staticmethod
def process_order(self, order: Order):
if order.status == Order.STATUS_WAITING_NEW:
order.status = Order.STATUS_NEW
order.save()
if order.price == 0:
Matching.take(order)
order.status = Order.STATUS_FILLED
order.save()
if order.price != 0:
Matching.take(order)
class TestOrder(TestCase):
def setUp(self) ->None:
self.ticker1 = Ticker.objects.create(name='USD')
self.ticker2 = Ticker.objects.create(name='EUR')
self.market = Market.objects.create(name='USD/EUR', base_currency=
self.ticker1, quote_currency=self.ticker2)
self.Alice = USER_MODEL.objects.create_user(username='Alice', email
='alice@yy.ru', password='hhhh')
self.Bob = USER_MODEL.objects.create_user(username='Bob', email=
'bob@yy.ru', password='hhhh')
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,
price=10000 + i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,
price=10000 - i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(2):
Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,
price=0, size=100000 + i * 10000, filled=0, status=Order.
STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)
def test_market_exists(self):
assert Market.objects.all().count() == 1
def test_orders_created(self):
print('---BID----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):
print(order.price, order.size)
print('---ASK----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):
print(order.price, order.size)
def test_get_level_1(self):
bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,
status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(
'-price')
ask = Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0
).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
print(f'Bid {bid_price} Ask {ask_price}')
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Matching:
@staticmethod
def get_bid_ask(market: Market):
bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[
Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')
ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[
Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
return bid_price, ask_price
<|reserved_special_token_0|>
@staticmethod
def process_order(self, order: Order):
if order.status == Order.STATUS_WAITING_NEW:
order.status = Order.STATUS_NEW
order.save()
if order.price == 0:
Matching.take(order)
order.status = Order.STATUS_FILLED
order.save()
if order.price != 0:
Matching.take(order)
class TestOrder(TestCase):
def setUp(self) ->None:
self.ticker1 = Ticker.objects.create(name='USD')
self.ticker2 = Ticker.objects.create(name='EUR')
self.market = Market.objects.create(name='USD/EUR', base_currency=
self.ticker1, quote_currency=self.ticker2)
self.Alice = USER_MODEL.objects.create_user(username='Alice', email
='alice@yy.ru', password='hhhh')
self.Bob = USER_MODEL.objects.create_user(username='Bob', email=
'bob@yy.ru', password='hhhh')
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,
price=10000 + i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,
price=10000 - i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(2):
Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,
price=0, size=100000 + i * 10000, filled=0, status=Order.
STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)
def test_market_exists(self):
assert Market.objects.all().count() == 1
def test_orders_created(self):
print('---BID----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):
print(order.price, order.size)
print('---ASK----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):
print(order.price, order.size)
def test_get_level_1(self):
bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,
status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(
'-price')
ask = Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0
).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
print(f'Bid {bid_price} Ask {ask_price}')
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Matching:
@staticmethod
def get_bid_ask(market: Market):
bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[
Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')
ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[
Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
return bid_price, ask_price
@staticmethod
def take(order: Order):
depth = []
if order.side == Order.SIDES_SELL:
depth = order.market.order_set.filter(side=Order.SIDES_BUY,
status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')
if order.side == Order.SIDES_BUY:
depth = order.market.order_set.filter(side=Order.SIDES_SELL,
status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')
for o in depth:
if (order.side == Order.SIDES_SELL and order.price != 0 and
order.price > o.price or order.side == Order.SIDES_BUY and
order.price != 0 and order.price < o.price):
break
if order.size - order.filled > o.size - o.filled:
fill_size = o.size - o.filled
else:
fill_size = order.size - order.filled
o.fill(fill_size)
order.fill(fill_size)
o.save()
order.save()
if order.side == Order.SIDES_SELL:
order_buy = o
order_sell = order
else:
order_buy = order
order_sell = o
Trade.objects.create(order_buy=order_buy, order_sell=order_sell,
price=o.price, side=order.side)
if order.status == Order.STATUS_FILLED:
break
@staticmethod
def process_order(self, order: Order):
if order.status == Order.STATUS_WAITING_NEW:
order.status = Order.STATUS_NEW
order.save()
if order.price == 0:
Matching.take(order)
order.status = Order.STATUS_FILLED
order.save()
if order.price != 0:
Matching.take(order)
class TestOrder(TestCase):
def setUp(self) ->None:
self.ticker1 = Ticker.objects.create(name='USD')
self.ticker2 = Ticker.objects.create(name='EUR')
self.market = Market.objects.create(name='USD/EUR', base_currency=
self.ticker1, quote_currency=self.ticker2)
self.Alice = USER_MODEL.objects.create_user(username='Alice', email
='alice@yy.ru', password='hhhh')
self.Bob = USER_MODEL.objects.create_user(username='Bob', email=
'bob@yy.ru', password='hhhh')
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,
price=10000 + i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,
price=10000 - i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(2):
Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,
price=0, size=100000 + i * 10000, filled=0, status=Order.
STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)
def test_market_exists(self):
assert Market.objects.all().count() == 1
def test_orders_created(self):
print('---BID----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):
print(order.price, order.size)
print('---ASK----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):
print(order.price, order.size)
def test_get_level_1(self):
bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,
status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(
'-price')
ask = Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0
).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
print(f'Bid {bid_price} Ask {ask_price}')
<|reserved_special_token_1|>
from django.contrib.auth import get_user_model
from django.test import TestCase
from .models import Order
from markets.models import Market
from tickers.models import Ticker
from trades.models import Trade
USER_MODEL = get_user_model()
class Matching:
@staticmethod
def get_bid_ask(market: Market):
bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[
Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')
ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[
Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
return bid_price, ask_price
@staticmethod
def take(order: Order):
depth = []
if order.side == Order.SIDES_SELL:
depth = order.market.order_set.filter(side=Order.SIDES_BUY,
status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')
if order.side == Order.SIDES_BUY:
depth = order.market.order_set.filter(side=Order.SIDES_SELL,
status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.
STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')
for o in depth:
if (order.side == Order.SIDES_SELL and order.price != 0 and
order.price > o.price or order.side == Order.SIDES_BUY and
order.price != 0 and order.price < o.price):
break
if order.size - order.filled > o.size - o.filled:
fill_size = o.size - o.filled
else:
fill_size = order.size - order.filled
o.fill(fill_size)
order.fill(fill_size)
o.save()
order.save()
if order.side == Order.SIDES_SELL:
order_buy = o
order_sell = order
else:
order_buy = order
order_sell = o
Trade.objects.create(order_buy=order_buy, order_sell=order_sell,
price=o.price, side=order.side)
if order.status == Order.STATUS_FILLED:
break
@staticmethod
def process_order(self, order: Order):
if order.status == Order.STATUS_WAITING_NEW:
order.status = Order.STATUS_NEW
order.save()
if order.price == 0:
Matching.take(order)
order.status = Order.STATUS_FILLED
order.save()
if order.price != 0:
Matching.take(order)
class TestOrder(TestCase):
def setUp(self) ->None:
self.ticker1 = Ticker.objects.create(name='USD')
self.ticker2 = Ticker.objects.create(name='EUR')
self.market = Market.objects.create(name='USD/EUR', base_currency=
self.ticker1, quote_currency=self.ticker2)
self.Alice = USER_MODEL.objects.create_user(username='Alice', email
='alice@yy.ru', password='hhhh')
self.Bob = USER_MODEL.objects.create_user(username='Bob', email=
'bob@yy.ru', password='hhhh')
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,
price=10000 + i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(20):
Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,
price=10000 - i * 100, size=100000 + i * 10000, filled=0,
status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',
market=self.market)
for i in range(2):
Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,
price=0, size=100000 + i * 10000, filled=0, status=Order.
STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)
def test_market_exists(self):
assert Market.objects.all().count() == 1
def test_orders_created(self):
print('---BID----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):
print(order.price, order.size)
print('---ASK----')
for order in Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):
print(order.price, order.size)
def test_get_level_1(self):
bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,
status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(
'-price')
ask = Market.objects.all()[0].order_set.filter(side=Order.
SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0
).order_by('price')
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
print(f'Bid {bid_price} Ask {ask_price}')
<|reserved_special_token_1|>
from django.contrib.auth import get_user_model
from django.test import TestCase
from .models import Order
from markets.models import Market
from tickers.models import Ticker
from trades.models import Trade
USER_MODEL = get_user_model()
class Matching:
@staticmethod
def get_bid_ask( market : Market):
bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by("-price")
ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by("price")
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
return bid_price, ask_price
@staticmethod
def take(order: Order):
depth = []
if order.side == Order.SIDES_SELL:
depth = order.market.order_set.filter(side=Order.SIDES_BUY, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by("-price")
if order.side == Order.SIDES_BUY:
depth = order.market.order_set.filter(side=Order.SIDES_SELL, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by("price")
for o in depth:
if (order.side == Order.SIDES_SELL and order.price != 0 and order.price > o.price) or (order.side == Order.SIDES_BUY and order.price != 0 and order.price < o.price):
break
if order.size - order.filled > o.size - o.filled:
fill_size = o.size - o.filled
else:
fill_size = order.size - order.filled
o.fill( fill_size )
order.fill( fill_size )
o.save()
order.save()
if order.side == Order.SIDES_SELL:
order_buy = o
order_sell = order
else:
order_buy = order
order_sell = o
# Creating trade object
Trade.objects.create(order_buy=order_buy, order_sell=order_sell, price=o.price,side=order.side)
if order.status == Order.STATUS_FILLED:
break
@staticmethod
def process_order(self, order: Order ):
if order.status == Order.STATUS_WAITING_NEW:
order.status = Order.STATUS_NEW
order.save()
# best_bid_price, best_ask_price = self.get_bid_ask(order.market)
if order.price == 0:
Matching.take(order)
order.status = Order.STATUS_FILLED
order.save()
if order.price != 0:
Matching.take(order)
class TestOrder(TestCase):
def setUp(self) -> None:
self.ticker1 = Ticker.objects.create(name="USD")
self.ticker2 = Ticker.objects.create(name="EUR")
self.market = Market.objects.create(name="USD/EUR",
base_currency=self.ticker1,
quote_currency=self.ticker2)
self.Alice = USER_MODEL.objects.create_user(username="Alice", email="alice@yy.ru", password="hhhh")
self.Bob = USER_MODEL.objects.create_user(username="Bob", email="bob@yy.ru", password="hhhh")
# Creating Alice orders
for i in range(20):
Order.objects.create(sender=self.Alice,
side=Order.SIDES_SELL,
price=10000 + i*100,
size=100000+i*10000,
filled=0,
status=Order.STATUS_WAITING_NEW,
hash_signature="SIGA",
market=self.market)
# Creating Alice orders
for i in range(20):
Order.objects.create(sender=self.Alice,
side=Order.SIDES_BUY,
price=10000 - i*100,
size=100000+i*10000,
filled=0,
status=Order.STATUS_WAITING_NEW,
hash_signature="SIGA",
market=self.market)
# Creating Bob orders
for i in range(2):
Order.objects.create(sender=self.Bob,
side=Order.SIDES_BUY,
price=0,
size=100000+i*10000,
filled=0,
status=Order.STATUS_WAITING_NEW,
hash_signature="SIGA",
market=self.market)
def test_market_exists(self):
assert Market.objects.all().count() == 1
def test_orders_created(self):
#assert Market.objects.all()[0].order_set.count() == 40
print("---BID----")
for order in Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY).exclude(price=0).order_by("-price", "created_at"):
print(order.price, order.size)
print("---ASK----")
for order in Market.objects.all()[0].order_set.filter(side=Order.SIDES_SELL).exclude(price=0).order_by("price", "created_at"):
print(order.price, order.size)
def test_get_level_1(self):
bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by("-price")
ask = Market.objects.all()[0].order_set.filter(side=Order.SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by("price")
bid_price = None
ask_price = None
if len(bid) > 0:
bid_price = bid[0].price
if len(ask) > 0:
ask_price = ask[0].price
print(f'Bid {bid_price} Ask {ask_price}')
|
flexible
|
{
"blob_id": "866ee2c4fa52bf9bda4730c7a9d46bb4798adcd4",
"index": 1775,
"step-1": "<mask token>\n\n\nclass Matching:\n <mask token>\n <mask token>\n\n @staticmethod\n def process_order(self, order: Order):\n if order.status == Order.STATUS_WAITING_NEW:\n order.status = Order.STATUS_NEW\n order.save()\n if order.price == 0:\n Matching.take(order)\n order.status = Order.STATUS_FILLED\n order.save()\n if order.price != 0:\n Matching.take(order)\n\n\nclass TestOrder(TestCase):\n\n def setUp(self) ->None:\n self.ticker1 = Ticker.objects.create(name='USD')\n self.ticker2 = Ticker.objects.create(name='EUR')\n self.market = Market.objects.create(name='USD/EUR', base_currency=\n self.ticker1, quote_currency=self.ticker2)\n self.Alice = USER_MODEL.objects.create_user(username='Alice', email\n ='alice@yy.ru', password='hhhh')\n self.Bob = USER_MODEL.objects.create_user(username='Bob', email=\n 'bob@yy.ru', password='hhhh')\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,\n price=10000 + i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,\n price=10000 - i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(2):\n Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,\n price=0, size=100000 + i * 10000, filled=0, status=Order.\n STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)\n\n def test_market_exists(self):\n assert Market.objects.all().count() == 1\n\n def test_orders_created(self):\n print('---BID----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):\n print(order.price, order.size)\n print('---ASK----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):\n print(order.price, order.size)\n\n def test_get_level_1(self):\n bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,\n status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(\n '-price')\n ask = Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0\n ).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n print(f'Bid {bid_price} Ask {ask_price}')\n",
"step-2": "<mask token>\n\n\nclass Matching:\n\n @staticmethod\n def get_bid_ask(market: Market):\n bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[\n Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')\n ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[\n Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n return bid_price, ask_price\n <mask token>\n\n @staticmethod\n def process_order(self, order: Order):\n if order.status == Order.STATUS_WAITING_NEW:\n order.status = Order.STATUS_NEW\n order.save()\n if order.price == 0:\n Matching.take(order)\n order.status = Order.STATUS_FILLED\n order.save()\n if order.price != 0:\n Matching.take(order)\n\n\nclass TestOrder(TestCase):\n\n def setUp(self) ->None:\n self.ticker1 = Ticker.objects.create(name='USD')\n self.ticker2 = Ticker.objects.create(name='EUR')\n self.market = Market.objects.create(name='USD/EUR', base_currency=\n self.ticker1, quote_currency=self.ticker2)\n self.Alice = USER_MODEL.objects.create_user(username='Alice', email\n ='alice@yy.ru', password='hhhh')\n self.Bob = USER_MODEL.objects.create_user(username='Bob', email=\n 'bob@yy.ru', password='hhhh')\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,\n price=10000 + i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,\n price=10000 - i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(2):\n Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,\n price=0, size=100000 + i * 10000, filled=0, status=Order.\n STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)\n\n def test_market_exists(self):\n assert Market.objects.all().count() == 1\n\n def test_orders_created(self):\n print('---BID----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):\n print(order.price, order.size)\n print('---ASK----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):\n print(order.price, order.size)\n\n def test_get_level_1(self):\n bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,\n status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(\n '-price')\n ask = Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0\n ).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n print(f'Bid {bid_price} Ask {ask_price}')\n",
"step-3": "<mask token>\n\n\nclass Matching:\n\n @staticmethod\n def get_bid_ask(market: Market):\n bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[\n Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')\n ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[\n Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n return bid_price, ask_price\n\n @staticmethod\n def take(order: Order):\n depth = []\n if order.side == Order.SIDES_SELL:\n depth = order.market.order_set.filter(side=Order.SIDES_BUY,\n status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')\n if order.side == Order.SIDES_BUY:\n depth = order.market.order_set.filter(side=Order.SIDES_SELL,\n status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')\n for o in depth:\n if (order.side == Order.SIDES_SELL and order.price != 0 and \n order.price > o.price or order.side == Order.SIDES_BUY and \n order.price != 0 and order.price < o.price):\n break\n if order.size - order.filled > o.size - o.filled:\n fill_size = o.size - o.filled\n else:\n fill_size = order.size - order.filled\n o.fill(fill_size)\n order.fill(fill_size)\n o.save()\n order.save()\n if order.side == Order.SIDES_SELL:\n order_buy = o\n order_sell = order\n else:\n order_buy = order\n order_sell = o\n Trade.objects.create(order_buy=order_buy, order_sell=order_sell,\n price=o.price, side=order.side)\n if order.status == Order.STATUS_FILLED:\n break\n\n @staticmethod\n def process_order(self, order: Order):\n if order.status == Order.STATUS_WAITING_NEW:\n order.status = Order.STATUS_NEW\n order.save()\n if order.price == 0:\n Matching.take(order)\n order.status = Order.STATUS_FILLED\n order.save()\n if order.price != 0:\n Matching.take(order)\n\n\nclass TestOrder(TestCase):\n\n def setUp(self) ->None:\n self.ticker1 = Ticker.objects.create(name='USD')\n self.ticker2 = Ticker.objects.create(name='EUR')\n self.market = Market.objects.create(name='USD/EUR', base_currency=\n self.ticker1, quote_currency=self.ticker2)\n self.Alice = USER_MODEL.objects.create_user(username='Alice', email\n ='alice@yy.ru', password='hhhh')\n self.Bob = USER_MODEL.objects.create_user(username='Bob', email=\n 'bob@yy.ru', password='hhhh')\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,\n price=10000 + i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,\n price=10000 - i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(2):\n Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,\n price=0, size=100000 + i * 10000, filled=0, status=Order.\n STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)\n\n def test_market_exists(self):\n assert Market.objects.all().count() == 1\n\n def test_orders_created(self):\n print('---BID----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):\n print(order.price, order.size)\n print('---ASK----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):\n print(order.price, order.size)\n\n def test_get_level_1(self):\n bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,\n status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(\n '-price')\n ask = Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0\n ).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n print(f'Bid {bid_price} Ask {ask_price}')\n",
"step-4": "from django.contrib.auth import get_user_model\nfrom django.test import TestCase\nfrom .models import Order\nfrom markets.models import Market\nfrom tickers.models import Ticker\nfrom trades.models import Trade\nUSER_MODEL = get_user_model()\n\n\nclass Matching:\n\n @staticmethod\n def get_bid_ask(market: Market):\n bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[\n Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')\n ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[\n Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n return bid_price, ask_price\n\n @staticmethod\n def take(order: Order):\n depth = []\n if order.side == Order.SIDES_SELL:\n depth = order.market.order_set.filter(side=Order.SIDES_BUY,\n status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('-price')\n if order.side == Order.SIDES_BUY:\n depth = order.market.order_set.filter(side=Order.SIDES_SELL,\n status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.\n STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by('price')\n for o in depth:\n if (order.side == Order.SIDES_SELL and order.price != 0 and \n order.price > o.price or order.side == Order.SIDES_BUY and \n order.price != 0 and order.price < o.price):\n break\n if order.size - order.filled > o.size - o.filled:\n fill_size = o.size - o.filled\n else:\n fill_size = order.size - order.filled\n o.fill(fill_size)\n order.fill(fill_size)\n o.save()\n order.save()\n if order.side == Order.SIDES_SELL:\n order_buy = o\n order_sell = order\n else:\n order_buy = order\n order_sell = o\n Trade.objects.create(order_buy=order_buy, order_sell=order_sell,\n price=o.price, side=order.side)\n if order.status == Order.STATUS_FILLED:\n break\n\n @staticmethod\n def process_order(self, order: Order):\n if order.status == Order.STATUS_WAITING_NEW:\n order.status = Order.STATUS_NEW\n order.save()\n if order.price == 0:\n Matching.take(order)\n order.status = Order.STATUS_FILLED\n order.save()\n if order.price != 0:\n Matching.take(order)\n\n\nclass TestOrder(TestCase):\n\n def setUp(self) ->None:\n self.ticker1 = Ticker.objects.create(name='USD')\n self.ticker2 = Ticker.objects.create(name='EUR')\n self.market = Market.objects.create(name='USD/EUR', base_currency=\n self.ticker1, quote_currency=self.ticker2)\n self.Alice = USER_MODEL.objects.create_user(username='Alice', email\n ='alice@yy.ru', password='hhhh')\n self.Bob = USER_MODEL.objects.create_user(username='Bob', email=\n 'bob@yy.ru', password='hhhh')\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_SELL,\n price=10000 + i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(20):\n Order.objects.create(sender=self.Alice, side=Order.SIDES_BUY,\n price=10000 - i * 100, size=100000 + i * 10000, filled=0,\n status=Order.STATUS_WAITING_NEW, hash_signature='SIGA',\n market=self.market)\n for i in range(2):\n Order.objects.create(sender=self.Bob, side=Order.SIDES_BUY,\n price=0, size=100000 + i * 10000, filled=0, status=Order.\n STATUS_WAITING_NEW, hash_signature='SIGA', market=self.market)\n\n def test_market_exists(self):\n assert Market.objects.all().count() == 1\n\n def test_orders_created(self):\n print('---BID----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_BUY).exclude(price=0).order_by('-price', 'created_at'):\n print(order.price, order.size)\n print('---ASK----')\n for order in Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL).exclude(price=0).order_by('price', 'created_at'):\n print(order.price, order.size)\n\n def test_get_level_1(self):\n bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY,\n status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(\n '-price')\n ask = Market.objects.all()[0].order_set.filter(side=Order.\n SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0\n ).order_by('price')\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n print(f'Bid {bid_price} Ask {ask_price}')\n",
"step-5": "from django.contrib.auth import get_user_model\nfrom django.test import TestCase\n\nfrom .models import Order\nfrom markets.models import Market\nfrom tickers.models import Ticker\nfrom trades.models import Trade\n\n\nUSER_MODEL = get_user_model()\n\n\nclass Matching:\n @staticmethod\n def get_bid_ask( market : Market):\n bid = market.order_set.filter(side=Order.SIDES_BUY, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by(\"-price\")\n ask = market.order_set.filter(side=Order.SIDES_SELL, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by(\"price\")\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n\n return bid_price, ask_price\n\n @staticmethod\n def take(order: Order):\n depth = []\n if order.side == Order.SIDES_SELL:\n depth = order.market.order_set.filter(side=Order.SIDES_BUY, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by(\"-price\")\n if order.side == Order.SIDES_BUY:\n depth = order.market.order_set.filter(side=Order.SIDES_SELL, status__in=[Order.STATUS_NEW, Order.STATUS_UPDATED, Order.STATUS_PARTIALLUY_FILLED]).exclude(price=0).order_by(\"price\")\n for o in depth:\n if (order.side == Order.SIDES_SELL and order.price != 0 and order.price > o.price) or (order.side == Order.SIDES_BUY and order.price != 0 and order.price < o.price):\n break\n if order.size - order.filled > o.size - o.filled:\n fill_size = o.size - o.filled\n else:\n fill_size = order.size - order.filled\n o.fill( fill_size )\n order.fill( fill_size )\n o.save()\n order.save()\n if order.side == Order.SIDES_SELL:\n order_buy = o\n order_sell = order\n else:\n order_buy = order\n order_sell = o\n\n # Creating trade object\n Trade.objects.create(order_buy=order_buy, order_sell=order_sell, price=o.price,side=order.side)\n\n if order.status == Order.STATUS_FILLED:\n break\n\n @staticmethod\n def process_order(self, order: Order ):\n if order.status == Order.STATUS_WAITING_NEW:\n order.status = Order.STATUS_NEW\n order.save()\n\n# best_bid_price, best_ask_price = self.get_bid_ask(order.market)\n if order.price == 0:\n Matching.take(order)\n order.status = Order.STATUS_FILLED\n order.save()\n if order.price != 0:\n Matching.take(order)\n\n\n\n\nclass TestOrder(TestCase):\n\n def setUp(self) -> None:\n self.ticker1 = Ticker.objects.create(name=\"USD\")\n self.ticker2 = Ticker.objects.create(name=\"EUR\")\n self.market = Market.objects.create(name=\"USD/EUR\",\n base_currency=self.ticker1,\n quote_currency=self.ticker2)\n\n self.Alice = USER_MODEL.objects.create_user(username=\"Alice\", email=\"alice@yy.ru\", password=\"hhhh\")\n self.Bob = USER_MODEL.objects.create_user(username=\"Bob\", email=\"bob@yy.ru\", password=\"hhhh\")\n\n # Creating Alice orders\n for i in range(20):\n Order.objects.create(sender=self.Alice,\n side=Order.SIDES_SELL,\n price=10000 + i*100,\n size=100000+i*10000,\n filled=0,\n status=Order.STATUS_WAITING_NEW,\n hash_signature=\"SIGA\",\n market=self.market)\n\n # Creating Alice orders\n for i in range(20):\n Order.objects.create(sender=self.Alice,\n side=Order.SIDES_BUY,\n price=10000 - i*100,\n size=100000+i*10000,\n filled=0,\n status=Order.STATUS_WAITING_NEW,\n hash_signature=\"SIGA\",\n market=self.market)\n\n # Creating Bob orders\n for i in range(2):\n Order.objects.create(sender=self.Bob,\n side=Order.SIDES_BUY,\n price=0,\n size=100000+i*10000,\n filled=0,\n status=Order.STATUS_WAITING_NEW,\n hash_signature=\"SIGA\",\n market=self.market)\n\n\n def test_market_exists(self):\n assert Market.objects.all().count() == 1\n\n def test_orders_created(self):\n #assert Market.objects.all()[0].order_set.count() == 40\n print(\"---BID----\")\n for order in Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY).exclude(price=0).order_by(\"-price\", \"created_at\"):\n print(order.price, order.size)\n\n print(\"---ASK----\")\n for order in Market.objects.all()[0].order_set.filter(side=Order.SIDES_SELL).exclude(price=0).order_by(\"price\", \"created_at\"):\n print(order.price, order.size)\n\n\n\n def test_get_level_1(self):\n bid = Market.objects.all()[0].order_set.filter(side=Order.SIDES_BUY, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(\"-price\")\n ask = Market.objects.all()[0].order_set.filter(side=Order.SIDES_SELL, status__in=[Order.STATUS_WAITING_NEW]).exclude(price=0).order_by(\"price\")\n bid_price = None\n ask_price = None\n if len(bid) > 0:\n bid_price = bid[0].price\n if len(ask) > 0:\n ask_price = ask[0].price\n\n print(f'Bid {bid_price} Ask {ask_price}')\n\n",
"step-ids": [
7,
8,
9,
11,
12
]
}
|
[
7,
8,
9,
11,
12
] |
s = 'ejp mysljylc kd kxveddknmc re jsicpdrysirbcpc ypc rtcsra dkh wyfrepkym veddknkmkrkcdde kr kd eoya kw aej tysr re ujdr lkgc jv'
sa = 'our language is impossible to understandthere are twenty six factorial possibilitiesso it is okay if you want to just give up'
ans = {}
for i in range(len(s)):
ans[s[i]] = sa[i];
S = set([])
for k in ans:
S.add(k)
#for w in range(26):
# if chr(w+97) not in S:
# print chr(w+97)
# q and z not in input so they must map to each other
ans['q'] = 'z'
ans['z'] = 'q'
f = open('A-small-attempt0.in', 'r')
L = f.readlines()
tc = 0
for i in range(1, len(L)):
s = L[i]
S = ''
for j in range(len(s)):
if s[j] == '\n':
continue
S += ans[s[j]]
tc += 1
print('Case #',tc,': ',S,sep='')
|
normal
|
{
"blob_id": "77b9b111cfb4d0b54e14b2aab81b7b05fd6bbccd",
"index": 8552,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(len(s)):\n ans[s[i]] = sa[i]\n<mask token>\nfor k in ans:\n S.add(k)\n<mask token>\nfor i in range(1, len(L)):\n s = L[i]\n S = ''\n for j in range(len(s)):\n if s[j] == '\\n':\n continue\n S += ans[s[j]]\n tc += 1\n print('Case #', tc, ': ', S, sep='')\n",
"step-3": "s = (\n 'ejp mysljylc kd kxveddknmc re jsicpdrysirbcpc ypc rtcsra dkh wyfrepkym veddknkmkrkcdde kr kd eoya kw aej tysr re ujdr lkgc jv'\n )\nsa = (\n 'our language is impossible to understandthere are twenty six factorial possibilitiesso it is okay if you want to just give up'\n )\nans = {}\nfor i in range(len(s)):\n ans[s[i]] = sa[i]\nS = set([])\nfor k in ans:\n S.add(k)\nans['q'] = 'z'\nans['z'] = 'q'\nf = open('A-small-attempt0.in', 'r')\nL = f.readlines()\ntc = 0\nfor i in range(1, len(L)):\n s = L[i]\n S = ''\n for j in range(len(s)):\n if s[j] == '\\n':\n continue\n S += ans[s[j]]\n tc += 1\n print('Case #', tc, ': ', S, sep='')\n",
"step-4": "s = 'ejp mysljylc kd kxveddknmc re jsicpdrysirbcpc ypc rtcsra dkh wyfrepkym veddknkmkrkcdde kr kd eoya kw aej tysr re ujdr lkgc jv'\nsa = 'our language is impossible to understandthere are twenty six factorial possibilitiesso it is okay if you want to just give up'\n\nans = {}\nfor i in range(len(s)):\n ans[s[i]] = sa[i];\nS = set([])\nfor k in ans:\n S.add(k)\n#for w in range(26):\n# if chr(w+97) not in S:\n# print chr(w+97)\n\n# q and z not in input so they must map to each other\nans['q'] = 'z'\nans['z'] = 'q'\n\nf = open('A-small-attempt0.in', 'r')\nL = f.readlines()\ntc = 0\nfor i in range(1, len(L)):\n s = L[i]\n S = ''\n for j in range(len(s)):\n if s[j] == '\\n':\n continue\n S += ans[s[j]]\n tc += 1\n print('Case #',tc,': ',S,sep='')\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print(pay)
<|reserved_special_token_0|>
print(odds)
print(type(name), type(age), type(weight), type(kill_streak))
<|reserved_special_token_0|>
print(mean)
<|reserved_special_token_0|>
print(tens)
<|reserved_special_token_0|>
print(average_age)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
work_hours = 8
work_days = 5
pay_periods = 2
total = work_hours * work_days * pay_periods
rate = 17
pay = total * rate
print(pay)
name = 'josh'
age = 30
weight = 160.5
kill_streak = [3, 5, 1, 9]
players = list(range(1, 10))
odds = list(range(1, 10, 2))
print(odds)
print(type(name), type(age), type(weight), type(kill_streak))
kill_streak_sum = sum(kill_streak)
length = len(kill_streak)
mean = kill_streak_sum / length
print(mean)
student_grades = [9.1, 8.8, 10.0, 7.7, 6.8, 8.0, 10.0, 8.1, 10.0, 9.9]
tens = student_grades.count(10)
print(tens)
family = {'josh': 30, 'jess': 31, 'bailey': 1.5}
age_sum = sum(family.values())
family_size = len(family)
average_age = age_sum / family_size
print(average_age)
palette_one = '#f1f1f1', '#333333', '#4287f5'
palette_two = '#f5f5f5', '#454545', '#6dd46a'
palette_three = '#f0fff0', '#c7c7c7', '#725fb0'
palettes = palette_one, palette_two, palette_three
color_codes = palettes
temperature_data = {'morning': (3.1, 2.0, 4.9), 'noon': (1.2, 0.9, 3.4),
'evening': (0.2, 0.1, 1.0)}
day_temperatures = temperature_data
<|reserved_special_token_1|>
work_hours = 8
work_days = 5
pay_periods = 2
total = work_hours * work_days * pay_periods
rate = 17
pay = total * rate
print(pay)
# variables
name = "josh"
age = 30
# float
weight = 160.5
# list
kill_streak = [3, 5, 1, 9] # [90.9] list can contain sub lists
# range
players = list(range(1,10))
odds = list(range(1, 10, 2))
print(odds)
print(type(name), type(age), type(weight), type(kill_streak))
# dir(str)
# attributes
# help(str.upper)
# dir(__builtins__)
kill_streak_sum = sum(kill_streak)
length = len(kill_streak)
mean = kill_streak_sum / length
print(mean)
student_grades = [9.1, 8.8, 10.0, 7.7, 6.8, 8.0, 10.0, 8.1, 10.0, 9.9]
tens = student_grades.count(10)
print(tens)
# dictionary (key:value)
family = {"josh": 30, "jess": 31, "bailey": 1.5}
age_sum = sum(family.values())
family_size = len(family)
average_age = age_sum / family_size
print(average_age)
# Tuple like a dictionary but non-mutable
palette_one = ("#f1f1f1", "#333333", "#4287f5")
palette_two = ("#f5f5f5", "#454545", "#6dd46a")
palette_three = ("#f0fff0", "#c7c7c7", "#725fb0")
palettes = (palette_one, palette_two, palette_three)
color_codes = palettes
temperature_data = {"morning": (3.1, 2.0, 4.9), "noon": (1.2, 0.9, 3.4), "evening": (0.2, 0.1, 1.0)}
day_temperatures = temperature_data
|
flexible
|
{
"blob_id": "af2ef3c77cefe675f3d30c3234401f0f9bda3505",
"index": 8916,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(pay)\n<mask token>\nprint(odds)\nprint(type(name), type(age), type(weight), type(kill_streak))\n<mask token>\nprint(mean)\n<mask token>\nprint(tens)\n<mask token>\nprint(average_age)\n<mask token>\n",
"step-3": "work_hours = 8\nwork_days = 5\npay_periods = 2\ntotal = work_hours * work_days * pay_periods\nrate = 17\npay = total * rate\nprint(pay)\nname = 'josh'\nage = 30\nweight = 160.5\nkill_streak = [3, 5, 1, 9]\nplayers = list(range(1, 10))\nodds = list(range(1, 10, 2))\nprint(odds)\nprint(type(name), type(age), type(weight), type(kill_streak))\nkill_streak_sum = sum(kill_streak)\nlength = len(kill_streak)\nmean = kill_streak_sum / length\nprint(mean)\nstudent_grades = [9.1, 8.8, 10.0, 7.7, 6.8, 8.0, 10.0, 8.1, 10.0, 9.9]\ntens = student_grades.count(10)\nprint(tens)\nfamily = {'josh': 30, 'jess': 31, 'bailey': 1.5}\nage_sum = sum(family.values())\nfamily_size = len(family)\naverage_age = age_sum / family_size\nprint(average_age)\npalette_one = '#f1f1f1', '#333333', '#4287f5'\npalette_two = '#f5f5f5', '#454545', '#6dd46a'\npalette_three = '#f0fff0', '#c7c7c7', '#725fb0'\npalettes = palette_one, palette_two, palette_three\ncolor_codes = palettes\ntemperature_data = {'morning': (3.1, 2.0, 4.9), 'noon': (1.2, 0.9, 3.4),\n 'evening': (0.2, 0.1, 1.0)}\nday_temperatures = temperature_data\n",
"step-4": "work_hours = 8\r\nwork_days = 5\r\npay_periods = 2\r\ntotal = work_hours * work_days * pay_periods\r\nrate = 17\r\npay = total * rate\r\n\r\nprint(pay)\r\n\r\n# variables\r\nname = \"josh\"\r\nage = 30\r\n# float\r\nweight = 160.5\r\n# list\r\nkill_streak = [3, 5, 1, 9] # [90.9] list can contain sub lists\r\n# range\r\nplayers = list(range(1,10))\r\nodds = list(range(1, 10, 2))\r\nprint(odds)\r\n\r\nprint(type(name), type(age), type(weight), type(kill_streak))\r\n\r\n# dir(str)\r\n# attributes\r\n# help(str.upper)\r\n\r\n# dir(__builtins__)\r\n\r\nkill_streak_sum = sum(kill_streak)\r\nlength = len(kill_streak)\r\nmean = kill_streak_sum / length\r\n\r\nprint(mean)\r\n\r\nstudent_grades = [9.1, 8.8, 10.0, 7.7, 6.8, 8.0, 10.0, 8.1, 10.0, 9.9]\r\ntens = student_grades.count(10)\r\n\r\nprint(tens)\r\n\r\n# dictionary (key:value)\r\nfamily = {\"josh\": 30, \"jess\": 31, \"bailey\": 1.5}\r\nage_sum = sum(family.values())\r\nfamily_size = len(family)\r\naverage_age = age_sum / family_size\r\n\r\nprint(average_age)\r\n\r\n# Tuple like a dictionary but non-mutable\r\npalette_one = (\"#f1f1f1\", \"#333333\", \"#4287f5\")\r\npalette_two = (\"#f5f5f5\", \"#454545\", \"#6dd46a\")\r\npalette_three = (\"#f0fff0\", \"#c7c7c7\", \"#725fb0\")\r\npalettes = (palette_one, palette_two, palette_three)\r\n\r\ncolor_codes = palettes\r\n\r\ntemperature_data = {\"morning\": (3.1, 2.0, 4.9), \"noon\": (1.2, 0.9, 3.4), \"evening\": (0.2, 0.1, 1.0)}\r\nday_temperatures = temperature_data\r\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
p.add_argument('--foo', action='store_true')
<|reserved_special_token_0|>
print(args.foo)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
p = argparse.ArgumentParser()
p.add_argument('--foo', action='store_true')
args = p.parse_args()
print(args.foo)
<|reserved_special_token_1|>
import argparse
p = argparse.ArgumentParser()
p.add_argument('--foo', action='store_true')
args = p.parse_args()
print(args.foo)
<|reserved_special_token_1|>
import argparse
p = argparse.ArgumentParser()
p.add_argument("--foo", action="store_true")
args = p.parse_args()
print(args.foo)
|
flexible
|
{
"blob_id": "2cc9f8c476026311456857d3395a14a45e2f4b80",
"index": 1460,
"step-1": "<mask token>\n",
"step-2": "<mask token>\np.add_argument('--foo', action='store_true')\n<mask token>\nprint(args.foo)\n",
"step-3": "<mask token>\np = argparse.ArgumentParser()\np.add_argument('--foo', action='store_true')\nargs = p.parse_args()\nprint(args.foo)\n",
"step-4": "import argparse\np = argparse.ArgumentParser()\np.add_argument('--foo', action='store_true')\nargs = p.parse_args()\nprint(args.foo)\n",
"step-5": "import argparse\n\np = argparse.ArgumentParser()\np.add_argument(\"--foo\", action=\"store_true\")\nargs = p.parse_args()\nprint(args.foo)\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
from .book import book
from . import style, to, read, dist
<|reserved_special_token_1|>
"""
.. currentmodule:: jotting
.. automodule:: jotting.book
:members:
.. automodule:: jotting.to
:members:
.. automodule:: jotting.read
:members:
.. automodule:: jotting.style
:members:
"""
from .book import book
from . import style, to, read, dist
|
flexible
|
{
"blob_id": "ce6dba2f682b091249f3bbf362bead4b95fee1f4",
"index": 292,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfrom .book import book\nfrom . import style, to, read, dist\n",
"step-3": "\"\"\"\n.. currentmodule:: jotting\n\n.. automodule:: jotting.book\n :members:\n\n.. automodule:: jotting.to\n :members:\n\n.. automodule:: jotting.read\n :members:\n\n.. automodule:: jotting.style\n :members:\n\"\"\"\n\n\nfrom .book import book\nfrom . import style, to, read, dist\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
from django.contrib import admin
from django_summernote.admin import SummernoteModelAdmin
from .models import ArticlePost
# Register your models here.
class SomeModelAdmin(SummernoteModelAdmin): # instead of ModelAdmin
summernote_fields = '__all__'
admin.site.register(ArticlePost, SummernoteModelAdmin)
|
normal
|
{
"blob_id": "a86b64ccd0dab4ab70ca9c2b7625fb34afec3794",
"index": 63,
"step-1": "<mask token>\n\n\nclass SomeModelAdmin(SummernoteModelAdmin):\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass SomeModelAdmin(SummernoteModelAdmin):\n summernote_fields = '__all__'\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass SomeModelAdmin(SummernoteModelAdmin):\n summernote_fields = '__all__'\n\n\nadmin.site.register(ArticlePost, SummernoteModelAdmin)\n",
"step-4": "from django.contrib import admin\nfrom django_summernote.admin import SummernoteModelAdmin\nfrom .models import ArticlePost\n\n\nclass SomeModelAdmin(SummernoteModelAdmin):\n summernote_fields = '__all__'\n\n\nadmin.site.register(ArticlePost, SummernoteModelAdmin)\n",
"step-5": "from django.contrib import admin\nfrom django_summernote.admin import SummernoteModelAdmin\nfrom .models import ArticlePost\n# Register your models here.\n\nclass SomeModelAdmin(SummernoteModelAdmin): # instead of ModelAdmin\n summernote_fields = '__all__'\n\nadmin.site.register(ArticlePost, SummernoteModelAdmin)",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
import json
import joblib
import numpy as np
import datetime
import sqlalchemy as sa
import cx_Oracle
import pandas as pd
from flask import Flask, render_template, session, request, redirect, url_for
app = Flask(__name__)
oracle_engine = sa.create_engine('oracle://ft:1234@localhost:1522/xe')
@app.route("/")
def index():
return render_template('index.html')
@app.route("/survey", methods=['POST', 'GET'])
def survey():
if request.method == 'GET':
return render_template('survey.html')
if request.method == 'POST':
is_oversea = request.form['oversea']
gender = request.form['gender']
age = request.form['age']
income = request.form['income']
knowledge = request.form['knowledge']
exp = request.form['exp']
risk = request.form['risk']
term = request.form['term']
s1 = request.form['s1']
s2 = request.form['s2']
s3 = request.form['s3']
s4 = request.form['s4']
s5 = request.form['s5']
i_list = [gender, age, income, knowledge, exp, risk, term, s1, s2, s3, s4, s5]
i_list = list(map(int, i_list)) # str -> int
score = sum(i_list)
i_list.append(score)
data = np.array(i_list).reshape(1, -1)
clf = joblib.load('./models/rf_model.pkl')
type_num = clf.predict(data)
if type_num == 0:
invest_type = "안정추구형"
elif type_num == 1:
invest_type = "안정형"
elif type_num == 2:
invest_type = "적극투자형"
elif type_num == 3:
invest_type = "공격투자형"
else:
invest_type = "위험중립형"
return render_template('result.html', KEY_INVEST_TYPE=invest_type, IS_OVERSEA=is_oversea)
@app.route("/portfolio", methods=['POST', 'GET'])
def portfolio():
if request.method == 'POST':
# 국내
portfolio0 = ['195930', '133690', '273130', '284430', '183700'] # 안정형
portfolio1 = ['195930', '133690', '239660', '284430', '183700'] # 안정추구형
portfolio2 = ['195930', '133690', '239660', '278620', '284430'] # 위험중립형
portfolio3 = ['195930', '278530', '133690', '239660', '284430'] # 적극투자형
portfolio4 = ['195930', '278530', '277630', '133690', '284430'] # 공격투자형
# 미국
portfolio5 = ['OILK', 'BBJP', 'ARKK', 'PALL', 'QQQ'] # 안정형
portfolio6 = ['OILK', 'SPHB', 'BBJP', 'ARKK', 'PALL'] # 안정추구형
portfolio7 = ['OILK', 'SPHB', 'JAGG', 'BBJP', 'ARKK'] # 위험중립형
portfolio8 = ['OILK', 'BBCA', 'SPHB', 'JAGG', 'ARKK'] # 적극투자형
portfolio9 = ['OILK', 'BBCA', 'BBEU', 'BBJP', 'ARKK'] # 공격투자형
price = request.form['price']
invest_type = request.form['type']
risk_no = request.form['risk_no']
is_oversea = request.form['oversea']
db = ""
if is_oversea == '0': # 해외 ETF
db = "ETF_US"
else: # 국내 ETF
db = "ETF_KR"
print(db)
with oracle_engine.connect() as conn:
try:
sql = "select * from " + db + " where invest_type=:1"
results = conn.execute(sql, (invest_type)).fetchall()
name_list = [] # 상품명
risk_list = [] # 위험등급
weight_list = [] # 가중치
returns_1y = [] # 1년 수익률
returns_3y = [] # 3년 수익률
returns_5y = [] # 5년 수익률
for etf in results:
name_list.append(etf[0])
risk_list.append(etf[2])
weight_list.append(etf[3])
returns_1y.append(etf[4])
returns_3y.append(etf[5])
returns_5y.append(etf[6])
# 투자성향 상품별 과거 수익률 데이터 가져오기
sql = "select * from RETURN"
return_df = pd.read_sql(sql, conn)
etf_list = []
return_list = {}
date_list = {}
if is_oversea == '0': # 해외
if invest_type == '안정형':
portfolio_data = portfolio5
elif invest_type == '안정추구형':
portfolio_data = portfolio6
elif invest_type == '위험중립형':
portfolio_data = portfolio7
elif invest_type == '적극투자형':
portfolio_data = portfolio8
else:
portfolio_data = portfolio9
else:
if invest_type == '안정형':
portfolio_data = portfolio0
elif invest_type == '안정추구형':
portfolio_data = portfolio1
elif invest_type == '위험중립형':
portfolio_data = portfolio2
elif invest_type == '적극투자형':
portfolio_data = portfolio3
else:
portfolio_data = portfolio4
for i, ticker in enumerate(portfolio_data):
name = return_df[return_df['ticker'] == ticker]['name'].unique().tolist()[0]
if name not in etf_list:
etf_list.append(name)
return_list[i] = list(return_df[return_df['ticker'] == ticker]['return'].map(float).values)
date_list[i] = list(
return_df[return_df['ticker'] == ticker]['rdate'].dt.strftime('%Y-%m-%d').unique())
# 포트폴리오 수익률 데이터 가져오기
if is_oversea == '0': # 해외
sql = "select * from pf_us"
pf_df = pd.read_sql(sql, conn)
pf_df = pf_df[46:]
else: # 국내
sql = "select * from pf_kr"
pf_df = pd.read_sql(sql, conn)
pf_df = pf_df[140:]
pf_list = pf_df[invest_type].map(float).tolist()
bt_data = []
for i, pf in enumerate(pf_list):
bt_data.append({'x': i, 'y': pf});
except Exception as e:
print(e)
# 투자 등급 카운팅 (파이차트에 비중 나타내기 위해 사용)
count_list = [0,0,0]
for risk_type in risk_list:
if risk_type == '위험':
count_list[0] += 1
elif risk_type == '중립':
count_list[1] += 1
else:
count_list[2] += 1
return render_template('portfolio.html', KEY_PRICE=price, KEY_INVEST_TYPE=invest_type, KEY_NAME_LIST=name_list,
KEY_RISK_LIST=risk_list, KEY_WEIGHT_LIST=weight_list, KEY_COUNT_LIST=count_list,
KEY_RETURN_1Y=returns_1y, KEY_RETURN_3Y=returns_3y, KEY_RETURN_5Y=returns_5y,
KEY_ETF_LIST=etf_list, KEY_RETURN_LIST=return_list, KEY_DATE_LIST=date_list,
KEY_BACKTESTING=bt_data)
if __name__ == '__main__':
app.run(debug=True)
|
normal
|
{
"blob_id": "74aa93bf3731d4e3ddb920bedc7daced50b4f2c3",
"index": 1565,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('index.html')\n\n\n@app.route('/survey', methods=['POST', 'GET'])\ndef survey():\n if request.method == 'GET':\n return render_template('survey.html')\n if request.method == 'POST':\n is_oversea = request.form['oversea']\n gender = request.form['gender']\n age = request.form['age']\n income = request.form['income']\n knowledge = request.form['knowledge']\n exp = request.form['exp']\n risk = request.form['risk']\n term = request.form['term']\n s1 = request.form['s1']\n s2 = request.form['s2']\n s3 = request.form['s3']\n s4 = request.form['s4']\n s5 = request.form['s5']\n i_list = [gender, age, income, knowledge, exp, risk, term, s1, s2,\n s3, s4, s5]\n i_list = list(map(int, i_list))\n score = sum(i_list)\n i_list.append(score)\n data = np.array(i_list).reshape(1, -1)\n clf = joblib.load('./models/rf_model.pkl')\n type_num = clf.predict(data)\n if type_num == 0:\n invest_type = '안정추구형'\n elif type_num == 1:\n invest_type = '안정형'\n elif type_num == 2:\n invest_type = '적극투자형'\n elif type_num == 3:\n invest_type = '공격투자형'\n else:\n invest_type = '위험중립형'\n return render_template('result.html', KEY_INVEST_TYPE=invest_type,\n IS_OVERSEA=is_oversea)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@app.route('/')\ndef index():\n return render_template('index.html')\n\n\n@app.route('/survey', methods=['POST', 'GET'])\ndef survey():\n if request.method == 'GET':\n return render_template('survey.html')\n if request.method == 'POST':\n is_oversea = request.form['oversea']\n gender = request.form['gender']\n age = request.form['age']\n income = request.form['income']\n knowledge = request.form['knowledge']\n exp = request.form['exp']\n risk = request.form['risk']\n term = request.form['term']\n s1 = request.form['s1']\n s2 = request.form['s2']\n s3 = request.form['s3']\n s4 = request.form['s4']\n s5 = request.form['s5']\n i_list = [gender, age, income, knowledge, exp, risk, term, s1, s2,\n s3, s4, s5]\n i_list = list(map(int, i_list))\n score = sum(i_list)\n i_list.append(score)\n data = np.array(i_list).reshape(1, -1)\n clf = joblib.load('./models/rf_model.pkl')\n type_num = clf.predict(data)\n if type_num == 0:\n invest_type = '안정추구형'\n elif type_num == 1:\n invest_type = '안정형'\n elif type_num == 2:\n invest_type = '적극투자형'\n elif type_num == 3:\n invest_type = '공격투자형'\n else:\n invest_type = '위험중립형'\n return render_template('result.html', KEY_INVEST_TYPE=invest_type,\n IS_OVERSEA=is_oversea)\n\n\n@app.route('/portfolio', methods=['POST', 'GET'])\ndef portfolio():\n if request.method == 'POST':\n portfolio0 = ['195930', '133690', '273130', '284430', '183700']\n portfolio1 = ['195930', '133690', '239660', '284430', '183700']\n portfolio2 = ['195930', '133690', '239660', '278620', '284430']\n portfolio3 = ['195930', '278530', '133690', '239660', '284430']\n portfolio4 = ['195930', '278530', '277630', '133690', '284430']\n portfolio5 = ['OILK', 'BBJP', 'ARKK', 'PALL', 'QQQ']\n portfolio6 = ['OILK', 'SPHB', 'BBJP', 'ARKK', 'PALL']\n portfolio7 = ['OILK', 'SPHB', 'JAGG', 'BBJP', 'ARKK']\n portfolio8 = ['OILK', 'BBCA', 'SPHB', 'JAGG', 'ARKK']\n portfolio9 = ['OILK', 'BBCA', 'BBEU', 'BBJP', 'ARKK']\n price = request.form['price']\n invest_type = request.form['type']\n risk_no = request.form['risk_no']\n is_oversea = request.form['oversea']\n db = ''\n if is_oversea == '0':\n db = 'ETF_US'\n else:\n db = 'ETF_KR'\n print(db)\n with oracle_engine.connect() as conn:\n try:\n sql = 'select * from ' + db + ' where invest_type=:1'\n results = conn.execute(sql, invest_type).fetchall()\n name_list = []\n risk_list = []\n weight_list = []\n returns_1y = []\n returns_3y = []\n returns_5y = []\n for etf in results:\n name_list.append(etf[0])\n risk_list.append(etf[2])\n weight_list.append(etf[3])\n returns_1y.append(etf[4])\n returns_3y.append(etf[5])\n returns_5y.append(etf[6])\n sql = 'select * from RETURN'\n return_df = pd.read_sql(sql, conn)\n etf_list = []\n return_list = {}\n date_list = {}\n if is_oversea == '0':\n if invest_type == '안정형':\n portfolio_data = portfolio5\n elif invest_type == '안정추구형':\n portfolio_data = portfolio6\n elif invest_type == '위험중립형':\n portfolio_data = portfolio7\n elif invest_type == '적극투자형':\n portfolio_data = portfolio8\n else:\n portfolio_data = portfolio9\n elif invest_type == '안정형':\n portfolio_data = portfolio0\n elif invest_type == '안정추구형':\n portfolio_data = portfolio1\n elif invest_type == '위험중립형':\n portfolio_data = portfolio2\n elif invest_type == '적극투자형':\n portfolio_data = portfolio3\n else:\n portfolio_data = portfolio4\n for i, ticker in enumerate(portfolio_data):\n name = return_df[return_df['ticker'] == ticker]['name'\n ].unique().tolist()[0]\n if name not in etf_list:\n etf_list.append(name)\n return_list[i] = list(return_df[return_df['ticker'] ==\n ticker]['return'].map(float).values)\n date_list[i] = list(return_df[return_df['ticker'] ==\n ticker]['rdate'].dt.strftime('%Y-%m-%d').unique())\n if is_oversea == '0':\n sql = 'select * from pf_us'\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[46:]\n else:\n sql = 'select * from pf_kr'\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[140:]\n pf_list = pf_df[invest_type].map(float).tolist()\n bt_data = []\n for i, pf in enumerate(pf_list):\n bt_data.append({'x': i, 'y': pf})\n except Exception as e:\n print(e)\n count_list = [0, 0, 0]\n for risk_type in risk_list:\n if risk_type == '위험':\n count_list[0] += 1\n elif risk_type == '중립':\n count_list[1] += 1\n else:\n count_list[2] += 1\n return render_template('portfolio.html', KEY_PRICE=price,\n KEY_INVEST_TYPE=invest_type, KEY_NAME_LIST=name_list,\n KEY_RISK_LIST=risk_list, KEY_WEIGHT_LIST=weight_list,\n KEY_COUNT_LIST=count_list, KEY_RETURN_1Y=returns_1y,\n KEY_RETURN_3Y=returns_3y, KEY_RETURN_5Y=returns_5y,\n KEY_ETF_LIST=etf_list, KEY_RETURN_LIST=return_list,\n KEY_DATE_LIST=date_list, KEY_BACKTESTING=bt_data)\n\n\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-3": "<mask token>\napp = Flask(__name__)\noracle_engine = sa.create_engine('oracle://ft:1234@localhost:1522/xe')\n\n\n@app.route('/')\ndef index():\n return render_template('index.html')\n\n\n@app.route('/survey', methods=['POST', 'GET'])\ndef survey():\n if request.method == 'GET':\n return render_template('survey.html')\n if request.method == 'POST':\n is_oversea = request.form['oversea']\n gender = request.form['gender']\n age = request.form['age']\n income = request.form['income']\n knowledge = request.form['knowledge']\n exp = request.form['exp']\n risk = request.form['risk']\n term = request.form['term']\n s1 = request.form['s1']\n s2 = request.form['s2']\n s3 = request.form['s3']\n s4 = request.form['s4']\n s5 = request.form['s5']\n i_list = [gender, age, income, knowledge, exp, risk, term, s1, s2,\n s3, s4, s5]\n i_list = list(map(int, i_list))\n score = sum(i_list)\n i_list.append(score)\n data = np.array(i_list).reshape(1, -1)\n clf = joblib.load('./models/rf_model.pkl')\n type_num = clf.predict(data)\n if type_num == 0:\n invest_type = '안정추구형'\n elif type_num == 1:\n invest_type = '안정형'\n elif type_num == 2:\n invest_type = '적극투자형'\n elif type_num == 3:\n invest_type = '공격투자형'\n else:\n invest_type = '위험중립형'\n return render_template('result.html', KEY_INVEST_TYPE=invest_type,\n IS_OVERSEA=is_oversea)\n\n\n@app.route('/portfolio', methods=['POST', 'GET'])\ndef portfolio():\n if request.method == 'POST':\n portfolio0 = ['195930', '133690', '273130', '284430', '183700']\n portfolio1 = ['195930', '133690', '239660', '284430', '183700']\n portfolio2 = ['195930', '133690', '239660', '278620', '284430']\n portfolio3 = ['195930', '278530', '133690', '239660', '284430']\n portfolio4 = ['195930', '278530', '277630', '133690', '284430']\n portfolio5 = ['OILK', 'BBJP', 'ARKK', 'PALL', 'QQQ']\n portfolio6 = ['OILK', 'SPHB', 'BBJP', 'ARKK', 'PALL']\n portfolio7 = ['OILK', 'SPHB', 'JAGG', 'BBJP', 'ARKK']\n portfolio8 = ['OILK', 'BBCA', 'SPHB', 'JAGG', 'ARKK']\n portfolio9 = ['OILK', 'BBCA', 'BBEU', 'BBJP', 'ARKK']\n price = request.form['price']\n invest_type = request.form['type']\n risk_no = request.form['risk_no']\n is_oversea = request.form['oversea']\n db = ''\n if is_oversea == '0':\n db = 'ETF_US'\n else:\n db = 'ETF_KR'\n print(db)\n with oracle_engine.connect() as conn:\n try:\n sql = 'select * from ' + db + ' where invest_type=:1'\n results = conn.execute(sql, invest_type).fetchall()\n name_list = []\n risk_list = []\n weight_list = []\n returns_1y = []\n returns_3y = []\n returns_5y = []\n for etf in results:\n name_list.append(etf[0])\n risk_list.append(etf[2])\n weight_list.append(etf[3])\n returns_1y.append(etf[4])\n returns_3y.append(etf[5])\n returns_5y.append(etf[6])\n sql = 'select * from RETURN'\n return_df = pd.read_sql(sql, conn)\n etf_list = []\n return_list = {}\n date_list = {}\n if is_oversea == '0':\n if invest_type == '안정형':\n portfolio_data = portfolio5\n elif invest_type == '안정추구형':\n portfolio_data = portfolio6\n elif invest_type == '위험중립형':\n portfolio_data = portfolio7\n elif invest_type == '적극투자형':\n portfolio_data = portfolio8\n else:\n portfolio_data = portfolio9\n elif invest_type == '안정형':\n portfolio_data = portfolio0\n elif invest_type == '안정추구형':\n portfolio_data = portfolio1\n elif invest_type == '위험중립형':\n portfolio_data = portfolio2\n elif invest_type == '적극투자형':\n portfolio_data = portfolio3\n else:\n portfolio_data = portfolio4\n for i, ticker in enumerate(portfolio_data):\n name = return_df[return_df['ticker'] == ticker]['name'\n ].unique().tolist()[0]\n if name not in etf_list:\n etf_list.append(name)\n return_list[i] = list(return_df[return_df['ticker'] ==\n ticker]['return'].map(float).values)\n date_list[i] = list(return_df[return_df['ticker'] ==\n ticker]['rdate'].dt.strftime('%Y-%m-%d').unique())\n if is_oversea == '0':\n sql = 'select * from pf_us'\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[46:]\n else:\n sql = 'select * from pf_kr'\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[140:]\n pf_list = pf_df[invest_type].map(float).tolist()\n bt_data = []\n for i, pf in enumerate(pf_list):\n bt_data.append({'x': i, 'y': pf})\n except Exception as e:\n print(e)\n count_list = [0, 0, 0]\n for risk_type in risk_list:\n if risk_type == '위험':\n count_list[0] += 1\n elif risk_type == '중립':\n count_list[1] += 1\n else:\n count_list[2] += 1\n return render_template('portfolio.html', KEY_PRICE=price,\n KEY_INVEST_TYPE=invest_type, KEY_NAME_LIST=name_list,\n KEY_RISK_LIST=risk_list, KEY_WEIGHT_LIST=weight_list,\n KEY_COUNT_LIST=count_list, KEY_RETURN_1Y=returns_1y,\n KEY_RETURN_3Y=returns_3y, KEY_RETURN_5Y=returns_5y,\n KEY_ETF_LIST=etf_list, KEY_RETURN_LIST=return_list,\n KEY_DATE_LIST=date_list, KEY_BACKTESTING=bt_data)\n\n\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-4": "import json\nimport joblib\nimport numpy as np\nimport datetime\nimport sqlalchemy as sa\nimport cx_Oracle\nimport pandas as pd\nfrom flask import Flask, render_template, session, request, redirect, url_for\napp = Flask(__name__)\noracle_engine = sa.create_engine('oracle://ft:1234@localhost:1522/xe')\n\n\n@app.route('/')\ndef index():\n return render_template('index.html')\n\n\n@app.route('/survey', methods=['POST', 'GET'])\ndef survey():\n if request.method == 'GET':\n return render_template('survey.html')\n if request.method == 'POST':\n is_oversea = request.form['oversea']\n gender = request.form['gender']\n age = request.form['age']\n income = request.form['income']\n knowledge = request.form['knowledge']\n exp = request.form['exp']\n risk = request.form['risk']\n term = request.form['term']\n s1 = request.form['s1']\n s2 = request.form['s2']\n s3 = request.form['s3']\n s4 = request.form['s4']\n s5 = request.form['s5']\n i_list = [gender, age, income, knowledge, exp, risk, term, s1, s2,\n s3, s4, s5]\n i_list = list(map(int, i_list))\n score = sum(i_list)\n i_list.append(score)\n data = np.array(i_list).reshape(1, -1)\n clf = joblib.load('./models/rf_model.pkl')\n type_num = clf.predict(data)\n if type_num == 0:\n invest_type = '안정추구형'\n elif type_num == 1:\n invest_type = '안정형'\n elif type_num == 2:\n invest_type = '적극투자형'\n elif type_num == 3:\n invest_type = '공격투자형'\n else:\n invest_type = '위험중립형'\n return render_template('result.html', KEY_INVEST_TYPE=invest_type,\n IS_OVERSEA=is_oversea)\n\n\n@app.route('/portfolio', methods=['POST', 'GET'])\ndef portfolio():\n if request.method == 'POST':\n portfolio0 = ['195930', '133690', '273130', '284430', '183700']\n portfolio1 = ['195930', '133690', '239660', '284430', '183700']\n portfolio2 = ['195930', '133690', '239660', '278620', '284430']\n portfolio3 = ['195930', '278530', '133690', '239660', '284430']\n portfolio4 = ['195930', '278530', '277630', '133690', '284430']\n portfolio5 = ['OILK', 'BBJP', 'ARKK', 'PALL', 'QQQ']\n portfolio6 = ['OILK', 'SPHB', 'BBJP', 'ARKK', 'PALL']\n portfolio7 = ['OILK', 'SPHB', 'JAGG', 'BBJP', 'ARKK']\n portfolio8 = ['OILK', 'BBCA', 'SPHB', 'JAGG', 'ARKK']\n portfolio9 = ['OILK', 'BBCA', 'BBEU', 'BBJP', 'ARKK']\n price = request.form['price']\n invest_type = request.form['type']\n risk_no = request.form['risk_no']\n is_oversea = request.form['oversea']\n db = ''\n if is_oversea == '0':\n db = 'ETF_US'\n else:\n db = 'ETF_KR'\n print(db)\n with oracle_engine.connect() as conn:\n try:\n sql = 'select * from ' + db + ' where invest_type=:1'\n results = conn.execute(sql, invest_type).fetchall()\n name_list = []\n risk_list = []\n weight_list = []\n returns_1y = []\n returns_3y = []\n returns_5y = []\n for etf in results:\n name_list.append(etf[0])\n risk_list.append(etf[2])\n weight_list.append(etf[3])\n returns_1y.append(etf[4])\n returns_3y.append(etf[5])\n returns_5y.append(etf[6])\n sql = 'select * from RETURN'\n return_df = pd.read_sql(sql, conn)\n etf_list = []\n return_list = {}\n date_list = {}\n if is_oversea == '0':\n if invest_type == '안정형':\n portfolio_data = portfolio5\n elif invest_type == '안정추구형':\n portfolio_data = portfolio6\n elif invest_type == '위험중립형':\n portfolio_data = portfolio7\n elif invest_type == '적극투자형':\n portfolio_data = portfolio8\n else:\n portfolio_data = portfolio9\n elif invest_type == '안정형':\n portfolio_data = portfolio0\n elif invest_type == '안정추구형':\n portfolio_data = portfolio1\n elif invest_type == '위험중립형':\n portfolio_data = portfolio2\n elif invest_type == '적극투자형':\n portfolio_data = portfolio3\n else:\n portfolio_data = portfolio4\n for i, ticker in enumerate(portfolio_data):\n name = return_df[return_df['ticker'] == ticker]['name'\n ].unique().tolist()[0]\n if name not in etf_list:\n etf_list.append(name)\n return_list[i] = list(return_df[return_df['ticker'] ==\n ticker]['return'].map(float).values)\n date_list[i] = list(return_df[return_df['ticker'] ==\n ticker]['rdate'].dt.strftime('%Y-%m-%d').unique())\n if is_oversea == '0':\n sql = 'select * from pf_us'\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[46:]\n else:\n sql = 'select * from pf_kr'\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[140:]\n pf_list = pf_df[invest_type].map(float).tolist()\n bt_data = []\n for i, pf in enumerate(pf_list):\n bt_data.append({'x': i, 'y': pf})\n except Exception as e:\n print(e)\n count_list = [0, 0, 0]\n for risk_type in risk_list:\n if risk_type == '위험':\n count_list[0] += 1\n elif risk_type == '중립':\n count_list[1] += 1\n else:\n count_list[2] += 1\n return render_template('portfolio.html', KEY_PRICE=price,\n KEY_INVEST_TYPE=invest_type, KEY_NAME_LIST=name_list,\n KEY_RISK_LIST=risk_list, KEY_WEIGHT_LIST=weight_list,\n KEY_COUNT_LIST=count_list, KEY_RETURN_1Y=returns_1y,\n KEY_RETURN_3Y=returns_3y, KEY_RETURN_5Y=returns_5y,\n KEY_ETF_LIST=etf_list, KEY_RETURN_LIST=return_list,\n KEY_DATE_LIST=date_list, KEY_BACKTESTING=bt_data)\n\n\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-5": "import json\nimport joblib\nimport numpy as np\nimport datetime\nimport sqlalchemy as sa\nimport cx_Oracle\nimport pandas as pd\n\nfrom flask import Flask, render_template, session, request, redirect, url_for\n\napp = Flask(__name__)\noracle_engine = sa.create_engine('oracle://ft:1234@localhost:1522/xe')\n\n@app.route(\"/\")\ndef index():\n return render_template('index.html')\n\n@app.route(\"/survey\", methods=['POST', 'GET'])\ndef survey():\n if request.method == 'GET':\n return render_template('survey.html')\n\n if request.method == 'POST':\n is_oversea = request.form['oversea']\n\n gender = request.form['gender']\n age = request.form['age']\n income = request.form['income']\n knowledge = request.form['knowledge']\n exp = request.form['exp']\n risk = request.form['risk']\n term = request.form['term']\n s1 = request.form['s1']\n s2 = request.form['s2']\n s3 = request.form['s3']\n s4 = request.form['s4']\n s5 = request.form['s5']\n\n i_list = [gender, age, income, knowledge, exp, risk, term, s1, s2, s3, s4, s5]\n i_list = list(map(int, i_list)) # str -> int\n score = sum(i_list)\n i_list.append(score)\n data = np.array(i_list).reshape(1, -1)\n\n clf = joblib.load('./models/rf_model.pkl')\n type_num = clf.predict(data)\n\n if type_num == 0:\n invest_type = \"안정추구형\"\n elif type_num == 1:\n invest_type = \"안정형\"\n elif type_num == 2:\n invest_type = \"적극투자형\"\n elif type_num == 3:\n invest_type = \"공격투자형\"\n else:\n invest_type = \"위험중립형\"\n\n return render_template('result.html', KEY_INVEST_TYPE=invest_type, IS_OVERSEA=is_oversea)\n\n@app.route(\"/portfolio\", methods=['POST', 'GET'])\ndef portfolio():\n if request.method == 'POST':\n # 국내\n portfolio0 = ['195930', '133690', '273130', '284430', '183700'] # 안정형\n portfolio1 = ['195930', '133690', '239660', '284430', '183700'] # 안정추구형\n portfolio2 = ['195930', '133690', '239660', '278620', '284430'] # 위험중립형\n portfolio3 = ['195930', '278530', '133690', '239660', '284430'] # 적극투자형\n portfolio4 = ['195930', '278530', '277630', '133690', '284430'] # 공격투자형\n\n # 미국\n portfolio5 = ['OILK', 'BBJP', 'ARKK', 'PALL', 'QQQ'] # 안정형\n portfolio6 = ['OILK', 'SPHB', 'BBJP', 'ARKK', 'PALL'] # 안정추구형\n portfolio7 = ['OILK', 'SPHB', 'JAGG', 'BBJP', 'ARKK'] # 위험중립형\n portfolio8 = ['OILK', 'BBCA', 'SPHB', 'JAGG', 'ARKK'] # 적극투자형\n portfolio9 = ['OILK', 'BBCA', 'BBEU', 'BBJP', 'ARKK'] # 공격투자형\n\n price = request.form['price']\n invest_type = request.form['type']\n risk_no = request.form['risk_no']\n is_oversea = request.form['oversea']\n\n db = \"\"\n\n if is_oversea == '0': # 해외 ETF\n db = \"ETF_US\"\n else: # 국내 ETF\n db = \"ETF_KR\"\n\n print(db)\n\n with oracle_engine.connect() as conn:\n try:\n sql = \"select * from \" + db + \" where invest_type=:1\"\n results = conn.execute(sql, (invest_type)).fetchall()\n\n name_list = [] # 상품명\n risk_list = [] # 위험등급\n weight_list = [] # 가중치\n returns_1y = [] # 1년 수익률\n returns_3y = [] # 3년 수익률\n returns_5y = [] # 5년 수익률\n\n for etf in results:\n name_list.append(etf[0])\n risk_list.append(etf[2])\n weight_list.append(etf[3])\n returns_1y.append(etf[4])\n returns_3y.append(etf[5])\n returns_5y.append(etf[6])\n\n # 투자성향 상품별 과거 수익률 데이터 가져오기\n sql = \"select * from RETURN\"\n return_df = pd.read_sql(sql, conn)\n\n etf_list = []\n return_list = {}\n date_list = {}\n\n if is_oversea == '0': # 해외\n if invest_type == '안정형':\n portfolio_data = portfolio5\n elif invest_type == '안정추구형':\n portfolio_data = portfolio6\n elif invest_type == '위험중립형':\n portfolio_data = portfolio7\n elif invest_type == '적극투자형':\n portfolio_data = portfolio8\n else:\n portfolio_data = portfolio9\n else:\n if invest_type == '안정형':\n portfolio_data = portfolio0\n elif invest_type == '안정추구형':\n portfolio_data = portfolio1\n elif invest_type == '위험중립형':\n portfolio_data = portfolio2\n elif invest_type == '적극투자형':\n portfolio_data = portfolio3\n else:\n portfolio_data = portfolio4\n\n for i, ticker in enumerate(portfolio_data):\n name = return_df[return_df['ticker'] == ticker]['name'].unique().tolist()[0]\n if name not in etf_list:\n etf_list.append(name)\n\n return_list[i] = list(return_df[return_df['ticker'] == ticker]['return'].map(float).values)\n date_list[i] = list(\n return_df[return_df['ticker'] == ticker]['rdate'].dt.strftime('%Y-%m-%d').unique())\n\n # 포트폴리오 수익률 데이터 가져오기\n if is_oversea == '0': # 해외\n sql = \"select * from pf_us\"\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[46:]\n else: # 국내\n sql = \"select * from pf_kr\"\n pf_df = pd.read_sql(sql, conn)\n pf_df = pf_df[140:]\n\n pf_list = pf_df[invest_type].map(float).tolist()\n\n bt_data = []\n for i, pf in enumerate(pf_list):\n bt_data.append({'x': i, 'y': pf});\n\n except Exception as e:\n print(e)\n\n # 투자 등급 카운팅 (파이차트에 비중 나타내기 위해 사용)\n count_list = [0,0,0]\n\n for risk_type in risk_list:\n if risk_type == '위험':\n count_list[0] += 1\n elif risk_type == '중립':\n count_list[1] += 1\n else:\n count_list[2] += 1\n\n return render_template('portfolio.html', KEY_PRICE=price, KEY_INVEST_TYPE=invest_type, KEY_NAME_LIST=name_list,\n KEY_RISK_LIST=risk_list, KEY_WEIGHT_LIST=weight_list, KEY_COUNT_LIST=count_list,\n KEY_RETURN_1Y=returns_1y, KEY_RETURN_3Y=returns_3y, KEY_RETURN_5Y=returns_5y,\n KEY_ETF_LIST=etf_list, KEY_RETURN_LIST=return_list, KEY_DATE_LIST=date_list,\n KEY_BACKTESTING=bt_data)\n\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-ids": [
2,
4,
5,
6,
7
]
}
|
[
2,
4,
5,
6,
7
] |
# Copyright 2013 Rackspace Hosting Inc.
# All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import contextlib
import mock
from neutron.common import exceptions as n_exc_ext
from neutron_lib import exceptions as n_exc
from quark import exceptions as q_exc
from quark.plugin_modules import ip_policies as ippol
from quark.tests import test_base
from quark.tests import test_quark_plugin
class TestQuarkGetIpPolicies(test_quark_plugin.TestQuarkPlugin):
@contextlib.contextmanager
def _stubs(self, ip_policy):
db_mod = "quark.db.api"
with mock.patch("%s.ip_policy_find" % db_mod) as ip_policy_find:
ip_policy_find.return_value = ip_policy
yield
def test_get_ip_policy_not_found(self):
with self._stubs(None):
with self.assertRaises(q_exc.IPPolicyNotFound):
self.plugin.get_ip_policy(self.context, 1)
def test_get_ip_policy(self):
ip_policy = dict(
id=1,
tenant_id=1,
name="foo",
subnets=[dict(id=1)],
networks=[dict(id=2)],
exclude=[dict(cidr="0.0.0.0/32")])
with self._stubs(ip_policy):
resp = self.plugin.get_ip_policy(self.context, 1)
self.assertEqual(len(resp.keys()), 6)
self.assertEqual(resp["id"], 1)
self.assertEqual(resp["name"], "foo")
self.assertEqual(resp["subnet_ids"], [1])
self.assertEqual(resp["network_ids"], [2])
self.assertEqual(resp["exclude"], ["0.0.0.0/32"])
self.assertEqual(resp["tenant_id"], 1)
def test_get_ip_policies(self):
ip_policy = dict(
id=1,
tenant_id=1,
name="foo",
subnets=[dict(id=1)],
networks=[dict(id=2)],
exclude=[dict(cidr="0.0.0.0/32")])
with self._stubs([ip_policy]):
resp = self.plugin.get_ip_policies(self.context)
self.assertEqual(len(resp), 1)
resp = resp[0]
self.assertEqual(len(resp.keys()), 6)
self.assertEqual(resp["id"], 1)
self.assertEqual(resp["subnet_ids"], [1])
self.assertEqual(resp["network_ids"], [2])
self.assertEqual(resp["exclude"], ["0.0.0.0/32"])
self.assertEqual(resp["name"], "foo")
self.assertEqual(resp["tenant_id"], 1)
class TestQuarkCreateIpPolicies(test_quark_plugin.TestQuarkPlugin):
@contextlib.contextmanager
def _stubs(self, ip_policy, subnets=None, nets=None):
db_mod = "quark.db.api"
with contextlib.nested(
mock.patch("%s.subnet_find" % db_mod),
mock.patch("%s.network_find" % db_mod),
mock.patch("%s.ip_policy_create" % db_mod),
mock.patch("%s.route_find" % db_mod)
) as (subnet_find, net_find, ip_policy_create, route_find):
subnet_find.return_value = subnets if subnets else None
net_find.return_value = nets if nets else None
ip_policy_create.return_value = ip_policy
route_find.return_value = [{"nexthop": "1.2.3.4"}]
yield ip_policy_create
def test_create_ip_policy_invalid_body_missing_exclude(self):
with self._stubs(None):
with self.assertRaises(n_exc.BadRequest):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict()))
def test_create_ip_policy_with_both_network_and_subnet_ids(self):
with self._stubs(None):
with self.assertRaises(n_exc.BadRequest):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(network_ids=[1], subnet_ids=[1])))
def test_create_ip_policy_invalid_body_missing_netsubnet(self):
with self._stubs(None):
with self.assertRaises(n_exc.BadRequest):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(exclude=["1.1.1.1/24"])))
def test_create_ip_policy_invalid_subnet(self):
with self._stubs(None):
with self.assertRaises(n_exc.SubnetNotFound):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[1],
exclude=["1.1.1.1/24"])))
def test_create_ip_policy_invalid_network(self):
with self._stubs(None):
with self.assertRaises(n_exc.NetworkNotFound):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(network_ids=[1],
exclude=["1.1.1.1/24"])))
def test_create_ip_policy_network_ip_policy_already_exists(self):
with self._stubs(None, nets=[dict(id=1, ip_policy=dict(id=2),
subnets=[dict(id=1,
cidr="1.1.1.1/16")])]):
with self.assertRaises(q_exc.IPPolicyAlreadyExists):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(network_ids=[1],
exclude=["1.1.1.1/24"])))
def test_create_ip_policy_subnet_ip_policy_already_exists(self):
with self._stubs(None, subnets=[dict(id=1, ip_policy=dict(id=2),
cidr="1.1.1.1/16")]):
with self.assertRaises(q_exc.IPPolicyAlreadyExists):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[1],
exclude=["1.1.1.1/24"])))
def test_create_ip_policy_network(self):
ipp = dict(subnet_id=None, network_id=1,
exclude=["1.1.1.1/24"])
with self._stubs(ipp, nets=[dict(id=1, ip_policy=dict(id=2),
subnets=[dict(id=1,
cidr="1.1.1.1/16")])]):
with self.assertRaises(q_exc.IPPolicyAlreadyExists):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(network_ids=[ipp["network_id"]],
exclude=ipp["exclude"])))
def test_create_ip_policy_subnet(self):
ipp = dict(subnet_id=1, network_id=None,
exclude=["1.1.1.1/24"])
with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=2),
cidr="1.1.1.1/16")]):
with self.assertRaises(q_exc.IPPolicyAlreadyExists):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[ipp["subnet_id"]],
exclude=ipp["exclude"])))
def test_create_ip_policy_with_cidr_that_does_not_fit_into_subnet(self):
ipp = dict(
subnets=[dict(id=1, version=4, cidr="192.168.1.1/24")],
networks=[],
id=1,
tenant_id=1,
exclude=["10.10.10.100/32"],
name="foo")
with self._stubs(ipp,
subnets=[dict(id=1, ip_policy=None,
version=ipp["subnets"][0]["version"],
cidr=ipp["subnets"][0]["cidr"])]):
with self.assertRaises(n_exc.BadRequest):
self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[1],
exclude=ipp["exclude"])))
def test_create_ip_policy_with_ipv6_subnet_cidr(self):
ipp = dict(
subnets=[dict(id=1, version=6, cidr='::/64')],
networks=[],
id=1,
tenant_id=1,
exclude=[dict(cidr="::/128")],
name="foo")
with self._stubs(ipp,
subnets=[dict(id=1, ip_policy=None,
version=ipp["subnets"][0]["version"],
cidr=ipp["subnets"][0]["cidr"])]):
exclude = [ippc["cidr"] for ippc in ipp["exclude"]]
resp = self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[1], exclude=exclude)))
self.assertEqual(len(resp.keys()), 6)
self.assertEqual(resp["subnet_ids"], [1])
self.assertEqual(resp["network_ids"], [])
# NOTE(jmeridth): below is mocked that way, so it won't get
# additional default policies in exclude
# ippol.ensure_default_policy is tested below in this file
self.assertEqual(resp["exclude"], ["::/128"])
self.assertEqual(resp["name"], "foo")
self.assertEqual(resp["tenant_id"], 1)
def test_create_ip_policy(self):
ipp = dict(
subnets=[dict(id=1, cidr='0.0.0.0/16')],
networks=[],
id=1,
tenant_id=1,
exclude=[dict(cidr="0.0.0.0/24")],
name="foo")
with self._stubs(ipp, subnets=[dict(
id=1, ip_policy=None, cidr=ipp["subnets"][0]["cidr"])]):
exclude = [ippc["cidr"] for ippc in ipp["exclude"]]
resp = self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[1], exclude=exclude)))
self.assertEqual(len(resp.keys()), 6)
self.assertEqual(resp["subnet_ids"], [1])
self.assertEqual(resp["network_ids"], [])
# NOTE(jmeridth): below is mocked that way, so it won't get
# additional default policies in exclude
# ippol.ensure_default_policy is tested below in this file
self.assertEqual(resp["exclude"], ["0.0.0.0/24"])
self.assertEqual(resp["name"], "foo")
self.assertEqual(resp["tenant_id"], 1)
def test_create_ip_policy_only_called_once_with_multiple_networks(self):
ipp = dict(
subnets=[],
networks=[dict(id=1, subnets=[dict(id=1,
ip_policy=None, cidr='0.0.0.0/24')]),
dict(id=2, subnets=[dict(id=2,
ip_policy=None, cidr='0.0.0.0/24')])],
id=1,
tenant_id=1,
exclude=[dict(cidr="0.0.0.1/32")],
name="foo")
with self._stubs(ipp, nets=ipp["networks"]) as (ip_policy_create):
resp = self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(network_ids=[1, 2], exclude=["0.0.0.1/32"])))
exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.0.255/32']
ip_policy_create.assert_called_once_with(
self.context, exclude=exclude,
networks=[{'subnets':
[{'cidr': '0.0.0.0/24', 'ip_policy': None,
'id': 1}], 'id': 1},
{'subnets':
[{'cidr': '0.0.0.0/24', 'ip_policy': None,
'id': 2}], 'id': 2}])
self.assertEqual(len(resp.keys()), 6)
self.assertEqual(resp["subnet_ids"], [])
self.assertEqual(resp["network_ids"], [1, 2])
# NOTE(jmeridth): below is mocked that way, so it won't get
# additional default policies in exclude
# ippol.ensure_default_policy is tested below in this file
self.assertEqual(resp["exclude"], ["0.0.0.1/32"])
self.assertEqual(resp["name"], "foo")
self.assertEqual(resp["tenant_id"], 1)
def test_create_ip_policy_only_called_once_with_multiple_subnets(self):
ipp = dict(
subnets=[dict(id=3, cidr='0.0.0.0/16'),
dict(id=4, cidr='0.0.0.0/16')],
networks=[],
id=1,
tenant_id=1,
exclude=[dict(cidr="0.0.0.1/32")],
name="foo")
with self._stubs(ipp, subnets=ipp["subnets"]) as (ip_policy_create):
resp = self.plugin.create_ip_policy(self.context, dict(
ip_policy=dict(subnet_ids=[3, 4], exclude=["0.0.0.1/32"])))
exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.255.255/32']
ip_policy_create.assert_called_once_with(
self.context, exclude=exclude,
subnets=[{'cidr': '0.0.0.0/16', 'id': 3},
{'cidr': '0.0.0.0/16', 'id': 4}])
self.assertEqual(len(resp.keys()), 6)
self.assertEqual(resp["subnet_ids"], [3, 4])
self.assertEqual(resp["network_ids"], [])
# NOTE(jmeridth): below is mocked that way, so it won't get
# additional default policies in exclude
# ippol.ensure_default_policy is tested below in this file
self.assertEqual(resp["exclude"], ["0.0.0.1/32"])
self.assertEqual(resp["name"], "foo")
self.assertEqual(resp["tenant_id"], 1)
class TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):
@contextlib.contextmanager
def _stubs(self, ip_policy, subnets=None, networks=None):
if not subnets:
subnets = []
if not networks:
networks = []
db_mod = "quark.db.api"
with contextlib.nested(
mock.patch("%s.ip_policy_find" % db_mod),
mock.patch("%s.subnet_find" % db_mod),
mock.patch("%s.network_find" % db_mod),
mock.patch("%s.ip_policy_update" % db_mod),
) as (ip_policy_find, subnet_find, network_find, ip_policy_update):
ip_policy_find.return_value = ip_policy
subnet_find.return_value = subnets
network_find.return_value = networks
yield ip_policy_update
def test_update_ip_policy_not_found(self):
with self._stubs(None):
with self.assertRaises(q_exc.IPPolicyNotFound):
self.plugin.update_ip_policy(self.context, 1,
dict(ip_policy=None))
def test_update_ip_policy_with_both_network_and_subnet_ids(self):
ipp = dict(id=1, subnets=[])
with self._stubs(ipp):
with self.assertRaises(n_exc.BadRequest):
self.plugin.update_ip_policy(self.context, 1, dict(
ip_policy=dict(network_ids=[1], subnet_ids=[1])))
def test_update_ip_policy_subnets_not_found(self):
ipp = dict(id=1, subnets=[])
with self._stubs(ipp):
with self.assertRaises(n_exc.SubnetNotFound):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(subnet_ids=[100])))
def test_update_ip_policy_subnets_already_exists(self):
ipp = dict(id=1, subnets=[dict()])
with self._stubs(
ipp, subnets=[dict(id=1, ip_policy=dict(id=1))]
):
with self.assertRaises(q_exc.IPPolicyAlreadyExists):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(subnet_ids=[100])))
def test_update_ip_policy_subnets(self):
ipp = dict(id=1, subnets=[dict()],
exclude=["0.0.0.0/24"],
name="foo", tenant_id=1)
with self._stubs(
ipp, subnets=[dict(id=1, ip_policy=None)]
) as (ip_policy_update):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(subnet_ids=[100])))
self.assertEqual(ip_policy_update.called, 1)
def test_update_ip_policy_subnets_empty_exclude(self):
ipp = dict(id=1, subnets=[dict()],
exclude=["0.0.0.40/32"],
name="foo", tenant_id=1)
with self._stubs(
ipp, subnets=[dict(id=1, cidr="0.0.0.0/16", ip_policy=None)]
) as (ip_policy_update):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(subnet_ids=[100], exclude=[])))
ip_policy_update.assert_called_once_with(
self.context, ipp, subnet_ids=[100], exclude=[
"0.0.0.0/32", "0.0.255.255/32"])
def test_update_ip_policy_subnets_empty_exclude_without_subnet_ids(self):
ipp = dict(id=1, subnets=[dict(cidr="0.0.0.0/16")],
exclude=["0.0.0.40/32"],
name="foo", tenant_id=1)
with self._stubs(ipp) as (ip_policy_update):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(exclude=[])))
ip_policy_update.assert_called_once_with(
self.context, ipp, exclude=["0.0.0.0/32", "0.0.255.255/32"])
def test_update_ip_policy_networks_not_found(self):
ipp = dict(id=1, networks=[])
with self._stubs(ipp):
with self.assertRaises(n_exc.NetworkNotFound):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(network_ids=[100])))
def test_update_ip_policy_networks(self):
ipp = dict(id=1, networks=[dict()],
exclude=["0.0.0.0/24"],
name="foo", tenant_id=1)
with self._stubs(
ipp, networks=[dict(id=1, ip_policy=None)]
) as (ip_policy_update):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(network_ids=[100])))
self.assertEqual(ip_policy_update.called, 1)
def test_update_ip_policy_exclude_v4(self):
subnets = [dict(id=100, cidr="0.0.0.0/16")]
ipp = dict(id=1, subnets=subnets,
exclude=["0.0.0.0/24"],
name="foo", tenant_id=1)
with self._stubs(ipp, subnets=subnets) as (ip_policy_update):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(subnet_ids=[100], exclude=["0.0.0.1/32"])))
ip_policy_update.assert_called_once_with(
self.context,
ipp,
subnet_ids=[100],
exclude=["0.0.0.1/32", "0.0.0.0/32", "0.0.255.255/32"])
def test_update_ip_policy_exclude_v6(self):
subnets = [dict(id=100, cidr="::/64")]
ipp = dict(id=1, subnets=subnets,
exclude=["::/128"],
name="foo", tenant_id=1)
with self._stubs(ipp, subnets=subnets) as (ip_policy_update):
self.plugin.update_ip_policy(
self.context,
1,
dict(ip_policy=dict(subnet_ids=[100], exclude=["::1/128"])))
ip_policy_update.assert_called_once_with(
self.context,
ipp,
subnet_ids=[100],
exclude=["::1/128", "::/128", "::ffff:ffff:ffff:ffff/128"])
class TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin):
@contextlib.contextmanager
def _stubs(self, ip_policy):
db_mod = "quark.db.api"
with contextlib.nested(
mock.patch("%s.ip_policy_find" % db_mod),
mock.patch("%s.ip_policy_delete" % db_mod),
) as (ip_policy_find, ip_policy_delete):
ip_policy_find.return_value = ip_policy
yield ip_policy_find, ip_policy_delete
def test_delete_ip_policy_not_found(self):
with self._stubs(None):
with self.assertRaises(q_exc.IPPolicyNotFound):
self.plugin.delete_ip_policy(self.context, 1)
def test_delete_ip_policy_in_use(self):
with self._stubs(dict(networks=True)):
with self.assertRaises(q_exc.IPPolicyInUse):
self.plugin.delete_ip_policy(self.context, 1)
def test_delete_ip_policy(self):
ip_policy = dict(
id=1,
networks=[],
subnets=[])
with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete):
self.plugin.delete_ip_policy(self.context, 1)
self.assertEqual(ip_policy_find.call_count, 1)
self.assertEqual(ip_policy_delete.call_count, 1)
class TestQuarkUpdatePolicySubnetWithRoutes(test_quark_plugin.TestQuarkPlugin):
@contextlib.contextmanager
def _stubs(self, ip_policy, subnets=None, routes=None):
subnets = subnets or []
db_mod = "quark.db.api"
with contextlib.nested(
mock.patch("%s.ip_policy_find" % db_mod),
mock.patch("%s.subnet_find" % db_mod),
mock.patch("%s.route_find" % db_mod),
mock.patch("%s.ip_policy_update" % db_mod),
) as (ip_policy_find, subnet_find, route_find, ip_policy_update):
ip_policy_find.return_value = ip_policy
subnet_find.return_value = subnets
route_find.return_value = routes
yield ip_policy_update
def test_update_ip_policy_has_route_conflict_raises(self):
subnet = dict(id=1, cidr="192.168.0.0/24")
ipp = dict(id=1, subnets=[subnet], exclude=["192.168.0.1/32"],
name="foo", tenant_id=1)
route = {"gateway": "192.168.0.1", "subnet_id": subnet["id"]}
with self._stubs(ipp, subnets=[subnet], routes=[route]):
with self.assertRaises(
n_exc_ext.GatewayConflictWithAllocationPools):
self.plugin.update_ip_policy(
self.context, 1,
dict(ip_policy=dict(subnet_ids=[1], exclude=[])))
def test_update_ip_policy_no_route_conflict(self):
subnet = dict(id=1, cidr="192.168.0.0/24")
ipp = dict(id=1, subnets=[subnet], exclude=["192.168.0.1/32"],
name="foo", tenant_id=1)
route = {"gateway": "192.168.0.1", "subnet_id": subnet["id"]}
with self._stubs(ipp, subnets=[subnet], routes=[route]):
try:
self.plugin.update_ip_policy(
self.context, 1,
dict(ip_policy=dict(subnet_ids=[1],
exclude=["192.168.0.0/24"])))
except Exception as e:
self.fail("This shouldn't have raised: %s" % e)
class TestQuarkValidateCIDRsFitsIntoSubnets(test_quark_plugin.TestQuarkPlugin):
def test_normal_cidr_and_valid_subnet(self):
try:
ippol._validate_cidrs_fit_into_subnets(
["192.168.0.100/32"],
[dict(id=1, cidr="192.168.0.0/24")])
except Exception:
self.fail("Should not have failed")
def test_normal_ipv4_cidr_and_valid_ipv6_subnet(self):
try:
ippol._validate_cidrs_fit_into_subnets(
["192.168.0.100/32"], [dict(id=1, cidr="::/96")])
except Exception:
self.fail("Should not have failed")
def test_normal_ipv6_cidr_and_valid_ipv6_subnet(self):
try:
ippol._validate_cidrs_fit_into_subnets(
["::/128"], [dict(id=1, cidr="::/96")])
except Exception:
self.fail("Should not have failed")
def test_normal_ipv6_cidr_and_valid_ipv4_subnet(self):
try:
ippol._validate_cidrs_fit_into_subnets(
["::/128"], [dict(id=1, cidr="192.168.0.0/24")])
except Exception:
self.fail("Should not have failed")
def test_normal_cidr_and_multiple_valid_subnet(self):
try:
ippol._validate_cidrs_fit_into_subnets(
["192.168.0.100/32"],
[dict(id=1, cidr="192.168.0.0/24"),
dict(id=2, cidr="192.168.0.0/16")])
except Exception:
self.fail("Should not have failed")
def test_normal_ipv6_cidr_and_multiple_valid_ipv6_subnet(self):
try:
ippol._validate_cidrs_fit_into_subnets(
["::/128"],
[dict(id=1, cidr="::/96"),
dict(id=2, cidr="::/64")])
except Exception:
self.fail("Should not have failed")
def test_normal_cidr_and_invalid_subnet(self):
with self.assertRaises(n_exc.BadRequest):
ippol._validate_cidrs_fit_into_subnets(
["192.168.0.100/32"],
[dict(id=1, cidr="10.10.10.0/24")])
def test_normal_ipv6_cidr_and_invalid_ipv6_subnet(self):
with self.assertRaises(n_exc.BadRequest):
ippol._validate_cidrs_fit_into_subnets(
["::/64"], [dict(id=1, cidr="::/96")])
def test_normal_cidr_and_one_invalid_and_one_valid_subnet(self):
with self.assertRaises(n_exc.BadRequest):
ippol._validate_cidrs_fit_into_subnets(
["192.168.0.100/32"],
[dict(id=1, cidr="10.10.10.0/24"),
dict(id=1, cidr="192.168.0.0/24")])
def test_normal_ipv6_cidr_and_one_invalid_and_one_valid_ipv6_subnet(self):
with self.assertRaises(n_exc.BadRequest):
ippol._validate_cidrs_fit_into_subnets(
["::/127"],
[dict(id=1, cidr="::/96"),
dict(id=1, cidr="::/128")])
class TestQuarkEnsureDefaultPolicy(test_base.TestBase):
def test_no_cidrs_no_subnets(self):
cidrs = []
subnets = []
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, [])
self.assertEqual(subnets, [])
def test_no_cidrs_v4(self):
cidrs = []
subnets = [dict(cidr="192.168.10.1/24")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["192.168.10.0/32", "192.168.10.255/32"])
self.assertEqual(subnets, [dict(cidr="192.168.10.1/24")])
def test_no_subnets_v4(self):
cidrs = ["192.168.10.0/32", "192.168.10.255/32"]
subnets = []
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["192.168.10.0/32", "192.168.10.255/32"])
self.assertEqual(subnets, [])
def test_cidrs_without_default_cidrs_v4(self):
cidrs = ["192.168.10.20/32", "192.168.10.40/32"]
subnets = [dict(cidr="192.168.10.1/24")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["192.168.10.20/32", "192.168.10.40/32",
"192.168.10.0/32", "192.168.10.255/32"])
self.assertEqual(subnets, [dict(cidr="192.168.10.1/24")])
def test_cidrs_with_default_cidrs_v4(self):
cidrs = ["192.168.10.0/32", "192.168.10.255/32"]
subnets = [dict(cidr="192.168.10.1/24")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["192.168.10.0/32", "192.168.10.255/32"])
self.assertEqual(subnets, [dict(cidr="192.168.10.1/24")])
def test_no_cidrs_v6(self):
cidrs = []
subnets = [dict(cidr="::/64")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["::/128", "::ffff:ffff:ffff:ffff/128"])
self.assertEqual(subnets, [dict(cidr="::/64")])
def test_no_subnets_v6(self):
cidrs = ["::/128", "::ffff:ffff:ffff:ffff/128"]
subnets = []
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["::/128", "::ffff:ffff:ffff:ffff/128"])
self.assertEqual(subnets, [])
def test_cidrs_without_default_cidrs_v6(self):
cidrs = ["::10/128", "::20/128"]
subnets = [dict(cidr="::/64")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["::10/128", "::20/128",
"::/128", "::ffff:ffff:ffff:ffff/128"])
self.assertEqual(subnets, [dict(cidr="::/64")])
def test_cidrs_with_default_cidrs_v6(self):
cidrs = ["::/128", "::ffff:ffff:ffff:ffff/128"]
subnets = [dict(cidr="::/64")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["::/128", "::ffff:ffff:ffff:ffff/128"])
self.assertEqual(subnets, [dict(cidr="::/64")])
def test_no_duplicates_in_result_when_called_twice(self):
cidrs = ["192.168.10.10/32"]
subnets = [dict(cidr="192.168.10.0/24")]
self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))
self.assertEqual(cidrs, ["192.168.10.10/32", "192.168.10.0/32",
"192.168.10.255/32"])
cidrs2 = ["192.168.10.10/32"]
self.assertIsNone(ippol.ensure_default_policy(cidrs2, subnets))
self.assertEqual(cidrs, ["192.168.10.10/32", "192.168.10.0/32",
"192.168.10.255/32"])
self.assertEqual(subnets, [dict(cidr="192.168.10.0/24")])
|
normal
|
{
"blob_id": "cf931da4c06e16fe6f6da5eb1826d8b7a59c1f7b",
"index": 9057,
"step-1": "<mask token>\n\n\nclass TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, networks=None):\n if not subnets:\n subnets = []\n if not networks:\n networks = []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.network_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, network_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n network_find.return_value = networks\n yield ip_policy_update\n\n def test_update_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=None))\n\n def test_update_ip_policy_with_both_network_and_subnet_ids(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[1], subnet_ids=[1])))\n <mask token>\n\n def test_update_ip_policy_subnets_already_exists(self):\n ipp = dict(id=1, subnets=[dict()])\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=1))]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n <mask token>\n\n def test_update_ip_policy_subnets_empty_exclude(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.40/32'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, cidr='0.0.0.0/16',\n ip_policy=None)]) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.0/32', '0.0.255.255/32'])\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy):\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.ip_policy_delete' % db_mod)) as (ip_policy_find,\n ip_policy_delete):\n ip_policy_find.return_value = ip_policy\n yield ip_policy_find, ip_policy_delete\n\n def test_delete_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy_in_use(self):\n with self._stubs(dict(networks=True)):\n with self.assertRaises(q_exc.IPPolicyInUse):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy(self):\n ip_policy = dict(id=1, networks=[], subnets=[])\n with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete):\n self.plugin.delete_ip_policy(self.context, 1)\n self.assertEqual(ip_policy_find.call_count, 1)\n self.assertEqual(ip_policy_delete.call_count, 1)\n\n\nclass TestQuarkUpdatePolicySubnetWithRoutes(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, routes=None):\n subnets = subnets or []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.route_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, route_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n route_find.return_value = routes\n yield ip_policy_update\n\n def test_update_ip_policy_has_route_conflict_raises(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n with self.assertRaises(n_exc_ext.GatewayConflictWithAllocationPools\n ):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=[])))\n\n def test_update_ip_policy_no_route_conflict(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n try:\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=['192.168.0.0/24']))\n )\n except Exception as e:\n self.fail(\"This shouldn't have raised: %s\" % e)\n\n\nclass TestQuarkValidateCIDRsFitsIntoSubnets(test_quark_plugin.TestQuarkPlugin):\n\n def test_normal_cidr_and_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv4_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv4_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_multiple_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24'), dict(id=2, cidr=\n '192.168.0.0/16')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_multiple_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96'), dict(id=2, cidr='::/64')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_invalid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24')])\n\n def test_normal_ipv6_cidr_and_invalid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/64'], [dict(id=1,\n cidr='::/96')])\n\n def test_normal_cidr_and_one_invalid_and_one_valid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24'), dict(id=1, cidr=\n '192.168.0.0/24')])\n\n def test_normal_ipv6_cidr_and_one_invalid_and_one_valid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/127'], [dict(id=1,\n cidr='::/96'), dict(id=1, cidr='::/128')])\n\n\nclass TestQuarkEnsureDefaultPolicy(test_base.TestBase):\n\n def test_no_cidrs_no_subnets(self):\n cidrs = []\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [])\n self.assertEqual(subnets, [])\n\n def test_no_cidrs_v4(self):\n cidrs = []\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_subnets_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v4(self):\n cidrs = ['192.168.10.20/32', '192.168.10.40/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.20/32', '192.168.10.40/32',\n '192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_cidrs_with_default_cidrs_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_cidrs_v6(self):\n cidrs = []\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_subnets_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v6(self):\n cidrs = ['::10/128', '::20/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::10/128', '::20/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_cidrs_with_default_cidrs_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_duplicates_in_result_when_called_twice(self):\n cidrs = ['192.168.10.10/32']\n subnets = [dict(cidr='192.168.10.0/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n cidrs2 = ['192.168.10.10/32']\n self.assertIsNone(ippol.ensure_default_policy(cidrs2, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.0/24')])\n",
"step-2": "<mask token>\n\n\nclass TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, networks=None):\n if not subnets:\n subnets = []\n if not networks:\n networks = []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.network_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, network_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n network_find.return_value = networks\n yield ip_policy_update\n\n def test_update_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=None))\n\n def test_update_ip_policy_with_both_network_and_subnet_ids(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[1], subnet_ids=[1])))\n\n def test_update_ip_policy_subnets_not_found(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.SubnetNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets_already_exists(self):\n ipp = dict(id=1, subnets=[dict()])\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=1))]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=None)]\n ) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_subnets_empty_exclude(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.40/32'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, cidr='0.0.0.0/16',\n ip_policy=None)]) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.0/32', '0.0.255.255/32'])\n\n def test_update_ip_policy_subnets_empty_exclude_without_subnet_ids(self):\n ipp = dict(id=1, subnets=[dict(cidr='0.0.0.0/16')], exclude=[\n '0.0.0.40/32'], name='foo', tenant_id=1)\n with self._stubs(ipp) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n exclude=['0.0.0.0/32', '0.0.255.255/32'])\n <mask token>\n\n def test_update_ip_policy_networks(self):\n ipp = dict(id=1, networks=[dict()], exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, networks=[dict(id=1, ip_policy=None)]\n ) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(network_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_exclude_v4(self):\n subnets = [dict(id=100, cidr='0.0.0.0/16')]\n ipp = dict(id=1, subnets=subnets, exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=['0.0.0.1/32'])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.1/32', '0.0.0.0/32',\n '0.0.255.255/32'])\n\n def test_update_ip_policy_exclude_v6(self):\n subnets = [dict(id=100, cidr='::/64')]\n ipp = dict(id=1, subnets=subnets, exclude=['::/128'], name='foo',\n tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=['::1/128'])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['::1/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n\n\nclass TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy):\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.ip_policy_delete' % db_mod)) as (ip_policy_find,\n ip_policy_delete):\n ip_policy_find.return_value = ip_policy\n yield ip_policy_find, ip_policy_delete\n\n def test_delete_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy_in_use(self):\n with self._stubs(dict(networks=True)):\n with self.assertRaises(q_exc.IPPolicyInUse):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy(self):\n ip_policy = dict(id=1, networks=[], subnets=[])\n with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete):\n self.plugin.delete_ip_policy(self.context, 1)\n self.assertEqual(ip_policy_find.call_count, 1)\n self.assertEqual(ip_policy_delete.call_count, 1)\n\n\nclass TestQuarkUpdatePolicySubnetWithRoutes(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, routes=None):\n subnets = subnets or []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.route_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, route_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n route_find.return_value = routes\n yield ip_policy_update\n\n def test_update_ip_policy_has_route_conflict_raises(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n with self.assertRaises(n_exc_ext.GatewayConflictWithAllocationPools\n ):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=[])))\n\n def test_update_ip_policy_no_route_conflict(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n try:\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=['192.168.0.0/24']))\n )\n except Exception as e:\n self.fail(\"This shouldn't have raised: %s\" % e)\n\n\nclass TestQuarkValidateCIDRsFitsIntoSubnets(test_quark_plugin.TestQuarkPlugin):\n\n def test_normal_cidr_and_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv4_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv4_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_multiple_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24'), dict(id=2, cidr=\n '192.168.0.0/16')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_multiple_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96'), dict(id=2, cidr='::/64')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_invalid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24')])\n\n def test_normal_ipv6_cidr_and_invalid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/64'], [dict(id=1,\n cidr='::/96')])\n\n def test_normal_cidr_and_one_invalid_and_one_valid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24'), dict(id=1, cidr=\n '192.168.0.0/24')])\n\n def test_normal_ipv6_cidr_and_one_invalid_and_one_valid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/127'], [dict(id=1,\n cidr='::/96'), dict(id=1, cidr='::/128')])\n\n\nclass TestQuarkEnsureDefaultPolicy(test_base.TestBase):\n\n def test_no_cidrs_no_subnets(self):\n cidrs = []\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [])\n self.assertEqual(subnets, [])\n\n def test_no_cidrs_v4(self):\n cidrs = []\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_subnets_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v4(self):\n cidrs = ['192.168.10.20/32', '192.168.10.40/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.20/32', '192.168.10.40/32',\n '192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_cidrs_with_default_cidrs_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_cidrs_v6(self):\n cidrs = []\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_subnets_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v6(self):\n cidrs = ['::10/128', '::20/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::10/128', '::20/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_cidrs_with_default_cidrs_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_duplicates_in_result_when_called_twice(self):\n cidrs = ['192.168.10.10/32']\n subnets = [dict(cidr='192.168.10.0/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n cidrs2 = ['192.168.10.10/32']\n self.assertIsNone(ippol.ensure_default_policy(cidrs2, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.0/24')])\n",
"step-3": "<mask token>\n\n\nclass TestQuarkCreateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n <mask token>\n <mask token>\n <mask token>\n\n def test_create_ip_policy_invalid_body_missing_netsubnet(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(exclude=['1.1.1.1/24'])))\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def test_create_ip_policy_network(self):\n ipp = dict(subnet_id=None, network_id=1, exclude=['1.1.1.1/24'])\n with self._stubs(ipp, nets=[dict(id=1, ip_policy=dict(id=2),\n subnets=[dict(id=1, cidr='1.1.1.1/16')])]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(network_ids=[ipp['network_id']], exclude=ipp[\n 'exclude'])))\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def test_create_ip_policy_only_called_once_with_multiple_networks(self):\n ipp = dict(subnets=[], networks=[dict(id=1, subnets=[dict(id=1,\n ip_policy=None, cidr='0.0.0.0/24')]), dict(id=2, subnets=[dict(\n id=2, ip_policy=None, cidr='0.0.0.0/24')])], id=1, tenant_id=1,\n exclude=[dict(cidr='0.0.0.1/32')], name='foo')\n with self._stubs(ipp, nets=ipp['networks']) as ip_policy_create:\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[1, 2], exclude=['0.0.0.1/32'])))\n exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.0.255/32']\n ip_policy_create.assert_called_once_with(self.context, exclude=\n exclude, networks=[{'subnets': [{'cidr': '0.0.0.0/24',\n 'ip_policy': None, 'id': 1}], 'id': 1}, {'subnets': [{\n 'cidr': '0.0.0.0/24', 'ip_policy': None, 'id': 2}], 'id': 2}])\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp['subnet_ids'], [])\n self.assertEqual(resp['network_ids'], [1, 2])\n self.assertEqual(resp['exclude'], ['0.0.0.1/32'])\n self.assertEqual(resp['name'], 'foo')\n self.assertEqual(resp['tenant_id'], 1)\n <mask token>\n\n\nclass TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, networks=None):\n if not subnets:\n subnets = []\n if not networks:\n networks = []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.network_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, network_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n network_find.return_value = networks\n yield ip_policy_update\n\n def test_update_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=None))\n\n def test_update_ip_policy_with_both_network_and_subnet_ids(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[1], subnet_ids=[1])))\n\n def test_update_ip_policy_subnets_not_found(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.SubnetNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets_already_exists(self):\n ipp = dict(id=1, subnets=[dict()])\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=1))]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=None)]\n ) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_subnets_empty_exclude(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.40/32'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, cidr='0.0.0.0/16',\n ip_policy=None)]) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.0/32', '0.0.255.255/32'])\n\n def test_update_ip_policy_subnets_empty_exclude_without_subnet_ids(self):\n ipp = dict(id=1, subnets=[dict(cidr='0.0.0.0/16')], exclude=[\n '0.0.0.40/32'], name='foo', tenant_id=1)\n with self._stubs(ipp) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n exclude=['0.0.0.0/32', '0.0.255.255/32'])\n\n def test_update_ip_policy_networks_not_found(self):\n ipp = dict(id=1, networks=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.NetworkNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[100])))\n\n def test_update_ip_policy_networks(self):\n ipp = dict(id=1, networks=[dict()], exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, networks=[dict(id=1, ip_policy=None)]\n ) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(network_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_exclude_v4(self):\n subnets = [dict(id=100, cidr='0.0.0.0/16')]\n ipp = dict(id=1, subnets=subnets, exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=['0.0.0.1/32'])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.1/32', '0.0.0.0/32',\n '0.0.255.255/32'])\n\n def test_update_ip_policy_exclude_v6(self):\n subnets = [dict(id=100, cidr='::/64')]\n ipp = dict(id=1, subnets=subnets, exclude=['::/128'], name='foo',\n tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=['::1/128'])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['::1/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n\n\nclass TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy):\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.ip_policy_delete' % db_mod)) as (ip_policy_find,\n ip_policy_delete):\n ip_policy_find.return_value = ip_policy\n yield ip_policy_find, ip_policy_delete\n\n def test_delete_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy_in_use(self):\n with self._stubs(dict(networks=True)):\n with self.assertRaises(q_exc.IPPolicyInUse):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy(self):\n ip_policy = dict(id=1, networks=[], subnets=[])\n with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete):\n self.plugin.delete_ip_policy(self.context, 1)\n self.assertEqual(ip_policy_find.call_count, 1)\n self.assertEqual(ip_policy_delete.call_count, 1)\n\n\nclass TestQuarkUpdatePolicySubnetWithRoutes(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, routes=None):\n subnets = subnets or []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.route_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, route_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n route_find.return_value = routes\n yield ip_policy_update\n\n def test_update_ip_policy_has_route_conflict_raises(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n with self.assertRaises(n_exc_ext.GatewayConflictWithAllocationPools\n ):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=[])))\n\n def test_update_ip_policy_no_route_conflict(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n try:\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=['192.168.0.0/24']))\n )\n except Exception as e:\n self.fail(\"This shouldn't have raised: %s\" % e)\n\n\nclass TestQuarkValidateCIDRsFitsIntoSubnets(test_quark_plugin.TestQuarkPlugin):\n\n def test_normal_cidr_and_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv4_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv4_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_multiple_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24'), dict(id=2, cidr=\n '192.168.0.0/16')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_multiple_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96'), dict(id=2, cidr='::/64')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_invalid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24')])\n\n def test_normal_ipv6_cidr_and_invalid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/64'], [dict(id=1,\n cidr='::/96')])\n\n def test_normal_cidr_and_one_invalid_and_one_valid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24'), dict(id=1, cidr=\n '192.168.0.0/24')])\n\n def test_normal_ipv6_cidr_and_one_invalid_and_one_valid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/127'], [dict(id=1,\n cidr='::/96'), dict(id=1, cidr='::/128')])\n\n\nclass TestQuarkEnsureDefaultPolicy(test_base.TestBase):\n\n def test_no_cidrs_no_subnets(self):\n cidrs = []\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [])\n self.assertEqual(subnets, [])\n\n def test_no_cidrs_v4(self):\n cidrs = []\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_subnets_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v4(self):\n cidrs = ['192.168.10.20/32', '192.168.10.40/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.20/32', '192.168.10.40/32',\n '192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_cidrs_with_default_cidrs_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_cidrs_v6(self):\n cidrs = []\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_subnets_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v6(self):\n cidrs = ['::10/128', '::20/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::10/128', '::20/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_cidrs_with_default_cidrs_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_duplicates_in_result_when_called_twice(self):\n cidrs = ['192.168.10.10/32']\n subnets = [dict(cidr='192.168.10.0/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n cidrs2 = ['192.168.10.10/32']\n self.assertIsNone(ippol.ensure_default_policy(cidrs2, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.0/24')])\n",
"step-4": "<mask token>\n\n\nclass TestQuarkCreateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, nets=None):\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.subnet_find' % db_mod), mock.\n patch('%s.network_find' % db_mod), mock.patch(\n '%s.ip_policy_create' % db_mod), mock.patch('%s.route_find' %\n db_mod)) as (subnet_find, net_find, ip_policy_create, route_find):\n subnet_find.return_value = subnets if subnets else None\n net_find.return_value = nets if nets else None\n ip_policy_create.return_value = ip_policy\n route_find.return_value = [{'nexthop': '1.2.3.4'}]\n yield ip_policy_create\n <mask token>\n\n def test_create_ip_policy_with_both_network_and_subnet_ids(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(network_ids=[1], subnet_ids=[1])))\n\n def test_create_ip_policy_invalid_body_missing_netsubnet(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(exclude=['1.1.1.1/24'])))\n <mask token>\n <mask token>\n\n def test_create_ip_policy_network_ip_policy_already_exists(self):\n with self._stubs(None, nets=[dict(id=1, ip_policy=dict(id=2),\n subnets=[dict(id=1, cidr='1.1.1.1/16')])]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(network_ids=[1], exclude=['1.1.1.1/24'])))\n\n def test_create_ip_policy_subnet_ip_policy_already_exists(self):\n with self._stubs(None, subnets=[dict(id=1, ip_policy=dict(id=2),\n cidr='1.1.1.1/16')]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(subnet_ids=[1], exclude=['1.1.1.1/24'])))\n\n def test_create_ip_policy_network(self):\n ipp = dict(subnet_id=None, network_id=1, exclude=['1.1.1.1/24'])\n with self._stubs(ipp, nets=[dict(id=1, ip_policy=dict(id=2),\n subnets=[dict(id=1, cidr='1.1.1.1/16')])]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(network_ids=[ipp['network_id']], exclude=ipp[\n 'exclude'])))\n\n def test_create_ip_policy_subnet(self):\n ipp = dict(subnet_id=1, network_id=None, exclude=['1.1.1.1/24'])\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=2),\n cidr='1.1.1.1/16')]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(subnet_ids=[ipp['subnet_id']], exclude=ipp[\n 'exclude'])))\n\n def test_create_ip_policy_with_cidr_that_does_not_fit_into_subnet(self):\n ipp = dict(subnets=[dict(id=1, version=4, cidr='192.168.1.1/24')],\n networks=[], id=1, tenant_id=1, exclude=['10.10.10.100/32'],\n name='foo')\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=None, version=\n ipp['subnets'][0]['version'], cidr=ipp['subnets'][0]['cidr'])]):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(ip_policy=\n dict(subnet_ids=[1], exclude=ipp['exclude'])))\n\n def test_create_ip_policy_with_ipv6_subnet_cidr(self):\n ipp = dict(subnets=[dict(id=1, version=6, cidr='::/64')], networks=\n [], id=1, tenant_id=1, exclude=[dict(cidr='::/128')], name='foo')\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=None, version=\n ipp['subnets'][0]['version'], cidr=ipp['subnets'][0]['cidr'])]):\n exclude = [ippc['cidr'] for ippc in ipp['exclude']]\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1], exclude=exclude)))\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp['subnet_ids'], [1])\n self.assertEqual(resp['network_ids'], [])\n self.assertEqual(resp['exclude'], ['::/128'])\n self.assertEqual(resp['name'], 'foo')\n self.assertEqual(resp['tenant_id'], 1)\n\n def test_create_ip_policy(self):\n ipp = dict(subnets=[dict(id=1, cidr='0.0.0.0/16')], networks=[], id\n =1, tenant_id=1, exclude=[dict(cidr='0.0.0.0/24')], name='foo')\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=None, cidr=ipp[\n 'subnets'][0]['cidr'])]):\n exclude = [ippc['cidr'] for ippc in ipp['exclude']]\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1], exclude=exclude)))\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp['subnet_ids'], [1])\n self.assertEqual(resp['network_ids'], [])\n self.assertEqual(resp['exclude'], ['0.0.0.0/24'])\n self.assertEqual(resp['name'], 'foo')\n self.assertEqual(resp['tenant_id'], 1)\n\n def test_create_ip_policy_only_called_once_with_multiple_networks(self):\n ipp = dict(subnets=[], networks=[dict(id=1, subnets=[dict(id=1,\n ip_policy=None, cidr='0.0.0.0/24')]), dict(id=2, subnets=[dict(\n id=2, ip_policy=None, cidr='0.0.0.0/24')])], id=1, tenant_id=1,\n exclude=[dict(cidr='0.0.0.1/32')], name='foo')\n with self._stubs(ipp, nets=ipp['networks']) as ip_policy_create:\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[1, 2], exclude=['0.0.0.1/32'])))\n exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.0.255/32']\n ip_policy_create.assert_called_once_with(self.context, exclude=\n exclude, networks=[{'subnets': [{'cidr': '0.0.0.0/24',\n 'ip_policy': None, 'id': 1}], 'id': 1}, {'subnets': [{\n 'cidr': '0.0.0.0/24', 'ip_policy': None, 'id': 2}], 'id': 2}])\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp['subnet_ids'], [])\n self.assertEqual(resp['network_ids'], [1, 2])\n self.assertEqual(resp['exclude'], ['0.0.0.1/32'])\n self.assertEqual(resp['name'], 'foo')\n self.assertEqual(resp['tenant_id'], 1)\n\n def test_create_ip_policy_only_called_once_with_multiple_subnets(self):\n ipp = dict(subnets=[dict(id=3, cidr='0.0.0.0/16'), dict(id=4, cidr=\n '0.0.0.0/16')], networks=[], id=1, tenant_id=1, exclude=[dict(\n cidr='0.0.0.1/32')], name='foo')\n with self._stubs(ipp, subnets=ipp['subnets']) as ip_policy_create:\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[3, 4], exclude=['0.0.0.1/32'])))\n exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.255.255/32']\n ip_policy_create.assert_called_once_with(self.context, exclude=\n exclude, subnets=[{'cidr': '0.0.0.0/16', 'id': 3}, {'cidr':\n '0.0.0.0/16', 'id': 4}])\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp['subnet_ids'], [3, 4])\n self.assertEqual(resp['network_ids'], [])\n self.assertEqual(resp['exclude'], ['0.0.0.1/32'])\n self.assertEqual(resp['name'], 'foo')\n self.assertEqual(resp['tenant_id'], 1)\n\n\nclass TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, networks=None):\n if not subnets:\n subnets = []\n if not networks:\n networks = []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.network_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, network_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n network_find.return_value = networks\n yield ip_policy_update\n\n def test_update_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=None))\n\n def test_update_ip_policy_with_both_network_and_subnet_ids(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[1], subnet_ids=[1])))\n\n def test_update_ip_policy_subnets_not_found(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.SubnetNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets_already_exists(self):\n ipp = dict(id=1, subnets=[dict()])\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=1))]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=None)]\n ) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_subnets_empty_exclude(self):\n ipp = dict(id=1, subnets=[dict()], exclude=['0.0.0.40/32'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=[dict(id=1, cidr='0.0.0.0/16',\n ip_policy=None)]) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.0/32', '0.0.255.255/32'])\n\n def test_update_ip_policy_subnets_empty_exclude_without_subnet_ids(self):\n ipp = dict(id=1, subnets=[dict(cidr='0.0.0.0/16')], exclude=[\n '0.0.0.40/32'], name='foo', tenant_id=1)\n with self._stubs(ipp) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(exclude=[])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n exclude=['0.0.0.0/32', '0.0.255.255/32'])\n\n def test_update_ip_policy_networks_not_found(self):\n ipp = dict(id=1, networks=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.NetworkNotFound):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[100])))\n\n def test_update_ip_policy_networks(self):\n ipp = dict(id=1, networks=[dict()], exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, networks=[dict(id=1, ip_policy=None)]\n ) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(network_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_exclude_v4(self):\n subnets = [dict(id=100, cidr='0.0.0.0/16')]\n ipp = dict(id=1, subnets=subnets, exclude=['0.0.0.0/24'], name=\n 'foo', tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=['0.0.0.1/32'])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['0.0.0.1/32', '0.0.0.0/32',\n '0.0.255.255/32'])\n\n def test_update_ip_policy_exclude_v6(self):\n subnets = [dict(id=100, cidr='::/64')]\n ipp = dict(id=1, subnets=subnets, exclude=['::/128'], name='foo',\n tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as ip_policy_update:\n self.plugin.update_ip_policy(self.context, 1, dict(ip_policy=\n dict(subnet_ids=[100], exclude=['::1/128'])))\n ip_policy_update.assert_called_once_with(self.context, ipp,\n subnet_ids=[100], exclude=['::1/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n\n\nclass TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy):\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.ip_policy_delete' % db_mod)) as (ip_policy_find,\n ip_policy_delete):\n ip_policy_find.return_value = ip_policy\n yield ip_policy_find, ip_policy_delete\n\n def test_delete_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy_in_use(self):\n with self._stubs(dict(networks=True)):\n with self.assertRaises(q_exc.IPPolicyInUse):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy(self):\n ip_policy = dict(id=1, networks=[], subnets=[])\n with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete):\n self.plugin.delete_ip_policy(self.context, 1)\n self.assertEqual(ip_policy_find.call_count, 1)\n self.assertEqual(ip_policy_delete.call_count, 1)\n\n\nclass TestQuarkUpdatePolicySubnetWithRoutes(test_quark_plugin.TestQuarkPlugin):\n\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, routes=None):\n subnets = subnets or []\n db_mod = 'quark.db.api'\n with contextlib.nested(mock.patch('%s.ip_policy_find' % db_mod),\n mock.patch('%s.subnet_find' % db_mod), mock.patch(\n '%s.route_find' % db_mod), mock.patch('%s.ip_policy_update' %\n db_mod)) as (ip_policy_find, subnet_find, route_find,\n ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n route_find.return_value = routes\n yield ip_policy_update\n\n def test_update_ip_policy_has_route_conflict_raises(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n with self.assertRaises(n_exc_ext.GatewayConflictWithAllocationPools\n ):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=[])))\n\n def test_update_ip_policy_no_route_conflict(self):\n subnet = dict(id=1, cidr='192.168.0.0/24')\n ipp = dict(id=1, subnets=[subnet], exclude=['192.168.0.1/32'], name\n ='foo', tenant_id=1)\n route = {'gateway': '192.168.0.1', 'subnet_id': subnet['id']}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n try:\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(subnet_ids=[1], exclude=['192.168.0.0/24']))\n )\n except Exception as e:\n self.fail(\"This shouldn't have raised: %s\" % e)\n\n\nclass TestQuarkValidateCIDRsFitsIntoSubnets(test_quark_plugin.TestQuarkPlugin):\n\n def test_normal_cidr_and_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv4_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_valid_ipv4_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='192.168.0.0/24')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_multiple_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='192.168.0.0/24'), dict(id=2, cidr=\n '192.168.0.0/16')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_ipv6_cidr_and_multiple_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(['::/128'], [dict(id=1,\n cidr='::/96'), dict(id=2, cidr='::/64')])\n except Exception:\n self.fail('Should not have failed')\n\n def test_normal_cidr_and_invalid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24')])\n\n def test_normal_ipv6_cidr_and_invalid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/64'], [dict(id=1,\n cidr='::/96')])\n\n def test_normal_cidr_and_one_invalid_and_one_valid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['192.168.0.100/32'], [\n dict(id=1, cidr='10.10.10.0/24'), dict(id=1, cidr=\n '192.168.0.0/24')])\n\n def test_normal_ipv6_cidr_and_one_invalid_and_one_valid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(['::/127'], [dict(id=1,\n cidr='::/96'), dict(id=1, cidr='::/128')])\n\n\nclass TestQuarkEnsureDefaultPolicy(test_base.TestBase):\n\n def test_no_cidrs_no_subnets(self):\n cidrs = []\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [])\n self.assertEqual(subnets, [])\n\n def test_no_cidrs_v4(self):\n cidrs = []\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_subnets_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v4(self):\n cidrs = ['192.168.10.20/32', '192.168.10.40/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.20/32', '192.168.10.40/32',\n '192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_cidrs_with_default_cidrs_v4(self):\n cidrs = ['192.168.10.0/32', '192.168.10.255/32']\n subnets = [dict(cidr='192.168.10.1/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.0/32', '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.1/24')])\n\n def test_no_cidrs_v6(self):\n cidrs = []\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_subnets_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v6(self):\n cidrs = ['::10/128', '::20/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::10/128', '::20/128', '::/128',\n '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_cidrs_with_default_cidrs_v6(self):\n cidrs = ['::/128', '::ffff:ffff:ffff:ffff/128']\n subnets = [dict(cidr='::/64')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['::/128', '::ffff:ffff:ffff:ffff/128'])\n self.assertEqual(subnets, [dict(cidr='::/64')])\n\n def test_no_duplicates_in_result_when_called_twice(self):\n cidrs = ['192.168.10.10/32']\n subnets = [dict(cidr='192.168.10.0/24')]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n cidrs2 = ['192.168.10.10/32']\n self.assertIsNone(ippol.ensure_default_policy(cidrs2, subnets))\n self.assertEqual(cidrs, ['192.168.10.10/32', '192.168.10.0/32',\n '192.168.10.255/32'])\n self.assertEqual(subnets, [dict(cidr='192.168.10.0/24')])\n",
"step-5": "# Copyright 2013 Rackspace Hosting Inc.\n# All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may\n# not use this file except in compliance with the License. You may obtain\n# a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT\n# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the\n# License for the specific language governing permissions and limitations\n# under the License.\n\nimport contextlib\n\nimport mock\nfrom neutron.common import exceptions as n_exc_ext\nfrom neutron_lib import exceptions as n_exc\n\nfrom quark import exceptions as q_exc\nfrom quark.plugin_modules import ip_policies as ippol\nfrom quark.tests import test_base\nfrom quark.tests import test_quark_plugin\n\n\nclass TestQuarkGetIpPolicies(test_quark_plugin.TestQuarkPlugin):\n @contextlib.contextmanager\n def _stubs(self, ip_policy):\n db_mod = \"quark.db.api\"\n with mock.patch(\"%s.ip_policy_find\" % db_mod) as ip_policy_find:\n ip_policy_find.return_value = ip_policy\n yield\n\n def test_get_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.get_ip_policy(self.context, 1)\n\n def test_get_ip_policy(self):\n ip_policy = dict(\n id=1,\n tenant_id=1,\n name=\"foo\",\n subnets=[dict(id=1)],\n networks=[dict(id=2)],\n exclude=[dict(cidr=\"0.0.0.0/32\")])\n with self._stubs(ip_policy):\n resp = self.plugin.get_ip_policy(self.context, 1)\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp[\"id\"], 1)\n self.assertEqual(resp[\"name\"], \"foo\")\n self.assertEqual(resp[\"subnet_ids\"], [1])\n self.assertEqual(resp[\"network_ids\"], [2])\n self.assertEqual(resp[\"exclude\"], [\"0.0.0.0/32\"])\n self.assertEqual(resp[\"tenant_id\"], 1)\n\n def test_get_ip_policies(self):\n ip_policy = dict(\n id=1,\n tenant_id=1,\n name=\"foo\",\n subnets=[dict(id=1)],\n networks=[dict(id=2)],\n exclude=[dict(cidr=\"0.0.0.0/32\")])\n with self._stubs([ip_policy]):\n resp = self.plugin.get_ip_policies(self.context)\n self.assertEqual(len(resp), 1)\n resp = resp[0]\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp[\"id\"], 1)\n self.assertEqual(resp[\"subnet_ids\"], [1])\n self.assertEqual(resp[\"network_ids\"], [2])\n self.assertEqual(resp[\"exclude\"], [\"0.0.0.0/32\"])\n self.assertEqual(resp[\"name\"], \"foo\")\n self.assertEqual(resp[\"tenant_id\"], 1)\n\n\nclass TestQuarkCreateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, nets=None):\n db_mod = \"quark.db.api\"\n with contextlib.nested(\n mock.patch(\"%s.subnet_find\" % db_mod),\n mock.patch(\"%s.network_find\" % db_mod),\n mock.patch(\"%s.ip_policy_create\" % db_mod),\n mock.patch(\"%s.route_find\" % db_mod)\n ) as (subnet_find, net_find, ip_policy_create, route_find):\n subnet_find.return_value = subnets if subnets else None\n net_find.return_value = nets if nets else None\n ip_policy_create.return_value = ip_policy\n route_find.return_value = [{\"nexthop\": \"1.2.3.4\"}]\n yield ip_policy_create\n\n def test_create_ip_policy_invalid_body_missing_exclude(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict()))\n\n def test_create_ip_policy_with_both_network_and_subnet_ids(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[1], subnet_ids=[1])))\n\n def test_create_ip_policy_invalid_body_missing_netsubnet(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(exclude=[\"1.1.1.1/24\"])))\n\n def test_create_ip_policy_invalid_subnet(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.SubnetNotFound):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1],\n exclude=[\"1.1.1.1/24\"])))\n\n def test_create_ip_policy_invalid_network(self):\n with self._stubs(None):\n with self.assertRaises(n_exc.NetworkNotFound):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[1],\n exclude=[\"1.1.1.1/24\"])))\n\n def test_create_ip_policy_network_ip_policy_already_exists(self):\n with self._stubs(None, nets=[dict(id=1, ip_policy=dict(id=2),\n subnets=[dict(id=1,\n cidr=\"1.1.1.1/16\")])]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[1],\n exclude=[\"1.1.1.1/24\"])))\n\n def test_create_ip_policy_subnet_ip_policy_already_exists(self):\n with self._stubs(None, subnets=[dict(id=1, ip_policy=dict(id=2),\n cidr=\"1.1.1.1/16\")]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1],\n exclude=[\"1.1.1.1/24\"])))\n\n def test_create_ip_policy_network(self):\n ipp = dict(subnet_id=None, network_id=1,\n exclude=[\"1.1.1.1/24\"])\n with self._stubs(ipp, nets=[dict(id=1, ip_policy=dict(id=2),\n subnets=[dict(id=1,\n cidr=\"1.1.1.1/16\")])]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[ipp[\"network_id\"]],\n exclude=ipp[\"exclude\"])))\n\n def test_create_ip_policy_subnet(self):\n ipp = dict(subnet_id=1, network_id=None,\n exclude=[\"1.1.1.1/24\"])\n with self._stubs(ipp, subnets=[dict(id=1, ip_policy=dict(id=2),\n cidr=\"1.1.1.1/16\")]):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[ipp[\"subnet_id\"]],\n exclude=ipp[\"exclude\"])))\n\n def test_create_ip_policy_with_cidr_that_does_not_fit_into_subnet(self):\n ipp = dict(\n subnets=[dict(id=1, version=4, cidr=\"192.168.1.1/24\")],\n networks=[],\n id=1,\n tenant_id=1,\n exclude=[\"10.10.10.100/32\"],\n name=\"foo\")\n with self._stubs(ipp,\n subnets=[dict(id=1, ip_policy=None,\n version=ipp[\"subnets\"][0][\"version\"],\n cidr=ipp[\"subnets\"][0][\"cidr\"])]):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1],\n exclude=ipp[\"exclude\"])))\n\n def test_create_ip_policy_with_ipv6_subnet_cidr(self):\n ipp = dict(\n subnets=[dict(id=1, version=6, cidr='::/64')],\n networks=[],\n id=1,\n tenant_id=1,\n exclude=[dict(cidr=\"::/128\")],\n name=\"foo\")\n with self._stubs(ipp,\n subnets=[dict(id=1, ip_policy=None,\n version=ipp[\"subnets\"][0][\"version\"],\n cidr=ipp[\"subnets\"][0][\"cidr\"])]):\n exclude = [ippc[\"cidr\"] for ippc in ipp[\"exclude\"]]\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1], exclude=exclude)))\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp[\"subnet_ids\"], [1])\n self.assertEqual(resp[\"network_ids\"], [])\n # NOTE(jmeridth): below is mocked that way, so it won't get\n # additional default policies in exclude\n # ippol.ensure_default_policy is tested below in this file\n self.assertEqual(resp[\"exclude\"], [\"::/128\"])\n self.assertEqual(resp[\"name\"], \"foo\")\n self.assertEqual(resp[\"tenant_id\"], 1)\n\n def test_create_ip_policy(self):\n ipp = dict(\n subnets=[dict(id=1, cidr='0.0.0.0/16')],\n networks=[],\n id=1,\n tenant_id=1,\n exclude=[dict(cidr=\"0.0.0.0/24\")],\n name=\"foo\")\n with self._stubs(ipp, subnets=[dict(\n id=1, ip_policy=None, cidr=ipp[\"subnets\"][0][\"cidr\"])]):\n exclude = [ippc[\"cidr\"] for ippc in ipp[\"exclude\"]]\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[1], exclude=exclude)))\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp[\"subnet_ids\"], [1])\n self.assertEqual(resp[\"network_ids\"], [])\n # NOTE(jmeridth): below is mocked that way, so it won't get\n # additional default policies in exclude\n # ippol.ensure_default_policy is tested below in this file\n self.assertEqual(resp[\"exclude\"], [\"0.0.0.0/24\"])\n self.assertEqual(resp[\"name\"], \"foo\")\n self.assertEqual(resp[\"tenant_id\"], 1)\n\n def test_create_ip_policy_only_called_once_with_multiple_networks(self):\n ipp = dict(\n subnets=[],\n networks=[dict(id=1, subnets=[dict(id=1,\n ip_policy=None, cidr='0.0.0.0/24')]),\n dict(id=2, subnets=[dict(id=2,\n ip_policy=None, cidr='0.0.0.0/24')])],\n id=1,\n tenant_id=1,\n exclude=[dict(cidr=\"0.0.0.1/32\")],\n name=\"foo\")\n with self._stubs(ipp, nets=ipp[\"networks\"]) as (ip_policy_create):\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(network_ids=[1, 2], exclude=[\"0.0.0.1/32\"])))\n exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.0.255/32']\n ip_policy_create.assert_called_once_with(\n self.context, exclude=exclude,\n networks=[{'subnets':\n [{'cidr': '0.0.0.0/24', 'ip_policy': None,\n 'id': 1}], 'id': 1},\n {'subnets':\n [{'cidr': '0.0.0.0/24', 'ip_policy': None,\n 'id': 2}], 'id': 2}])\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp[\"subnet_ids\"], [])\n self.assertEqual(resp[\"network_ids\"], [1, 2])\n # NOTE(jmeridth): below is mocked that way, so it won't get\n # additional default policies in exclude\n # ippol.ensure_default_policy is tested below in this file\n self.assertEqual(resp[\"exclude\"], [\"0.0.0.1/32\"])\n self.assertEqual(resp[\"name\"], \"foo\")\n self.assertEqual(resp[\"tenant_id\"], 1)\n\n def test_create_ip_policy_only_called_once_with_multiple_subnets(self):\n ipp = dict(\n subnets=[dict(id=3, cidr='0.0.0.0/16'),\n dict(id=4, cidr='0.0.0.0/16')],\n networks=[],\n id=1,\n tenant_id=1,\n exclude=[dict(cidr=\"0.0.0.1/32\")],\n name=\"foo\")\n with self._stubs(ipp, subnets=ipp[\"subnets\"]) as (ip_policy_create):\n resp = self.plugin.create_ip_policy(self.context, dict(\n ip_policy=dict(subnet_ids=[3, 4], exclude=[\"0.0.0.1/32\"])))\n exclude = ['0.0.0.1/32', '0.0.0.0/32', '0.0.255.255/32']\n ip_policy_create.assert_called_once_with(\n self.context, exclude=exclude,\n subnets=[{'cidr': '0.0.0.0/16', 'id': 3},\n {'cidr': '0.0.0.0/16', 'id': 4}])\n self.assertEqual(len(resp.keys()), 6)\n self.assertEqual(resp[\"subnet_ids\"], [3, 4])\n self.assertEqual(resp[\"network_ids\"], [])\n # NOTE(jmeridth): below is mocked that way, so it won't get\n # additional default policies in exclude\n # ippol.ensure_default_policy is tested below in this file\n self.assertEqual(resp[\"exclude\"], [\"0.0.0.1/32\"])\n self.assertEqual(resp[\"name\"], \"foo\")\n self.assertEqual(resp[\"tenant_id\"], 1)\n\n\nclass TestQuarkUpdateIpPolicies(test_quark_plugin.TestQuarkPlugin):\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, networks=None):\n if not subnets:\n subnets = []\n if not networks:\n networks = []\n db_mod = \"quark.db.api\"\n with contextlib.nested(\n mock.patch(\"%s.ip_policy_find\" % db_mod),\n mock.patch(\"%s.subnet_find\" % db_mod),\n mock.patch(\"%s.network_find\" % db_mod),\n mock.patch(\"%s.ip_policy_update\" % db_mod),\n ) as (ip_policy_find, subnet_find, network_find, ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n network_find.return_value = networks\n yield ip_policy_update\n\n def test_update_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.update_ip_policy(self.context, 1,\n dict(ip_policy=None))\n\n def test_update_ip_policy_with_both_network_and_subnet_ids(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.BadRequest):\n self.plugin.update_ip_policy(self.context, 1, dict(\n ip_policy=dict(network_ids=[1], subnet_ids=[1])))\n\n def test_update_ip_policy_subnets_not_found(self):\n ipp = dict(id=1, subnets=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.SubnetNotFound):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets_already_exists(self):\n ipp = dict(id=1, subnets=[dict()])\n with self._stubs(\n ipp, subnets=[dict(id=1, ip_policy=dict(id=1))]\n ):\n with self.assertRaises(q_exc.IPPolicyAlreadyExists):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(subnet_ids=[100])))\n\n def test_update_ip_policy_subnets(self):\n ipp = dict(id=1, subnets=[dict()],\n exclude=[\"0.0.0.0/24\"],\n name=\"foo\", tenant_id=1)\n with self._stubs(\n ipp, subnets=[dict(id=1, ip_policy=None)]\n ) as (ip_policy_update):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(subnet_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_subnets_empty_exclude(self):\n ipp = dict(id=1, subnets=[dict()],\n exclude=[\"0.0.0.40/32\"],\n name=\"foo\", tenant_id=1)\n with self._stubs(\n ipp, subnets=[dict(id=1, cidr=\"0.0.0.0/16\", ip_policy=None)]\n ) as (ip_policy_update):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(subnet_ids=[100], exclude=[])))\n ip_policy_update.assert_called_once_with(\n self.context, ipp, subnet_ids=[100], exclude=[\n \"0.0.0.0/32\", \"0.0.255.255/32\"])\n\n def test_update_ip_policy_subnets_empty_exclude_without_subnet_ids(self):\n ipp = dict(id=1, subnets=[dict(cidr=\"0.0.0.0/16\")],\n exclude=[\"0.0.0.40/32\"],\n name=\"foo\", tenant_id=1)\n with self._stubs(ipp) as (ip_policy_update):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(exclude=[])))\n ip_policy_update.assert_called_once_with(\n self.context, ipp, exclude=[\"0.0.0.0/32\", \"0.0.255.255/32\"])\n\n def test_update_ip_policy_networks_not_found(self):\n ipp = dict(id=1, networks=[])\n with self._stubs(ipp):\n with self.assertRaises(n_exc.NetworkNotFound):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(network_ids=[100])))\n\n def test_update_ip_policy_networks(self):\n ipp = dict(id=1, networks=[dict()],\n exclude=[\"0.0.0.0/24\"],\n name=\"foo\", tenant_id=1)\n with self._stubs(\n ipp, networks=[dict(id=1, ip_policy=None)]\n ) as (ip_policy_update):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(network_ids=[100])))\n self.assertEqual(ip_policy_update.called, 1)\n\n def test_update_ip_policy_exclude_v4(self):\n subnets = [dict(id=100, cidr=\"0.0.0.0/16\")]\n ipp = dict(id=1, subnets=subnets,\n exclude=[\"0.0.0.0/24\"],\n name=\"foo\", tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as (ip_policy_update):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(subnet_ids=[100], exclude=[\"0.0.0.1/32\"])))\n ip_policy_update.assert_called_once_with(\n self.context,\n ipp,\n subnet_ids=[100],\n exclude=[\"0.0.0.1/32\", \"0.0.0.0/32\", \"0.0.255.255/32\"])\n\n def test_update_ip_policy_exclude_v6(self):\n subnets = [dict(id=100, cidr=\"::/64\")]\n ipp = dict(id=1, subnets=subnets,\n exclude=[\"::/128\"],\n name=\"foo\", tenant_id=1)\n with self._stubs(ipp, subnets=subnets) as (ip_policy_update):\n self.plugin.update_ip_policy(\n self.context,\n 1,\n dict(ip_policy=dict(subnet_ids=[100], exclude=[\"::1/128\"])))\n ip_policy_update.assert_called_once_with(\n self.context,\n ipp,\n subnet_ids=[100],\n exclude=[\"::1/128\", \"::/128\", \"::ffff:ffff:ffff:ffff/128\"])\n\n\nclass TestQuarkDeleteIpPolicies(test_quark_plugin.TestQuarkPlugin):\n @contextlib.contextmanager\n def _stubs(self, ip_policy):\n db_mod = \"quark.db.api\"\n with contextlib.nested(\n mock.patch(\"%s.ip_policy_find\" % db_mod),\n mock.patch(\"%s.ip_policy_delete\" % db_mod),\n ) as (ip_policy_find, ip_policy_delete):\n ip_policy_find.return_value = ip_policy\n yield ip_policy_find, ip_policy_delete\n\n def test_delete_ip_policy_not_found(self):\n with self._stubs(None):\n with self.assertRaises(q_exc.IPPolicyNotFound):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy_in_use(self):\n with self._stubs(dict(networks=True)):\n with self.assertRaises(q_exc.IPPolicyInUse):\n self.plugin.delete_ip_policy(self.context, 1)\n\n def test_delete_ip_policy(self):\n ip_policy = dict(\n id=1,\n networks=[],\n subnets=[])\n with self._stubs(ip_policy) as (ip_policy_find, ip_policy_delete):\n self.plugin.delete_ip_policy(self.context, 1)\n self.assertEqual(ip_policy_find.call_count, 1)\n self.assertEqual(ip_policy_delete.call_count, 1)\n\n\nclass TestQuarkUpdatePolicySubnetWithRoutes(test_quark_plugin.TestQuarkPlugin):\n @contextlib.contextmanager\n def _stubs(self, ip_policy, subnets=None, routes=None):\n subnets = subnets or []\n db_mod = \"quark.db.api\"\n with contextlib.nested(\n mock.patch(\"%s.ip_policy_find\" % db_mod),\n mock.patch(\"%s.subnet_find\" % db_mod),\n mock.patch(\"%s.route_find\" % db_mod),\n mock.patch(\"%s.ip_policy_update\" % db_mod),\n ) as (ip_policy_find, subnet_find, route_find, ip_policy_update):\n ip_policy_find.return_value = ip_policy\n subnet_find.return_value = subnets\n route_find.return_value = routes\n yield ip_policy_update\n\n def test_update_ip_policy_has_route_conflict_raises(self):\n subnet = dict(id=1, cidr=\"192.168.0.0/24\")\n ipp = dict(id=1, subnets=[subnet], exclude=[\"192.168.0.1/32\"],\n name=\"foo\", tenant_id=1)\n route = {\"gateway\": \"192.168.0.1\", \"subnet_id\": subnet[\"id\"]}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n with self.assertRaises(\n n_exc_ext.GatewayConflictWithAllocationPools):\n self.plugin.update_ip_policy(\n self.context, 1,\n dict(ip_policy=dict(subnet_ids=[1], exclude=[])))\n\n def test_update_ip_policy_no_route_conflict(self):\n subnet = dict(id=1, cidr=\"192.168.0.0/24\")\n ipp = dict(id=1, subnets=[subnet], exclude=[\"192.168.0.1/32\"],\n name=\"foo\", tenant_id=1)\n route = {\"gateway\": \"192.168.0.1\", \"subnet_id\": subnet[\"id\"]}\n with self._stubs(ipp, subnets=[subnet], routes=[route]):\n try:\n self.plugin.update_ip_policy(\n self.context, 1,\n dict(ip_policy=dict(subnet_ids=[1],\n exclude=[\"192.168.0.0/24\"])))\n except Exception as e:\n self.fail(\"This shouldn't have raised: %s\" % e)\n\n\nclass TestQuarkValidateCIDRsFitsIntoSubnets(test_quark_plugin.TestQuarkPlugin):\n def test_normal_cidr_and_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(\n [\"192.168.0.100/32\"],\n [dict(id=1, cidr=\"192.168.0.0/24\")])\n except Exception:\n self.fail(\"Should not have failed\")\n\n def test_normal_ipv4_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(\n [\"192.168.0.100/32\"], [dict(id=1, cidr=\"::/96\")])\n except Exception:\n self.fail(\"Should not have failed\")\n\n def test_normal_ipv6_cidr_and_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(\n [\"::/128\"], [dict(id=1, cidr=\"::/96\")])\n except Exception:\n self.fail(\"Should not have failed\")\n\n def test_normal_ipv6_cidr_and_valid_ipv4_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(\n [\"::/128\"], [dict(id=1, cidr=\"192.168.0.0/24\")])\n except Exception:\n self.fail(\"Should not have failed\")\n\n def test_normal_cidr_and_multiple_valid_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(\n [\"192.168.0.100/32\"],\n [dict(id=1, cidr=\"192.168.0.0/24\"),\n dict(id=2, cidr=\"192.168.0.0/16\")])\n except Exception:\n self.fail(\"Should not have failed\")\n\n def test_normal_ipv6_cidr_and_multiple_valid_ipv6_subnet(self):\n try:\n ippol._validate_cidrs_fit_into_subnets(\n [\"::/128\"],\n [dict(id=1, cidr=\"::/96\"),\n dict(id=2, cidr=\"::/64\")])\n except Exception:\n self.fail(\"Should not have failed\")\n\n def test_normal_cidr_and_invalid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(\n [\"192.168.0.100/32\"],\n [dict(id=1, cidr=\"10.10.10.0/24\")])\n\n def test_normal_ipv6_cidr_and_invalid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(\n [\"::/64\"], [dict(id=1, cidr=\"::/96\")])\n\n def test_normal_cidr_and_one_invalid_and_one_valid_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(\n [\"192.168.0.100/32\"],\n [dict(id=1, cidr=\"10.10.10.0/24\"),\n dict(id=1, cidr=\"192.168.0.0/24\")])\n\n def test_normal_ipv6_cidr_and_one_invalid_and_one_valid_ipv6_subnet(self):\n with self.assertRaises(n_exc.BadRequest):\n ippol._validate_cidrs_fit_into_subnets(\n [\"::/127\"],\n [dict(id=1, cidr=\"::/96\"),\n dict(id=1, cidr=\"::/128\")])\n\n\nclass TestQuarkEnsureDefaultPolicy(test_base.TestBase):\n def test_no_cidrs_no_subnets(self):\n cidrs = []\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [])\n self.assertEqual(subnets, [])\n\n def test_no_cidrs_v4(self):\n cidrs = []\n subnets = [dict(cidr=\"192.168.10.1/24\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"192.168.10.0/32\", \"192.168.10.255/32\"])\n self.assertEqual(subnets, [dict(cidr=\"192.168.10.1/24\")])\n\n def test_no_subnets_v4(self):\n cidrs = [\"192.168.10.0/32\", \"192.168.10.255/32\"]\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"192.168.10.0/32\", \"192.168.10.255/32\"])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v4(self):\n cidrs = [\"192.168.10.20/32\", \"192.168.10.40/32\"]\n subnets = [dict(cidr=\"192.168.10.1/24\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"192.168.10.20/32\", \"192.168.10.40/32\",\n \"192.168.10.0/32\", \"192.168.10.255/32\"])\n self.assertEqual(subnets, [dict(cidr=\"192.168.10.1/24\")])\n\n def test_cidrs_with_default_cidrs_v4(self):\n cidrs = [\"192.168.10.0/32\", \"192.168.10.255/32\"]\n subnets = [dict(cidr=\"192.168.10.1/24\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"192.168.10.0/32\", \"192.168.10.255/32\"])\n self.assertEqual(subnets, [dict(cidr=\"192.168.10.1/24\")])\n\n def test_no_cidrs_v6(self):\n cidrs = []\n subnets = [dict(cidr=\"::/64\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"::/128\", \"::ffff:ffff:ffff:ffff/128\"])\n self.assertEqual(subnets, [dict(cidr=\"::/64\")])\n\n def test_no_subnets_v6(self):\n cidrs = [\"::/128\", \"::ffff:ffff:ffff:ffff/128\"]\n subnets = []\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"::/128\", \"::ffff:ffff:ffff:ffff/128\"])\n self.assertEqual(subnets, [])\n\n def test_cidrs_without_default_cidrs_v6(self):\n cidrs = [\"::10/128\", \"::20/128\"]\n subnets = [dict(cidr=\"::/64\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"::10/128\", \"::20/128\",\n \"::/128\", \"::ffff:ffff:ffff:ffff/128\"])\n self.assertEqual(subnets, [dict(cidr=\"::/64\")])\n\n def test_cidrs_with_default_cidrs_v6(self):\n cidrs = [\"::/128\", \"::ffff:ffff:ffff:ffff/128\"]\n subnets = [dict(cidr=\"::/64\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"::/128\", \"::ffff:ffff:ffff:ffff/128\"])\n self.assertEqual(subnets, [dict(cidr=\"::/64\")])\n\n def test_no_duplicates_in_result_when_called_twice(self):\n cidrs = [\"192.168.10.10/32\"]\n subnets = [dict(cidr=\"192.168.10.0/24\")]\n self.assertIsNone(ippol.ensure_default_policy(cidrs, subnets))\n self.assertEqual(cidrs, [\"192.168.10.10/32\", \"192.168.10.0/32\",\n \"192.168.10.255/32\"])\n cidrs2 = [\"192.168.10.10/32\"]\n self.assertIsNone(ippol.ensure_default_policy(cidrs2, subnets))\n self.assertEqual(cidrs, [\"192.168.10.10/32\", \"192.168.10.0/32\",\n \"192.168.10.255/32\"])\n self.assertEqual(subnets, [dict(cidr=\"192.168.10.0/24\")])\n",
"step-ids": [
37,
43,
48,
57,
67
]
}
|
[
37,
43,
48,
57,
67
] |
<|reserved_special_token_0|>
class Department(SQLAlchemyObjectType):
class Meta:
model = DepartmentModel
interfaces = relay.Node,
class Query(graphene.ObjectType):
node = relay.Node.Field()
all_employees = SQLAlchemyConnectionField(Department)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Department(SQLAlchemyObjectType):
class Meta:
model = DepartmentModel
interfaces = relay.Node,
class Query(graphene.ObjectType):
node = relay.Node.Field()
all_employees = SQLAlchemyConnectionField(Department)
def create_app(config_name):
app = FlaskAPI(__name__, instance_relative_config=True)
bcrypt = Bcrypt(app)
schema = graphene.Schema(query=Query)
app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql',
schema=schema, graphiql=True))
app.config.from_object(app_config[config_name])
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db.init_app(app)
@app.route('/api/areas/create', methods=['POST'])
def create_areas():
name = request.data.get('name', '')
geodata = request.data.get('geodata', '')
center_lat = request.data.get('center_lat')
center_lng = request.data.get('center_lng')
zoom = request.data.get('zoom')
area = Area(name=name, geodata=geodata, center_lat=center_lat,
center_lng=center_lng, zoom=zoom)
area.save()
response = jsonify({'id': area.id, 'name': area.name, 'geodata':
area.geodata, 'center_lat': area.center_lat, 'center_lng': area
.center_lng, 'zoom': area.zoom, 'date_created': area.
date_created, 'date_modified': area.date_modified})
return make_response(response), 201
@app.route('/api/areas/delete', methods=['POST'])
def delete_areas():
id = request.data.get('id', 0)
area = Area.query.filter_by(id=id).first()
if area is not None:
area.delete()
return make_response(jsonify({'id': id})), 200
@app.route('/api/sightingsperhour', methods=['GET'])
def get_sightingsperhour():
sightings = SightingsPerHourPerCountry.query.all()
results = []
for sighting in sightings:
results.append({'country': sighting.country, 'hour': sighting.
hour, 'count': sighting.count})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sightingsnew', methods=['POST'])
def sightingsnew():
sightings = db.session.query(SightingsBase.site_id, SightingsBase.
country, func.count(SightingsBase.roundedtoday)).filter(
SightingsBase.site_id.in_(request.data['selectedRow'])).filter(
SightingsBase.roundedtoday.between(request.data['selectedDates'
][0], request.data['selectedDates'][1])).group_by(SightingsBase
.site_id, SightingsBase.country).order_by(SightingsBase.site_id,
func.count(SightingsBase.roundedtoday).desc())
results = []
for sighting in sightings.all():
results.append({'country': sighting.country, 'site_id':
sighting.site_id, 'count': sighting[2]})
return make_response(jsonify({'list': results})), 200
@app.route('/api/widesightingsnew', methods=['POST', 'GET'])
def widesightingsnew():
sightings = db.session.query(WideSighting.site_id, WideSighting.
gender, func.count(WideSighting.gender)).filter(WideSighting.
site_id.in_([138, 134])).group_by(WideSighting.site_id,
WideSighting.gender)
results = []
for sighting in sightings.all():
results.append({'site_id': sighting.site_id, 'gender': sighting
.gender, 'count': sighting[2]})
return make_response(jsonify({'list': results})), 200
@app.route('/api/widesightings', methods=['GET'])
def widesightings():
sightings = WideSighting.get_all()
results = []
for sighting in sightings:
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/sites', methods=['GET'])
def get_sites():
sites = Site.get_all()
results = []
for site in sites:
results.append(site.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/dates', methods=['GET'])
def get_dates():
dates = Date.get_all()
results = []
for date in dates:
results.append(date.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/areas', methods=['GET'])
def get_areas():
areas = Area.get_all()
allSmallCells = SmallCell.get_all()
results = []
for area in areas:
smallcellInArea = []
for smallcell in allSmallCells:
smallcellInArea.append(smallcell.serialise())
obj = {'id': area.id, 'name': area.name, 'date_created': area.
date_created, 'date_modified': area.date_modified,
'center_lat': area.center_lat, 'center_lng': area.
center_lng, 'zoom': area.zoom, 'geodata': area.geodata,
'smallcells': smallcellInArea}
results.append(obj)
return make_response(jsonify({'list': results})), 200
@app.route('/api/smallcells', methods=['GET'])
def get_smallcells():
allSmallCells = SmallCell.query.order_by(SmallCell.id).all()
results = []
for smallcell in allSmallCells:
results.append(smallcell.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/smallcells/update', methods=['POST'])
def update_smallcell():
smallcell_id = request.data.get('id', '')
site_id = request.data.get('site_id', '')
smallcell = SmallCell.query.filter_by(id=smallcell_id).first()
smallcell.site_id = site_id
smallcell.save()
return make_response(jsonify({'smallcell_id': smallcell.id,
'site_id': smallcell.site_id})), 200
@app.route('/api/sighting/byarea/<areaid>', methods=['GET'])
def get_sighting(areaid):
import string
area = Area.query.filter_by(id=areaid).first()
if area is None:
return make_response(jsonify({'list': []})), 200
sites = []
for site in Site.get_all():
if area.contains(site):
sites.append(str(site.id))
def generate_random_data(num_rows):
import random
latitude = 51.51451110408478
longitude = -0.12620388576521444
result = []
for _ in range(num_rows):
dec_lat = random.random() / 10
dec_lon = random.random() / 10
result.append({'lat': latitude + dec_lat, 'lng': longitude +
dec_lon})
return result
results = []
if len(sites) > 0:
for row in db.session.execute(
'select * from get_gender_crossfilter(ARRAY[' + ','.join(
sites) + '])'):
results.append({'geos': generate_random_data(5), 'gender':
row['__gender'], 'age_range': row['__age_range'],
'timestamp': row['__sighting_date'], 'count': row[
'__count']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting/getgender/', methods=['POST'])
def get_gender():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute('select * from get_gender(ARRAY[' +
site_ids + '],' + "'" + from_sighting_date + "'" + ',' + "'" +
to_sighting_date + "'" + ')'):
results.append({'site_id': row['__site_id'], 'date_month': row[
'__date_month'], 'gender': row['__gender'], 'age_range':
row['__age_range'], 'perc_visits': row['__perc_visits'],
'scaled_visits': row['__scaled_visits']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting/getgendertotals/', methods=['POST'])
def get_gender_age_totals():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute(
'select * from get_gender_age_totals(ARRAY[' + site_ids + '],' +
"'" + from_sighting_date + "'" + ',' + "'" + to_sighting_date +
"'" + ')'):
results.append({'site_id': row['__site_id'], 'gender': row[
'__gender'], 'age_range': row['__age_range'], '__visits':
row['__visits']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting', methods=['GET'])
def get_sightings():
results = []
for sighting in LTESighting.get_all():
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/sitescomparison', methods=['POST'])
def get_sitescomparison():
sightings = LTESighting.query.filter(LTESighting.smallcell.has(
SmallCell.site_id.in_(request.data['selectedRow']))).filter(
LTESighting.timestamp.between(request.data['selectedDates'][0],
request.data['selectedDates'][1]))
return make_response(jsonify({'list': [sighting.serialise() for
sighting in sightings]})), 200
@app.route('/api/sighting/bysite', methods=['GET'])
def get_sightings_by_site():
site_ids = request.args.getlist('site_id')
results = []
for sighting in LTESighting.query:
if str(sighting.smallcell.site_id) in site_ids:
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/origindestination/all', methods=['GET'])
def get_all():
journeys = Journey.query.all()
thing = {}
for journey in journeys:
if journey.origin_id not in thing:
thing[journey.origin_id] = {}
if journey.destination_id not in thing[journey.origin_id
] and journey.destination_id != journey.origin_id:
thing[journey.origin_id][journey.destination_id
] = journey.data['total']
return make_response(jsonify(thing)), 200
@app.route('/api/origindestination/<origin_id>', methods=['GET'])
def get_od(origin_id):
journeys = Journey.query.all()
_j = []
for journey in journeys:
_j.append({'origin_id': journey.origin_id, 'destination_id':
journey.destination_id, 'total': journey.data['total']})
return make_response(jsonify({'list': _j})), 200
@app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>',
methods=['GET'])
def purchase(home_district_name, type_visitor):
days_sql = db.session.query(PurchDistrict.start_dow, func.count(
PurchDistrict.start_dow)).group_by(PurchDistrict.start_dow).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).order_by(func.
count(PurchDistrict.start_dow).desc()).all()
gender_sql = db.session.query(PurchDistrict.gender, func.count(
PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, func.count(PurchDistrict.gender)).group_by(
PurchDistrict.gender, PurchDistrict.age).filter(PurchDistrict.
gender.isnot(None)).filter(PurchDistrict.age.isnot(None)).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict
.gender)).group_by(PurchDistrict.gender, PurchDistrict.age,
PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)
).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.
type_visitor.in_([type_visitor])).all()
days_total = sum(i[1] for i in days_sql)
gender_total = sum(i[1] for i in gender_sql)
gender_age_total = sum(i[2] for i in gender_age_sql)
days_results = []
for result in days_sql:
days_results.append({'start_dow': result.start_dow, 'count':
result[1], 'percent': float(result[1]) / float(days_total),
'total': days_total})
gender_results = []
for result in gender_sql:
gender_results.append({'gender': result.gender, 'count': result
[1], 'percent': float(result[1]) / float(gender_total)})
gender_age_results = []
for result in gender_age_sql:
gender_age_results.append({'gender': result.gender, 'age':
result.age, 'count': result[2], 'percent': float(result[2]) /
float(gender_age_total)})
return make_response(jsonify({'days': days_results, 'gender':
gender_results, 'gender_age': gender_age_results})), 200
@app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=[
'GET'])
def purchase_rent(type_visitor):
gender_sql = db.session.query(PurchDistrict.gender, func.count(
PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict
.gender)).group_by(PurchDistrict.gender, PurchDistrict.age,
PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)
).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.
type_visitor.in_([type_visitor])).all()
gender_total = sum(i[1] for i in gender_sql)
gender_results = []
for result in gender_sql:
gender_results.append({'gender': result.gender, 'count': result
[1], 'percent': float(result[1]) / float(gender_total)})
gender_age_rent_results = []
for result in gender_age_rent_sql:
gender_age_rent_results.append({'gender': result.gender, 'age':
result.age, 'rent': result.rent, 'count': result[3]})
return make_response(jsonify({'gender': gender_results,
'gender_age_rent': gender_age_rent_results})), 200
@app.route('/api/ng_event/districts', methods=['GET'])
def districts():
home_results = []
for result in db.session.query(ZoneDistrict.home_district_code,
ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)
).group_by(ZoneDistrict.home_district_code, ZoneDistrict.
home_district_name).all():
home_results.append({'district_code': result.home_district_code,
'district_name': result.home_district_name, 'visitors':
result[2]})
work_results = []
for result in db.session.query(ZoneDistrict.work_district_code,
ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)
).group_by(ZoneDistrict.work_district_code, ZoneDistrict.
work_district_name).all():
work_results.append({'district_code': result.work_district_code,
'district_name': result.work_district_name, 'visitors':
result[2]})
return make_response(jsonify({'work': {'list': work_results},
'home': {'list': home_results}})), 200
@app.route('/api/ng_event/attractiontotals', methods=['GET'])
def attractiontotals():
results = []
for result in db.session.query(AttractionTotal.zone_visitors,
AttractionTotal.num_visitors).all():
results.append({'zone_visitors': result.zone_visitors,
'num_visitors': result.num_visitors})
return make_response(jsonify({'totals': {'list': results}})), 200
@app.route('/api/ng_event/profiles', methods=['GET'])
def profiles():
results = []
for result in db.session.query(Profile.country, Profile.nationality,
Profile.name_province, Profile.gender, Profile.age, Profile.
rent, Profile.type_visitor, Profile.date, Profile.day, Profile.
period, Profile.name_tur_zone).limit(10000):
district = ''
if result.name_tur_zone == 'Zone 1':
district = 'Chamartin'
if result.name_tur_zone == 'Zone 2':
district = 'Chamberi'
if result.name_tur_zone == 'Zone 3':
district = 'Salamanca'
day = ''
if result.day == 'Monday':
day = 'Mon'
if result.day == 'Tuesday':
day = 'Tue'
if result.day == 'Wednesday':
day = 'Wed'
if result.day == 'Thursday':
day = 'Thu'
if result.day == 'Friday':
day = 'Fri'
if result.day == 'Saturday':
day = 'Sat'
if result.day == 'Sunday':
day = 'Sun'
results.append({'country': result.country, 'nationality':
result.nationality, 'name_province': district, 'gender':
result.gender, 'age': result.age, 'rent': result.rent,
'type_visitor': result.type_visitor, 'date': result.date,
'day': day, 'period': result.period, 'zone': result.
name_tur_zone})
return make_response(jsonify(results)), 200
@app.route('/api/ng_event/dowfreq', methods=['GET'])
def dowfreq():
results = []
for result in db.session.query(DOWFrequency.type_visitor,
DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count
).all():
results.append({'type_visitor': result.type_visitor,
'start_dow': result.start_dow, 'start_hour': result.
start_hour, 'count': result.count})
return make_response(jsonify(results)), 200
return app
<|reserved_special_token_1|>
<|reserved_special_token_0|>
db = SQLAlchemy()
<|reserved_special_token_0|>
class Department(SQLAlchemyObjectType):
class Meta:
model = DepartmentModel
interfaces = relay.Node,
class Query(graphene.ObjectType):
node = relay.Node.Field()
all_employees = SQLAlchemyConnectionField(Department)
def create_app(config_name):
app = FlaskAPI(__name__, instance_relative_config=True)
bcrypt = Bcrypt(app)
schema = graphene.Schema(query=Query)
app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql',
schema=schema, graphiql=True))
app.config.from_object(app_config[config_name])
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db.init_app(app)
@app.route('/api/areas/create', methods=['POST'])
def create_areas():
name = request.data.get('name', '')
geodata = request.data.get('geodata', '')
center_lat = request.data.get('center_lat')
center_lng = request.data.get('center_lng')
zoom = request.data.get('zoom')
area = Area(name=name, geodata=geodata, center_lat=center_lat,
center_lng=center_lng, zoom=zoom)
area.save()
response = jsonify({'id': area.id, 'name': area.name, 'geodata':
area.geodata, 'center_lat': area.center_lat, 'center_lng': area
.center_lng, 'zoom': area.zoom, 'date_created': area.
date_created, 'date_modified': area.date_modified})
return make_response(response), 201
@app.route('/api/areas/delete', methods=['POST'])
def delete_areas():
id = request.data.get('id', 0)
area = Area.query.filter_by(id=id).first()
if area is not None:
area.delete()
return make_response(jsonify({'id': id})), 200
@app.route('/api/sightingsperhour', methods=['GET'])
def get_sightingsperhour():
sightings = SightingsPerHourPerCountry.query.all()
results = []
for sighting in sightings:
results.append({'country': sighting.country, 'hour': sighting.
hour, 'count': sighting.count})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sightingsnew', methods=['POST'])
def sightingsnew():
sightings = db.session.query(SightingsBase.site_id, SightingsBase.
country, func.count(SightingsBase.roundedtoday)).filter(
SightingsBase.site_id.in_(request.data['selectedRow'])).filter(
SightingsBase.roundedtoday.between(request.data['selectedDates'
][0], request.data['selectedDates'][1])).group_by(SightingsBase
.site_id, SightingsBase.country).order_by(SightingsBase.site_id,
func.count(SightingsBase.roundedtoday).desc())
results = []
for sighting in sightings.all():
results.append({'country': sighting.country, 'site_id':
sighting.site_id, 'count': sighting[2]})
return make_response(jsonify({'list': results})), 200
@app.route('/api/widesightingsnew', methods=['POST', 'GET'])
def widesightingsnew():
sightings = db.session.query(WideSighting.site_id, WideSighting.
gender, func.count(WideSighting.gender)).filter(WideSighting.
site_id.in_([138, 134])).group_by(WideSighting.site_id,
WideSighting.gender)
results = []
for sighting in sightings.all():
results.append({'site_id': sighting.site_id, 'gender': sighting
.gender, 'count': sighting[2]})
return make_response(jsonify({'list': results})), 200
@app.route('/api/widesightings', methods=['GET'])
def widesightings():
sightings = WideSighting.get_all()
results = []
for sighting in sightings:
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/sites', methods=['GET'])
def get_sites():
sites = Site.get_all()
results = []
for site in sites:
results.append(site.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/dates', methods=['GET'])
def get_dates():
dates = Date.get_all()
results = []
for date in dates:
results.append(date.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/areas', methods=['GET'])
def get_areas():
areas = Area.get_all()
allSmallCells = SmallCell.get_all()
results = []
for area in areas:
smallcellInArea = []
for smallcell in allSmallCells:
smallcellInArea.append(smallcell.serialise())
obj = {'id': area.id, 'name': area.name, 'date_created': area.
date_created, 'date_modified': area.date_modified,
'center_lat': area.center_lat, 'center_lng': area.
center_lng, 'zoom': area.zoom, 'geodata': area.geodata,
'smallcells': smallcellInArea}
results.append(obj)
return make_response(jsonify({'list': results})), 200
@app.route('/api/smallcells', methods=['GET'])
def get_smallcells():
allSmallCells = SmallCell.query.order_by(SmallCell.id).all()
results = []
for smallcell in allSmallCells:
results.append(smallcell.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/smallcells/update', methods=['POST'])
def update_smallcell():
smallcell_id = request.data.get('id', '')
site_id = request.data.get('site_id', '')
smallcell = SmallCell.query.filter_by(id=smallcell_id).first()
smallcell.site_id = site_id
smallcell.save()
return make_response(jsonify({'smallcell_id': smallcell.id,
'site_id': smallcell.site_id})), 200
@app.route('/api/sighting/byarea/<areaid>', methods=['GET'])
def get_sighting(areaid):
import string
area = Area.query.filter_by(id=areaid).first()
if area is None:
return make_response(jsonify({'list': []})), 200
sites = []
for site in Site.get_all():
if area.contains(site):
sites.append(str(site.id))
def generate_random_data(num_rows):
import random
latitude = 51.51451110408478
longitude = -0.12620388576521444
result = []
for _ in range(num_rows):
dec_lat = random.random() / 10
dec_lon = random.random() / 10
result.append({'lat': latitude + dec_lat, 'lng': longitude +
dec_lon})
return result
results = []
if len(sites) > 0:
for row in db.session.execute(
'select * from get_gender_crossfilter(ARRAY[' + ','.join(
sites) + '])'):
results.append({'geos': generate_random_data(5), 'gender':
row['__gender'], 'age_range': row['__age_range'],
'timestamp': row['__sighting_date'], 'count': row[
'__count']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting/getgender/', methods=['POST'])
def get_gender():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute('select * from get_gender(ARRAY[' +
site_ids + '],' + "'" + from_sighting_date + "'" + ',' + "'" +
to_sighting_date + "'" + ')'):
results.append({'site_id': row['__site_id'], 'date_month': row[
'__date_month'], 'gender': row['__gender'], 'age_range':
row['__age_range'], 'perc_visits': row['__perc_visits'],
'scaled_visits': row['__scaled_visits']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting/getgendertotals/', methods=['POST'])
def get_gender_age_totals():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute(
'select * from get_gender_age_totals(ARRAY[' + site_ids + '],' +
"'" + from_sighting_date + "'" + ',' + "'" + to_sighting_date +
"'" + ')'):
results.append({'site_id': row['__site_id'], 'gender': row[
'__gender'], 'age_range': row['__age_range'], '__visits':
row['__visits']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting', methods=['GET'])
def get_sightings():
results = []
for sighting in LTESighting.get_all():
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/sitescomparison', methods=['POST'])
def get_sitescomparison():
sightings = LTESighting.query.filter(LTESighting.smallcell.has(
SmallCell.site_id.in_(request.data['selectedRow']))).filter(
LTESighting.timestamp.between(request.data['selectedDates'][0],
request.data['selectedDates'][1]))
return make_response(jsonify({'list': [sighting.serialise() for
sighting in sightings]})), 200
@app.route('/api/sighting/bysite', methods=['GET'])
def get_sightings_by_site():
site_ids = request.args.getlist('site_id')
results = []
for sighting in LTESighting.query:
if str(sighting.smallcell.site_id) in site_ids:
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/origindestination/all', methods=['GET'])
def get_all():
journeys = Journey.query.all()
thing = {}
for journey in journeys:
if journey.origin_id not in thing:
thing[journey.origin_id] = {}
if journey.destination_id not in thing[journey.origin_id
] and journey.destination_id != journey.origin_id:
thing[journey.origin_id][journey.destination_id
] = journey.data['total']
return make_response(jsonify(thing)), 200
@app.route('/api/origindestination/<origin_id>', methods=['GET'])
def get_od(origin_id):
journeys = Journey.query.all()
_j = []
for journey in journeys:
_j.append({'origin_id': journey.origin_id, 'destination_id':
journey.destination_id, 'total': journey.data['total']})
return make_response(jsonify({'list': _j})), 200
@app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>',
methods=['GET'])
def purchase(home_district_name, type_visitor):
days_sql = db.session.query(PurchDistrict.start_dow, func.count(
PurchDistrict.start_dow)).group_by(PurchDistrict.start_dow).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).order_by(func.
count(PurchDistrict.start_dow).desc()).all()
gender_sql = db.session.query(PurchDistrict.gender, func.count(
PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, func.count(PurchDistrict.gender)).group_by(
PurchDistrict.gender, PurchDistrict.age).filter(PurchDistrict.
gender.isnot(None)).filter(PurchDistrict.age.isnot(None)).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict
.gender)).group_by(PurchDistrict.gender, PurchDistrict.age,
PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)
).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.
type_visitor.in_([type_visitor])).all()
days_total = sum(i[1] for i in days_sql)
gender_total = sum(i[1] for i in gender_sql)
gender_age_total = sum(i[2] for i in gender_age_sql)
days_results = []
for result in days_sql:
days_results.append({'start_dow': result.start_dow, 'count':
result[1], 'percent': float(result[1]) / float(days_total),
'total': days_total})
gender_results = []
for result in gender_sql:
gender_results.append({'gender': result.gender, 'count': result
[1], 'percent': float(result[1]) / float(gender_total)})
gender_age_results = []
for result in gender_age_sql:
gender_age_results.append({'gender': result.gender, 'age':
result.age, 'count': result[2], 'percent': float(result[2]) /
float(gender_age_total)})
return make_response(jsonify({'days': days_results, 'gender':
gender_results, 'gender_age': gender_age_results})), 200
@app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=[
'GET'])
def purchase_rent(type_visitor):
gender_sql = db.session.query(PurchDistrict.gender, func.count(
PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict
.gender)).group_by(PurchDistrict.gender, PurchDistrict.age,
PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)
).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.
type_visitor.in_([type_visitor])).all()
gender_total = sum(i[1] for i in gender_sql)
gender_results = []
for result in gender_sql:
gender_results.append({'gender': result.gender, 'count': result
[1], 'percent': float(result[1]) / float(gender_total)})
gender_age_rent_results = []
for result in gender_age_rent_sql:
gender_age_rent_results.append({'gender': result.gender, 'age':
result.age, 'rent': result.rent, 'count': result[3]})
return make_response(jsonify({'gender': gender_results,
'gender_age_rent': gender_age_rent_results})), 200
@app.route('/api/ng_event/districts', methods=['GET'])
def districts():
home_results = []
for result in db.session.query(ZoneDistrict.home_district_code,
ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)
).group_by(ZoneDistrict.home_district_code, ZoneDistrict.
home_district_name).all():
home_results.append({'district_code': result.home_district_code,
'district_name': result.home_district_name, 'visitors':
result[2]})
work_results = []
for result in db.session.query(ZoneDistrict.work_district_code,
ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)
).group_by(ZoneDistrict.work_district_code, ZoneDistrict.
work_district_name).all():
work_results.append({'district_code': result.work_district_code,
'district_name': result.work_district_name, 'visitors':
result[2]})
return make_response(jsonify({'work': {'list': work_results},
'home': {'list': home_results}})), 200
@app.route('/api/ng_event/attractiontotals', methods=['GET'])
def attractiontotals():
results = []
for result in db.session.query(AttractionTotal.zone_visitors,
AttractionTotal.num_visitors).all():
results.append({'zone_visitors': result.zone_visitors,
'num_visitors': result.num_visitors})
return make_response(jsonify({'totals': {'list': results}})), 200
@app.route('/api/ng_event/profiles', methods=['GET'])
def profiles():
results = []
for result in db.session.query(Profile.country, Profile.nationality,
Profile.name_province, Profile.gender, Profile.age, Profile.
rent, Profile.type_visitor, Profile.date, Profile.day, Profile.
period, Profile.name_tur_zone).limit(10000):
district = ''
if result.name_tur_zone == 'Zone 1':
district = 'Chamartin'
if result.name_tur_zone == 'Zone 2':
district = 'Chamberi'
if result.name_tur_zone == 'Zone 3':
district = 'Salamanca'
day = ''
if result.day == 'Monday':
day = 'Mon'
if result.day == 'Tuesday':
day = 'Tue'
if result.day == 'Wednesday':
day = 'Wed'
if result.day == 'Thursday':
day = 'Thu'
if result.day == 'Friday':
day = 'Fri'
if result.day == 'Saturday':
day = 'Sat'
if result.day == 'Sunday':
day = 'Sun'
results.append({'country': result.country, 'nationality':
result.nationality, 'name_province': district, 'gender':
result.gender, 'age': result.age, 'rent': result.rent,
'type_visitor': result.type_visitor, 'date': result.date,
'day': day, 'period': result.period, 'zone': result.
name_tur_zone})
return make_response(jsonify(results)), 200
@app.route('/api/ng_event/dowfreq', methods=['GET'])
def dowfreq():
results = []
for result in db.session.query(DOWFrequency.type_visitor,
DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count
).all():
results.append({'type_visitor': result.type_visitor,
'start_dow': result.start_dow, 'start_hour': result.
start_hour, 'count': result.count})
return make_response(jsonify(results)), 200
return app
<|reserved_special_token_1|>
import json
from flask_api import FlaskAPI, status
import graphene
from graphene import relay
from graphene_sqlalchemy import SQLAlchemyConnectionField, SQLAlchemyObjectType
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func
from flask import request, jsonify, abort, make_response
from flask_graphql import GraphQLView
from shapely.geometry import shape, Point
from instance.config import app_config
from flask_bcrypt import Bcrypt
db = SQLAlchemy()
from app.models import Date, Area, LTESighting, SmallCell, Site, SightingsPerHourPerCountry, SightingsNew, SightingsBase, WideSighting, Journey
from app.models import Department as DepartmentModel
from app.ng_event_models import ZoneDistrict, AttractionTotal, Profile, PurchDistrict, DOWFrequency
class Department(SQLAlchemyObjectType):
class Meta:
model = DepartmentModel
interfaces = relay.Node,
class Query(graphene.ObjectType):
node = relay.Node.Field()
all_employees = SQLAlchemyConnectionField(Department)
def create_app(config_name):
app = FlaskAPI(__name__, instance_relative_config=True)
bcrypt = Bcrypt(app)
schema = graphene.Schema(query=Query)
app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql',
schema=schema, graphiql=True))
app.config.from_object(app_config[config_name])
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db.init_app(app)
@app.route('/api/areas/create', methods=['POST'])
def create_areas():
name = request.data.get('name', '')
geodata = request.data.get('geodata', '')
center_lat = request.data.get('center_lat')
center_lng = request.data.get('center_lng')
zoom = request.data.get('zoom')
area = Area(name=name, geodata=geodata, center_lat=center_lat,
center_lng=center_lng, zoom=zoom)
area.save()
response = jsonify({'id': area.id, 'name': area.name, 'geodata':
area.geodata, 'center_lat': area.center_lat, 'center_lng': area
.center_lng, 'zoom': area.zoom, 'date_created': area.
date_created, 'date_modified': area.date_modified})
return make_response(response), 201
@app.route('/api/areas/delete', methods=['POST'])
def delete_areas():
id = request.data.get('id', 0)
area = Area.query.filter_by(id=id).first()
if area is not None:
area.delete()
return make_response(jsonify({'id': id})), 200
@app.route('/api/sightingsperhour', methods=['GET'])
def get_sightingsperhour():
sightings = SightingsPerHourPerCountry.query.all()
results = []
for sighting in sightings:
results.append({'country': sighting.country, 'hour': sighting.
hour, 'count': sighting.count})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sightingsnew', methods=['POST'])
def sightingsnew():
sightings = db.session.query(SightingsBase.site_id, SightingsBase.
country, func.count(SightingsBase.roundedtoday)).filter(
SightingsBase.site_id.in_(request.data['selectedRow'])).filter(
SightingsBase.roundedtoday.between(request.data['selectedDates'
][0], request.data['selectedDates'][1])).group_by(SightingsBase
.site_id, SightingsBase.country).order_by(SightingsBase.site_id,
func.count(SightingsBase.roundedtoday).desc())
results = []
for sighting in sightings.all():
results.append({'country': sighting.country, 'site_id':
sighting.site_id, 'count': sighting[2]})
return make_response(jsonify({'list': results})), 200
@app.route('/api/widesightingsnew', methods=['POST', 'GET'])
def widesightingsnew():
sightings = db.session.query(WideSighting.site_id, WideSighting.
gender, func.count(WideSighting.gender)).filter(WideSighting.
site_id.in_([138, 134])).group_by(WideSighting.site_id,
WideSighting.gender)
results = []
for sighting in sightings.all():
results.append({'site_id': sighting.site_id, 'gender': sighting
.gender, 'count': sighting[2]})
return make_response(jsonify({'list': results})), 200
@app.route('/api/widesightings', methods=['GET'])
def widesightings():
sightings = WideSighting.get_all()
results = []
for sighting in sightings:
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/sites', methods=['GET'])
def get_sites():
sites = Site.get_all()
results = []
for site in sites:
results.append(site.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/dates', methods=['GET'])
def get_dates():
dates = Date.get_all()
results = []
for date in dates:
results.append(date.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/areas', methods=['GET'])
def get_areas():
areas = Area.get_all()
allSmallCells = SmallCell.get_all()
results = []
for area in areas:
smallcellInArea = []
for smallcell in allSmallCells:
smallcellInArea.append(smallcell.serialise())
obj = {'id': area.id, 'name': area.name, 'date_created': area.
date_created, 'date_modified': area.date_modified,
'center_lat': area.center_lat, 'center_lng': area.
center_lng, 'zoom': area.zoom, 'geodata': area.geodata,
'smallcells': smallcellInArea}
results.append(obj)
return make_response(jsonify({'list': results})), 200
@app.route('/api/smallcells', methods=['GET'])
def get_smallcells():
allSmallCells = SmallCell.query.order_by(SmallCell.id).all()
results = []
for smallcell in allSmallCells:
results.append(smallcell.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/smallcells/update', methods=['POST'])
def update_smallcell():
smallcell_id = request.data.get('id', '')
site_id = request.data.get('site_id', '')
smallcell = SmallCell.query.filter_by(id=smallcell_id).first()
smallcell.site_id = site_id
smallcell.save()
return make_response(jsonify({'smallcell_id': smallcell.id,
'site_id': smallcell.site_id})), 200
@app.route('/api/sighting/byarea/<areaid>', methods=['GET'])
def get_sighting(areaid):
import string
area = Area.query.filter_by(id=areaid).first()
if area is None:
return make_response(jsonify({'list': []})), 200
sites = []
for site in Site.get_all():
if area.contains(site):
sites.append(str(site.id))
def generate_random_data(num_rows):
import random
latitude = 51.51451110408478
longitude = -0.12620388576521444
result = []
for _ in range(num_rows):
dec_lat = random.random() / 10
dec_lon = random.random() / 10
result.append({'lat': latitude + dec_lat, 'lng': longitude +
dec_lon})
return result
results = []
if len(sites) > 0:
for row in db.session.execute(
'select * from get_gender_crossfilter(ARRAY[' + ','.join(
sites) + '])'):
results.append({'geos': generate_random_data(5), 'gender':
row['__gender'], 'age_range': row['__age_range'],
'timestamp': row['__sighting_date'], 'count': row[
'__count']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting/getgender/', methods=['POST'])
def get_gender():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute('select * from get_gender(ARRAY[' +
site_ids + '],' + "'" + from_sighting_date + "'" + ',' + "'" +
to_sighting_date + "'" + ')'):
results.append({'site_id': row['__site_id'], 'date_month': row[
'__date_month'], 'gender': row['__gender'], 'age_range':
row['__age_range'], 'perc_visits': row['__perc_visits'],
'scaled_visits': row['__scaled_visits']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting/getgendertotals/', methods=['POST'])
def get_gender_age_totals():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute(
'select * from get_gender_age_totals(ARRAY[' + site_ids + '],' +
"'" + from_sighting_date + "'" + ',' + "'" + to_sighting_date +
"'" + ')'):
results.append({'site_id': row['__site_id'], 'gender': row[
'__gender'], 'age_range': row['__age_range'], '__visits':
row['__visits']})
return make_response(jsonify({'list': results})), 200
@app.route('/api/sighting', methods=['GET'])
def get_sightings():
results = []
for sighting in LTESighting.get_all():
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/sitescomparison', methods=['POST'])
def get_sitescomparison():
sightings = LTESighting.query.filter(LTESighting.smallcell.has(
SmallCell.site_id.in_(request.data['selectedRow']))).filter(
LTESighting.timestamp.between(request.data['selectedDates'][0],
request.data['selectedDates'][1]))
return make_response(jsonify({'list': [sighting.serialise() for
sighting in sightings]})), 200
@app.route('/api/sighting/bysite', methods=['GET'])
def get_sightings_by_site():
site_ids = request.args.getlist('site_id')
results = []
for sighting in LTESighting.query:
if str(sighting.smallcell.site_id) in site_ids:
results.append(sighting.serialise())
return make_response(jsonify({'list': results})), 200
@app.route('/api/origindestination/all', methods=['GET'])
def get_all():
journeys = Journey.query.all()
thing = {}
for journey in journeys:
if journey.origin_id not in thing:
thing[journey.origin_id] = {}
if journey.destination_id not in thing[journey.origin_id
] and journey.destination_id != journey.origin_id:
thing[journey.origin_id][journey.destination_id
] = journey.data['total']
return make_response(jsonify(thing)), 200
@app.route('/api/origindestination/<origin_id>', methods=['GET'])
def get_od(origin_id):
journeys = Journey.query.all()
_j = []
for journey in journeys:
_j.append({'origin_id': journey.origin_id, 'destination_id':
journey.destination_id, 'total': journey.data['total']})
return make_response(jsonify({'list': _j})), 200
@app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>',
methods=['GET'])
def purchase(home_district_name, type_visitor):
days_sql = db.session.query(PurchDistrict.start_dow, func.count(
PurchDistrict.start_dow)).group_by(PurchDistrict.start_dow).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).order_by(func.
count(PurchDistrict.start_dow).desc()).all()
gender_sql = db.session.query(PurchDistrict.gender, func.count(
PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, func.count(PurchDistrict.gender)).group_by(
PurchDistrict.gender, PurchDistrict.age).filter(PurchDistrict.
gender.isnot(None)).filter(PurchDistrict.age.isnot(None)).filter(
PurchDistrict.home_district_name.in_([home_district_name])).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict
.gender)).group_by(PurchDistrict.gender, PurchDistrict.age,
PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)
).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.
type_visitor.in_([type_visitor])).all()
days_total = sum(i[1] for i in days_sql)
gender_total = sum(i[1] for i in gender_sql)
gender_age_total = sum(i[2] for i in gender_age_sql)
days_results = []
for result in days_sql:
days_results.append({'start_dow': result.start_dow, 'count':
result[1], 'percent': float(result[1]) / float(days_total),
'total': days_total})
gender_results = []
for result in gender_sql:
gender_results.append({'gender': result.gender, 'count': result
[1], 'percent': float(result[1]) / float(gender_total)})
gender_age_results = []
for result in gender_age_sql:
gender_age_results.append({'gender': result.gender, 'age':
result.age, 'count': result[2], 'percent': float(result[2]) /
float(gender_age_total)})
return make_response(jsonify({'days': days_results, 'gender':
gender_results, 'gender_age': gender_age_results})), 200
@app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=[
'GET'])
def purchase_rent(type_visitor):
gender_sql = db.session.query(PurchDistrict.gender, func.count(
PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(
PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender,
PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict
.gender)).group_by(PurchDistrict.gender, PurchDistrict.age,
PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)
).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.
type_visitor.in_([type_visitor])).all()
gender_total = sum(i[1] for i in gender_sql)
gender_results = []
for result in gender_sql:
gender_results.append({'gender': result.gender, 'count': result
[1], 'percent': float(result[1]) / float(gender_total)})
gender_age_rent_results = []
for result in gender_age_rent_sql:
gender_age_rent_results.append({'gender': result.gender, 'age':
result.age, 'rent': result.rent, 'count': result[3]})
return make_response(jsonify({'gender': gender_results,
'gender_age_rent': gender_age_rent_results})), 200
@app.route('/api/ng_event/districts', methods=['GET'])
def districts():
home_results = []
for result in db.session.query(ZoneDistrict.home_district_code,
ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)
).group_by(ZoneDistrict.home_district_code, ZoneDistrict.
home_district_name).all():
home_results.append({'district_code': result.home_district_code,
'district_name': result.home_district_name, 'visitors':
result[2]})
work_results = []
for result in db.session.query(ZoneDistrict.work_district_code,
ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)
).group_by(ZoneDistrict.work_district_code, ZoneDistrict.
work_district_name).all():
work_results.append({'district_code': result.work_district_code,
'district_name': result.work_district_name, 'visitors':
result[2]})
return make_response(jsonify({'work': {'list': work_results},
'home': {'list': home_results}})), 200
@app.route('/api/ng_event/attractiontotals', methods=['GET'])
def attractiontotals():
results = []
for result in db.session.query(AttractionTotal.zone_visitors,
AttractionTotal.num_visitors).all():
results.append({'zone_visitors': result.zone_visitors,
'num_visitors': result.num_visitors})
return make_response(jsonify({'totals': {'list': results}})), 200
@app.route('/api/ng_event/profiles', methods=['GET'])
def profiles():
results = []
for result in db.session.query(Profile.country, Profile.nationality,
Profile.name_province, Profile.gender, Profile.age, Profile.
rent, Profile.type_visitor, Profile.date, Profile.day, Profile.
period, Profile.name_tur_zone).limit(10000):
district = ''
if result.name_tur_zone == 'Zone 1':
district = 'Chamartin'
if result.name_tur_zone == 'Zone 2':
district = 'Chamberi'
if result.name_tur_zone == 'Zone 3':
district = 'Salamanca'
day = ''
if result.day == 'Monday':
day = 'Mon'
if result.day == 'Tuesday':
day = 'Tue'
if result.day == 'Wednesday':
day = 'Wed'
if result.day == 'Thursday':
day = 'Thu'
if result.day == 'Friday':
day = 'Fri'
if result.day == 'Saturday':
day = 'Sat'
if result.day == 'Sunday':
day = 'Sun'
results.append({'country': result.country, 'nationality':
result.nationality, 'name_province': district, 'gender':
result.gender, 'age': result.age, 'rent': result.rent,
'type_visitor': result.type_visitor, 'date': result.date,
'day': day, 'period': result.period, 'zone': result.
name_tur_zone})
return make_response(jsonify(results)), 200
@app.route('/api/ng_event/dowfreq', methods=['GET'])
def dowfreq():
results = []
for result in db.session.query(DOWFrequency.type_visitor,
DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count
).all():
results.append({'type_visitor': result.type_visitor,
'start_dow': result.start_dow, 'start_hour': result.
start_hour, 'count': result.count})
return make_response(jsonify(results)), 200
return app
<|reserved_special_token_1|>
# app/__init__.py
import json
from flask_api import FlaskAPI, status
import graphene
from graphene import relay
from graphene_sqlalchemy import SQLAlchemyConnectionField, SQLAlchemyObjectType
from flask_sqlalchemy import SQLAlchemy
from sqlalchemy import func
from flask import request, jsonify, abort, make_response
from flask_graphql import GraphQLView
from shapely.geometry import shape, Point
# local import
from instance.config import app_config
# For password hashing
from flask_bcrypt import Bcrypt
# initialize db
db = SQLAlchemy()
from app.models import Date, Area, LTESighting, SmallCell, Site, SightingsPerHourPerCountry, SightingsNew, SightingsBase, WideSighting, Journey
from app.models import Department as DepartmentModel
from app.ng_event_models import ZoneDistrict, AttractionTotal, Profile, PurchDistrict, DOWFrequency
class Department(SQLAlchemyObjectType):
class Meta:
model = DepartmentModel
interfaces = (relay.Node, )
class Query(graphene.ObjectType):
node = relay.Node.Field()
all_employees = SQLAlchemyConnectionField(Department)
def create_app(config_name):
app = FlaskAPI(__name__, instance_relative_config=True)
# overriding Werkzeugs built-in password hashing utilities using Bcrypt.
bcrypt = Bcrypt(app)
schema = graphene.Schema(query=Query)
app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql', schema=schema, graphiql=True))
app.config.from_object(app_config[config_name])
app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
db.init_app(app)
@app.route('/api/areas/create', methods=['POST'])
def create_areas():
# get the access token
name = request.data.get('name', '')
geodata = request.data.get('geodata', '')
center_lat = request.data.get('center_lat')
center_lng = request.data.get('center_lng')
zoom = request.data.get('zoom')
area = Area(name=name, geodata=geodata, center_lat=center_lat, center_lng=center_lng, zoom=zoom)
area.save()
response = jsonify({
'id': area.id,
'name': area.name,
'geodata': area.geodata,
'center_lat' : area.center_lat,
'center_lng' : area.center_lng,
'zoom' : area.zoom,
'date_created': area.date_created,
'date_modified': area.date_modified
})
return make_response(response), 201
@app.route('/api/areas/delete', methods=['POST'])
def delete_areas():
# get the access token
id = request.data.get('id', 0)
area = Area.query.filter_by(id=id).first()
if (area is not None):
area.delete()
return make_response(jsonify({'id':id})), 200
@app.route('/api/sightingsperhour', methods=['GET'])
def get_sightingsperhour():
# get all the areas
sightings = SightingsPerHourPerCountry.query.all()
results = []
for sighting in sightings:
results.append({'country' : sighting.country, 'hour' : sighting.hour, 'count' : sighting.count})
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/sightingsnew', methods=['POST'])
def sightingsnew():
sightings = db.session.query(SightingsBase.site_id, SightingsBase.country, func.count(SightingsBase.roundedtoday))\
.filter(SightingsBase.site_id.in_(request.data['selectedRow']))\
.filter(SightingsBase.roundedtoday.between(request.data['selectedDates'][0], request.data['selectedDates'][1]))\
.group_by(SightingsBase.site_id, SightingsBase.country)\
.order_by(SightingsBase.site_id, func.count(SightingsBase.roundedtoday).desc())\
results = []
for sighting in sightings.all():
results.append({'country' : sighting.country, 'site_id' : sighting.site_id, 'count' : sighting[2]})
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/widesightingsnew', methods=['POST', 'GET'])
def widesightingsnew():
sightings = db.session.query(WideSighting.site_id, WideSighting.gender, func.count(WideSighting.gender))\
.filter(WideSighting.site_id.in_([138, 134]))\
.group_by(WideSighting.site_id, WideSighting.gender)
results = []
for sighting in sightings.all():
#gender = sighting.gender if len(sighting.gender) else 'unknown'
results.append({'site_id' : sighting.site_id, 'gender' : sighting.gender, 'count' : sighting[2]})
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/widesightings', methods=['GET'])
def widesightings():
sightings = WideSighting.get_all()
results = []
for sighting in sightings:
results.append(sighting.serialise())
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/sites', methods=['GET'])
def get_sites():
# get all the areas
sites = Site.get_all()
results = []
for site in sites:
results.append(site.serialise())
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/dates', methods=['GET'])
def get_dates():
# get all the areas
dates = Date.get_all()
results = []
for date in dates:
results.append(date.serialise())
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/areas', methods=['GET'])
def get_areas():
# get all the areas
areas = Area.get_all()
allSmallCells = SmallCell.get_all()
results = []
for area in areas:
smallcellInArea = []
for smallcell in allSmallCells:
smallcellInArea.append(smallcell.serialise())
obj = {
'id': area.id,
'name': area.name,
'date_created': area.date_created,
'date_modified': area.date_modified,
'center_lat' : area.center_lat,
'center_lng' : area.center_lng,
'zoom' : area.zoom,
'geodata': area.geodata,
'smallcells' : smallcellInArea
}
results.append(obj)
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/smallcells', methods=['GET'])
def get_smallcells():
allSmallCells = SmallCell.query.order_by(SmallCell.id).all()
results = []
for smallcell in allSmallCells:
results.append(smallcell.serialise())
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/smallcells/update', methods=['POST'])
def update_smallcell():
smallcell_id = request.data.get('id', '')
site_id = request.data.get('site_id', '')
smallcell = SmallCell.query.filter_by(id=smallcell_id).first()
smallcell.site_id = site_id
smallcell.save()
return make_response(jsonify({ 'smallcell_id' : smallcell.id, 'site_id' : smallcell.site_id })), 200
@app.route('/api/sighting/byarea/<areaid>', methods=['GET'])
def get_sighting(areaid):
import string
area = Area.query.filter_by(id=areaid).first()
if area is None : return make_response(jsonify({ 'list' : [] })), 200
sites = []
for site in Site.get_all():
if area.contains(site):
sites.append(str(site.id))
def generate_random_data(num_rows):
import random
latitude = 51.51451110408478
longitude = -0.12620388576521444
result = []
for _ in range(num_rows):
dec_lat = random.random()/10
dec_lon = random.random()/10
result.append({'lat' : latitude + dec_lat, 'lng' : longitude + dec_lon})
return result
results = []
if (len(sites) > 0):
for row in db.session.execute('select * from get_gender_crossfilter(ARRAY[' + ','.join(sites) + '])'):
results.append(({ 'geos': generate_random_data(5), 'gender' : row['__gender'], 'age_range' : row['__age_range'], 'timestamp' : row['__sighting_date'], 'count' : row['__count'] }))
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/sighting/getgender/', methods=['POST'])
def get_gender():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute("select * from get_gender(ARRAY[" + site_ids + "]," + "'" + from_sighting_date + "'" + "," + "'" + to_sighting_date + "'" + ")"):
results.append(({ 'site_id' : row['__site_id'], 'date_month' : row['__date_month'], 'gender' : row['__gender'], 'age_range' : row['__age_range'], 'perc_visits' : row['__perc_visits'], 'scaled_visits' : row['__scaled_visits'] }))
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/sighting/getgendertotals/', methods=['POST'])
def get_gender_age_totals():
site_ids = str(request.data.get('site_ids', ''))
from_sighting_date = request.data.get('selectedDates')[0]
to_sighting_date = request.data.get('selectedDates')[1]
import string
results = []
for row in db.session.execute("select * from get_gender_age_totals(ARRAY[" + site_ids + "]," + "'" + from_sighting_date + "'" + "," + "'" + to_sighting_date + "'" + ")"):
results.append(({ 'site_id' : row['__site_id'], 'gender' : row['__gender'], 'age_range' : row['__age_range'], '__visits' : row['__visits'] }))
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/sighting', methods=['GET'])
def get_sightings():
results = []
for sighting in LTESighting.get_all():
results.append(sighting.serialise())
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/sitescomparison', methods=['POST'])
def get_sitescomparison():
sightings = LTESighting.query\
.filter(LTESighting.smallcell.has(SmallCell.site_id.in_(request.data['selectedRow'])))\
.filter(LTESighting.timestamp.between(request.data['selectedDates'][0], request.data['selectedDates'][1]))
return make_response(jsonify({ 'list' : [sighting.serialise() for sighting in sightings] })), 200
@app.route('/api/sighting/bysite', methods=['GET'])
def get_sightings_by_site():
site_ids = (request.args.getlist('site_id'))
results = []
#should do this better with joins!
for sighting in LTESighting.query:
if (str(sighting.smallcell.site_id)) in site_ids : results.append(sighting.serialise())
return make_response(jsonify({ 'list' : results })), 200
@app.route('/api/origindestination/all', methods=['GET'])
def get_all():
journeys = Journey.query.all()
thing = {}
for journey in journeys:
if (journey.origin_id not in thing) :
thing[journey.origin_id] = {}
if (journey.destination_id not in thing[journey.origin_id] and journey.destination_id != journey.origin_id) :
thing[journey.origin_id][journey.destination_id] = journey.data['total']
return make_response(jsonify(thing)), 200
@app.route('/api/origindestination/<origin_id>', methods=['GET'])
def get_od(origin_id):
journeys = Journey.query.all()#.filter_by(origin_id=origin_id).all()
_j = []
for journey in journeys:
_j.append({'origin_id' : journey.origin_id, 'destination_id' : journey.destination_id, 'total' : journey.data['total']})
#_j.append({'origin_id' : journey.origin_id, 'data' : (journey.data)})
return make_response(jsonify({ 'list' : _j })), 200
@app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>', methods=['GET'])
def purchase(home_district_name, type_visitor):
days_sql = db.session.query(PurchDistrict.start_dow, func.count(PurchDistrict.start_dow))\
.group_by(PurchDistrict.start_dow)\
.filter(PurchDistrict.home_district_name.in_([home_district_name]))\
.filter(PurchDistrict.type_visitor.in_([type_visitor]))\
.order_by(func.count(PurchDistrict.start_dow).desc())\
.all()
gender_sql = db.session.query(PurchDistrict.gender, func.count(PurchDistrict.gender))\
.group_by(PurchDistrict.gender)\
.filter(PurchDistrict.home_district_name.in_([home_district_name]))\
.filter(PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_sql = db.session.query(PurchDistrict.gender, PurchDistrict.age, func.count(PurchDistrict.gender))\
.group_by(PurchDistrict.gender, PurchDistrict.age)\
.filter(PurchDistrict.gender.isnot(None))\
.filter(PurchDistrict.age.isnot(None))\
.filter(PurchDistrict.home_district_name.in_([home_district_name]))\
.filter(PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict.gender))\
.group_by(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent)\
.filter(PurchDistrict.gender.isnot(None))\
.filter(PurchDistrict.age.isnot(None))\
.filter(PurchDistrict.type_visitor.in_([type_visitor])).all()
days_total = sum(i[1] for i in days_sql)
gender_total = sum(i[1] for i in gender_sql)
gender_age_total = sum(i[2] for i in gender_age_sql)
days_results = []
for result in days_sql:
days_results.append({ 'start_dow' : result.start_dow, 'count' : result[1], 'percent' : float(result[1])/float(days_total), 'total' : days_total})
gender_results = []
for result in gender_sql:
gender_results.append({'gender' : result.gender, 'count' : result[1], 'percent' : float(result[1])/float(gender_total)})
gender_age_results = []
for result in gender_age_sql:
gender_age_results.append({'gender' : result.gender, 'age' : result.age, 'count' : result[2], 'percent' : float(result[2])/float(gender_age_total)})
return make_response(jsonify({'days' : days_results, 'gender' : gender_results, 'gender_age' : gender_age_results})), 200
@app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=['GET'])
def purchase_rent(type_visitor):
gender_sql = db.session.query(PurchDistrict.gender, func.count(PurchDistrict.gender))\
.group_by(PurchDistrict.gender)\
.filter(PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_age_rent_sql = db.session.query(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict.gender))\
.group_by(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent)\
.filter(PurchDistrict.gender.isnot(None))\
.filter(PurchDistrict.age.isnot(None))\
.filter(PurchDistrict.type_visitor.in_([type_visitor])).all()
gender_total = sum(i[1] for i in gender_sql)
gender_results = []
for result in gender_sql:
gender_results.append({'gender' : result.gender, 'count' : result[1], 'percent' : float(result[1])/float(gender_total)})
gender_age_rent_results = []
for result in gender_age_rent_sql:
gender_age_rent_results.append({'gender' : result.gender, 'age' : result.age, 'rent' : result.rent, 'count' : result[3]})
return make_response(jsonify({'gender' : gender_results, 'gender_age_rent' : gender_age_rent_results})), 200
@app.route('/api/ng_event/districts', methods=['GET'])
def districts():
home_results = []
for result in db.session.query(ZoneDistrict.home_district_code, ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)).group_by(ZoneDistrict.home_district_code, ZoneDistrict.home_district_name).all():
home_results.append({'district_code' : result.home_district_code, 'district_name' : result.home_district_name, 'visitors' : result[2]})
work_results = []
for result in db.session.query(ZoneDistrict.work_district_code, ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)).group_by(ZoneDistrict.work_district_code, ZoneDistrict.work_district_name).all():
work_results.append({'district_code' : result.work_district_code, 'district_name' : result.work_district_name, 'visitors' : result[2]})
return make_response(jsonify({'work' : { 'list' : work_results }, 'home' : { 'list' : home_results }})), 200
@app.route('/api/ng_event/attractiontotals', methods=['GET'])
def attractiontotals():
results = []
for result in db.session.query(AttractionTotal.zone_visitors, AttractionTotal.num_visitors).all():
results.append({'zone_visitors' : result.zone_visitors, 'num_visitors' : result.num_visitors})
return make_response(jsonify({'totals' : { 'list' : results }})), 200
@app.route('/api/ng_event/profiles', methods=['GET'])
def profiles():
results = []
for result in db.session.query(Profile.country, Profile.nationality, Profile.name_province, Profile.gender, Profile.age, Profile.rent, Profile.type_visitor, Profile.date, Profile.day, Profile.period, Profile.name_tur_zone).limit(10000):
district = ''
if result.name_tur_zone == 'Zone 1' : district = 'Chamartin'
if result.name_tur_zone == 'Zone 2' : district = 'Chamberi'
if result.name_tur_zone == 'Zone 3' : district = 'Salamanca'
day = ''
if result.day == 'Monday' : day = 'Mon'
if result.day == 'Tuesday' : day = 'Tue'
if result.day == 'Wednesday' : day = 'Wed'
if result.day == 'Thursday' : day = 'Thu'
if result.day == 'Friday' : day = 'Fri'
if result.day == 'Saturday' : day = 'Sat'
if result.day == 'Sunday' : day = 'Sun'
results.append({'country' : result.country, 'nationality' : result.nationality, 'name_province' : district, 'gender' : result.gender, 'age' : result.age, 'rent' : result.rent, 'type_visitor' : result.type_visitor, 'date' : result.date, 'day' : day, 'period' : result.period, 'zone' : result.name_tur_zone })
return make_response(jsonify(results)), 200
@app.route('/api/ng_event/dowfreq', methods=['GET'])
def dowfreq():
results = []
for result in db.session.query(DOWFrequency.type_visitor, DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count).all():
results.append({'type_visitor' : result.type_visitor, 'start_dow' : result.start_dow, 'start_hour' : result.start_hour, 'count' : result.count })
return make_response(jsonify(results)), 200
return app
|
flexible
|
{
"blob_id": "2f76bcfde11597f87bb9e058f7617e95c78ed383",
"index": 7950,
"step-1": "<mask token>\n\n\nclass Department(SQLAlchemyObjectType):\n\n\n class Meta:\n model = DepartmentModel\n interfaces = relay.Node,\n\n\nclass Query(graphene.ObjectType):\n node = relay.Node.Field()\n all_employees = SQLAlchemyConnectionField(Department)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Department(SQLAlchemyObjectType):\n\n\n class Meta:\n model = DepartmentModel\n interfaces = relay.Node,\n\n\nclass Query(graphene.ObjectType):\n node = relay.Node.Field()\n all_employees = SQLAlchemyConnectionField(Department)\n\n\ndef create_app(config_name):\n app = FlaskAPI(__name__, instance_relative_config=True)\n bcrypt = Bcrypt(app)\n schema = graphene.Schema(query=Query)\n app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql',\n schema=schema, graphiql=True))\n app.config.from_object(app_config[config_name])\n app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False\n db.init_app(app)\n\n @app.route('/api/areas/create', methods=['POST'])\n def create_areas():\n name = request.data.get('name', '')\n geodata = request.data.get('geodata', '')\n center_lat = request.data.get('center_lat')\n center_lng = request.data.get('center_lng')\n zoom = request.data.get('zoom')\n area = Area(name=name, geodata=geodata, center_lat=center_lat,\n center_lng=center_lng, zoom=zoom)\n area.save()\n response = jsonify({'id': area.id, 'name': area.name, 'geodata':\n area.geodata, 'center_lat': area.center_lat, 'center_lng': area\n .center_lng, 'zoom': area.zoom, 'date_created': area.\n date_created, 'date_modified': area.date_modified})\n return make_response(response), 201\n\n @app.route('/api/areas/delete', methods=['POST'])\n def delete_areas():\n id = request.data.get('id', 0)\n area = Area.query.filter_by(id=id).first()\n if area is not None:\n area.delete()\n return make_response(jsonify({'id': id})), 200\n\n @app.route('/api/sightingsperhour', methods=['GET'])\n def get_sightingsperhour():\n sightings = SightingsPerHourPerCountry.query.all()\n results = []\n for sighting in sightings:\n results.append({'country': sighting.country, 'hour': sighting.\n hour, 'count': sighting.count})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sightingsnew', methods=['POST'])\n def sightingsnew():\n sightings = db.session.query(SightingsBase.site_id, SightingsBase.\n country, func.count(SightingsBase.roundedtoday)).filter(\n SightingsBase.site_id.in_(request.data['selectedRow'])).filter(\n SightingsBase.roundedtoday.between(request.data['selectedDates'\n ][0], request.data['selectedDates'][1])).group_by(SightingsBase\n .site_id, SightingsBase.country).order_by(SightingsBase.site_id,\n func.count(SightingsBase.roundedtoday).desc())\n results = []\n for sighting in sightings.all():\n results.append({'country': sighting.country, 'site_id':\n sighting.site_id, 'count': sighting[2]})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/widesightingsnew', methods=['POST', 'GET'])\n def widesightingsnew():\n sightings = db.session.query(WideSighting.site_id, WideSighting.\n gender, func.count(WideSighting.gender)).filter(WideSighting.\n site_id.in_([138, 134])).group_by(WideSighting.site_id,\n WideSighting.gender)\n results = []\n for sighting in sightings.all():\n results.append({'site_id': sighting.site_id, 'gender': sighting\n .gender, 'count': sighting[2]})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/widesightings', methods=['GET'])\n def widesightings():\n sightings = WideSighting.get_all()\n results = []\n for sighting in sightings:\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sites', methods=['GET'])\n def get_sites():\n sites = Site.get_all()\n results = []\n for site in sites:\n results.append(site.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/dates', methods=['GET'])\n def get_dates():\n dates = Date.get_all()\n results = []\n for date in dates:\n results.append(date.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/areas', methods=['GET'])\n def get_areas():\n areas = Area.get_all()\n allSmallCells = SmallCell.get_all()\n results = []\n for area in areas:\n smallcellInArea = []\n for smallcell in allSmallCells:\n smallcellInArea.append(smallcell.serialise())\n obj = {'id': area.id, 'name': area.name, 'date_created': area.\n date_created, 'date_modified': area.date_modified,\n 'center_lat': area.center_lat, 'center_lng': area.\n center_lng, 'zoom': area.zoom, 'geodata': area.geodata,\n 'smallcells': smallcellInArea}\n results.append(obj)\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/smallcells', methods=['GET'])\n def get_smallcells():\n allSmallCells = SmallCell.query.order_by(SmallCell.id).all()\n results = []\n for smallcell in allSmallCells:\n results.append(smallcell.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/smallcells/update', methods=['POST'])\n def update_smallcell():\n smallcell_id = request.data.get('id', '')\n site_id = request.data.get('site_id', '')\n smallcell = SmallCell.query.filter_by(id=smallcell_id).first()\n smallcell.site_id = site_id\n smallcell.save()\n return make_response(jsonify({'smallcell_id': smallcell.id,\n 'site_id': smallcell.site_id})), 200\n\n @app.route('/api/sighting/byarea/<areaid>', methods=['GET'])\n def get_sighting(areaid):\n import string\n area = Area.query.filter_by(id=areaid).first()\n if area is None:\n return make_response(jsonify({'list': []})), 200\n sites = []\n for site in Site.get_all():\n if area.contains(site):\n sites.append(str(site.id))\n\n def generate_random_data(num_rows):\n import random\n latitude = 51.51451110408478\n longitude = -0.12620388576521444\n result = []\n for _ in range(num_rows):\n dec_lat = random.random() / 10\n dec_lon = random.random() / 10\n result.append({'lat': latitude + dec_lat, 'lng': longitude +\n dec_lon})\n return result\n results = []\n if len(sites) > 0:\n for row in db.session.execute(\n 'select * from get_gender_crossfilter(ARRAY[' + ','.join(\n sites) + '])'):\n results.append({'geos': generate_random_data(5), 'gender':\n row['__gender'], 'age_range': row['__age_range'],\n 'timestamp': row['__sighting_date'], 'count': row[\n '__count']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting/getgender/', methods=['POST'])\n def get_gender():\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n import string\n results = []\n for row in db.session.execute('select * from get_gender(ARRAY[' +\n site_ids + '],' + \"'\" + from_sighting_date + \"'\" + ',' + \"'\" +\n to_sighting_date + \"'\" + ')'):\n results.append({'site_id': row['__site_id'], 'date_month': row[\n '__date_month'], 'gender': row['__gender'], 'age_range':\n row['__age_range'], 'perc_visits': row['__perc_visits'],\n 'scaled_visits': row['__scaled_visits']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting/getgendertotals/', methods=['POST'])\n def get_gender_age_totals():\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n import string\n results = []\n for row in db.session.execute(\n 'select * from get_gender_age_totals(ARRAY[' + site_ids + '],' +\n \"'\" + from_sighting_date + \"'\" + ',' + \"'\" + to_sighting_date +\n \"'\" + ')'):\n results.append({'site_id': row['__site_id'], 'gender': row[\n '__gender'], 'age_range': row['__age_range'], '__visits':\n row['__visits']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting', methods=['GET'])\n def get_sightings():\n results = []\n for sighting in LTESighting.get_all():\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sitescomparison', methods=['POST'])\n def get_sitescomparison():\n sightings = LTESighting.query.filter(LTESighting.smallcell.has(\n SmallCell.site_id.in_(request.data['selectedRow']))).filter(\n LTESighting.timestamp.between(request.data['selectedDates'][0],\n request.data['selectedDates'][1]))\n return make_response(jsonify({'list': [sighting.serialise() for\n sighting in sightings]})), 200\n\n @app.route('/api/sighting/bysite', methods=['GET'])\n def get_sightings_by_site():\n site_ids = request.args.getlist('site_id')\n results = []\n for sighting in LTESighting.query:\n if str(sighting.smallcell.site_id) in site_ids:\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/origindestination/all', methods=['GET'])\n def get_all():\n journeys = Journey.query.all()\n thing = {}\n for journey in journeys:\n if journey.origin_id not in thing:\n thing[journey.origin_id] = {}\n if journey.destination_id not in thing[journey.origin_id\n ] and journey.destination_id != journey.origin_id:\n thing[journey.origin_id][journey.destination_id\n ] = journey.data['total']\n return make_response(jsonify(thing)), 200\n\n @app.route('/api/origindestination/<origin_id>', methods=['GET'])\n def get_od(origin_id):\n journeys = Journey.query.all()\n _j = []\n for journey in journeys:\n _j.append({'origin_id': journey.origin_id, 'destination_id':\n journey.destination_id, 'total': journey.data['total']})\n return make_response(jsonify({'list': _j})), 200\n\n @app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>',\n methods=['GET'])\n def purchase(home_district_name, type_visitor):\n days_sql = db.session.query(PurchDistrict.start_dow, func.count(\n PurchDistrict.start_dow)).group_by(PurchDistrict.start_dow).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).order_by(func.\n count(PurchDistrict.start_dow).desc()).all()\n gender_sql = db.session.query(PurchDistrict.gender, func.count(\n PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, func.count(PurchDistrict.gender)).group_by(\n PurchDistrict.gender, PurchDistrict.age).filter(PurchDistrict.\n gender.isnot(None)).filter(PurchDistrict.age.isnot(None)).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_rent_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict\n .gender)).group_by(PurchDistrict.gender, PurchDistrict.age,\n PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)\n ).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.\n type_visitor.in_([type_visitor])).all()\n days_total = sum(i[1] for i in days_sql)\n gender_total = sum(i[1] for i in gender_sql)\n gender_age_total = sum(i[2] for i in gender_age_sql)\n days_results = []\n for result in days_sql:\n days_results.append({'start_dow': result.start_dow, 'count':\n result[1], 'percent': float(result[1]) / float(days_total),\n 'total': days_total})\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender': result.gender, 'count': result\n [1], 'percent': float(result[1]) / float(gender_total)})\n gender_age_results = []\n for result in gender_age_sql:\n gender_age_results.append({'gender': result.gender, 'age':\n result.age, 'count': result[2], 'percent': float(result[2]) /\n float(gender_age_total)})\n return make_response(jsonify({'days': days_results, 'gender':\n gender_results, 'gender_age': gender_age_results})), 200\n\n @app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=[\n 'GET'])\n def purchase_rent(type_visitor):\n gender_sql = db.session.query(PurchDistrict.gender, func.count(\n PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_rent_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict\n .gender)).group_by(PurchDistrict.gender, PurchDistrict.age,\n PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)\n ).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.\n type_visitor.in_([type_visitor])).all()\n gender_total = sum(i[1] for i in gender_sql)\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender': result.gender, 'count': result\n [1], 'percent': float(result[1]) / float(gender_total)})\n gender_age_rent_results = []\n for result in gender_age_rent_sql:\n gender_age_rent_results.append({'gender': result.gender, 'age':\n result.age, 'rent': result.rent, 'count': result[3]})\n return make_response(jsonify({'gender': gender_results,\n 'gender_age_rent': gender_age_rent_results})), 200\n\n @app.route('/api/ng_event/districts', methods=['GET'])\n def districts():\n home_results = []\n for result in db.session.query(ZoneDistrict.home_district_code,\n ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)\n ).group_by(ZoneDistrict.home_district_code, ZoneDistrict.\n home_district_name).all():\n home_results.append({'district_code': result.home_district_code,\n 'district_name': result.home_district_name, 'visitors':\n result[2]})\n work_results = []\n for result in db.session.query(ZoneDistrict.work_district_code,\n ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)\n ).group_by(ZoneDistrict.work_district_code, ZoneDistrict.\n work_district_name).all():\n work_results.append({'district_code': result.work_district_code,\n 'district_name': result.work_district_name, 'visitors':\n result[2]})\n return make_response(jsonify({'work': {'list': work_results},\n 'home': {'list': home_results}})), 200\n\n @app.route('/api/ng_event/attractiontotals', methods=['GET'])\n def attractiontotals():\n results = []\n for result in db.session.query(AttractionTotal.zone_visitors,\n AttractionTotal.num_visitors).all():\n results.append({'zone_visitors': result.zone_visitors,\n 'num_visitors': result.num_visitors})\n return make_response(jsonify({'totals': {'list': results}})), 200\n\n @app.route('/api/ng_event/profiles', methods=['GET'])\n def profiles():\n results = []\n for result in db.session.query(Profile.country, Profile.nationality,\n Profile.name_province, Profile.gender, Profile.age, Profile.\n rent, Profile.type_visitor, Profile.date, Profile.day, Profile.\n period, Profile.name_tur_zone).limit(10000):\n district = ''\n if result.name_tur_zone == 'Zone 1':\n district = 'Chamartin'\n if result.name_tur_zone == 'Zone 2':\n district = 'Chamberi'\n if result.name_tur_zone == 'Zone 3':\n district = 'Salamanca'\n day = ''\n if result.day == 'Monday':\n day = 'Mon'\n if result.day == 'Tuesday':\n day = 'Tue'\n if result.day == 'Wednesday':\n day = 'Wed'\n if result.day == 'Thursday':\n day = 'Thu'\n if result.day == 'Friday':\n day = 'Fri'\n if result.day == 'Saturday':\n day = 'Sat'\n if result.day == 'Sunday':\n day = 'Sun'\n results.append({'country': result.country, 'nationality':\n result.nationality, 'name_province': district, 'gender':\n result.gender, 'age': result.age, 'rent': result.rent,\n 'type_visitor': result.type_visitor, 'date': result.date,\n 'day': day, 'period': result.period, 'zone': result.\n name_tur_zone})\n return make_response(jsonify(results)), 200\n\n @app.route('/api/ng_event/dowfreq', methods=['GET'])\n def dowfreq():\n results = []\n for result in db.session.query(DOWFrequency.type_visitor,\n DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count\n ).all():\n results.append({'type_visitor': result.type_visitor,\n 'start_dow': result.start_dow, 'start_hour': result.\n start_hour, 'count': result.count})\n return make_response(jsonify(results)), 200\n return app\n",
"step-3": "<mask token>\ndb = SQLAlchemy()\n<mask token>\n\n\nclass Department(SQLAlchemyObjectType):\n\n\n class Meta:\n model = DepartmentModel\n interfaces = relay.Node,\n\n\nclass Query(graphene.ObjectType):\n node = relay.Node.Field()\n all_employees = SQLAlchemyConnectionField(Department)\n\n\ndef create_app(config_name):\n app = FlaskAPI(__name__, instance_relative_config=True)\n bcrypt = Bcrypt(app)\n schema = graphene.Schema(query=Query)\n app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql',\n schema=schema, graphiql=True))\n app.config.from_object(app_config[config_name])\n app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False\n db.init_app(app)\n\n @app.route('/api/areas/create', methods=['POST'])\n def create_areas():\n name = request.data.get('name', '')\n geodata = request.data.get('geodata', '')\n center_lat = request.data.get('center_lat')\n center_lng = request.data.get('center_lng')\n zoom = request.data.get('zoom')\n area = Area(name=name, geodata=geodata, center_lat=center_lat,\n center_lng=center_lng, zoom=zoom)\n area.save()\n response = jsonify({'id': area.id, 'name': area.name, 'geodata':\n area.geodata, 'center_lat': area.center_lat, 'center_lng': area\n .center_lng, 'zoom': area.zoom, 'date_created': area.\n date_created, 'date_modified': area.date_modified})\n return make_response(response), 201\n\n @app.route('/api/areas/delete', methods=['POST'])\n def delete_areas():\n id = request.data.get('id', 0)\n area = Area.query.filter_by(id=id).first()\n if area is not None:\n area.delete()\n return make_response(jsonify({'id': id})), 200\n\n @app.route('/api/sightingsperhour', methods=['GET'])\n def get_sightingsperhour():\n sightings = SightingsPerHourPerCountry.query.all()\n results = []\n for sighting in sightings:\n results.append({'country': sighting.country, 'hour': sighting.\n hour, 'count': sighting.count})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sightingsnew', methods=['POST'])\n def sightingsnew():\n sightings = db.session.query(SightingsBase.site_id, SightingsBase.\n country, func.count(SightingsBase.roundedtoday)).filter(\n SightingsBase.site_id.in_(request.data['selectedRow'])).filter(\n SightingsBase.roundedtoday.between(request.data['selectedDates'\n ][0], request.data['selectedDates'][1])).group_by(SightingsBase\n .site_id, SightingsBase.country).order_by(SightingsBase.site_id,\n func.count(SightingsBase.roundedtoday).desc())\n results = []\n for sighting in sightings.all():\n results.append({'country': sighting.country, 'site_id':\n sighting.site_id, 'count': sighting[2]})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/widesightingsnew', methods=['POST', 'GET'])\n def widesightingsnew():\n sightings = db.session.query(WideSighting.site_id, WideSighting.\n gender, func.count(WideSighting.gender)).filter(WideSighting.\n site_id.in_([138, 134])).group_by(WideSighting.site_id,\n WideSighting.gender)\n results = []\n for sighting in sightings.all():\n results.append({'site_id': sighting.site_id, 'gender': sighting\n .gender, 'count': sighting[2]})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/widesightings', methods=['GET'])\n def widesightings():\n sightings = WideSighting.get_all()\n results = []\n for sighting in sightings:\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sites', methods=['GET'])\n def get_sites():\n sites = Site.get_all()\n results = []\n for site in sites:\n results.append(site.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/dates', methods=['GET'])\n def get_dates():\n dates = Date.get_all()\n results = []\n for date in dates:\n results.append(date.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/areas', methods=['GET'])\n def get_areas():\n areas = Area.get_all()\n allSmallCells = SmallCell.get_all()\n results = []\n for area in areas:\n smallcellInArea = []\n for smallcell in allSmallCells:\n smallcellInArea.append(smallcell.serialise())\n obj = {'id': area.id, 'name': area.name, 'date_created': area.\n date_created, 'date_modified': area.date_modified,\n 'center_lat': area.center_lat, 'center_lng': area.\n center_lng, 'zoom': area.zoom, 'geodata': area.geodata,\n 'smallcells': smallcellInArea}\n results.append(obj)\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/smallcells', methods=['GET'])\n def get_smallcells():\n allSmallCells = SmallCell.query.order_by(SmallCell.id).all()\n results = []\n for smallcell in allSmallCells:\n results.append(smallcell.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/smallcells/update', methods=['POST'])\n def update_smallcell():\n smallcell_id = request.data.get('id', '')\n site_id = request.data.get('site_id', '')\n smallcell = SmallCell.query.filter_by(id=smallcell_id).first()\n smallcell.site_id = site_id\n smallcell.save()\n return make_response(jsonify({'smallcell_id': smallcell.id,\n 'site_id': smallcell.site_id})), 200\n\n @app.route('/api/sighting/byarea/<areaid>', methods=['GET'])\n def get_sighting(areaid):\n import string\n area = Area.query.filter_by(id=areaid).first()\n if area is None:\n return make_response(jsonify({'list': []})), 200\n sites = []\n for site in Site.get_all():\n if area.contains(site):\n sites.append(str(site.id))\n\n def generate_random_data(num_rows):\n import random\n latitude = 51.51451110408478\n longitude = -0.12620388576521444\n result = []\n for _ in range(num_rows):\n dec_lat = random.random() / 10\n dec_lon = random.random() / 10\n result.append({'lat': latitude + dec_lat, 'lng': longitude +\n dec_lon})\n return result\n results = []\n if len(sites) > 0:\n for row in db.session.execute(\n 'select * from get_gender_crossfilter(ARRAY[' + ','.join(\n sites) + '])'):\n results.append({'geos': generate_random_data(5), 'gender':\n row['__gender'], 'age_range': row['__age_range'],\n 'timestamp': row['__sighting_date'], 'count': row[\n '__count']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting/getgender/', methods=['POST'])\n def get_gender():\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n import string\n results = []\n for row in db.session.execute('select * from get_gender(ARRAY[' +\n site_ids + '],' + \"'\" + from_sighting_date + \"'\" + ',' + \"'\" +\n to_sighting_date + \"'\" + ')'):\n results.append({'site_id': row['__site_id'], 'date_month': row[\n '__date_month'], 'gender': row['__gender'], 'age_range':\n row['__age_range'], 'perc_visits': row['__perc_visits'],\n 'scaled_visits': row['__scaled_visits']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting/getgendertotals/', methods=['POST'])\n def get_gender_age_totals():\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n import string\n results = []\n for row in db.session.execute(\n 'select * from get_gender_age_totals(ARRAY[' + site_ids + '],' +\n \"'\" + from_sighting_date + \"'\" + ',' + \"'\" + to_sighting_date +\n \"'\" + ')'):\n results.append({'site_id': row['__site_id'], 'gender': row[\n '__gender'], 'age_range': row['__age_range'], '__visits':\n row['__visits']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting', methods=['GET'])\n def get_sightings():\n results = []\n for sighting in LTESighting.get_all():\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sitescomparison', methods=['POST'])\n def get_sitescomparison():\n sightings = LTESighting.query.filter(LTESighting.smallcell.has(\n SmallCell.site_id.in_(request.data['selectedRow']))).filter(\n LTESighting.timestamp.between(request.data['selectedDates'][0],\n request.data['selectedDates'][1]))\n return make_response(jsonify({'list': [sighting.serialise() for\n sighting in sightings]})), 200\n\n @app.route('/api/sighting/bysite', methods=['GET'])\n def get_sightings_by_site():\n site_ids = request.args.getlist('site_id')\n results = []\n for sighting in LTESighting.query:\n if str(sighting.smallcell.site_id) in site_ids:\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/origindestination/all', methods=['GET'])\n def get_all():\n journeys = Journey.query.all()\n thing = {}\n for journey in journeys:\n if journey.origin_id not in thing:\n thing[journey.origin_id] = {}\n if journey.destination_id not in thing[journey.origin_id\n ] and journey.destination_id != journey.origin_id:\n thing[journey.origin_id][journey.destination_id\n ] = journey.data['total']\n return make_response(jsonify(thing)), 200\n\n @app.route('/api/origindestination/<origin_id>', methods=['GET'])\n def get_od(origin_id):\n journeys = Journey.query.all()\n _j = []\n for journey in journeys:\n _j.append({'origin_id': journey.origin_id, 'destination_id':\n journey.destination_id, 'total': journey.data['total']})\n return make_response(jsonify({'list': _j})), 200\n\n @app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>',\n methods=['GET'])\n def purchase(home_district_name, type_visitor):\n days_sql = db.session.query(PurchDistrict.start_dow, func.count(\n PurchDistrict.start_dow)).group_by(PurchDistrict.start_dow).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).order_by(func.\n count(PurchDistrict.start_dow).desc()).all()\n gender_sql = db.session.query(PurchDistrict.gender, func.count(\n PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, func.count(PurchDistrict.gender)).group_by(\n PurchDistrict.gender, PurchDistrict.age).filter(PurchDistrict.\n gender.isnot(None)).filter(PurchDistrict.age.isnot(None)).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_rent_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict\n .gender)).group_by(PurchDistrict.gender, PurchDistrict.age,\n PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)\n ).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.\n type_visitor.in_([type_visitor])).all()\n days_total = sum(i[1] for i in days_sql)\n gender_total = sum(i[1] for i in gender_sql)\n gender_age_total = sum(i[2] for i in gender_age_sql)\n days_results = []\n for result in days_sql:\n days_results.append({'start_dow': result.start_dow, 'count':\n result[1], 'percent': float(result[1]) / float(days_total),\n 'total': days_total})\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender': result.gender, 'count': result\n [1], 'percent': float(result[1]) / float(gender_total)})\n gender_age_results = []\n for result in gender_age_sql:\n gender_age_results.append({'gender': result.gender, 'age':\n result.age, 'count': result[2], 'percent': float(result[2]) /\n float(gender_age_total)})\n return make_response(jsonify({'days': days_results, 'gender':\n gender_results, 'gender_age': gender_age_results})), 200\n\n @app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=[\n 'GET'])\n def purchase_rent(type_visitor):\n gender_sql = db.session.query(PurchDistrict.gender, func.count(\n PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_rent_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict\n .gender)).group_by(PurchDistrict.gender, PurchDistrict.age,\n PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)\n ).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.\n type_visitor.in_([type_visitor])).all()\n gender_total = sum(i[1] for i in gender_sql)\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender': result.gender, 'count': result\n [1], 'percent': float(result[1]) / float(gender_total)})\n gender_age_rent_results = []\n for result in gender_age_rent_sql:\n gender_age_rent_results.append({'gender': result.gender, 'age':\n result.age, 'rent': result.rent, 'count': result[3]})\n return make_response(jsonify({'gender': gender_results,\n 'gender_age_rent': gender_age_rent_results})), 200\n\n @app.route('/api/ng_event/districts', methods=['GET'])\n def districts():\n home_results = []\n for result in db.session.query(ZoneDistrict.home_district_code,\n ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)\n ).group_by(ZoneDistrict.home_district_code, ZoneDistrict.\n home_district_name).all():\n home_results.append({'district_code': result.home_district_code,\n 'district_name': result.home_district_name, 'visitors':\n result[2]})\n work_results = []\n for result in db.session.query(ZoneDistrict.work_district_code,\n ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)\n ).group_by(ZoneDistrict.work_district_code, ZoneDistrict.\n work_district_name).all():\n work_results.append({'district_code': result.work_district_code,\n 'district_name': result.work_district_name, 'visitors':\n result[2]})\n return make_response(jsonify({'work': {'list': work_results},\n 'home': {'list': home_results}})), 200\n\n @app.route('/api/ng_event/attractiontotals', methods=['GET'])\n def attractiontotals():\n results = []\n for result in db.session.query(AttractionTotal.zone_visitors,\n AttractionTotal.num_visitors).all():\n results.append({'zone_visitors': result.zone_visitors,\n 'num_visitors': result.num_visitors})\n return make_response(jsonify({'totals': {'list': results}})), 200\n\n @app.route('/api/ng_event/profiles', methods=['GET'])\n def profiles():\n results = []\n for result in db.session.query(Profile.country, Profile.nationality,\n Profile.name_province, Profile.gender, Profile.age, Profile.\n rent, Profile.type_visitor, Profile.date, Profile.day, Profile.\n period, Profile.name_tur_zone).limit(10000):\n district = ''\n if result.name_tur_zone == 'Zone 1':\n district = 'Chamartin'\n if result.name_tur_zone == 'Zone 2':\n district = 'Chamberi'\n if result.name_tur_zone == 'Zone 3':\n district = 'Salamanca'\n day = ''\n if result.day == 'Monday':\n day = 'Mon'\n if result.day == 'Tuesday':\n day = 'Tue'\n if result.day == 'Wednesday':\n day = 'Wed'\n if result.day == 'Thursday':\n day = 'Thu'\n if result.day == 'Friday':\n day = 'Fri'\n if result.day == 'Saturday':\n day = 'Sat'\n if result.day == 'Sunday':\n day = 'Sun'\n results.append({'country': result.country, 'nationality':\n result.nationality, 'name_province': district, 'gender':\n result.gender, 'age': result.age, 'rent': result.rent,\n 'type_visitor': result.type_visitor, 'date': result.date,\n 'day': day, 'period': result.period, 'zone': result.\n name_tur_zone})\n return make_response(jsonify(results)), 200\n\n @app.route('/api/ng_event/dowfreq', methods=['GET'])\n def dowfreq():\n results = []\n for result in db.session.query(DOWFrequency.type_visitor,\n DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count\n ).all():\n results.append({'type_visitor': result.type_visitor,\n 'start_dow': result.start_dow, 'start_hour': result.\n start_hour, 'count': result.count})\n return make_response(jsonify(results)), 200\n return app\n",
"step-4": "import json\nfrom flask_api import FlaskAPI, status\nimport graphene\nfrom graphene import relay\nfrom graphene_sqlalchemy import SQLAlchemyConnectionField, SQLAlchemyObjectType\nfrom flask_sqlalchemy import SQLAlchemy\nfrom sqlalchemy import func\nfrom flask import request, jsonify, abort, make_response\nfrom flask_graphql import GraphQLView\nfrom shapely.geometry import shape, Point\nfrom instance.config import app_config\nfrom flask_bcrypt import Bcrypt\ndb = SQLAlchemy()\nfrom app.models import Date, Area, LTESighting, SmallCell, Site, SightingsPerHourPerCountry, SightingsNew, SightingsBase, WideSighting, Journey\nfrom app.models import Department as DepartmentModel\nfrom app.ng_event_models import ZoneDistrict, AttractionTotal, Profile, PurchDistrict, DOWFrequency\n\n\nclass Department(SQLAlchemyObjectType):\n\n\n class Meta:\n model = DepartmentModel\n interfaces = relay.Node,\n\n\nclass Query(graphene.ObjectType):\n node = relay.Node.Field()\n all_employees = SQLAlchemyConnectionField(Department)\n\n\ndef create_app(config_name):\n app = FlaskAPI(__name__, instance_relative_config=True)\n bcrypt = Bcrypt(app)\n schema = graphene.Schema(query=Query)\n app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql',\n schema=schema, graphiql=True))\n app.config.from_object(app_config[config_name])\n app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False\n db.init_app(app)\n\n @app.route('/api/areas/create', methods=['POST'])\n def create_areas():\n name = request.data.get('name', '')\n geodata = request.data.get('geodata', '')\n center_lat = request.data.get('center_lat')\n center_lng = request.data.get('center_lng')\n zoom = request.data.get('zoom')\n area = Area(name=name, geodata=geodata, center_lat=center_lat,\n center_lng=center_lng, zoom=zoom)\n area.save()\n response = jsonify({'id': area.id, 'name': area.name, 'geodata':\n area.geodata, 'center_lat': area.center_lat, 'center_lng': area\n .center_lng, 'zoom': area.zoom, 'date_created': area.\n date_created, 'date_modified': area.date_modified})\n return make_response(response), 201\n\n @app.route('/api/areas/delete', methods=['POST'])\n def delete_areas():\n id = request.data.get('id', 0)\n area = Area.query.filter_by(id=id).first()\n if area is not None:\n area.delete()\n return make_response(jsonify({'id': id})), 200\n\n @app.route('/api/sightingsperhour', methods=['GET'])\n def get_sightingsperhour():\n sightings = SightingsPerHourPerCountry.query.all()\n results = []\n for sighting in sightings:\n results.append({'country': sighting.country, 'hour': sighting.\n hour, 'count': sighting.count})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sightingsnew', methods=['POST'])\n def sightingsnew():\n sightings = db.session.query(SightingsBase.site_id, SightingsBase.\n country, func.count(SightingsBase.roundedtoday)).filter(\n SightingsBase.site_id.in_(request.data['selectedRow'])).filter(\n SightingsBase.roundedtoday.between(request.data['selectedDates'\n ][0], request.data['selectedDates'][1])).group_by(SightingsBase\n .site_id, SightingsBase.country).order_by(SightingsBase.site_id,\n func.count(SightingsBase.roundedtoday).desc())\n results = []\n for sighting in sightings.all():\n results.append({'country': sighting.country, 'site_id':\n sighting.site_id, 'count': sighting[2]})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/widesightingsnew', methods=['POST', 'GET'])\n def widesightingsnew():\n sightings = db.session.query(WideSighting.site_id, WideSighting.\n gender, func.count(WideSighting.gender)).filter(WideSighting.\n site_id.in_([138, 134])).group_by(WideSighting.site_id,\n WideSighting.gender)\n results = []\n for sighting in sightings.all():\n results.append({'site_id': sighting.site_id, 'gender': sighting\n .gender, 'count': sighting[2]})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/widesightings', methods=['GET'])\n def widesightings():\n sightings = WideSighting.get_all()\n results = []\n for sighting in sightings:\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sites', methods=['GET'])\n def get_sites():\n sites = Site.get_all()\n results = []\n for site in sites:\n results.append(site.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/dates', methods=['GET'])\n def get_dates():\n dates = Date.get_all()\n results = []\n for date in dates:\n results.append(date.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/areas', methods=['GET'])\n def get_areas():\n areas = Area.get_all()\n allSmallCells = SmallCell.get_all()\n results = []\n for area in areas:\n smallcellInArea = []\n for smallcell in allSmallCells:\n smallcellInArea.append(smallcell.serialise())\n obj = {'id': area.id, 'name': area.name, 'date_created': area.\n date_created, 'date_modified': area.date_modified,\n 'center_lat': area.center_lat, 'center_lng': area.\n center_lng, 'zoom': area.zoom, 'geodata': area.geodata,\n 'smallcells': smallcellInArea}\n results.append(obj)\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/smallcells', methods=['GET'])\n def get_smallcells():\n allSmallCells = SmallCell.query.order_by(SmallCell.id).all()\n results = []\n for smallcell in allSmallCells:\n results.append(smallcell.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/smallcells/update', methods=['POST'])\n def update_smallcell():\n smallcell_id = request.data.get('id', '')\n site_id = request.data.get('site_id', '')\n smallcell = SmallCell.query.filter_by(id=smallcell_id).first()\n smallcell.site_id = site_id\n smallcell.save()\n return make_response(jsonify({'smallcell_id': smallcell.id,\n 'site_id': smallcell.site_id})), 200\n\n @app.route('/api/sighting/byarea/<areaid>', methods=['GET'])\n def get_sighting(areaid):\n import string\n area = Area.query.filter_by(id=areaid).first()\n if area is None:\n return make_response(jsonify({'list': []})), 200\n sites = []\n for site in Site.get_all():\n if area.contains(site):\n sites.append(str(site.id))\n\n def generate_random_data(num_rows):\n import random\n latitude = 51.51451110408478\n longitude = -0.12620388576521444\n result = []\n for _ in range(num_rows):\n dec_lat = random.random() / 10\n dec_lon = random.random() / 10\n result.append({'lat': latitude + dec_lat, 'lng': longitude +\n dec_lon})\n return result\n results = []\n if len(sites) > 0:\n for row in db.session.execute(\n 'select * from get_gender_crossfilter(ARRAY[' + ','.join(\n sites) + '])'):\n results.append({'geos': generate_random_data(5), 'gender':\n row['__gender'], 'age_range': row['__age_range'],\n 'timestamp': row['__sighting_date'], 'count': row[\n '__count']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting/getgender/', methods=['POST'])\n def get_gender():\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n import string\n results = []\n for row in db.session.execute('select * from get_gender(ARRAY[' +\n site_ids + '],' + \"'\" + from_sighting_date + \"'\" + ',' + \"'\" +\n to_sighting_date + \"'\" + ')'):\n results.append({'site_id': row['__site_id'], 'date_month': row[\n '__date_month'], 'gender': row['__gender'], 'age_range':\n row['__age_range'], 'perc_visits': row['__perc_visits'],\n 'scaled_visits': row['__scaled_visits']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting/getgendertotals/', methods=['POST'])\n def get_gender_age_totals():\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n import string\n results = []\n for row in db.session.execute(\n 'select * from get_gender_age_totals(ARRAY[' + site_ids + '],' +\n \"'\" + from_sighting_date + \"'\" + ',' + \"'\" + to_sighting_date +\n \"'\" + ')'):\n results.append({'site_id': row['__site_id'], 'gender': row[\n '__gender'], 'age_range': row['__age_range'], '__visits':\n row['__visits']})\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sighting', methods=['GET'])\n def get_sightings():\n results = []\n for sighting in LTESighting.get_all():\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/sitescomparison', methods=['POST'])\n def get_sitescomparison():\n sightings = LTESighting.query.filter(LTESighting.smallcell.has(\n SmallCell.site_id.in_(request.data['selectedRow']))).filter(\n LTESighting.timestamp.between(request.data['selectedDates'][0],\n request.data['selectedDates'][1]))\n return make_response(jsonify({'list': [sighting.serialise() for\n sighting in sightings]})), 200\n\n @app.route('/api/sighting/bysite', methods=['GET'])\n def get_sightings_by_site():\n site_ids = request.args.getlist('site_id')\n results = []\n for sighting in LTESighting.query:\n if str(sighting.smallcell.site_id) in site_ids:\n results.append(sighting.serialise())\n return make_response(jsonify({'list': results})), 200\n\n @app.route('/api/origindestination/all', methods=['GET'])\n def get_all():\n journeys = Journey.query.all()\n thing = {}\n for journey in journeys:\n if journey.origin_id not in thing:\n thing[journey.origin_id] = {}\n if journey.destination_id not in thing[journey.origin_id\n ] and journey.destination_id != journey.origin_id:\n thing[journey.origin_id][journey.destination_id\n ] = journey.data['total']\n return make_response(jsonify(thing)), 200\n\n @app.route('/api/origindestination/<origin_id>', methods=['GET'])\n def get_od(origin_id):\n journeys = Journey.query.all()\n _j = []\n for journey in journeys:\n _j.append({'origin_id': journey.origin_id, 'destination_id':\n journey.destination_id, 'total': journey.data['total']})\n return make_response(jsonify({'list': _j})), 200\n\n @app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>',\n methods=['GET'])\n def purchase(home_district_name, type_visitor):\n days_sql = db.session.query(PurchDistrict.start_dow, func.count(\n PurchDistrict.start_dow)).group_by(PurchDistrict.start_dow).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).order_by(func.\n count(PurchDistrict.start_dow).desc()).all()\n gender_sql = db.session.query(PurchDistrict.gender, func.count(\n PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, func.count(PurchDistrict.gender)).group_by(\n PurchDistrict.gender, PurchDistrict.age).filter(PurchDistrict.\n gender.isnot(None)).filter(PurchDistrict.age.isnot(None)).filter(\n PurchDistrict.home_district_name.in_([home_district_name])).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_rent_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict\n .gender)).group_by(PurchDistrict.gender, PurchDistrict.age,\n PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)\n ).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.\n type_visitor.in_([type_visitor])).all()\n days_total = sum(i[1] for i in days_sql)\n gender_total = sum(i[1] for i in gender_sql)\n gender_age_total = sum(i[2] for i in gender_age_sql)\n days_results = []\n for result in days_sql:\n days_results.append({'start_dow': result.start_dow, 'count':\n result[1], 'percent': float(result[1]) / float(days_total),\n 'total': days_total})\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender': result.gender, 'count': result\n [1], 'percent': float(result[1]) / float(gender_total)})\n gender_age_results = []\n for result in gender_age_sql:\n gender_age_results.append({'gender': result.gender, 'age':\n result.age, 'count': result[2], 'percent': float(result[2]) /\n float(gender_age_total)})\n return make_response(jsonify({'days': days_results, 'gender':\n gender_results, 'gender_age': gender_age_results})), 200\n\n @app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=[\n 'GET'])\n def purchase_rent(type_visitor):\n gender_sql = db.session.query(PurchDistrict.gender, func.count(\n PurchDistrict.gender)).group_by(PurchDistrict.gender).filter(\n PurchDistrict.type_visitor.in_([type_visitor])).all()\n gender_age_rent_sql = db.session.query(PurchDistrict.gender,\n PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict\n .gender)).group_by(PurchDistrict.gender, PurchDistrict.age,\n PurchDistrict.rent).filter(PurchDistrict.gender.isnot(None)\n ).filter(PurchDistrict.age.isnot(None)).filter(PurchDistrict.\n type_visitor.in_([type_visitor])).all()\n gender_total = sum(i[1] for i in gender_sql)\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender': result.gender, 'count': result\n [1], 'percent': float(result[1]) / float(gender_total)})\n gender_age_rent_results = []\n for result in gender_age_rent_sql:\n gender_age_rent_results.append({'gender': result.gender, 'age':\n result.age, 'rent': result.rent, 'count': result[3]})\n return make_response(jsonify({'gender': gender_results,\n 'gender_age_rent': gender_age_rent_results})), 200\n\n @app.route('/api/ng_event/districts', methods=['GET'])\n def districts():\n home_results = []\n for result in db.session.query(ZoneDistrict.home_district_code,\n ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)\n ).group_by(ZoneDistrict.home_district_code, ZoneDistrict.\n home_district_name).all():\n home_results.append({'district_code': result.home_district_code,\n 'district_name': result.home_district_name, 'visitors':\n result[2]})\n work_results = []\n for result in db.session.query(ZoneDistrict.work_district_code,\n ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)\n ).group_by(ZoneDistrict.work_district_code, ZoneDistrict.\n work_district_name).all():\n work_results.append({'district_code': result.work_district_code,\n 'district_name': result.work_district_name, 'visitors':\n result[2]})\n return make_response(jsonify({'work': {'list': work_results},\n 'home': {'list': home_results}})), 200\n\n @app.route('/api/ng_event/attractiontotals', methods=['GET'])\n def attractiontotals():\n results = []\n for result in db.session.query(AttractionTotal.zone_visitors,\n AttractionTotal.num_visitors).all():\n results.append({'zone_visitors': result.zone_visitors,\n 'num_visitors': result.num_visitors})\n return make_response(jsonify({'totals': {'list': results}})), 200\n\n @app.route('/api/ng_event/profiles', methods=['GET'])\n def profiles():\n results = []\n for result in db.session.query(Profile.country, Profile.nationality,\n Profile.name_province, Profile.gender, Profile.age, Profile.\n rent, Profile.type_visitor, Profile.date, Profile.day, Profile.\n period, Profile.name_tur_zone).limit(10000):\n district = ''\n if result.name_tur_zone == 'Zone 1':\n district = 'Chamartin'\n if result.name_tur_zone == 'Zone 2':\n district = 'Chamberi'\n if result.name_tur_zone == 'Zone 3':\n district = 'Salamanca'\n day = ''\n if result.day == 'Monday':\n day = 'Mon'\n if result.day == 'Tuesday':\n day = 'Tue'\n if result.day == 'Wednesday':\n day = 'Wed'\n if result.day == 'Thursday':\n day = 'Thu'\n if result.day == 'Friday':\n day = 'Fri'\n if result.day == 'Saturday':\n day = 'Sat'\n if result.day == 'Sunday':\n day = 'Sun'\n results.append({'country': result.country, 'nationality':\n result.nationality, 'name_province': district, 'gender':\n result.gender, 'age': result.age, 'rent': result.rent,\n 'type_visitor': result.type_visitor, 'date': result.date,\n 'day': day, 'period': result.period, 'zone': result.\n name_tur_zone})\n return make_response(jsonify(results)), 200\n\n @app.route('/api/ng_event/dowfreq', methods=['GET'])\n def dowfreq():\n results = []\n for result in db.session.query(DOWFrequency.type_visitor,\n DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count\n ).all():\n results.append({'type_visitor': result.type_visitor,\n 'start_dow': result.start_dow, 'start_hour': result.\n start_hour, 'count': result.count})\n return make_response(jsonify(results)), 200\n return app\n",
"step-5": "# app/__init__.py\nimport json\nfrom flask_api import FlaskAPI, status\nimport graphene\nfrom graphene import relay\nfrom graphene_sqlalchemy import SQLAlchemyConnectionField, SQLAlchemyObjectType\nfrom flask_sqlalchemy import SQLAlchemy\nfrom sqlalchemy import func\nfrom flask import request, jsonify, abort, make_response\n\nfrom flask_graphql import GraphQLView\n\nfrom shapely.geometry import shape, Point\n\n# local import\n\nfrom instance.config import app_config\n\n# For password hashing\nfrom flask_bcrypt import Bcrypt\n\n# initialize db\ndb = SQLAlchemy()\n\nfrom app.models import Date, Area, LTESighting, SmallCell, Site, SightingsPerHourPerCountry, SightingsNew, SightingsBase, WideSighting, Journey\nfrom app.models import Department as DepartmentModel\nfrom app.ng_event_models import ZoneDistrict, AttractionTotal, Profile, PurchDistrict, DOWFrequency\n\nclass Department(SQLAlchemyObjectType):\n\n class Meta:\n model = DepartmentModel\n interfaces = (relay.Node, )\n\nclass Query(graphene.ObjectType):\n node = relay.Node.Field()\n all_employees = SQLAlchemyConnectionField(Department)\n\ndef create_app(config_name):\n\n app = FlaskAPI(__name__, instance_relative_config=True)\n # overriding Werkzeugs built-in password hashing utilities using Bcrypt.\n bcrypt = Bcrypt(app)\n\n schema = graphene.Schema(query=Query)\n\n app.add_url_rule('/graphql', view_func=GraphQLView.as_view('graphql', schema=schema, graphiql=True))\n\n app.config.from_object(app_config[config_name])\n app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False\n db.init_app(app)\n\n @app.route('/api/areas/create', methods=['POST'])\n def create_areas():\n # get the access token\n\n name = request.data.get('name', '')\n geodata = request.data.get('geodata', '')\n center_lat = request.data.get('center_lat')\n center_lng = request.data.get('center_lng')\n zoom = request.data.get('zoom')\n\n area = Area(name=name, geodata=geodata, center_lat=center_lat, center_lng=center_lng, zoom=zoom)\n area.save()\n response = jsonify({\n 'id': area.id,\n 'name': area.name,\n 'geodata': area.geodata,\n 'center_lat' : area.center_lat,\n 'center_lng' : area.center_lng,\n 'zoom' : area.zoom,\n 'date_created': area.date_created,\n 'date_modified': area.date_modified\n })\n\n return make_response(response), 201\n\n @app.route('/api/areas/delete', methods=['POST'])\n def delete_areas():\n # get the access token\n id = request.data.get('id', 0)\n area = Area.query.filter_by(id=id).first()\n\n if (area is not None):\n area.delete()\n\n return make_response(jsonify({'id':id})), 200\n\n\n @app.route('/api/sightingsperhour', methods=['GET'])\n def get_sightingsperhour():\n # get all the areas\n sightings = SightingsPerHourPerCountry.query.all()\n results = []\n for sighting in sightings:\n results.append({'country' : sighting.country, 'hour' : sighting.hour, 'count' : sighting.count})\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/sightingsnew', methods=['POST'])\n def sightingsnew():\n\n sightings = db.session.query(SightingsBase.site_id, SightingsBase.country, func.count(SightingsBase.roundedtoday))\\\n .filter(SightingsBase.site_id.in_(request.data['selectedRow']))\\\n .filter(SightingsBase.roundedtoday.between(request.data['selectedDates'][0], request.data['selectedDates'][1]))\\\n .group_by(SightingsBase.site_id, SightingsBase.country)\\\n .order_by(SightingsBase.site_id, func.count(SightingsBase.roundedtoday).desc())\\\n\n results = []\n for sighting in sightings.all():\n results.append({'country' : sighting.country, 'site_id' : sighting.site_id, 'count' : sighting[2]})\n\n return make_response(jsonify({ 'list' : results })), 200\n\n\n @app.route('/api/widesightingsnew', methods=['POST', 'GET'])\n def widesightingsnew():\n\n sightings = db.session.query(WideSighting.site_id, WideSighting.gender, func.count(WideSighting.gender))\\\n .filter(WideSighting.site_id.in_([138, 134]))\\\n .group_by(WideSighting.site_id, WideSighting.gender)\n\n results = []\n for sighting in sightings.all():\n #gender = sighting.gender if len(sighting.gender) else 'unknown'\n results.append({'site_id' : sighting.site_id, 'gender' : sighting.gender, 'count' : sighting[2]})\n\n return make_response(jsonify({ 'list' : results })), 200\n\n\n @app.route('/api/widesightings', methods=['GET'])\n def widesightings():\n\n sightings = WideSighting.get_all()\n\n results = []\n for sighting in sightings:\n results.append(sighting.serialise())\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/sites', methods=['GET'])\n def get_sites():\n # get all the areas\n sites = Site.get_all()\n results = []\n for site in sites:\n results.append(site.serialise())\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/dates', methods=['GET'])\n def get_dates():\n # get all the areas\n dates = Date.get_all()\n results = []\n for date in dates:\n results.append(date.serialise())\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/areas', methods=['GET'])\n def get_areas():\n # get all the areas\n areas = Area.get_all()\n allSmallCells = SmallCell.get_all()\n\n results = []\n\n for area in areas:\n\n smallcellInArea = []\n for smallcell in allSmallCells:\n smallcellInArea.append(smallcell.serialise())\n\n obj = {\n 'id': area.id,\n 'name': area.name,\n 'date_created': area.date_created,\n 'date_modified': area.date_modified,\n 'center_lat' : area.center_lat,\n 'center_lng' : area.center_lng,\n 'zoom' : area.zoom,\n 'geodata': area.geodata,\n 'smallcells' : smallcellInArea\n }\n results.append(obj)\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/smallcells', methods=['GET'])\n def get_smallcells():\n allSmallCells = SmallCell.query.order_by(SmallCell.id).all()\n\n results = []\n for smallcell in allSmallCells:\n results.append(smallcell.serialise())\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/smallcells/update', methods=['POST'])\n def update_smallcell():\n smallcell_id = request.data.get('id', '')\n site_id = request.data.get('site_id', '')\n\n smallcell = SmallCell.query.filter_by(id=smallcell_id).first()\n smallcell.site_id = site_id\n smallcell.save()\n\n return make_response(jsonify({ 'smallcell_id' : smallcell.id, 'site_id' : smallcell.site_id })), 200\n\n @app.route('/api/sighting/byarea/<areaid>', methods=['GET'])\n def get_sighting(areaid):\n import string\n area = Area.query.filter_by(id=areaid).first()\n if area is None : return make_response(jsonify({ 'list' : [] })), 200\n\n sites = []\n for site in Site.get_all():\n if area.contains(site):\n sites.append(str(site.id))\n\n def generate_random_data(num_rows):\n import random\n latitude = 51.51451110408478\n longitude = -0.12620388576521444\n result = []\n for _ in range(num_rows):\n dec_lat = random.random()/10\n dec_lon = random.random()/10\n result.append({'lat' : latitude + dec_lat, 'lng' : longitude + dec_lon})\n return result\n\n results = []\n if (len(sites) > 0):\n for row in db.session.execute('select * from get_gender_crossfilter(ARRAY[' + ','.join(sites) + '])'):\n\n results.append(({ 'geos': generate_random_data(5), 'gender' : row['__gender'], 'age_range' : row['__age_range'], 'timestamp' : row['__sighting_date'], 'count' : row['__count'] }))\n\n return make_response(jsonify({ 'list' : results })), 200\n\n\n\n @app.route('/api/sighting/getgender/', methods=['POST'])\n def get_gender():\n\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n\n import string\n\n results = []\n\n for row in db.session.execute(\"select * from get_gender(ARRAY[\" + site_ids + \"],\" + \"'\" + from_sighting_date + \"'\" + \",\" + \"'\" + to_sighting_date + \"'\" + \")\"):\n results.append(({ 'site_id' : row['__site_id'], 'date_month' : row['__date_month'], 'gender' : row['__gender'], 'age_range' : row['__age_range'], 'perc_visits' : row['__perc_visits'], 'scaled_visits' : row['__scaled_visits'] }))\n\n return make_response(jsonify({ 'list' : results })), 200\n\n\n @app.route('/api/sighting/getgendertotals/', methods=['POST'])\n def get_gender_age_totals():\n\n site_ids = str(request.data.get('site_ids', ''))\n from_sighting_date = request.data.get('selectedDates')[0]\n to_sighting_date = request.data.get('selectedDates')[1]\n\n import string\n\n results = []\n\n for row in db.session.execute(\"select * from get_gender_age_totals(ARRAY[\" + site_ids + \"],\" + \"'\" + from_sighting_date + \"'\" + \",\" + \"'\" + to_sighting_date + \"'\" + \")\"):\n results.append(({ 'site_id' : row['__site_id'], 'gender' : row['__gender'], 'age_range' : row['__age_range'], '__visits' : row['__visits'] }))\n\n return make_response(jsonify({ 'list' : results })), 200\n\n\n\n @app.route('/api/sighting', methods=['GET'])\n def get_sightings():\n\n results = []\n for sighting in LTESighting.get_all():\n results.append(sighting.serialise())\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/sitescomparison', methods=['POST'])\n def get_sitescomparison():\n\n sightings = LTESighting.query\\\n .filter(LTESighting.smallcell.has(SmallCell.site_id.in_(request.data['selectedRow'])))\\\n .filter(LTESighting.timestamp.between(request.data['selectedDates'][0], request.data['selectedDates'][1]))\n\n return make_response(jsonify({ 'list' : [sighting.serialise() for sighting in sightings] })), 200\n\n @app.route('/api/sighting/bysite', methods=['GET'])\n def get_sightings_by_site():\n\n site_ids = (request.args.getlist('site_id'))\n\n results = []\n #should do this better with joins!\n for sighting in LTESighting.query:\n if (str(sighting.smallcell.site_id)) in site_ids : results.append(sighting.serialise())\n\n return make_response(jsonify({ 'list' : results })), 200\n\n @app.route('/api/origindestination/all', methods=['GET'])\n def get_all():\n journeys = Journey.query.all()\n thing = {}\n for journey in journeys:\n if (journey.origin_id not in thing) :\n thing[journey.origin_id] = {}\n if (journey.destination_id not in thing[journey.origin_id] and journey.destination_id != journey.origin_id) :\n thing[journey.origin_id][journey.destination_id] = journey.data['total']\n\n return make_response(jsonify(thing)), 200\n\n @app.route('/api/origindestination/<origin_id>', methods=['GET'])\n def get_od(origin_id):\n journeys = Journey.query.all()#.filter_by(origin_id=origin_id).all()\n _j = []\n for journey in journeys:\n _j.append({'origin_id' : journey.origin_id, 'destination_id' : journey.destination_id, 'total' : journey.data['total']})\n #_j.append({'origin_id' : journey.origin_id, 'data' : (journey.data)})\n\n return make_response(jsonify({ 'list' : _j })), 200\n\n @app.route('/api/ng_event/purchase/<home_district_name>/<type_visitor>', methods=['GET'])\n def purchase(home_district_name, type_visitor):\n\n days_sql = db.session.query(PurchDistrict.start_dow, func.count(PurchDistrict.start_dow))\\\n .group_by(PurchDistrict.start_dow)\\\n .filter(PurchDistrict.home_district_name.in_([home_district_name]))\\\n .filter(PurchDistrict.type_visitor.in_([type_visitor]))\\\n .order_by(func.count(PurchDistrict.start_dow).desc())\\\n .all()\n\n gender_sql = db.session.query(PurchDistrict.gender, func.count(PurchDistrict.gender))\\\n .group_by(PurchDistrict.gender)\\\n .filter(PurchDistrict.home_district_name.in_([home_district_name]))\\\n .filter(PurchDistrict.type_visitor.in_([type_visitor])).all()\n\n gender_age_sql = db.session.query(PurchDistrict.gender, PurchDistrict.age, func.count(PurchDistrict.gender))\\\n .group_by(PurchDistrict.gender, PurchDistrict.age)\\\n .filter(PurchDistrict.gender.isnot(None))\\\n .filter(PurchDistrict.age.isnot(None))\\\n .filter(PurchDistrict.home_district_name.in_([home_district_name]))\\\n .filter(PurchDistrict.type_visitor.in_([type_visitor])).all()\n\n\n gender_age_rent_sql = db.session.query(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict.gender))\\\n .group_by(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent)\\\n .filter(PurchDistrict.gender.isnot(None))\\\n .filter(PurchDistrict.age.isnot(None))\\\n .filter(PurchDistrict.type_visitor.in_([type_visitor])).all()\n\n days_total = sum(i[1] for i in days_sql)\n gender_total = sum(i[1] for i in gender_sql)\n gender_age_total = sum(i[2] for i in gender_age_sql)\n\n days_results = []\n for result in days_sql:\n days_results.append({ 'start_dow' : result.start_dow, 'count' : result[1], 'percent' : float(result[1])/float(days_total), 'total' : days_total})\n\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender' : result.gender, 'count' : result[1], 'percent' : float(result[1])/float(gender_total)})\n\n gender_age_results = []\n for result in gender_age_sql:\n gender_age_results.append({'gender' : result.gender, 'age' : result.age, 'count' : result[2], 'percent' : float(result[2])/float(gender_age_total)})\n\n return make_response(jsonify({'days' : days_results, 'gender' : gender_results, 'gender_age' : gender_age_results})), 200\n\n\n @app.route('/api/ng_event/purchase_affluence/<type_visitor>', methods=['GET'])\n def purchase_rent(type_visitor):\n\n gender_sql = db.session.query(PurchDistrict.gender, func.count(PurchDistrict.gender))\\\n .group_by(PurchDistrict.gender)\\\n .filter(PurchDistrict.type_visitor.in_([type_visitor])).all()\n\n gender_age_rent_sql = db.session.query(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent, func.count(PurchDistrict.gender))\\\n .group_by(PurchDistrict.gender, PurchDistrict.age, PurchDistrict.rent)\\\n .filter(PurchDistrict.gender.isnot(None))\\\n .filter(PurchDistrict.age.isnot(None))\\\n .filter(PurchDistrict.type_visitor.in_([type_visitor])).all()\n\n gender_total = sum(i[1] for i in gender_sql)\n\n gender_results = []\n for result in gender_sql:\n gender_results.append({'gender' : result.gender, 'count' : result[1], 'percent' : float(result[1])/float(gender_total)})\n\n gender_age_rent_results = []\n for result in gender_age_rent_sql:\n gender_age_rent_results.append({'gender' : result.gender, 'age' : result.age, 'rent' : result.rent, 'count' : result[3]})\n\n return make_response(jsonify({'gender' : gender_results, 'gender_age_rent' : gender_age_rent_results})), 200\n\n\n @app.route('/api/ng_event/districts', methods=['GET'])\n def districts():\n\n home_results = []\n for result in db.session.query(ZoneDistrict.home_district_code, ZoneDistrict.home_district_name, func.sum(ZoneDistrict.visitors)).group_by(ZoneDistrict.home_district_code, ZoneDistrict.home_district_name).all():\n home_results.append({'district_code' : result.home_district_code, 'district_name' : result.home_district_name, 'visitors' : result[2]})\n\n work_results = []\n for result in db.session.query(ZoneDistrict.work_district_code, ZoneDistrict.work_district_name, func.sum(ZoneDistrict.visitors)).group_by(ZoneDistrict.work_district_code, ZoneDistrict.work_district_name).all():\n work_results.append({'district_code' : result.work_district_code, 'district_name' : result.work_district_name, 'visitors' : result[2]})\n\n return make_response(jsonify({'work' : { 'list' : work_results }, 'home' : { 'list' : home_results }})), 200\n\n\n @app.route('/api/ng_event/attractiontotals', methods=['GET'])\n def attractiontotals():\n\n results = []\n for result in db.session.query(AttractionTotal.zone_visitors, AttractionTotal.num_visitors).all():\n results.append({'zone_visitors' : result.zone_visitors, 'num_visitors' : result.num_visitors})\n\n return make_response(jsonify({'totals' : { 'list' : results }})), 200\n\n\n @app.route('/api/ng_event/profiles', methods=['GET'])\n def profiles():\n\n results = []\n for result in db.session.query(Profile.country, Profile.nationality, Profile.name_province, Profile.gender, Profile.age, Profile.rent, Profile.type_visitor, Profile.date, Profile.day, Profile.period, Profile.name_tur_zone).limit(10000):\n district = ''\n if result.name_tur_zone == 'Zone 1' : district = 'Chamartin'\n if result.name_tur_zone == 'Zone 2' : district = 'Chamberi'\n if result.name_tur_zone == 'Zone 3' : district = 'Salamanca'\n\n day = ''\n if result.day == 'Monday' : day = 'Mon'\n if result.day == 'Tuesday' : day = 'Tue'\n if result.day == 'Wednesday' : day = 'Wed'\n if result.day == 'Thursday' : day = 'Thu'\n if result.day == 'Friday' : day = 'Fri'\n if result.day == 'Saturday' : day = 'Sat'\n if result.day == 'Sunday' : day = 'Sun'\n\n results.append({'country' : result.country, 'nationality' : result.nationality, 'name_province' : district, 'gender' : result.gender, 'age' : result.age, 'rent' : result.rent, 'type_visitor' : result.type_visitor, 'date' : result.date, 'day' : day, 'period' : result.period, 'zone' : result.name_tur_zone })\n\n return make_response(jsonify(results)), 200\n\n @app.route('/api/ng_event/dowfreq', methods=['GET'])\n def dowfreq():\n\n results = []\n for result in db.session.query(DOWFrequency.type_visitor, DOWFrequency.start_dow, DOWFrequency.start_hour, DOWFrequency.count).all():\n results.append({'type_visitor' : result.type_visitor, 'start_dow' : result.start_dow, 'start_hour' : result.start_hour, 'count' : result.count })\n\n return make_response(jsonify(results)), 200\n\n return app\n",
"step-ids": [
3,
4,
5,
6,
7
]
}
|
[
3,
4,
5,
6,
7
] |
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 15 10:39:55 2019
@author: PC
"""
import pandas as pd
dictionary={"Name":["Ali","Buse","Selma","Hakan","Bülent","Yağmur","Ahmet"],
"Age":[18,45,12,36,40,18,63],
"Maas":[100,200,400,500,740,963,123]}
dataFrame1=pd.DataFrame(dictionary) #excel gibi tablo oluşturur
head=dataFrame1.head() ##ilk 5 indisi verir
tail=dataFrame1.tail()
print(dataFrame1.columns)
print(dataFrame1.info())
print(dataFrame1.dtypes)
print(dataFrame1.describe())
|
normal
|
{
"blob_id": "efa94f8442c9f43234d56a781d2412c9f7ab1bb3",
"index": 7910,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(dataFrame1.columns)\nprint(dataFrame1.info())\nprint(dataFrame1.dtypes)\nprint(dataFrame1.describe())\n",
"step-3": "<mask token>\ndictionary = {'Name': ['Ali', 'Buse', 'Selma', 'Hakan', 'Bülent', 'Yağmur',\n 'Ahmet'], 'Age': [18, 45, 12, 36, 40, 18, 63], 'Maas': [100, 200, 400, \n 500, 740, 963, 123]}\ndataFrame1 = pd.DataFrame(dictionary)\nhead = dataFrame1.head()\ntail = dataFrame1.tail()\nprint(dataFrame1.columns)\nprint(dataFrame1.info())\nprint(dataFrame1.dtypes)\nprint(dataFrame1.describe())\n",
"step-4": "<mask token>\nimport pandas as pd\ndictionary = {'Name': ['Ali', 'Buse', 'Selma', 'Hakan', 'Bülent', 'Yağmur',\n 'Ahmet'], 'Age': [18, 45, 12, 36, 40, 18, 63], 'Maas': [100, 200, 400, \n 500, 740, 963, 123]}\ndataFrame1 = pd.DataFrame(dictionary)\nhead = dataFrame1.head()\ntail = dataFrame1.tail()\nprint(dataFrame1.columns)\nprint(dataFrame1.info())\nprint(dataFrame1.dtypes)\nprint(dataFrame1.describe())\n",
"step-5": "# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Fri Nov 15 10:39:55 2019\r\n\r\n@author: PC\r\n\"\"\"\r\n\r\nimport pandas as pd\r\ndictionary={\"Name\":[\"Ali\",\"Buse\",\"Selma\",\"Hakan\",\"Bülent\",\"Yağmur\",\"Ahmet\"],\r\n \"Age\":[18,45,12,36,40,18,63],\r\n \"Maas\":[100,200,400,500,740,963,123]}\r\n\r\ndataFrame1=pd.DataFrame(dictionary) #excel gibi tablo oluşturur\r\nhead=dataFrame1.head() ##ilk 5 indisi verir\r\n\r\ntail=dataFrame1.tail()\r\n\r\nprint(dataFrame1.columns)\r\n\r\nprint(dataFrame1.info())\r\n\r\nprint(dataFrame1.dtypes)\r\n\r\nprint(dataFrame1.describe())",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import json
import os
import sys
"""
Course: cmps 4883
Assignemt: A03
Date: 2/10/19
Github username: acdczlc
Repo url: https://github.com/acdczlc/4883-SWTools-Conley
Name: Zac Conley
Description:
Calculates all stats for questions about stats
"""
##############################################################
# MostTeams(dict of off and def players)
# gets player who played for most teams
#
# Params:
# dict of players
# Returns:
# player with most teams
def MostTeams(OffAndDef):
most=[]
count=0 # set comparison
for playerid, playerdata in OffAndDef.items():
if(playerdata['name']!=''): #only get real players
if(len(playerdata['Teams'])>count):
count=len(playerdata['Teams']) #get count
most=[[playerdata['name'],len(playerdata['Teams'])]] # replace with player
elif(len(playerdata['Teams'])==count):
most.append([playerdata['name'],len(playerdata['Teams'])]) # add multiple teams
return most
##############################################################
# MostTeamsOneYear(dict of off and def players)
# gets player who played for most teams in one year
#
# Params:
# dict of players
# Returns:
# player with most teams
def MostTeamsOneYear(OffAndDef):
teams={}
maximum={}
count=0
for playerid, playerdata in OffAndDef.items():
if(playerdata['name']!=''):
for years in playerdata: #avoids all keys except years
if(years!='Drops' and years!='NegRushYards' and years!='NegRush' and years!='Teams' and years!='PassForLoss' and years!="name"):
try: #try block to avoid nonplayers
if(len(playerdata[years])>count): # if player has most teams so far
if((len(playerdata[years]) not in teams.keys())):
teams.clear() # delete all previous players
teams[len(playerdata[years])]={}
teams[len(playerdata[years])][playerdata['name']]=years
count=len(playerdata[years])
elif(len(playerdata[years])==count): #multiple players have the same number of teams
teams[len(playerdata[years])].append(playerdata['name'],years)
except:
pass
return teams
##############################################################
# NegativeRushingYards(dict of off and def players)
# gets player with most negative rushing yards
#
# Params:
# dict of players
# Returns:
# player with most negative rushing yards
def NegativeRushingYards(OffAndDef):
NegRushYds=[]
yds=0
for playerid, playerdata in OffAndDef.items():
if(playerdata['NegRushYards']<yds):
yds=playerdata['NegRushYards']
NegRushYds=[[playerdata['name'],playerdata['NegRushYards']]]
elif(playerdata['NegRushYards']==yds):
NegRushYds.append([playerdata['name'],playerdata['NegRushYards']])
return NegRushYds
##############################################################
# NegativeRushes(dict of off and def players)
# gets player with most negative rushes
#
# Params:
# dict of players
# Returns:
# player with most negative rushes
def NegativeRushes(OffAndDef):
rushes=[]
att=0 #attempts
for player in OffAndDef:
if(OffAndDef[player]['NegRush']>att):
att=OffAndDef[player]['NegRush']
rushes=[[OffAndDef[player]['name'],OffAndDef[player]['NegRush']]]
elif(OffAndDef[player]['NegRush']==att):
rushes.append([OffAndDef[player]['name'],OffAndDef[player]['NegRush']])
return rushes
##############################################################
# MostPassForLoss(dict of off and def players)
# gets player with most negative rushes
#
# Params:
# dict of players
# Returns:
# player with most negative rushes
def MostPassForLoss(OffAndDef):
PassForLoss=[]
att=0 #attempts
for player in OffAndDef:
if(OffAndDef[player]['PassForLoss']>att):
att=OffAndDef[player]['PassForLoss']
PassForLoss=[[OffAndDef[player]['name'],OffAndDef[player]['PassForLoss']]]
elif(OffAndDef[player]['PassForLoss']==att):
PassForLoss.append([OffAndDef[player]['name'],OffAndDef[player]['PassForLoss']])
return PassForLoss
##############################################################
# MostPenalties(dict of team penalties)
# gets team with most penalties
#
# Params:
# dict of teams
# Returns:
# player with most negative rushes
def MostPenalties(penalties):
pens=[]
num=0
for teamname,teamdata in penalties.items():
if(teamdata['Penalties']>num):
num=teamdata['Penalties']
pens=[[teamname,teamdata['Penalties']]]
elif (teamdata['Penalties']==num):
pens.append([teamname,teamdata['Penalties']])
return pens
##############################################################
# TeamPenaltyYards(dict of team penalties)
# gets team with most penaltiy yards
#
# Params:
# dict of teams
# Returns:
# team with most penalty yards
def TeamPenaltyYards(penalties):
pens=[]
num=0
for teamname,teamdata in penalties.items():
if(teamdata['PenaltyYards']>num):
num=teamdata['PenaltyYards']
pens=[[teamname,teamdata['PenaltyYards']]]
elif (teamdata['PenaltyYards']==num):
pens.append([teamname,teamdata['PenaltyYards']])
return pens
##############################################################
# PenaltyWins(most penalized team,dict of team penalties)
# shows correlation between penalty and record
#
# Params:
# dict of teams, most penalized team
# Returns:
# team with most penaltys and least
def PenaltyWins(penalties):
x=MostPenalties(penalties) #calls function to get most penalized team
mostPenalized=[]
for temp in x:
mostPenalized.append(team[0])
least=penalties[mostPenalized[0]]['Penalties']
mostandleast=[[mostPenalized[0],penalties[mostPenalized[0]]['Wins'],penalties[mostPenalized[0]]['Losses']]] # sets most penalized record
leastTeam=[]
for teamname, teamdata in penalties.items():
if(teamdata['Penalties']<least):
least=teamdata['Penalties']
leastTeam=[[teamname,teamdata['Wins'],teamdata['Losses']]]
elif (teamdata['Penalties']==least):
leastTeam.append([teamname,teamdata['Wins'],teamdata['Losses']])
mostandleast.append(leastTeam[0]) #adds team and record to list at end
return mostandleast
##############################################################
# AverageNumberOfPlays()
# shows average number of plays
#
# Params:
# none
# Returns:
# avg number of plays
def AverageNumberOfPlays():
games=0
plays=0
for filename in os.listdir(os.path.dirname(os.path.abspath(__file__))+'/stats'): # sets path to all stats
with open(os.path.dirname(os.path.abspath(__file__))+"/stats/"+filename,"r") as json_file:
try: #gets all stats and stores each game in a dict
data=json.load(json_file)
except:
pass
else:
for gameid, gamedata in data.items():
if(gameid!="nextupdate"):
games+=1 #increment number of games
for driveid, drivedata in gamedata['drives'].items():
if(driveid!="crntdrv"):
plays+=drivedata['numplays'] #increment number of plays
avgplays=plays/games
return avgplays
##############################################################
# LongestFG(dict of fgs)
# longest field goal
#
# Params:
# dict of fgs
# Returns:
# longest field goal and kicker
def LongestFG(fg):
fgs=[]
length=0 #longest fg
for playerid,playerdata in fg.items():
if(playerdata['Long']>length):
length=playerdata['Long']
fgs=[[playerdata['Name'],playerdata['Long']]]
elif (playerdata['Long']==length):
fgs.append([playerdata['Name'],playerdata['Long']])
return fgs
##############################################################
# MostFG(dict of fgs)
# most made field goals
#
# Params:
# dict of fgs
# Returns:
# most made field goals and kicker
def MostFG(fg):
fgs=[]
count=0 #sets counter to 0
for playerid,playerdata in fg.items():
if(playerdata['FG']>count): #if largest number of fg so far
count=playerdata['FG']
fgs=[[playerdata['Name'],playerdata['FG']]]
elif (playerdata['FG']==count): #if same number of fg
fgs.append([playerdata['Name'],playerdata['FG']])
return fgs
##############################################################
# MostMFG(dict of fgs)
# most missed field goals
#
# Params:
# dict of fgs
# Returns:
# most missed field goals and kicker
def MostMFG(fg):
fgs=[]
count=0 #set counter to 0
for playerid,playerdata in fg.items():
if(playerdata['MFG']>count): #if most misses so far
count=playerdata['MFG']
fgs=[[playerdata['Name'],playerdata['MFG']]]
elif (playerdata['MFG']==count): #if same as most misses
fgs.append([playerdata['Name'],playerdata['MFG']])
return fgs
##############################################################
# MostDrops(dict of players)
# most drops
#
# Params:
# dict of players
# Returns:
# most drops
def MostDrops(OffAndDef):
drops=[]
count=0 #set drops to 0
for player in OffAndDef:
if(OffAndDef[player]['Drops']>count):
count=OffAndDef[player]['Drops']
drops=[[OffAndDef[player]['name'],OffAndDef[player]['Drops']]]
elif(OffAndDef[player]['Drops']==count):
drops.append([OffAndDef[player]['name'],OffAndDef[player]['Drops']])
return drops
path= os.path.dirname(os.path.abspath(__file__)) #set path to current location
f=open(path+'/OffAndDef.json','r') #open separated files
OffAndDef=json.load(f)
f.close()
f=open(path+'/Penalties.json','r')
penalties=json.load(f)
f.close()
f=open(path+'/FG.json','r')
fg=json.load(f)
f.close()
print("\n")
print("Name: Zac Conley")
print("Assignment: A03 - Nfl Stats")
print("Date: 2/10/19")
print("==================================================================================")
print("Question 1: Find the player(s) that played for the most teams.")
playerlist=MostTeams(OffAndDef)
for p in playerlist:
print(str(p[0]) + ": "+ str(p[1]) +" teams\n")
print("==================================================================================")
print("Question 2: Find the player(s) that played for multiple teams in one year.")
ans=MostTeamsOneYear(OffAndDef)
count=0
for numteams in ans.items():
for player in numteams[1].items():
print(player[1]+": " +player[0]+" "+str(numteams[0])+" teams." )
print
print("==================================================================================")
print("Question 3: Find the player(s) that had the most yards rushed for a loss.")
ans=NegativeRushingYards(OffAndDef)
for player in ans:
print(player[0]+": "+str(player[1])+" rushing yards.\n")
print("==================================================================================")
print("Question 4: Find the player(s) that had the most rushes for a loss.")
ans=NegativeRushes(OffAndDef)
for player in ans:
print(player[0]+": "+str(player[1])+" negative rushes.\n")
print("==================================================================================")
print("Question 5: Find the player(s) with the most number of passes for a loss.")
ans=MostPassForLoss(OffAndDef)
for player in ans:
print(player[0]+": "+str(player[1])+" negative passes.\n")
temp=[]
print("==================================================================================")
print("Question 6: Find the team with the most penalties.")
ans=MostPenalties(penalties)
for team in ans:
print(str(team[0])+" had "+str(team[1])+" penalties.\n")
print("==================================================================================")
print("Question 7: Find the team with the most yards in penalties.")
ans=TeamPenaltyYards(penalties)
for team in ans:
print(team[0]+": "+str(int(team[1]))+" penalty yards.\n")
print("==================================================================================")
print("Question 8: Find the correlation between most penalized teams and games won / lost.")
ans=PenaltyWins(penalties)
print("Most Penalties: "+ans[0][0]+": "+str(ans[0][1]) +"-" +str(ans[0][2]))
print("Least Penalties: "+ans[1][0]+" : "+str(ans[1][1])+"-" +str(ans[1][2])+"\n")
print("==================================================================================")
print("Question 9: Average number of plays in a game. (This may take up to a minute.)")
ans=AverageNumberOfPlays()
print("On average, there are " +str(ans) +" plays each game. \n")
print("==================================================================================")
print("Question 10: Longest field goal.")
ans=LongestFG(fg)
for player in ans:
print(player[0]+": "+str(player[1])+" yards.\n")
print("==================================================================================")
print("Question 11: Most field goals.")
ans=MostFG(fg)
for player in ans:
print(player[0]+": "+str(player[1])+" FGs.\n")
print("==================================================================================")
print("Question 12: Most missed field goals.")
ans=MostMFG(fg)
for player in ans:
print(player[0]+": "+str(player[1])+" missed FGs.\n")
print("==================================================================================")
print("Question 13: Most dropped passes.")
ans=MostDrops(OffAndDef)
for player in ans:
print(player[0]+": "+str(player[1])+" drops.")
|
normal
|
{
"blob_id": "2a4f57cd0fc1c50cba06c285849432c6f71f28e2",
"index": 2642,
"step-1": "<mask token>\n\n\ndef MostTeams(OffAndDef):\n most = []\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n if len(playerdata['Teams']) > count:\n count = len(playerdata['Teams'])\n most = [[playerdata['name'], len(playerdata['Teams'])]]\n elif len(playerdata['Teams']) == count:\n most.append([playerdata['name'], len(playerdata['Teams'])])\n return most\n\n\ndef MostTeamsOneYear(OffAndDef):\n teams = {}\n maximum = {}\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n for years in playerdata:\n if (years != 'Drops' and years != 'NegRushYards' and years !=\n 'NegRush' and years != 'Teams' and years !=\n 'PassForLoss' and years != 'name'):\n try:\n if len(playerdata[years]) > count:\n if len(playerdata[years]) not in teams.keys():\n teams.clear()\n teams[len(playerdata[years])] = {}\n teams[len(playerdata[years])][playerdata['name']\n ] = years\n count = len(playerdata[years])\n elif len(playerdata[years]) == count:\n teams[len(playerdata[years])].append(playerdata\n ['name'], years)\n except:\n pass\n return teams\n\n\n<mask token>\n\n\ndef MostPassForLoss(OffAndDef):\n PassForLoss = []\n att = 0\n for player in OffAndDef:\n if OffAndDef[player]['PassForLoss'] > att:\n att = OffAndDef[player]['PassForLoss']\n PassForLoss = [[OffAndDef[player]['name'], OffAndDef[player][\n 'PassForLoss']]]\n elif OffAndDef[player]['PassForLoss'] == att:\n PassForLoss.append([OffAndDef[player]['name'], OffAndDef[player\n ]['PassForLoss']])\n return PassForLoss\n\n\n<mask token>\n\n\ndef TeamPenaltyYards(penalties):\n pens = []\n num = 0\n for teamname, teamdata in penalties.items():\n if teamdata['PenaltyYards'] > num:\n num = teamdata['PenaltyYards']\n pens = [[teamname, teamdata['PenaltyYards']]]\n elif teamdata['PenaltyYards'] == num:\n pens.append([teamname, teamdata['PenaltyYards']])\n return pens\n\n\n<mask token>\n\n\ndef AverageNumberOfPlays():\n games = 0\n plays = 0\n for filename in os.listdir(os.path.dirname(os.path.abspath(__file__)) +\n '/stats'):\n with open(os.path.dirname(os.path.abspath(__file__)) + '/stats/' +\n filename, 'r') as json_file:\n try:\n data = json.load(json_file)\n except:\n pass\n else:\n for gameid, gamedata in data.items():\n if gameid != 'nextupdate':\n games += 1\n for driveid, drivedata in gamedata['drives'].items():\n if driveid != 'crntdrv':\n plays += drivedata['numplays']\n avgplays = plays / games\n return avgplays\n\n\ndef LongestFG(fg):\n fgs = []\n length = 0\n for playerid, playerdata in fg.items():\n if playerdata['Long'] > length:\n length = playerdata['Long']\n fgs = [[playerdata['Name'], playerdata['Long']]]\n elif playerdata['Long'] == length:\n fgs.append([playerdata['Name'], playerdata['Long']])\n return fgs\n\n\ndef MostFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['FG'] > count:\n count = playerdata['FG']\n fgs = [[playerdata['Name'], playerdata['FG']]]\n elif playerdata['FG'] == count:\n fgs.append([playerdata['Name'], playerdata['FG']])\n return fgs\n\n\ndef MostMFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['MFG'] > count:\n count = playerdata['MFG']\n fgs = [[playerdata['Name'], playerdata['MFG']]]\n elif playerdata['MFG'] == count:\n fgs.append([playerdata['Name'], playerdata['MFG']])\n return fgs\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef MostTeams(OffAndDef):\n most = []\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n if len(playerdata['Teams']) > count:\n count = len(playerdata['Teams'])\n most = [[playerdata['name'], len(playerdata['Teams'])]]\n elif len(playerdata['Teams']) == count:\n most.append([playerdata['name'], len(playerdata['Teams'])])\n return most\n\n\ndef MostTeamsOneYear(OffAndDef):\n teams = {}\n maximum = {}\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n for years in playerdata:\n if (years != 'Drops' and years != 'NegRushYards' and years !=\n 'NegRush' and years != 'Teams' and years !=\n 'PassForLoss' and years != 'name'):\n try:\n if len(playerdata[years]) > count:\n if len(playerdata[years]) not in teams.keys():\n teams.clear()\n teams[len(playerdata[years])] = {}\n teams[len(playerdata[years])][playerdata['name']\n ] = years\n count = len(playerdata[years])\n elif len(playerdata[years]) == count:\n teams[len(playerdata[years])].append(playerdata\n ['name'], years)\n except:\n pass\n return teams\n\n\n<mask token>\n\n\ndef MostPassForLoss(OffAndDef):\n PassForLoss = []\n att = 0\n for player in OffAndDef:\n if OffAndDef[player]['PassForLoss'] > att:\n att = OffAndDef[player]['PassForLoss']\n PassForLoss = [[OffAndDef[player]['name'], OffAndDef[player][\n 'PassForLoss']]]\n elif OffAndDef[player]['PassForLoss'] == att:\n PassForLoss.append([OffAndDef[player]['name'], OffAndDef[player\n ]['PassForLoss']])\n return PassForLoss\n\n\n<mask token>\n\n\ndef TeamPenaltyYards(penalties):\n pens = []\n num = 0\n for teamname, teamdata in penalties.items():\n if teamdata['PenaltyYards'] > num:\n num = teamdata['PenaltyYards']\n pens = [[teamname, teamdata['PenaltyYards']]]\n elif teamdata['PenaltyYards'] == num:\n pens.append([teamname, teamdata['PenaltyYards']])\n return pens\n\n\ndef PenaltyWins(penalties):\n x = MostPenalties(penalties)\n mostPenalized = []\n for temp in x:\n mostPenalized.append(team[0])\n least = penalties[mostPenalized[0]]['Penalties']\n mostandleast = [[mostPenalized[0], penalties[mostPenalized[0]]['Wins'],\n penalties[mostPenalized[0]]['Losses']]]\n leastTeam = []\n for teamname, teamdata in penalties.items():\n if teamdata['Penalties'] < least:\n least = teamdata['Penalties']\n leastTeam = [[teamname, teamdata['Wins'], teamdata['Losses']]]\n elif teamdata['Penalties'] == least:\n leastTeam.append([teamname, teamdata['Wins'], teamdata['Losses']])\n mostandleast.append(leastTeam[0])\n return mostandleast\n\n\ndef AverageNumberOfPlays():\n games = 0\n plays = 0\n for filename in os.listdir(os.path.dirname(os.path.abspath(__file__)) +\n '/stats'):\n with open(os.path.dirname(os.path.abspath(__file__)) + '/stats/' +\n filename, 'r') as json_file:\n try:\n data = json.load(json_file)\n except:\n pass\n else:\n for gameid, gamedata in data.items():\n if gameid != 'nextupdate':\n games += 1\n for driveid, drivedata in gamedata['drives'].items():\n if driveid != 'crntdrv':\n plays += drivedata['numplays']\n avgplays = plays / games\n return avgplays\n\n\ndef LongestFG(fg):\n fgs = []\n length = 0\n for playerid, playerdata in fg.items():\n if playerdata['Long'] > length:\n length = playerdata['Long']\n fgs = [[playerdata['Name'], playerdata['Long']]]\n elif playerdata['Long'] == length:\n fgs.append([playerdata['Name'], playerdata['Long']])\n return fgs\n\n\ndef MostFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['FG'] > count:\n count = playerdata['FG']\n fgs = [[playerdata['Name'], playerdata['FG']]]\n elif playerdata['FG'] == count:\n fgs.append([playerdata['Name'], playerdata['FG']])\n return fgs\n\n\ndef MostMFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['MFG'] > count:\n count = playerdata['MFG']\n fgs = [[playerdata['Name'], playerdata['MFG']]]\n elif playerdata['MFG'] == count:\n fgs.append([playerdata['Name'], playerdata['MFG']])\n return fgs\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef MostTeams(OffAndDef):\n most = []\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n if len(playerdata['Teams']) > count:\n count = len(playerdata['Teams'])\n most = [[playerdata['name'], len(playerdata['Teams'])]]\n elif len(playerdata['Teams']) == count:\n most.append([playerdata['name'], len(playerdata['Teams'])])\n return most\n\n\ndef MostTeamsOneYear(OffAndDef):\n teams = {}\n maximum = {}\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n for years in playerdata:\n if (years != 'Drops' and years != 'NegRushYards' and years !=\n 'NegRush' and years != 'Teams' and years !=\n 'PassForLoss' and years != 'name'):\n try:\n if len(playerdata[years]) > count:\n if len(playerdata[years]) not in teams.keys():\n teams.clear()\n teams[len(playerdata[years])] = {}\n teams[len(playerdata[years])][playerdata['name']\n ] = years\n count = len(playerdata[years])\n elif len(playerdata[years]) == count:\n teams[len(playerdata[years])].append(playerdata\n ['name'], years)\n except:\n pass\n return teams\n\n\ndef NegativeRushingYards(OffAndDef):\n NegRushYds = []\n yds = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['NegRushYards'] < yds:\n yds = playerdata['NegRushYards']\n NegRushYds = [[playerdata['name'], playerdata['NegRushYards']]]\n elif playerdata['NegRushYards'] == yds:\n NegRushYds.append([playerdata['name'], playerdata['NegRushYards']])\n return NegRushYds\n\n\n<mask token>\n\n\ndef MostPassForLoss(OffAndDef):\n PassForLoss = []\n att = 0\n for player in OffAndDef:\n if OffAndDef[player]['PassForLoss'] > att:\n att = OffAndDef[player]['PassForLoss']\n PassForLoss = [[OffAndDef[player]['name'], OffAndDef[player][\n 'PassForLoss']]]\n elif OffAndDef[player]['PassForLoss'] == att:\n PassForLoss.append([OffAndDef[player]['name'], OffAndDef[player\n ]['PassForLoss']])\n return PassForLoss\n\n\n<mask token>\n\n\ndef TeamPenaltyYards(penalties):\n pens = []\n num = 0\n for teamname, teamdata in penalties.items():\n if teamdata['PenaltyYards'] > num:\n num = teamdata['PenaltyYards']\n pens = [[teamname, teamdata['PenaltyYards']]]\n elif teamdata['PenaltyYards'] == num:\n pens.append([teamname, teamdata['PenaltyYards']])\n return pens\n\n\ndef PenaltyWins(penalties):\n x = MostPenalties(penalties)\n mostPenalized = []\n for temp in x:\n mostPenalized.append(team[0])\n least = penalties[mostPenalized[0]]['Penalties']\n mostandleast = [[mostPenalized[0], penalties[mostPenalized[0]]['Wins'],\n penalties[mostPenalized[0]]['Losses']]]\n leastTeam = []\n for teamname, teamdata in penalties.items():\n if teamdata['Penalties'] < least:\n least = teamdata['Penalties']\n leastTeam = [[teamname, teamdata['Wins'], teamdata['Losses']]]\n elif teamdata['Penalties'] == least:\n leastTeam.append([teamname, teamdata['Wins'], teamdata['Losses']])\n mostandleast.append(leastTeam[0])\n return mostandleast\n\n\ndef AverageNumberOfPlays():\n games = 0\n plays = 0\n for filename in os.listdir(os.path.dirname(os.path.abspath(__file__)) +\n '/stats'):\n with open(os.path.dirname(os.path.abspath(__file__)) + '/stats/' +\n filename, 'r') as json_file:\n try:\n data = json.load(json_file)\n except:\n pass\n else:\n for gameid, gamedata in data.items():\n if gameid != 'nextupdate':\n games += 1\n for driveid, drivedata in gamedata['drives'].items():\n if driveid != 'crntdrv':\n plays += drivedata['numplays']\n avgplays = plays / games\n return avgplays\n\n\ndef LongestFG(fg):\n fgs = []\n length = 0\n for playerid, playerdata in fg.items():\n if playerdata['Long'] > length:\n length = playerdata['Long']\n fgs = [[playerdata['Name'], playerdata['Long']]]\n elif playerdata['Long'] == length:\n fgs.append([playerdata['Name'], playerdata['Long']])\n return fgs\n\n\ndef MostFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['FG'] > count:\n count = playerdata['FG']\n fgs = [[playerdata['Name'], playerdata['FG']]]\n elif playerdata['FG'] == count:\n fgs.append([playerdata['Name'], playerdata['FG']])\n return fgs\n\n\ndef MostMFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['MFG'] > count:\n count = playerdata['MFG']\n fgs = [[playerdata['Name'], playerdata['MFG']]]\n elif playerdata['MFG'] == count:\n fgs.append([playerdata['Name'], playerdata['MFG']])\n return fgs\n\n\n<mask token>\n",
"step-4": "<mask token>\n\n\ndef MostTeams(OffAndDef):\n most = []\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n if len(playerdata['Teams']) > count:\n count = len(playerdata['Teams'])\n most = [[playerdata['name'], len(playerdata['Teams'])]]\n elif len(playerdata['Teams']) == count:\n most.append([playerdata['name'], len(playerdata['Teams'])])\n return most\n\n\ndef MostTeamsOneYear(OffAndDef):\n teams = {}\n maximum = {}\n count = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['name'] != '':\n for years in playerdata:\n if (years != 'Drops' and years != 'NegRushYards' and years !=\n 'NegRush' and years != 'Teams' and years !=\n 'PassForLoss' and years != 'name'):\n try:\n if len(playerdata[years]) > count:\n if len(playerdata[years]) not in teams.keys():\n teams.clear()\n teams[len(playerdata[years])] = {}\n teams[len(playerdata[years])][playerdata['name']\n ] = years\n count = len(playerdata[years])\n elif len(playerdata[years]) == count:\n teams[len(playerdata[years])].append(playerdata\n ['name'], years)\n except:\n pass\n return teams\n\n\ndef NegativeRushingYards(OffAndDef):\n NegRushYds = []\n yds = 0\n for playerid, playerdata in OffAndDef.items():\n if playerdata['NegRushYards'] < yds:\n yds = playerdata['NegRushYards']\n NegRushYds = [[playerdata['name'], playerdata['NegRushYards']]]\n elif playerdata['NegRushYards'] == yds:\n NegRushYds.append([playerdata['name'], playerdata['NegRushYards']])\n return NegRushYds\n\n\ndef NegativeRushes(OffAndDef):\n rushes = []\n att = 0\n for player in OffAndDef:\n if OffAndDef[player]['NegRush'] > att:\n att = OffAndDef[player]['NegRush']\n rushes = [[OffAndDef[player]['name'], OffAndDef[player]['NegRush']]\n ]\n elif OffAndDef[player]['NegRush'] == att:\n rushes.append([OffAndDef[player]['name'], OffAndDef[player][\n 'NegRush']])\n return rushes\n\n\ndef MostPassForLoss(OffAndDef):\n PassForLoss = []\n att = 0\n for player in OffAndDef:\n if OffAndDef[player]['PassForLoss'] > att:\n att = OffAndDef[player]['PassForLoss']\n PassForLoss = [[OffAndDef[player]['name'], OffAndDef[player][\n 'PassForLoss']]]\n elif OffAndDef[player]['PassForLoss'] == att:\n PassForLoss.append([OffAndDef[player]['name'], OffAndDef[player\n ]['PassForLoss']])\n return PassForLoss\n\n\ndef MostPenalties(penalties):\n pens = []\n num = 0\n for teamname, teamdata in penalties.items():\n if teamdata['Penalties'] > num:\n num = teamdata['Penalties']\n pens = [[teamname, teamdata['Penalties']]]\n elif teamdata['Penalties'] == num:\n pens.append([teamname, teamdata['Penalties']])\n return pens\n\n\ndef TeamPenaltyYards(penalties):\n pens = []\n num = 0\n for teamname, teamdata in penalties.items():\n if teamdata['PenaltyYards'] > num:\n num = teamdata['PenaltyYards']\n pens = [[teamname, teamdata['PenaltyYards']]]\n elif teamdata['PenaltyYards'] == num:\n pens.append([teamname, teamdata['PenaltyYards']])\n return pens\n\n\ndef PenaltyWins(penalties):\n x = MostPenalties(penalties)\n mostPenalized = []\n for temp in x:\n mostPenalized.append(team[0])\n least = penalties[mostPenalized[0]]['Penalties']\n mostandleast = [[mostPenalized[0], penalties[mostPenalized[0]]['Wins'],\n penalties[mostPenalized[0]]['Losses']]]\n leastTeam = []\n for teamname, teamdata in penalties.items():\n if teamdata['Penalties'] < least:\n least = teamdata['Penalties']\n leastTeam = [[teamname, teamdata['Wins'], teamdata['Losses']]]\n elif teamdata['Penalties'] == least:\n leastTeam.append([teamname, teamdata['Wins'], teamdata['Losses']])\n mostandleast.append(leastTeam[0])\n return mostandleast\n\n\ndef AverageNumberOfPlays():\n games = 0\n plays = 0\n for filename in os.listdir(os.path.dirname(os.path.abspath(__file__)) +\n '/stats'):\n with open(os.path.dirname(os.path.abspath(__file__)) + '/stats/' +\n filename, 'r') as json_file:\n try:\n data = json.load(json_file)\n except:\n pass\n else:\n for gameid, gamedata in data.items():\n if gameid != 'nextupdate':\n games += 1\n for driveid, drivedata in gamedata['drives'].items():\n if driveid != 'crntdrv':\n plays += drivedata['numplays']\n avgplays = plays / games\n return avgplays\n\n\ndef LongestFG(fg):\n fgs = []\n length = 0\n for playerid, playerdata in fg.items():\n if playerdata['Long'] > length:\n length = playerdata['Long']\n fgs = [[playerdata['Name'], playerdata['Long']]]\n elif playerdata['Long'] == length:\n fgs.append([playerdata['Name'], playerdata['Long']])\n return fgs\n\n\ndef MostFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['FG'] > count:\n count = playerdata['FG']\n fgs = [[playerdata['Name'], playerdata['FG']]]\n elif playerdata['FG'] == count:\n fgs.append([playerdata['Name'], playerdata['FG']])\n return fgs\n\n\ndef MostMFG(fg):\n fgs = []\n count = 0\n for playerid, playerdata in fg.items():\n if playerdata['MFG'] > count:\n count = playerdata['MFG']\n fgs = [[playerdata['Name'], playerdata['MFG']]]\n elif playerdata['MFG'] == count:\n fgs.append([playerdata['Name'], playerdata['MFG']])\n return fgs\n\n\ndef MostDrops(OffAndDef):\n drops = []\n count = 0\n for player in OffAndDef:\n if OffAndDef[player]['Drops'] > count:\n count = OffAndDef[player]['Drops']\n drops = [[OffAndDef[player]['name'], OffAndDef[player]['Drops']]]\n elif OffAndDef[player]['Drops'] == count:\n drops.append([OffAndDef[player]['name'], OffAndDef[player][\n 'Drops']])\n return drops\n\n\npath = os.path.dirname(os.path.abspath(__file__))\nf = open(path + '/OffAndDef.json', 'r')\nOffAndDef = json.load(f)\nf.close()\nf = open(path + '/Penalties.json', 'r')\npenalties = json.load(f)\nf.close()\nf = open(path + '/FG.json', 'r')\nfg = json.load(f)\nf.close()\nprint('\\n')\nprint('Name: Zac Conley')\nprint('Assignment: A03 - Nfl Stats')\nprint('Date: 2/10/19')\nprint(\n '=================================================================================='\n )\nprint('Question 1: Find the player(s) that played for the most teams.')\nplayerlist = MostTeams(OffAndDef)\nfor p in playerlist:\n print(str(p[0]) + ': ' + str(p[1]) + ' teams\\n')\nprint(\n '=================================================================================='\n )\nprint(\n 'Question 2: Find the player(s) that played for multiple teams in one year.'\n )\nans = MostTeamsOneYear(OffAndDef)\ncount = 0\nfor numteams in ans.items():\n for player in numteams[1].items():\n print(player[1] + ': ' + player[0] + ' ' + str(numteams[0]) + ' teams.'\n )\nprint\nprint(\n '=================================================================================='\n )\nprint(\n 'Question 3: Find the player(s) that had the most yards rushed for a loss.'\n )\nans = NegativeRushingYards(OffAndDef)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' rushing yards.\\n')\nprint(\n '=================================================================================='\n )\nprint('Question 4: Find the player(s) that had the most rushes for a loss.')\nans = NegativeRushes(OffAndDef)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' negative rushes.\\n')\nprint(\n '=================================================================================='\n )\nprint(\n 'Question 5: Find the player(s) with the most number of passes for a loss.'\n )\nans = MostPassForLoss(OffAndDef)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' negative passes.\\n')\ntemp = []\nprint(\n '=================================================================================='\n )\nprint('Question 6: Find the team with the most penalties.')\nans = MostPenalties(penalties)\nfor team in ans:\n print(str(team[0]) + ' had ' + str(team[1]) + ' penalties.\\n')\nprint(\n '=================================================================================='\n )\nprint('Question 7: Find the team with the most yards in penalties.')\nans = TeamPenaltyYards(penalties)\nfor team in ans:\n print(team[0] + ': ' + str(int(team[1])) + ' penalty yards.\\n')\nprint(\n '=================================================================================='\n )\nprint(\n 'Question 8: Find the correlation between most penalized teams and games won / lost.'\n )\nans = PenaltyWins(penalties)\nprint('Most Penalties: ' + ans[0][0] + ': ' + str(ans[0][1]) + '-' + str(\n ans[0][2]))\nprint('Least Penalties: ' + ans[1][0] + ' : ' + str(ans[1][1]) + '-' + str(\n ans[1][2]) + '\\n')\nprint(\n '=================================================================================='\n )\nprint(\n 'Question 9: Average number of plays in a game. (This may take up to a minute.)'\n )\nans = AverageNumberOfPlays()\nprint('On average, there are ' + str(ans) + ' plays each game. \\n')\nprint(\n '=================================================================================='\n )\nprint('Question 10: Longest field goal.')\nans = LongestFG(fg)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' yards.\\n')\nprint(\n '=================================================================================='\n )\nprint('Question 11: Most field goals.')\nans = MostFG(fg)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' FGs.\\n')\nprint(\n '=================================================================================='\n )\nprint('Question 12: Most missed field goals.')\nans = MostMFG(fg)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' missed FGs.\\n')\nprint(\n '=================================================================================='\n )\nprint('Question 13: Most dropped passes.')\nans = MostDrops(OffAndDef)\nfor player in ans:\n print(player[0] + ': ' + str(player[1]) + ' drops.')\n",
"step-5": "import json\nimport os\nimport sys\n\"\"\"\nCourse: cmps 4883\nAssignemt: A03\nDate: 2/10/19\nGithub username: acdczlc\nRepo url: https://github.com/acdczlc/4883-SWTools-Conley\nName: Zac Conley\nDescription: \n Calculates all stats for questions about stats\n\n\"\"\"\n##############################################################\n# MostTeams(dict of off and def players)\n# gets player who played for most teams\n# \n# Params: \n# dict of players\n# Returns: \n# player with most teams\ndef MostTeams(OffAndDef):\n most=[]\n count=0 # set comparison\n for playerid, playerdata in OffAndDef.items():\n if(playerdata['name']!=''): #only get real players\n if(len(playerdata['Teams'])>count):\n count=len(playerdata['Teams']) #get count\n most=[[playerdata['name'],len(playerdata['Teams'])]] # replace with player\n elif(len(playerdata['Teams'])==count):\n most.append([playerdata['name'],len(playerdata['Teams'])]) # add multiple teams\n return most\n\n##############################################################\n# MostTeamsOneYear(dict of off and def players)\n# gets player who played for most teams in one year\n# \n# Params: \n# dict of players\n# Returns: \n# player with most teams\ndef MostTeamsOneYear(OffAndDef):\n teams={}\n maximum={}\n count=0\n for playerid, playerdata in OffAndDef.items():\n if(playerdata['name']!=''):\n for years in playerdata: #avoids all keys except years \n if(years!='Drops' and years!='NegRushYards' and years!='NegRush' and years!='Teams' and years!='PassForLoss' and years!=\"name\"):\n try: #try block to avoid nonplayers\n if(len(playerdata[years])>count): # if player has most teams so far\n if((len(playerdata[years]) not in teams.keys())): \n teams.clear() # delete all previous players\n teams[len(playerdata[years])]={}\n teams[len(playerdata[years])][playerdata['name']]=years\n count=len(playerdata[years])\n elif(len(playerdata[years])==count): #multiple players have the same number of teams\n teams[len(playerdata[years])].append(playerdata['name'],years)\n except:\n pass\n\n return teams\n##############################################################\n# NegativeRushingYards(dict of off and def players)\n# gets player with most negative rushing yards\n# \n# Params: \n# dict of players\n# Returns: \n# player with most negative rushing yards\ndef NegativeRushingYards(OffAndDef):\n NegRushYds=[]\n yds=0\n for playerid, playerdata in OffAndDef.items():\n if(playerdata['NegRushYards']<yds):\n yds=playerdata['NegRushYards']\n NegRushYds=[[playerdata['name'],playerdata['NegRushYards']]]\n elif(playerdata['NegRushYards']==yds):\n NegRushYds.append([playerdata['name'],playerdata['NegRushYards']])\n return NegRushYds\n##############################################################\n# NegativeRushes(dict of off and def players)\n# gets player with most negative rushes\n# \n# Params: \n# dict of players\n# Returns: \n# player with most negative rushes\ndef NegativeRushes(OffAndDef):\n rushes=[]\n att=0 #attempts\n for player in OffAndDef:\n if(OffAndDef[player]['NegRush']>att):\n att=OffAndDef[player]['NegRush']\n rushes=[[OffAndDef[player]['name'],OffAndDef[player]['NegRush']]]\n elif(OffAndDef[player]['NegRush']==att):\n rushes.append([OffAndDef[player]['name'],OffAndDef[player]['NegRush']])\n return rushes \n##############################################################\n# MostPassForLoss(dict of off and def players)\n# gets player with most negative rushes\n# \n# Params: \n# dict of players\n# Returns: \n# player with most negative rushes\ndef MostPassForLoss(OffAndDef):\n PassForLoss=[]\n att=0 #attempts\n for player in OffAndDef:\n if(OffAndDef[player]['PassForLoss']>att):\n att=OffAndDef[player]['PassForLoss']\n PassForLoss=[[OffAndDef[player]['name'],OffAndDef[player]['PassForLoss']]]\n elif(OffAndDef[player]['PassForLoss']==att):\n PassForLoss.append([OffAndDef[player]['name'],OffAndDef[player]['PassForLoss']])\n return PassForLoss \n\n##############################################################\n# MostPenalties(dict of team penalties)\n# gets team with most penalties\n# \n# Params: \n# dict of teams\n# Returns: \n# player with most negative rushes\ndef MostPenalties(penalties):\n pens=[]\n num=0\n for teamname,teamdata in penalties.items():\n if(teamdata['Penalties']>num):\n num=teamdata['Penalties']\n pens=[[teamname,teamdata['Penalties']]]\n elif (teamdata['Penalties']==num):\n pens.append([teamname,teamdata['Penalties']])\n return pens\n \n##############################################################\n# TeamPenaltyYards(dict of team penalties)\n# gets team with most penaltiy yards\n# \n# Params: \n# dict of teams\n# Returns: \n# team with most penalty yards\ndef TeamPenaltyYards(penalties):\n pens=[]\n num=0\n for teamname,teamdata in penalties.items():\n if(teamdata['PenaltyYards']>num):\n num=teamdata['PenaltyYards']\n pens=[[teamname,teamdata['PenaltyYards']]]\n elif (teamdata['PenaltyYards']==num):\n pens.append([teamname,teamdata['PenaltyYards']])\n return pens\n##############################################################\n# PenaltyWins(most penalized team,dict of team penalties)\n# shows correlation between penalty and record\n# \n# Params: \n# dict of teams, most penalized team\n# Returns: \n# team with most penaltys and least\ndef PenaltyWins(penalties):\n x=MostPenalties(penalties) #calls function to get most penalized team\n mostPenalized=[]\n for temp in x:\n mostPenalized.append(team[0])\n least=penalties[mostPenalized[0]]['Penalties']\n mostandleast=[[mostPenalized[0],penalties[mostPenalized[0]]['Wins'],penalties[mostPenalized[0]]['Losses']]] # sets most penalized record\n leastTeam=[]\n for teamname, teamdata in penalties.items():\n if(teamdata['Penalties']<least):\n least=teamdata['Penalties']\n leastTeam=[[teamname,teamdata['Wins'],teamdata['Losses']]]\n elif (teamdata['Penalties']==least):\n leastTeam.append([teamname,teamdata['Wins'],teamdata['Losses']])\n mostandleast.append(leastTeam[0]) #adds team and record to list at end\n return mostandleast\n\n##############################################################\n# AverageNumberOfPlays()\n# shows average number of plays\n# \n# Params: \n# none\n# Returns: \n# avg number of plays\ndef AverageNumberOfPlays():\n games=0\n plays=0\n for filename in os.listdir(os.path.dirname(os.path.abspath(__file__))+'/stats'): # sets path to all stats\n with open(os.path.dirname(os.path.abspath(__file__))+\"/stats/\"+filename,\"r\") as json_file:\n try: #gets all stats and stores each game in a dict\n data=json.load(json_file)\n except:\n pass\n else:\n for gameid, gamedata in data.items(): \n if(gameid!=\"nextupdate\"):\n games+=1 #increment number of games\n for driveid, drivedata in gamedata['drives'].items():\n if(driveid!=\"crntdrv\"):\n plays+=drivedata['numplays'] #increment number of plays\n avgplays=plays/games\n return avgplays\n##############################################################\n# LongestFG(dict of fgs)\n# longest field goal\n# \n# Params: \n# dict of fgs\n# Returns: \n# longest field goal and kicker\ndef LongestFG(fg):\n fgs=[]\n length=0 #longest fg\n for playerid,playerdata in fg.items():\n if(playerdata['Long']>length):\n length=playerdata['Long']\n fgs=[[playerdata['Name'],playerdata['Long']]]\n elif (playerdata['Long']==length):\n fgs.append([playerdata['Name'],playerdata['Long']])\n return fgs\n##############################################################\n# MostFG(dict of fgs)\n# most made field goals\n# \n# Params: \n# dict of fgs\n# Returns: \n# most made field goals and kicker\ndef MostFG(fg):\n fgs=[]\n count=0 #sets counter to 0\n for playerid,playerdata in fg.items():\n if(playerdata['FG']>count): #if largest number of fg so far\n count=playerdata['FG']\n fgs=[[playerdata['Name'],playerdata['FG']]]\n elif (playerdata['FG']==count): #if same number of fg\n fgs.append([playerdata['Name'],playerdata['FG']])\n return fgs\n##############################################################\n# MostMFG(dict of fgs)\n# most missed field goals\n# \n# Params: \n# dict of fgs\n# Returns: \n# most missed field goals and kicker\ndef MostMFG(fg):\n fgs=[]\n count=0 #set counter to 0\n for playerid,playerdata in fg.items():\n if(playerdata['MFG']>count): #if most misses so far\n count=playerdata['MFG']\n fgs=[[playerdata['Name'],playerdata['MFG']]]\n elif (playerdata['MFG']==count): #if same as most misses\n fgs.append([playerdata['Name'],playerdata['MFG']])\n return fgs\n##############################################################\n# MostDrops(dict of players)\n# most drops\n# \n# Params: \n# dict of players\n# Returns: \n# most drops\ndef MostDrops(OffAndDef):\n drops=[] \n count=0 #set drops to 0\n for player in OffAndDef:\n if(OffAndDef[player]['Drops']>count):\n count=OffAndDef[player]['Drops']\n drops=[[OffAndDef[player]['name'],OffAndDef[player]['Drops']]]\n elif(OffAndDef[player]['Drops']==count):\n drops.append([OffAndDef[player]['name'],OffAndDef[player]['Drops']])\n return drops\n\npath= os.path.dirname(os.path.abspath(__file__)) #set path to current location\nf=open(path+'/OffAndDef.json','r') #open separated files\nOffAndDef=json.load(f)\nf.close()\nf=open(path+'/Penalties.json','r') \npenalties=json.load(f)\nf.close()\nf=open(path+'/FG.json','r')\nfg=json.load(f)\nf.close()\nprint(\"\\n\")\nprint(\"Name: Zac Conley\")\nprint(\"Assignment: A03 - Nfl Stats\")\nprint(\"Date: 2/10/19\")\nprint(\"==================================================================================\")\nprint(\"Question 1: Find the player(s) that played for the most teams.\")\nplayerlist=MostTeams(OffAndDef)\nfor p in playerlist:\n print(str(p[0]) + \": \"+ str(p[1]) +\" teams\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 2: Find the player(s) that played for multiple teams in one year.\")\nans=MostTeamsOneYear(OffAndDef)\ncount=0\nfor numteams in ans.items():\n for player in numteams[1].items():\n print(player[1]+\": \" +player[0]+\" \"+str(numteams[0])+\" teams.\" )\nprint\nprint(\"==================================================================================\")\nprint(\"Question 3: Find the player(s) that had the most yards rushed for a loss.\")\nans=NegativeRushingYards(OffAndDef)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" rushing yards.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 4: Find the player(s) that had the most rushes for a loss.\")\nans=NegativeRushes(OffAndDef)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" negative rushes.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 5: Find the player(s) with the most number of passes for a loss.\")\nans=MostPassForLoss(OffAndDef)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" negative passes.\\n\")\ntemp=[]\nprint(\"==================================================================================\")\nprint(\"Question 6: Find the team with the most penalties.\")\nans=MostPenalties(penalties)\nfor team in ans:\n print(str(team[0])+\" had \"+str(team[1])+\" penalties.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 7: Find the team with the most yards in penalties.\")\nans=TeamPenaltyYards(penalties)\nfor team in ans:\n print(team[0]+\": \"+str(int(team[1]))+\" penalty yards.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 8: Find the correlation between most penalized teams and games won / lost.\")\nans=PenaltyWins(penalties)\nprint(\"Most Penalties: \"+ans[0][0]+\": \"+str(ans[0][1]) +\"-\" +str(ans[0][2]))\nprint(\"Least Penalties: \"+ans[1][0]+\" : \"+str(ans[1][1])+\"-\" +str(ans[1][2])+\"\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 9: Average number of plays in a game. (This may take up to a minute.)\")\nans=AverageNumberOfPlays()\nprint(\"On average, there are \" +str(ans) +\" plays each game. \\n\")\nprint(\"==================================================================================\")\nprint(\"Question 10: Longest field goal.\")\nans=LongestFG(fg)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" yards.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 11: Most field goals.\")\nans=MostFG(fg)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" FGs.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 12: Most missed field goals.\")\nans=MostMFG(fg)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" missed FGs.\\n\")\nprint(\"==================================================================================\")\nprint(\"Question 13: Most dropped passes.\")\nans=MostDrops(OffAndDef)\nfor player in ans:\n print(player[0]+\": \"+str(player[1])+\" drops.\")",
"step-ids": [
8,
9,
10,
15,
17
]
}
|
[
8,
9,
10,
15,
17
] |
#Nianzu Wang
#Email: wangn89@gmail.com
#for_while.py: demonstrates some fun things with for and while loops
def starsFor(x):
array = range(x, 0, -1)
array2 = range(1, x)
for num in array2:
print "*" * num
for num in array:
print "*" * num
def starsWhile(n):
a = 1
while a < n:
print "*" * a
a += 1
while n > 0:
print "*" * n
n -= 1
return
def countdown(x):
array = range(x, -1, -1)
for num in array:
if num == 0:
print "Blastoff!!!"
else:
print num
def parade(string):
lineUp = list(string)
print """Welcome to the Dragon*Con Parade!
The marching order is as follows:"""
for num in lineUp:
if num == "1":
print num + " - Klingons"
elif num == "2":
print num + " - Storm Troopers"
elif num == "3":
print num + " - SGC Officers"
elif num == "4":
print num + " - Superheroes"
elif num == "5":
print num + " - Elves"
elif num == "6":
print num + " - Video Game Characters"
else:
print num + " - Not in Parade"
def walkOfFame():
celeb = input("""We're off to see celebrities!
How many guests would you like to see?""")
if celeb == 0:
return "Maybe you should try gaming..."
nums = range(celeb, 0, -1)
array = " "
for num in nums:
name = raw_input("Please enter the guest's name.")
if len(name) <= 6:
print name + " ...Who?"
array += (" " + name)
elif len(name) <= 9:
print name + " Hey, I've seen them in that show!"
array += (" " + name)
elif len(name) <= 12:
print name + " Ooh, getting to the big time!"
array += (" " + name)
else:
print name + " Wow! They are super famous. Definitely worth the autograph."
array += (" " + name)
print
print "Get those autograph books ready, you get to see: "
print array
|
normal
|
{
"blob_id": "7e287eca041cf27d99292a331604fef9e9f90fc2",
"index": 7268,
"step-1": "#Nianzu Wang\n#Email: wangn89@gmail.com\n\n#for_while.py: demonstrates some fun things with for and while loops\n\ndef starsFor(x):\n array = range(x, 0, -1)\n array2 = range(1, x)\n for num in array2:\n print \"*\" * num\n for num in array:\n print \"*\" * num\n\ndef starsWhile(n):\n a = 1\n while a < n:\n print \"*\" * a\n a += 1 \n while n > 0:\n print \"*\" * n\n n -= 1\n return\n\ndef countdown(x):\n array = range(x, -1, -1)\n for num in array:\n if num == 0:\n print \"Blastoff!!!\"\n else:\n print num\n\ndef parade(string):\n lineUp = list(string)\n print \"\"\"Welcome to the Dragon*Con Parade!\n The marching order is as follows:\"\"\"\n for num in lineUp:\n if num == \"1\":\n print num + \" - Klingons\"\n elif num == \"2\":\n print num + \" - Storm Troopers\"\n elif num == \"3\":\n print num + \" - SGC Officers\"\n elif num == \"4\":\n print num + \" - Superheroes\"\n elif num == \"5\":\n print num + \" - Elves\"\n elif num == \"6\":\n print num + \" - Video Game Characters\"\n else:\n print num + \" - Not in Parade\"\n\ndef walkOfFame():\n celeb = input(\"\"\"We're off to see celebrities!\nHow many guests would you like to see?\"\"\")\n if celeb == 0:\n return \"Maybe you should try gaming...\"\n nums = range(celeb, 0, -1)\n array = \" \"\n for num in nums:\n name = raw_input(\"Please enter the guest's name.\")\n if len(name) <= 6:\n print name + \" ...Who?\"\n array += (\" \" + name)\n elif len(name) <= 9:\n print name + \" Hey, I've seen them in that show!\"\n array += (\" \" + name)\n elif len(name) <= 12:\n print name + \" Ooh, getting to the big time!\"\n array += (\" \" + name)\n else:\n print name + \" Wow! They are super famous. Definitely worth the autograph.\"\n array += (\" \" + name)\n print\n print \"Get those autograph books ready, you get to see: \"\n print array\n",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
from django.db import models
from albums.models import Albums
class Song(models.Model):
name = models.CharField(max_length=255)
filename = models.FileField(upload_to='canciones/')
album = models.ForeignKey(Albums)
def __unicode__(self,):
return self.name
|
normal
|
{
"blob_id": "8ec18e259af1123fad7563aee3a363e095e30e8e",
"index": 1064,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass Song(models.Model):\n <mask token>\n <mask token>\n <mask token>\n\n def __unicode__(self):\n return self.name\n",
"step-3": "<mask token>\n\n\nclass Song(models.Model):\n name = models.CharField(max_length=255)\n filename = models.FileField(upload_to='canciones/')\n album = models.ForeignKey(Albums)\n\n def __unicode__(self):\n return self.name\n",
"step-4": "from django.db import models\nfrom albums.models import Albums\n\n\nclass Song(models.Model):\n name = models.CharField(max_length=255)\n filename = models.FileField(upload_to='canciones/')\n album = models.ForeignKey(Albums)\n\n def __unicode__(self):\n return self.name\n",
"step-5": "from django.db import models\n\nfrom albums.models import Albums\n\nclass Song(models.Model):\n name = models.CharField(max_length=255)\n filename = models.FileField(upload_to='canciones/')\n album = models.ForeignKey(Albums)\n\n def __unicode__(self,):\n return self.name\n",
"step-ids": [
0,
2,
3,
4,
5
]
}
|
[
0,
2,
3,
4,
5
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class HookView(APIView):
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class HookView(APIView):
def post(self, request, *args, **kwargs):
SCRIPT_PATH = os.path.join(settings.BASE_DIR, 'deploy/hooks.sh')
payload = json.loads(request.data['payload'])
ref = payload['ref']
if ref == 'refs/heads/deploy':
output = subprocess.run(['bash', SCRIPT_PATH]).stdout
return Response(status=status.HTTP_200_OK, data=output)
return Response(status=status.HTTP_400_BAD_REQUEST)
<|reserved_special_token_1|>
from django.shortcuts import render
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.response import Response
from django.conf import settings
import subprocess
import os
import json
class HookView(APIView):
def post(self, request, *args, **kwargs):
SCRIPT_PATH = os.path.join(settings.BASE_DIR, 'deploy/hooks.sh')
payload = json.loads(request.data['payload'])
ref = payload['ref']
if ref == 'refs/heads/deploy':
output = subprocess.run(['bash', SCRIPT_PATH]).stdout
return Response(status=status.HTTP_200_OK, data=output)
return Response(status=status.HTTP_400_BAD_REQUEST)
<|reserved_special_token_1|>
from django.shortcuts import render
from rest_framework import status
from rest_framework.views import APIView
from rest_framework.response import Response
from django.conf import settings
import subprocess
import os
import json
class HookView(APIView):
def post(self, request, *args, **kwargs):
SCRIPT_PATH = os.path.join(settings.BASE_DIR, 'deploy/hooks.sh')
# payload from webhook
payload = json.loads(request.data['payload'])
ref = payload['ref']
if ref == 'refs/heads/deploy':
output = subprocess.run(['bash', SCRIPT_PATH]).stdout
return Response(status=status.HTTP_200_OK, data=output)
return Response(status=status.HTTP_400_BAD_REQUEST)
|
flexible
|
{
"blob_id": "6f5bca8c1afcd9d9971a64300a576ca2b2f6ef70",
"index": 1694,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass HookView(APIView):\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass HookView(APIView):\n\n def post(self, request, *args, **kwargs):\n SCRIPT_PATH = os.path.join(settings.BASE_DIR, 'deploy/hooks.sh')\n payload = json.loads(request.data['payload'])\n ref = payload['ref']\n if ref == 'refs/heads/deploy':\n output = subprocess.run(['bash', SCRIPT_PATH]).stdout\n return Response(status=status.HTTP_200_OK, data=output)\n return Response(status=status.HTTP_400_BAD_REQUEST)\n",
"step-4": "from django.shortcuts import render\nfrom rest_framework import status\nfrom rest_framework.views import APIView\nfrom rest_framework.response import Response\nfrom django.conf import settings\nimport subprocess\nimport os\nimport json\n\n\nclass HookView(APIView):\n\n def post(self, request, *args, **kwargs):\n SCRIPT_PATH = os.path.join(settings.BASE_DIR, 'deploy/hooks.sh')\n payload = json.loads(request.data['payload'])\n ref = payload['ref']\n if ref == 'refs/heads/deploy':\n output = subprocess.run(['bash', SCRIPT_PATH]).stdout\n return Response(status=status.HTTP_200_OK, data=output)\n return Response(status=status.HTTP_400_BAD_REQUEST)\n",
"step-5": "from django.shortcuts import render\nfrom rest_framework import status\nfrom rest_framework.views import APIView\nfrom rest_framework.response import Response\nfrom django.conf import settings\nimport subprocess\nimport os\nimport json\n\n\nclass HookView(APIView):\n def post(self, request, *args, **kwargs):\n SCRIPT_PATH = os.path.join(settings.BASE_DIR, 'deploy/hooks.sh')\n # payload from webhook\n payload = json.loads(request.data['payload'])\n ref = payload['ref']\n if ref == 'refs/heads/deploy':\n output = subprocess.run(['bash', SCRIPT_PATH]).stdout\n return Response(status=status.HTTP_200_OK, data=output)\n\n return Response(status=status.HTTP_400_BAD_REQUEST)\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import torch
import torch.nn as nn
import numpy as np
class EuclideanLoss(nn.Module):
def __init__(self, c_p, c_h):
super().__init__()
self.c_p = c_p
self.c_h = c_h
def forward(self, y, d):
'''
y: prediction, size = (n_product, n_obs)
d: actual sales, size = (n_product, n_obs)
'''
diff = torch.add(y, -d)
diff = torch.add(torch.mul(torch.max(diff, torch.zeros(1)), self.c_p), torch.mul(torch.max(-diff, torch.zeros(1)), self.c_h))
diff = torch.norm(diff)
diff = torch.sum(diff)
return diff
class CostFunction(nn.Module):
def __init__(self, c_p, c_h):
super().__init__()
self.c_p = c_p
self.c_h = c_h
def forward(self, y, d):
'''
y: prediction, size = (n_product, n_obs)
d: actual sales, size = (n_product, n_obs)
'''
cost = torch.add(y, -d)
cost = torch.add(torch.mul(torch.max(cost, torch.zeros(1)), self.c_p), torch.mul(torch.max(-cost, torch.zeros(1)), self.c_h))
cost = torch.sum(cost)
return cost
|
normal
|
{
"blob_id": "67be25e8fdf004515e18e1c20b8d0238222a2172",
"index": 1401,
"step-1": "<mask token>\n\n\nclass EuclideanLoss(nn.Module):\n <mask token>\n <mask token>\n\n\nclass CostFunction(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n \"\"\"\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n \"\"\"\n cost = torch.add(y, -d)\n cost = torch.add(torch.mul(torch.max(cost, torch.zeros(1)), self.\n c_p), torch.mul(torch.max(-cost, torch.zeros(1)), self.c_h))\n cost = torch.sum(cost)\n return cost\n",
"step-2": "<mask token>\n\n\nclass EuclideanLoss(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n <mask token>\n\n\nclass CostFunction(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n \"\"\"\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n \"\"\"\n cost = torch.add(y, -d)\n cost = torch.add(torch.mul(torch.max(cost, torch.zeros(1)), self.\n c_p), torch.mul(torch.max(-cost, torch.zeros(1)), self.c_h))\n cost = torch.sum(cost)\n return cost\n",
"step-3": "<mask token>\n\n\nclass EuclideanLoss(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n \"\"\"\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n \"\"\"\n diff = torch.add(y, -d)\n diff = torch.add(torch.mul(torch.max(diff, torch.zeros(1)), self.\n c_p), torch.mul(torch.max(-diff, torch.zeros(1)), self.c_h))\n diff = torch.norm(diff)\n diff = torch.sum(diff)\n return diff\n\n\nclass CostFunction(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n \"\"\"\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n \"\"\"\n cost = torch.add(y, -d)\n cost = torch.add(torch.mul(torch.max(cost, torch.zeros(1)), self.\n c_p), torch.mul(torch.max(-cost, torch.zeros(1)), self.c_h))\n cost = torch.sum(cost)\n return cost\n",
"step-4": "import torch\nimport torch.nn as nn\nimport numpy as np\n\n\nclass EuclideanLoss(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n \"\"\"\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n \"\"\"\n diff = torch.add(y, -d)\n diff = torch.add(torch.mul(torch.max(diff, torch.zeros(1)), self.\n c_p), torch.mul(torch.max(-diff, torch.zeros(1)), self.c_h))\n diff = torch.norm(diff)\n diff = torch.sum(diff)\n return diff\n\n\nclass CostFunction(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n \"\"\"\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n \"\"\"\n cost = torch.add(y, -d)\n cost = torch.add(torch.mul(torch.max(cost, torch.zeros(1)), self.\n c_p), torch.mul(torch.max(-cost, torch.zeros(1)), self.c_h))\n cost = torch.sum(cost)\n return cost\n",
"step-5": "import torch\nimport torch.nn as nn\nimport numpy as np\n\nclass EuclideanLoss(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n '''\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n '''\n\n diff = torch.add(y, -d)\n diff = torch.add(torch.mul(torch.max(diff, torch.zeros(1)), self.c_p), torch.mul(torch.max(-diff, torch.zeros(1)), self.c_h))\n diff = torch.norm(diff)\n diff = torch.sum(diff)\n return diff\n\nclass CostFunction(nn.Module):\n\n def __init__(self, c_p, c_h):\n super().__init__()\n self.c_p = c_p\n self.c_h = c_h\n\n def forward(self, y, d):\n '''\n y: prediction, size = (n_product, n_obs)\n d: actual sales, size = (n_product, n_obs)\n '''\n\n cost = torch.add(y, -d)\n cost = torch.add(torch.mul(torch.max(cost, torch.zeros(1)), self.c_p), torch.mul(torch.max(-cost, torch.zeros(1)), self.c_h))\n cost = torch.sum(cost)\n\n return cost",
"step-ids": [
4,
5,
6,
7,
8
]
}
|
[
4,
5,
6,
7,
8
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for index in range(test_set.shape[0]):
print(index)
<|reserved_special_token_1|>
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 24 22:05:12 2019
@author: admin
"""
for index in range(test_set.shape[0]):
print(index)
|
flexible
|
{
"blob_id": "35647ed5e2c128a5bf819a1e47ead7e958172b1c",
"index": 9711,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor index in range(test_set.shape[0]):\n print(index)\n",
"step-3": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Apr 24 22:05:12 2019\n\n@author: admin\n\"\"\"\n\nfor index in range(test_set.shape[0]):\n print(index)",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
#!/bin/env python3
"""
https://www.hackerrank.com/challenges/triangle-quest-2
INPUT:
integer N
where 0 < N < 10
OUTPUT:
print palindromic triangle of size N
e.g.for N=5
1
121
12321
1234321
123454321
"""
for i in range(1, int(input()) + 1):
j = 1
while j < i:
print(j,end='')
j += 1
while i > 0:
print(i,end='')
i -= 1
print()
|
normal
|
{
"blob_id": "94cbd9554e3326897147dc417d9fc8f91974786a",
"index": 5098,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor i in range(1, int(input()) + 1):\n j = 1\n while j < i:\n print(j, end='')\n j += 1\n while i > 0:\n print(i, end='')\n i -= 1\n print()\n",
"step-3": "#!/bin/env python3\n\"\"\"\nhttps://www.hackerrank.com/challenges/triangle-quest-2\n\nINPUT:\n integer N\n where 0 < N < 10\n\nOUTPUT:\n print palindromic triangle of size N\n\n e.g.for N=5\n1\n121\n12321\n1234321\n123454321\n\n\"\"\"\nfor i in range(1, int(input()) + 1):\n j = 1\n while j < i:\n print(j,end='')\n j += 1\n\n while i > 0:\n print(i,end='')\n i -= 1\n print()\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
import dash_html_components as html
import dash_core_components as dcc
layout = html.Div([
html.Div([
html.Div([
html.H6('Répartition des biens'),
dcc.Graph(
id = "pieGraph",
figure = {
"data": [{
"values": [2878001,2342181,1773296,521395],
"labels": [ 'Maison', 'Appartement', 'Dependance','local_indistriel' ],
"name": "Biens",
"hoverinfo":"label+name+percent",
"hole": .7,
"type": "pie",
"marker": {'colors':['#3b7548','#ea1313','#ffd700','#FF00FF']}
}],
"layout": {
"width": "2000",
"annotations": [{
"font": {
"size": 20
},
"showarrow": False,
"text": "",
"x": 0.2,
"y": 0.2
}],
"showlegend": False
}
}
)
], className="six columns"),
html.Div([
html.H6('Effectif des biens'),
dcc.Graph(
id = "3",
figure ={
"data": [{
'x':[ 'Maison', 'Appartement', 'Dependance','local_indistriel' ],
'y':[2878001,2342181,1773296,521395],
'name':'Bar biens',
'type':'bar',
'marker' :dict(color=['#3b7548','#ea1313','#ffd700','#FF00FF']),
}],
"layout": {
"xaxis" : dict(tickfont=dict(color='black')),
"yaxis" : dict(tickfont=dict(color='black')),
"width": "2000",
'yaxis':{
'title':'Nombre'
},
'xaxis':{
'title':'Type'
},
"annotations": [{
"font": {"size": 20},
"showarrow": False,
"text": "",
"x": 0.2,
"y": 0.2
}],
"showlegend": False
}
}
)
], className="six columns"),
], className="row", style={"margin": "1% 3%"})
])
|
normal
|
{
"blob_id": "83c3193ea40c9328d16fb91774762a76352d8e09",
"index": 8417,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nlayout = html.Div([html.Div([html.Div([html.H6('Répartition des biens'),\n dcc.Graph(id='pieGraph', figure={'data': [{'values': [2878001, 2342181,\n 1773296, 521395], 'labels': ['Maison', 'Appartement', 'Dependance',\n 'local_indistriel'], 'name': 'Biens', 'hoverinfo': 'label+name+percent',\n 'hole': 0.7, 'type': 'pie', 'marker': {'colors': ['#3b7548', '#ea1313',\n '#ffd700', '#FF00FF']}}], 'layout': {'width': '2000', 'annotations': [{\n 'font': {'size': 20}, 'showarrow': False, 'text': '', 'x': 0.2, 'y': \n 0.2}], 'showlegend': False}})], className='six columns'), html.Div([\n html.H6('Effectif des biens'), dcc.Graph(id='3', figure={'data': [{'x':\n ['Maison', 'Appartement', 'Dependance', 'local_indistriel'], 'y': [\n 2878001, 2342181, 1773296, 521395], 'name': 'Bar biens', 'type': 'bar',\n 'marker': dict(color=['#3b7548', '#ea1313', '#ffd700', '#FF00FF'])}],\n 'layout': {'xaxis': dict(tickfont=dict(color='black')), 'yaxis': dict(\n tickfont=dict(color='black')), 'width': '2000', 'yaxis': {'title':\n 'Nombre'}, 'xaxis': {'title': 'Type'}, 'annotations': [{'font': {'size':\n 20}, 'showarrow': False, 'text': '', 'x': 0.2, 'y': 0.2}], 'showlegend':\n False}})], className='six columns')], className='row', style={'margin':\n '1% 3%'})])\n",
"step-3": "import dash_html_components as html\nimport dash_core_components as dcc\nlayout = html.Div([html.Div([html.Div([html.H6('Répartition des biens'),\n dcc.Graph(id='pieGraph', figure={'data': [{'values': [2878001, 2342181,\n 1773296, 521395], 'labels': ['Maison', 'Appartement', 'Dependance',\n 'local_indistriel'], 'name': 'Biens', 'hoverinfo': 'label+name+percent',\n 'hole': 0.7, 'type': 'pie', 'marker': {'colors': ['#3b7548', '#ea1313',\n '#ffd700', '#FF00FF']}}], 'layout': {'width': '2000', 'annotations': [{\n 'font': {'size': 20}, 'showarrow': False, 'text': '', 'x': 0.2, 'y': \n 0.2}], 'showlegend': False}})], className='six columns'), html.Div([\n html.H6('Effectif des biens'), dcc.Graph(id='3', figure={'data': [{'x':\n ['Maison', 'Appartement', 'Dependance', 'local_indistriel'], 'y': [\n 2878001, 2342181, 1773296, 521395], 'name': 'Bar biens', 'type': 'bar',\n 'marker': dict(color=['#3b7548', '#ea1313', '#ffd700', '#FF00FF'])}],\n 'layout': {'xaxis': dict(tickfont=dict(color='black')), 'yaxis': dict(\n tickfont=dict(color='black')), 'width': '2000', 'yaxis': {'title':\n 'Nombre'}, 'xaxis': {'title': 'Type'}, 'annotations': [{'font': {'size':\n 20}, 'showarrow': False, 'text': '', 'x': 0.2, 'y': 0.2}], 'showlegend':\n False}})], className='six columns')], className='row', style={'margin':\n '1% 3%'})])\n",
"step-4": "import dash_html_components as html\nimport dash_core_components as dcc\n\n\n\nlayout = html.Div([\n html.Div([\n html.Div([\n html.H6('Répartition des biens'),\n dcc.Graph(\n id = \"pieGraph\",\n figure = {\n \"data\": [{\n \"values\": [2878001,2342181,1773296,521395],\n \"labels\": [ 'Maison', 'Appartement', 'Dependance','local_indistriel' ],\n \"name\": \"Biens\",\n \"hoverinfo\":\"label+name+percent\",\n \"hole\": .7,\n \"type\": \"pie\",\n \"marker\": {'colors':['#3b7548','#ea1313','#ffd700','#FF00FF']}\n }],\n \"layout\": {\n \"width\": \"2000\",\n \"annotations\": [{\n \"font\": {\n \"size\": 20\n },\n \"showarrow\": False,\n \"text\": \"\",\n \"x\": 0.2,\n \"y\": 0.2\n }],\n \"showlegend\": False \n }\n }\n )\n ], className=\"six columns\"),\n\n html.Div([\n html.H6('Effectif des biens'),\n\n dcc.Graph(\n id = \"3\",\n figure ={\n \"data\": [{\n 'x':[ 'Maison', 'Appartement', 'Dependance','local_indistriel' ],\n 'y':[2878001,2342181,1773296,521395],\n 'name':'Bar biens',\n 'type':'bar',\n 'marker' :dict(color=['#3b7548','#ea1313','#ffd700','#FF00FF']),\n }],\n \"layout\": {\n \"xaxis\" : dict(tickfont=dict(color='black')),\n \"yaxis\" : dict(tickfont=dict(color='black')),\n \"width\": \"2000\",\n 'yaxis':{\n 'title':'Nombre'\n },\n 'xaxis':{\n 'title':'Type'\n },\n \"annotations\": [{\n \"font\": {\"size\": 20},\n \"showarrow\": False,\n \"text\": \"\",\n \"x\": 0.2,\n \"y\": 0.2\n }],\n \"showlegend\": False \n }\n }\n )\n\n ], className=\"six columns\"),\n\n ], className=\"row\", style={\"margin\": \"1% 3%\"})\n])",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2017--2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You may not
# use this file except in compliance with the License. A copy of the License
# is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is distributed on
# an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language governing
# permissions and limitations under the License.
"""
SacreBLEU provides hassle-free computation of shareable, comparable, and reproducible BLEU scores.
Inspired by Rico Sennrich's `multi-bleu-detok.perl`, it produces the official WMT scores but works with plain text.
It also knows all the standard test sets and handles downloading, processing, and tokenization for you.
See the [README.md] file for more information.
"""
import argparse
import gzip
import hashlib
import io
import logging
import math
import os
import portalocker
import re
import sys
import ssl
import urllib.request
from collections import Counter
from itertools import zip_longest
from typing import List, Iterable, Tuple, Union
from .tokenizer import TOKENIZERS, TokenizeMeCab
from .dataset import DATASETS, DOMAINS, COUNTRIES, SUBSETS
from . import __version__ as VERSION
sacrelogger = logging.getLogger('sacrebleu')
try:
# SIGPIPE is not available on Windows machines, throwing an exception.
from signal import SIGPIPE
# If SIGPIPE is available, change behaviour to default instead of ignore.
from signal import signal, SIG_DFL
signal(SIGPIPE, SIG_DFL)
except ImportError:
sacrelogger.warning('Could not import signal.SIGPIPE (this is expected on Windows machines)')
# Where to store downloaded test sets.
# Define the environment variable $SACREBLEU, or use the default of ~/.sacrebleu.
#
# Querying for a HOME environment variable can result in None (e.g., on Windows)
# in which case the os.path.join() throws a TypeError. Using expanduser() is
# a safe way to get the user's home folder.
USERHOME = os.path.expanduser("~")
SACREBLEU_DIR = os.environ.get('SACREBLEU', os.path.join(USERHOME, '.sacrebleu'))
# n-gram order. Don't change this.
NGRAM_ORDER = 4
# Default values for CHRF
CHRF_ORDER = 6
# default to 2 (per http://www.aclweb.org/anthology/W16-2341)
CHRF_BETA = 2
# The default floor value to use with `--smooth floor`
SMOOTH_VALUE_DEFAULT = {'floor': 0.0, 'add-k': 1}
DEFAULT_TOKENIZER = '13a'
def smart_open(file, mode='rt', encoding='utf-8'):
"""Convenience function for reading compressed or plain text files.
:param file: The file to read.
:param mode: The file mode (read, write).
:param encoding: The file encoding.
"""
if file.endswith('.gz'):
return gzip.open(file, mode=mode, encoding=encoding, newline="\n")
return open(file, mode=mode, encoding=encoding, newline="\n")
def my_log(num):
"""
Floors the log function
:param num: the number
:return: log(num) floored to a very low number
"""
if num == 0.0:
return -9999999999
return math.log(num)
def bleu_signature(args, numrefs):
"""
Builds a signature that uniquely identifies the scoring parameters used.
:param args: the arguments passed into the script
:return: the signature
"""
# Abbreviations for the signature
abbr = {
'test': 't',
'lang': 'l',
'smooth': 's',
'case': 'c',
'tok': 'tok',
'numrefs': '#',
'version': 'v',
'origlang': 'o',
'subset': 'S',
}
signature = {'tok': args.tokenize,
'version': VERSION,
'smooth': args.smooth,
'numrefs': numrefs,
'case': 'lc' if args.lc else 'mixed'}
# For the Japanese tokenizer, add a dictionary type and its version to the signature.
if args.tokenize == "ja-mecab":
signature['tok'] += "-" + TokenizeMeCab().signature()
if args.test_set is not None:
signature['test'] = args.test_set
if args.langpair is not None:
signature['lang'] = args.langpair
if args.origlang is not None:
signature['origlang'] = args.origlang
if args.subset is not None:
signature['subset'] = args.subset
sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x, signature[x]) for x in sorted(signature.keys())])
return sigstr
def chrf_signature(args, numrefs):
"""
Builds a signature that uniquely identifies the scoring parameters used.
:param args: the arguments passed into the script
:return: the chrF signature
"""
# Abbreviations for the signature
abbr = {
'test': 't',
'lang': 'l',
'numchars': 'n',
'space': 's',
'case': 'c',
'numrefs': '#',
'version': 'v',
'origlang': 'o',
'subset': 'S',
}
signature = {'version': VERSION,
'space': args.chrf_whitespace,
'numchars': args.chrf_order,
'numrefs': numrefs,
'case': 'lc' if args.lc else 'mixed'}
if args.test_set is not None:
signature['test'] = args.test_set
if args.langpair is not None:
signature['lang'] = args.langpair
if args.origlang is not None:
signature['origlang'] = args.origlang
if args.subset is not None:
signature['subset'] = args.subset
sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x, signature[x]) for x in sorted(signature.keys())])
return sigstr
def extract_ngrams(line, min_order=1, max_order=NGRAM_ORDER) -> Counter:
"""Extracts all the ngrams (min_order <= n <= max_order) from a sequence of tokens.
:param line: A segment containing a sequence of words.
:param min_order: Minimum n-gram length (default: 1).
:param max_order: Maximum n-gram length (default: NGRAM_ORDER).
:return: a dictionary containing ngrams and counts
"""
ngrams = Counter()
tokens = line.split()
for n in range(min_order, max_order + 1):
for i in range(0, len(tokens) - n + 1):
ngram = ' '.join(tokens[i: i + n])
ngrams[ngram] += 1
return ngrams
def extract_char_ngrams(s: str, n: int) -> Counter:
"""
Yields counts of character n-grams from string s of order n.
"""
return Counter([s[i:i + n] for i in range(len(s) - n + 1)])
def ref_stats(output, refs):
ngrams = Counter()
closest_diff = None
closest_len = None
for ref in refs:
tokens = ref.split()
reflen = len(tokens)
diff = abs(len(output.split()) - reflen)
if closest_diff is None or diff < closest_diff:
closest_diff = diff
closest_len = reflen
elif diff == closest_diff:
if reflen < closest_len:
closest_len = reflen
ngrams_ref = extract_ngrams(ref)
for ngram in ngrams_ref.keys():
ngrams[ngram] = max(ngrams[ngram], ngrams_ref[ngram])
return ngrams, closest_diff, closest_len
def _clean(s):
"""
Removes trailing and leading spaces and collapses multiple consecutive internal spaces to a single one.
:param s: The string.
:return: A cleaned-up string.
"""
return re.sub(r'\s+', ' ', s.strip())
def process_to_text(rawfile, txtfile, field: int=None):
"""Processes raw files to plain text files.
:param rawfile: the input file (possibly SGML)
:param txtfile: the plaintext file
:param field: For TSV files, which field to extract.
"""
if not os.path.exists(txtfile) or os.path.getsize(txtfile) == 0:
sacrelogger.info("Processing %s to %s", rawfile, txtfile)
if rawfile.endswith('.sgm') or rawfile.endswith('.sgml'):
with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:
for line in fin:
if line.startswith('<seg '):
print(_clean(re.sub(r'<seg.*?>(.*)</seg>.*?', '\\1', line)), file=fout)
elif rawfile.endswith('.xml'): # IWSLT
with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:
for line in fin:
if line.startswith('<seg '):
print(_clean(re.sub(r'<seg.*?>(.*)</seg>.*?', '\\1', line)), file=fout)
elif rawfile.endswith('.txt'): # wmt17/ms
with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:
for line in fin:
print(line.rstrip(), file=fout)
elif rawfile.endswith('.tsv'): # MTNT
with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:
for line in fin:
print(line.rstrip().split('\t')[field], file=fout)
def print_test_set(test_set, langpair, side, origlang=None, subset=None):
"""Prints to STDOUT the specified side of the specified test set
:param test_set: the test set to print
:param langpair: the language pair
:param side: 'src' for source, 'ref' for reference
:param origlang: print only sentences with a given original language (2-char ISO639-1 code), "non-" prefix means negation
:param subset: print only sentences whose document annotation matches a given regex
"""
files = download_test_set(test_set, langpair)
if side == 'src':
files = [files[0]]
elif side == 'ref':
files.pop(0)
streams = [smart_open(file) for file in files]
streams = _filter_subset(streams, test_set, langpair, origlang, subset)
for lines in zip(*streams):
print('\t'.join(map(lambda x: x.rstrip(), lines)))
def download_test_set(test_set, langpair=None):
"""Downloads the specified test to the system location specified by the SACREBLEU environment variable.
:param test_set: the test set to download
:param langpair: the language pair (needed for some datasets)
:return: the set of processed files
"""
outdir = os.path.join(SACREBLEU_DIR, test_set)
os.makedirs(outdir, exist_ok=True)
expected_checksums = DATASETS[test_set].get('md5', [None] * len(DATASETS[test_set]))
for dataset, expected_md5 in zip(DATASETS[test_set]['data'], expected_checksums):
tarball = os.path.join(outdir, os.path.basename(dataset))
rawdir = os.path.join(outdir, 'raw')
lockfile = '{}.lock'.format(tarball)
with portalocker.Lock(lockfile, 'w', timeout=60):
if not os.path.exists(tarball) or os.path.getsize(tarball) == 0:
sacrelogger.info("Downloading %s to %s", dataset, tarball)
try:
with urllib.request.urlopen(dataset) as f, open(tarball, 'wb') as out:
out.write(f.read())
except ssl.SSLError:
sacrelogger.warning('An SSL error was encountered in downloading the files. If you\'re on a Mac, '
'you may need to run the "Install Certificates.command" file located in the '
'"Python 3" folder, often found under /Applications')
sys.exit(1)
# Check md5sum
if expected_md5 is not None:
md5 = hashlib.md5()
with open(tarball, 'rb') as infile:
for line in infile:
md5.update(line)
if md5.hexdigest() != expected_md5:
sacrelogger.error('Fatal: MD5 sum of downloaded file was incorrect (got {}, expected {}).'.format(md5.hexdigest(), expected_md5))
sacrelogger.error('Please manually delete "{}" and rerun the command.'.format(tarball))
sacrelogger.error('If the problem persists, the tarball may have changed, in which case, please contact the SacreBLEU maintainer.')
sys.exit(1)
else:
sacrelogger.info('Checksum passed: {}'.format(md5.hexdigest()))
# Extract the tarball
sacrelogger.info('Extracting %s', tarball)
if tarball.endswith('.tar.gz') or tarball.endswith('.tgz'):
import tarfile
with tarfile.open(tarball) as tar:
tar.extractall(path=rawdir)
elif tarball.endswith('.zip'):
import zipfile
with zipfile.ZipFile(tarball, 'r') as zipfile:
zipfile.extractall(path=rawdir)
found = []
# Process the files into plain text
languages = DATASETS[test_set].keys() if langpair is None else [langpair]
for pair in languages:
if '-' not in pair:
continue
src, tgt = pair.split('-')
rawfile = DATASETS[test_set][pair][0]
field = None # used for TSV files
if rawfile.endswith('.tsv'):
field, rawfile = rawfile.split(':', maxsplit=1)
field = int(field)
rawpath = os.path.join(rawdir, rawfile)
outpath = os.path.join(outdir, '{}.{}'.format(pair, src))
process_to_text(rawpath, outpath, field=field)
found.append(outpath)
refs = DATASETS[test_set][pair][1:]
for i, ref in enumerate(refs):
field = None
if ref.endswith('.tsv'):
field, ref = ref.split(':', maxsplit=1)
field = int(field)
rawpath = os.path.join(rawdir, ref)
if len(refs) >= 2:
outpath = os.path.join(outdir, '{}.{}.{}'.format(pair, tgt, i))
else:
outpath = os.path.join(outdir, '{}.{}'.format(pair, tgt))
process_to_text(rawpath, outpath, field=field)
found.append(outpath)
return found
class Result:
def __init__(self, score: float):
self.score = score
def __str__(self):
return self.format()
class BLEU(Result):
def __init__(self,
score: float,
counts,
totals,
precisions,
bp,
sys_len,
ref_len):
super().__init__(score)
self.counts = counts
self.totals = totals
self.precisions = precisions
self.bp = bp
self.sys_len = sys_len
self.ref_len = ref_len
def format(self, width=2):
precisions = "/".join(["{:.1f}".format(p) for p in self.precisions])
return 'BLEU = {score:.{width}f} {precisions} (BP = {bp:.3f} ratio = {ratio:.3f} hyp_len = {sys_len:d} ref_len = {ref_len:d})'.format(
score=self.score,
width=width,
precisions=precisions,
bp=self.bp,
ratio=self.sys_len / self.ref_len,
sys_len=self.sys_len,
ref_len=self.ref_len)
class CHRF(Result):
def __init__(self, score: float):
super().__init__(score)
def format(self, width=2):
return '{score:.{width}f}'.format(score=self.score, width=width)
def compute_bleu(correct: List[int],
total: List[int],
sys_len: int,
ref_len: int,
smooth_method = 'none',
smooth_value = None,
use_effective_order = False) -> BLEU:
"""Computes BLEU score from its sufficient statistics. Adds smoothing.
Smoothing methods (citing "A Systematic Comparison of Smoothing Techniques for Sentence-Level BLEU",
Boxing Chen and Colin Cherry, WMT 2014: http://aclweb.org/anthology/W14-3346)
- exp: NIST smoothing method (Method 3)
- floor: Method 1
- add-k: Method 2 (generalizing Lin and Och, 2004)
- none: do nothing.
:param correct: List of counts of correct ngrams, 1 <= n <= NGRAM_ORDER
:param total: List of counts of total ngrams, 1 <= n <= NGRAM_ORDER
:param sys_len: The cumulative system length
:param ref_len: The cumulative reference length
:param smooth: The smoothing method to use
:param smooth_value: The smoothing value added, if smooth method 'floor' is used
:param use_effective_order: If true, use the length of `correct` for the n-gram order instead of NGRAM_ORDER.
:return: A BLEU object with the score (100-based) and other statistics.
"""
if smooth_method in SMOOTH_VALUE_DEFAULT and smooth_value is None:
smooth_value = SMOOTH_VALUE_DEFAULT[smooth_method]
precisions = [0 for x in range(NGRAM_ORDER)]
smooth_mteval = 1.
effective_order = NGRAM_ORDER
for n in range(1, NGRAM_ORDER + 1):
if smooth_method == 'add-k' and n > 1:
correct[n-1] += smooth_value
total[n-1] += smooth_value
if total[n-1] == 0:
break
if use_effective_order:
effective_order = n
if correct[n-1] == 0:
if smooth_method == 'exp':
smooth_mteval *= 2
precisions[n-1] = 100. / (smooth_mteval * total[n-1])
elif smooth_method == 'floor':
precisions[n-1] = 100. * smooth_value / total[n-1]
else:
precisions[n-1] = 100. * correct[n-1] / total[n-1]
# If the system guesses no i-grams, 1 <= i <= NGRAM_ORDER, the BLEU score is 0 (technically undefined).
# This is a problem for sentence-level BLEU or a corpus of short sentences, where systems will get no credit
# if sentence lengths fall under the NGRAM_ORDER threshold. This fix scales NGRAM_ORDER to the observed
# maximum order. It is only available through the API and off by default
brevity_penalty = 1.0
if sys_len < ref_len:
brevity_penalty = math.exp(1 - ref_len / sys_len) if sys_len > 0 else 0.0
score = brevity_penalty * math.exp(sum(map(my_log, precisions[:effective_order])) / effective_order)
return BLEU(score, correct, total, precisions, brevity_penalty, sys_len, ref_len)
def sentence_bleu(hypothesis: str,
references: List[str],
smooth_method: str = 'floor',
smooth_value: float = None,
use_effective_order: bool = True) -> BLEU:
"""
Computes BLEU on a single sentence pair.
Disclaimer: computing BLEU on the sentence level is not its intended use,
BLEU is a corpus-level metric.
:param hypothesis: Hypothesis string.
:param reference: Reference string.
:param smooth_value: For 'floor' smoothing, the floor value to use.
:param use_effective_order: Account for references that are shorter than the largest n-gram.
:return: Returns a single BLEU score as a float.
"""
bleu = corpus_bleu(hypothesis, references,
smooth_method=smooth_method,
smooth_value=smooth_value,
use_effective_order=use_effective_order)
return bleu
def corpus_bleu(sys_stream: Union[str, Iterable[str]],
ref_streams: Union[str, List[Iterable[str]]],
smooth_method='exp',
smooth_value=None,
force=False,
lowercase=False,
tokenize=DEFAULT_TOKENIZER,
use_effective_order=False) -> BLEU:
"""Produces BLEU scores along with its sufficient statistics from a source against one or more references.
:param sys_stream: The system stream (a sequence of segments)
:param ref_streams: A list of one or more reference streams (each a sequence of segments)
:param smooth: The smoothing method to use
:param smooth_value: For 'floor' smoothing, the floor to use
:param force: Ignore data that looks already tokenized
:param lowercase: Lowercase the data
:param tokenize: The tokenizer to use
:return: a BLEU object containing everything you'd want
"""
# Add some robustness to the input arguments
if isinstance(sys_stream, str):
sys_stream = [sys_stream]
if isinstance(ref_streams, str):
ref_streams = [[ref_streams]]
sys_len = 0
ref_len = 0
correct = [0 for n in range(NGRAM_ORDER)]
total = [0 for n in range(NGRAM_ORDER)]
# look for already-tokenized sentences
tokenized_count = 0
fhs = [sys_stream] + ref_streams
for lines in zip_longest(*fhs):
if None in lines:
raise EOFError("Source and reference streams have different lengths!")
if lowercase:
lines = [x.lower() for x in lines]
if not (force or tokenize == 'none') and lines[0].rstrip().endswith(' .'):
tokenized_count += 1
if tokenized_count == 100:
sacrelogger.warning('That\'s 100 lines that end in a tokenized period (\'.\')')
sacrelogger.warning('It looks like you forgot to detokenize your test data, which may hurt your score.')
sacrelogger.warning('If you insist your data is detokenized, or don\'t care, you can suppress this message with \'--force\'.')
output, *refs = [TOKENIZERS[tokenize](x.rstrip()) for x in lines]
ref_ngrams, closest_diff, closest_len = ref_stats(output, refs)
sys_len += len(output.split())
ref_len += closest_len
sys_ngrams = extract_ngrams(output)
for ngram in sys_ngrams.keys():
n = len(ngram.split())
correct[n-1] += min(sys_ngrams[ngram], ref_ngrams.get(ngram, 0))
total[n-1] += sys_ngrams[ngram]
return compute_bleu(correct, total, sys_len, ref_len, smooth_method=smooth_method, smooth_value=smooth_value, use_effective_order=use_effective_order)
def raw_corpus_bleu(sys_stream,
ref_streams,
smooth_value=None) -> BLEU:
"""Convenience function that wraps corpus_bleu().
This is convenient if you're using sacrebleu as a library, say for scoring on dev.
It uses no tokenization and 'floor' smoothing, with the floor default to 0 (no smoothing).
:param sys_stream: the system stream (a sequence of segments)
:param ref_streams: a list of one or more reference streams (each a sequence of segments)
"""
return corpus_bleu(sys_stream, ref_streams, smooth_method='floor', smooth_value=smooth_value, force=True, tokenize='none', use_effective_order=True)
def delete_whitespace(text: str) -> str:
"""
Removes whitespaces from text.
"""
return re.sub(r'\s+', '', text).strip()
def get_sentence_statistics(hypothesis: str,
reference: str,
order: int = CHRF_ORDER,
remove_whitespace: bool = True) -> List[float]:
hypothesis = delete_whitespace(hypothesis) if remove_whitespace else hypothesis
reference = delete_whitespace(reference) if remove_whitespace else reference
statistics = [0] * (order * 3)
for i in range(order):
n = i + 1
hypothesis_ngrams = extract_char_ngrams(hypothesis, n)
reference_ngrams = extract_char_ngrams(reference, n)
common_ngrams = hypothesis_ngrams & reference_ngrams
statistics[3 * i + 0] = sum(hypothesis_ngrams.values())
statistics[3 * i + 1] = sum(reference_ngrams.values())
statistics[3 * i + 2] = sum(common_ngrams.values())
return statistics
def get_corpus_statistics(hypotheses: Iterable[str],
references: Iterable[str],
order: int = CHRF_ORDER,
remove_whitespace: bool = True) -> List[float]:
corpus_statistics = [0] * (order * 3)
for hypothesis, reference in zip(hypotheses, references):
statistics = get_sentence_statistics(hypothesis, reference, order=order, remove_whitespace=remove_whitespace)
for i in range(len(statistics)):
corpus_statistics[i] += statistics[i]
return corpus_statistics
def _avg_precision_and_recall(statistics: List[float], order: int) -> Tuple[float, float]:
avg_precision = 0.0
avg_recall = 0.0
effective_order = 0
for i in range(order):
hypotheses_ngrams = statistics[3 * i + 0]
references_ngrams = statistics[3 * i + 1]
common_ngrams = statistics[3 * i + 2]
if hypotheses_ngrams > 0 and references_ngrams > 0:
avg_precision += common_ngrams / hypotheses_ngrams
avg_recall += common_ngrams / references_ngrams
effective_order += 1
if effective_order == 0:
return 0.0, 0.0
avg_precision /= effective_order
avg_recall /= effective_order
return avg_precision, avg_recall
def _chrf(avg_precision, avg_recall, beta: int = CHRF_BETA) -> float:
if avg_precision + avg_recall == 0:
return 0.0
beta_square = beta ** 2
score = (1 + beta_square) * (avg_precision * avg_recall) / ((beta_square * avg_precision) + avg_recall)
return score
def corpus_chrf(hypotheses: Iterable[str],
references: Iterable[str],
order: int = CHRF_ORDER,
beta: float = CHRF_BETA,
remove_whitespace: bool = True) -> CHRF:
"""
Computes Chrf on a corpus.
:param hypotheses: Stream of hypotheses.
:param references: Stream of references
:param order: Maximum n-gram order.
:param remove_whitespace: Whether to delete all whitespace from hypothesis and reference strings.
:param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.
:return: Chrf score.
"""
corpus_statistics = get_corpus_statistics(hypotheses, references, order=order, remove_whitespace=remove_whitespace)
avg_precision, avg_recall = _avg_precision_and_recall(corpus_statistics, order)
return CHRF(_chrf(avg_precision, avg_recall, beta=beta))
def sentence_chrf(hypothesis: str,
reference: str,
order: int = CHRF_ORDER,
beta: float = CHRF_BETA,
remove_whitespace: bool = True) -> CHRF:
"""
Computes ChrF on a single sentence pair.
:param hypothesis: Hypothesis string.
:param reference: Reference string.
:param order: Maximum n-gram order.
:param remove_whitespace: Whether to delete whitespaces from hypothesis and reference strings.
:param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.
:return: Chrf score.
"""
statistics = get_sentence_statistics(hypothesis, reference, order=order, remove_whitespace=remove_whitespace)
avg_precision, avg_recall = _avg_precision_and_recall(statistics, order)
return CHRF(_chrf(avg_precision, avg_recall, beta=beta))
def get_langpairs_for_testset(testset: str) -> List:
"""Return a list of language pairs for a given test set."""
return list(filter(lambda x: re.match('\w\w\-\w\w', x), DATASETS.get(testset, {}).keys()))
def get_a_list_of_testset_names() -> str:
"""Return a string with a formatted list of available test sets plus their descriptions. """
message = 'The available test sets are:'
for testset in sorted(DATASETS.keys(), reverse=True):
message += '\n%20s: %s' % (testset, DATASETS[testset].get('description', ''))
return message
def _available_origlangs(test_sets, langpair):
"""Return a list of origlang values in according to the raw SGM files."""
origlangs = set()
for test_set in test_sets.split(','):
rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[test_set][langpair][0])
if rawfile.endswith('.sgm'):
with smart_open(rawfile) as fin:
for line in fin:
if line.startswith('<doc '):
doc_origlang = re.sub(r'.* origlang="([^"]+)".*\n', '\\1', line)
origlangs.add(doc_origlang)
return sorted(list(origlangs))
def _filter_subset(systems, test_sets, langpair, origlang, subset=None):
"""Filter sentences with a given origlang (or subset) according to the raw SGM files."""
if origlang is None and subset is None:
return systems
if test_sets is None or langpair is None:
raise ValueError('Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).')
indices_to_keep = []
for test_set in test_sets.split(','):
rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[test_set][langpair][0])
if not rawfile.endswith('.sgm'):
raise Exception('--origlang and --subset supports only *.sgm files, not %s', rawfile)
if subset is not None:
if test_set not in SUBSETS:
raise Exception('No subset annotation available for test set ' + test_set)
doc_to_tags = SUBSETS[test_set]
number_sentences_included = 0
with smart_open(rawfile) as fin:
include_doc = False
for line in fin:
if line.startswith('<doc '):
if origlang is None:
include_doc = True
else:
doc_origlang = re.sub(r'.* origlang="([^"]+)".*\n', '\\1', line)
if origlang.startswith('non-'):
include_doc = doc_origlang != origlang[4:]
else:
include_doc = doc_origlang == origlang
if subset is not None:
doc_id = re.sub(r'.* docid="([^"]+)".*\n', '\\1', line)
if not re.search(subset, doc_to_tags.get(doc_id, '')):
include_doc = False
if line.startswith('<seg '):
indices_to_keep.append(include_doc)
number_sentences_included += 1 if include_doc else 0
return [[sentence for sentence,keep in zip(sys, indices_to_keep) if keep] for sys in systems]
def main():
args = parse_args()
# Explicitly set the encoding
sys.stdin = open(sys.stdin.fileno(), mode='r', encoding='utf-8', buffering=True, newline="\n")
sys.stdout = open(sys.stdout.fileno(), mode='w', encoding='utf-8', buffering=True)
if not args.quiet:
logging.basicConfig(level=logging.INFO, format='sacreBLEU: %(message)s')
if args.download:
download_test_set(args.download, args.langpair)
sys.exit(0)
if args.list:
if args.test_set:
print(' '.join(get_langpairs_for_testset(args.test_set)))
else:
print(get_a_list_of_testset_names())
sys.exit(0)
if args.sentence_level and len(args.metrics) > 1:
sacrelogger.error('Only one metric can be used with Sentence-level reporting.')
sys.exit(1)
if args.citation:
if not args.test_set:
sacrelogger.error('I need a test set (-t).')
sys.exit(1)
for test_set in args.test_set.split(','):
if 'citation' not in DATASETS[test_set]:
sacrelogger.error('No citation found for %s', test_set)
else:
print(DATASETS[test_set]['citation'])
sys.exit(0)
if args.num_refs != 1 and (args.test_set is not None or len(args.refs) > 1):
sacrelogger.error('The --num-refs argument allows you to provide any number of tab-delimited references in a single file.')
sacrelogger.error('You can only use it with externaly-provided references, however (i.e., not with `-t`),')
sacrelogger.error('and you cannot then provide multiple reference files.')
sys.exit(1)
if args.test_set is not None:
for test_set in args.test_set.split(','):
if test_set not in DATASETS:
sacrelogger.error('Unknown test set "%s"\n%s', test_set, get_a_list_of_testset_names())
sys.exit(1)
if args.test_set is None:
if len(args.refs) == 0:
sacrelogger.error('I need either a predefined test set (-t) or a list of references')
sacrelogger.error(get_a_list_of_testset_names())
sys.exit(1)
elif len(args.refs) > 0:
sacrelogger.error('I need exactly one of (a) a predefined test set (-t) or (b) a list of references')
sys.exit(1)
elif args.langpair is None:
sacrelogger.error('I need a language pair (-l).')
sys.exit(1)
else:
for test_set in args.test_set.split(','):
if args.langpair not in DATASETS[test_set]:
sacrelogger.error('No such language pair "%s"', args.langpair)
sacrelogger.error('Available language pairs for test set "%s": %s', test_set,
', '.join(x for x in DATASETS[test_set].keys() if '-' in x))
sys.exit(1)
if args.echo:
if args.langpair is None or args.test_set is None:
sacrelogger.warning("--echo requires a test set (--t) and a language pair (-l)")
sys.exit(1)
for test_set in args.test_set.split(','):
print_test_set(test_set, args.langpair, args.echo, args.origlang, args.subset)
sys.exit(0)
if args.test_set is not None and args.tokenize == 'none':
sacrelogger.warning("You are turning off sacrebleu's internal tokenization ('--tokenize none'), presumably to supply\n"
"your own reference tokenization. Published numbers will not be comparable with other papers.\n")
# Internal tokenizer settings. Set to 'zh' for Chinese DEFAULT_TOKENIZER (
if args.tokenize is None:
# set default
if args.langpair is not None and args.langpair.split('-')[1] == 'zh':
args.tokenize = 'zh'
elif args.langpair is not None and args.langpair.split('-')[1] == 'ja':
args.tokenize = 'ja-mecab'
else:
args.tokenize = DEFAULT_TOKENIZER
if args.langpair is not None and 'bleu' in args.metrics:
if args.langpair.split('-')[1] == 'zh' and args.tokenize != 'zh':
logger.warning('You should also pass "--tok zh" when scoring Chinese...')
if args.langpair.split('-')[1] == 'ja' and not args.tokenize.startswith('ja-'):
logger.warning('You should also pass "--tok ja-mecab" when scoring Japanese...')
# concat_ref_files is a list of list of reference filenames, for example:
# concat_ref_files = [[testset1_refA, testset1_refB], [testset2_refA, testset2_refB]]
if args.test_set is None:
concat_ref_files = [args.refs]
else:
concat_ref_files = []
for test_set in args.test_set.split(','):
_, *ref_files = download_test_set(test_set, args.langpair)
if len(ref_files) == 0:
sacrelogger.warning('No references found for test set {}/{}.'.format(test_set, args.langpair))
concat_ref_files.append(ref_files)
inputfh = io.TextIOWrapper(sys.stdin.buffer, encoding=args.encoding) if args.input == '-' else smart_open(args.input, encoding=args.encoding)
full_system = inputfh.readlines()
# Read references
full_refs = [[] for x in range(max(len(concat_ref_files[0]), args.num_refs))]
for ref_files in concat_ref_files:
for refno, ref_file in enumerate(ref_files):
for lineno, line in enumerate(smart_open(ref_file, encoding=args.encoding), 1):
if args.num_refs != 1:
splits = line.rstrip().split(sep='\t', maxsplit=args.num_refs-1)
if len(splits) != args.num_refs:
sacrelogger.error('FATAL: line {}: expected {} fields, but found {}.'.format(lineno, args.num_refs, len(splits)))
sys.exit(17)
for refno, split in enumerate(splits):
full_refs[refno].append(split)
else:
full_refs[refno].append(line)
# Filter sentences according to a given origlang
system, *refs = _filter_subset([full_system, *full_refs], args.test_set, args.langpair, args.origlang, args.subset)
if len(system) == 0:
message = 'Test set %s contains no sentence' % args.test_set
if args.origlang is not None or args.subset is not None:
message += ' with'
message += '' if args.origlang is None else ' origlang=' + args.origlang
message += '' if args.subset is None else ' subset=' + args.subset
sacrelogger.error(message)
exit(1)
# Handle sentence level and quit
if args.sentence_level:
for output, *references in zip(system, *refs):
results = []
for metric in args.metrics:
if metric == 'bleu':
bleu = sentence_bleu(output,
[[x] for x in references],
smooth_method=args.smooth,
smooth_value=args.smooth_value)
results.append(bleu)
if metric == 'chrf':
chrf = sentence_chrf(output,
references[0],
args.chrf_order,
args.chrf_beta,
remove_whitespace=not args.chrf_whitespace)
results.append(chrf)
display_metric(args.metrics, results, len(refs), args)
sys.exit(0)
# Else, handle system level
results = []
try:
for metric in args.metrics:
if metric == 'bleu':
bleu = corpus_bleu(system, refs, smooth_method=args.smooth, smooth_value=args.smooth_value, force=args.force, lowercase=args.lc, tokenize=args.tokenize)
results.append(bleu)
elif metric == 'chrf':
chrf = corpus_chrf(system, refs[0], beta=args.chrf_beta, order=args.chrf_order, remove_whitespace=not args.chrf_whitespace)
results.append(chrf)
except EOFError:
sacrelogger.error('The input and reference stream(s) were of different lengths.')
if args.test_set is not None:
sacrelogger.error('\nThis could be a problem with your system output or with sacreBLEU\'s reference database.\n'
'If the latter, you can clean out the references cache by typing:\n'
'\n'
' rm -r %s/%s\n'
'\n'
'They will be downloaded automatically again the next time you run sacreBLEU.', SACREBLEU_DIR,
args.test_set)
sys.exit(1)
display_metric(args.metrics, results, len(refs), args)
if args.detail:
width = args.width
sents_digits = len(str(len(full_system)))
origlangs = args.origlang if args.origlang else _available_origlangs(args.test_set, args.langpair)
for origlang in origlangs:
subsets = [None]
if args.subset is not None:
subsets += [args.subset]
elif all(t in SUBSETS for t in args.test_set.split(',')):
subsets += COUNTRIES + DOMAINS
for subset in subsets:
system, *refs = _filter_subset([full_system, *full_refs], args.test_set, args.langpair, origlang, subset)
if len(system) == 0:
continue
if subset in COUNTRIES:
subset_str = '%20s' % ('country=' + subset)
elif subset in DOMAINS:
subset_str = '%20s' % ('domain=' + subset)
else:
subset_str = '%20s' % ''
if 'bleu' in args.metrics:
bleu = corpus_bleu(system, refs, smooth_method=args.smooth, smooth_value=args.smooth_value, force=args.force, lowercase=args.lc, tokenize=args.tokenize)
print('origlang={} {}: sentences={:{}} BLEU={:{}.{}f}'.format(origlang, subset_str, len(system), sents_digits, bleu.score, width+4, width))
if 'chrf' in args.metrics:
chrf = corpus_chrf(system, refs[0], beta=args.chrf_beta, order=args.chrf_order, remove_whitespace=not args.chrf_whitespace)
print('origlang={} {}: sentences={:{}} chrF={:{}.{}f}'.format(origlang, subset_str, len(system), sents_digits, chrf.score, width+4, width))
def display_metric(metrics_to_print, results, num_refs, args):
"""
Badly in need of refactoring.
One idea is to put all of this in the BLEU and CHRF classes, and then define
a Result::signature() function.
"""
for metric, result in zip(metrics_to_print, results):
if metric == 'bleu':
if args.score_only:
print('{0:.{1}f}'.format(result.score, args.width))
else:
version_str = bleu_signature(args, num_refs)
print(result.format(args.width).replace('BLEU', 'BLEU+' + version_str))
elif metric == 'chrf':
if args.score_only:
print('{0:.{1}f}'.format(result.score, args.width))
else:
version_str = chrf_signature(args, num_refs)
print('chrF{0:d}+{1} = {2:.{3}f}'.format(args.chrf_beta, version_str, result.score, args.width))
def parse_args():
arg_parser = argparse.ArgumentParser(
description='sacreBLEU: Hassle-free computation of shareable BLEU scores.\n'
'Quick usage: score your detokenized output against WMT\'14 EN-DE:\n'
' cat output.detok.de | sacrebleu -t wmt14 -l en-de',
# epilog = 'Available test sets: ' + ','.join(sorted(DATASETS.keys(), reverse=True)),
formatter_class=argparse.RawDescriptionHelpFormatter)
arg_parser.add_argument('--test-set', '-t', type=str, default=None,
help='the test set to use (see also --list) or a comma-separated list of test sets to be concatenated')
arg_parser.add_argument('-lc', action='store_true', default=False,
help='Use case-insensitive BLEU (default: actual case)')
arg_parser.add_argument('--sentence-level', '-sl', action='store_true',
help='Output metric on each sentence.')
arg_parser.add_argument('--smooth', '-s', choices=['exp', 'floor', 'add-k', 'none'],
default='exp',
help='smoothing method: exponential decay (default), floor (increment zero counts), add-k (increment num/denom by k for n>1), or none')
arg_parser.add_argument('--smooth-value', '-sv', type=float, default=None,
help='The value to pass to the smoothing technique, only used for floor and add-k. Default floor: {}, add-k: {}.'.format(
SMOOTH_VALUE_DEFAULT['floor'], SMOOTH_VALUE_DEFAULT['add-k']))
arg_parser.add_argument('--tokenize', '-tok', choices=TOKENIZERS.keys(), default=None,
help='tokenization method to use')
arg_parser.add_argument('--language-pair', '-l', dest='langpair', default=None,
help='source-target language pair (2-char ISO639-1 codes)')
arg_parser.add_argument('--origlang', '-ol', dest='origlang', default=None,
help='use a subset of sentences with a given original language (2-char ISO639-1 codes), "non-" prefix means negation')
arg_parser.add_argument('--subset', dest='subset', default=None,
help='use a subset of sentences whose document annotation matches a give regex (see SUBSETS in the source code)')
arg_parser.add_argument('--download', type=str, default=None,
help='download a test set and quit')
arg_parser.add_argument('--echo', choices=['src', 'ref', 'both'], type=str, default=None,
help='output the source (src), reference (ref), or both (both, pasted) to STDOUT and quit')
arg_parser.add_argument('--input', '-i', type=str, default='-',
help='Read input from a file instead of STDIN')
arg_parser.add_argument('--num-refs', '-nr', type=int, default=1,
help='Split the reference stream on tabs, and expect this many references. Default: %(default)s.')
arg_parser.add_argument('refs', nargs='*', default=[],
help='optional list of references (for backwards-compatibility with older scripts)')
arg_parser.add_argument('--metrics', '-m', choices=['bleu', 'chrf'], nargs='+',
default=['bleu'],
help='metrics to compute (default: bleu)')
arg_parser.add_argument('--chrf-order', type=int, default=CHRF_ORDER,
help='chrf character order (default: %(default)s)')
arg_parser.add_argument('--chrf-beta', type=int, default=CHRF_BETA,
help='chrf BETA parameter (default: %(default)s)')
arg_parser.add_argument('--chrf-whitespace', action='store_true', default=False,
help='include whitespace in chrF calculation (default: %(default)s)')
arg_parser.add_argument('--short', default=False, action='store_true',
help='produce a shorter (less human readable) signature')
arg_parser.add_argument('--score-only', '-b', default=False, action='store_true',
help='output only the BLEU score')
arg_parser.add_argument('--force', default=False, action='store_true',
help='insist that your tokenized input is actually detokenized')
arg_parser.add_argument('--quiet', '-q', default=False, action='store_true',
help='suppress informative output')
arg_parser.add_argument('--encoding', '-e', type=str, default='utf-8',
help='open text files with specified encoding (default: %(default)s)')
arg_parser.add_argument('--list', default=False, action='store_true',
help='print a list of all available test sets.')
arg_parser.add_argument('--citation', '--cite', default=False, action='store_true',
help='dump the bibtex citation and quit.')
arg_parser.add_argument('--width', '-w', type=int, default=1,
help='floating point width (default: %(default)s)')
arg_parser.add_argument('--detail', '-d', default=False, action='store_true',
help='print extra information (split test sets based on origlang)')
arg_parser.add_argument('-V', '--version', action='version',
version='%(prog)s {}'.format(VERSION))
args = arg_parser.parse_args()
return args
if __name__ == '__main__':
main()
|
normal
|
{
"blob_id": "8adcd75e925fe0c5a50b2fc7dc8c472a9610b4f2",
"index": 9575,
"step-1": "<mask token>\n\n\ndef smart_open(file, mode='rt', encoding='utf-8'):\n \"\"\"Convenience function for reading compressed or plain text files.\n :param file: The file to read.\n :param mode: The file mode (read, write).\n :param encoding: The file encoding.\n \"\"\"\n if file.endswith('.gz'):\n return gzip.open(file, mode=mode, encoding=encoding, newline='\\n')\n return open(file, mode=mode, encoding=encoding, newline='\\n')\n\n\ndef my_log(num):\n \"\"\"\n Floors the log function\n\n :param num: the number\n :return: log(num) floored to a very low number\n \"\"\"\n if num == 0.0:\n return -9999999999\n return math.log(num)\n\n\ndef bleu_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'smooth': 's', 'case': 'c', 'tok':\n 'tok', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'tok': args.tokenize, 'version': VERSION, 'smooth': args.\n smooth, 'numrefs': numrefs, 'case': 'lc' if args.lc else 'mixed'}\n if args.tokenize == 'ja-mecab':\n signature['tok'] += '-' + TokenizeMeCab().signature()\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\ndef chrf_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the chrF signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'numchars': 'n', 'space': 's', 'case':\n 'c', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'version': VERSION, 'space': args.chrf_whitespace,\n 'numchars': args.chrf_order, 'numrefs': numrefs, 'case': 'lc' if\n args.lc else 'mixed'}\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\n<mask token>\n\n\ndef extract_char_ngrams(s: str, n: int) ->Counter:\n \"\"\"\n Yields counts of character n-grams from string s of order n.\n \"\"\"\n return Counter([s[i:i + n] for i in range(len(s) - n + 1)])\n\n\ndef ref_stats(output, refs):\n ngrams = Counter()\n closest_diff = None\n closest_len = None\n for ref in refs:\n tokens = ref.split()\n reflen = len(tokens)\n diff = abs(len(output.split()) - reflen)\n if closest_diff is None or diff < closest_diff:\n closest_diff = diff\n closest_len = reflen\n elif diff == closest_diff:\n if reflen < closest_len:\n closest_len = reflen\n ngrams_ref = extract_ngrams(ref)\n for ngram in ngrams_ref.keys():\n ngrams[ngram] = max(ngrams[ngram], ngrams_ref[ngram])\n return ngrams, closest_diff, closest_len\n\n\ndef _clean(s):\n \"\"\"\n Removes trailing and leading spaces and collapses multiple consecutive internal spaces to a single one.\n\n :param s: The string.\n :return: A cleaned-up string.\n \"\"\"\n return re.sub('\\\\s+', ' ', s.strip())\n\n\ndef process_to_text(rawfile, txtfile, field: int=None):\n \"\"\"Processes raw files to plain text files.\n :param rawfile: the input file (possibly SGML)\n :param txtfile: the plaintext file\n :param field: For TSV files, which field to extract.\n \"\"\"\n if not os.path.exists(txtfile) or os.path.getsize(txtfile) == 0:\n sacrelogger.info('Processing %s to %s', rawfile, txtfile)\n if rawfile.endswith('.sgm') or rawfile.endswith('.sgml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.xml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.txt'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip(), file=fout)\n elif rawfile.endswith('.tsv'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip().split('\\t')[field], file=fout)\n\n\ndef print_test_set(test_set, langpair, side, origlang=None, subset=None):\n \"\"\"Prints to STDOUT the specified side of the specified test set\n :param test_set: the test set to print\n :param langpair: the language pair\n :param side: 'src' for source, 'ref' for reference\n :param origlang: print only sentences with a given original language (2-char ISO639-1 code), \"non-\" prefix means negation\n :param subset: print only sentences whose document annotation matches a given regex\n \"\"\"\n files = download_test_set(test_set, langpair)\n if side == 'src':\n files = [files[0]]\n elif side == 'ref':\n files.pop(0)\n streams = [smart_open(file) for file in files]\n streams = _filter_subset(streams, test_set, langpair, origlang, subset)\n for lines in zip(*streams):\n print('\\t'.join(map(lambda x: x.rstrip(), lines)))\n\n\n<mask token>\n\n\nclass Result:\n\n def __init__(self, score: float):\n self.score = score\n\n def __str__(self):\n return self.format()\n\n\nclass BLEU(Result):\n\n def __init__(self, score: float, counts, totals, precisions, bp,\n sys_len, ref_len):\n super().__init__(score)\n self.counts = counts\n self.totals = totals\n self.precisions = precisions\n self.bp = bp\n self.sys_len = sys_len\n self.ref_len = ref_len\n\n def format(self, width=2):\n precisions = '/'.join(['{:.1f}'.format(p) for p in self.precisions])\n return (\n 'BLEU = {score:.{width}f} {precisions} (BP = {bp:.3f} ratio = {ratio:.3f} hyp_len = {sys_len:d} ref_len = {ref_len:d})'\n .format(score=self.score, width=width, precisions=precisions,\n bp=self.bp, ratio=self.sys_len / self.ref_len, sys_len=self.\n sys_len, ref_len=self.ref_len))\n\n\nclass CHRF(Result):\n\n def __init__(self, score: float):\n super().__init__(score)\n\n def format(self, width=2):\n return '{score:.{width}f}'.format(score=self.score, width=width)\n\n\n<mask token>\n\n\ndef corpus_bleu(sys_stream: Union[str, Iterable[str]], ref_streams: Union[\n str, List[Iterable[str]]], smooth_method='exp', smooth_value=None,\n force=False, lowercase=False, tokenize=DEFAULT_TOKENIZER,\n use_effective_order=False) ->BLEU:\n \"\"\"Produces BLEU scores along with its sufficient statistics from a source against one or more references.\n\n :param sys_stream: The system stream (a sequence of segments)\n :param ref_streams: A list of one or more reference streams (each a sequence of segments)\n :param smooth: The smoothing method to use\n :param smooth_value: For 'floor' smoothing, the floor to use\n :param force: Ignore data that looks already tokenized\n :param lowercase: Lowercase the data\n :param tokenize: The tokenizer to use\n :return: a BLEU object containing everything you'd want\n \"\"\"\n if isinstance(sys_stream, str):\n sys_stream = [sys_stream]\n if isinstance(ref_streams, str):\n ref_streams = [[ref_streams]]\n sys_len = 0\n ref_len = 0\n correct = [(0) for n in range(NGRAM_ORDER)]\n total = [(0) for n in range(NGRAM_ORDER)]\n tokenized_count = 0\n fhs = [sys_stream] + ref_streams\n for lines in zip_longest(*fhs):\n if None in lines:\n raise EOFError(\n 'Source and reference streams have different lengths!')\n if lowercase:\n lines = [x.lower() for x in lines]\n if not (force or tokenize == 'none') and lines[0].rstrip().endswith(\n ' .'):\n tokenized_count += 1\n if tokenized_count == 100:\n sacrelogger.warning(\n \"That's 100 lines that end in a tokenized period ('.')\")\n sacrelogger.warning(\n 'It looks like you forgot to detokenize your test data, which may hurt your score.'\n )\n sacrelogger.warning(\n \"If you insist your data is detokenized, or don't care, you can suppress this message with '--force'.\"\n )\n output, *refs = [TOKENIZERS[tokenize](x.rstrip()) for x in lines]\n ref_ngrams, closest_diff, closest_len = ref_stats(output, refs)\n sys_len += len(output.split())\n ref_len += closest_len\n sys_ngrams = extract_ngrams(output)\n for ngram in sys_ngrams.keys():\n n = len(ngram.split())\n correct[n - 1] += min(sys_ngrams[ngram], ref_ngrams.get(ngram, 0))\n total[n - 1] += sys_ngrams[ngram]\n return compute_bleu(correct, total, sys_len, ref_len, smooth_method=\n smooth_method, smooth_value=smooth_value, use_effective_order=\n use_effective_order)\n\n\ndef raw_corpus_bleu(sys_stream, ref_streams, smooth_value=None) ->BLEU:\n \"\"\"Convenience function that wraps corpus_bleu().\n This is convenient if you're using sacrebleu as a library, say for scoring on dev.\n It uses no tokenization and 'floor' smoothing, with the floor default to 0 (no smoothing).\n\n :param sys_stream: the system stream (a sequence of segments)\n :param ref_streams: a list of one or more reference streams (each a sequence of segments)\n \"\"\"\n return corpus_bleu(sys_stream, ref_streams, smooth_method='floor',\n smooth_value=smooth_value, force=True, tokenize='none',\n use_effective_order=True)\n\n\ndef delete_whitespace(text: str) ->str:\n \"\"\"\n Removes whitespaces from text.\n \"\"\"\n return re.sub('\\\\s+', '', text).strip()\n\n\n<mask token>\n\n\ndef _chrf(avg_precision, avg_recall, beta: int=CHRF_BETA) ->float:\n if avg_precision + avg_recall == 0:\n return 0.0\n beta_square = beta ** 2\n score = (1 + beta_square) * (avg_precision * avg_recall) / (beta_square *\n avg_precision + avg_recall)\n return score\n\n\ndef corpus_chrf(hypotheses: Iterable[str], references: Iterable[str], order:\n int=CHRF_ORDER, beta: float=CHRF_BETA, remove_whitespace: bool=True\n ) ->CHRF:\n \"\"\"\n Computes Chrf on a corpus.\n\n :param hypotheses: Stream of hypotheses.\n :param references: Stream of references\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete all whitespace from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n corpus_statistics = get_corpus_statistics(hypotheses, references, order\n =order, remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(corpus_statistics,\n order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\n<mask token>\n\n\ndef get_langpairs_for_testset(testset: str) ->List:\n \"\"\"Return a list of language pairs for a given test set.\"\"\"\n return list(filter(lambda x: re.match('\\\\w\\\\w\\\\-\\\\w\\\\w', x), DATASETS.\n get(testset, {}).keys()))\n\n\ndef get_a_list_of_testset_names() ->str:\n \"\"\"Return a string with a formatted list of available test sets plus their descriptions. \"\"\"\n message = 'The available test sets are:'\n for testset in sorted(DATASETS.keys(), reverse=True):\n message += '\\n%20s: %s' % (testset, DATASETS[testset].get(\n 'description', ''))\n return message\n\n\n<mask token>\n\n\ndef _filter_subset(systems, test_sets, langpair, origlang, subset=None):\n \"\"\"Filter sentences with a given origlang (or subset) according to the raw SGM files.\"\"\"\n if origlang is None and subset is None:\n return systems\n if test_sets is None or langpair is None:\n raise ValueError(\n 'Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).'\n )\n indices_to_keep = []\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[\n test_set][langpair][0])\n if not rawfile.endswith('.sgm'):\n raise Exception(\n '--origlang and --subset supports only *.sgm files, not %s',\n rawfile)\n if subset is not None:\n if test_set not in SUBSETS:\n raise Exception(\n 'No subset annotation available for test set ' + test_set)\n doc_to_tags = SUBSETS[test_set]\n number_sentences_included = 0\n with smart_open(rawfile) as fin:\n include_doc = False\n for line in fin:\n if line.startswith('<doc '):\n if origlang is None:\n include_doc = True\n else:\n doc_origlang = re.sub('.* origlang=\"([^\"]+)\".*\\\\n',\n '\\\\1', line)\n if origlang.startswith('non-'):\n include_doc = doc_origlang != origlang[4:]\n else:\n include_doc = doc_origlang == origlang\n if subset is not None:\n doc_id = re.sub('.* docid=\"([^\"]+)\".*\\\\n', '\\\\1', line)\n if not re.search(subset, doc_to_tags.get(doc_id, '')):\n include_doc = False\n if line.startswith('<seg '):\n indices_to_keep.append(include_doc)\n number_sentences_included += 1 if include_doc else 0\n return [[sentence for sentence, keep in zip(sys, indices_to_keep) if\n keep] for sys in systems]\n\n\n<mask token>\n\n\ndef parse_args():\n arg_parser = argparse.ArgumentParser(description=\n \"\"\"sacreBLEU: Hassle-free computation of shareable BLEU scores.\nQuick usage: score your detokenized output against WMT'14 EN-DE:\n cat output.detok.de | sacrebleu -t wmt14 -l en-de\"\"\"\n , formatter_class=argparse.RawDescriptionHelpFormatter)\n arg_parser.add_argument('--test-set', '-t', type=str, default=None,\n help=\n 'the test set to use (see also --list) or a comma-separated list of test sets to be concatenated'\n )\n arg_parser.add_argument('-lc', action='store_true', default=False, help\n ='Use case-insensitive BLEU (default: actual case)')\n arg_parser.add_argument('--sentence-level', '-sl', action='store_true',\n help='Output metric on each sentence.')\n arg_parser.add_argument('--smooth', '-s', choices=['exp', 'floor',\n 'add-k', 'none'], default='exp', help=\n 'smoothing method: exponential decay (default), floor (increment zero counts), add-k (increment num/denom by k for n>1), or none'\n )\n arg_parser.add_argument('--smooth-value', '-sv', type=float, default=\n None, help=\n 'The value to pass to the smoothing technique, only used for floor and add-k. Default floor: {}, add-k: {}.'\n .format(SMOOTH_VALUE_DEFAULT['floor'], SMOOTH_VALUE_DEFAULT['add-k']))\n arg_parser.add_argument('--tokenize', '-tok', choices=TOKENIZERS.keys(),\n default=None, help='tokenization method to use')\n arg_parser.add_argument('--language-pair', '-l', dest='langpair',\n default=None, help=\n 'source-target language pair (2-char ISO639-1 codes)')\n arg_parser.add_argument('--origlang', '-ol', dest='origlang', default=\n None, help=\n 'use a subset of sentences with a given original language (2-char ISO639-1 codes), \"non-\" prefix means negation'\n )\n arg_parser.add_argument('--subset', dest='subset', default=None, help=\n 'use a subset of sentences whose document annotation matches a give regex (see SUBSETS in the source code)'\n )\n arg_parser.add_argument('--download', type=str, default=None, help=\n 'download a test set and quit')\n arg_parser.add_argument('--echo', choices=['src', 'ref', 'both'], type=\n str, default=None, help=\n 'output the source (src), reference (ref), or both (both, pasted) to STDOUT and quit'\n )\n arg_parser.add_argument('--input', '-i', type=str, default='-', help=\n 'Read input from a file instead of STDIN')\n arg_parser.add_argument('--num-refs', '-nr', type=int, default=1, help=\n 'Split the reference stream on tabs, and expect this many references. Default: %(default)s.'\n )\n arg_parser.add_argument('refs', nargs='*', default=[], help=\n 'optional list of references (for backwards-compatibility with older scripts)'\n )\n arg_parser.add_argument('--metrics', '-m', choices=['bleu', 'chrf'],\n nargs='+', default=['bleu'], help='metrics to compute (default: bleu)')\n arg_parser.add_argument('--chrf-order', type=int, default=CHRF_ORDER,\n help='chrf character order (default: %(default)s)')\n arg_parser.add_argument('--chrf-beta', type=int, default=CHRF_BETA,\n help='chrf BETA parameter (default: %(default)s)')\n arg_parser.add_argument('--chrf-whitespace', action='store_true',\n default=False, help=\n 'include whitespace in chrF calculation (default: %(default)s)')\n arg_parser.add_argument('--short', default=False, action='store_true',\n help='produce a shorter (less human readable) signature')\n arg_parser.add_argument('--score-only', '-b', default=False, action=\n 'store_true', help='output only the BLEU score')\n arg_parser.add_argument('--force', default=False, action='store_true',\n help='insist that your tokenized input is actually detokenized')\n arg_parser.add_argument('--quiet', '-q', default=False, action=\n 'store_true', help='suppress informative output')\n arg_parser.add_argument('--encoding', '-e', type=str, default='utf-8',\n help='open text files with specified encoding (default: %(default)s)')\n arg_parser.add_argument('--list', default=False, action='store_true',\n help='print a list of all available test sets.')\n arg_parser.add_argument('--citation', '--cite', default=False, action=\n 'store_true', help='dump the bibtex citation and quit.')\n arg_parser.add_argument('--width', '-w', type=int, default=1, help=\n 'floating point width (default: %(default)s)')\n arg_parser.add_argument('--detail', '-d', default=False, action=\n 'store_true', help=\n 'print extra information (split test sets based on origlang)')\n arg_parser.add_argument('-V', '--version', action='version', version=\n '%(prog)s {}'.format(VERSION))\n args = arg_parser.parse_args()\n return args\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef smart_open(file, mode='rt', encoding='utf-8'):\n \"\"\"Convenience function for reading compressed or plain text files.\n :param file: The file to read.\n :param mode: The file mode (read, write).\n :param encoding: The file encoding.\n \"\"\"\n if file.endswith('.gz'):\n return gzip.open(file, mode=mode, encoding=encoding, newline='\\n')\n return open(file, mode=mode, encoding=encoding, newline='\\n')\n\n\ndef my_log(num):\n \"\"\"\n Floors the log function\n\n :param num: the number\n :return: log(num) floored to a very low number\n \"\"\"\n if num == 0.0:\n return -9999999999\n return math.log(num)\n\n\ndef bleu_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'smooth': 's', 'case': 'c', 'tok':\n 'tok', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'tok': args.tokenize, 'version': VERSION, 'smooth': args.\n smooth, 'numrefs': numrefs, 'case': 'lc' if args.lc else 'mixed'}\n if args.tokenize == 'ja-mecab':\n signature['tok'] += '-' + TokenizeMeCab().signature()\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\ndef chrf_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the chrF signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'numchars': 'n', 'space': 's', 'case':\n 'c', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'version': VERSION, 'space': args.chrf_whitespace,\n 'numchars': args.chrf_order, 'numrefs': numrefs, 'case': 'lc' if\n args.lc else 'mixed'}\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\n<mask token>\n\n\ndef extract_char_ngrams(s: str, n: int) ->Counter:\n \"\"\"\n Yields counts of character n-grams from string s of order n.\n \"\"\"\n return Counter([s[i:i + n] for i in range(len(s) - n + 1)])\n\n\ndef ref_stats(output, refs):\n ngrams = Counter()\n closest_diff = None\n closest_len = None\n for ref in refs:\n tokens = ref.split()\n reflen = len(tokens)\n diff = abs(len(output.split()) - reflen)\n if closest_diff is None or diff < closest_diff:\n closest_diff = diff\n closest_len = reflen\n elif diff == closest_diff:\n if reflen < closest_len:\n closest_len = reflen\n ngrams_ref = extract_ngrams(ref)\n for ngram in ngrams_ref.keys():\n ngrams[ngram] = max(ngrams[ngram], ngrams_ref[ngram])\n return ngrams, closest_diff, closest_len\n\n\ndef _clean(s):\n \"\"\"\n Removes trailing and leading spaces and collapses multiple consecutive internal spaces to a single one.\n\n :param s: The string.\n :return: A cleaned-up string.\n \"\"\"\n return re.sub('\\\\s+', ' ', s.strip())\n\n\ndef process_to_text(rawfile, txtfile, field: int=None):\n \"\"\"Processes raw files to plain text files.\n :param rawfile: the input file (possibly SGML)\n :param txtfile: the plaintext file\n :param field: For TSV files, which field to extract.\n \"\"\"\n if not os.path.exists(txtfile) or os.path.getsize(txtfile) == 0:\n sacrelogger.info('Processing %s to %s', rawfile, txtfile)\n if rawfile.endswith('.sgm') or rawfile.endswith('.sgml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.xml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.txt'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip(), file=fout)\n elif rawfile.endswith('.tsv'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip().split('\\t')[field], file=fout)\n\n\ndef print_test_set(test_set, langpair, side, origlang=None, subset=None):\n \"\"\"Prints to STDOUT the specified side of the specified test set\n :param test_set: the test set to print\n :param langpair: the language pair\n :param side: 'src' for source, 'ref' for reference\n :param origlang: print only sentences with a given original language (2-char ISO639-1 code), \"non-\" prefix means negation\n :param subset: print only sentences whose document annotation matches a given regex\n \"\"\"\n files = download_test_set(test_set, langpair)\n if side == 'src':\n files = [files[0]]\n elif side == 'ref':\n files.pop(0)\n streams = [smart_open(file) for file in files]\n streams = _filter_subset(streams, test_set, langpair, origlang, subset)\n for lines in zip(*streams):\n print('\\t'.join(map(lambda x: x.rstrip(), lines)))\n\n\ndef download_test_set(test_set, langpair=None):\n \"\"\"Downloads the specified test to the system location specified by the SACREBLEU environment variable.\n\n :param test_set: the test set to download\n :param langpair: the language pair (needed for some datasets)\n :return: the set of processed files\n \"\"\"\n outdir = os.path.join(SACREBLEU_DIR, test_set)\n os.makedirs(outdir, exist_ok=True)\n expected_checksums = DATASETS[test_set].get('md5', [None] * len(\n DATASETS[test_set]))\n for dataset, expected_md5 in zip(DATASETS[test_set]['data'],\n expected_checksums):\n tarball = os.path.join(outdir, os.path.basename(dataset))\n rawdir = os.path.join(outdir, 'raw')\n lockfile = '{}.lock'.format(tarball)\n with portalocker.Lock(lockfile, 'w', timeout=60):\n if not os.path.exists(tarball) or os.path.getsize(tarball) == 0:\n sacrelogger.info('Downloading %s to %s', dataset, tarball)\n try:\n with urllib.request.urlopen(dataset) as f, open(tarball,\n 'wb') as out:\n out.write(f.read())\n except ssl.SSLError:\n sacrelogger.warning(\n 'An SSL error was encountered in downloading the files. If you\\'re on a Mac, you may need to run the \"Install Certificates.command\" file located in the \"Python 3\" folder, often found under /Applications'\n )\n sys.exit(1)\n if expected_md5 is not None:\n md5 = hashlib.md5()\n with open(tarball, 'rb') as infile:\n for line in infile:\n md5.update(line)\n if md5.hexdigest() != expected_md5:\n sacrelogger.error(\n 'Fatal: MD5 sum of downloaded file was incorrect (got {}, expected {}).'\n .format(md5.hexdigest(), expected_md5))\n sacrelogger.error(\n 'Please manually delete \"{}\" and rerun the command.'\n .format(tarball))\n sacrelogger.error(\n 'If the problem persists, the tarball may have changed, in which case, please contact the SacreBLEU maintainer.'\n )\n sys.exit(1)\n else:\n sacrelogger.info('Checksum passed: {}'.format(md5.\n hexdigest()))\n sacrelogger.info('Extracting %s', tarball)\n if tarball.endswith('.tar.gz') or tarball.endswith('.tgz'):\n import tarfile\n with tarfile.open(tarball) as tar:\n tar.extractall(path=rawdir)\n elif tarball.endswith('.zip'):\n import zipfile\n with zipfile.ZipFile(tarball, 'r') as zipfile:\n zipfile.extractall(path=rawdir)\n found = []\n languages = DATASETS[test_set].keys() if langpair is None else [langpair]\n for pair in languages:\n if '-' not in pair:\n continue\n src, tgt = pair.split('-')\n rawfile = DATASETS[test_set][pair][0]\n field = None\n if rawfile.endswith('.tsv'):\n field, rawfile = rawfile.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, rawfile)\n outpath = os.path.join(outdir, '{}.{}'.format(pair, src))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n refs = DATASETS[test_set][pair][1:]\n for i, ref in enumerate(refs):\n field = None\n if ref.endswith('.tsv'):\n field, ref = ref.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, ref)\n if len(refs) >= 2:\n outpath = os.path.join(outdir, '{}.{}.{}'.format(pair, tgt, i))\n else:\n outpath = os.path.join(outdir, '{}.{}'.format(pair, tgt))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n return found\n\n\nclass Result:\n\n def __init__(self, score: float):\n self.score = score\n\n def __str__(self):\n return self.format()\n\n\nclass BLEU(Result):\n\n def __init__(self, score: float, counts, totals, precisions, bp,\n sys_len, ref_len):\n super().__init__(score)\n self.counts = counts\n self.totals = totals\n self.precisions = precisions\n self.bp = bp\n self.sys_len = sys_len\n self.ref_len = ref_len\n\n def format(self, width=2):\n precisions = '/'.join(['{:.1f}'.format(p) for p in self.precisions])\n return (\n 'BLEU = {score:.{width}f} {precisions} (BP = {bp:.3f} ratio = {ratio:.3f} hyp_len = {sys_len:d} ref_len = {ref_len:d})'\n .format(score=self.score, width=width, precisions=precisions,\n bp=self.bp, ratio=self.sys_len / self.ref_len, sys_len=self.\n sys_len, ref_len=self.ref_len))\n\n\nclass CHRF(Result):\n\n def __init__(self, score: float):\n super().__init__(score)\n\n def format(self, width=2):\n return '{score:.{width}f}'.format(score=self.score, width=width)\n\n\n<mask token>\n\n\ndef sentence_bleu(hypothesis: str, references: List[str], smooth_method:\n str='floor', smooth_value: float=None, use_effective_order: bool=True\n ) ->BLEU:\n \"\"\"\n Computes BLEU on a single sentence pair.\n\n Disclaimer: computing BLEU on the sentence level is not its intended use,\n BLEU is a corpus-level metric.\n\n :param hypothesis: Hypothesis string.\n :param reference: Reference string.\n :param smooth_value: For 'floor' smoothing, the floor value to use.\n :param use_effective_order: Account for references that are shorter than the largest n-gram.\n :return: Returns a single BLEU score as a float.\n \"\"\"\n bleu = corpus_bleu(hypothesis, references, smooth_method=smooth_method,\n smooth_value=smooth_value, use_effective_order=use_effective_order)\n return bleu\n\n\ndef corpus_bleu(sys_stream: Union[str, Iterable[str]], ref_streams: Union[\n str, List[Iterable[str]]], smooth_method='exp', smooth_value=None,\n force=False, lowercase=False, tokenize=DEFAULT_TOKENIZER,\n use_effective_order=False) ->BLEU:\n \"\"\"Produces BLEU scores along with its sufficient statistics from a source against one or more references.\n\n :param sys_stream: The system stream (a sequence of segments)\n :param ref_streams: A list of one or more reference streams (each a sequence of segments)\n :param smooth: The smoothing method to use\n :param smooth_value: For 'floor' smoothing, the floor to use\n :param force: Ignore data that looks already tokenized\n :param lowercase: Lowercase the data\n :param tokenize: The tokenizer to use\n :return: a BLEU object containing everything you'd want\n \"\"\"\n if isinstance(sys_stream, str):\n sys_stream = [sys_stream]\n if isinstance(ref_streams, str):\n ref_streams = [[ref_streams]]\n sys_len = 0\n ref_len = 0\n correct = [(0) for n in range(NGRAM_ORDER)]\n total = [(0) for n in range(NGRAM_ORDER)]\n tokenized_count = 0\n fhs = [sys_stream] + ref_streams\n for lines in zip_longest(*fhs):\n if None in lines:\n raise EOFError(\n 'Source and reference streams have different lengths!')\n if lowercase:\n lines = [x.lower() for x in lines]\n if not (force or tokenize == 'none') and lines[0].rstrip().endswith(\n ' .'):\n tokenized_count += 1\n if tokenized_count == 100:\n sacrelogger.warning(\n \"That's 100 lines that end in a tokenized period ('.')\")\n sacrelogger.warning(\n 'It looks like you forgot to detokenize your test data, which may hurt your score.'\n )\n sacrelogger.warning(\n \"If you insist your data is detokenized, or don't care, you can suppress this message with '--force'.\"\n )\n output, *refs = [TOKENIZERS[tokenize](x.rstrip()) for x in lines]\n ref_ngrams, closest_diff, closest_len = ref_stats(output, refs)\n sys_len += len(output.split())\n ref_len += closest_len\n sys_ngrams = extract_ngrams(output)\n for ngram in sys_ngrams.keys():\n n = len(ngram.split())\n correct[n - 1] += min(sys_ngrams[ngram], ref_ngrams.get(ngram, 0))\n total[n - 1] += sys_ngrams[ngram]\n return compute_bleu(correct, total, sys_len, ref_len, smooth_method=\n smooth_method, smooth_value=smooth_value, use_effective_order=\n use_effective_order)\n\n\ndef raw_corpus_bleu(sys_stream, ref_streams, smooth_value=None) ->BLEU:\n \"\"\"Convenience function that wraps corpus_bleu().\n This is convenient if you're using sacrebleu as a library, say for scoring on dev.\n It uses no tokenization and 'floor' smoothing, with the floor default to 0 (no smoothing).\n\n :param sys_stream: the system stream (a sequence of segments)\n :param ref_streams: a list of one or more reference streams (each a sequence of segments)\n \"\"\"\n return corpus_bleu(sys_stream, ref_streams, smooth_method='floor',\n smooth_value=smooth_value, force=True, tokenize='none',\n use_effective_order=True)\n\n\ndef delete_whitespace(text: str) ->str:\n \"\"\"\n Removes whitespaces from text.\n \"\"\"\n return re.sub('\\\\s+', '', text).strip()\n\n\n<mask token>\n\n\ndef _chrf(avg_precision, avg_recall, beta: int=CHRF_BETA) ->float:\n if avg_precision + avg_recall == 0:\n return 0.0\n beta_square = beta ** 2\n score = (1 + beta_square) * (avg_precision * avg_recall) / (beta_square *\n avg_precision + avg_recall)\n return score\n\n\ndef corpus_chrf(hypotheses: Iterable[str], references: Iterable[str], order:\n int=CHRF_ORDER, beta: float=CHRF_BETA, remove_whitespace: bool=True\n ) ->CHRF:\n \"\"\"\n Computes Chrf on a corpus.\n\n :param hypotheses: Stream of hypotheses.\n :param references: Stream of references\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete all whitespace from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n corpus_statistics = get_corpus_statistics(hypotheses, references, order\n =order, remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(corpus_statistics,\n order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\n<mask token>\n\n\ndef get_langpairs_for_testset(testset: str) ->List:\n \"\"\"Return a list of language pairs for a given test set.\"\"\"\n return list(filter(lambda x: re.match('\\\\w\\\\w\\\\-\\\\w\\\\w', x), DATASETS.\n get(testset, {}).keys()))\n\n\ndef get_a_list_of_testset_names() ->str:\n \"\"\"Return a string with a formatted list of available test sets plus their descriptions. \"\"\"\n message = 'The available test sets are:'\n for testset in sorted(DATASETS.keys(), reverse=True):\n message += '\\n%20s: %s' % (testset, DATASETS[testset].get(\n 'description', ''))\n return message\n\n\n<mask token>\n\n\ndef _filter_subset(systems, test_sets, langpair, origlang, subset=None):\n \"\"\"Filter sentences with a given origlang (or subset) according to the raw SGM files.\"\"\"\n if origlang is None and subset is None:\n return systems\n if test_sets is None or langpair is None:\n raise ValueError(\n 'Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).'\n )\n indices_to_keep = []\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[\n test_set][langpair][0])\n if not rawfile.endswith('.sgm'):\n raise Exception(\n '--origlang and --subset supports only *.sgm files, not %s',\n rawfile)\n if subset is not None:\n if test_set not in SUBSETS:\n raise Exception(\n 'No subset annotation available for test set ' + test_set)\n doc_to_tags = SUBSETS[test_set]\n number_sentences_included = 0\n with smart_open(rawfile) as fin:\n include_doc = False\n for line in fin:\n if line.startswith('<doc '):\n if origlang is None:\n include_doc = True\n else:\n doc_origlang = re.sub('.* origlang=\"([^\"]+)\".*\\\\n',\n '\\\\1', line)\n if origlang.startswith('non-'):\n include_doc = doc_origlang != origlang[4:]\n else:\n include_doc = doc_origlang == origlang\n if subset is not None:\n doc_id = re.sub('.* docid=\"([^\"]+)\".*\\\\n', '\\\\1', line)\n if not re.search(subset, doc_to_tags.get(doc_id, '')):\n include_doc = False\n if line.startswith('<seg '):\n indices_to_keep.append(include_doc)\n number_sentences_included += 1 if include_doc else 0\n return [[sentence for sentence, keep in zip(sys, indices_to_keep) if\n keep] for sys in systems]\n\n\n<mask token>\n\n\ndef parse_args():\n arg_parser = argparse.ArgumentParser(description=\n \"\"\"sacreBLEU: Hassle-free computation of shareable BLEU scores.\nQuick usage: score your detokenized output against WMT'14 EN-DE:\n cat output.detok.de | sacrebleu -t wmt14 -l en-de\"\"\"\n , formatter_class=argparse.RawDescriptionHelpFormatter)\n arg_parser.add_argument('--test-set', '-t', type=str, default=None,\n help=\n 'the test set to use (see also --list) or a comma-separated list of test sets to be concatenated'\n )\n arg_parser.add_argument('-lc', action='store_true', default=False, help\n ='Use case-insensitive BLEU (default: actual case)')\n arg_parser.add_argument('--sentence-level', '-sl', action='store_true',\n help='Output metric on each sentence.')\n arg_parser.add_argument('--smooth', '-s', choices=['exp', 'floor',\n 'add-k', 'none'], default='exp', help=\n 'smoothing method: exponential decay (default), floor (increment zero counts), add-k (increment num/denom by k for n>1), or none'\n )\n arg_parser.add_argument('--smooth-value', '-sv', type=float, default=\n None, help=\n 'The value to pass to the smoothing technique, only used for floor and add-k. Default floor: {}, add-k: {}.'\n .format(SMOOTH_VALUE_DEFAULT['floor'], SMOOTH_VALUE_DEFAULT['add-k']))\n arg_parser.add_argument('--tokenize', '-tok', choices=TOKENIZERS.keys(),\n default=None, help='tokenization method to use')\n arg_parser.add_argument('--language-pair', '-l', dest='langpair',\n default=None, help=\n 'source-target language pair (2-char ISO639-1 codes)')\n arg_parser.add_argument('--origlang', '-ol', dest='origlang', default=\n None, help=\n 'use a subset of sentences with a given original language (2-char ISO639-1 codes), \"non-\" prefix means negation'\n )\n arg_parser.add_argument('--subset', dest='subset', default=None, help=\n 'use a subset of sentences whose document annotation matches a give regex (see SUBSETS in the source code)'\n )\n arg_parser.add_argument('--download', type=str, default=None, help=\n 'download a test set and quit')\n arg_parser.add_argument('--echo', choices=['src', 'ref', 'both'], type=\n str, default=None, help=\n 'output the source (src), reference (ref), or both (both, pasted) to STDOUT and quit'\n )\n arg_parser.add_argument('--input', '-i', type=str, default='-', help=\n 'Read input from a file instead of STDIN')\n arg_parser.add_argument('--num-refs', '-nr', type=int, default=1, help=\n 'Split the reference stream on tabs, and expect this many references. Default: %(default)s.'\n )\n arg_parser.add_argument('refs', nargs='*', default=[], help=\n 'optional list of references (for backwards-compatibility with older scripts)'\n )\n arg_parser.add_argument('--metrics', '-m', choices=['bleu', 'chrf'],\n nargs='+', default=['bleu'], help='metrics to compute (default: bleu)')\n arg_parser.add_argument('--chrf-order', type=int, default=CHRF_ORDER,\n help='chrf character order (default: %(default)s)')\n arg_parser.add_argument('--chrf-beta', type=int, default=CHRF_BETA,\n help='chrf BETA parameter (default: %(default)s)')\n arg_parser.add_argument('--chrf-whitespace', action='store_true',\n default=False, help=\n 'include whitespace in chrF calculation (default: %(default)s)')\n arg_parser.add_argument('--short', default=False, action='store_true',\n help='produce a shorter (less human readable) signature')\n arg_parser.add_argument('--score-only', '-b', default=False, action=\n 'store_true', help='output only the BLEU score')\n arg_parser.add_argument('--force', default=False, action='store_true',\n help='insist that your tokenized input is actually detokenized')\n arg_parser.add_argument('--quiet', '-q', default=False, action=\n 'store_true', help='suppress informative output')\n arg_parser.add_argument('--encoding', '-e', type=str, default='utf-8',\n help='open text files with specified encoding (default: %(default)s)')\n arg_parser.add_argument('--list', default=False, action='store_true',\n help='print a list of all available test sets.')\n arg_parser.add_argument('--citation', '--cite', default=False, action=\n 'store_true', help='dump the bibtex citation and quit.')\n arg_parser.add_argument('--width', '-w', type=int, default=1, help=\n 'floating point width (default: %(default)s)')\n arg_parser.add_argument('--detail', '-d', default=False, action=\n 'store_true', help=\n 'print extra information (split test sets based on origlang)')\n arg_parser.add_argument('-V', '--version', action='version', version=\n '%(prog)s {}'.format(VERSION))\n args = arg_parser.parse_args()\n return args\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef smart_open(file, mode='rt', encoding='utf-8'):\n \"\"\"Convenience function for reading compressed or plain text files.\n :param file: The file to read.\n :param mode: The file mode (read, write).\n :param encoding: The file encoding.\n \"\"\"\n if file.endswith('.gz'):\n return gzip.open(file, mode=mode, encoding=encoding, newline='\\n')\n return open(file, mode=mode, encoding=encoding, newline='\\n')\n\n\ndef my_log(num):\n \"\"\"\n Floors the log function\n\n :param num: the number\n :return: log(num) floored to a very low number\n \"\"\"\n if num == 0.0:\n return -9999999999\n return math.log(num)\n\n\ndef bleu_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'smooth': 's', 'case': 'c', 'tok':\n 'tok', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'tok': args.tokenize, 'version': VERSION, 'smooth': args.\n smooth, 'numrefs': numrefs, 'case': 'lc' if args.lc else 'mixed'}\n if args.tokenize == 'ja-mecab':\n signature['tok'] += '-' + TokenizeMeCab().signature()\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\ndef chrf_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the chrF signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'numchars': 'n', 'space': 's', 'case':\n 'c', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'version': VERSION, 'space': args.chrf_whitespace,\n 'numchars': args.chrf_order, 'numrefs': numrefs, 'case': 'lc' if\n args.lc else 'mixed'}\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\ndef extract_ngrams(line, min_order=1, max_order=NGRAM_ORDER) ->Counter:\n \"\"\"Extracts all the ngrams (min_order <= n <= max_order) from a sequence of tokens.\n\n :param line: A segment containing a sequence of words.\n :param min_order: Minimum n-gram length (default: 1).\n :param max_order: Maximum n-gram length (default: NGRAM_ORDER).\n :return: a dictionary containing ngrams and counts\n \"\"\"\n ngrams = Counter()\n tokens = line.split()\n for n in range(min_order, max_order + 1):\n for i in range(0, len(tokens) - n + 1):\n ngram = ' '.join(tokens[i:i + n])\n ngrams[ngram] += 1\n return ngrams\n\n\ndef extract_char_ngrams(s: str, n: int) ->Counter:\n \"\"\"\n Yields counts of character n-grams from string s of order n.\n \"\"\"\n return Counter([s[i:i + n] for i in range(len(s) - n + 1)])\n\n\ndef ref_stats(output, refs):\n ngrams = Counter()\n closest_diff = None\n closest_len = None\n for ref in refs:\n tokens = ref.split()\n reflen = len(tokens)\n diff = abs(len(output.split()) - reflen)\n if closest_diff is None or diff < closest_diff:\n closest_diff = diff\n closest_len = reflen\n elif diff == closest_diff:\n if reflen < closest_len:\n closest_len = reflen\n ngrams_ref = extract_ngrams(ref)\n for ngram in ngrams_ref.keys():\n ngrams[ngram] = max(ngrams[ngram], ngrams_ref[ngram])\n return ngrams, closest_diff, closest_len\n\n\ndef _clean(s):\n \"\"\"\n Removes trailing and leading spaces and collapses multiple consecutive internal spaces to a single one.\n\n :param s: The string.\n :return: A cleaned-up string.\n \"\"\"\n return re.sub('\\\\s+', ' ', s.strip())\n\n\ndef process_to_text(rawfile, txtfile, field: int=None):\n \"\"\"Processes raw files to plain text files.\n :param rawfile: the input file (possibly SGML)\n :param txtfile: the plaintext file\n :param field: For TSV files, which field to extract.\n \"\"\"\n if not os.path.exists(txtfile) or os.path.getsize(txtfile) == 0:\n sacrelogger.info('Processing %s to %s', rawfile, txtfile)\n if rawfile.endswith('.sgm') or rawfile.endswith('.sgml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.xml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.txt'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip(), file=fout)\n elif rawfile.endswith('.tsv'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip().split('\\t')[field], file=fout)\n\n\ndef print_test_set(test_set, langpair, side, origlang=None, subset=None):\n \"\"\"Prints to STDOUT the specified side of the specified test set\n :param test_set: the test set to print\n :param langpair: the language pair\n :param side: 'src' for source, 'ref' for reference\n :param origlang: print only sentences with a given original language (2-char ISO639-1 code), \"non-\" prefix means negation\n :param subset: print only sentences whose document annotation matches a given regex\n \"\"\"\n files = download_test_set(test_set, langpair)\n if side == 'src':\n files = [files[0]]\n elif side == 'ref':\n files.pop(0)\n streams = [smart_open(file) for file in files]\n streams = _filter_subset(streams, test_set, langpair, origlang, subset)\n for lines in zip(*streams):\n print('\\t'.join(map(lambda x: x.rstrip(), lines)))\n\n\ndef download_test_set(test_set, langpair=None):\n \"\"\"Downloads the specified test to the system location specified by the SACREBLEU environment variable.\n\n :param test_set: the test set to download\n :param langpair: the language pair (needed for some datasets)\n :return: the set of processed files\n \"\"\"\n outdir = os.path.join(SACREBLEU_DIR, test_set)\n os.makedirs(outdir, exist_ok=True)\n expected_checksums = DATASETS[test_set].get('md5', [None] * len(\n DATASETS[test_set]))\n for dataset, expected_md5 in zip(DATASETS[test_set]['data'],\n expected_checksums):\n tarball = os.path.join(outdir, os.path.basename(dataset))\n rawdir = os.path.join(outdir, 'raw')\n lockfile = '{}.lock'.format(tarball)\n with portalocker.Lock(lockfile, 'w', timeout=60):\n if not os.path.exists(tarball) or os.path.getsize(tarball) == 0:\n sacrelogger.info('Downloading %s to %s', dataset, tarball)\n try:\n with urllib.request.urlopen(dataset) as f, open(tarball,\n 'wb') as out:\n out.write(f.read())\n except ssl.SSLError:\n sacrelogger.warning(\n 'An SSL error was encountered in downloading the files. If you\\'re on a Mac, you may need to run the \"Install Certificates.command\" file located in the \"Python 3\" folder, often found under /Applications'\n )\n sys.exit(1)\n if expected_md5 is not None:\n md5 = hashlib.md5()\n with open(tarball, 'rb') as infile:\n for line in infile:\n md5.update(line)\n if md5.hexdigest() != expected_md5:\n sacrelogger.error(\n 'Fatal: MD5 sum of downloaded file was incorrect (got {}, expected {}).'\n .format(md5.hexdigest(), expected_md5))\n sacrelogger.error(\n 'Please manually delete \"{}\" and rerun the command.'\n .format(tarball))\n sacrelogger.error(\n 'If the problem persists, the tarball may have changed, in which case, please contact the SacreBLEU maintainer.'\n )\n sys.exit(1)\n else:\n sacrelogger.info('Checksum passed: {}'.format(md5.\n hexdigest()))\n sacrelogger.info('Extracting %s', tarball)\n if tarball.endswith('.tar.gz') or tarball.endswith('.tgz'):\n import tarfile\n with tarfile.open(tarball) as tar:\n tar.extractall(path=rawdir)\n elif tarball.endswith('.zip'):\n import zipfile\n with zipfile.ZipFile(tarball, 'r') as zipfile:\n zipfile.extractall(path=rawdir)\n found = []\n languages = DATASETS[test_set].keys() if langpair is None else [langpair]\n for pair in languages:\n if '-' not in pair:\n continue\n src, tgt = pair.split('-')\n rawfile = DATASETS[test_set][pair][0]\n field = None\n if rawfile.endswith('.tsv'):\n field, rawfile = rawfile.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, rawfile)\n outpath = os.path.join(outdir, '{}.{}'.format(pair, src))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n refs = DATASETS[test_set][pair][1:]\n for i, ref in enumerate(refs):\n field = None\n if ref.endswith('.tsv'):\n field, ref = ref.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, ref)\n if len(refs) >= 2:\n outpath = os.path.join(outdir, '{}.{}.{}'.format(pair, tgt, i))\n else:\n outpath = os.path.join(outdir, '{}.{}'.format(pair, tgt))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n return found\n\n\nclass Result:\n\n def __init__(self, score: float):\n self.score = score\n\n def __str__(self):\n return self.format()\n\n\nclass BLEU(Result):\n\n def __init__(self, score: float, counts, totals, precisions, bp,\n sys_len, ref_len):\n super().__init__(score)\n self.counts = counts\n self.totals = totals\n self.precisions = precisions\n self.bp = bp\n self.sys_len = sys_len\n self.ref_len = ref_len\n\n def format(self, width=2):\n precisions = '/'.join(['{:.1f}'.format(p) for p in self.precisions])\n return (\n 'BLEU = {score:.{width}f} {precisions} (BP = {bp:.3f} ratio = {ratio:.3f} hyp_len = {sys_len:d} ref_len = {ref_len:d})'\n .format(score=self.score, width=width, precisions=precisions,\n bp=self.bp, ratio=self.sys_len / self.ref_len, sys_len=self.\n sys_len, ref_len=self.ref_len))\n\n\nclass CHRF(Result):\n\n def __init__(self, score: float):\n super().__init__(score)\n\n def format(self, width=2):\n return '{score:.{width}f}'.format(score=self.score, width=width)\n\n\n<mask token>\n\n\ndef sentence_bleu(hypothesis: str, references: List[str], smooth_method:\n str='floor', smooth_value: float=None, use_effective_order: bool=True\n ) ->BLEU:\n \"\"\"\n Computes BLEU on a single sentence pair.\n\n Disclaimer: computing BLEU on the sentence level is not its intended use,\n BLEU is a corpus-level metric.\n\n :param hypothesis: Hypothesis string.\n :param reference: Reference string.\n :param smooth_value: For 'floor' smoothing, the floor value to use.\n :param use_effective_order: Account for references that are shorter than the largest n-gram.\n :return: Returns a single BLEU score as a float.\n \"\"\"\n bleu = corpus_bleu(hypothesis, references, smooth_method=smooth_method,\n smooth_value=smooth_value, use_effective_order=use_effective_order)\n return bleu\n\n\ndef corpus_bleu(sys_stream: Union[str, Iterable[str]], ref_streams: Union[\n str, List[Iterable[str]]], smooth_method='exp', smooth_value=None,\n force=False, lowercase=False, tokenize=DEFAULT_TOKENIZER,\n use_effective_order=False) ->BLEU:\n \"\"\"Produces BLEU scores along with its sufficient statistics from a source against one or more references.\n\n :param sys_stream: The system stream (a sequence of segments)\n :param ref_streams: A list of one or more reference streams (each a sequence of segments)\n :param smooth: The smoothing method to use\n :param smooth_value: For 'floor' smoothing, the floor to use\n :param force: Ignore data that looks already tokenized\n :param lowercase: Lowercase the data\n :param tokenize: The tokenizer to use\n :return: a BLEU object containing everything you'd want\n \"\"\"\n if isinstance(sys_stream, str):\n sys_stream = [sys_stream]\n if isinstance(ref_streams, str):\n ref_streams = [[ref_streams]]\n sys_len = 0\n ref_len = 0\n correct = [(0) for n in range(NGRAM_ORDER)]\n total = [(0) for n in range(NGRAM_ORDER)]\n tokenized_count = 0\n fhs = [sys_stream] + ref_streams\n for lines in zip_longest(*fhs):\n if None in lines:\n raise EOFError(\n 'Source and reference streams have different lengths!')\n if lowercase:\n lines = [x.lower() for x in lines]\n if not (force or tokenize == 'none') and lines[0].rstrip().endswith(\n ' .'):\n tokenized_count += 1\n if tokenized_count == 100:\n sacrelogger.warning(\n \"That's 100 lines that end in a tokenized period ('.')\")\n sacrelogger.warning(\n 'It looks like you forgot to detokenize your test data, which may hurt your score.'\n )\n sacrelogger.warning(\n \"If you insist your data is detokenized, or don't care, you can suppress this message with '--force'.\"\n )\n output, *refs = [TOKENIZERS[tokenize](x.rstrip()) for x in lines]\n ref_ngrams, closest_diff, closest_len = ref_stats(output, refs)\n sys_len += len(output.split())\n ref_len += closest_len\n sys_ngrams = extract_ngrams(output)\n for ngram in sys_ngrams.keys():\n n = len(ngram.split())\n correct[n - 1] += min(sys_ngrams[ngram], ref_ngrams.get(ngram, 0))\n total[n - 1] += sys_ngrams[ngram]\n return compute_bleu(correct, total, sys_len, ref_len, smooth_method=\n smooth_method, smooth_value=smooth_value, use_effective_order=\n use_effective_order)\n\n\ndef raw_corpus_bleu(sys_stream, ref_streams, smooth_value=None) ->BLEU:\n \"\"\"Convenience function that wraps corpus_bleu().\n This is convenient if you're using sacrebleu as a library, say for scoring on dev.\n It uses no tokenization and 'floor' smoothing, with the floor default to 0 (no smoothing).\n\n :param sys_stream: the system stream (a sequence of segments)\n :param ref_streams: a list of one or more reference streams (each a sequence of segments)\n \"\"\"\n return corpus_bleu(sys_stream, ref_streams, smooth_method='floor',\n smooth_value=smooth_value, force=True, tokenize='none',\n use_effective_order=True)\n\n\ndef delete_whitespace(text: str) ->str:\n \"\"\"\n Removes whitespaces from text.\n \"\"\"\n return re.sub('\\\\s+', '', text).strip()\n\n\n<mask token>\n\n\ndef get_corpus_statistics(hypotheses: Iterable[str], references: Iterable[\n str], order: int=CHRF_ORDER, remove_whitespace: bool=True) ->List[float]:\n corpus_statistics = [0] * (order * 3)\n for hypothesis, reference in zip(hypotheses, references):\n statistics = get_sentence_statistics(hypothesis, reference, order=\n order, remove_whitespace=remove_whitespace)\n for i in range(len(statistics)):\n corpus_statistics[i] += statistics[i]\n return corpus_statistics\n\n\n<mask token>\n\n\ndef _chrf(avg_precision, avg_recall, beta: int=CHRF_BETA) ->float:\n if avg_precision + avg_recall == 0:\n return 0.0\n beta_square = beta ** 2\n score = (1 + beta_square) * (avg_precision * avg_recall) / (beta_square *\n avg_precision + avg_recall)\n return score\n\n\ndef corpus_chrf(hypotheses: Iterable[str], references: Iterable[str], order:\n int=CHRF_ORDER, beta: float=CHRF_BETA, remove_whitespace: bool=True\n ) ->CHRF:\n \"\"\"\n Computes Chrf on a corpus.\n\n :param hypotheses: Stream of hypotheses.\n :param references: Stream of references\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete all whitespace from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n corpus_statistics = get_corpus_statistics(hypotheses, references, order\n =order, remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(corpus_statistics,\n order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\n<mask token>\n\n\ndef get_langpairs_for_testset(testset: str) ->List:\n \"\"\"Return a list of language pairs for a given test set.\"\"\"\n return list(filter(lambda x: re.match('\\\\w\\\\w\\\\-\\\\w\\\\w', x), DATASETS.\n get(testset, {}).keys()))\n\n\ndef get_a_list_of_testset_names() ->str:\n \"\"\"Return a string with a formatted list of available test sets plus their descriptions. \"\"\"\n message = 'The available test sets are:'\n for testset in sorted(DATASETS.keys(), reverse=True):\n message += '\\n%20s: %s' % (testset, DATASETS[testset].get(\n 'description', ''))\n return message\n\n\n<mask token>\n\n\ndef _filter_subset(systems, test_sets, langpair, origlang, subset=None):\n \"\"\"Filter sentences with a given origlang (or subset) according to the raw SGM files.\"\"\"\n if origlang is None and subset is None:\n return systems\n if test_sets is None or langpair is None:\n raise ValueError(\n 'Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).'\n )\n indices_to_keep = []\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[\n test_set][langpair][0])\n if not rawfile.endswith('.sgm'):\n raise Exception(\n '--origlang and --subset supports only *.sgm files, not %s',\n rawfile)\n if subset is not None:\n if test_set not in SUBSETS:\n raise Exception(\n 'No subset annotation available for test set ' + test_set)\n doc_to_tags = SUBSETS[test_set]\n number_sentences_included = 0\n with smart_open(rawfile) as fin:\n include_doc = False\n for line in fin:\n if line.startswith('<doc '):\n if origlang is None:\n include_doc = True\n else:\n doc_origlang = re.sub('.* origlang=\"([^\"]+)\".*\\\\n',\n '\\\\1', line)\n if origlang.startswith('non-'):\n include_doc = doc_origlang != origlang[4:]\n else:\n include_doc = doc_origlang == origlang\n if subset is not None:\n doc_id = re.sub('.* docid=\"([^\"]+)\".*\\\\n', '\\\\1', line)\n if not re.search(subset, doc_to_tags.get(doc_id, '')):\n include_doc = False\n if line.startswith('<seg '):\n indices_to_keep.append(include_doc)\n number_sentences_included += 1 if include_doc else 0\n return [[sentence for sentence, keep in zip(sys, indices_to_keep) if\n keep] for sys in systems]\n\n\n<mask token>\n\n\ndef parse_args():\n arg_parser = argparse.ArgumentParser(description=\n \"\"\"sacreBLEU: Hassle-free computation of shareable BLEU scores.\nQuick usage: score your detokenized output against WMT'14 EN-DE:\n cat output.detok.de | sacrebleu -t wmt14 -l en-de\"\"\"\n , formatter_class=argparse.RawDescriptionHelpFormatter)\n arg_parser.add_argument('--test-set', '-t', type=str, default=None,\n help=\n 'the test set to use (see also --list) or a comma-separated list of test sets to be concatenated'\n )\n arg_parser.add_argument('-lc', action='store_true', default=False, help\n ='Use case-insensitive BLEU (default: actual case)')\n arg_parser.add_argument('--sentence-level', '-sl', action='store_true',\n help='Output metric on each sentence.')\n arg_parser.add_argument('--smooth', '-s', choices=['exp', 'floor',\n 'add-k', 'none'], default='exp', help=\n 'smoothing method: exponential decay (default), floor (increment zero counts), add-k (increment num/denom by k for n>1), or none'\n )\n arg_parser.add_argument('--smooth-value', '-sv', type=float, default=\n None, help=\n 'The value to pass to the smoothing technique, only used for floor and add-k. Default floor: {}, add-k: {}.'\n .format(SMOOTH_VALUE_DEFAULT['floor'], SMOOTH_VALUE_DEFAULT['add-k']))\n arg_parser.add_argument('--tokenize', '-tok', choices=TOKENIZERS.keys(),\n default=None, help='tokenization method to use')\n arg_parser.add_argument('--language-pair', '-l', dest='langpair',\n default=None, help=\n 'source-target language pair (2-char ISO639-1 codes)')\n arg_parser.add_argument('--origlang', '-ol', dest='origlang', default=\n None, help=\n 'use a subset of sentences with a given original language (2-char ISO639-1 codes), \"non-\" prefix means negation'\n )\n arg_parser.add_argument('--subset', dest='subset', default=None, help=\n 'use a subset of sentences whose document annotation matches a give regex (see SUBSETS in the source code)'\n )\n arg_parser.add_argument('--download', type=str, default=None, help=\n 'download a test set and quit')\n arg_parser.add_argument('--echo', choices=['src', 'ref', 'both'], type=\n str, default=None, help=\n 'output the source (src), reference (ref), or both (both, pasted) to STDOUT and quit'\n )\n arg_parser.add_argument('--input', '-i', type=str, default='-', help=\n 'Read input from a file instead of STDIN')\n arg_parser.add_argument('--num-refs', '-nr', type=int, default=1, help=\n 'Split the reference stream on tabs, and expect this many references. Default: %(default)s.'\n )\n arg_parser.add_argument('refs', nargs='*', default=[], help=\n 'optional list of references (for backwards-compatibility with older scripts)'\n )\n arg_parser.add_argument('--metrics', '-m', choices=['bleu', 'chrf'],\n nargs='+', default=['bleu'], help='metrics to compute (default: bleu)')\n arg_parser.add_argument('--chrf-order', type=int, default=CHRF_ORDER,\n help='chrf character order (default: %(default)s)')\n arg_parser.add_argument('--chrf-beta', type=int, default=CHRF_BETA,\n help='chrf BETA parameter (default: %(default)s)')\n arg_parser.add_argument('--chrf-whitespace', action='store_true',\n default=False, help=\n 'include whitespace in chrF calculation (default: %(default)s)')\n arg_parser.add_argument('--short', default=False, action='store_true',\n help='produce a shorter (less human readable) signature')\n arg_parser.add_argument('--score-only', '-b', default=False, action=\n 'store_true', help='output only the BLEU score')\n arg_parser.add_argument('--force', default=False, action='store_true',\n help='insist that your tokenized input is actually detokenized')\n arg_parser.add_argument('--quiet', '-q', default=False, action=\n 'store_true', help='suppress informative output')\n arg_parser.add_argument('--encoding', '-e', type=str, default='utf-8',\n help='open text files with specified encoding (default: %(default)s)')\n arg_parser.add_argument('--list', default=False, action='store_true',\n help='print a list of all available test sets.')\n arg_parser.add_argument('--citation', '--cite', default=False, action=\n 'store_true', help='dump the bibtex citation and quit.')\n arg_parser.add_argument('--width', '-w', type=int, default=1, help=\n 'floating point width (default: %(default)s)')\n arg_parser.add_argument('--detail', '-d', default=False, action=\n 'store_true', help=\n 'print extra information (split test sets based on origlang)')\n arg_parser.add_argument('-V', '--version', action='version', version=\n '%(prog)s {}'.format(VERSION))\n args = arg_parser.parse_args()\n return args\n\n\n<mask token>\n",
"step-4": "<mask token>\n\n\ndef smart_open(file, mode='rt', encoding='utf-8'):\n \"\"\"Convenience function for reading compressed or plain text files.\n :param file: The file to read.\n :param mode: The file mode (read, write).\n :param encoding: The file encoding.\n \"\"\"\n if file.endswith('.gz'):\n return gzip.open(file, mode=mode, encoding=encoding, newline='\\n')\n return open(file, mode=mode, encoding=encoding, newline='\\n')\n\n\ndef my_log(num):\n \"\"\"\n Floors the log function\n\n :param num: the number\n :return: log(num) floored to a very low number\n \"\"\"\n if num == 0.0:\n return -9999999999\n return math.log(num)\n\n\ndef bleu_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'smooth': 's', 'case': 'c', 'tok':\n 'tok', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'tok': args.tokenize, 'version': VERSION, 'smooth': args.\n smooth, 'numrefs': numrefs, 'case': 'lc' if args.lc else 'mixed'}\n if args.tokenize == 'ja-mecab':\n signature['tok'] += '-' + TokenizeMeCab().signature()\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\ndef chrf_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the chrF signature\n \"\"\"\n abbr = {'test': 't', 'lang': 'l', 'numchars': 'n', 'space': 's', 'case':\n 'c', 'numrefs': '#', 'version': 'v', 'origlang': 'o', 'subset': 'S'}\n signature = {'version': VERSION, 'space': args.chrf_whitespace,\n 'numchars': args.chrf_order, 'numrefs': numrefs, 'case': 'lc' if\n args.lc else 'mixed'}\n if args.test_set is not None:\n signature['test'] = args.test_set\n if args.langpair is not None:\n signature['lang'] = args.langpair\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x,\n signature[x]) for x in sorted(signature.keys())])\n return sigstr\n\n\ndef extract_ngrams(line, min_order=1, max_order=NGRAM_ORDER) ->Counter:\n \"\"\"Extracts all the ngrams (min_order <= n <= max_order) from a sequence of tokens.\n\n :param line: A segment containing a sequence of words.\n :param min_order: Minimum n-gram length (default: 1).\n :param max_order: Maximum n-gram length (default: NGRAM_ORDER).\n :return: a dictionary containing ngrams and counts\n \"\"\"\n ngrams = Counter()\n tokens = line.split()\n for n in range(min_order, max_order + 1):\n for i in range(0, len(tokens) - n + 1):\n ngram = ' '.join(tokens[i:i + n])\n ngrams[ngram] += 1\n return ngrams\n\n\ndef extract_char_ngrams(s: str, n: int) ->Counter:\n \"\"\"\n Yields counts of character n-grams from string s of order n.\n \"\"\"\n return Counter([s[i:i + n] for i in range(len(s) - n + 1)])\n\n\ndef ref_stats(output, refs):\n ngrams = Counter()\n closest_diff = None\n closest_len = None\n for ref in refs:\n tokens = ref.split()\n reflen = len(tokens)\n diff = abs(len(output.split()) - reflen)\n if closest_diff is None or diff < closest_diff:\n closest_diff = diff\n closest_len = reflen\n elif diff == closest_diff:\n if reflen < closest_len:\n closest_len = reflen\n ngrams_ref = extract_ngrams(ref)\n for ngram in ngrams_ref.keys():\n ngrams[ngram] = max(ngrams[ngram], ngrams_ref[ngram])\n return ngrams, closest_diff, closest_len\n\n\ndef _clean(s):\n \"\"\"\n Removes trailing and leading spaces and collapses multiple consecutive internal spaces to a single one.\n\n :param s: The string.\n :return: A cleaned-up string.\n \"\"\"\n return re.sub('\\\\s+', ' ', s.strip())\n\n\ndef process_to_text(rawfile, txtfile, field: int=None):\n \"\"\"Processes raw files to plain text files.\n :param rawfile: the input file (possibly SGML)\n :param txtfile: the plaintext file\n :param field: For TSV files, which field to extract.\n \"\"\"\n if not os.path.exists(txtfile) or os.path.getsize(txtfile) == 0:\n sacrelogger.info('Processing %s to %s', rawfile, txtfile)\n if rawfile.endswith('.sgm') or rawfile.endswith('.sgml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.xml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub('<seg.*?>(.*)</seg>.*?', '\\\\1',\n line)), file=fout)\n elif rawfile.endswith('.txt'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip(), file=fout)\n elif rawfile.endswith('.tsv'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip().split('\\t')[field], file=fout)\n\n\ndef print_test_set(test_set, langpair, side, origlang=None, subset=None):\n \"\"\"Prints to STDOUT the specified side of the specified test set\n :param test_set: the test set to print\n :param langpair: the language pair\n :param side: 'src' for source, 'ref' for reference\n :param origlang: print only sentences with a given original language (2-char ISO639-1 code), \"non-\" prefix means negation\n :param subset: print only sentences whose document annotation matches a given regex\n \"\"\"\n files = download_test_set(test_set, langpair)\n if side == 'src':\n files = [files[0]]\n elif side == 'ref':\n files.pop(0)\n streams = [smart_open(file) for file in files]\n streams = _filter_subset(streams, test_set, langpair, origlang, subset)\n for lines in zip(*streams):\n print('\\t'.join(map(lambda x: x.rstrip(), lines)))\n\n\ndef download_test_set(test_set, langpair=None):\n \"\"\"Downloads the specified test to the system location specified by the SACREBLEU environment variable.\n\n :param test_set: the test set to download\n :param langpair: the language pair (needed for some datasets)\n :return: the set of processed files\n \"\"\"\n outdir = os.path.join(SACREBLEU_DIR, test_set)\n os.makedirs(outdir, exist_ok=True)\n expected_checksums = DATASETS[test_set].get('md5', [None] * len(\n DATASETS[test_set]))\n for dataset, expected_md5 in zip(DATASETS[test_set]['data'],\n expected_checksums):\n tarball = os.path.join(outdir, os.path.basename(dataset))\n rawdir = os.path.join(outdir, 'raw')\n lockfile = '{}.lock'.format(tarball)\n with portalocker.Lock(lockfile, 'w', timeout=60):\n if not os.path.exists(tarball) or os.path.getsize(tarball) == 0:\n sacrelogger.info('Downloading %s to %s', dataset, tarball)\n try:\n with urllib.request.urlopen(dataset) as f, open(tarball,\n 'wb') as out:\n out.write(f.read())\n except ssl.SSLError:\n sacrelogger.warning(\n 'An SSL error was encountered in downloading the files. If you\\'re on a Mac, you may need to run the \"Install Certificates.command\" file located in the \"Python 3\" folder, often found under /Applications'\n )\n sys.exit(1)\n if expected_md5 is not None:\n md5 = hashlib.md5()\n with open(tarball, 'rb') as infile:\n for line in infile:\n md5.update(line)\n if md5.hexdigest() != expected_md5:\n sacrelogger.error(\n 'Fatal: MD5 sum of downloaded file was incorrect (got {}, expected {}).'\n .format(md5.hexdigest(), expected_md5))\n sacrelogger.error(\n 'Please manually delete \"{}\" and rerun the command.'\n .format(tarball))\n sacrelogger.error(\n 'If the problem persists, the tarball may have changed, in which case, please contact the SacreBLEU maintainer.'\n )\n sys.exit(1)\n else:\n sacrelogger.info('Checksum passed: {}'.format(md5.\n hexdigest()))\n sacrelogger.info('Extracting %s', tarball)\n if tarball.endswith('.tar.gz') or tarball.endswith('.tgz'):\n import tarfile\n with tarfile.open(tarball) as tar:\n tar.extractall(path=rawdir)\n elif tarball.endswith('.zip'):\n import zipfile\n with zipfile.ZipFile(tarball, 'r') as zipfile:\n zipfile.extractall(path=rawdir)\n found = []\n languages = DATASETS[test_set].keys() if langpair is None else [langpair]\n for pair in languages:\n if '-' not in pair:\n continue\n src, tgt = pair.split('-')\n rawfile = DATASETS[test_set][pair][0]\n field = None\n if rawfile.endswith('.tsv'):\n field, rawfile = rawfile.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, rawfile)\n outpath = os.path.join(outdir, '{}.{}'.format(pair, src))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n refs = DATASETS[test_set][pair][1:]\n for i, ref in enumerate(refs):\n field = None\n if ref.endswith('.tsv'):\n field, ref = ref.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, ref)\n if len(refs) >= 2:\n outpath = os.path.join(outdir, '{}.{}.{}'.format(pair, tgt, i))\n else:\n outpath = os.path.join(outdir, '{}.{}'.format(pair, tgt))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n return found\n\n\nclass Result:\n\n def __init__(self, score: float):\n self.score = score\n\n def __str__(self):\n return self.format()\n\n\nclass BLEU(Result):\n\n def __init__(self, score: float, counts, totals, precisions, bp,\n sys_len, ref_len):\n super().__init__(score)\n self.counts = counts\n self.totals = totals\n self.precisions = precisions\n self.bp = bp\n self.sys_len = sys_len\n self.ref_len = ref_len\n\n def format(self, width=2):\n precisions = '/'.join(['{:.1f}'.format(p) for p in self.precisions])\n return (\n 'BLEU = {score:.{width}f} {precisions} (BP = {bp:.3f} ratio = {ratio:.3f} hyp_len = {sys_len:d} ref_len = {ref_len:d})'\n .format(score=self.score, width=width, precisions=precisions,\n bp=self.bp, ratio=self.sys_len / self.ref_len, sys_len=self.\n sys_len, ref_len=self.ref_len))\n\n\nclass CHRF(Result):\n\n def __init__(self, score: float):\n super().__init__(score)\n\n def format(self, width=2):\n return '{score:.{width}f}'.format(score=self.score, width=width)\n\n\n<mask token>\n\n\ndef sentence_bleu(hypothesis: str, references: List[str], smooth_method:\n str='floor', smooth_value: float=None, use_effective_order: bool=True\n ) ->BLEU:\n \"\"\"\n Computes BLEU on a single sentence pair.\n\n Disclaimer: computing BLEU on the sentence level is not its intended use,\n BLEU is a corpus-level metric.\n\n :param hypothesis: Hypothesis string.\n :param reference: Reference string.\n :param smooth_value: For 'floor' smoothing, the floor value to use.\n :param use_effective_order: Account for references that are shorter than the largest n-gram.\n :return: Returns a single BLEU score as a float.\n \"\"\"\n bleu = corpus_bleu(hypothesis, references, smooth_method=smooth_method,\n smooth_value=smooth_value, use_effective_order=use_effective_order)\n return bleu\n\n\ndef corpus_bleu(sys_stream: Union[str, Iterable[str]], ref_streams: Union[\n str, List[Iterable[str]]], smooth_method='exp', smooth_value=None,\n force=False, lowercase=False, tokenize=DEFAULT_TOKENIZER,\n use_effective_order=False) ->BLEU:\n \"\"\"Produces BLEU scores along with its sufficient statistics from a source against one or more references.\n\n :param sys_stream: The system stream (a sequence of segments)\n :param ref_streams: A list of one or more reference streams (each a sequence of segments)\n :param smooth: The smoothing method to use\n :param smooth_value: For 'floor' smoothing, the floor to use\n :param force: Ignore data that looks already tokenized\n :param lowercase: Lowercase the data\n :param tokenize: The tokenizer to use\n :return: a BLEU object containing everything you'd want\n \"\"\"\n if isinstance(sys_stream, str):\n sys_stream = [sys_stream]\n if isinstance(ref_streams, str):\n ref_streams = [[ref_streams]]\n sys_len = 0\n ref_len = 0\n correct = [(0) for n in range(NGRAM_ORDER)]\n total = [(0) for n in range(NGRAM_ORDER)]\n tokenized_count = 0\n fhs = [sys_stream] + ref_streams\n for lines in zip_longest(*fhs):\n if None in lines:\n raise EOFError(\n 'Source and reference streams have different lengths!')\n if lowercase:\n lines = [x.lower() for x in lines]\n if not (force or tokenize == 'none') and lines[0].rstrip().endswith(\n ' .'):\n tokenized_count += 1\n if tokenized_count == 100:\n sacrelogger.warning(\n \"That's 100 lines that end in a tokenized period ('.')\")\n sacrelogger.warning(\n 'It looks like you forgot to detokenize your test data, which may hurt your score.'\n )\n sacrelogger.warning(\n \"If you insist your data is detokenized, or don't care, you can suppress this message with '--force'.\"\n )\n output, *refs = [TOKENIZERS[tokenize](x.rstrip()) for x in lines]\n ref_ngrams, closest_diff, closest_len = ref_stats(output, refs)\n sys_len += len(output.split())\n ref_len += closest_len\n sys_ngrams = extract_ngrams(output)\n for ngram in sys_ngrams.keys():\n n = len(ngram.split())\n correct[n - 1] += min(sys_ngrams[ngram], ref_ngrams.get(ngram, 0))\n total[n - 1] += sys_ngrams[ngram]\n return compute_bleu(correct, total, sys_len, ref_len, smooth_method=\n smooth_method, smooth_value=smooth_value, use_effective_order=\n use_effective_order)\n\n\ndef raw_corpus_bleu(sys_stream, ref_streams, smooth_value=None) ->BLEU:\n \"\"\"Convenience function that wraps corpus_bleu().\n This is convenient if you're using sacrebleu as a library, say for scoring on dev.\n It uses no tokenization and 'floor' smoothing, with the floor default to 0 (no smoothing).\n\n :param sys_stream: the system stream (a sequence of segments)\n :param ref_streams: a list of one or more reference streams (each a sequence of segments)\n \"\"\"\n return corpus_bleu(sys_stream, ref_streams, smooth_method='floor',\n smooth_value=smooth_value, force=True, tokenize='none',\n use_effective_order=True)\n\n\ndef delete_whitespace(text: str) ->str:\n \"\"\"\n Removes whitespaces from text.\n \"\"\"\n return re.sub('\\\\s+', '', text).strip()\n\n\ndef get_sentence_statistics(hypothesis: str, reference: str, order: int=\n CHRF_ORDER, remove_whitespace: bool=True) ->List[float]:\n hypothesis = delete_whitespace(hypothesis\n ) if remove_whitespace else hypothesis\n reference = delete_whitespace(reference\n ) if remove_whitespace else reference\n statistics = [0] * (order * 3)\n for i in range(order):\n n = i + 1\n hypothesis_ngrams = extract_char_ngrams(hypothesis, n)\n reference_ngrams = extract_char_ngrams(reference, n)\n common_ngrams = hypothesis_ngrams & reference_ngrams\n statistics[3 * i + 0] = sum(hypothesis_ngrams.values())\n statistics[3 * i + 1] = sum(reference_ngrams.values())\n statistics[3 * i + 2] = sum(common_ngrams.values())\n return statistics\n\n\ndef get_corpus_statistics(hypotheses: Iterable[str], references: Iterable[\n str], order: int=CHRF_ORDER, remove_whitespace: bool=True) ->List[float]:\n corpus_statistics = [0] * (order * 3)\n for hypothesis, reference in zip(hypotheses, references):\n statistics = get_sentence_statistics(hypothesis, reference, order=\n order, remove_whitespace=remove_whitespace)\n for i in range(len(statistics)):\n corpus_statistics[i] += statistics[i]\n return corpus_statistics\n\n\ndef _avg_precision_and_recall(statistics: List[float], order: int) ->Tuple[\n float, float]:\n avg_precision = 0.0\n avg_recall = 0.0\n effective_order = 0\n for i in range(order):\n hypotheses_ngrams = statistics[3 * i + 0]\n references_ngrams = statistics[3 * i + 1]\n common_ngrams = statistics[3 * i + 2]\n if hypotheses_ngrams > 0 and references_ngrams > 0:\n avg_precision += common_ngrams / hypotheses_ngrams\n avg_recall += common_ngrams / references_ngrams\n effective_order += 1\n if effective_order == 0:\n return 0.0, 0.0\n avg_precision /= effective_order\n avg_recall /= effective_order\n return avg_precision, avg_recall\n\n\ndef _chrf(avg_precision, avg_recall, beta: int=CHRF_BETA) ->float:\n if avg_precision + avg_recall == 0:\n return 0.0\n beta_square = beta ** 2\n score = (1 + beta_square) * (avg_precision * avg_recall) / (beta_square *\n avg_precision + avg_recall)\n return score\n\n\ndef corpus_chrf(hypotheses: Iterable[str], references: Iterable[str], order:\n int=CHRF_ORDER, beta: float=CHRF_BETA, remove_whitespace: bool=True\n ) ->CHRF:\n \"\"\"\n Computes Chrf on a corpus.\n\n :param hypotheses: Stream of hypotheses.\n :param references: Stream of references\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete all whitespace from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n corpus_statistics = get_corpus_statistics(hypotheses, references, order\n =order, remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(corpus_statistics,\n order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\ndef sentence_chrf(hypothesis: str, reference: str, order: int=CHRF_ORDER,\n beta: float=CHRF_BETA, remove_whitespace: bool=True) ->CHRF:\n \"\"\"\n Computes ChrF on a single sentence pair.\n\n :param hypothesis: Hypothesis string.\n :param reference: Reference string.\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete whitespaces from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n statistics = get_sentence_statistics(hypothesis, reference, order=order,\n remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(statistics, order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\ndef get_langpairs_for_testset(testset: str) ->List:\n \"\"\"Return a list of language pairs for a given test set.\"\"\"\n return list(filter(lambda x: re.match('\\\\w\\\\w\\\\-\\\\w\\\\w', x), DATASETS.\n get(testset, {}).keys()))\n\n\ndef get_a_list_of_testset_names() ->str:\n \"\"\"Return a string with a formatted list of available test sets plus their descriptions. \"\"\"\n message = 'The available test sets are:'\n for testset in sorted(DATASETS.keys(), reverse=True):\n message += '\\n%20s: %s' % (testset, DATASETS[testset].get(\n 'description', ''))\n return message\n\n\ndef _available_origlangs(test_sets, langpair):\n \"\"\"Return a list of origlang values in according to the raw SGM files.\"\"\"\n origlangs = set()\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[\n test_set][langpair][0])\n if rawfile.endswith('.sgm'):\n with smart_open(rawfile) as fin:\n for line in fin:\n if line.startswith('<doc '):\n doc_origlang = re.sub('.* origlang=\"([^\"]+)\".*\\\\n',\n '\\\\1', line)\n origlangs.add(doc_origlang)\n return sorted(list(origlangs))\n\n\ndef _filter_subset(systems, test_sets, langpair, origlang, subset=None):\n \"\"\"Filter sentences with a given origlang (or subset) according to the raw SGM files.\"\"\"\n if origlang is None and subset is None:\n return systems\n if test_sets is None or langpair is None:\n raise ValueError(\n 'Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).'\n )\n indices_to_keep = []\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[\n test_set][langpair][0])\n if not rawfile.endswith('.sgm'):\n raise Exception(\n '--origlang and --subset supports only *.sgm files, not %s',\n rawfile)\n if subset is not None:\n if test_set not in SUBSETS:\n raise Exception(\n 'No subset annotation available for test set ' + test_set)\n doc_to_tags = SUBSETS[test_set]\n number_sentences_included = 0\n with smart_open(rawfile) as fin:\n include_doc = False\n for line in fin:\n if line.startswith('<doc '):\n if origlang is None:\n include_doc = True\n else:\n doc_origlang = re.sub('.* origlang=\"([^\"]+)\".*\\\\n',\n '\\\\1', line)\n if origlang.startswith('non-'):\n include_doc = doc_origlang != origlang[4:]\n else:\n include_doc = doc_origlang == origlang\n if subset is not None:\n doc_id = re.sub('.* docid=\"([^\"]+)\".*\\\\n', '\\\\1', line)\n if not re.search(subset, doc_to_tags.get(doc_id, '')):\n include_doc = False\n if line.startswith('<seg '):\n indices_to_keep.append(include_doc)\n number_sentences_included += 1 if include_doc else 0\n return [[sentence for sentence, keep in zip(sys, indices_to_keep) if\n keep] for sys in systems]\n\n\ndef main():\n args = parse_args()\n sys.stdin = open(sys.stdin.fileno(), mode='r', encoding='utf-8',\n buffering=True, newline='\\n')\n sys.stdout = open(sys.stdout.fileno(), mode='w', encoding='utf-8',\n buffering=True)\n if not args.quiet:\n logging.basicConfig(level=logging.INFO, format='sacreBLEU: %(message)s'\n )\n if args.download:\n download_test_set(args.download, args.langpair)\n sys.exit(0)\n if args.list:\n if args.test_set:\n print(' '.join(get_langpairs_for_testset(args.test_set)))\n else:\n print(get_a_list_of_testset_names())\n sys.exit(0)\n if args.sentence_level and len(args.metrics) > 1:\n sacrelogger.error(\n 'Only one metric can be used with Sentence-level reporting.')\n sys.exit(1)\n if args.citation:\n if not args.test_set:\n sacrelogger.error('I need a test set (-t).')\n sys.exit(1)\n for test_set in args.test_set.split(','):\n if 'citation' not in DATASETS[test_set]:\n sacrelogger.error('No citation found for %s', test_set)\n else:\n print(DATASETS[test_set]['citation'])\n sys.exit(0)\n if args.num_refs != 1 and (args.test_set is not None or len(args.refs) > 1\n ):\n sacrelogger.error(\n 'The --num-refs argument allows you to provide any number of tab-delimited references in a single file.'\n )\n sacrelogger.error(\n 'You can only use it with externaly-provided references, however (i.e., not with `-t`),'\n )\n sacrelogger.error(\n 'and you cannot then provide multiple reference files.')\n sys.exit(1)\n if args.test_set is not None:\n for test_set in args.test_set.split(','):\n if test_set not in DATASETS:\n sacrelogger.error('Unknown test set \"%s\"\\n%s', test_set,\n get_a_list_of_testset_names())\n sys.exit(1)\n if args.test_set is None:\n if len(args.refs) == 0:\n sacrelogger.error(\n 'I need either a predefined test set (-t) or a list of references'\n )\n sacrelogger.error(get_a_list_of_testset_names())\n sys.exit(1)\n elif len(args.refs) > 0:\n sacrelogger.error(\n 'I need exactly one of (a) a predefined test set (-t) or (b) a list of references'\n )\n sys.exit(1)\n elif args.langpair is None:\n sacrelogger.error('I need a language pair (-l).')\n sys.exit(1)\n else:\n for test_set in args.test_set.split(','):\n if args.langpair not in DATASETS[test_set]:\n sacrelogger.error('No such language pair \"%s\"', args.langpair)\n sacrelogger.error(\n 'Available language pairs for test set \"%s\": %s',\n test_set, ', '.join(x for x in DATASETS[test_set].keys(\n ) if '-' in x))\n sys.exit(1)\n if args.echo:\n if args.langpair is None or args.test_set is None:\n sacrelogger.warning(\n '--echo requires a test set (--t) and a language pair (-l)')\n sys.exit(1)\n for test_set in args.test_set.split(','):\n print_test_set(test_set, args.langpair, args.echo, args.\n origlang, args.subset)\n sys.exit(0)\n if args.test_set is not None and args.tokenize == 'none':\n sacrelogger.warning(\n \"\"\"You are turning off sacrebleu's internal tokenization ('--tokenize none'), presumably to supply\nyour own reference tokenization. Published numbers will not be comparable with other papers.\n\"\"\"\n )\n if args.tokenize is None:\n if args.langpair is not None and args.langpair.split('-')[1] == 'zh':\n args.tokenize = 'zh'\n elif args.langpair is not None and args.langpair.split('-')[1] == 'ja':\n args.tokenize = 'ja-mecab'\n else:\n args.tokenize = DEFAULT_TOKENIZER\n if args.langpair is not None and 'bleu' in args.metrics:\n if args.langpair.split('-')[1] == 'zh' and args.tokenize != 'zh':\n logger.warning(\n 'You should also pass \"--tok zh\" when scoring Chinese...')\n if args.langpair.split('-')[1\n ] == 'ja' and not args.tokenize.startswith('ja-'):\n logger.warning(\n 'You should also pass \"--tok ja-mecab\" when scoring Japanese...'\n )\n if args.test_set is None:\n concat_ref_files = [args.refs]\n else:\n concat_ref_files = []\n for test_set in args.test_set.split(','):\n _, *ref_files = download_test_set(test_set, args.langpair)\n if len(ref_files) == 0:\n sacrelogger.warning('No references found for test set {}/{}.'\n .format(test_set, args.langpair))\n concat_ref_files.append(ref_files)\n inputfh = io.TextIOWrapper(sys.stdin.buffer, encoding=args.encoding\n ) if args.input == '-' else smart_open(args.input, encoding=args.\n encoding)\n full_system = inputfh.readlines()\n full_refs = [[] for x in range(max(len(concat_ref_files[0]), args.\n num_refs))]\n for ref_files in concat_ref_files:\n for refno, ref_file in enumerate(ref_files):\n for lineno, line in enumerate(smart_open(ref_file, encoding=\n args.encoding), 1):\n if args.num_refs != 1:\n splits = line.rstrip().split(sep='\\t', maxsplit=args.\n num_refs - 1)\n if len(splits) != args.num_refs:\n sacrelogger.error(\n 'FATAL: line {}: expected {} fields, but found {}.'\n .format(lineno, args.num_refs, len(splits)))\n sys.exit(17)\n for refno, split in enumerate(splits):\n full_refs[refno].append(split)\n else:\n full_refs[refno].append(line)\n system, *refs = _filter_subset([full_system, *full_refs], args.test_set,\n args.langpair, args.origlang, args.subset)\n if len(system) == 0:\n message = 'Test set %s contains no sentence' % args.test_set\n if args.origlang is not None or args.subset is not None:\n message += ' with'\n message += ('' if args.origlang is None else ' origlang=' +\n args.origlang)\n message += '' if args.subset is None else ' subset=' + args.subset\n sacrelogger.error(message)\n exit(1)\n if args.sentence_level:\n for output, *references in zip(system, *refs):\n results = []\n for metric in args.metrics:\n if metric == 'bleu':\n bleu = sentence_bleu(output, [[x] for x in references],\n smooth_method=args.smooth, smooth_value=args.\n smooth_value)\n results.append(bleu)\n if metric == 'chrf':\n chrf = sentence_chrf(output, references[0], args.\n chrf_order, args.chrf_beta, remove_whitespace=not\n args.chrf_whitespace)\n results.append(chrf)\n display_metric(args.metrics, results, len(refs), args)\n sys.exit(0)\n results = []\n try:\n for metric in args.metrics:\n if metric == 'bleu':\n bleu = corpus_bleu(system, refs, smooth_method=args.smooth,\n smooth_value=args.smooth_value, force=args.force,\n lowercase=args.lc, tokenize=args.tokenize)\n results.append(bleu)\n elif metric == 'chrf':\n chrf = corpus_chrf(system, refs[0], beta=args.chrf_beta,\n order=args.chrf_order, remove_whitespace=not args.\n chrf_whitespace)\n results.append(chrf)\n except EOFError:\n sacrelogger.error(\n 'The input and reference stream(s) were of different lengths.')\n if args.test_set is not None:\n sacrelogger.error(\n \"\"\"\nThis could be a problem with your system output or with sacreBLEU's reference database.\nIf the latter, you can clean out the references cache by typing:\n\n rm -r %s/%s\n\nThey will be downloaded automatically again the next time you run sacreBLEU.\"\"\"\n , SACREBLEU_DIR, args.test_set)\n sys.exit(1)\n display_metric(args.metrics, results, len(refs), args)\n if args.detail:\n width = args.width\n sents_digits = len(str(len(full_system)))\n origlangs = args.origlang if args.origlang else _available_origlangs(\n args.test_set, args.langpair)\n for origlang in origlangs:\n subsets = [None]\n if args.subset is not None:\n subsets += [args.subset]\n elif all(t in SUBSETS for t in args.test_set.split(',')):\n subsets += COUNTRIES + DOMAINS\n for subset in subsets:\n system, *refs = _filter_subset([full_system, *full_refs],\n args.test_set, args.langpair, origlang, subset)\n if len(system) == 0:\n continue\n if subset in COUNTRIES:\n subset_str = '%20s' % ('country=' + subset)\n elif subset in DOMAINS:\n subset_str = '%20s' % ('domain=' + subset)\n else:\n subset_str = '%20s' % ''\n if 'bleu' in args.metrics:\n bleu = corpus_bleu(system, refs, smooth_method=args.\n smooth, smooth_value=args.smooth_value, force=args.\n force, lowercase=args.lc, tokenize=args.tokenize)\n print('origlang={} {}: sentences={:{}} BLEU={:{}.{}f}'.\n format(origlang, subset_str, len(system),\n sents_digits, bleu.score, width + 4, width))\n if 'chrf' in args.metrics:\n chrf = corpus_chrf(system, refs[0], beta=args.chrf_beta,\n order=args.chrf_order, remove_whitespace=not args.\n chrf_whitespace)\n print('origlang={} {}: sentences={:{}} chrF={:{}.{}f}'.\n format(origlang, subset_str, len(system),\n sents_digits, chrf.score, width + 4, width))\n\n\ndef display_metric(metrics_to_print, results, num_refs, args):\n \"\"\"\n Badly in need of refactoring.\n One idea is to put all of this in the BLEU and CHRF classes, and then define\n a Result::signature() function.\n \"\"\"\n for metric, result in zip(metrics_to_print, results):\n if metric == 'bleu':\n if args.score_only:\n print('{0:.{1}f}'.format(result.score, args.width))\n else:\n version_str = bleu_signature(args, num_refs)\n print(result.format(args.width).replace('BLEU', 'BLEU+' +\n version_str))\n elif metric == 'chrf':\n if args.score_only:\n print('{0:.{1}f}'.format(result.score, args.width))\n else:\n version_str = chrf_signature(args, num_refs)\n print('chrF{0:d}+{1} = {2:.{3}f}'.format(args.chrf_beta,\n version_str, result.score, args.width))\n\n\ndef parse_args():\n arg_parser = argparse.ArgumentParser(description=\n \"\"\"sacreBLEU: Hassle-free computation of shareable BLEU scores.\nQuick usage: score your detokenized output against WMT'14 EN-DE:\n cat output.detok.de | sacrebleu -t wmt14 -l en-de\"\"\"\n , formatter_class=argparse.RawDescriptionHelpFormatter)\n arg_parser.add_argument('--test-set', '-t', type=str, default=None,\n help=\n 'the test set to use (see also --list) or a comma-separated list of test sets to be concatenated'\n )\n arg_parser.add_argument('-lc', action='store_true', default=False, help\n ='Use case-insensitive BLEU (default: actual case)')\n arg_parser.add_argument('--sentence-level', '-sl', action='store_true',\n help='Output metric on each sentence.')\n arg_parser.add_argument('--smooth', '-s', choices=['exp', 'floor',\n 'add-k', 'none'], default='exp', help=\n 'smoothing method: exponential decay (default), floor (increment zero counts), add-k (increment num/denom by k for n>1), or none'\n )\n arg_parser.add_argument('--smooth-value', '-sv', type=float, default=\n None, help=\n 'The value to pass to the smoothing technique, only used for floor and add-k. Default floor: {}, add-k: {}.'\n .format(SMOOTH_VALUE_DEFAULT['floor'], SMOOTH_VALUE_DEFAULT['add-k']))\n arg_parser.add_argument('--tokenize', '-tok', choices=TOKENIZERS.keys(),\n default=None, help='tokenization method to use')\n arg_parser.add_argument('--language-pair', '-l', dest='langpair',\n default=None, help=\n 'source-target language pair (2-char ISO639-1 codes)')\n arg_parser.add_argument('--origlang', '-ol', dest='origlang', default=\n None, help=\n 'use a subset of sentences with a given original language (2-char ISO639-1 codes), \"non-\" prefix means negation'\n )\n arg_parser.add_argument('--subset', dest='subset', default=None, help=\n 'use a subset of sentences whose document annotation matches a give regex (see SUBSETS in the source code)'\n )\n arg_parser.add_argument('--download', type=str, default=None, help=\n 'download a test set and quit')\n arg_parser.add_argument('--echo', choices=['src', 'ref', 'both'], type=\n str, default=None, help=\n 'output the source (src), reference (ref), or both (both, pasted) to STDOUT and quit'\n )\n arg_parser.add_argument('--input', '-i', type=str, default='-', help=\n 'Read input from a file instead of STDIN')\n arg_parser.add_argument('--num-refs', '-nr', type=int, default=1, help=\n 'Split the reference stream on tabs, and expect this many references. Default: %(default)s.'\n )\n arg_parser.add_argument('refs', nargs='*', default=[], help=\n 'optional list of references (for backwards-compatibility with older scripts)'\n )\n arg_parser.add_argument('--metrics', '-m', choices=['bleu', 'chrf'],\n nargs='+', default=['bleu'], help='metrics to compute (default: bleu)')\n arg_parser.add_argument('--chrf-order', type=int, default=CHRF_ORDER,\n help='chrf character order (default: %(default)s)')\n arg_parser.add_argument('--chrf-beta', type=int, default=CHRF_BETA,\n help='chrf BETA parameter (default: %(default)s)')\n arg_parser.add_argument('--chrf-whitespace', action='store_true',\n default=False, help=\n 'include whitespace in chrF calculation (default: %(default)s)')\n arg_parser.add_argument('--short', default=False, action='store_true',\n help='produce a shorter (less human readable) signature')\n arg_parser.add_argument('--score-only', '-b', default=False, action=\n 'store_true', help='output only the BLEU score')\n arg_parser.add_argument('--force', default=False, action='store_true',\n help='insist that your tokenized input is actually detokenized')\n arg_parser.add_argument('--quiet', '-q', default=False, action=\n 'store_true', help='suppress informative output')\n arg_parser.add_argument('--encoding', '-e', type=str, default='utf-8',\n help='open text files with specified encoding (default: %(default)s)')\n arg_parser.add_argument('--list', default=False, action='store_true',\n help='print a list of all available test sets.')\n arg_parser.add_argument('--citation', '--cite', default=False, action=\n 'store_true', help='dump the bibtex citation and quit.')\n arg_parser.add_argument('--width', '-w', type=int, default=1, help=\n 'floating point width (default: %(default)s)')\n arg_parser.add_argument('--detail', '-d', default=False, action=\n 'store_true', help=\n 'print extra information (split test sets based on origlang)')\n arg_parser.add_argument('-V', '--version', action='version', version=\n '%(prog)s {}'.format(VERSION))\n args = arg_parser.parse_args()\n return args\n\n\n<mask token>\n",
"step-5": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# Copyright 2017--2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"). You may not\n# use this file except in compliance with the License. A copy of the License\n# is located at\n#\n# http://aws.amazon.com/apache2.0/\n#\n# or in the \"license\" file accompanying this file. This file is distributed on\n# an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either\n# express or implied. See the License for the specific language governing\n# permissions and limitations under the License.\n\n\"\"\"\nSacreBLEU provides hassle-free computation of shareable, comparable, and reproducible BLEU scores.\nInspired by Rico Sennrich's `multi-bleu-detok.perl`, it produces the official WMT scores but works with plain text.\nIt also knows all the standard test sets and handles downloading, processing, and tokenization for you.\n\nSee the [README.md] file for more information.\n\"\"\"\n\nimport argparse\nimport gzip\nimport hashlib\nimport io\nimport logging\nimport math\nimport os\nimport portalocker\nimport re\nimport sys\nimport ssl\nimport urllib.request\n\nfrom collections import Counter\nfrom itertools import zip_longest\nfrom typing import List, Iterable, Tuple, Union\nfrom .tokenizer import TOKENIZERS, TokenizeMeCab\nfrom .dataset import DATASETS, DOMAINS, COUNTRIES, SUBSETS\nfrom . import __version__ as VERSION\n\nsacrelogger = logging.getLogger('sacrebleu')\n\ntry:\n # SIGPIPE is not available on Windows machines, throwing an exception.\n from signal import SIGPIPE\n\n # If SIGPIPE is available, change behaviour to default instead of ignore.\n from signal import signal, SIG_DFL\n signal(SIGPIPE, SIG_DFL)\n\nexcept ImportError:\n sacrelogger.warning('Could not import signal.SIGPIPE (this is expected on Windows machines)')\n\n# Where to store downloaded test sets.\n# Define the environment variable $SACREBLEU, or use the default of ~/.sacrebleu.\n#\n# Querying for a HOME environment variable can result in None (e.g., on Windows)\n# in which case the os.path.join() throws a TypeError. Using expanduser() is\n# a safe way to get the user's home folder.\nUSERHOME = os.path.expanduser(\"~\")\nSACREBLEU_DIR = os.environ.get('SACREBLEU', os.path.join(USERHOME, '.sacrebleu'))\n\n# n-gram order. Don't change this.\nNGRAM_ORDER = 4\n\n# Default values for CHRF\nCHRF_ORDER = 6\n# default to 2 (per http://www.aclweb.org/anthology/W16-2341)\nCHRF_BETA = 2\n\n# The default floor value to use with `--smooth floor`\nSMOOTH_VALUE_DEFAULT = {'floor': 0.0, 'add-k': 1}\n\n\nDEFAULT_TOKENIZER = '13a'\n\n\ndef smart_open(file, mode='rt', encoding='utf-8'):\n \"\"\"Convenience function for reading compressed or plain text files.\n :param file: The file to read.\n :param mode: The file mode (read, write).\n :param encoding: The file encoding.\n \"\"\"\n if file.endswith('.gz'):\n return gzip.open(file, mode=mode, encoding=encoding, newline=\"\\n\")\n return open(file, mode=mode, encoding=encoding, newline=\"\\n\")\n\n\ndef my_log(num):\n \"\"\"\n Floors the log function\n\n :param num: the number\n :return: log(num) floored to a very low number\n \"\"\"\n\n if num == 0.0:\n return -9999999999\n return math.log(num)\n\n\ndef bleu_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the signature\n \"\"\"\n\n # Abbreviations for the signature\n abbr = {\n 'test': 't',\n 'lang': 'l',\n 'smooth': 's',\n 'case': 'c',\n 'tok': 'tok',\n 'numrefs': '#',\n 'version': 'v',\n 'origlang': 'o',\n 'subset': 'S',\n }\n\n signature = {'tok': args.tokenize,\n 'version': VERSION,\n 'smooth': args.smooth,\n 'numrefs': numrefs,\n 'case': 'lc' if args.lc else 'mixed'}\n\n # For the Japanese tokenizer, add a dictionary type and its version to the signature.\n if args.tokenize == \"ja-mecab\":\n signature['tok'] += \"-\" + TokenizeMeCab().signature()\n\n if args.test_set is not None:\n signature['test'] = args.test_set\n\n if args.langpair is not None:\n signature['lang'] = args.langpair\n\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x, signature[x]) for x in sorted(signature.keys())])\n\n return sigstr\n\n\ndef chrf_signature(args, numrefs):\n \"\"\"\n Builds a signature that uniquely identifies the scoring parameters used.\n :param args: the arguments passed into the script\n :return: the chrF signature\n \"\"\"\n\n # Abbreviations for the signature\n abbr = {\n 'test': 't',\n 'lang': 'l',\n 'numchars': 'n',\n 'space': 's',\n 'case': 'c',\n 'numrefs': '#',\n 'version': 'v',\n 'origlang': 'o',\n 'subset': 'S',\n }\n\n signature = {'version': VERSION,\n 'space': args.chrf_whitespace,\n 'numchars': args.chrf_order,\n 'numrefs': numrefs,\n 'case': 'lc' if args.lc else 'mixed'}\n\n if args.test_set is not None:\n signature['test'] = args.test_set\n\n if args.langpair is not None:\n signature['lang'] = args.langpair\n\n if args.origlang is not None:\n signature['origlang'] = args.origlang\n if args.subset is not None:\n signature['subset'] = args.subset\n\n sigstr = '+'.join(['{}.{}'.format(abbr[x] if args.short else x, signature[x]) for x in sorted(signature.keys())])\n\n return sigstr\n\n\ndef extract_ngrams(line, min_order=1, max_order=NGRAM_ORDER) -> Counter:\n \"\"\"Extracts all the ngrams (min_order <= n <= max_order) from a sequence of tokens.\n\n :param line: A segment containing a sequence of words.\n :param min_order: Minimum n-gram length (default: 1).\n :param max_order: Maximum n-gram length (default: NGRAM_ORDER).\n :return: a dictionary containing ngrams and counts\n \"\"\"\n\n ngrams = Counter()\n tokens = line.split()\n for n in range(min_order, max_order + 1):\n for i in range(0, len(tokens) - n + 1):\n ngram = ' '.join(tokens[i: i + n])\n ngrams[ngram] += 1\n\n return ngrams\n\n\ndef extract_char_ngrams(s: str, n: int) -> Counter:\n \"\"\"\n Yields counts of character n-grams from string s of order n.\n \"\"\"\n return Counter([s[i:i + n] for i in range(len(s) - n + 1)])\n\n\ndef ref_stats(output, refs):\n ngrams = Counter()\n closest_diff = None\n closest_len = None\n for ref in refs:\n tokens = ref.split()\n reflen = len(tokens)\n diff = abs(len(output.split()) - reflen)\n if closest_diff is None or diff < closest_diff:\n closest_diff = diff\n closest_len = reflen\n elif diff == closest_diff:\n if reflen < closest_len:\n closest_len = reflen\n\n ngrams_ref = extract_ngrams(ref)\n for ngram in ngrams_ref.keys():\n ngrams[ngram] = max(ngrams[ngram], ngrams_ref[ngram])\n\n return ngrams, closest_diff, closest_len\n\n\ndef _clean(s):\n \"\"\"\n Removes trailing and leading spaces and collapses multiple consecutive internal spaces to a single one.\n\n :param s: The string.\n :return: A cleaned-up string.\n \"\"\"\n return re.sub(r'\\s+', ' ', s.strip())\n\n\ndef process_to_text(rawfile, txtfile, field: int=None):\n \"\"\"Processes raw files to plain text files.\n :param rawfile: the input file (possibly SGML)\n :param txtfile: the plaintext file\n :param field: For TSV files, which field to extract.\n \"\"\"\n\n if not os.path.exists(txtfile) or os.path.getsize(txtfile) == 0:\n sacrelogger.info(\"Processing %s to %s\", rawfile, txtfile)\n if rawfile.endswith('.sgm') or rawfile.endswith('.sgml'):\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub(r'<seg.*?>(.*)</seg>.*?', '\\\\1', line)), file=fout)\n elif rawfile.endswith('.xml'): # IWSLT\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n if line.startswith('<seg '):\n print(_clean(re.sub(r'<seg.*?>(.*)</seg>.*?', '\\\\1', line)), file=fout)\n elif rawfile.endswith('.txt'): # wmt17/ms\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip(), file=fout)\n elif rawfile.endswith('.tsv'): # MTNT\n with smart_open(rawfile) as fin, smart_open(txtfile, 'wt') as fout:\n for line in fin:\n print(line.rstrip().split('\\t')[field], file=fout)\n\n\ndef print_test_set(test_set, langpair, side, origlang=None, subset=None):\n \"\"\"Prints to STDOUT the specified side of the specified test set\n :param test_set: the test set to print\n :param langpair: the language pair\n :param side: 'src' for source, 'ref' for reference\n :param origlang: print only sentences with a given original language (2-char ISO639-1 code), \"non-\" prefix means negation\n :param subset: print only sentences whose document annotation matches a given regex\n \"\"\"\n\n files = download_test_set(test_set, langpair)\n if side == 'src':\n files = [files[0]]\n elif side == 'ref':\n files.pop(0)\n\n streams = [smart_open(file) for file in files]\n streams = _filter_subset(streams, test_set, langpair, origlang, subset)\n for lines in zip(*streams):\n print('\\t'.join(map(lambda x: x.rstrip(), lines)))\n\n\ndef download_test_set(test_set, langpair=None):\n \"\"\"Downloads the specified test to the system location specified by the SACREBLEU environment variable.\n\n :param test_set: the test set to download\n :param langpair: the language pair (needed for some datasets)\n :return: the set of processed files\n \"\"\"\n\n outdir = os.path.join(SACREBLEU_DIR, test_set)\n os.makedirs(outdir, exist_ok=True)\n\n expected_checksums = DATASETS[test_set].get('md5', [None] * len(DATASETS[test_set]))\n for dataset, expected_md5 in zip(DATASETS[test_set]['data'], expected_checksums):\n tarball = os.path.join(outdir, os.path.basename(dataset))\n rawdir = os.path.join(outdir, 'raw')\n\n lockfile = '{}.lock'.format(tarball)\n with portalocker.Lock(lockfile, 'w', timeout=60):\n if not os.path.exists(tarball) or os.path.getsize(tarball) == 0:\n sacrelogger.info(\"Downloading %s to %s\", dataset, tarball)\n try:\n with urllib.request.urlopen(dataset) as f, open(tarball, 'wb') as out:\n out.write(f.read())\n except ssl.SSLError:\n sacrelogger.warning('An SSL error was encountered in downloading the files. If you\\'re on a Mac, '\n 'you may need to run the \"Install Certificates.command\" file located in the '\n '\"Python 3\" folder, often found under /Applications')\n sys.exit(1)\n\n # Check md5sum\n if expected_md5 is not None:\n md5 = hashlib.md5()\n with open(tarball, 'rb') as infile:\n for line in infile:\n md5.update(line)\n if md5.hexdigest() != expected_md5:\n sacrelogger.error('Fatal: MD5 sum of downloaded file was incorrect (got {}, expected {}).'.format(md5.hexdigest(), expected_md5))\n sacrelogger.error('Please manually delete \"{}\" and rerun the command.'.format(tarball))\n sacrelogger.error('If the problem persists, the tarball may have changed, in which case, please contact the SacreBLEU maintainer.')\n sys.exit(1)\n else:\n sacrelogger.info('Checksum passed: {}'.format(md5.hexdigest()))\n\n # Extract the tarball\n sacrelogger.info('Extracting %s', tarball)\n if tarball.endswith('.tar.gz') or tarball.endswith('.tgz'):\n import tarfile\n with tarfile.open(tarball) as tar:\n tar.extractall(path=rawdir)\n elif tarball.endswith('.zip'):\n import zipfile\n with zipfile.ZipFile(tarball, 'r') as zipfile:\n zipfile.extractall(path=rawdir)\n\n found = []\n\n # Process the files into plain text\n languages = DATASETS[test_set].keys() if langpair is None else [langpair]\n for pair in languages:\n if '-' not in pair:\n continue\n src, tgt = pair.split('-')\n rawfile = DATASETS[test_set][pair][0]\n field = None # used for TSV files\n if rawfile.endswith('.tsv'):\n field, rawfile = rawfile.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, rawfile)\n outpath = os.path.join(outdir, '{}.{}'.format(pair, src))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n\n refs = DATASETS[test_set][pair][1:]\n for i, ref in enumerate(refs):\n field = None\n if ref.endswith('.tsv'):\n field, ref = ref.split(':', maxsplit=1)\n field = int(field)\n rawpath = os.path.join(rawdir, ref)\n if len(refs) >= 2:\n outpath = os.path.join(outdir, '{}.{}.{}'.format(pair, tgt, i))\n else:\n outpath = os.path.join(outdir, '{}.{}'.format(pair, tgt))\n process_to_text(rawpath, outpath, field=field)\n found.append(outpath)\n\n return found\n\n\nclass Result:\n def __init__(self, score: float):\n self.score = score\n\n def __str__(self):\n return self.format()\n\n\nclass BLEU(Result):\n def __init__(self,\n score: float,\n counts,\n totals,\n precisions,\n bp,\n sys_len,\n ref_len):\n super().__init__(score)\n\n self.counts = counts\n self.totals = totals\n self.precisions = precisions\n self.bp = bp\n self.sys_len = sys_len\n self.ref_len = ref_len\n\n def format(self, width=2):\n precisions = \"/\".join([\"{:.1f}\".format(p) for p in self.precisions])\n return 'BLEU = {score:.{width}f} {precisions} (BP = {bp:.3f} ratio = {ratio:.3f} hyp_len = {sys_len:d} ref_len = {ref_len:d})'.format(\n score=self.score,\n width=width,\n precisions=precisions,\n bp=self.bp,\n ratio=self.sys_len / self.ref_len,\n sys_len=self.sys_len,\n ref_len=self.ref_len)\n\n\nclass CHRF(Result):\n def __init__(self, score: float):\n super().__init__(score)\n\n def format(self, width=2):\n return '{score:.{width}f}'.format(score=self.score, width=width)\n\n\ndef compute_bleu(correct: List[int],\n total: List[int],\n sys_len: int,\n ref_len: int,\n smooth_method = 'none',\n smooth_value = None,\n use_effective_order = False) -> BLEU:\n \"\"\"Computes BLEU score from its sufficient statistics. Adds smoothing.\n\n Smoothing methods (citing \"A Systematic Comparison of Smoothing Techniques for Sentence-Level BLEU\",\n Boxing Chen and Colin Cherry, WMT 2014: http://aclweb.org/anthology/W14-3346)\n\n - exp: NIST smoothing method (Method 3)\n - floor: Method 1\n - add-k: Method 2 (generalizing Lin and Och, 2004)\n - none: do nothing.\n\n :param correct: List of counts of correct ngrams, 1 <= n <= NGRAM_ORDER\n :param total: List of counts of total ngrams, 1 <= n <= NGRAM_ORDER\n :param sys_len: The cumulative system length\n :param ref_len: The cumulative reference length\n :param smooth: The smoothing method to use\n :param smooth_value: The smoothing value added, if smooth method 'floor' is used\n :param use_effective_order: If true, use the length of `correct` for the n-gram order instead of NGRAM_ORDER.\n :return: A BLEU object with the score (100-based) and other statistics.\n \"\"\"\n if smooth_method in SMOOTH_VALUE_DEFAULT and smooth_value is None:\n smooth_value = SMOOTH_VALUE_DEFAULT[smooth_method]\n\n precisions = [0 for x in range(NGRAM_ORDER)]\n\n smooth_mteval = 1.\n effective_order = NGRAM_ORDER\n for n in range(1, NGRAM_ORDER + 1):\n if smooth_method == 'add-k' and n > 1:\n correct[n-1] += smooth_value\n total[n-1] += smooth_value\n if total[n-1] == 0:\n break\n\n if use_effective_order:\n effective_order = n\n\n if correct[n-1] == 0:\n if smooth_method == 'exp':\n smooth_mteval *= 2\n precisions[n-1] = 100. / (smooth_mteval * total[n-1])\n elif smooth_method == 'floor':\n precisions[n-1] = 100. * smooth_value / total[n-1]\n else:\n precisions[n-1] = 100. * correct[n-1] / total[n-1]\n\n # If the system guesses no i-grams, 1 <= i <= NGRAM_ORDER, the BLEU score is 0 (technically undefined).\n # This is a problem for sentence-level BLEU or a corpus of short sentences, where systems will get no credit\n # if sentence lengths fall under the NGRAM_ORDER threshold. This fix scales NGRAM_ORDER to the observed\n # maximum order. It is only available through the API and off by default\n\n brevity_penalty = 1.0\n if sys_len < ref_len:\n brevity_penalty = math.exp(1 - ref_len / sys_len) if sys_len > 0 else 0.0\n\n score = brevity_penalty * math.exp(sum(map(my_log, precisions[:effective_order])) / effective_order)\n\n return BLEU(score, correct, total, precisions, brevity_penalty, sys_len, ref_len)\n\n\ndef sentence_bleu(hypothesis: str,\n references: List[str],\n smooth_method: str = 'floor',\n smooth_value: float = None,\n use_effective_order: bool = True) -> BLEU:\n \"\"\"\n Computes BLEU on a single sentence pair.\n\n Disclaimer: computing BLEU on the sentence level is not its intended use,\n BLEU is a corpus-level metric.\n\n :param hypothesis: Hypothesis string.\n :param reference: Reference string.\n :param smooth_value: For 'floor' smoothing, the floor value to use.\n :param use_effective_order: Account for references that are shorter than the largest n-gram.\n :return: Returns a single BLEU score as a float.\n \"\"\"\n bleu = corpus_bleu(hypothesis, references,\n smooth_method=smooth_method,\n smooth_value=smooth_value,\n use_effective_order=use_effective_order)\n return bleu\n\n\ndef corpus_bleu(sys_stream: Union[str, Iterable[str]],\n ref_streams: Union[str, List[Iterable[str]]],\n smooth_method='exp',\n smooth_value=None,\n force=False,\n lowercase=False,\n tokenize=DEFAULT_TOKENIZER,\n use_effective_order=False) -> BLEU:\n \"\"\"Produces BLEU scores along with its sufficient statistics from a source against one or more references.\n\n :param sys_stream: The system stream (a sequence of segments)\n :param ref_streams: A list of one or more reference streams (each a sequence of segments)\n :param smooth: The smoothing method to use\n :param smooth_value: For 'floor' smoothing, the floor to use\n :param force: Ignore data that looks already tokenized\n :param lowercase: Lowercase the data\n :param tokenize: The tokenizer to use\n :return: a BLEU object containing everything you'd want\n \"\"\"\n\n # Add some robustness to the input arguments\n if isinstance(sys_stream, str):\n sys_stream = [sys_stream]\n if isinstance(ref_streams, str):\n ref_streams = [[ref_streams]]\n\n sys_len = 0\n ref_len = 0\n\n correct = [0 for n in range(NGRAM_ORDER)]\n total = [0 for n in range(NGRAM_ORDER)]\n\n # look for already-tokenized sentences\n tokenized_count = 0\n\n fhs = [sys_stream] + ref_streams\n for lines in zip_longest(*fhs):\n if None in lines:\n raise EOFError(\"Source and reference streams have different lengths!\")\n\n if lowercase:\n lines = [x.lower() for x in lines]\n\n if not (force or tokenize == 'none') and lines[0].rstrip().endswith(' .'):\n tokenized_count += 1\n\n if tokenized_count == 100:\n sacrelogger.warning('That\\'s 100 lines that end in a tokenized period (\\'.\\')')\n sacrelogger.warning('It looks like you forgot to detokenize your test data, which may hurt your score.')\n sacrelogger.warning('If you insist your data is detokenized, or don\\'t care, you can suppress this message with \\'--force\\'.')\n\n output, *refs = [TOKENIZERS[tokenize](x.rstrip()) for x in lines]\n\n ref_ngrams, closest_diff, closest_len = ref_stats(output, refs)\n\n sys_len += len(output.split())\n ref_len += closest_len\n\n sys_ngrams = extract_ngrams(output)\n for ngram in sys_ngrams.keys():\n n = len(ngram.split())\n correct[n-1] += min(sys_ngrams[ngram], ref_ngrams.get(ngram, 0))\n total[n-1] += sys_ngrams[ngram]\n\n return compute_bleu(correct, total, sys_len, ref_len, smooth_method=smooth_method, smooth_value=smooth_value, use_effective_order=use_effective_order)\n\n\ndef raw_corpus_bleu(sys_stream,\n ref_streams,\n smooth_value=None) -> BLEU:\n \"\"\"Convenience function that wraps corpus_bleu().\n This is convenient if you're using sacrebleu as a library, say for scoring on dev.\n It uses no tokenization and 'floor' smoothing, with the floor default to 0 (no smoothing).\n\n :param sys_stream: the system stream (a sequence of segments)\n :param ref_streams: a list of one or more reference streams (each a sequence of segments)\n \"\"\"\n return corpus_bleu(sys_stream, ref_streams, smooth_method='floor', smooth_value=smooth_value, force=True, tokenize='none', use_effective_order=True)\n\n\ndef delete_whitespace(text: str) -> str:\n \"\"\"\n Removes whitespaces from text.\n \"\"\"\n return re.sub(r'\\s+', '', text).strip()\n\n\ndef get_sentence_statistics(hypothesis: str,\n reference: str,\n order: int = CHRF_ORDER,\n remove_whitespace: bool = True) -> List[float]:\n hypothesis = delete_whitespace(hypothesis) if remove_whitespace else hypothesis\n reference = delete_whitespace(reference) if remove_whitespace else reference\n statistics = [0] * (order * 3)\n for i in range(order):\n n = i + 1\n hypothesis_ngrams = extract_char_ngrams(hypothesis, n)\n reference_ngrams = extract_char_ngrams(reference, n)\n common_ngrams = hypothesis_ngrams & reference_ngrams\n statistics[3 * i + 0] = sum(hypothesis_ngrams.values())\n statistics[3 * i + 1] = sum(reference_ngrams.values())\n statistics[3 * i + 2] = sum(common_ngrams.values())\n return statistics\n\n\ndef get_corpus_statistics(hypotheses: Iterable[str],\n references: Iterable[str],\n order: int = CHRF_ORDER,\n remove_whitespace: bool = True) -> List[float]:\n corpus_statistics = [0] * (order * 3)\n for hypothesis, reference in zip(hypotheses, references):\n statistics = get_sentence_statistics(hypothesis, reference, order=order, remove_whitespace=remove_whitespace)\n for i in range(len(statistics)):\n corpus_statistics[i] += statistics[i]\n return corpus_statistics\n\n\ndef _avg_precision_and_recall(statistics: List[float], order: int) -> Tuple[float, float]:\n avg_precision = 0.0\n avg_recall = 0.0\n effective_order = 0\n for i in range(order):\n hypotheses_ngrams = statistics[3 * i + 0]\n references_ngrams = statistics[3 * i + 1]\n common_ngrams = statistics[3 * i + 2]\n if hypotheses_ngrams > 0 and references_ngrams > 0:\n avg_precision += common_ngrams / hypotheses_ngrams\n avg_recall += common_ngrams / references_ngrams\n effective_order += 1\n if effective_order == 0:\n return 0.0, 0.0\n avg_precision /= effective_order\n avg_recall /= effective_order\n return avg_precision, avg_recall\n\n\ndef _chrf(avg_precision, avg_recall, beta: int = CHRF_BETA) -> float:\n if avg_precision + avg_recall == 0:\n return 0.0\n beta_square = beta ** 2\n score = (1 + beta_square) * (avg_precision * avg_recall) / ((beta_square * avg_precision) + avg_recall)\n return score\n\n\ndef corpus_chrf(hypotheses: Iterable[str],\n references: Iterable[str],\n order: int = CHRF_ORDER,\n beta: float = CHRF_BETA,\n remove_whitespace: bool = True) -> CHRF:\n \"\"\"\n Computes Chrf on a corpus.\n\n :param hypotheses: Stream of hypotheses.\n :param references: Stream of references\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete all whitespace from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n corpus_statistics = get_corpus_statistics(hypotheses, references, order=order, remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(corpus_statistics, order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\ndef sentence_chrf(hypothesis: str,\n reference: str,\n order: int = CHRF_ORDER,\n beta: float = CHRF_BETA,\n remove_whitespace: bool = True) -> CHRF:\n \"\"\"\n Computes ChrF on a single sentence pair.\n\n :param hypothesis: Hypothesis string.\n :param reference: Reference string.\n :param order: Maximum n-gram order.\n :param remove_whitespace: Whether to delete whitespaces from hypothesis and reference strings.\n :param beta: Defines importance of recall w.r.t precision. If beta=1, same importance.\n :return: Chrf score.\n \"\"\"\n statistics = get_sentence_statistics(hypothesis, reference, order=order, remove_whitespace=remove_whitespace)\n avg_precision, avg_recall = _avg_precision_and_recall(statistics, order)\n return CHRF(_chrf(avg_precision, avg_recall, beta=beta))\n\n\ndef get_langpairs_for_testset(testset: str) -> List:\n \"\"\"Return a list of language pairs for a given test set.\"\"\"\n return list(filter(lambda x: re.match('\\w\\w\\-\\w\\w', x), DATASETS.get(testset, {}).keys()))\n\n\ndef get_a_list_of_testset_names() -> str:\n \"\"\"Return a string with a formatted list of available test sets plus their descriptions. \"\"\"\n message = 'The available test sets are:'\n for testset in sorted(DATASETS.keys(), reverse=True):\n message += '\\n%20s: %s' % (testset, DATASETS[testset].get('description', ''))\n return message\n\n\ndef _available_origlangs(test_sets, langpair):\n \"\"\"Return a list of origlang values in according to the raw SGM files.\"\"\"\n origlangs = set()\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[test_set][langpair][0])\n if rawfile.endswith('.sgm'):\n with smart_open(rawfile) as fin:\n for line in fin:\n if line.startswith('<doc '):\n doc_origlang = re.sub(r'.* origlang=\"([^\"]+)\".*\\n', '\\\\1', line)\n origlangs.add(doc_origlang)\n return sorted(list(origlangs))\n\n\ndef _filter_subset(systems, test_sets, langpair, origlang, subset=None):\n \"\"\"Filter sentences with a given origlang (or subset) according to the raw SGM files.\"\"\"\n if origlang is None and subset is None:\n return systems\n if test_sets is None or langpair is None:\n raise ValueError('Filtering for --origlang or --subset needs a test (-t) and a language pair (-l).')\n\n indices_to_keep = []\n for test_set in test_sets.split(','):\n rawfile = os.path.join(SACREBLEU_DIR, test_set, 'raw', DATASETS[test_set][langpair][0])\n if not rawfile.endswith('.sgm'):\n raise Exception('--origlang and --subset supports only *.sgm files, not %s', rawfile)\n if subset is not None:\n if test_set not in SUBSETS:\n raise Exception('No subset annotation available for test set ' + test_set)\n doc_to_tags = SUBSETS[test_set]\n number_sentences_included = 0\n with smart_open(rawfile) as fin:\n include_doc = False\n for line in fin:\n if line.startswith('<doc '):\n if origlang is None:\n include_doc = True\n else:\n doc_origlang = re.sub(r'.* origlang=\"([^\"]+)\".*\\n', '\\\\1', line)\n if origlang.startswith('non-'):\n include_doc = doc_origlang != origlang[4:]\n else:\n include_doc = doc_origlang == origlang\n if subset is not None:\n doc_id = re.sub(r'.* docid=\"([^\"]+)\".*\\n', '\\\\1', line)\n if not re.search(subset, doc_to_tags.get(doc_id, '')):\n include_doc = False\n if line.startswith('<seg '):\n indices_to_keep.append(include_doc)\n number_sentences_included += 1 if include_doc else 0\n return [[sentence for sentence,keep in zip(sys, indices_to_keep) if keep] for sys in systems]\n\n\ndef main():\n args = parse_args()\n\n # Explicitly set the encoding\n sys.stdin = open(sys.stdin.fileno(), mode='r', encoding='utf-8', buffering=True, newline=\"\\n\")\n sys.stdout = open(sys.stdout.fileno(), mode='w', encoding='utf-8', buffering=True)\n\n if not args.quiet:\n logging.basicConfig(level=logging.INFO, format='sacreBLEU: %(message)s')\n\n if args.download:\n download_test_set(args.download, args.langpair)\n sys.exit(0)\n\n if args.list:\n if args.test_set:\n print(' '.join(get_langpairs_for_testset(args.test_set)))\n else:\n print(get_a_list_of_testset_names())\n sys.exit(0)\n\n if args.sentence_level and len(args.metrics) > 1:\n sacrelogger.error('Only one metric can be used with Sentence-level reporting.')\n sys.exit(1)\n\n if args.citation:\n if not args.test_set:\n sacrelogger.error('I need a test set (-t).')\n sys.exit(1)\n for test_set in args.test_set.split(','):\n if 'citation' not in DATASETS[test_set]:\n sacrelogger.error('No citation found for %s', test_set)\n else:\n print(DATASETS[test_set]['citation'])\n sys.exit(0)\n\n if args.num_refs != 1 and (args.test_set is not None or len(args.refs) > 1):\n sacrelogger.error('The --num-refs argument allows you to provide any number of tab-delimited references in a single file.')\n sacrelogger.error('You can only use it with externaly-provided references, however (i.e., not with `-t`),')\n sacrelogger.error('and you cannot then provide multiple reference files.')\n sys.exit(1)\n\n if args.test_set is not None:\n for test_set in args.test_set.split(','):\n if test_set not in DATASETS:\n sacrelogger.error('Unknown test set \"%s\"\\n%s', test_set, get_a_list_of_testset_names())\n sys.exit(1)\n\n if args.test_set is None:\n if len(args.refs) == 0:\n sacrelogger.error('I need either a predefined test set (-t) or a list of references')\n sacrelogger.error(get_a_list_of_testset_names())\n sys.exit(1)\n elif len(args.refs) > 0:\n sacrelogger.error('I need exactly one of (a) a predefined test set (-t) or (b) a list of references')\n sys.exit(1)\n elif args.langpair is None:\n sacrelogger.error('I need a language pair (-l).')\n sys.exit(1)\n else:\n for test_set in args.test_set.split(','):\n if args.langpair not in DATASETS[test_set]:\n sacrelogger.error('No such language pair \"%s\"', args.langpair)\n sacrelogger.error('Available language pairs for test set \"%s\": %s', test_set,\n ', '.join(x for x in DATASETS[test_set].keys() if '-' in x))\n sys.exit(1)\n\n if args.echo:\n if args.langpair is None or args.test_set is None:\n sacrelogger.warning(\"--echo requires a test set (--t) and a language pair (-l)\")\n sys.exit(1)\n for test_set in args.test_set.split(','):\n print_test_set(test_set, args.langpair, args.echo, args.origlang, args.subset)\n sys.exit(0)\n\n if args.test_set is not None and args.tokenize == 'none':\n sacrelogger.warning(\"You are turning off sacrebleu's internal tokenization ('--tokenize none'), presumably to supply\\n\"\n \"your own reference tokenization. Published numbers will not be comparable with other papers.\\n\")\n\n # Internal tokenizer settings. Set to 'zh' for Chinese DEFAULT_TOKENIZER (\n if args.tokenize is None:\n # set default\n if args.langpair is not None and args.langpair.split('-')[1] == 'zh':\n args.tokenize = 'zh'\n elif args.langpair is not None and args.langpair.split('-')[1] == 'ja':\n args.tokenize = 'ja-mecab'\n else:\n args.tokenize = DEFAULT_TOKENIZER\n\n if args.langpair is not None and 'bleu' in args.metrics:\n if args.langpair.split('-')[1] == 'zh' and args.tokenize != 'zh':\n logger.warning('You should also pass \"--tok zh\" when scoring Chinese...')\n if args.langpair.split('-')[1] == 'ja' and not args.tokenize.startswith('ja-'):\n logger.warning('You should also pass \"--tok ja-mecab\" when scoring Japanese...')\n\n # concat_ref_files is a list of list of reference filenames, for example:\n # concat_ref_files = [[testset1_refA, testset1_refB], [testset2_refA, testset2_refB]]\n if args.test_set is None:\n concat_ref_files = [args.refs]\n else:\n concat_ref_files = []\n for test_set in args.test_set.split(','):\n _, *ref_files = download_test_set(test_set, args.langpair)\n if len(ref_files) == 0:\n sacrelogger.warning('No references found for test set {}/{}.'.format(test_set, args.langpair))\n concat_ref_files.append(ref_files)\n\n\n inputfh = io.TextIOWrapper(sys.stdin.buffer, encoding=args.encoding) if args.input == '-' else smart_open(args.input, encoding=args.encoding)\n full_system = inputfh.readlines()\n\n # Read references\n full_refs = [[] for x in range(max(len(concat_ref_files[0]), args.num_refs))]\n for ref_files in concat_ref_files:\n for refno, ref_file in enumerate(ref_files):\n for lineno, line in enumerate(smart_open(ref_file, encoding=args.encoding), 1):\n if args.num_refs != 1:\n splits = line.rstrip().split(sep='\\t', maxsplit=args.num_refs-1)\n if len(splits) != args.num_refs:\n sacrelogger.error('FATAL: line {}: expected {} fields, but found {}.'.format(lineno, args.num_refs, len(splits)))\n sys.exit(17)\n for refno, split in enumerate(splits):\n full_refs[refno].append(split)\n else:\n full_refs[refno].append(line)\n\n # Filter sentences according to a given origlang\n system, *refs = _filter_subset([full_system, *full_refs], args.test_set, args.langpair, args.origlang, args.subset)\n if len(system) == 0:\n message = 'Test set %s contains no sentence' % args.test_set\n if args.origlang is not None or args.subset is not None:\n message += ' with'\n message += '' if args.origlang is None else ' origlang=' + args.origlang\n message += '' if args.subset is None else ' subset=' + args.subset\n sacrelogger.error(message)\n exit(1)\n\n # Handle sentence level and quit\n if args.sentence_level:\n for output, *references in zip(system, *refs):\n results = []\n for metric in args.metrics:\n if metric == 'bleu':\n bleu = sentence_bleu(output,\n [[x] for x in references],\n smooth_method=args.smooth,\n smooth_value=args.smooth_value)\n results.append(bleu)\n if metric == 'chrf':\n chrf = sentence_chrf(output,\n references[0],\n args.chrf_order,\n args.chrf_beta,\n remove_whitespace=not args.chrf_whitespace)\n results.append(chrf)\n\n display_metric(args.metrics, results, len(refs), args)\n\n sys.exit(0)\n\n # Else, handle system level\n results = []\n try:\n for metric in args.metrics:\n if metric == 'bleu':\n bleu = corpus_bleu(system, refs, smooth_method=args.smooth, smooth_value=args.smooth_value, force=args.force, lowercase=args.lc, tokenize=args.tokenize)\n results.append(bleu)\n elif metric == 'chrf':\n chrf = corpus_chrf(system, refs[0], beta=args.chrf_beta, order=args.chrf_order, remove_whitespace=not args.chrf_whitespace)\n results.append(chrf)\n except EOFError:\n sacrelogger.error('The input and reference stream(s) were of different lengths.')\n if args.test_set is not None:\n sacrelogger.error('\\nThis could be a problem with your system output or with sacreBLEU\\'s reference database.\\n'\n 'If the latter, you can clean out the references cache by typing:\\n'\n '\\n'\n ' rm -r %s/%s\\n'\n '\\n'\n 'They will be downloaded automatically again the next time you run sacreBLEU.', SACREBLEU_DIR,\n args.test_set)\n sys.exit(1)\n\n display_metric(args.metrics, results, len(refs), args)\n\n if args.detail:\n width = args.width\n sents_digits = len(str(len(full_system)))\n origlangs = args.origlang if args.origlang else _available_origlangs(args.test_set, args.langpair)\n for origlang in origlangs:\n subsets = [None]\n if args.subset is not None:\n subsets += [args.subset]\n elif all(t in SUBSETS for t in args.test_set.split(',')):\n subsets += COUNTRIES + DOMAINS\n for subset in subsets:\n system, *refs = _filter_subset([full_system, *full_refs], args.test_set, args.langpair, origlang, subset)\n if len(system) == 0:\n continue\n if subset in COUNTRIES:\n subset_str = '%20s' % ('country=' + subset)\n elif subset in DOMAINS:\n subset_str = '%20s' % ('domain=' + subset)\n else:\n subset_str = '%20s' % ''\n if 'bleu' in args.metrics:\n bleu = corpus_bleu(system, refs, smooth_method=args.smooth, smooth_value=args.smooth_value, force=args.force, lowercase=args.lc, tokenize=args.tokenize)\n print('origlang={} {}: sentences={:{}} BLEU={:{}.{}f}'.format(origlang, subset_str, len(system), sents_digits, bleu.score, width+4, width))\n if 'chrf' in args.metrics:\n chrf = corpus_chrf(system, refs[0], beta=args.chrf_beta, order=args.chrf_order, remove_whitespace=not args.chrf_whitespace)\n print('origlang={} {}: sentences={:{}} chrF={:{}.{}f}'.format(origlang, subset_str, len(system), sents_digits, chrf.score, width+4, width))\n\n\ndef display_metric(metrics_to_print, results, num_refs, args):\n \"\"\"\n Badly in need of refactoring.\n One idea is to put all of this in the BLEU and CHRF classes, and then define\n a Result::signature() function.\n \"\"\"\n for metric, result in zip(metrics_to_print, results):\n if metric == 'bleu':\n if args.score_only:\n print('{0:.{1}f}'.format(result.score, args.width))\n else:\n version_str = bleu_signature(args, num_refs)\n print(result.format(args.width).replace('BLEU', 'BLEU+' + version_str))\n\n elif metric == 'chrf':\n if args.score_only:\n print('{0:.{1}f}'.format(result.score, args.width))\n else:\n version_str = chrf_signature(args, num_refs)\n print('chrF{0:d}+{1} = {2:.{3}f}'.format(args.chrf_beta, version_str, result.score, args.width))\n\n\ndef parse_args():\n arg_parser = argparse.ArgumentParser(\n description='sacreBLEU: Hassle-free computation of shareable BLEU scores.\\n'\n 'Quick usage: score your detokenized output against WMT\\'14 EN-DE:\\n'\n ' cat output.detok.de | sacrebleu -t wmt14 -l en-de',\n # epilog = 'Available test sets: ' + ','.join(sorted(DATASETS.keys(), reverse=True)),\n formatter_class=argparse.RawDescriptionHelpFormatter)\n arg_parser.add_argument('--test-set', '-t', type=str, default=None,\n help='the test set to use (see also --list) or a comma-separated list of test sets to be concatenated')\n arg_parser.add_argument('-lc', action='store_true', default=False,\n help='Use case-insensitive BLEU (default: actual case)')\n arg_parser.add_argument('--sentence-level', '-sl', action='store_true',\n help='Output metric on each sentence.')\n arg_parser.add_argument('--smooth', '-s', choices=['exp', 'floor', 'add-k', 'none'],\n default='exp',\n help='smoothing method: exponential decay (default), floor (increment zero counts), add-k (increment num/denom by k for n>1), or none')\n arg_parser.add_argument('--smooth-value', '-sv', type=float, default=None,\n help='The value to pass to the smoothing technique, only used for floor and add-k. Default floor: {}, add-k: {}.'.format(\n SMOOTH_VALUE_DEFAULT['floor'], SMOOTH_VALUE_DEFAULT['add-k']))\n arg_parser.add_argument('--tokenize', '-tok', choices=TOKENIZERS.keys(), default=None,\n help='tokenization method to use')\n arg_parser.add_argument('--language-pair', '-l', dest='langpair', default=None,\n help='source-target language pair (2-char ISO639-1 codes)')\n arg_parser.add_argument('--origlang', '-ol', dest='origlang', default=None,\n help='use a subset of sentences with a given original language (2-char ISO639-1 codes), \"non-\" prefix means negation')\n arg_parser.add_argument('--subset', dest='subset', default=None,\n help='use a subset of sentences whose document annotation matches a give regex (see SUBSETS in the source code)')\n arg_parser.add_argument('--download', type=str, default=None,\n help='download a test set and quit')\n arg_parser.add_argument('--echo', choices=['src', 'ref', 'both'], type=str, default=None,\n help='output the source (src), reference (ref), or both (both, pasted) to STDOUT and quit')\n arg_parser.add_argument('--input', '-i', type=str, default='-',\n help='Read input from a file instead of STDIN')\n arg_parser.add_argument('--num-refs', '-nr', type=int, default=1,\n help='Split the reference stream on tabs, and expect this many references. Default: %(default)s.')\n arg_parser.add_argument('refs', nargs='*', default=[],\n help='optional list of references (for backwards-compatibility with older scripts)')\n arg_parser.add_argument('--metrics', '-m', choices=['bleu', 'chrf'], nargs='+',\n default=['bleu'],\n help='metrics to compute (default: bleu)')\n arg_parser.add_argument('--chrf-order', type=int, default=CHRF_ORDER,\n help='chrf character order (default: %(default)s)')\n arg_parser.add_argument('--chrf-beta', type=int, default=CHRF_BETA,\n help='chrf BETA parameter (default: %(default)s)')\n arg_parser.add_argument('--chrf-whitespace', action='store_true', default=False,\n help='include whitespace in chrF calculation (default: %(default)s)')\n arg_parser.add_argument('--short', default=False, action='store_true',\n help='produce a shorter (less human readable) signature')\n arg_parser.add_argument('--score-only', '-b', default=False, action='store_true',\n help='output only the BLEU score')\n arg_parser.add_argument('--force', default=False, action='store_true',\n help='insist that your tokenized input is actually detokenized')\n arg_parser.add_argument('--quiet', '-q', default=False, action='store_true',\n help='suppress informative output')\n arg_parser.add_argument('--encoding', '-e', type=str, default='utf-8',\n help='open text files with specified encoding (default: %(default)s)')\n arg_parser.add_argument('--list', default=False, action='store_true',\n help='print a list of all available test sets.')\n arg_parser.add_argument('--citation', '--cite', default=False, action='store_true',\n help='dump the bibtex citation and quit.')\n arg_parser.add_argument('--width', '-w', type=int, default=1,\n help='floating point width (default: %(default)s)')\n arg_parser.add_argument('--detail', '-d', default=False, action='store_true',\n help='print extra information (split test sets based on origlang)')\n arg_parser.add_argument('-V', '--version', action='version',\n version='%(prog)s {}'.format(VERSION))\n args = arg_parser.parse_args()\n return args\n\n\nif __name__ == '__main__':\n main()\n",
"step-ids": [
27,
29,
31,
37,
42
]
}
|
[
27,
29,
31,
37,
42
] |
class Solution(object):
def lexicalOrder(self, n):
"""
:type n: int
:rtype: List[int]
"""
acc = []
self.backtrack(acc, 1, n)
return acc
def backtrack(self, acc, counter, n):
if counter > n:
return
elif len(acc) == n:
return
else:
acc.append(counter)
self.backtrack(acc, counter * 10, n)
if counter % 10 != 9:
self.backtrack(acc, counter + 1, n)
|
normal
|
{
"blob_id": "79f4ede16628c6fbf37dfb4fe5afb8489c120f5a",
"index": 6597,
"step-1": "<mask token>\n",
"step-2": "class Solution(object):\n <mask token>\n <mask token>\n",
"step-3": "class Solution(object):\n\n def lexicalOrder(self, n):\n \"\"\"\n :type n: int\n :rtype: List[int]\n \"\"\"\n acc = []\n self.backtrack(acc, 1, n)\n return acc\n <mask token>\n",
"step-4": "class Solution(object):\n\n def lexicalOrder(self, n):\n \"\"\"\n :type n: int\n :rtype: List[int]\n \"\"\"\n acc = []\n self.backtrack(acc, 1, n)\n return acc\n\n def backtrack(self, acc, counter, n):\n if counter > n:\n return\n elif len(acc) == n:\n return\n else:\n acc.append(counter)\n self.backtrack(acc, counter * 10, n)\n if counter % 10 != 9:\n self.backtrack(acc, counter + 1, n)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
#roblem: Have the function PrimeTime(num)
# take the num parameter being passed and return
# the string true if the parameter is a prime number, \
# otherwise return the string false.
# The range will be between 1 and 2^16.
def PrimeTime(num):
prime1 = (num-1)%6
prime2 = (num+1)%6
if prime1 * prime2 == 0:
return 'True'
else:
return 'False'
print(PrimeTime(12))
|
normal
|
{
"blob_id": "5068a78a1aa31a277b3b5854ddd1d8990d07b104",
"index": 3627,
"step-1": "<mask token>\n",
"step-2": "def PrimeTime(num):\n prime1 = (num - 1) % 6\n prime2 = (num + 1) % 6\n if prime1 * prime2 == 0:\n return 'True'\n else:\n return 'False'\n\n\n<mask token>\n",
"step-3": "def PrimeTime(num):\n prime1 = (num - 1) % 6\n prime2 = (num + 1) % 6\n if prime1 * prime2 == 0:\n return 'True'\n else:\n return 'False'\n\n\nprint(PrimeTime(12))\n",
"step-4": "#roblem: Have the function PrimeTime(num) \n# take the num parameter being passed and return \n# the string true if the parameter is a prime number, \\\n# otherwise return the string false.\n# The range will be between 1 and 2^16.\n\ndef PrimeTime(num):\n\n prime1 = (num-1)%6\n prime2 = (num+1)%6\n\n if prime1 * prime2 == 0:\n return 'True'\n else:\n return 'False'\n\nprint(PrimeTime(12))",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
import datetime
class assignmentObject:
def __init__(self, name, day):
self.name = name
self.day = day
|
normal
|
{
"blob_id": "1673214215043644e1a878ed7c30b69064f1a022",
"index": 5375,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass assignmentObject:\n <mask token>\n",
"step-3": "<mask token>\n\n\nclass assignmentObject:\n\n def __init__(self, name, day):\n self.name = name\n self.day = day\n",
"step-4": "import datetime\n\n\nclass assignmentObject:\n\n def __init__(self, name, day):\n self.name = name\n self.day = day\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def TheRabbitsFoot(s, encode):
if encode:
return encode_s(s)
return decode_s(s)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def decode_s(s):
arr = s.split(' ')
decoded_s = ''
for j in range(0, len(arr[0])):
for word in arr:
if len(word) > j:
decoded_s = decoded_s + word[j]
return decoded_s
def TheRabbitsFoot(s, encode):
if encode:
return encode_s(s)
return decode_s(s)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def encode_s(s):
encoded_s = ''
s_with_no_spaces = s.replace(' ', '')
step = ceil(sqrt(len(s_with_no_spaces)))
for j in range(0, step):
i = j
while i < len(s_with_no_spaces):
encoded_s = encoded_s + s_with_no_spaces[i]
i += step
if j != step - 1:
encoded_s = encoded_s + ' '
return encoded_s
def decode_s(s):
arr = s.split(' ')
decoded_s = ''
for j in range(0, len(arr[0])):
for word in arr:
if len(word) > j:
decoded_s = decoded_s + word[j]
return decoded_s
def TheRabbitsFoot(s, encode):
if encode:
return encode_s(s)
return decode_s(s)
<|reserved_special_token_1|>
from math import sqrt, ceil
def encode_s(s):
encoded_s = ''
s_with_no_spaces = s.replace(' ', '')
step = ceil(sqrt(len(s_with_no_spaces)))
for j in range(0, step):
i = j
while i < len(s_with_no_spaces):
encoded_s = encoded_s + s_with_no_spaces[i]
i += step
if j != step - 1:
encoded_s = encoded_s + ' '
return encoded_s
def decode_s(s):
arr = s.split(' ')
decoded_s = ''
for j in range(0, len(arr[0])):
for word in arr:
if len(word) > j:
decoded_s = decoded_s + word[j]
return decoded_s
def TheRabbitsFoot(s, encode):
if encode:
return encode_s(s)
return decode_s(s)
|
flexible
|
{
"blob_id": "a3ed47c285b26dca452fa192eb354a21a78b8424",
"index": 4632,
"step-1": "<mask token>\n\n\ndef TheRabbitsFoot(s, encode):\n if encode:\n return encode_s(s)\n return decode_s(s)\n",
"step-2": "<mask token>\n\n\ndef decode_s(s):\n arr = s.split(' ')\n decoded_s = ''\n for j in range(0, len(arr[0])):\n for word in arr:\n if len(word) > j:\n decoded_s = decoded_s + word[j]\n return decoded_s\n\n\ndef TheRabbitsFoot(s, encode):\n if encode:\n return encode_s(s)\n return decode_s(s)\n",
"step-3": "<mask token>\n\n\ndef encode_s(s):\n encoded_s = ''\n s_with_no_spaces = s.replace(' ', '')\n step = ceil(sqrt(len(s_with_no_spaces)))\n for j in range(0, step):\n i = j\n while i < len(s_with_no_spaces):\n encoded_s = encoded_s + s_with_no_spaces[i]\n i += step\n if j != step - 1:\n encoded_s = encoded_s + ' '\n return encoded_s\n\n\ndef decode_s(s):\n arr = s.split(' ')\n decoded_s = ''\n for j in range(0, len(arr[0])):\n for word in arr:\n if len(word) > j:\n decoded_s = decoded_s + word[j]\n return decoded_s\n\n\ndef TheRabbitsFoot(s, encode):\n if encode:\n return encode_s(s)\n return decode_s(s)\n",
"step-4": "from math import sqrt, ceil\n\n\ndef encode_s(s):\n encoded_s = ''\n s_with_no_spaces = s.replace(' ', '')\n step = ceil(sqrt(len(s_with_no_spaces)))\n for j in range(0, step):\n i = j\n while i < len(s_with_no_spaces):\n encoded_s = encoded_s + s_with_no_spaces[i]\n i += step\n if j != step - 1:\n encoded_s = encoded_s + ' '\n return encoded_s\n\n\ndef decode_s(s):\n arr = s.split(' ')\n decoded_s = ''\n for j in range(0, len(arr[0])):\n for word in arr:\n if len(word) > j:\n decoded_s = decoded_s + word[j]\n return decoded_s\n\n\ndef TheRabbitsFoot(s, encode):\n if encode:\n return encode_s(s)\n return decode_s(s)\n",
"step-5": null,
"step-ids": [
1,
2,
3,
4
]
}
|
[
1,
2,
3,
4
] |
<|reserved_special_token_0|>
class StageOneCustomize:
<|reserved_special_token_0|>
def __init__(self, process, customize, metaConditions):
self.process = process
self.customize = customize
self.metaConditions = metaConditions
self.modifyForttH = True
self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [
'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [
'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [
'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [
'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [
'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [
'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],
['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0
], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',
0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',
0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [
'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2',
0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [
'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',
0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],
['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [
'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [
'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],
['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',
0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],
['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],
['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [
'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',
0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [
'RECO_WH_LEP_PTV_75_150_Tag0', 0], [
'RECO_WH_LEP_PTV_75_150_Tag1', 0], [
'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [
'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [
'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [
'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',
0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [
'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [
'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]
if self.customize.processId == 'Data':
self.tagList.pop(1)
self.stageOneVariable = [
'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']
self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(
'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(
'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(
'flashggStageOneCombinedTag')))
self.customizeTagSequence()
<|reserved_special_token_0|>
def systematicVariables(self):
systematicVariables = []
systematicVariables += self.stageOneVariable
systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']
return systematicVariables
def noTagVariables(self):
noTagVariables = []
noTagVariables += self.stageOneVariable
for direction in ['Up', 'Down']:
noTagVariables.append(
'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mu%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Res%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig01%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig12%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF2j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF3j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT60%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT120%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_qmtop%s01sigma")'
% (direction, direction))
return noTagVariables
def customizeTagSequence(self):
self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')
self.process.flashggTagSequence.remove(self.process.
flashggVBFDiPhoDiJetMVA)
self.process.flashggTagSequence.remove(self.process.
flashggTTHDiLeptonTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHLeptonicTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHHadronicTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHLeptonicLooseTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHHadronicTag)
self.process.flashggTagSequence.remove(self.process.flashggVBFTag)
self.process.flashggTagSequence.replace(self.process.
flashggUntagged, self.process.flashggStageOneCombinedTag)
self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])
self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])
self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self
.metaConditions['stageOneCombinedTag']['rawGghBounds'])
self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])
self.metaConditions['L1Prefiring']['applyToCentral'] = True
self.process.flashggTagSorter.TagPriorityRanges = (self.
tagPriorityRanges)
self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.
customize.processId.count('ggh')))
self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.
customize.applyNNLOPSweight)
self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src
=cms.VInputTag('flashggTagSorter'))
def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,
jetsystlabels):
for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:
getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(
phosystlabels)
getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels
)
getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)
getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(
True)
getattr(self.process, tag).UseLargeMVAs = cms.bool(True)
self.process.p.remove(self.process.flashggTagSorter)
self.process.p.replace(self.process.flashggSystTagMerger, cms.
Sequence(self.process.flashggTTHLeptonicTag + self.process.
flashggTTHHadronicTag) * self.process.flashggTagSorter * self.
process.flashggSystTagMerger)
for systlabel in systlabels:
if systlabel == '':
continue
self.process.p.remove(getattr(self.process, 'flashggTagSorter' +
systlabel))
self.process.p.replace(self.process.flashggSystTagMerger,
getattr(self.process, 'flashggTagSorter' + systlabel) *
self.process.flashggSystTagMerger)
modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.
InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(
TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),
cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +
systlabel)), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.
InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(
TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.
PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +
systlabel)))
setattr(getattr(self.process, 'flashggTagSorter' + systlabel),
'TagPriorityRanges', modifiedPriorityRanges)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class StageOneCustomize:
<|reserved_special_token_0|>
def __init__(self, process, customize, metaConditions):
self.process = process
self.customize = customize
self.metaConditions = metaConditions
self.modifyForttH = True
self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [
'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [
'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [
'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [
'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [
'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [
'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],
['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0
], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',
0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',
0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [
'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2',
0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [
'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',
0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],
['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [
'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [
'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],
['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',
0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],
['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],
['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [
'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',
0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [
'RECO_WH_LEP_PTV_75_150_Tag0', 0], [
'RECO_WH_LEP_PTV_75_150_Tag1', 0], [
'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [
'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [
'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [
'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',
0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [
'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [
'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]
if self.customize.processId == 'Data':
self.tagList.pop(1)
self.stageOneVariable = [
'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']
self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(
'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(
'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(
'flashggStageOneCombinedTag')))
self.customizeTagSequence()
def variablesToDump(self):
ws_variables = []
ws_variables += self.stageOneVariable
ws_variables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass',
'dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)',
'NNLOPSweight[1,-999999.,999999.] := tagTruth().weight("NNLOPSweight")'
,
'btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight("btagReshapeNorm_TTH_LEP")'
,
'btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight("btagReshapeNorm_TTH_HAD")'
,
'btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight("btagReshapeNorm_THQ_LEP")'
, 'centralObjectWeight[1,-999999.,999999.] := centralWeight']
ntup_variables = ws_variables
if self.customize.dumpWorkspace:
return ws_variables
else:
return ntup_variables
def systematicVariables(self):
systematicVariables = []
systematicVariables += self.stageOneVariable
systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']
return systematicVariables
def noTagVariables(self):
noTagVariables = []
noTagVariables += self.stageOneVariable
for direction in ['Up', 'Down']:
noTagVariables.append(
'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mu%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Res%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig01%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig12%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF2j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF3j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT60%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT120%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_qmtop%s01sigma")'
% (direction, direction))
return noTagVariables
def customizeTagSequence(self):
self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')
self.process.flashggTagSequence.remove(self.process.
flashggVBFDiPhoDiJetMVA)
self.process.flashggTagSequence.remove(self.process.
flashggTTHDiLeptonTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHLeptonicTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHHadronicTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHLeptonicLooseTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHHadronicTag)
self.process.flashggTagSequence.remove(self.process.flashggVBFTag)
self.process.flashggTagSequence.replace(self.process.
flashggUntagged, self.process.flashggStageOneCombinedTag)
self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])
self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])
self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self
.metaConditions['stageOneCombinedTag']['rawGghBounds'])
self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])
self.metaConditions['L1Prefiring']['applyToCentral'] = True
self.process.flashggTagSorter.TagPriorityRanges = (self.
tagPriorityRanges)
self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.
customize.processId.count('ggh')))
self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.
customize.applyNNLOPSweight)
self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src
=cms.VInputTag('flashggTagSorter'))
def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,
jetsystlabels):
for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:
getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(
phosystlabels)
getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels
)
getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)
getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(
True)
getattr(self.process, tag).UseLargeMVAs = cms.bool(True)
self.process.p.remove(self.process.flashggTagSorter)
self.process.p.replace(self.process.flashggSystTagMerger, cms.
Sequence(self.process.flashggTTHLeptonicTag + self.process.
flashggTTHHadronicTag) * self.process.flashggTagSorter * self.
process.flashggSystTagMerger)
for systlabel in systlabels:
if systlabel == '':
continue
self.process.p.remove(getattr(self.process, 'flashggTagSorter' +
systlabel))
self.process.p.replace(self.process.flashggSystTagMerger,
getattr(self.process, 'flashggTagSorter' + systlabel) *
self.process.flashggSystTagMerger)
modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.
InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(
TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),
cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +
systlabel)), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.
InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(
TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.
PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +
systlabel)))
setattr(getattr(self.process, 'flashggTagSorter' + systlabel),
'TagPriorityRanges', modifiedPriorityRanges)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class StageOneCustomize:
"""
Customizaton class for STXS stage 1 analysis
"""
def __init__(self, process, customize, metaConditions):
self.process = process
self.customize = customize
self.metaConditions = metaConditions
self.modifyForttH = True
self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [
'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [
'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [
'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [
'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [
'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [
'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],
['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0
], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',
0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',
0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [
'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2',
0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [
'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',
0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],
['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [
'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [
'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],
['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',
0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],
['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],
['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [
'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',
0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [
'RECO_WH_LEP_PTV_75_150_Tag0', 0], [
'RECO_WH_LEP_PTV_75_150_Tag1', 0], [
'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [
'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [
'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [
'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',
0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [
'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [
'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]
if self.customize.processId == 'Data':
self.tagList.pop(1)
self.stageOneVariable = [
'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']
self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(
'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(
'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(
'flashggStageOneCombinedTag')))
self.customizeTagSequence()
def variablesToDump(self):
ws_variables = []
ws_variables += self.stageOneVariable
ws_variables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass',
'dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)',
'NNLOPSweight[1,-999999.,999999.] := tagTruth().weight("NNLOPSweight")'
,
'btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight("btagReshapeNorm_TTH_LEP")'
,
'btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight("btagReshapeNorm_TTH_HAD")'
,
'btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight("btagReshapeNorm_THQ_LEP")'
, 'centralObjectWeight[1,-999999.,999999.] := centralWeight']
ntup_variables = ws_variables
if self.customize.dumpWorkspace:
return ws_variables
else:
return ntup_variables
def systematicVariables(self):
systematicVariables = []
systematicVariables += self.stageOneVariable
systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']
return systematicVariables
def noTagVariables(self):
noTagVariables = []
noTagVariables += self.stageOneVariable
for direction in ['Up', 'Down']:
noTagVariables.append(
'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mu%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Res%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig01%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig12%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF2j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF3j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT60%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT120%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_qmtop%s01sigma")'
% (direction, direction))
return noTagVariables
def customizeTagSequence(self):
self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')
self.process.flashggTagSequence.remove(self.process.
flashggVBFDiPhoDiJetMVA)
self.process.flashggTagSequence.remove(self.process.
flashggTTHDiLeptonTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHLeptonicTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHHadronicTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHLeptonicLooseTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHHadronicTag)
self.process.flashggTagSequence.remove(self.process.flashggVBFTag)
self.process.flashggTagSequence.replace(self.process.
flashggUntagged, self.process.flashggStageOneCombinedTag)
self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])
self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])
self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self
.metaConditions['stageOneCombinedTag']['rawGghBounds'])
self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])
self.metaConditions['L1Prefiring']['applyToCentral'] = True
self.process.flashggTagSorter.TagPriorityRanges = (self.
tagPriorityRanges)
self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.
customize.processId.count('ggh')))
self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.
customize.applyNNLOPSweight)
self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src
=cms.VInputTag('flashggTagSorter'))
def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,
jetsystlabels):
for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:
getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(
phosystlabels)
getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels
)
getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)
getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(
True)
getattr(self.process, tag).UseLargeMVAs = cms.bool(True)
self.process.p.remove(self.process.flashggTagSorter)
self.process.p.replace(self.process.flashggSystTagMerger, cms.
Sequence(self.process.flashggTTHLeptonicTag + self.process.
flashggTTHHadronicTag) * self.process.flashggTagSorter * self.
process.flashggSystTagMerger)
for systlabel in systlabels:
if systlabel == '':
continue
self.process.p.remove(getattr(self.process, 'flashggTagSorter' +
systlabel))
self.process.p.replace(self.process.flashggSystTagMerger,
getattr(self.process, 'flashggTagSorter' + systlabel) *
self.process.flashggSystTagMerger)
modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.
InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(
TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),
cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +
systlabel)), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.
InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(
TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.
PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +
systlabel)))
setattr(getattr(self.process, 'flashggTagSorter' + systlabel),
'TagPriorityRanges', modifiedPriorityRanges)
<|reserved_special_token_1|>
import FWCore.ParameterSet.Config as cms
class StageOneCustomize:
"""
Customizaton class for STXS stage 1 analysis
"""
def __init__(self, process, customize, metaConditions):
self.process = process
self.customize = customize
self.metaConditions = metaConditions
self.modifyForttH = True
self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [
'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [
'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [
'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [
'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [
'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [
'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],
['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0
], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',
0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',
0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [
'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2',
0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [
'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',
0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],
['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [
'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [
'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],
['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [
'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',
0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],
['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],
['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [
'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [
'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [
'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [
'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [
'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',
0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [
'RECO_WH_LEP_PTV_75_150_Tag0', 0], [
'RECO_WH_LEP_PTV_75_150_Tag1', 0], [
'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [
'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [
'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [
'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',
0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [
'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [
'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [
'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [
'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]
if self.customize.processId == 'Data':
self.tagList.pop(1)
self.stageOneVariable = [
'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']
self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(
'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(
'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(
'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(
'flashggStageOneCombinedTag')))
self.customizeTagSequence()
def variablesToDump(self):
ws_variables = []
ws_variables += self.stageOneVariable
ws_variables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass',
'dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)',
'NNLOPSweight[1,-999999.,999999.] := tagTruth().weight("NNLOPSweight")'
,
'btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight("btagReshapeNorm_TTH_LEP")'
,
'btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight("btagReshapeNorm_TTH_HAD")'
,
'btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight("btagReshapeNorm_THQ_LEP")'
, 'centralObjectWeight[1,-999999.,999999.] := centralWeight']
ntup_variables = ws_variables
if self.customize.dumpWorkspace:
return ws_variables
else:
return ntup_variables
def systematicVariables(self):
systematicVariables = []
systematicVariables += self.stageOneVariable
systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']
return systematicVariables
def noTagVariables(self):
noTagVariables = []
noTagVariables += self.stageOneVariable
for direction in ['Up', 'Down']:
noTagVariables.append(
'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mu%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Res%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig01%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_Mig12%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF2j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_VBF3j%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT60%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_PT120%s01sigma")'
% (direction, direction))
noTagVariables.append(
'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight("THU_ggH_qmtop%s01sigma")'
% (direction, direction))
return noTagVariables
def customizeTagSequence(self):
self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')
self.process.flashggTagSequence.remove(self.process.
flashggVBFDiPhoDiJetMVA)
self.process.flashggTagSequence.remove(self.process.
flashggTTHDiLeptonTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHLeptonicTag)
self.process.flashggTagSequence.remove(self.process.
flashggTTHHadronicTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHLeptonicLooseTag)
self.process.flashggTagSequence.remove(self.process.
flashggVHHadronicTag)
self.process.flashggTagSequence.remove(self.process.flashggVBFTag)
self.process.flashggTagSequence.replace(self.process.
flashggUntagged, self.process.flashggStageOneCombinedTag)
self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])
self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])
self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self
.metaConditions['stageOneCombinedTag']['rawGghBounds'])
self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(
self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])
self.metaConditions['L1Prefiring']['applyToCentral'] = True
self.process.flashggTagSorter.TagPriorityRanges = (self.
tagPriorityRanges)
self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.
customize.processId.count('ggh')))
self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.
customize.applyNNLOPSweight)
self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src
=cms.VInputTag('flashggTagSorter'))
def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,
jetsystlabels):
for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:
getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(
phosystlabels)
getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels
)
getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)
getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(
True)
getattr(self.process, tag).UseLargeMVAs = cms.bool(True)
self.process.p.remove(self.process.flashggTagSorter)
self.process.p.replace(self.process.flashggSystTagMerger, cms.
Sequence(self.process.flashggTTHLeptonicTag + self.process.
flashggTTHHadronicTag) * self.process.flashggTagSorter * self.
process.flashggSystTagMerger)
for systlabel in systlabels:
if systlabel == '':
continue
self.process.p.remove(getattr(self.process, 'flashggTagSorter' +
systlabel))
self.process.p.replace(self.process.flashggSystTagMerger,
getattr(self.process, 'flashggTagSorter' + systlabel) *
self.process.flashggSystTagMerger)
modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.
InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(
TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),
cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +
systlabel)), cms.PSet(TagName=cms.InputTag(
'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.
InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(
TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.
PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +
systlabel)))
setattr(getattr(self.process, 'flashggTagSorter' + systlabel),
'TagPriorityRanges', modifiedPriorityRanges)
<|reserved_special_token_1|>
import FWCore.ParameterSet.Config as cms
class StageOneCustomize():
"""
Customizaton class for STXS stage 1 analysis
"""
def __init__(self, process, customize, metaConditions):
self.process = process
self.customize = customize
self.metaConditions = metaConditions
self.modifyForttH = True
self.tagList = [
["LOGICERROR",0], ["NOTAG",0],
["RECO_0J_PTH_0_10_Tag0",0], ["RECO_0J_PTH_0_10_Tag1",0], ["RECO_0J_PTH_0_10_Tag2",0],
["RECO_0J_PTH_GT10_Tag0",0], ["RECO_0J_PTH_GT10_Tag1",0],["RECO_0J_PTH_GT10_Tag2",0],
["RECO_1J_PTH_0_60_Tag0",0], ["RECO_1J_PTH_0_60_Tag1",0], ["RECO_1J_PTH_0_60_Tag2",0],
["RECO_1J_PTH_60_120_Tag0",0], ["RECO_1J_PTH_60_120_Tag1",0], ["RECO_1J_PTH_60_120_Tag2",0],
["RECO_1J_PTH_120_200_Tag0",0], ["RECO_1J_PTH_120_200_Tag1",0],["RECO_1J_PTH_120_200_Tag2",0],
["RECO_GE2J_PTH_0_60_Tag0",0], ["RECO_GE2J_PTH_0_60_Tag1",0], ["RECO_GE2J_PTH_0_60_Tag2",0],
["RECO_GE2J_PTH_60_120_Tag0",0], ["RECO_GE2J_PTH_60_120_Tag1",0], ["RECO_GE2J_PTH_60_120_Tag2",0],
["RECO_GE2J_PTH_120_200_Tag0",0], ["RECO_GE2J_PTH_120_200_Tag1",0], ["RECO_GE2J_PTH_120_200_Tag2",0],
["RECO_PTH_200_300_Tag0",0], ["RECO_PTH_200_300_Tag1",0], ["RECO_PTH_300_450_Tag0",0], ["RECO_PTH_300_450_Tag1",0],
["RECO_PTH_450_650_Tag0",0], ["RECO_PTH_GT650_Tag0",0],
["RECO_VBFTOPO_VHHAD_Tag0",0], ["RECO_VBFTOPO_VHHAD_Tag1",0],
["RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0",0], ["RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1",0],
["RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0",0], ["RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1",0],
["RECO_VBFTOPO_JET3_LOWMJJ_Tag0",0], ["RECO_VBFTOPO_JET3_LOWMJJ_Tag1",0],
["RECO_VBFTOPO_JET3_HIGHMJJ_Tag0",0], ["RECO_VBFTOPO_JET3_HIGHMJJ_Tag1",0],
["RECO_VBFTOPO_BSM_Tag0",0], ["RECO_VBFTOPO_BSM_Tag1",0],
["RECO_VBFLIKEGGH_Tag0",0], ["RECO_VBFLIKEGGH_Tag1",0],
["RECO_TTH_HAD_PTH_0_60_Tag0",0], ["RECO_TTH_HAD_PTH_0_60_Tag1",0], ["RECO_TTH_HAD_PTH_0_60_Tag2",0],
["RECO_TTH_HAD_PTH_60_120_Tag0",0], ["RECO_TTH_HAD_PTH_60_120_Tag1",0], ["RECO_TTH_HAD_PTH_60_120_Tag2",0],
["RECO_TTH_HAD_PTH_120_200_Tag0",0], ["RECO_TTH_HAD_PTH_120_200_Tag1",0], ["RECO_TTH_HAD_PTH_120_200_Tag2",0], ["RECO_TTH_HAD_PTH_120_200_Tag3",0],
["RECO_TTH_HAD_PTH_200_300_Tag0",0], ["RECO_TTH_HAD_PTH_200_300_Tag1",0], ["RECO_TTH_HAD_PTH_200_300_Tag2",0],
["RECO_TTH_HAD_PTH_GT300_Tag0",0], ["RECO_TTH_HAD_PTH_GT300_Tag1",0],
["RECO_WH_LEP_PTV_0_75_Tag0",0], ["RECO_WH_LEP_PTV_0_75_Tag1",0],
["RECO_WH_LEP_PTV_75_150_Tag0",0], ["RECO_WH_LEP_PTV_75_150_Tag1",0],
["RECO_WH_LEP_PTV_GT150_Tag0",0],
["RECO_ZH_LEP_Tag0",0], ["RECO_ZH_LEP_Tag1",0],
["RECO_VH_MET_Tag0",0], ["RECO_VH_MET_Tag1",0], ["RECO_VH_MET_Tag2",0],
["RECO_TTH_LEP_PTH_0_60_Tag0",0], ["RECO_TTH_LEP_PTH_0_60_Tag1",0], ["RECO_TTH_LEP_PTH_0_60_Tag2",0],
["RECO_TTH_LEP_PTH_60_120_Tag0",0], ["RECO_TTH_LEP_PTH_60_120_Tag1",0], ["RECO_TTH_LEP_PTH_60_120_Tag2",0],
["RECO_TTH_LEP_PTH_120_200_Tag0",0], ["RECO_TTH_LEP_PTH_120_200_Tag1",0],
["RECO_TTH_LEP_PTH_200_300_Tag0",0],
["RECO_TTH_LEP_PTH_GT300_Tag0",0],
["RECO_THQ_LEP",0]
]
if self.customize.processId == "Data":
self.tagList.pop(1) ## remove NoTag for data
self.stageOneVariable = ["stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin"]
self.tagPriorityRanges = cms.VPSet(
cms.PSet(TagName = cms.InputTag('flashggTHQLeptonicTag')),
cms.PSet(TagName = cms.InputTag('flashggTTHLeptonicTag')),
cms.PSet(TagName = cms.InputTag('flashggZHLeptonicTag')),
cms.PSet(TagName = cms.InputTag('flashggWHLeptonicTag')),
cms.PSet(TagName = cms.InputTag('flashggTTHHadronicTag')),
cms.PSet(TagName = cms.InputTag('flashggVHMetTag')),
cms.PSet(TagName = cms.InputTag('flashggStageOneCombinedTag'))
)
self.customizeTagSequence()
def variablesToDump(self):
ws_variables = []
ws_variables += self.stageOneVariable
ws_variables += [
"CMS_hgg_mass[160,100,180]:=diPhoton().mass",
"dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)",
"NNLOPSweight[1,-999999.,999999.] := tagTruth().weight(\"NNLOPSweight\")",
"btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_LEP\")",
"btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_HAD\")",
"btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_THQ_LEP\")",
"centralObjectWeight[1,-999999.,999999.] := centralWeight"
]
ntup_variables = ws_variables #+ [
# "truthNNLOPS[1,-999999.,999999.]:=tagTruth().weight(\"NNLOPS\")",
# "leadJetPt[1,-999999.,999999.]:=VBFMVA().dijet_LeadJPt"
# ]
if self.customize.dumpWorkspace:
return ws_variables
else:
return ntup_variables
def systematicVariables(self):
systematicVariables = []
systematicVariables += self.stageOneVariable
systematicVariables += [
"CMS_hgg_mass[160,100,180]:=diPhoton().mass"
]
return systematicVariables
def noTagVariables(self):
noTagVariables = []
noTagVariables += self.stageOneVariable
for direction in ["Up","Down"]:
noTagVariables.append("THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mu%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Res%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig01%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig12%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF2j%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF3j%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT60%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT120%s01sigma\")" % (direction,direction))
noTagVariables.append("THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_qmtop%s01sigma\")" % (direction,direction))
return noTagVariables
def customizeTagSequence(self):
self.process.load("flashgg.Taggers.flashggStageOneCombinedTag_cfi")
## remove unneeded tags
self.process.flashggTagSequence.remove(self.process.flashggVBFDiPhoDiJetMVA)
#self.process.flashggTagSequence.remove(self.process.flashggTHQLeptonicTag) ## now included in analysis
self.process.flashggTagSequence.remove(self.process.flashggTTHDiLeptonTag)
self.process.flashggTagSequence.remove(self.process.flashggTTHLeptonicTag) ## will be added back in later
self.process.flashggTagSequence.remove(self.process.flashggTTHHadronicTag) ## will be added back in later
#self.process.flashggTagSequence.remove(self.process.flashggVHMetTag) ## now included in analysis
#self.process.flashggTagSequence.remove(self.process.flashggZHLeptonicTag) ## now included in analysis
#self.process.flashggTagSequence.remove(self.process.flashggWHLeptonicTag) ## now included in analysis
self.process.flashggTagSequence.remove(self.process.flashggVHLeptonicLooseTag)
self.process.flashggTagSequence.remove(self.process.flashggVHHadronicTag)
self.process.flashggTagSequence.remove(self.process.flashggVBFTag)
self.process.flashggTagSequence.replace(self.process.flashggUntagged,self.process.flashggStageOneCombinedTag)
## customize from meta conditions - category thresholds set here
self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble( self.metaConditions["stageOneCombinedTag"]["rawDiphoBounds"] )
self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble( self.metaConditions["stageOneCombinedTag"]["rawDijetBounds"] )
self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble( self.metaConditions["stageOneCombinedTag"]["rawGghBounds"] )
self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble( self.metaConditions["stageOneCombinedTag"]["rawVhHadBounds"] )
## set the pre-firing to be applied
self.metaConditions["L1Prefiring"]["applyToCentral"] = True
## set tag priorities
self.process.flashggTagSorter.TagPriorityRanges = self.tagPriorityRanges
self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.customize.processId.count("ggh")))
self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.customize.applyNNLOPSweight)
## set the tag merging
self.process.flashggSystTagMerger = cms.EDProducer("TagMerger",src=cms.VInputTag("flashggTagSorter"))
## this adds in the ttH tags with their correct, modified systematics workflow
def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels, jetsystlabels):
# Set lists of systematics for each tag
for tag in ["flashggTTHLeptonicTag", "flashggTTHHadronicTag"]:
getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(phosystlabels)
getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels)
getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)
getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(True)
getattr(self.process, tag).UseLargeMVAs = cms.bool(True) # enable memory-intensive MVAs
self.process.p.remove(self.process.flashggTagSorter)
self.process.p.replace(self.process.flashggSystTagMerger, cms.Sequence(self.process.flashggTTHLeptonicTag + self.process.flashggTTHHadronicTag)*self.process.flashggTagSorter*self.process.flashggSystTagMerger)
for systlabel in systlabels:
if systlabel == "":
continue
self.process.p.remove(getattr(self.process, 'flashggTagSorter' + systlabel))
self.process.p.replace(self.process.flashggSystTagMerger, getattr(self.process, 'flashggTagSorter' + systlabel) * self.process.flashggSystTagMerger)
modifiedPriorityRanges = cms.VPSet(
cms.PSet(TagName = cms.InputTag('flashggTHQLeptonicTag'+systlabel)),
cms.PSet(TagName = cms.InputTag('flashggTTHLeptonicTag', systlabel)),
cms.PSet(TagName = cms.InputTag('flashggZHLeptonicTag'+systlabel)),
cms.PSet(TagName = cms.InputTag('flashggWHLeptonicTag'+systlabel)),
cms.PSet(TagName = cms.InputTag('flashggTTHHadronicTag', systlabel)),
cms.PSet(TagName = cms.InputTag('flashggVHMetTag'+systlabel)),
cms.PSet(TagName = cms.InputTag('flashggStageOneCombinedTag'+systlabel))
)
setattr(getattr(self.process, 'flashggTagSorter'+systlabel), 'TagPriorityRanges', modifiedPriorityRanges)
|
flexible
|
{
"blob_id": "ce12ede15f4ca4a085e38e455515d8a028da8fd2",
"index": 2115,
"step-1": "<mask token>\n\n\nclass StageOneCustomize:\n <mask token>\n\n def __init__(self, process, customize, metaConditions):\n self.process = process\n self.customize = customize\n self.metaConditions = metaConditions\n self.modifyForttH = True\n self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [\n 'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [\n 'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [\n 'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [\n 'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [\n 'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [\n 'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],\n ['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0\n ], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',\n 0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',\n 0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [\n 'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2', \n 0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [\n 'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',\n 0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],\n ['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [\n 'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [\n 'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],\n ['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',\n 0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],\n ['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],\n ['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',\n 0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag0', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag1', 0], [\n 'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [\n 'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [\n 'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',\n 0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]\n if self.customize.processId == 'Data':\n self.tagList.pop(1)\n self.stageOneVariable = [\n 'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']\n self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(\n 'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggStageOneCombinedTag')))\n self.customizeTagSequence()\n <mask token>\n\n def systematicVariables(self):\n systematicVariables = []\n systematicVariables += self.stageOneVariable\n systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']\n return systematicVariables\n\n def noTagVariables(self):\n noTagVariables = []\n noTagVariables += self.stageOneVariable\n for direction in ['Up', 'Down']:\n noTagVariables.append(\n 'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mu%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Res%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig01%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig12%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF2j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF3j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT60%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT120%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_qmtop%s01sigma\")'\n % (direction, direction))\n return noTagVariables\n\n def customizeTagSequence(self):\n self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')\n self.process.flashggTagSequence.remove(self.process.\n flashggVBFDiPhoDiJetMVA)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHDiLeptonTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHLeptonicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHLeptonicLooseTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.flashggVBFTag)\n self.process.flashggTagSequence.replace(self.process.\n flashggUntagged, self.process.flashggStageOneCombinedTag)\n self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])\n self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])\n self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self\n .metaConditions['stageOneCombinedTag']['rawGghBounds'])\n self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])\n self.metaConditions['L1Prefiring']['applyToCentral'] = True\n self.process.flashggTagSorter.TagPriorityRanges = (self.\n tagPriorityRanges)\n self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.\n customize.processId.count('ggh')))\n self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.\n customize.applyNNLOPSweight)\n self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src\n =cms.VInputTag('flashggTagSorter'))\n\n def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,\n jetsystlabels):\n for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:\n getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(\n phosystlabels)\n getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels\n )\n getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)\n getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(\n True)\n getattr(self.process, tag).UseLargeMVAs = cms.bool(True)\n self.process.p.remove(self.process.flashggTagSorter)\n self.process.p.replace(self.process.flashggSystTagMerger, cms.\n Sequence(self.process.flashggTTHLeptonicTag + self.process.\n flashggTTHHadronicTag) * self.process.flashggTagSorter * self.\n process.flashggSystTagMerger)\n for systlabel in systlabels:\n if systlabel == '':\n continue\n self.process.p.remove(getattr(self.process, 'flashggTagSorter' +\n systlabel))\n self.process.p.replace(self.process.flashggSystTagMerger, \n getattr(self.process, 'flashggTagSorter' + systlabel) *\n self.process.flashggSystTagMerger)\n modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.\n InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),\n cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +\n systlabel)), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.\n InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.\n PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +\n systlabel)))\n setattr(getattr(self.process, 'flashggTagSorter' + systlabel),\n 'TagPriorityRanges', modifiedPriorityRanges)\n",
"step-2": "<mask token>\n\n\nclass StageOneCustomize:\n <mask token>\n\n def __init__(self, process, customize, metaConditions):\n self.process = process\n self.customize = customize\n self.metaConditions = metaConditions\n self.modifyForttH = True\n self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [\n 'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [\n 'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [\n 'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [\n 'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [\n 'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [\n 'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],\n ['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0\n ], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',\n 0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',\n 0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [\n 'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2', \n 0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [\n 'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',\n 0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],\n ['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [\n 'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [\n 'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],\n ['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',\n 0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],\n ['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],\n ['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',\n 0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag0', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag1', 0], [\n 'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [\n 'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [\n 'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',\n 0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]\n if self.customize.processId == 'Data':\n self.tagList.pop(1)\n self.stageOneVariable = [\n 'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']\n self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(\n 'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggStageOneCombinedTag')))\n self.customizeTagSequence()\n\n def variablesToDump(self):\n ws_variables = []\n ws_variables += self.stageOneVariable\n ws_variables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass',\n 'dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)',\n 'NNLOPSweight[1,-999999.,999999.] := tagTruth().weight(\"NNLOPSweight\")'\n ,\n 'btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_LEP\")'\n ,\n 'btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_HAD\")'\n ,\n 'btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_THQ_LEP\")'\n , 'centralObjectWeight[1,-999999.,999999.] := centralWeight']\n ntup_variables = ws_variables\n if self.customize.dumpWorkspace:\n return ws_variables\n else:\n return ntup_variables\n\n def systematicVariables(self):\n systematicVariables = []\n systematicVariables += self.stageOneVariable\n systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']\n return systematicVariables\n\n def noTagVariables(self):\n noTagVariables = []\n noTagVariables += self.stageOneVariable\n for direction in ['Up', 'Down']:\n noTagVariables.append(\n 'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mu%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Res%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig01%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig12%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF2j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF3j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT60%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT120%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_qmtop%s01sigma\")'\n % (direction, direction))\n return noTagVariables\n\n def customizeTagSequence(self):\n self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')\n self.process.flashggTagSequence.remove(self.process.\n flashggVBFDiPhoDiJetMVA)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHDiLeptonTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHLeptonicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHLeptonicLooseTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.flashggVBFTag)\n self.process.flashggTagSequence.replace(self.process.\n flashggUntagged, self.process.flashggStageOneCombinedTag)\n self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])\n self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])\n self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self\n .metaConditions['stageOneCombinedTag']['rawGghBounds'])\n self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])\n self.metaConditions['L1Prefiring']['applyToCentral'] = True\n self.process.flashggTagSorter.TagPriorityRanges = (self.\n tagPriorityRanges)\n self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.\n customize.processId.count('ggh')))\n self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.\n customize.applyNNLOPSweight)\n self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src\n =cms.VInputTag('flashggTagSorter'))\n\n def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,\n jetsystlabels):\n for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:\n getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(\n phosystlabels)\n getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels\n )\n getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)\n getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(\n True)\n getattr(self.process, tag).UseLargeMVAs = cms.bool(True)\n self.process.p.remove(self.process.flashggTagSorter)\n self.process.p.replace(self.process.flashggSystTagMerger, cms.\n Sequence(self.process.flashggTTHLeptonicTag + self.process.\n flashggTTHHadronicTag) * self.process.flashggTagSorter * self.\n process.flashggSystTagMerger)\n for systlabel in systlabels:\n if systlabel == '':\n continue\n self.process.p.remove(getattr(self.process, 'flashggTagSorter' +\n systlabel))\n self.process.p.replace(self.process.flashggSystTagMerger, \n getattr(self.process, 'flashggTagSorter' + systlabel) *\n self.process.flashggSystTagMerger)\n modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.\n InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),\n cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +\n systlabel)), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.\n InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.\n PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +\n systlabel)))\n setattr(getattr(self.process, 'flashggTagSorter' + systlabel),\n 'TagPriorityRanges', modifiedPriorityRanges)\n",
"step-3": "<mask token>\n\n\nclass StageOneCustomize:\n \"\"\"\n Customizaton class for STXS stage 1 analysis\n \"\"\"\n\n def __init__(self, process, customize, metaConditions):\n self.process = process\n self.customize = customize\n self.metaConditions = metaConditions\n self.modifyForttH = True\n self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [\n 'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [\n 'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [\n 'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [\n 'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [\n 'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [\n 'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],\n ['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0\n ], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',\n 0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',\n 0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [\n 'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2', \n 0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [\n 'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',\n 0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],\n ['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [\n 'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [\n 'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],\n ['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',\n 0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],\n ['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],\n ['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',\n 0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag0', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag1', 0], [\n 'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [\n 'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [\n 'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',\n 0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]\n if self.customize.processId == 'Data':\n self.tagList.pop(1)\n self.stageOneVariable = [\n 'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']\n self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(\n 'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggStageOneCombinedTag')))\n self.customizeTagSequence()\n\n def variablesToDump(self):\n ws_variables = []\n ws_variables += self.stageOneVariable\n ws_variables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass',\n 'dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)',\n 'NNLOPSweight[1,-999999.,999999.] := tagTruth().weight(\"NNLOPSweight\")'\n ,\n 'btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_LEP\")'\n ,\n 'btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_HAD\")'\n ,\n 'btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_THQ_LEP\")'\n , 'centralObjectWeight[1,-999999.,999999.] := centralWeight']\n ntup_variables = ws_variables\n if self.customize.dumpWorkspace:\n return ws_variables\n else:\n return ntup_variables\n\n def systematicVariables(self):\n systematicVariables = []\n systematicVariables += self.stageOneVariable\n systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']\n return systematicVariables\n\n def noTagVariables(self):\n noTagVariables = []\n noTagVariables += self.stageOneVariable\n for direction in ['Up', 'Down']:\n noTagVariables.append(\n 'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mu%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Res%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig01%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig12%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF2j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF3j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT60%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT120%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_qmtop%s01sigma\")'\n % (direction, direction))\n return noTagVariables\n\n def customizeTagSequence(self):\n self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')\n self.process.flashggTagSequence.remove(self.process.\n flashggVBFDiPhoDiJetMVA)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHDiLeptonTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHLeptonicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHLeptonicLooseTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.flashggVBFTag)\n self.process.flashggTagSequence.replace(self.process.\n flashggUntagged, self.process.flashggStageOneCombinedTag)\n self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])\n self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])\n self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self\n .metaConditions['stageOneCombinedTag']['rawGghBounds'])\n self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])\n self.metaConditions['L1Prefiring']['applyToCentral'] = True\n self.process.flashggTagSorter.TagPriorityRanges = (self.\n tagPriorityRanges)\n self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.\n customize.processId.count('ggh')))\n self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.\n customize.applyNNLOPSweight)\n self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src\n =cms.VInputTag('flashggTagSorter'))\n\n def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,\n jetsystlabels):\n for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:\n getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(\n phosystlabels)\n getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels\n )\n getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)\n getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(\n True)\n getattr(self.process, tag).UseLargeMVAs = cms.bool(True)\n self.process.p.remove(self.process.flashggTagSorter)\n self.process.p.replace(self.process.flashggSystTagMerger, cms.\n Sequence(self.process.flashggTTHLeptonicTag + self.process.\n flashggTTHHadronicTag) * self.process.flashggTagSorter * self.\n process.flashggSystTagMerger)\n for systlabel in systlabels:\n if systlabel == '':\n continue\n self.process.p.remove(getattr(self.process, 'flashggTagSorter' +\n systlabel))\n self.process.p.replace(self.process.flashggSystTagMerger, \n getattr(self.process, 'flashggTagSorter' + systlabel) *\n self.process.flashggSystTagMerger)\n modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.\n InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),\n cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +\n systlabel)), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.\n InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.\n PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +\n systlabel)))\n setattr(getattr(self.process, 'flashggTagSorter' + systlabel),\n 'TagPriorityRanges', modifiedPriorityRanges)\n",
"step-4": "import FWCore.ParameterSet.Config as cms\n\n\nclass StageOneCustomize:\n \"\"\"\n Customizaton class for STXS stage 1 analysis\n \"\"\"\n\n def __init__(self, process, customize, metaConditions):\n self.process = process\n self.customize = customize\n self.metaConditions = metaConditions\n self.modifyForttH = True\n self.tagList = [['LOGICERROR', 0], ['NOTAG', 0], [\n 'RECO_0J_PTH_0_10_Tag0', 0], ['RECO_0J_PTH_0_10_Tag1', 0], [\n 'RECO_0J_PTH_0_10_Tag2', 0], ['RECO_0J_PTH_GT10_Tag0', 0], [\n 'RECO_0J_PTH_GT10_Tag1', 0], ['RECO_0J_PTH_GT10_Tag2', 0], [\n 'RECO_1J_PTH_0_60_Tag0', 0], ['RECO_1J_PTH_0_60_Tag1', 0], [\n 'RECO_1J_PTH_0_60_Tag2', 0], ['RECO_1J_PTH_60_120_Tag0', 0], [\n 'RECO_1J_PTH_60_120_Tag1', 0], ['RECO_1J_PTH_60_120_Tag2', 0],\n ['RECO_1J_PTH_120_200_Tag0', 0], ['RECO_1J_PTH_120_200_Tag1', 0\n ], ['RECO_1J_PTH_120_200_Tag2', 0], ['RECO_GE2J_PTH_0_60_Tag0',\n 0], ['RECO_GE2J_PTH_0_60_Tag1', 0], ['RECO_GE2J_PTH_0_60_Tag2',\n 0], ['RECO_GE2J_PTH_60_120_Tag0', 0], [\n 'RECO_GE2J_PTH_60_120_Tag1', 0], ['RECO_GE2J_PTH_60_120_Tag2', \n 0], ['RECO_GE2J_PTH_120_200_Tag0', 0], [\n 'RECO_GE2J_PTH_120_200_Tag1', 0], ['RECO_GE2J_PTH_120_200_Tag2',\n 0], ['RECO_PTH_200_300_Tag0', 0], ['RECO_PTH_200_300_Tag1', 0],\n ['RECO_PTH_300_450_Tag0', 0], ['RECO_PTH_300_450_Tag1', 0], [\n 'RECO_PTH_450_650_Tag0', 0], ['RECO_PTH_GT650_Tag0', 0], [\n 'RECO_VBFTOPO_VHHAD_Tag0', 0], ['RECO_VBFTOPO_VHHAD_Tag1', 0],\n ['RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_LOWMJJ_Tag1', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag0', 0], [\n 'RECO_VBFTOPO_JET3_HIGHMJJ_Tag1', 0], ['RECO_VBFTOPO_BSM_Tag0',\n 0], ['RECO_VBFTOPO_BSM_Tag1', 0], ['RECO_VBFLIKEGGH_Tag0', 0],\n ['RECO_VBFLIKEGGH_Tag1', 0], ['RECO_TTH_HAD_PTH_0_60_Tag0', 0],\n ['RECO_TTH_HAD_PTH_0_60_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_120_200_Tag3', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag1', 0], [\n 'RECO_TTH_HAD_PTH_200_300_Tag2', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag0', 0], [\n 'RECO_TTH_HAD_PTH_GT300_Tag1', 0], ['RECO_WH_LEP_PTV_0_75_Tag0',\n 0], ['RECO_WH_LEP_PTV_0_75_Tag1', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag0', 0], [\n 'RECO_WH_LEP_PTV_75_150_Tag1', 0], [\n 'RECO_WH_LEP_PTV_GT150_Tag0', 0], ['RECO_ZH_LEP_Tag0', 0], [\n 'RECO_ZH_LEP_Tag1', 0], ['RECO_VH_MET_Tag0', 0], [\n 'RECO_VH_MET_Tag1', 0], ['RECO_VH_MET_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_0_60_Tag0', 0], ['RECO_TTH_LEP_PTH_0_60_Tag1',\n 0], ['RECO_TTH_LEP_PTH_0_60_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_60_120_Tag2', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_120_200_Tag1', 0], [\n 'RECO_TTH_LEP_PTH_200_300_Tag0', 0], [\n 'RECO_TTH_LEP_PTH_GT300_Tag0', 0], ['RECO_THQ_LEP', 0]]\n if self.customize.processId == 'Data':\n self.tagList.pop(1)\n self.stageOneVariable = [\n 'stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin']\n self.tagPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.InputTag(\n 'flashggTHQLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggZHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggTTHHadronicTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggVHMetTag')), cms.PSet(TagName=cms.InputTag(\n 'flashggStageOneCombinedTag')))\n self.customizeTagSequence()\n\n def variablesToDump(self):\n ws_variables = []\n ws_variables += self.stageOneVariable\n ws_variables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass',\n 'dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)',\n 'NNLOPSweight[1,-999999.,999999.] := tagTruth().weight(\"NNLOPSweight\")'\n ,\n 'btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_LEP\")'\n ,\n 'btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight(\"btagReshapeNorm_TTH_HAD\")'\n ,\n 'btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight(\"btagReshapeNorm_THQ_LEP\")'\n , 'centralObjectWeight[1,-999999.,999999.] := centralWeight']\n ntup_variables = ws_variables\n if self.customize.dumpWorkspace:\n return ws_variables\n else:\n return ntup_variables\n\n def systematicVariables(self):\n systematicVariables = []\n systematicVariables += self.stageOneVariable\n systematicVariables += ['CMS_hgg_mass[160,100,180]:=diPhoton().mass']\n return systematicVariables\n\n def noTagVariables(self):\n noTagVariables = []\n noTagVariables += self.stageOneVariable\n for direction in ['Up', 'Down']:\n noTagVariables.append(\n 'THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mu%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Res%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig01%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_Mig12%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF2j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_VBF3j%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT60%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_PT120%s01sigma\")'\n % (direction, direction))\n noTagVariables.append(\n 'THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight(\"THU_ggH_qmtop%s01sigma\")'\n % (direction, direction))\n return noTagVariables\n\n def customizeTagSequence(self):\n self.process.load('flashgg.Taggers.flashggStageOneCombinedTag_cfi')\n self.process.flashggTagSequence.remove(self.process.\n flashggVBFDiPhoDiJetMVA)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHDiLeptonTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHLeptonicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggTTHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHLeptonicLooseTag)\n self.process.flashggTagSequence.remove(self.process.\n flashggVHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.flashggVBFTag)\n self.process.flashggTagSequence.replace(self.process.\n flashggUntagged, self.process.flashggStageOneCombinedTag)\n self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDiphoBounds'])\n self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawDijetBounds'])\n self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble(self\n .metaConditions['stageOneCombinedTag']['rawGghBounds'])\n self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble(\n self.metaConditions['stageOneCombinedTag']['rawVhHadBounds'])\n self.metaConditions['L1Prefiring']['applyToCentral'] = True\n self.process.flashggTagSorter.TagPriorityRanges = (self.\n tagPriorityRanges)\n self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.\n customize.processId.count('ggh')))\n self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.\n customize.applyNNLOPSweight)\n self.process.flashggSystTagMerger = cms.EDProducer('TagMerger', src\n =cms.VInputTag('flashggTagSorter'))\n\n def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels,\n jetsystlabels):\n for tag in ['flashggTTHLeptonicTag', 'flashggTTHHadronicTag']:\n getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(\n phosystlabels)\n getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels\n )\n getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)\n getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(\n True)\n getattr(self.process, tag).UseLargeMVAs = cms.bool(True)\n self.process.p.remove(self.process.flashggTagSorter)\n self.process.p.replace(self.process.flashggSystTagMerger, cms.\n Sequence(self.process.flashggTTHLeptonicTag + self.process.\n flashggTTHHadronicTag) * self.process.flashggTagSorter * self.\n process.flashggSystTagMerger)\n for systlabel in systlabels:\n if systlabel == '':\n continue\n self.process.p.remove(getattr(self.process, 'flashggTagSorter' +\n systlabel))\n self.process.p.replace(self.process.flashggSystTagMerger, \n getattr(self.process, 'flashggTagSorter' + systlabel) *\n self.process.flashggSystTagMerger)\n modifiedPriorityRanges = cms.VPSet(cms.PSet(TagName=cms.\n InputTag('flashggTHQLeptonicTag' + systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggTTHLeptonicTag', systlabel)),\n cms.PSet(TagName=cms.InputTag('flashggZHLeptonicTag' +\n systlabel)), cms.PSet(TagName=cms.InputTag(\n 'flashggWHLeptonicTag' + systlabel)), cms.PSet(TagName=cms.\n InputTag('flashggTTHHadronicTag', systlabel)), cms.PSet(\n TagName=cms.InputTag('flashggVHMetTag' + systlabel)), cms.\n PSet(TagName=cms.InputTag('flashggStageOneCombinedTag' +\n systlabel)))\n setattr(getattr(self.process, 'flashggTagSorter' + systlabel),\n 'TagPriorityRanges', modifiedPriorityRanges)\n",
"step-5": "import FWCore.ParameterSet.Config as cms\n\nclass StageOneCustomize():\n \"\"\"\n Customizaton class for STXS stage 1 analysis\n \"\"\"\n \n def __init__(self, process, customize, metaConditions):\n self.process = process\n self.customize = customize\n self.metaConditions = metaConditions\n self.modifyForttH = True\n self.tagList = [\n [\"LOGICERROR\",0], [\"NOTAG\",0], \n [\"RECO_0J_PTH_0_10_Tag0\",0], [\"RECO_0J_PTH_0_10_Tag1\",0], [\"RECO_0J_PTH_0_10_Tag2\",0],\n [\"RECO_0J_PTH_GT10_Tag0\",0], [\"RECO_0J_PTH_GT10_Tag1\",0],[\"RECO_0J_PTH_GT10_Tag2\",0],\n [\"RECO_1J_PTH_0_60_Tag0\",0], [\"RECO_1J_PTH_0_60_Tag1\",0], [\"RECO_1J_PTH_0_60_Tag2\",0],\n [\"RECO_1J_PTH_60_120_Tag0\",0], [\"RECO_1J_PTH_60_120_Tag1\",0], [\"RECO_1J_PTH_60_120_Tag2\",0],\n [\"RECO_1J_PTH_120_200_Tag0\",0], [\"RECO_1J_PTH_120_200_Tag1\",0],[\"RECO_1J_PTH_120_200_Tag2\",0],\n [\"RECO_GE2J_PTH_0_60_Tag0\",0], [\"RECO_GE2J_PTH_0_60_Tag1\",0], [\"RECO_GE2J_PTH_0_60_Tag2\",0],\n [\"RECO_GE2J_PTH_60_120_Tag0\",0], [\"RECO_GE2J_PTH_60_120_Tag1\",0], [\"RECO_GE2J_PTH_60_120_Tag2\",0],\n [\"RECO_GE2J_PTH_120_200_Tag0\",0], [\"RECO_GE2J_PTH_120_200_Tag1\",0], [\"RECO_GE2J_PTH_120_200_Tag2\",0],\n [\"RECO_PTH_200_300_Tag0\",0], [\"RECO_PTH_200_300_Tag1\",0], [\"RECO_PTH_300_450_Tag0\",0], [\"RECO_PTH_300_450_Tag1\",0],\n [\"RECO_PTH_450_650_Tag0\",0], [\"RECO_PTH_GT650_Tag0\",0], \n [\"RECO_VBFTOPO_VHHAD_Tag0\",0], [\"RECO_VBFTOPO_VHHAD_Tag1\",0],\n [\"RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag0\",0], [\"RECO_VBFTOPO_JET3VETO_LOWMJJ_Tag1\",0], \n [\"RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag0\",0], [\"RECO_VBFTOPO_JET3VETO_HIGHMJJ_Tag1\",0], \n [\"RECO_VBFTOPO_JET3_LOWMJJ_Tag0\",0], [\"RECO_VBFTOPO_JET3_LOWMJJ_Tag1\",0], \n [\"RECO_VBFTOPO_JET3_HIGHMJJ_Tag0\",0], [\"RECO_VBFTOPO_JET3_HIGHMJJ_Tag1\",0], \n [\"RECO_VBFTOPO_BSM_Tag0\",0], [\"RECO_VBFTOPO_BSM_Tag1\",0],\n [\"RECO_VBFLIKEGGH_Tag0\",0], [\"RECO_VBFLIKEGGH_Tag1\",0], \n [\"RECO_TTH_HAD_PTH_0_60_Tag0\",0], [\"RECO_TTH_HAD_PTH_0_60_Tag1\",0], [\"RECO_TTH_HAD_PTH_0_60_Tag2\",0],\n [\"RECO_TTH_HAD_PTH_60_120_Tag0\",0], [\"RECO_TTH_HAD_PTH_60_120_Tag1\",0], [\"RECO_TTH_HAD_PTH_60_120_Tag2\",0],\n [\"RECO_TTH_HAD_PTH_120_200_Tag0\",0], [\"RECO_TTH_HAD_PTH_120_200_Tag1\",0], [\"RECO_TTH_HAD_PTH_120_200_Tag2\",0], [\"RECO_TTH_HAD_PTH_120_200_Tag3\",0],\n [\"RECO_TTH_HAD_PTH_200_300_Tag0\",0], [\"RECO_TTH_HAD_PTH_200_300_Tag1\",0], [\"RECO_TTH_HAD_PTH_200_300_Tag2\",0],\n [\"RECO_TTH_HAD_PTH_GT300_Tag0\",0], [\"RECO_TTH_HAD_PTH_GT300_Tag1\",0],\n [\"RECO_WH_LEP_PTV_0_75_Tag0\",0], [\"RECO_WH_LEP_PTV_0_75_Tag1\",0],\n [\"RECO_WH_LEP_PTV_75_150_Tag0\",0], [\"RECO_WH_LEP_PTV_75_150_Tag1\",0],\n [\"RECO_WH_LEP_PTV_GT150_Tag0\",0],\n [\"RECO_ZH_LEP_Tag0\",0], [\"RECO_ZH_LEP_Tag1\",0],\n [\"RECO_VH_MET_Tag0\",0], [\"RECO_VH_MET_Tag1\",0], [\"RECO_VH_MET_Tag2\",0],\n [\"RECO_TTH_LEP_PTH_0_60_Tag0\",0], [\"RECO_TTH_LEP_PTH_0_60_Tag1\",0], [\"RECO_TTH_LEP_PTH_0_60_Tag2\",0],\n [\"RECO_TTH_LEP_PTH_60_120_Tag0\",0], [\"RECO_TTH_LEP_PTH_60_120_Tag1\",0], [\"RECO_TTH_LEP_PTH_60_120_Tag2\",0],\n [\"RECO_TTH_LEP_PTH_120_200_Tag0\",0], [\"RECO_TTH_LEP_PTH_120_200_Tag1\",0],\n [\"RECO_TTH_LEP_PTH_200_300_Tag0\",0],\n [\"RECO_TTH_LEP_PTH_GT300_Tag0\",0],\n [\"RECO_THQ_LEP\",0]\n ]\n if self.customize.processId == \"Data\": \n self.tagList.pop(1) ## remove NoTag for data\n self.stageOneVariable = [\"stage1p2bin[57,-8.5,48.5] := tagTruth().HTXSstage1p2orderedBin\"]\n self.tagPriorityRanges = cms.VPSet(\n\t cms.PSet(TagName = cms.InputTag('flashggTHQLeptonicTag')),\n cms.PSet(TagName = cms.InputTag('flashggTTHLeptonicTag')), \n cms.PSet(TagName = cms.InputTag('flashggZHLeptonicTag')),\n cms.PSet(TagName = cms.InputTag('flashggWHLeptonicTag')),\n cms.PSet(TagName = cms.InputTag('flashggTTHHadronicTag')), \n cms.PSet(TagName = cms.InputTag('flashggVHMetTag')),\n cms.PSet(TagName = cms.InputTag('flashggStageOneCombinedTag'))\n )\n self.customizeTagSequence()\n\n\n def variablesToDump(self):\n ws_variables = []\n ws_variables += self.stageOneVariable \n ws_variables += [\n \"CMS_hgg_mass[160,100,180]:=diPhoton().mass\",\n \"dZ[40,-20.,20.]:=(tagTruth().genPV().z-diPhoton().vtx().z)\",\n \"NNLOPSweight[1,-999999.,999999.] := tagTruth().weight(\\\"NNLOPSweight\\\")\",\n \"btagReshapeNorm_TTH_LEP[1,-999999.,999999.] := weight(\\\"btagReshapeNorm_TTH_LEP\\\")\",\n \"btagReshapeNorm_TTH_HAD[1,-999999.,999999.] := weight(\\\"btagReshapeNorm_TTH_HAD\\\")\",\n \"btagReshapeNorm_THQ_LEP[1,-999999.,999999.] := weight(\\\"btagReshapeNorm_THQ_LEP\\\")\",\n \"centralObjectWeight[1,-999999.,999999.] := centralWeight\"\n ]\n\n ntup_variables = ws_variables #+ [\n # \"truthNNLOPS[1,-999999.,999999.]:=tagTruth().weight(\\\"NNLOPS\\\")\",\n # \"leadJetPt[1,-999999.,999999.]:=VBFMVA().dijet_LeadJPt\"\n # ]\n \n if self.customize.dumpWorkspace:\n return ws_variables\n else:\n return ntup_variables\n\n\n def systematicVariables(self):\n systematicVariables = [] \n systematicVariables += self.stageOneVariable \n systematicVariables += [\n \"CMS_hgg_mass[160,100,180]:=diPhoton().mass\"\n ]\n return systematicVariables\n\n def noTagVariables(self):\n noTagVariables = []\n noTagVariables += self.stageOneVariable\n for direction in [\"Up\",\"Down\"]:\n noTagVariables.append(\"THU_ggH_Mu%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_Mu%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_Res%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_Res%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_Mig01%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_Mig01%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_Mig12%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_Mig12%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_VBF2j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_VBF2j%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_VBF3j%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_VBF3j%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_PT60%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_PT60%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_PT120%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_PT120%s01sigma\\\")\" % (direction,direction))\n noTagVariables.append(\"THU_ggH_qmtop%s01sigma[1,-999999.,999999.] := getTheoryWeight(\\\"THU_ggH_qmtop%s01sigma\\\")\" % (direction,direction))\n return noTagVariables\n\n\n def customizeTagSequence(self):\n self.process.load(\"flashgg.Taggers.flashggStageOneCombinedTag_cfi\")\n\n ## remove unneeded tags\n self.process.flashggTagSequence.remove(self.process.flashggVBFDiPhoDiJetMVA)\n #self.process.flashggTagSequence.remove(self.process.flashggTHQLeptonicTag) ## now included in analysis\n self.process.flashggTagSequence.remove(self.process.flashggTTHDiLeptonTag)\n self.process.flashggTagSequence.remove(self.process.flashggTTHLeptonicTag) ## will be added back in later\n self.process.flashggTagSequence.remove(self.process.flashggTTHHadronicTag) ## will be added back in later\n #self.process.flashggTagSequence.remove(self.process.flashggVHMetTag) ## now included in analysis\n #self.process.flashggTagSequence.remove(self.process.flashggZHLeptonicTag) ## now included in analysis\n #self.process.flashggTagSequence.remove(self.process.flashggWHLeptonicTag) ## now included in analysis\n self.process.flashggTagSequence.remove(self.process.flashggVHLeptonicLooseTag)\n self.process.flashggTagSequence.remove(self.process.flashggVHHadronicTag)\n self.process.flashggTagSequence.remove(self.process.flashggVBFTag)\n self.process.flashggTagSequence.replace(self.process.flashggUntagged,self.process.flashggStageOneCombinedTag)\n\n ## customize from meta conditions - category thresholds set here\n self.process.flashggStageOneCombinedTag.rawDiphoBounds = cms.vdouble( self.metaConditions[\"stageOneCombinedTag\"][\"rawDiphoBounds\"] )\n self.process.flashggStageOneCombinedTag.rawDijetBounds = cms.vdouble( self.metaConditions[\"stageOneCombinedTag\"][\"rawDijetBounds\"] )\n self.process.flashggStageOneCombinedTag.rawGghBounds = cms.vdouble( self.metaConditions[\"stageOneCombinedTag\"][\"rawGghBounds\"] )\n self.process.flashggStageOneCombinedTag.rawVhHadBounds = cms.vdouble( self.metaConditions[\"stageOneCombinedTag\"][\"rawVhHadBounds\"] )\n\n ## set the pre-firing to be applied\n self.metaConditions[\"L1Prefiring\"][\"applyToCentral\"] = True\n\n ## set tag priorities\n self.process.flashggTagSorter.TagPriorityRanges = self.tagPriorityRanges\n self.process.flashggTagSorter.isGluonFusion = cms.bool(bool(self.customize.processId.count(\"ggh\")))\n self.process.flashggTagSorter.applyNNLOPSweight = cms.bool(self.customize.applyNNLOPSweight)\n\n ## set the tag merging\n self.process.flashggSystTagMerger = cms.EDProducer(\"TagMerger\",src=cms.VInputTag(\"flashggTagSorter\"))\n\n ## this adds in the ttH tags with their correct, modified systematics workflow\n def modifyWorkflowForttH(self, systlabels, phosystlabels, metsystlabels, jetsystlabels):\n # Set lists of systematics for each tag\n for tag in [\"flashggTTHLeptonicTag\", \"flashggTTHHadronicTag\"]:\n getattr(self.process, tag).DiPhotonSuffixes = cms.vstring(phosystlabels)\n getattr(self.process, tag).JetsSuffixes = cms.vstring(jetsystlabels)\n getattr(self.process, tag).MetSuffixes = cms.vstring(metsystlabels)\n \n getattr(self.process, tag).ModifySystematicsWorkflow = cms.bool(True)\n getattr(self.process, tag).UseLargeMVAs = cms.bool(True) # enable memory-intensive MVAs\n\n self.process.p.remove(self.process.flashggTagSorter)\n self.process.p.replace(self.process.flashggSystTagMerger, cms.Sequence(self.process.flashggTTHLeptonicTag + self.process.flashggTTHHadronicTag)*self.process.flashggTagSorter*self.process.flashggSystTagMerger)\n \n for systlabel in systlabels:\n if systlabel == \"\":\n continue\n self.process.p.remove(getattr(self.process, 'flashggTagSorter' + systlabel))\n self.process.p.replace(self.process.flashggSystTagMerger, getattr(self.process, 'flashggTagSorter' + systlabel) * self.process.flashggSystTagMerger)\n modifiedPriorityRanges = cms.VPSet(\n\t cms.PSet(TagName = cms.InputTag('flashggTHQLeptonicTag'+systlabel)),\n cms.PSet(TagName = cms.InputTag('flashggTTHLeptonicTag', systlabel)),\n cms.PSet(TagName = cms.InputTag('flashggZHLeptonicTag'+systlabel)),\n cms.PSet(TagName = cms.InputTag('flashggWHLeptonicTag'+systlabel)),\n cms.PSet(TagName = cms.InputTag('flashggTTHHadronicTag', systlabel)),\n cms.PSet(TagName = cms.InputTag('flashggVHMetTag'+systlabel)),\n cms.PSet(TagName = cms.InputTag('flashggStageOneCombinedTag'+systlabel))\n )\n setattr(getattr(self.process, 'flashggTagSorter'+systlabel), 'TagPriorityRanges', modifiedPriorityRanges)\n",
"step-ids": [
6,
7,
8,
9,
10
]
}
|
[
6,
7,
8,
9,
10
] |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import division, print_function, absolute_import, unicode_literals
import os
from qtpy.QtCore import *
# from qtpy.QtGui import *
from qtpy.QtWidgets import *
from six import string_types
from ..widgets import PathParamWidget, RelPathParamWidget, FilePathWidget
class TypeBase(object):
@classmethod
def create(cls, _):
"""
Create instance or return class
"""
return cls
@classmethod
def control(cls, delegate, property_item, parent):
return None
@staticmethod
def data(value):
"""
return item's data() value
"""
return value
@classmethod
def value(cls, control):
return None
@staticmethod
def icon(_):
return None
@classmethod
def height(cls):
return -1
@classmethod
def default(cls, value):
return value
@classmethod
def filter(cls, value):
return value
@classmethod
def set_link(cls, value):
pass
@classmethod
def link_value(cls, default_value, link_value):
return link_value or default_value
@classmethod
def sizeHint(cls):
return QSize(-1, -1)
@classmethod
def setup(cls, item):
pass
@classmethod
def set_value(cls, control, value):
control.setText(value)
is_persistent_editor = False
class TypeBool(TypeBase):
@classmethod
def control(cls, delegate, property_item, parent):
combo = QComboBox(parent)
combo.addItem("Yes")
combo.addItem("No")
return combo
@classmethod
def set_value(cls, control, value):
control.setCurrentIndex(0 if value else 1)
@classmethod
def value(cls, control):
return control.currentIndex() == 0
@staticmethod
def data(value):
return "Yes" if value else "No"
class CheckBox(QCheckBox):
def __init__(self, item, parent):
super(CheckBox, self).__init__(parent)
self.item = item
# noinspection PyUnresolvedReferences
self.stateChanged.connect(self.on_state_changed)
def on_state_changed(self, state):
self.item.set_value(state == Qt.Checked, force_update=True)
class TypeCheck(TypeBase):
is_persistent_editor = True
@classmethod
def control(cls, delegate, property_item, parent):
check = CheckBox(property_item, parent)
return check
@classmethod
def set_value(cls, control, value):
# type: (QCheckBox, bool) -> None
control.setCheckState(Qt.Checked if value else Qt.Unchecked)
@classmethod
def value(cls, control):
# type: (QCheckBox) -> bool
return control.isChecked()
class TypeFilePath(TypeBase):
@classmethod
def control(cls, delegate, property_item, parent):
return FilePathWidget(delegate, property_item.params, parent=parent)
@classmethod
def set_value(cls, control, value):
control.setText(value)
@classmethod
def value(cls, control):
return control.text()
@classmethod
def filter(cls, value):
return os.path.normpath(value) if value else value
@classmethod
def link_value(cls, default_value, link_value):
if default_value is None and link_value is None:
return ""
if link_value is None:
return default_value
if default_value is None:
return link_value
return os.path.join(default_value, link_value)
@classmethod
def sizeHint(cls):
return QSize(-1, 28)
class TypeDirPath(TypeBase):
@classmethod
def control(cls, delegate, property_item, parent):
return PathParamWidget(delegate, parent=parent)
@classmethod
def set_value(cls, control, value):
control.setText(value)
@classmethod
def value(cls, control):
return control.text()
@classmethod
def filter(cls, value):
return os.path.normpath(value) if value else value
@classmethod
def link_value(cls, default_value, link_value):
if default_value is None and link_value is None:
return ""
if link_value is None:
return default_value
if default_value is None:
return link_value
return os.path.join(default_value, link_value)
@classmethod
def sizeHint(cls):
return QSize(-1, 28)
class TypeRelDirPath(TypeDirPath):
@classmethod
def create(cls, params):
return cls(params)
def __init__(self, params):
self.relpath = params.get("relpath", ".")
def control(self, delegate, property_item, parent):
return RelPathParamWidget(delegate, relpath=self.relpath, parent=parent)
def default(self, path):
self.relpath = path or "."
return "."
def set_link(self, value):
self.relpath = value or "."
def filter(self, value):
if not value:
return "."
try:
if os.path.isabs(value):
return os.path.relpath(value, self.relpath)
else:
return value
except ValueError:
return "."
# noinspection PyArgumentList
class TypeChoice(TypeBase):
@classmethod
def create(cls, params):
return cls(params.get("choices", []))
def __init__(self, choices):
self.selects = []
self._data_dict = {}
self.setup_choices(choices)
def setup_choices(self, choices):
self.selects = []
for item in choices:
if isinstance(item, string_types):
item = {
"text": item,
"value": item,
}
self.selects.append(item)
self._data_dict = {item["value"]: item for item in self.selects}
def control(self, delegate, property_item, parent):
combo = QComboBox(parent)
self.setup_combo_box(combo)
return combo
def setup_combo_box(self, combo):
for i, item in enumerate(self.selects):
combo.addItem(item["text"])
combo.setItemData(i, item["value"])
if "icon" in item:
combo.setItemIcon(i, item["icon"])
# noinspection PyMethodOverriding
@staticmethod
def set_value(combo, value):
# type: (QComboBox, str) -> None
index = combo.findData(value)
combo.setCurrentIndex(index)
@classmethod
def value(cls, combo):
# type: (QComboBox, str) -> None
return combo.itemData(combo.currentIndex())
# noinspection PyMethodOverriding
def data(self, value):
return self._data_dict[value]["text"] if value in self._data_dict else None
# noinspection PyMethodOverriding
def icon(self, value):
try:
return self._data_dict[value]["icon"] if value in self._data_dict else None
except KeyError:
return None
|
normal
|
{
"blob_id": "ee91e8c9dcb940882733b2d23b74a76d0392f4fe",
"index": 2126,
"step-1": "<mask token>\n\n\nclass TypeDirPath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return PathParamWidget(delegate, parent=parent)\n <mask token>\n\n @classmethod\n def value(cls, control):\n return control.text()\n <mask token>\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n <mask token>\n\n\nclass TypeRelDirPath(TypeDirPath):\n\n @classmethod\n def create(cls, params):\n return cls(params)\n\n def __init__(self, params):\n self.relpath = params.get('relpath', '.')\n\n def control(self, delegate, property_item, parent):\n return RelPathParamWidget(delegate, relpath=self.relpath, parent=parent\n )\n\n def default(self, path):\n self.relpath = path or '.'\n return '.'\n\n def set_link(self, value):\n self.relpath = value or '.'\n\n def filter(self, value):\n if not value:\n return '.'\n try:\n if os.path.isabs(value):\n return os.path.relpath(value, self.relpath)\n else:\n return value\n except ValueError:\n return '.'\n\n\nclass TypeChoice(TypeBase):\n\n @classmethod\n def create(cls, params):\n return cls(params.get('choices', []))\n\n def __init__(self, choices):\n self.selects = []\n self._data_dict = {}\n self.setup_choices(choices)\n\n def setup_choices(self, choices):\n self.selects = []\n for item in choices:\n if isinstance(item, string_types):\n item = {'text': item, 'value': item}\n self.selects.append(item)\n self._data_dict = {item['value']: item for item in self.selects}\n\n def control(self, delegate, property_item, parent):\n combo = QComboBox(parent)\n self.setup_combo_box(combo)\n return combo\n\n def setup_combo_box(self, combo):\n for i, item in enumerate(self.selects):\n combo.addItem(item['text'])\n combo.setItemData(i, item['value'])\n if 'icon' in item:\n combo.setItemIcon(i, item['icon'])\n\n @staticmethod\n def set_value(combo, value):\n index = combo.findData(value)\n combo.setCurrentIndex(index)\n\n @classmethod\n def value(cls, combo):\n return combo.itemData(combo.currentIndex())\n\n def data(self, value):\n return self._data_dict[value]['text'\n ] if value in self._data_dict else None\n\n def icon(self, value):\n try:\n return self._data_dict[value]['icon'\n ] if value in self._data_dict else None\n except KeyError:\n return None\n",
"step-2": "<mask token>\n\n\nclass TypeBool(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n combo = QComboBox(parent)\n combo.addItem('Yes')\n combo.addItem('No')\n return combo\n <mask token>\n <mask token>\n <mask token>\n\n\nclass CheckBox(QCheckBox):\n\n def __init__(self, item, parent):\n super(CheckBox, self).__init__(parent)\n self.item = item\n self.stateChanged.connect(self.on_state_changed)\n\n def on_state_changed(self, state):\n self.item.set_value(state == Qt.Checked, force_update=True)\n\n\nclass TypeCheck(TypeBase):\n is_persistent_editor = True\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n check = CheckBox(property_item, parent)\n return check\n\n @classmethod\n def set_value(cls, control, value):\n control.setCheckState(Qt.Checked if value else Qt.Unchecked)\n\n @classmethod\n def value(cls, control):\n return control.isChecked()\n\n\nclass TypeFilePath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return FilePathWidget(delegate, property_item.params, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeDirPath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return PathParamWidget(delegate, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeRelDirPath(TypeDirPath):\n\n @classmethod\n def create(cls, params):\n return cls(params)\n\n def __init__(self, params):\n self.relpath = params.get('relpath', '.')\n\n def control(self, delegate, property_item, parent):\n return RelPathParamWidget(delegate, relpath=self.relpath, parent=parent\n )\n\n def default(self, path):\n self.relpath = path or '.'\n return '.'\n\n def set_link(self, value):\n self.relpath = value or '.'\n\n def filter(self, value):\n if not value:\n return '.'\n try:\n if os.path.isabs(value):\n return os.path.relpath(value, self.relpath)\n else:\n return value\n except ValueError:\n return '.'\n\n\nclass TypeChoice(TypeBase):\n\n @classmethod\n def create(cls, params):\n return cls(params.get('choices', []))\n\n def __init__(self, choices):\n self.selects = []\n self._data_dict = {}\n self.setup_choices(choices)\n\n def setup_choices(self, choices):\n self.selects = []\n for item in choices:\n if isinstance(item, string_types):\n item = {'text': item, 'value': item}\n self.selects.append(item)\n self._data_dict = {item['value']: item for item in self.selects}\n\n def control(self, delegate, property_item, parent):\n combo = QComboBox(parent)\n self.setup_combo_box(combo)\n return combo\n\n def setup_combo_box(self, combo):\n for i, item in enumerate(self.selects):\n combo.addItem(item['text'])\n combo.setItemData(i, item['value'])\n if 'icon' in item:\n combo.setItemIcon(i, item['icon'])\n\n @staticmethod\n def set_value(combo, value):\n index = combo.findData(value)\n combo.setCurrentIndex(index)\n\n @classmethod\n def value(cls, combo):\n return combo.itemData(combo.currentIndex())\n\n def data(self, value):\n return self._data_dict[value]['text'\n ] if value in self._data_dict else None\n\n def icon(self, value):\n try:\n return self._data_dict[value]['icon'\n ] if value in self._data_dict else None\n except KeyError:\n return None\n",
"step-3": "<mask token>\n\n\nclass TypeBool(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n combo = QComboBox(parent)\n combo.addItem('Yes')\n combo.addItem('No')\n return combo\n <mask token>\n\n @classmethod\n def value(cls, control):\n return control.currentIndex() == 0\n\n @staticmethod\n def data(value):\n return 'Yes' if value else 'No'\n\n\nclass CheckBox(QCheckBox):\n\n def __init__(self, item, parent):\n super(CheckBox, self).__init__(parent)\n self.item = item\n self.stateChanged.connect(self.on_state_changed)\n\n def on_state_changed(self, state):\n self.item.set_value(state == Qt.Checked, force_update=True)\n\n\nclass TypeCheck(TypeBase):\n is_persistent_editor = True\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n check = CheckBox(property_item, parent)\n return check\n\n @classmethod\n def set_value(cls, control, value):\n control.setCheckState(Qt.Checked if value else Qt.Unchecked)\n\n @classmethod\n def value(cls, control):\n return control.isChecked()\n\n\nclass TypeFilePath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return FilePathWidget(delegate, property_item.params, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeDirPath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return PathParamWidget(delegate, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeRelDirPath(TypeDirPath):\n\n @classmethod\n def create(cls, params):\n return cls(params)\n\n def __init__(self, params):\n self.relpath = params.get('relpath', '.')\n\n def control(self, delegate, property_item, parent):\n return RelPathParamWidget(delegate, relpath=self.relpath, parent=parent\n )\n\n def default(self, path):\n self.relpath = path or '.'\n return '.'\n\n def set_link(self, value):\n self.relpath = value or '.'\n\n def filter(self, value):\n if not value:\n return '.'\n try:\n if os.path.isabs(value):\n return os.path.relpath(value, self.relpath)\n else:\n return value\n except ValueError:\n return '.'\n\n\nclass TypeChoice(TypeBase):\n\n @classmethod\n def create(cls, params):\n return cls(params.get('choices', []))\n\n def __init__(self, choices):\n self.selects = []\n self._data_dict = {}\n self.setup_choices(choices)\n\n def setup_choices(self, choices):\n self.selects = []\n for item in choices:\n if isinstance(item, string_types):\n item = {'text': item, 'value': item}\n self.selects.append(item)\n self._data_dict = {item['value']: item for item in self.selects}\n\n def control(self, delegate, property_item, parent):\n combo = QComboBox(parent)\n self.setup_combo_box(combo)\n return combo\n\n def setup_combo_box(self, combo):\n for i, item in enumerate(self.selects):\n combo.addItem(item['text'])\n combo.setItemData(i, item['value'])\n if 'icon' in item:\n combo.setItemIcon(i, item['icon'])\n\n @staticmethod\n def set_value(combo, value):\n index = combo.findData(value)\n combo.setCurrentIndex(index)\n\n @classmethod\n def value(cls, combo):\n return combo.itemData(combo.currentIndex())\n\n def data(self, value):\n return self._data_dict[value]['text'\n ] if value in self._data_dict else None\n\n def icon(self, value):\n try:\n return self._data_dict[value]['icon'\n ] if value in self._data_dict else None\n except KeyError:\n return None\n",
"step-4": "<mask token>\n\n\nclass TypeBase(object):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass TypeBool(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n combo = QComboBox(parent)\n combo.addItem('Yes')\n combo.addItem('No')\n return combo\n\n @classmethod\n def set_value(cls, control, value):\n control.setCurrentIndex(0 if value else 1)\n\n @classmethod\n def value(cls, control):\n return control.currentIndex() == 0\n\n @staticmethod\n def data(value):\n return 'Yes' if value else 'No'\n\n\nclass CheckBox(QCheckBox):\n\n def __init__(self, item, parent):\n super(CheckBox, self).__init__(parent)\n self.item = item\n self.stateChanged.connect(self.on_state_changed)\n\n def on_state_changed(self, state):\n self.item.set_value(state == Qt.Checked, force_update=True)\n\n\nclass TypeCheck(TypeBase):\n is_persistent_editor = True\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n check = CheckBox(property_item, parent)\n return check\n\n @classmethod\n def set_value(cls, control, value):\n control.setCheckState(Qt.Checked if value else Qt.Unchecked)\n\n @classmethod\n def value(cls, control):\n return control.isChecked()\n\n\nclass TypeFilePath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return FilePathWidget(delegate, property_item.params, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeDirPath(TypeBase):\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return PathParamWidget(delegate, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return ''\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeRelDirPath(TypeDirPath):\n\n @classmethod\n def create(cls, params):\n return cls(params)\n\n def __init__(self, params):\n self.relpath = params.get('relpath', '.')\n\n def control(self, delegate, property_item, parent):\n return RelPathParamWidget(delegate, relpath=self.relpath, parent=parent\n )\n\n def default(self, path):\n self.relpath = path or '.'\n return '.'\n\n def set_link(self, value):\n self.relpath = value or '.'\n\n def filter(self, value):\n if not value:\n return '.'\n try:\n if os.path.isabs(value):\n return os.path.relpath(value, self.relpath)\n else:\n return value\n except ValueError:\n return '.'\n\n\nclass TypeChoice(TypeBase):\n\n @classmethod\n def create(cls, params):\n return cls(params.get('choices', []))\n\n def __init__(self, choices):\n self.selects = []\n self._data_dict = {}\n self.setup_choices(choices)\n\n def setup_choices(self, choices):\n self.selects = []\n for item in choices:\n if isinstance(item, string_types):\n item = {'text': item, 'value': item}\n self.selects.append(item)\n self._data_dict = {item['value']: item for item in self.selects}\n\n def control(self, delegate, property_item, parent):\n combo = QComboBox(parent)\n self.setup_combo_box(combo)\n return combo\n\n def setup_combo_box(self, combo):\n for i, item in enumerate(self.selects):\n combo.addItem(item['text'])\n combo.setItemData(i, item['value'])\n if 'icon' in item:\n combo.setItemIcon(i, item['icon'])\n\n @staticmethod\n def set_value(combo, value):\n index = combo.findData(value)\n combo.setCurrentIndex(index)\n\n @classmethod\n def value(cls, combo):\n return combo.itemData(combo.currentIndex())\n\n def data(self, value):\n return self._data_dict[value]['text'\n ] if value in self._data_dict else None\n\n def icon(self, value):\n try:\n return self._data_dict[value]['icon'\n ] if value in self._data_dict else None\n except KeyError:\n return None\n",
"step-5": "#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom __future__ import division, print_function, absolute_import, unicode_literals\n\nimport os\n\nfrom qtpy.QtCore import *\n# from qtpy.QtGui import *\nfrom qtpy.QtWidgets import *\nfrom six import string_types\n\nfrom ..widgets import PathParamWidget, RelPathParamWidget, FilePathWidget\n\n\nclass TypeBase(object):\n @classmethod\n def create(cls, _):\n \"\"\"\n Create instance or return class\n \"\"\"\n return cls\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n return None\n\n @staticmethod\n def data(value):\n \"\"\"\n return item's data() value\n \"\"\"\n return value\n\n @classmethod\n def value(cls, control):\n return None\n\n @staticmethod\n def icon(_):\n return None\n\n @classmethod\n def height(cls):\n return -1\n\n @classmethod\n def default(cls, value):\n return value\n\n @classmethod\n def filter(cls, value):\n return value\n\n @classmethod\n def set_link(cls, value):\n pass\n\n @classmethod\n def link_value(cls, default_value, link_value):\n return link_value or default_value\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, -1)\n\n @classmethod\n def setup(cls, item):\n pass\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n is_persistent_editor = False\n\n\nclass TypeBool(TypeBase):\n @classmethod\n def control(cls, delegate, property_item, parent):\n combo = QComboBox(parent)\n combo.addItem(\"Yes\")\n combo.addItem(\"No\")\n return combo\n\n @classmethod\n def set_value(cls, control, value):\n control.setCurrentIndex(0 if value else 1)\n\n @classmethod\n def value(cls, control):\n return control.currentIndex() == 0\n\n @staticmethod\n def data(value):\n return \"Yes\" if value else \"No\"\n\n\nclass CheckBox(QCheckBox):\n def __init__(self, item, parent):\n super(CheckBox, self).__init__(parent)\n self.item = item\n # noinspection PyUnresolvedReferences\n self.stateChanged.connect(self.on_state_changed)\n\n def on_state_changed(self, state):\n self.item.set_value(state == Qt.Checked, force_update=True)\n\n\nclass TypeCheck(TypeBase):\n is_persistent_editor = True\n\n @classmethod\n def control(cls, delegate, property_item, parent):\n check = CheckBox(property_item, parent)\n return check\n\n @classmethod\n def set_value(cls, control, value):\n # type: (QCheckBox, bool) -> None\n control.setCheckState(Qt.Checked if value else Qt.Unchecked)\n\n @classmethod\n def value(cls, control):\n # type: (QCheckBox) -> bool\n return control.isChecked()\n\n\nclass TypeFilePath(TypeBase):\n @classmethod\n def control(cls, delegate, property_item, parent):\n return FilePathWidget(delegate, property_item.params, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return \"\"\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeDirPath(TypeBase):\n @classmethod\n def control(cls, delegate, property_item, parent):\n return PathParamWidget(delegate, parent=parent)\n\n @classmethod\n def set_value(cls, control, value):\n control.setText(value)\n\n @classmethod\n def value(cls, control):\n return control.text()\n\n @classmethod\n def filter(cls, value):\n return os.path.normpath(value) if value else value\n\n @classmethod\n def link_value(cls, default_value, link_value):\n if default_value is None and link_value is None:\n return \"\"\n if link_value is None:\n return default_value\n if default_value is None:\n return link_value\n return os.path.join(default_value, link_value)\n\n @classmethod\n def sizeHint(cls):\n return QSize(-1, 28)\n\n\nclass TypeRelDirPath(TypeDirPath):\n @classmethod\n def create(cls, params):\n return cls(params)\n\n def __init__(self, params):\n self.relpath = params.get(\"relpath\", \".\")\n\n def control(self, delegate, property_item, parent):\n return RelPathParamWidget(delegate, relpath=self.relpath, parent=parent)\n\n def default(self, path):\n self.relpath = path or \".\"\n return \".\"\n\n def set_link(self, value):\n self.relpath = value or \".\"\n\n def filter(self, value):\n if not value:\n return \".\"\n try:\n if os.path.isabs(value):\n return os.path.relpath(value, self.relpath)\n else:\n return value\n except ValueError:\n return \".\"\n\n\n# noinspection PyArgumentList\nclass TypeChoice(TypeBase):\n @classmethod\n def create(cls, params):\n return cls(params.get(\"choices\", []))\n\n def __init__(self, choices):\n self.selects = []\n self._data_dict = {}\n self.setup_choices(choices)\n\n def setup_choices(self, choices):\n self.selects = []\n\n for item in choices:\n if isinstance(item, string_types):\n item = {\n \"text\": item,\n \"value\": item,\n }\n self.selects.append(item)\n self._data_dict = {item[\"value\"]: item for item in self.selects}\n\n def control(self, delegate, property_item, parent):\n combo = QComboBox(parent)\n self.setup_combo_box(combo)\n return combo\n\n def setup_combo_box(self, combo):\n for i, item in enumerate(self.selects):\n combo.addItem(item[\"text\"])\n combo.setItemData(i, item[\"value\"])\n if \"icon\" in item:\n combo.setItemIcon(i, item[\"icon\"])\n\n # noinspection PyMethodOverriding\n @staticmethod\n def set_value(combo, value):\n # type: (QComboBox, str) -> None\n index = combo.findData(value)\n combo.setCurrentIndex(index)\n\n @classmethod\n def value(cls, combo):\n # type: (QComboBox, str) -> None\n return combo.itemData(combo.currentIndex())\n\n # noinspection PyMethodOverriding\n def data(self, value):\n return self._data_dict[value][\"text\"] if value in self._data_dict else None\n\n # noinspection PyMethodOverriding\n def icon(self, value):\n try:\n return self._data_dict[value][\"icon\"] if value in self._data_dict else None\n except KeyError:\n return None\n",
"step-ids": [
21,
41,
43,
45,
61
]
}
|
[
21,
41,
43,
45,
61
] |
# # -*- coding: utf-8 -*-
#
# """
# Py40 PyQt5 tutorial
#
# This example shows three labels on a window
# using absolute positioning.
#
# author: Jan Bodnar
# website: py40.com
# last edited: January 2015
# """
#
# import sys
# from PyQt5.QtWidgets import QWidget, QLabel, QApplication
#
#
# class Example(QWidget):
#
# def __init__(self):
# super().__init__()
#
# self.initUI()
#
# def initUI(self):
# lbl1 = QLabel('Zetcode', self)
# lbl1.move(15, 10)
#
# lbl2 = QLabel('tutorials', self)
# lbl2.move(35, 40)
#
# lbl3 = QLabel('for programmers', self)
# lbl3.move(55, 70)
#
# self.setGeometry(300, 300, 250, 150)
# self.setWindowTitle('Absolute')
# self.show()
#
#
# if __name__ == '__main__':
# app = QApplication(sys.argv)
# ex = Example()
# sys.exit(app.exec_())
import psycopg2
def absent(lectureid,sectionid):
connection = psycopg2.connect(database="profmate", user="python", password="python", host="34.74.217.167",
port="5432")
cursor = connection.cursor()
postgreSQL_select_Query ="select * from lec_%s \
where student_id not in (select base.studentid\
from (select S.SectionID,Lectures.Lecture_Name,P.StudentID\
from Sections As S\
Join POOL as P\
On (P.Time > S.Time_Start)\
and (P.Time < S.Time_End)\
Join Lectures\
ON S.LectureID = Lectures.Lecture_ID\
Order By SectionID) as base\
join Students \
ON base.studentid = Students.Student_ID\
where sectionid = '%s' );"
cursor.execute(postgreSQL_select_Query,(lectureid,sectionid))
print("Selecting rows from POOL table using cursor.fetchall")
current_table = cursor.fetchall()
print("Print each row and it's columns values")
longstring = str('')
for row in current_table:
# print("Student ID = ", row[0])
# print("Family Name = ", row[1])
# print("Given Name = ", row[2], "\n")
longstring = "".join((longstring, "Student ID = ",str(row[0]),"\n"))
longstring = "".join((longstring, "Family Name = ", row[1], "\n"))
longstring = "".join((longstring, "Given Name = ", row[2], "\n"))
cursor.close()
connection.close()
print("PostgreSQL connection is closed")
return longstring
if __name__ == '__main__':
a = '234567890'
b = 'Tester'
c = 'One'
# insert_students(a, b, c)
print(absent(101, 1001))
|
normal
|
{
"blob_id": "e05dac901228e6972c1cb48ce2def3d248b4c167",
"index": 3053,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef absent(lectureid, sectionid):\n connection = psycopg2.connect(database='profmate', user='python',\n password='python', host='34.74.217.167', port='5432')\n cursor = connection.cursor()\n postgreSQL_select_Query = (\n \"select * from lec_%s where student_id not in (select base.studentid from (select S.SectionID,Lectures.Lecture_Name,P.StudentID from Sections As S Join POOL as P On (P.Time > S.Time_Start) and (P.Time < S.Time_End) Join Lectures ON S.LectureID = Lectures.Lecture_ID Order By SectionID) as base join Students ON base.studentid = Students.Student_ID where sectionid = '%s' );\"\n )\n cursor.execute(postgreSQL_select_Query, (lectureid, sectionid))\n print('Selecting rows from POOL table using cursor.fetchall')\n current_table = cursor.fetchall()\n print(\"Print each row and it's columns values\")\n longstring = str('')\n for row in current_table:\n longstring = ''.join((longstring, 'Student ID = ', str(row[0]), '\\n'))\n longstring = ''.join((longstring, 'Family Name = ', row[1], '\\n'))\n longstring = ''.join((longstring, 'Given Name = ', row[2], '\\n'))\n cursor.close()\n connection.close()\n print('PostgreSQL connection is closed')\n return longstring\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef absent(lectureid, sectionid):\n connection = psycopg2.connect(database='profmate', user='python',\n password='python', host='34.74.217.167', port='5432')\n cursor = connection.cursor()\n postgreSQL_select_Query = (\n \"select * from lec_%s where student_id not in (select base.studentid from (select S.SectionID,Lectures.Lecture_Name,P.StudentID from Sections As S Join POOL as P On (P.Time > S.Time_Start) and (P.Time < S.Time_End) Join Lectures ON S.LectureID = Lectures.Lecture_ID Order By SectionID) as base join Students ON base.studentid = Students.Student_ID where sectionid = '%s' );\"\n )\n cursor.execute(postgreSQL_select_Query, (lectureid, sectionid))\n print('Selecting rows from POOL table using cursor.fetchall')\n current_table = cursor.fetchall()\n print(\"Print each row and it's columns values\")\n longstring = str('')\n for row in current_table:\n longstring = ''.join((longstring, 'Student ID = ', str(row[0]), '\\n'))\n longstring = ''.join((longstring, 'Family Name = ', row[1], '\\n'))\n longstring = ''.join((longstring, 'Given Name = ', row[2], '\\n'))\n cursor.close()\n connection.close()\n print('PostgreSQL connection is closed')\n return longstring\n\n\nif __name__ == '__main__':\n a = '234567890'\n b = 'Tester'\n c = 'One'\n print(absent(101, 1001))\n",
"step-4": "import psycopg2\n\n\ndef absent(lectureid, sectionid):\n connection = psycopg2.connect(database='profmate', user='python',\n password='python', host='34.74.217.167', port='5432')\n cursor = connection.cursor()\n postgreSQL_select_Query = (\n \"select * from lec_%s where student_id not in (select base.studentid from (select S.SectionID,Lectures.Lecture_Name,P.StudentID from Sections As S Join POOL as P On (P.Time > S.Time_Start) and (P.Time < S.Time_End) Join Lectures ON S.LectureID = Lectures.Lecture_ID Order By SectionID) as base join Students ON base.studentid = Students.Student_ID where sectionid = '%s' );\"\n )\n cursor.execute(postgreSQL_select_Query, (lectureid, sectionid))\n print('Selecting rows from POOL table using cursor.fetchall')\n current_table = cursor.fetchall()\n print(\"Print each row and it's columns values\")\n longstring = str('')\n for row in current_table:\n longstring = ''.join((longstring, 'Student ID = ', str(row[0]), '\\n'))\n longstring = ''.join((longstring, 'Family Name = ', row[1], '\\n'))\n longstring = ''.join((longstring, 'Given Name = ', row[2], '\\n'))\n cursor.close()\n connection.close()\n print('PostgreSQL connection is closed')\n return longstring\n\n\nif __name__ == '__main__':\n a = '234567890'\n b = 'Tester'\n c = 'One'\n print(absent(101, 1001))\n",
"step-5": "# # -*- coding: utf-8 -*-\n#\n# \"\"\"\n# Py40 PyQt5 tutorial\n#\n# This example shows three labels on a window\n# using absolute positioning.\n#\n# author: Jan Bodnar\n# website: py40.com\n# last edited: January 2015\n# \"\"\"\n#\n# import sys\n# from PyQt5.QtWidgets import QWidget, QLabel, QApplication\n#\n#\n# class Example(QWidget):\n#\n# def __init__(self):\n# super().__init__()\n#\n# self.initUI()\n#\n# def initUI(self):\n# lbl1 = QLabel('Zetcode', self)\n# lbl1.move(15, 10)\n#\n# lbl2 = QLabel('tutorials', self)\n# lbl2.move(35, 40)\n#\n# lbl3 = QLabel('for programmers', self)\n# lbl3.move(55, 70)\n#\n# self.setGeometry(300, 300, 250, 150)\n# self.setWindowTitle('Absolute')\n# self.show()\n#\n#\n# if __name__ == '__main__':\n# app = QApplication(sys.argv)\n# ex = Example()\n# sys.exit(app.exec_())\nimport psycopg2\n\ndef absent(lectureid,sectionid):\n connection = psycopg2.connect(database=\"profmate\", user=\"python\", password=\"python\", host=\"34.74.217.167\",\n port=\"5432\")\n cursor = connection.cursor()\n postgreSQL_select_Query =\"select * from lec_%s \\\n where student_id not in (select base.studentid\\\n from (select S.SectionID,Lectures.Lecture_Name,P.StudentID\\\n from Sections As S\\\n Join POOL as P\\\n On (P.Time > S.Time_Start)\\\n and (P.Time < S.Time_End)\\\n Join Lectures\\\n ON S.LectureID = Lectures.Lecture_ID\\\n Order By SectionID) as base\\\n join Students \\\n ON base.studentid = Students.Student_ID\\\n where sectionid = '%s' );\"\n\n cursor.execute(postgreSQL_select_Query,(lectureid,sectionid))\n print(\"Selecting rows from POOL table using cursor.fetchall\")\n current_table = cursor.fetchall()\n\n print(\"Print each row and it's columns values\")\n\n longstring = str('')\n for row in current_table:\n # print(\"Student ID = \", row[0])\n # print(\"Family Name = \", row[1])\n # print(\"Given Name = \", row[2], \"\\n\")\n longstring = \"\".join((longstring, \"Student ID = \",str(row[0]),\"\\n\"))\n longstring = \"\".join((longstring, \"Family Name = \", row[1], \"\\n\"))\n longstring = \"\".join((longstring, \"Given Name = \", row[2], \"\\n\"))\n\n cursor.close()\n connection.close()\n print(\"PostgreSQL connection is closed\")\n return longstring\n\nif __name__ == '__main__':\n a = '234567890'\n b = 'Tester'\n c = 'One'\n # insert_students(a, b, c)\n print(absent(101, 1001))",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
from flask import Flask, request, render_template, redirect
from pymongo import MongoClient
from envparse import env
from flask_httpauth import HTTPDigestAuth
import os.path
# Get env vars stored either in an env file or on the machine
def get_env(name):
if (os.path.exists('./env')):
env.read_envfile('./env')
return env(name)
app = Flask(__name__)
app.config['SECRET_KEY'] = get_env('SECRET_KEY')
users = users = {
"admin": get_env('ADMIN_PASS')
}
auth = HTTPDigestAuth()
@auth.get_password
def get_pw(username):
if username in users:
return users.get(username)
return None
# Utility method for mongo connections
def mongo_login():
mongo_uri=get_env('MONGO_URI')
client = MongoClient(mongo_uri)
return client['rescuebnb']
# Home page with host form
@app.route('/')
def show_home():
return render_template('index.html')
# Post endpoint for committing host to db
@app.route('/addhost', methods = ['GET', 'POST'])
def hosts():
if request.method == 'POST':
db = mongo_login()
hosts_collection = db.hosts
host = request.form.to_dict()
hosts_collection.insert_one(host) # should probably check for completed insert
return redirect('/')
return render_template('addhosts.html')
# Post endpoint for committing people who need shelter to db
@app.route('/requestshelter', methods = ['GET', 'POST'])
def guests():
if request.method == 'POST':
db = mongo_login()
guest_collection = db.guests
guest = request.form.to_dict()
guest_collection.insert_one(guest) # should probably check for completed insert
return redirect('/')
return render_template('request_shelter.html')
# Get involved page
@app.route('/getinvolved')
def get_involved():
return render_template('get_involved.html')
# Get involved page
@app.route('/volunteer')
def volunteer():
return render_template('volunteer.html')
# "Secured" endpoint for viewing registered hosts
@app.route('/hosts')
@auth.login_required
def viewhosts():
db = mongo_login()
hosts_collection = db.hosts
guests_collection = db.guests
return render_template('viewhosts.html', hosts=list(hosts_collection.find()),
guests=list(guests_collection.find()))
@app.route('/ussd')
def ussd():
db = mongo_login()
ussd_collection = db.ussd
ussd = request.form.to_dict()
ussd_collection.insert_one(ussd)
return render_template('index.html')
if __name__ == '__main__':
app.run()
#app.run(debug=True)
|
normal
|
{
"blob_id": "ad813216ba8162a7089340c677e47c3e656f7c95",
"index": 6198,
"step-1": "<mask token>\n\n\n@app.route('/')\ndef show_home():\n return render_template('index.html')\n\n\n@app.route('/addhost', methods=['GET', 'POST'])\ndef hosts():\n if request.method == 'POST':\n db = mongo_login()\n hosts_collection = db.hosts\n host = request.form.to_dict()\n hosts_collection.insert_one(host)\n return redirect('/')\n return render_template('addhosts.html')\n\n\n<mask token>\n\n\n@app.route('/getinvolved')\ndef get_involved():\n return render_template('get_involved.html')\n\n\n@app.route('/volunteer')\ndef volunteer():\n return render_template('volunteer.html')\n\n\n@app.route('/hosts')\n@auth.login_required\ndef viewhosts():\n db = mongo_login()\n hosts_collection = db.hosts\n guests_collection = db.guests\n return render_template('viewhosts.html', hosts=list(hosts_collection.\n find()), guests=list(guests_collection.find()))\n\n\n@app.route('/ussd')\ndef ussd():\n db = mongo_login()\n ussd_collection = db.ussd\n ussd = request.form.to_dict()\n ussd_collection.insert_one(ussd)\n return render_template('index.html')\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\n@auth.get_password\ndef get_pw(username):\n if username in users:\n return users.get(username)\n return None\n\n\n<mask token>\n\n\n@app.route('/')\ndef show_home():\n return render_template('index.html')\n\n\n@app.route('/addhost', methods=['GET', 'POST'])\ndef hosts():\n if request.method == 'POST':\n db = mongo_login()\n hosts_collection = db.hosts\n host = request.form.to_dict()\n hosts_collection.insert_one(host)\n return redirect('/')\n return render_template('addhosts.html')\n\n\n<mask token>\n\n\n@app.route('/getinvolved')\ndef get_involved():\n return render_template('get_involved.html')\n\n\n@app.route('/volunteer')\ndef volunteer():\n return render_template('volunteer.html')\n\n\n@app.route('/hosts')\n@auth.login_required\ndef viewhosts():\n db = mongo_login()\n hosts_collection = db.hosts\n guests_collection = db.guests\n return render_template('viewhosts.html', hosts=list(hosts_collection.\n find()), guests=list(guests_collection.find()))\n\n\n@app.route('/ussd')\ndef ussd():\n db = mongo_login()\n ussd_collection = db.ussd\n ussd = request.form.to_dict()\n ussd_collection.insert_one(ussd)\n return render_template('index.html')\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef get_env(name):\n if os.path.exists('./env'):\n env.read_envfile('./env')\n return env(name)\n\n\n<mask token>\n\n\n@auth.get_password\ndef get_pw(username):\n if username in users:\n return users.get(username)\n return None\n\n\ndef mongo_login():\n mongo_uri = get_env('MONGO_URI')\n client = MongoClient(mongo_uri)\n return client['rescuebnb']\n\n\n@app.route('/')\ndef show_home():\n return render_template('index.html')\n\n\n@app.route('/addhost', methods=['GET', 'POST'])\ndef hosts():\n if request.method == 'POST':\n db = mongo_login()\n hosts_collection = db.hosts\n host = request.form.to_dict()\n hosts_collection.insert_one(host)\n return redirect('/')\n return render_template('addhosts.html')\n\n\n@app.route('/requestshelter', methods=['GET', 'POST'])\ndef guests():\n if request.method == 'POST':\n db = mongo_login()\n guest_collection = db.guests\n guest = request.form.to_dict()\n guest_collection.insert_one(guest)\n return redirect('/')\n return render_template('request_shelter.html')\n\n\n@app.route('/getinvolved')\ndef get_involved():\n return render_template('get_involved.html')\n\n\n@app.route('/volunteer')\ndef volunteer():\n return render_template('volunteer.html')\n\n\n@app.route('/hosts')\n@auth.login_required\ndef viewhosts():\n db = mongo_login()\n hosts_collection = db.hosts\n guests_collection = db.guests\n return render_template('viewhosts.html', hosts=list(hosts_collection.\n find()), guests=list(guests_collection.find()))\n\n\n@app.route('/ussd')\ndef ussd():\n db = mongo_login()\n ussd_collection = db.ussd\n ussd = request.form.to_dict()\n ussd_collection.insert_one(ussd)\n return render_template('index.html')\n\n\n<mask token>\n",
"step-4": "from flask import Flask, request, render_template, redirect\nfrom pymongo import MongoClient\nfrom envparse import env\nfrom flask_httpauth import HTTPDigestAuth\nimport os.path\n\n\ndef get_env(name):\n if os.path.exists('./env'):\n env.read_envfile('./env')\n return env(name)\n\n\napp = Flask(__name__)\napp.config['SECRET_KEY'] = get_env('SECRET_KEY')\nusers = users = {'admin': get_env('ADMIN_PASS')}\nauth = HTTPDigestAuth()\n\n\n@auth.get_password\ndef get_pw(username):\n if username in users:\n return users.get(username)\n return None\n\n\ndef mongo_login():\n mongo_uri = get_env('MONGO_URI')\n client = MongoClient(mongo_uri)\n return client['rescuebnb']\n\n\n@app.route('/')\ndef show_home():\n return render_template('index.html')\n\n\n@app.route('/addhost', methods=['GET', 'POST'])\ndef hosts():\n if request.method == 'POST':\n db = mongo_login()\n hosts_collection = db.hosts\n host = request.form.to_dict()\n hosts_collection.insert_one(host)\n return redirect('/')\n return render_template('addhosts.html')\n\n\n@app.route('/requestshelter', methods=['GET', 'POST'])\ndef guests():\n if request.method == 'POST':\n db = mongo_login()\n guest_collection = db.guests\n guest = request.form.to_dict()\n guest_collection.insert_one(guest)\n return redirect('/')\n return render_template('request_shelter.html')\n\n\n@app.route('/getinvolved')\ndef get_involved():\n return render_template('get_involved.html')\n\n\n@app.route('/volunteer')\ndef volunteer():\n return render_template('volunteer.html')\n\n\n@app.route('/hosts')\n@auth.login_required\ndef viewhosts():\n db = mongo_login()\n hosts_collection = db.hosts\n guests_collection = db.guests\n return render_template('viewhosts.html', hosts=list(hosts_collection.\n find()), guests=list(guests_collection.find()))\n\n\n@app.route('/ussd')\ndef ussd():\n db = mongo_login()\n ussd_collection = db.ussd\n ussd = request.form.to_dict()\n ussd_collection.insert_one(ussd)\n return render_template('index.html')\n\n\nif __name__ == '__main__':\n app.run()\n",
"step-5": "from flask import Flask, request, render_template, redirect\nfrom pymongo import MongoClient\nfrom envparse import env\nfrom flask_httpauth import HTTPDigestAuth\nimport os.path\n\n\n# Get env vars stored either in an env file or on the machine\ndef get_env(name):\n\tif (os.path.exists('./env')):\n\t\tenv.read_envfile('./env')\n\treturn env(name)\n\napp = Flask(__name__)\napp.config['SECRET_KEY'] = get_env('SECRET_KEY')\nusers = users = {\n \"admin\": get_env('ADMIN_PASS')\n}\nauth = HTTPDigestAuth()\n\n@auth.get_password\ndef get_pw(username):\n if username in users:\n return users.get(username)\n return None\n\n\n# Utility method for mongo connections\ndef mongo_login():\n\tmongo_uri=get_env('MONGO_URI')\n\tclient = MongoClient(mongo_uri)\n\treturn client['rescuebnb']\n\n# Home page with host form\n@app.route('/')\ndef show_home():\n\treturn render_template('index.html')\n\n# Post endpoint for committing host to db\n@app.route('/addhost', methods = ['GET', 'POST'])\ndef hosts():\n\tif request.method == 'POST':\n\t\tdb = mongo_login()\n\t\thosts_collection = db.hosts\n\t\thost = request.form.to_dict()\n\t\thosts_collection.insert_one(host) # should probably check for completed insert\n\t\treturn redirect('/')\n\treturn render_template('addhosts.html')\n\n# Post endpoint for committing people who need shelter to db\n@app.route('/requestshelter', methods = ['GET', 'POST'])\ndef guests():\n\tif request.method == 'POST':\n\t\tdb = mongo_login()\n\t\tguest_collection = db.guests\n\t\tguest = request.form.to_dict()\n\t\tguest_collection.insert_one(guest) # should probably check for completed insert\n\t\treturn redirect('/')\n\treturn render_template('request_shelter.html')\n\n# Get involved page\n@app.route('/getinvolved')\ndef get_involved():\n\treturn render_template('get_involved.html')\n\n# Get involved page\n@app.route('/volunteer')\ndef volunteer():\n\treturn render_template('volunteer.html')\n\n# \"Secured\" endpoint for viewing registered hosts\n@app.route('/hosts')\n@auth.login_required\ndef viewhosts():\n\tdb = mongo_login()\n\thosts_collection = db.hosts\n\tguests_collection = db.guests\n\t\n\treturn render_template('viewhosts.html', hosts=list(hosts_collection.find()),\n\t\tguests=list(guests_collection.find()))\n\n@app.route('/ussd')\ndef ussd():\n\tdb = mongo_login()\n\tussd_collection = db.ussd\n\tussd = request.form.to_dict()\n\tussd_collection.insert_one(ussd)\n\treturn render_template('index.html')\n\nif __name__ == '__main__':\n\tapp.run()\n #app.run(debug=True)",
"step-ids": [
6,
7,
10,
13,
14
]
}
|
[
6,
7,
10,
13,
14
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
print('Valor da conta com 10%: R$', a)
<|reserved_special_token_1|>
a = float.input('Valor da conta')
print('Valor da conta com 10%: R$', a)
<|reserved_special_token_1|>
a=float.input('Valor da conta')
print('Valor da conta com 10%: R$',(a))
|
flexible
|
{
"blob_id": "d1ce6c081dce2e4bdb6087cd61d7f857dbb1348d",
"index": 8781,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint('Valor da conta com 10%: R$', a)\n",
"step-3": "a = float.input('Valor da conta')\nprint('Valor da conta com 10%: R$', a)\n",
"step-4": "a=float.input('Valor da conta')\nprint('Valor da conta com 10%: R$',(a))\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
class TimeInterval(object):
def __init__(self, start_time, end_time):
self.start_time = start_time
self.end_time = end_time
|
normal
|
{
"blob_id": "9d772d5500593583907b65bc2c81490e61375e8b",
"index": 8081,
"step-1": "<mask token>\n",
"step-2": "class TimeInterval(object):\n <mask token>\n",
"step-3": "class TimeInterval(object):\n\n def __init__(self, start_time, end_time):\n self.start_time = start_time\n self.end_time = end_time\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
from os import chdir
from os.path import dirname, realpath
import random
from flask import Flask, render_template, send_from_directory
app = Flask(__name__)
# gets list of list of all classes
def get_data():
class_list = []
with open('counts.tsv') as fd:
for line in fd.read().splitlines():
class_data = line.split("\t")
class_list.append(class_data)
return class_list
# Gets list of list of all fall 2016 classes
def get_fall_2016():
directory = get_data() # list of all classes of all years
fall_2016_list = []
for n in directory: # for any individual course,
if n[0] == '2016' and n[1] == 'fall':
fall_2016_list.append(n)
return fall_2016_list
# searches fall 2016 classes for a specific Core requirement and creates new list of courses that satisfy that core
def get_fall_2016_core(core):
directory = get_fall_2016()
core_satisfied_list = [] # list of all classes that satisfy specified core requirement
for n in directory:
core_possible = n[9].split(";") # splits multiple core requirements into list of the individual ones
if core in core_possible: # if core argument is satisfied by the class, add class to list of classes
core_satisfied_list.append(n)
return core_satisfied_list
@app.route('/')
def display_full_courses():
courses = get_data()
return render_template('base.html', courses=courses)
# All of the remaining functions display website with 3 (different) random classes that satisfy specified core requirement
@app.route('/CPAF')
def display_random_CPAF():
courses = get_fall_2016_core('CPAF')
list_of_three = []
course1 = random.choice(courses)
for i in range(10): # ensures second course is different from first one
course2 = random.choice(courses)
if course2[5] != course1[5]:
break # if course titles are different, keep course 2. if not, try again
for i in range(10): # ensures third course is different from first and second
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break # if course titles are different, keep course 3. if not, try again
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPAS')
def display_random_CPAS():
courses = get_fall_2016_core('CPAS')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPEU')
def display_random_CPEU():
courses = get_fall_2016_core('CPEU')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPFA')
def display_random_CPFA():
courses = get_fall_2016_core('CPFA')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPAP')
def display_random_CPAP():
courses = get_fall_2016_core('CPAP')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CFAP')
def display_random_CFAP():
courses = get_fall_2016_core('CFAP')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPGC')
def display_random_CPGC():
courses = get_fall_2016_core('CPGC')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPIC')
def display_random_CPIC():
courses = get_fall_2016_core('CPIC')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPLS')
def display_random_CPLS():
courses = get_fall_2016_core('CPLS')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPLA')
def display_random_CPLA():
courses = get_fall_2016_core('CPLA')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPMS')
def display_random_CPMS():
courses = get_fall_2016_core('CPMS')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPPE')
def display_random_CPPE():
courses = get_fall_2016_core('CPPE')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPRF')
def display_random_CPRF():
courses = get_fall_2016_core('CPRF')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPUS')
def display_random_CPUS():
courses = get_fall_2016_core('CPUS')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CPUD')
def display_random_CPUD():
courses = get_fall_2016_core('CPUD')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
@app.route('/CUSP')
def display_random_CUSP():
courses = get_fall_2016_core('CUSP')
list_of_three = []
course1 = random.choice(courses)
for i in range(10):
course2 = random.choice(courses)
if course2[5] != course1[5]:
break
for i in range(10):
course3 = random.choice(courses)
if (course3[5] != course1[5]) and (course3[5] != course2[5]):
break
list_of_three.append(course1)
list_of_three.append(course2)
list_of_three.append(course3)
return render_template('courses.html', courses=list_of_three)
# The functions below lets you access files in the css, js, and images folders.
# You should not change them unless you know what you are doing.
@app.route('/images/<file>')
def get_image(file):
return send_from_directory('images', file)
@app.route('/css/<file>')
def get_css(file):
return send_from_directory('css', file)
@app.route('/js/<file>')
def get_js(file):
return send_from_directory('js', file)
if __name__ == '__main__':
app.run(debug=True)
|
normal
|
{
"blob_id": "af8a3fbce35685cd89dee72449a8be2a133b4a3f",
"index": 4684,
"step-1": "<mask token>\n\n\ndef get_data():\n class_list = []\n with open('counts.tsv') as fd:\n for line in fd.read().splitlines():\n class_data = line.split('\\t')\n class_list.append(class_data)\n return class_list\n\n\ndef get_fall_2016():\n directory = get_data()\n fall_2016_list = []\n for n in directory:\n if n[0] == '2016' and n[1] == 'fall':\n fall_2016_list.append(n)\n return fall_2016_list\n\n\ndef get_fall_2016_core(core):\n directory = get_fall_2016()\n core_satisfied_list = []\n for n in directory:\n core_possible = n[9].split(';')\n if core in core_possible:\n core_satisfied_list.append(n)\n return core_satisfied_list\n\n\n<mask token>\n\n\n@app.route('/CPAF')\ndef display_random_CPAF():\n courses = get_fall_2016_core('CPAF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPAS')\ndef display_random_CPAS():\n courses = get_fall_2016_core('CPAS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n<mask token>\n\n\n@app.route('/CFAP')\ndef display_random_CFAP():\n courses = get_fall_2016_core('CFAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n<mask token>\n\n\n@app.route('/CPLS')\ndef display_random_CPLS():\n courses = get_fall_2016_core('CPLS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLA')\ndef display_random_CPLA():\n courses = get_fall_2016_core('CPLA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPMS')\ndef display_random_CPMS():\n courses = get_fall_2016_core('CPMS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPPE')\ndef display_random_CPPE():\n courses = get_fall_2016_core('CPPE')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPRF')\ndef display_random_CPRF():\n courses = get_fall_2016_core('CPRF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUS')\ndef display_random_CPUS():\n courses = get_fall_2016_core('CPUS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUD')\ndef display_random_CPUD():\n courses = get_fall_2016_core('CPUD')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CUSP')\ndef display_random_CUSP():\n courses = get_fall_2016_core('CUSP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/images/<file>')\ndef get_image(file):\n return send_from_directory('images', file)\n\n\n@app.route('/css/<file>')\ndef get_css(file):\n return send_from_directory('css', file)\n\n\n@app.route('/js/<file>')\ndef get_js(file):\n return send_from_directory('js', file)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_data():\n class_list = []\n with open('counts.tsv') as fd:\n for line in fd.read().splitlines():\n class_data = line.split('\\t')\n class_list.append(class_data)\n return class_list\n\n\ndef get_fall_2016():\n directory = get_data()\n fall_2016_list = []\n for n in directory:\n if n[0] == '2016' and n[1] == 'fall':\n fall_2016_list.append(n)\n return fall_2016_list\n\n\ndef get_fall_2016_core(core):\n directory = get_fall_2016()\n core_satisfied_list = []\n for n in directory:\n core_possible = n[9].split(';')\n if core in core_possible:\n core_satisfied_list.append(n)\n return core_satisfied_list\n\n\n<mask token>\n\n\n@app.route('/CPAF')\ndef display_random_CPAF():\n courses = get_fall_2016_core('CPAF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPAS')\ndef display_random_CPAS():\n courses = get_fall_2016_core('CPAS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n<mask token>\n\n\n@app.route('/CFAP')\ndef display_random_CFAP():\n courses = get_fall_2016_core('CFAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPGC')\ndef display_random_CPGC():\n courses = get_fall_2016_core('CPGC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPIC')\ndef display_random_CPIC():\n courses = get_fall_2016_core('CPIC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLS')\ndef display_random_CPLS():\n courses = get_fall_2016_core('CPLS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLA')\ndef display_random_CPLA():\n courses = get_fall_2016_core('CPLA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPMS')\ndef display_random_CPMS():\n courses = get_fall_2016_core('CPMS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPPE')\ndef display_random_CPPE():\n courses = get_fall_2016_core('CPPE')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPRF')\ndef display_random_CPRF():\n courses = get_fall_2016_core('CPRF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUS')\ndef display_random_CPUS():\n courses = get_fall_2016_core('CPUS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUD')\ndef display_random_CPUD():\n courses = get_fall_2016_core('CPUD')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CUSP')\ndef display_random_CUSP():\n courses = get_fall_2016_core('CUSP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/images/<file>')\ndef get_image(file):\n return send_from_directory('images', file)\n\n\n@app.route('/css/<file>')\ndef get_css(file):\n return send_from_directory('css', file)\n\n\n@app.route('/js/<file>')\ndef get_js(file):\n return send_from_directory('js', file)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef get_data():\n class_list = []\n with open('counts.tsv') as fd:\n for line in fd.read().splitlines():\n class_data = line.split('\\t')\n class_list.append(class_data)\n return class_list\n\n\ndef get_fall_2016():\n directory = get_data()\n fall_2016_list = []\n for n in directory:\n if n[0] == '2016' and n[1] == 'fall':\n fall_2016_list.append(n)\n return fall_2016_list\n\n\ndef get_fall_2016_core(core):\n directory = get_fall_2016()\n core_satisfied_list = []\n for n in directory:\n core_possible = n[9].split(';')\n if core in core_possible:\n core_satisfied_list.append(n)\n return core_satisfied_list\n\n\n@app.route('/')\ndef display_full_courses():\n courses = get_data()\n return render_template('base.html', courses=courses)\n\n\n@app.route('/CPAF')\ndef display_random_CPAF():\n courses = get_fall_2016_core('CPAF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPAS')\ndef display_random_CPAS():\n courses = get_fall_2016_core('CPAS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPEU')\ndef display_random_CPEU():\n courses = get_fall_2016_core('CPEU')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPFA')\ndef display_random_CPFA():\n courses = get_fall_2016_core('CPFA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPAP')\ndef display_random_CPAP():\n courses = get_fall_2016_core('CPAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CFAP')\ndef display_random_CFAP():\n courses = get_fall_2016_core('CFAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPGC')\ndef display_random_CPGC():\n courses = get_fall_2016_core('CPGC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPIC')\ndef display_random_CPIC():\n courses = get_fall_2016_core('CPIC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLS')\ndef display_random_CPLS():\n courses = get_fall_2016_core('CPLS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLA')\ndef display_random_CPLA():\n courses = get_fall_2016_core('CPLA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPMS')\ndef display_random_CPMS():\n courses = get_fall_2016_core('CPMS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPPE')\ndef display_random_CPPE():\n courses = get_fall_2016_core('CPPE')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPRF')\ndef display_random_CPRF():\n courses = get_fall_2016_core('CPRF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUS')\ndef display_random_CPUS():\n courses = get_fall_2016_core('CPUS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUD')\ndef display_random_CPUD():\n courses = get_fall_2016_core('CPUD')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CUSP')\ndef display_random_CUSP():\n courses = get_fall_2016_core('CUSP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/images/<file>')\ndef get_image(file):\n return send_from_directory('images', file)\n\n\n@app.route('/css/<file>')\ndef get_css(file):\n return send_from_directory('css', file)\n\n\n@app.route('/js/<file>')\ndef get_js(file):\n return send_from_directory('js', file)\n\n\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-4": "from os import chdir\nfrom os.path import dirname, realpath\nimport random\nfrom flask import Flask, render_template, send_from_directory\napp = Flask(__name__)\n\n\ndef get_data():\n class_list = []\n with open('counts.tsv') as fd:\n for line in fd.read().splitlines():\n class_data = line.split('\\t')\n class_list.append(class_data)\n return class_list\n\n\ndef get_fall_2016():\n directory = get_data()\n fall_2016_list = []\n for n in directory:\n if n[0] == '2016' and n[1] == 'fall':\n fall_2016_list.append(n)\n return fall_2016_list\n\n\ndef get_fall_2016_core(core):\n directory = get_fall_2016()\n core_satisfied_list = []\n for n in directory:\n core_possible = n[9].split(';')\n if core in core_possible:\n core_satisfied_list.append(n)\n return core_satisfied_list\n\n\n@app.route('/')\ndef display_full_courses():\n courses = get_data()\n return render_template('base.html', courses=courses)\n\n\n@app.route('/CPAF')\ndef display_random_CPAF():\n courses = get_fall_2016_core('CPAF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPAS')\ndef display_random_CPAS():\n courses = get_fall_2016_core('CPAS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPEU')\ndef display_random_CPEU():\n courses = get_fall_2016_core('CPEU')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPFA')\ndef display_random_CPFA():\n courses = get_fall_2016_core('CPFA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPAP')\ndef display_random_CPAP():\n courses = get_fall_2016_core('CPAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CFAP')\ndef display_random_CFAP():\n courses = get_fall_2016_core('CFAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPGC')\ndef display_random_CPGC():\n courses = get_fall_2016_core('CPGC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPIC')\ndef display_random_CPIC():\n courses = get_fall_2016_core('CPIC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLS')\ndef display_random_CPLS():\n courses = get_fall_2016_core('CPLS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPLA')\ndef display_random_CPLA():\n courses = get_fall_2016_core('CPLA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPMS')\ndef display_random_CPMS():\n courses = get_fall_2016_core('CPMS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPPE')\ndef display_random_CPPE():\n courses = get_fall_2016_core('CPPE')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPRF')\ndef display_random_CPRF():\n courses = get_fall_2016_core('CPRF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUS')\ndef display_random_CPUS():\n courses = get_fall_2016_core('CPUS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CPUD')\ndef display_random_CPUD():\n courses = get_fall_2016_core('CPUD')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/CUSP')\ndef display_random_CUSP():\n courses = get_fall_2016_core('CUSP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if course3[5] != course1[5] and course3[5] != course2[5]:\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n\n@app.route('/images/<file>')\ndef get_image(file):\n return send_from_directory('images', file)\n\n\n@app.route('/css/<file>')\ndef get_css(file):\n return send_from_directory('css', file)\n\n\n@app.route('/js/<file>')\ndef get_js(file):\n return send_from_directory('js', file)\n\n\nif __name__ == '__main__':\n app.run(debug=True)\n",
"step-5": "from os import chdir\nfrom os.path import dirname, realpath\nimport random\n\nfrom flask import Flask, render_template, send_from_directory\n\napp = Flask(__name__)\n\n\n# gets list of list of all classes\ndef get_data():\n class_list = []\n with open('counts.tsv') as fd:\n for line in fd.read().splitlines():\n class_data = line.split(\"\\t\")\n class_list.append(class_data)\n return class_list\n\n\n# Gets list of list of all fall 2016 classes\ndef get_fall_2016():\n directory = get_data() # list of all classes of all years\n fall_2016_list = []\n for n in directory: # for any individual course,\n if n[0] == '2016' and n[1] == 'fall':\n fall_2016_list.append(n)\n return fall_2016_list\n\n\n# searches fall 2016 classes for a specific Core requirement and creates new list of courses that satisfy that core\ndef get_fall_2016_core(core):\n directory = get_fall_2016()\n core_satisfied_list = [] # list of all classes that satisfy specified core requirement\n for n in directory:\n core_possible = n[9].split(\";\") # splits multiple core requirements into list of the individual ones\n if core in core_possible: # if core argument is satisfied by the class, add class to list of classes\n core_satisfied_list.append(n)\n return core_satisfied_list\n\n\n@app.route('/')\ndef display_full_courses():\n courses = get_data()\n return render_template('base.html', courses=courses)\n\n# All of the remaining functions display website with 3 (different) random classes that satisfy specified core requirement\n\n@app.route('/CPAF')\ndef display_random_CPAF():\n courses = get_fall_2016_core('CPAF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10): # ensures second course is different from first one\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break # if course titles are different, keep course 2. if not, try again\n for i in range(10): # ensures third course is different from first and second\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break # if course titles are different, keep course 3. if not, try again\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPAS')\ndef display_random_CPAS():\n courses = get_fall_2016_core('CPAS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPEU')\ndef display_random_CPEU():\n courses = get_fall_2016_core('CPEU')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPFA')\ndef display_random_CPFA():\n courses = get_fall_2016_core('CPFA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPAP')\ndef display_random_CPAP():\n courses = get_fall_2016_core('CPAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CFAP')\ndef display_random_CFAP():\n courses = get_fall_2016_core('CFAP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPGC')\ndef display_random_CPGC():\n courses = get_fall_2016_core('CPGC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPIC')\ndef display_random_CPIC():\n courses = get_fall_2016_core('CPIC')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPLS')\ndef display_random_CPLS():\n courses = get_fall_2016_core('CPLS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPLA')\ndef display_random_CPLA():\n courses = get_fall_2016_core('CPLA')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPMS')\ndef display_random_CPMS():\n courses = get_fall_2016_core('CPMS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPPE')\ndef display_random_CPPE():\n courses = get_fall_2016_core('CPPE')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPRF')\ndef display_random_CPRF():\n courses = get_fall_2016_core('CPRF')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPUS')\ndef display_random_CPUS():\n courses = get_fall_2016_core('CPUS')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CPUD')\ndef display_random_CPUD():\n courses = get_fall_2016_core('CPUD')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n@app.route('/CUSP')\ndef display_random_CUSP():\n courses = get_fall_2016_core('CUSP')\n list_of_three = []\n course1 = random.choice(courses)\n for i in range(10):\n course2 = random.choice(courses)\n if course2[5] != course1[5]:\n break\n for i in range(10):\n course3 = random.choice(courses)\n if (course3[5] != course1[5]) and (course3[5] != course2[5]):\n break\n list_of_three.append(course1)\n list_of_three.append(course2)\n list_of_three.append(course3)\n return render_template('courses.html', courses=list_of_three)\n\n# The functions below lets you access files in the css, js, and images folders.\n# You should not change them unless you know what you are doing.\n\n@app.route('/images/<file>')\ndef get_image(file):\n return send_from_directory('images', file)\n\n@app.route('/css/<file>')\ndef get_css(file):\n return send_from_directory('css', file)\n\n@app.route('/js/<file>')\ndef get_js(file):\n return send_from_directory('js', file)\n\nif __name__ == '__main__':\n app.run(debug=True)",
"step-ids": [
17,
19,
24,
26,
27
]
}
|
[
17,
19,
24,
26,
27
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for gen in range(params['gens']):
parents = select(population, params['n_pars'])
offspring = reproduce(params, parents, crossover)
offspring = mutate(params, offspring)
offspring = evaluate(params, offspring)
population = replace(np.concatenate((population, offspring), axis=0),
params['pop_size'])
print(gen)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
initialize = init.permutation
evaluate = eval.custom
select = sel.rank_based
mutate = mut.swap
reproduce = rec.pairwise
crossover = rec.order
replace = sel.rank_based
params = {'gens': 100, 'n_off': 50, 'n_pars': 100, 'n_objs': 1, 'pop_size':
150, 'len_gene': 100, 'mut_rate': 0.5}
population = initialize(params)
population = evaluate(params, population)
for gen in range(params['gens']):
parents = select(population, params['n_pars'])
offspring = reproduce(params, parents, crossover)
offspring = mutate(params, offspring)
offspring = evaluate(params, offspring)
population = replace(np.concatenate((population, offspring), axis=0),
params['pop_size'])
print(gen)
<|reserved_special_token_1|>
import numpy as np
import initialization as init
import evaluation as eval
import selection as sel
import recombination as rec
import mutation as mut
initialize = init.permutation
evaluate = eval.custom
select = sel.rank_based
mutate = mut.swap
reproduce = rec.pairwise
crossover = rec.order
replace = sel.rank_based
params = {'gens': 100, 'n_off': 50, 'n_pars': 100, 'n_objs': 1, 'pop_size':
150, 'len_gene': 100, 'mut_rate': 0.5}
population = initialize(params)
population = evaluate(params, population)
for gen in range(params['gens']):
parents = select(population, params['n_pars'])
offspring = reproduce(params, parents, crossover)
offspring = mutate(params, offspring)
offspring = evaluate(params, offspring)
population = replace(np.concatenate((population, offspring), axis=0),
params['pop_size'])
print(gen)
|
flexible
|
{
"blob_id": "5eab41a2ef536365bab6f6b5ad97efb8d26d7687",
"index": 4456,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor gen in range(params['gens']):\n parents = select(population, params['n_pars'])\n offspring = reproduce(params, parents, crossover)\n offspring = mutate(params, offspring)\n offspring = evaluate(params, offspring)\n population = replace(np.concatenate((population, offspring), axis=0),\n params['pop_size'])\n print(gen)\n",
"step-3": "<mask token>\ninitialize = init.permutation\nevaluate = eval.custom\nselect = sel.rank_based\nmutate = mut.swap\nreproduce = rec.pairwise\ncrossover = rec.order\nreplace = sel.rank_based\nparams = {'gens': 100, 'n_off': 50, 'n_pars': 100, 'n_objs': 1, 'pop_size':\n 150, 'len_gene': 100, 'mut_rate': 0.5}\npopulation = initialize(params)\npopulation = evaluate(params, population)\nfor gen in range(params['gens']):\n parents = select(population, params['n_pars'])\n offspring = reproduce(params, parents, crossover)\n offspring = mutate(params, offspring)\n offspring = evaluate(params, offspring)\n population = replace(np.concatenate((population, offspring), axis=0),\n params['pop_size'])\n print(gen)\n",
"step-4": "import numpy as np\nimport initialization as init\nimport evaluation as eval\nimport selection as sel\nimport recombination as rec\nimport mutation as mut\ninitialize = init.permutation\nevaluate = eval.custom\nselect = sel.rank_based\nmutate = mut.swap\nreproduce = rec.pairwise\ncrossover = rec.order\nreplace = sel.rank_based\nparams = {'gens': 100, 'n_off': 50, 'n_pars': 100, 'n_objs': 1, 'pop_size':\n 150, 'len_gene': 100, 'mut_rate': 0.5}\npopulation = initialize(params)\npopulation = evaluate(params, population)\nfor gen in range(params['gens']):\n parents = select(population, params['n_pars'])\n offspring = reproduce(params, parents, crossover)\n offspring = mutate(params, offspring)\n offspring = evaluate(params, offspring)\n population = replace(np.concatenate((population, offspring), axis=0),\n params['pop_size'])\n print(gen)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
#import fungsi_saya as fs
# from fungsi_saya import kalkulator as k
# hasil = k(10,5,'+')
# print(hasil)
from kelas import Siswa
siswa_1 = Siswa('Afif', "A.I.", 17, 'XII IPA')
siswa_2 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')
siswa_3 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')
siswa_4 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')
siswa_5 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')
siswa_6 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')
siswa_7 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')
#print(Siswa.jum_siswa)
|
normal
|
{
"blob_id": "bd2c327915c1e133a6e7b7a46290369440d50347",
"index": 3876,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsiswa_1 = Siswa('Afif', 'A.I.', 17, 'XII IPA')\nsiswa_2 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_3 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_4 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_5 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_6 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_7 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\n",
"step-3": "from kelas import Siswa\nsiswa_1 = Siswa('Afif', 'A.I.', 17, 'XII IPA')\nsiswa_2 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_3 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_4 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_5 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_6 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_7 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\n",
"step-4": "#import fungsi_saya as fs\n# from fungsi_saya import kalkulator as k\n\n# hasil = k(10,5,'+')\n# print(hasil)\n\nfrom kelas import Siswa\n\nsiswa_1 = Siswa('Afif', \"A.I.\", 17, 'XII IPA')\nsiswa_2 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_3 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_4 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_5 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_6 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\nsiswa_7 = Siswa('Bayu', 'Sudrajat', 20, 'XII IPS')\n#print(Siswa.jum_siswa)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
MusicDir = 'AudioFiles\\'
ModelsDir = 'Models\\'
MonstersDir = 'Models\\Monsters\\'
<|reserved_special_token_1|>
# Sets up directories
MusicDir = "AudioFiles\\"
ModelsDir = "Models\\"
MonstersDir = "Models\\Monsters\\"
|
flexible
|
{
"blob_id": "a929bfbe2be6d8f93cafa5b6cc66c7506037ffca",
"index": 4735,
"step-1": "<mask token>\n",
"step-2": "MusicDir = 'AudioFiles\\\\'\nModelsDir = 'Models\\\\'\nMonstersDir = 'Models\\\\Monsters\\\\'\n",
"step-3": "# Sets up directories\nMusicDir = \"AudioFiles\\\\\"\nModelsDir = \"Models\\\\\"\nMonstersDir = \"Models\\\\Monsters\\\\\"",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
@borg.on(admin_cmd(pattern='stupid$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
await event.edit('brain')
animation_chars = [
'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\x8f ðŸ§\xa0\n\nðŸ§\xa0 <(^_^ <)🗑'
,
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
<(^_^ <)🗑"""]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f'bombs$', outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
"""
)
await asyncio.sleep(1)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💥💥💥💥
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💥💥💥💥
💥💥💥💥
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
😵😵😵😵
"""
)
await asyncio.sleep(0.5)
await event.edit('`RIP PLOXXX......`')
await asyncio.sleep(2)
@borg.on(admin_cmd(pattern=f'kill$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.7
animation_ttl = range(0, 12)
await event.edit('ready to die dude.....')
animation_chars = ['Ｆｉｉｉｉｉｒｅ',
'(　･ิω･ิ)︻デâ•\x90一-->',
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\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0____'
, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',
"""`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`
'#Sad_Reacts_Online'
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern='ding$'))
async def _(event):
animation_interval = 0.3
animation_ttl = range(0, 30)
animation_chars = ['🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜',
"""⬜⬜⬛⬜⬜
⬜⬛⬜⬜⬜
🔴⬜⬜⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬛⬜⬜
⬜⬜🔴⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬜⬛⬜
⬜⬜⬜⬜🔴""",
"""⬜⬜⬛⬛🔴
⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬜⬛⬜
⬜⬜⬜⬜🔴""",
"""⬜⬜⬛⬜⬜
⬜⬜⬛⬜⬜
⬜⬜🔴⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬛⬜⬜⬜
🔴⬜⬜⬜⬜""",
"""🔴⬛⬛⬜⬜
⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜""",
"""⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜
⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜
⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜"""
]
if event.fwd_from:
return
await event.edit('ding..dong..ding..dong ...')
await asyncio.sleep(4)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern=f'hypno$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 15)
await event.edit('hypo....')
animation_chars = [
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬛⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬛⬛⬛⬜⬜
⬜⬜⬛⬜⬛⬜⬜
⬜⬜⬛⬛⬛⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛"""
,
"""⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬛
⬛⬜⬛⬜⬛
⬛⬜⬜⬜⬛
⬛⬛⬛⬛⬛"""
, """⬜⬜⬜
⬜⬛⬜
⬜⬜⬜""", '[👉🔴👈])']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 15])
@borg.on(admin_cmd(pattern='gangasta$'))
async def _(event):
await event.edit('EVERyBOdy')
await asyncio.sleep(0.3)
await event.edit('iZ')
await asyncio.sleep(0.2)
await event.edit('GangSTur')
await asyncio.sleep(0.5)
await event.edit('UNtIL ')
await asyncio.sleep(0.2)
await event.edit('I')
await asyncio.sleep(0.3)
await event.edit('ArRivE')
await asyncio.sleep(0.3)
await event.edit('🔥🔥🔥')
await asyncio.sleep(0.3)
await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')
@borg.on(admin_cmd(pattern=f'charging$'))
async def timer_blankx(e):
txt = e.text[10:] + """
`Tesla Wireless Charging (beta) Started...
Device Detected: Nokia 1100
Battery Percentage:` """
j = 10
k = j
for j in range(j):
await e.edit(txt + str(k))
k = k + 10
await asyncio.sleep(1)
await asyncio.sleep(1)
await e.edit(
"""`Tesla Wireless Charging (beta) Completed...
Device Detected: Nokia 1100 (Space Grey Varient)
Battery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) """
, link_preview=True)
@borg.on(admin_cmd('bigoof'))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 7)
await event.edit(
"""â”â”â”â”┓╋╋╋╋â”â”â”â”┓
┃â”â”┓┃╋╋╋╋┃â”â”┓┃
┃┃╋┃┣┓â”┓â”┫┃╋┃┃
┃┃╋┃┃┗┛┗┛┃┃╋┃┃
┃┗â”┛┣┓â”┓â”┫┗â”┛┃
â”—â”â”â”┛┗┛┗┛┗â”â”â”â”›"""
)
animation_chars = [
"""â•â”â”â”╮╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”╯╰╯ """
,
"""â•â”â”â”╮╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 7])
@borg.on(admin_cmd(pattern='g1 ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = (
"""{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}"""
.format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *
1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))
await event.edit(pay)
@borg.on(admin_cmd(pattern='uff ?(.*)'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',
'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',
'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern='ctext ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext *
8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,
paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8,
paytext * 8)
await event.edit(pay)
@borg.on(admin_cmd(pattern='ftext ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext *
8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,
paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2,
paytext * 2)
await event.edit(pay)
@borg.on(admin_cmd(outgoing=True, pattern='kf$(.*)'))
async def _(event):
r = random.randint(0, 3)
logger.debug(r)
if r == 0:
await event.edit(
"""â”â”â”â”┓
┃â”â”â”â”›
┃┗â”â”┓
┃â”â”â”â”›
┃┃
â”—â”›"""
)
else:
r == 1
await event.edit(
"""â•â”â”â”â•®
┃â•â”â”╯
┃╰â”â”â•®
┃â•â”â”╯
┃┃
╰╯"""
)
@borg.on(admin_cmd(pattern='f (.*)'))
async def payf(e):
paytext = e.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext * 5, paytext * 1,
paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)
await e.edit(pay)
@borg.on(admin_cmd(pattern=f'loading$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\xad', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'square$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['◧', '◨', '◧', '◨', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'up$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['╹', '╻', '╹', '╻', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'round$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['âš«', '⬤', 'â—\x8f', '∘', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'hart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 20)
animation_chars = ['🖤', 'â\x9d¤ï¸\x8f', '🖤', 'â\x9d¤ï¸\x8f', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'anim$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 11)
animation_chars = ['ðŸ˜\x81', '😧', '😡', '😢',
'‎**HellBoy Bolte Public**', 'ðŸ˜\x81', '😧', '😡', '😢',
'[PAPA HERE](https://t.me/Kraken_The_BadASS)',
'__**Good to See you Guys....**__']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'fnl$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = ['ðŸ˜\x81ðŸ\x8f¿', 'ðŸ˜\x81ðŸ\x8f¾', 'ðŸ˜\x81ðŸ\x8f½',
'ðŸ˜\x81ðŸ\x8f¼', '‎ðŸ˜\x81', '**Good to See you Guys....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'monkey$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = ['ðŸ\x90µ', '🙉', '🙈', '🙊',
'🖕‎ðŸ\x90µðŸ–•', '**Good to See you Guys....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'herber$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 11)
animation_chars = [
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 10%
â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 5.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.13GB
**🔹used:** 33.77GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 158.98GB
**🔹recv:** 146.27GB
**🔹sent_packets:** 84518799
**🔹recv_packets:** 159720314
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 30%
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 20.4%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 7.18GB
**🔹used:** 28.26GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 146.27GB
**🔹recv:** 124.33GB
**🔹sent_packets:** 54635686
**🔹recv_packets:** 143565654
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 60%
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 60.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 6.52GB
**🔹used:** 35.78GB
**🔹total:** 60.0GB
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 124.33GB
**🔹recv:** 162.48GB
**🔹sent_packets:** 25655655
**🔹recv_packets:** 165289456
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 100%
â—â—â—â—â—â—â—â—â—â—
**🔹cpu core**
**🔹core_usage:** 100.0%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 9.81GB
**🔹used:** 30.11GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 162.48GB
**🔹recv:** 175.75GB
**🔹sent_packets:** 56565435
**🔹recv_packets:** 135345655
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 70%
â—â—â—â—â—â—â—â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 80.4%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 5.76GB
**🔹used:** 29.35GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 175.75GB
**🔹recv:** 118.55GB
**🔹sent_packets:** 36547698
**🔹recv_packets:** 185466554
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 60%
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 62.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.23GB
**🔹used:** 33.32GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 118.55GB
**🔹recv:** 168.65GB
**🔹sent_packets:** 24786554
**🔹recv_packets:** 156745865
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 30%
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 30.6%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 9.75GB
**🔹used:** 36.54GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 168.65GB
**🔹recv:** 128.35GB
**🔹sent_packets:** 56565435
**🔹recv_packets:** 1475823589
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 10%
â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 10.2%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 10.20GB
**🔹used:** 25.40GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 128.35GB
**🔹recv:** 108.31GB
**🔹sent_packets:** 54635686
**🔹recv_packets:** 157865426
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 100%
â—â—â—â—â—â—â—â—â—â—
**🔹cpu core**
**🔹core_usage:** 100.0%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 5.25GB
**🔹used:** 31.14GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 108.31GB
**🔹recv:** 167.17GB
**🔹sent_packets:** 84518799
**🔹recv_packets:** 124575356
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 70%
â—â—â—â—â—â—â—â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 76.2%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.01GB
**🔹used:** 33.27GB
**🔹total:** 60.0GB
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 167.17GB
**🔹recv:** 158.98GB
**🔹sent_packets:** 36547698
**🔹recv_packets:** 165455856
**===================**
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'hand$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
animation_chars = ['👈', '👉', 'â˜\x9dï¸\x8f', '👆', '🖕',
'👇', '✌ï¸\x8f', '🤞', '🖖', '🤘', '🤙',
'ðŸ–\x90ï¸\x8f', '👌']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f'gsg$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = ['🔟', '9ï¸\x8f⃣', '8ï¸\x8f⃣', '7ï¸\x8f⃣',
'6ï¸\x8f⃣', '5ï¸\x8f⃣', '4ï¸\x8f⃣', '3ï¸\x8f⃣',
'2ï¸\x8f⃣', '1ï¸\x8f⃣', '0ï¸\x8f⃣', '🆘']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern='theart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 54)
animation_chars = ['â\x9d¤ï¸\x8f', '🧡', '💛', '💚', '💙',
'💜', '🖤', '💘', 'ðŸ’\x9d', 'â\x9d¤ï¸\x8f', '🧡', '💛',
'💚', '💙', '💜', '🖤', '💘', 'ðŸ’\x9d']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 18])
@borg.on(admin_cmd(pattern='fdance'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 5)
await event.edit('Connecting..')
animation_chars = [
"""⠀⠀⠀⣶⣿⣶
⠀⠀⠀⣿⣿⣿⣀
⠀⣀⣿⣿⣿⣿⣿⣿
⣶⣿⠛â£â£¿â£¿â£¿â£¿
⠛⠛⠛⣿⣿⣿⣿⠿
⠀⠀⠀⠀⣿⣿⣿
⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€
⠀⠤⣿⣿⣿⣿⣿⣿⠉
⠀⣿⣿⣿⣿⣿⣿⠉
⣿⣿⣿⣿⣿⣿
⣿⣿⣶⣿⣿
⠉⠛⣿⣿⣶⣤
⠀⠀⠉⠿⣿⣿⣤
⠀⠀⣀⣤⣿⣿⣿
⠀⠒⠿⠛⠉⠿⣿
⠀⠀⠀⠀⠀⣀⣿⣿
⠀⠀⠀⠀⣶⠿⠿⠛
"""
,
"""⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿
⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀
⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀
⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤
⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿
⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉
⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉
⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€
⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿
⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛
"""
,
"""⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶
⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶
⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤
⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀
⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿
⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶
⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒
⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰
⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›
⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£
⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤
⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿
⠀⠀⠀⠀⠀⠀⣿⠛
⠀⠀⠀⠀⠀⠀â£â£¶
"""
,
"""⠀⠀⠀⠀⠀⠀⣶⣿⣶
⠀⠀⠀⣤⣤⣤⣿⣿⣿
⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶
⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿
⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶
⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿
⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶
⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤
⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿
⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉
⠀⠀⠀⣿⣿⣿⣿⣿⣶
⠀⠀⠀⠀⣿⠉⠿⣿⣿
⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿
⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶
⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿
⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉
"""
,
"""⠀⠀⠀⠀⠀⠀⣤⣶⣶
⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀
⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿
⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿
⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿
⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤
⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿
⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿
⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛
⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀
⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿
⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿
⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿
⠀⠀⠀⠀⠀⠀⣀⣿⣿
⠀⠀⠀⠀⠤⣿⠿⠿⠿
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 5])
@borg.on(admin_cmd(pattern=f'snake$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 27)
await event.edit('snake..')
animation_chars = [
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 27])
@borg.on(admin_cmd(pattern=f'human$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
await event.edit('human...')
animation_chars = [
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛🚗
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛🚗⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛🚗⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛🚗⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛🚗⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛🚗⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
🚗⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜😊⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬛⬜⬛
⬛⬛⬜⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬛⬛⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬛😊⬛⬜⬛
⬛⬛⬜⬜⬜⬛⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬛⬛⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬛⬜⬜⬜⬛⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜😊⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=f'mc$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 28)
await event.edit('mc..')
animation_chars = [
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 28])
@borg.on(admin_cmd(pattern='virus$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 30)
await event.edit('Injecting virus....')
animation_chars = [
"""🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
, """â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸""",
"""â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸""", 'â—¼ï¸\x8f']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern='repe$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.2
animation_ttl = range(0, 30)
await event.edit('repe')
animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',
'**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',
'**rape_trai**', '**rape_train**', '**ape_train🚅**',
'**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',
'**_train🚅🚃🚃🚃🚃**',
'**train🚅🚃🚃🚃🚃🚃**',
'**rain🚅🚃🚃🚃🚃🚃🚃**',
'**ain🚅🚃🚃🚃🚃🚃🚃🚃**',
'**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',
'**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',
'🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=f'isro$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 24)
await event.edit('Connecting..')
animation_chars = [
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
🚀⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛🚀⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🚀⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🚀⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛🚀⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛🚀
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""🛸⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
🛸⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛🛸⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🛸⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🛸⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛"""
,
"""⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛🚶â€â™‚ï¸
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
👽⬛⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛👽⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛👽🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
, '__Signal Lost....__']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 24])
@borg.on(admin_cmd(pattern=f'nakal$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 6)
await event.edit('nakal')
animation_chars = [
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇
⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇
⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'music$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.5
animation_ttl = range(0, 11)
await event.edit('starting player...')
animation_chars = [
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'squ$', outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(6)
@borg.on(admin_cmd(pattern='star$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='boxs'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'rain$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🌬â˜\x81ï¸\x8f🌩🌨🌧🌦🌥⛅🌤'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='clol$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🤔ðŸ§\x90🤨🤔ðŸ§\x90🤨'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='odra$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🚶ðŸ\x8fƒðŸš¶ðŸ\x8fƒðŸš¶ðŸ\x8fƒðŸš¶ðŸ\x8fƒ'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='deploy$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 3
animation_ttl = range(0, 12)
await event.edit('Deploying...')
animation_chars = ['**Heroku Connecting To Latest Github Build **',
f'**Build started by user** @Kraken_The_BadASS',
f'**Deploy** `535a74f0` for user by my master!!',
'**Restarting Heroku Server...**',
'**State changed from up to starting**',
'**Stopping all processes with SIGTERM**',
'**Process exited with** `status 143`',
'**Starting process with command** `python3 -m stdborg`',
'**State changed from starting to up**',
'__INFO:Userbot:Logged in as 557667062__',
'__INFO:Userbot:Successfully loaded all plugins__',
'**Build Succeeded**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern='dump ?(.*)'))
async def _(message):
try:
obj = message.pattern_match.group(1)
if len(obj) != 3:
raise IndexError
inp = ' '.join(obj)
except IndexError:
inp = '🥞 🎂 ðŸ\x8d«'
u, t, g, o, s, n = inp.split(
), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\xa0€ ', '\n'
h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]
for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,
s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +
(o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),
o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i
] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(
''), g, t))] for i, f in enumerate(reversed(h)))]):
for something_else in something:
await asyncio.sleep(0.3)
try:
await message.edit(something_else)
except errors.MessageIdInvalidError:
return
@borg.on(admin_cmd(pattern='fleaveme$'))
async def _(event):
animation_interval = 1
animation_ttl = range(0, 10)
animation_chars = ['⬛⬛⬛\n⬛⬛⬛\n⬛⬛⬛',
'⬛⬛⬛\n⬛🔄⬛\n⬛⬛⬛',
"""⬛⬆ï¸â¬›
⬛🔄⬛
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄⬛
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬛↘ï¸""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬇ï¸â†˜ï¸""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
↙ï¸â¬‡ï¸â†˜ï¸""",
"""⬛⬆ï¸â†—ï¸
⬅ï¸ðŸ”„âž¡ï¸
↙ï¸â¬‡ï¸â†˜ï¸""",
"""↖ï¸â¬†ï¸â†—ï¸
⬅ï¸ðŸ”„âž¡ï¸
↙ï¸â¬‡ï¸â†˜ï¸"""]
if event.fwd_from:
return
await event.edit('fleaveme....')
await asyncio.sleep(2)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern='loveu', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 70)
await event.edit('loveu')
animation_chars = ['😀', '👩â€\x8d🎨', 'ðŸ˜\x81', '😂', '🤣',
'😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',
'ðŸ˜\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\x90',
'😯', '😴', '😔', '😕', '☹', 'ðŸ™\x81', '😖', '😞',
'😟', '😢', 'ðŸ˜\xad', '🤯', '💔', 'â\x9d¤', 'i Love Youâ\x9d¤'
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 35])
@borg.on(admin_cmd(pattern=f'plane', outgoing=True))
async def _(event):
if event.fwd_from:
retun
await event.edit('✈-------------')
await event.edit('-✈------------')
await event.edit('--✈-----------')
await event.edit('---✈----------')
await event.edit('----✈---------')
await event.edit('-----✈--------')
await event.edit('------✈-------')
await event.edit('-------✈------')
await event.edit('--------✈-----')
await event.edit('---------✈----')
await event.edit('----------✈---')
await event.edit('-----------✈--')
await event.edit('------------✈-')
await event.edit('-------------✈')
await asyncio.sleep(3)
await event.delete()
@borg.on(admin_cmd(pattern='pulis'))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 12)
await event.edit('Pulis')
animation_chars = [
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
, f'{DEFAULTUSER} **Police iz Here**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern=f'jio$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 19)
await event.edit('jio network boosting...')
animation_chars = ['`Connecting To JIO NETWORK ....`',
'`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–‡ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–’ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–’ â–’ â–\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',
'*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–’ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–‡ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 19])
@borg.on(admin_cmd(pattern=f'solarsystem', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 80)
await event.edit('solarsystem')
animation_chars = [
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern='lul$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('😂🤣😂🤣😂🤣'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='nothappy$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('ðŸ˜\x81☹ï¸\x8fðŸ˜\x81☹ï¸\x8fðŸ˜\x81☹ï¸\x8fðŸ˜\x81')
)
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern='clock$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\x90🕛'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='muah$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('😗😙😚😚😘'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='heart$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('â\x9d¤ï¸\x8f🧡💛💚💙💜🖤'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='gym$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list(
'ðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8dðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8dðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8d'
))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'earth$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('ðŸŒ\x8fðŸŒ\x8d🌎🌎ðŸŒ\x8dðŸŒ\x8fðŸŒ\x8d🌎'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern='moon$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='candy$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list(
'ðŸ\x8d¦ðŸ\x8d§ðŸ\x8d©ðŸ\x8dªðŸŽ‚ðŸ\x8d°ðŸ§\x81ðŸ\x8d«ðŸ\x8d¬ðŸ\x8d\xad'
))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'smoon$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 101)
await event.edit('smoon..')
animation_chars = [
"""🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗"""
,
"""🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘"""
,
"""🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑"""
,
"""🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒"""
,
"""🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓"""
,
"""🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔"""
,
"""🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕"""
,
"""🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=f'tmoon$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 117)
await event.edit('tmoon')
animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 32])
@borg.on(admin_cmd(pattern=f'clown$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\x8f',
'🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',
'🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',
'🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',
'🤡🤡', '🤡', 'You', 'You Are', 'You Are A',
'You Are A Clown 🤡']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern='aheart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.3
animation_ttl = range(0, 50)
animation_chars = ['â\x9d¤ï¸\x8f', '🧡', '💛', '💚', '💙',
'💜', '🖤', '💘', 'ðŸ’\x9d', '💔', 'â\x9d¤ï¸\x8f', '🧡',
'💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\x9d', '💔']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 20])
<|reserved_special_token_1|>
<|reserved_special_token_0|>
DEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else 'Cat'
@borg.on(admin_cmd(pattern='stupid$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
await event.edit('brain')
animation_chars = [
'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\x8f ðŸ§\xa0\n\nðŸ§\xa0 <(^_^ <)🗑'
,
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
<(^_^ <)🗑"""]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f'bombs$', outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
"""
)
await asyncio.sleep(1)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💥💥💥💥
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💥💥💥💥
💥💥💥💥
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
😵😵😵😵
"""
)
await asyncio.sleep(0.5)
await event.edit('`RIP PLOXXX......`')
await asyncio.sleep(2)
@borg.on(admin_cmd(pattern=f'kill$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.7
animation_ttl = range(0, 12)
await event.edit('ready to die dude.....')
animation_chars = ['Ｆｉｉｉｉｉｒｅ',
'(　･ิω･ิ)︻デâ•\x90一-->',
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\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0____'
, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',
"""`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`
'#Sad_Reacts_Online'
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern='ding$'))
async def _(event):
animation_interval = 0.3
animation_ttl = range(0, 30)
animation_chars = ['🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜',
"""⬜⬜⬛⬜⬜
⬜⬛⬜⬜⬜
🔴⬜⬜⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬛⬜⬜
⬜⬜🔴⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬜⬛⬜
⬜⬜⬜⬜🔴""",
"""⬜⬜⬛⬛🔴
⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬜⬛⬜
⬜⬜⬜⬜🔴""",
"""⬜⬜⬛⬜⬜
⬜⬜⬛⬜⬜
⬜⬜🔴⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬛⬜⬜⬜
🔴⬜⬜⬜⬜""",
"""🔴⬛⬛⬜⬜
⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜""",
"""⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜
⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜
⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜"""
]
if event.fwd_from:
return
await event.edit('ding..dong..ding..dong ...')
await asyncio.sleep(4)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern=f'hypno$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 15)
await event.edit('hypo....')
animation_chars = [
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬛⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬛⬛⬛⬜⬜
⬜⬜⬛⬜⬛⬜⬜
⬜⬜⬛⬛⬛⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛"""
,
"""⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬛
⬛⬜⬛⬜⬛
⬛⬜⬜⬜⬛
⬛⬛⬛⬛⬛"""
, """⬜⬜⬜
⬜⬛⬜
⬜⬜⬜""", '[👉🔴👈])']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 15])
@borg.on(admin_cmd(pattern='gangasta$'))
async def _(event):
await event.edit('EVERyBOdy')
await asyncio.sleep(0.3)
await event.edit('iZ')
await asyncio.sleep(0.2)
await event.edit('GangSTur')
await asyncio.sleep(0.5)
await event.edit('UNtIL ')
await asyncio.sleep(0.2)
await event.edit('I')
await asyncio.sleep(0.3)
await event.edit('ArRivE')
await asyncio.sleep(0.3)
await event.edit('🔥🔥🔥')
await asyncio.sleep(0.3)
await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')
@borg.on(admin_cmd(pattern=f'charging$'))
async def timer_blankx(e):
txt = e.text[10:] + """
`Tesla Wireless Charging (beta) Started...
Device Detected: Nokia 1100
Battery Percentage:` """
j = 10
k = j
for j in range(j):
await e.edit(txt + str(k))
k = k + 10
await asyncio.sleep(1)
await asyncio.sleep(1)
await e.edit(
"""`Tesla Wireless Charging (beta) Completed...
Device Detected: Nokia 1100 (Space Grey Varient)
Battery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) """
, link_preview=True)
@borg.on(admin_cmd('bigoof'))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 7)
await event.edit(
"""â”â”â”â”┓╋╋╋╋â”â”â”â”┓
┃â”â”┓┃╋╋╋╋┃â”â”┓┃
┃┃╋┃┣┓â”┓â”┫┃╋┃┃
┃┃╋┃┃┗┛┗┛┃┃╋┃┃
┃┗â”┛┣┓â”┓â”┫┗â”┛┃
â”—â”â”â”┛┗┛┗┛┗â”â”â”â”›"""
)
animation_chars = [
"""â•â”â”â”╮╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”╯╰╯ """
,
"""â•â”â”â”╮╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 7])
@borg.on(admin_cmd(pattern='g1 ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = (
"""{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}"""
.format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *
1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))
await event.edit(pay)
@borg.on(admin_cmd(pattern='uff ?(.*)'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',
'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',
'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern='ctext ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext *
8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,
paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8,
paytext * 8)
await event.edit(pay)
@borg.on(admin_cmd(pattern='ftext ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext *
8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,
paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2,
paytext * 2)
await event.edit(pay)
@borg.on(admin_cmd(outgoing=True, pattern='kf$(.*)'))
async def _(event):
r = random.randint(0, 3)
logger.debug(r)
if r == 0:
await event.edit(
"""â”â”â”â”┓
┃â”â”â”â”›
┃┗â”â”┓
┃â”â”â”â”›
┃┃
â”—â”›"""
)
else:
r == 1
await event.edit(
"""â•â”â”â”â•®
┃â•â”â”╯
┃╰â”â”â•®
┃â•â”â”╯
┃┃
╰╯"""
)
@borg.on(admin_cmd(pattern='f (.*)'))
async def payf(e):
paytext = e.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext * 5, paytext * 1,
paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)
await e.edit(pay)
@borg.on(admin_cmd(pattern=f'loading$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\xad', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'square$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['◧', '◨', '◧', '◨', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'up$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['╹', '╻', '╹', '╻', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'round$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['âš«', '⬤', 'â—\x8f', '∘', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'hart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 20)
animation_chars = ['🖤', 'â\x9d¤ï¸\x8f', '🖤', 'â\x9d¤ï¸\x8f', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'anim$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 11)
animation_chars = ['ðŸ˜\x81', '😧', '😡', '😢',
'‎**HellBoy Bolte Public**', 'ðŸ˜\x81', '😧', '😡', '😢',
'[PAPA HERE](https://t.me/Kraken_The_BadASS)',
'__**Good to See you Guys....**__']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'fnl$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = ['ðŸ˜\x81ðŸ\x8f¿', 'ðŸ˜\x81ðŸ\x8f¾', 'ðŸ˜\x81ðŸ\x8f½',
'ðŸ˜\x81ðŸ\x8f¼', '‎ðŸ˜\x81', '**Good to See you Guys....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'monkey$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = ['ðŸ\x90µ', '🙉', '🙈', '🙊',
'🖕‎ðŸ\x90µðŸ–•', '**Good to See you Guys....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'herber$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 11)
animation_chars = [
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 10%
â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 5.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.13GB
**🔹used:** 33.77GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 158.98GB
**🔹recv:** 146.27GB
**🔹sent_packets:** 84518799
**🔹recv_packets:** 159720314
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 30%
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 20.4%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 7.18GB
**🔹used:** 28.26GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 146.27GB
**🔹recv:** 124.33GB
**🔹sent_packets:** 54635686
**🔹recv_packets:** 143565654
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 60%
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 60.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 6.52GB
**🔹used:** 35.78GB
**🔹total:** 60.0GB
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 124.33GB
**🔹recv:** 162.48GB
**🔹sent_packets:** 25655655
**🔹recv_packets:** 165289456
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 100%
â—â—â—â—â—â—â—â—â—â—
**🔹cpu core**
**🔹core_usage:** 100.0%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 9.81GB
**🔹used:** 30.11GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 162.48GB
**🔹recv:** 175.75GB
**🔹sent_packets:** 56565435
**🔹recv_packets:** 135345655
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 70%
â—â—â—â—â—â—â—â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 80.4%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 5.76GB
**🔹used:** 29.35GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 175.75GB
**🔹recv:** 118.55GB
**🔹sent_packets:** 36547698
**🔹recv_packets:** 185466554
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 60%
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 62.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.23GB
**🔹used:** 33.32GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 118.55GB
**🔹recv:** 168.65GB
**🔹sent_packets:** 24786554
**🔹recv_packets:** 156745865
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 30%
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 30.6%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 9.75GB
**🔹used:** 36.54GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 168.65GB
**🔹recv:** 128.35GB
**🔹sent_packets:** 56565435
**🔹recv_packets:** 1475823589
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 10%
â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 10.2%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 10.20GB
**🔹used:** 25.40GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 128.35GB
**🔹recv:** 108.31GB
**🔹sent_packets:** 54635686
**🔹recv_packets:** 157865426
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 100%
â—â—â—â—â—â—â—â—â—â—
**🔹cpu core**
**🔹core_usage:** 100.0%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 5.25GB
**🔹used:** 31.14GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 108.31GB
**🔹recv:** 167.17GB
**🔹sent_packets:** 84518799
**🔹recv_packets:** 124575356
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 70%
â—â—â—â—â—â—â—â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 76.2%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.01GB
**🔹used:** 33.27GB
**🔹total:** 60.0GB
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 167.17GB
**🔹recv:** 158.98GB
**🔹sent_packets:** 36547698
**🔹recv_packets:** 165455856
**===================**
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'hand$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
animation_chars = ['👈', '👉', 'â˜\x9dï¸\x8f', '👆', '🖕',
'👇', '✌ï¸\x8f', '🤞', '🖖', '🤘', '🤙',
'ðŸ–\x90ï¸\x8f', '👌']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f'gsg$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = ['🔟', '9ï¸\x8f⃣', '8ï¸\x8f⃣', '7ï¸\x8f⃣',
'6ï¸\x8f⃣', '5ï¸\x8f⃣', '4ï¸\x8f⃣', '3ï¸\x8f⃣',
'2ï¸\x8f⃣', '1ï¸\x8f⃣', '0ï¸\x8f⃣', '🆘']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern='theart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 54)
animation_chars = ['â\x9d¤ï¸\x8f', '🧡', '💛', '💚', '💙',
'💜', '🖤', '💘', 'ðŸ’\x9d', 'â\x9d¤ï¸\x8f', '🧡', '💛',
'💚', '💙', '💜', '🖤', '💘', 'ðŸ’\x9d']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 18])
@borg.on(admin_cmd(pattern='fdance'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 5)
await event.edit('Connecting..')
animation_chars = [
"""⠀⠀⠀⣶⣿⣶
⠀⠀⠀⣿⣿⣿⣀
⠀⣀⣿⣿⣿⣿⣿⣿
⣶⣿⠛â£â£¿â£¿â£¿â£¿
⠛⠛⠛⣿⣿⣿⣿⠿
⠀⠀⠀⠀⣿⣿⣿
⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€
⠀⠤⣿⣿⣿⣿⣿⣿⠉
⠀⣿⣿⣿⣿⣿⣿⠉
⣿⣿⣿⣿⣿⣿
⣿⣿⣶⣿⣿
⠉⠛⣿⣿⣶⣤
⠀⠀⠉⠿⣿⣿⣤
⠀⠀⣀⣤⣿⣿⣿
⠀⠒⠿⠛⠉⠿⣿
⠀⠀⠀⠀⠀⣀⣿⣿
⠀⠀⠀⠀⣶⠿⠿⠛
"""
,
"""⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿
⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀
⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀
⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤
⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿
⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉
⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉
⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€
⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿
⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛
"""
,
"""⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶
⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶
⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤
⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀
⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿
⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶
⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒
⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰
⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›
⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£
⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤
⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿
⠀⠀⠀⠀⠀⠀⣿⠛
⠀⠀⠀⠀⠀⠀â£â£¶
"""
,
"""⠀⠀⠀⠀⠀⠀⣶⣿⣶
⠀⠀⠀⣤⣤⣤⣿⣿⣿
⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶
⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿
⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶
⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿
⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶
⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤
⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿
⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉
⠀⠀⠀⣿⣿⣿⣿⣿⣶
⠀⠀⠀⠀⣿⠉⠿⣿⣿
⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿
⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶
⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿
⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉
"""
,
"""⠀⠀⠀⠀⠀⠀⣤⣶⣶
⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀
⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿
⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿
⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿
⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤
⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿
⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿
⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛
⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀
⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿
⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿
⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿
⠀⠀⠀⠀⠀⠀⣀⣿⣿
⠀⠀⠀⠀⠤⣿⠿⠿⠿
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 5])
@borg.on(admin_cmd(pattern=f'snake$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 27)
await event.edit('snake..')
animation_chars = [
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 27])
@borg.on(admin_cmd(pattern=f'human$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
await event.edit('human...')
animation_chars = [
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛🚗
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛🚗⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛🚗⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛🚗⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛🚗⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛🚗⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
🚗⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜😊⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬛⬜⬛
⬛⬛⬜⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬛⬛⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬛😊⬛⬜⬛
⬛⬛⬜⬜⬜⬛⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬛⬛⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬛⬜⬜⬜⬛⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜😊⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=f'mc$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 28)
await event.edit('mc..')
animation_chars = [
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 28])
@borg.on(admin_cmd(pattern='virus$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 30)
await event.edit('Injecting virus....')
animation_chars = [
"""🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
, """â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸""",
"""â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸""", 'â—¼ï¸\x8f']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern='repe$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.2
animation_ttl = range(0, 30)
await event.edit('repe')
animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',
'**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',
'**rape_trai**', '**rape_train**', '**ape_train🚅**',
'**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',
'**_train🚅🚃🚃🚃🚃**',
'**train🚅🚃🚃🚃🚃🚃**',
'**rain🚅🚃🚃🚃🚃🚃🚃**',
'**ain🚅🚃🚃🚃🚃🚃🚃🚃**',
'**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',
'**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',
'🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=f'isro$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 24)
await event.edit('Connecting..')
animation_chars = [
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
🚀⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛🚀⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🚀⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🚀⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛🚀⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛🚀
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""🛸⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
🛸⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛🛸⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🛸⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🛸⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛"""
,
"""⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛🚶â€â™‚ï¸
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
👽⬛⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛👽⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛👽🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
, '__Signal Lost....__']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 24])
@borg.on(admin_cmd(pattern=f'nakal$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 6)
await event.edit('nakal')
animation_chars = [
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇
⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇
⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'music$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.5
animation_ttl = range(0, 11)
await event.edit('starting player...')
animation_chars = [
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'squ$', outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(6)
@borg.on(admin_cmd(pattern='star$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='boxs'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'rain$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🌬â˜\x81ï¸\x8f🌩🌨🌧🌦🌥⛅🌤'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='clol$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🤔ðŸ§\x90🤨🤔ðŸ§\x90🤨'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='odra$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🚶ðŸ\x8fƒðŸš¶ðŸ\x8fƒðŸš¶ðŸ\x8fƒðŸš¶ðŸ\x8fƒ'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='deploy$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 3
animation_ttl = range(0, 12)
await event.edit('Deploying...')
animation_chars = ['**Heroku Connecting To Latest Github Build **',
f'**Build started by user** @Kraken_The_BadASS',
f'**Deploy** `535a74f0` for user by my master!!',
'**Restarting Heroku Server...**',
'**State changed from up to starting**',
'**Stopping all processes with SIGTERM**',
'**Process exited with** `status 143`',
'**Starting process with command** `python3 -m stdborg`',
'**State changed from starting to up**',
'__INFO:Userbot:Logged in as 557667062__',
'__INFO:Userbot:Successfully loaded all plugins__',
'**Build Succeeded**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern='dump ?(.*)'))
async def _(message):
try:
obj = message.pattern_match.group(1)
if len(obj) != 3:
raise IndexError
inp = ' '.join(obj)
except IndexError:
inp = '🥞 🎂 ðŸ\x8d«'
u, t, g, o, s, n = inp.split(
), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\xa0€ ', '\n'
h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]
for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,
s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +
(o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),
o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i
] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(
''), g, t))] for i, f in enumerate(reversed(h)))]):
for something_else in something:
await asyncio.sleep(0.3)
try:
await message.edit(something_else)
except errors.MessageIdInvalidError:
return
@borg.on(admin_cmd(pattern='fleaveme$'))
async def _(event):
animation_interval = 1
animation_ttl = range(0, 10)
animation_chars = ['⬛⬛⬛\n⬛⬛⬛\n⬛⬛⬛',
'⬛⬛⬛\n⬛🔄⬛\n⬛⬛⬛',
"""⬛⬆ï¸â¬›
⬛🔄⬛
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄⬛
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬛↘ï¸""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬇ï¸â†˜ï¸""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
↙ï¸â¬‡ï¸â†˜ï¸""",
"""⬛⬆ï¸â†—ï¸
⬅ï¸ðŸ”„âž¡ï¸
↙ï¸â¬‡ï¸â†˜ï¸""",
"""↖ï¸â¬†ï¸â†—ï¸
⬅ï¸ðŸ”„âž¡ï¸
↙ï¸â¬‡ï¸â†˜ï¸"""]
if event.fwd_from:
return
await event.edit('fleaveme....')
await asyncio.sleep(2)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern='loveu', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 70)
await event.edit('loveu')
animation_chars = ['😀', '👩â€\x8d🎨', 'ðŸ˜\x81', '😂', '🤣',
'😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',
'ðŸ˜\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\x90',
'😯', '😴', '😔', '😕', '☹', 'ðŸ™\x81', '😖', '😞',
'😟', '😢', 'ðŸ˜\xad', '🤯', '💔', 'â\x9d¤', 'i Love Youâ\x9d¤'
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 35])
@borg.on(admin_cmd(pattern=f'plane', outgoing=True))
async def _(event):
if event.fwd_from:
retun
await event.edit('✈-------------')
await event.edit('-✈------------')
await event.edit('--✈-----------')
await event.edit('---✈----------')
await event.edit('----✈---------')
await event.edit('-----✈--------')
await event.edit('------✈-------')
await event.edit('-------✈------')
await event.edit('--------✈-----')
await event.edit('---------✈----')
await event.edit('----------✈---')
await event.edit('-----------✈--')
await event.edit('------------✈-')
await event.edit('-------------✈')
await asyncio.sleep(3)
await event.delete()
@borg.on(admin_cmd(pattern='pulis'))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 12)
await event.edit('Pulis')
animation_chars = [
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
, f'{DEFAULTUSER} **Police iz Here**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern=f'jio$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 19)
await event.edit('jio network boosting...')
animation_chars = ['`Connecting To JIO NETWORK ....`',
'`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–‡ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–’ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–’ â–’ â–\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',
'*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–’ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–‡ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 19])
@borg.on(admin_cmd(pattern=f'solarsystem', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 80)
await event.edit('solarsystem')
animation_chars = [
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern='lul$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('😂🤣😂🤣😂🤣'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='nothappy$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('ðŸ˜\x81☹ï¸\x8fðŸ˜\x81☹ï¸\x8fðŸ˜\x81☹ï¸\x8fðŸ˜\x81')
)
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern='clock$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\x90🕛'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='muah$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('😗😙😚😚😘'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='heart$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('â\x9d¤ï¸\x8f🧡💛💚💙💜🖤'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='gym$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list(
'ðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8dðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8dðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8d'
))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'earth$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('ðŸŒ\x8fðŸŒ\x8d🌎🌎ðŸŒ\x8dðŸŒ\x8fðŸŒ\x8d🌎'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern='moon$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='candy$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list(
'ðŸ\x8d¦ðŸ\x8d§ðŸ\x8d©ðŸ\x8dªðŸŽ‚ðŸ\x8d°ðŸ§\x81ðŸ\x8d«ðŸ\x8d¬ðŸ\x8d\xad'
))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'smoon$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 101)
await event.edit('smoon..')
animation_chars = [
"""🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗"""
,
"""🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘"""
,
"""🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑"""
,
"""🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒"""
,
"""🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓"""
,
"""🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔"""
,
"""🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕"""
,
"""🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=f'tmoon$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 117)
await event.edit('tmoon')
animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 32])
@borg.on(admin_cmd(pattern=f'clown$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\x8f',
'🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',
'🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',
'🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',
'🤡🤡', '🤡', 'You', 'You Are', 'You Are A',
'You Are A Clown 🤡']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern='aheart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.3
animation_ttl = range(0, 50)
animation_chars = ['â\x9d¤ï¸\x8f', '🧡', '💛', '💚', '💙',
'💜', '🖤', '💘', 'ðŸ’\x9d', '💔', 'â\x9d¤ï¸\x8f', '🧡',
'💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\x9d', '💔']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 20])
<|reserved_special_token_1|>
import os
import sys
import logging
from telethon import events
import asyncio
from userbot.utils import admin_cmd
from userbot import ALIVE_NAME
import random, re
from userbot import CMD_HELP
from collections import deque
import importlib.util
import random
DEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else 'Cat'
@borg.on(admin_cmd(pattern='stupid$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
await event.edit('brain')
animation_chars = [
'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\x8f ðŸ§\xa0\n\nðŸ§\xa0 <(^_^ <)🗑'
,
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
🧠<(^_^ <) 🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🧠🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
(> ^_^)>🗑""",
"""YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§
<(^_^ <)🗑"""]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f'bombs$', outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💣💣💣💣
"""
)
await asyncio.sleep(1)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💥💥💥💥
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
💥💥💥💥
💥💥💥💥
"""
)
await asyncio.sleep(0.5)
await event.edit(
"""â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
â–ªï¸â–ªï¸â–ªï¸â–ªï¸
😵😵😵😵
"""
)
await asyncio.sleep(0.5)
await event.edit('`RIP PLOXXX......`')
await asyncio.sleep(2)
@borg.on(admin_cmd(pattern=f'kill$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.7
animation_ttl = range(0, 12)
await event.edit('ready to die dude.....')
animation_chars = ['Ｆｉｉｉｉｉｒｅ',
'(　･ิω･ิ)︻デâ•\x90一-->',
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\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0â\x81\xa0____'
, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',
"""`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`
'#Sad_Reacts_Online'
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern='ding$'))
async def _(event):
animation_interval = 0.3
animation_ttl = range(0, 30)
animation_chars = ['🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜',
"""⬜⬜⬛⬜⬜
⬜⬛⬜⬜⬜
🔴⬜⬜⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬛⬜⬜
⬜⬜🔴⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬜⬛⬜
⬜⬜⬜⬜🔴""",
"""⬜⬜⬛⬛🔴
⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬜⬜⬛⬜
⬜⬜⬜⬜🔴""",
"""⬜⬜⬛⬜⬜
⬜⬜⬛⬜⬜
⬜⬜🔴⬜⬜""",
"""⬜⬜⬛⬜⬜
⬜⬛⬜⬜⬜
🔴⬜⬜⬜⬜""",
"""🔴⬛⬛⬜⬜
⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜""",
"""⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜
⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜
⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜"""
]
if event.fwd_from:
return
await event.edit('ding..dong..ding..dong ...')
await asyncio.sleep(4)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern=f'hypno$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 15)
await event.edit('hypo....')
animation_chars = [
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬛⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬛⬛⬛⬜⬜
⬜⬜⬛⬜⬛⬜⬜
⬜⬜⬛⬛⬛⬜⬜
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛"""
,
"""⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛⬜"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬛⬛⬛⬛"""
,
"""⬜⬜⬜⬜⬜⬜⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬜⬛⬜⬛⬜
⬜⬛⬜⬜⬜⬛⬜
⬜⬛⬛⬛⬛⬛⬜
⬜⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛
⬛⬜⬜⬜⬛
⬛⬜⬛⬜⬛
⬛⬜⬜⬜⬛
⬛⬛⬛⬛⬛"""
, """⬜⬜⬜
⬜⬛⬜
⬜⬜⬜""", '[👉🔴👈])']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 15])
@borg.on(admin_cmd(pattern='gangasta$'))
async def _(event):
await event.edit('EVERyBOdy')
await asyncio.sleep(0.3)
await event.edit('iZ')
await asyncio.sleep(0.2)
await event.edit('GangSTur')
await asyncio.sleep(0.5)
await event.edit('UNtIL ')
await asyncio.sleep(0.2)
await event.edit('I')
await asyncio.sleep(0.3)
await event.edit('ArRivE')
await asyncio.sleep(0.3)
await event.edit('🔥🔥🔥')
await asyncio.sleep(0.3)
await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')
@borg.on(admin_cmd(pattern=f'charging$'))
async def timer_blankx(e):
txt = e.text[10:] + """
`Tesla Wireless Charging (beta) Started...
Device Detected: Nokia 1100
Battery Percentage:` """
j = 10
k = j
for j in range(j):
await e.edit(txt + str(k))
k = k + 10
await asyncio.sleep(1)
await asyncio.sleep(1)
await e.edit(
"""`Tesla Wireless Charging (beta) Completed...
Device Detected: Nokia 1100 (Space Grey Varient)
Battery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) """
, link_preview=True)
@borg.on(admin_cmd('bigoof'))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 7)
await event.edit(
"""â”â”â”â”┓╋╋╋╋â”â”â”â”┓
┃â”â”┓┃╋╋╋╋┃â”â”┓┃
┃┃╋┃┣┓â”┓â”┫┃╋┃┃
┃┃╋┃┃┗┛┗┛┃┃╋┃┃
┃┗â”┛┣┓â”┓â”┫┗â”┛┃
â”—â”â”â”┛┗┛┗┛┗â”â”â”â”›"""
)
animation_chars = [
"""â•â”â”â”╮╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”╯╰╯ """
,
"""â•â”â”â”╮╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
,
"""â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•®
┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯
┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮
┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯
┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃
â•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 7])
@borg.on(admin_cmd(pattern='g1 ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = (
"""{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}
{}"""
.format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *
1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,
paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))
await event.edit(pay)
@borg.on(admin_cmd(pattern='uff ?(.*)'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',
'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',
'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern='ctext ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext *
8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,
paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8,
paytext * 8)
await event.edit(pay)
@borg.on(admin_cmd(pattern='ftext ?(.*)'))
async def payf(event):
paytext = event.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext *
8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,
paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2,
paytext * 2)
await event.edit(pay)
@borg.on(admin_cmd(outgoing=True, pattern='kf$(.*)'))
async def _(event):
r = random.randint(0, 3)
logger.debug(r)
if r == 0:
await event.edit(
"""â”â”â”â”┓
┃â”â”â”â”›
┃┗â”â”┓
┃â”â”â”â”›
┃┃
â”—â”›"""
)
else:
r == 1
await event.edit(
"""â•â”â”â”â•®
┃â•â”â”╯
┃╰â”â”â•®
┃â•â”â”╯
┃┃
╰╯"""
)
@borg.on(admin_cmd(pattern='f (.*)'))
async def payf(e):
paytext = e.pattern_match.group(1)
pay = '{}\n{}\n{}\n{}\n{}\n{}\n{}'.format(paytext * 5, paytext * 1,
paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)
await e.edit(pay)
@borg.on(admin_cmd(pattern=f'loading$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\xad', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'square$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['◧', '◨', '◧', '◨', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'up$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['╹', '╻', '╹', '╻', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'round$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = ['âš«', '⬤', 'â—\x8f', '∘', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'hart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 20)
animation_chars = ['🖤', 'â\x9d¤ï¸\x8f', '🖤', 'â\x9d¤ï¸\x8f', '‎']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f'anim$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 11)
animation_chars = ['ðŸ˜\x81', '😧', '😡', '😢',
'‎**HellBoy Bolte Public**', 'ðŸ˜\x81', '😧', '😡', '😢',
'[PAPA HERE](https://t.me/Kraken_The_BadASS)',
'__**Good to See you Guys....**__']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'fnl$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = ['ðŸ˜\x81ðŸ\x8f¿', 'ðŸ˜\x81ðŸ\x8f¾', 'ðŸ˜\x81ðŸ\x8f½',
'ðŸ˜\x81ðŸ\x8f¼', '‎ðŸ˜\x81', '**Good to See you Guys....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'monkey$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = ['ðŸ\x90µ', '🙉', '🙈', '🙊',
'🖕‎ðŸ\x90µðŸ–•', '**Good to See you Guys....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'herber$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 11)
animation_chars = [
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 10%
â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 5.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.13GB
**🔹used:** 33.77GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 158.98GB
**🔹recv:** 146.27GB
**🔹sent_packets:** 84518799
**🔹recv_packets:** 159720314
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 30%
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 20.4%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 7.18GB
**🔹used:** 28.26GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 146.27GB
**🔹recv:** 124.33GB
**🔹sent_packets:** 54635686
**🔹recv_packets:** 143565654
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 60%
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 60.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 6.52GB
**🔹used:** 35.78GB
**🔹total:** 60.0GB
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 124.33GB
**🔹recv:** 162.48GB
**🔹sent_packets:** 25655655
**🔹recv_packets:** 165289456
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 100%
â—â—â—â—â—â—â—â—â—â—
**🔹cpu core**
**🔹core_usage:** 100.0%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 9.81GB
**🔹used:** 30.11GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 162.48GB
**🔹recv:** 175.75GB
**🔹sent_packets:** 56565435
**🔹recv_packets:** 135345655
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 70%
â—â—â—â—â—â—â—â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 80.4%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 5.76GB
**🔹used:** 29.35GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 175.75GB
**🔹recv:** 118.55GB
**🔹sent_packets:** 36547698
**🔹recv_packets:** 185466554
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 60%
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 62.9%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.23GB
**🔹used:** 33.32GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 118.55GB
**🔹recv:** 168.65GB
**🔹sent_packets:** 24786554
**🔹recv_packets:** 156745865
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 30%
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 30.6%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 9.75GB
**🔹used:** 36.54GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 168.65GB
**🔹recv:** 128.35GB
**🔹sent_packets:** 56565435
**🔹recv_packets:** 1475823589
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 10%
â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 10.2%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 10.20GB
**🔹used:** 25.40GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 128.35GB
**🔹recv:** 108.31GB
**🔹sent_packets:** 54635686
**🔹recv_packets:** 157865426
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 100%
â—â—â—â—â—â—â—â—â—â—
**🔹cpu core**
**🔹core_usage:** 100.0%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 5.25GB
**🔹used:** 31.14GB
**🔹total:** 60.0GB
â—â—â—â—â—â—â—â—â—â—
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 108.31GB
**🔹recv:** 167.17GB
**🔹sent_packets:** 84518799
**🔹recv_packets:** 124575356
**===================**
"""
,
"""**===================**
**Server Details**
**===================**
**=>>> CPU <<<=**
**🔹current_freq:** 2500.09MHz
**🔹total_usage:** 70%
â—â—â—â—â—â—â—â—‹â—‹â—‹
**🔹cpu core**
**🔹core_usage:** 76.2%
**🔹current_freq:** 2500.09MHz
|██████████▉ |
**=>>> RAM <<<=**
**🔹free:** 8.01GB
**🔹used:** 33.27GB
**🔹total:** 60.0GB
â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹
**=>>> DISK <<<=**
**🔹free:** 224.12GB
**🔹used:** 131.84GB
**🔹total:** 375.02GB
**🔹usage:** 37.0%
|████■|
**=>>> NETWORK <<<=**
**🔹sent:** 167.17GB
**🔹recv:** 158.98GB
**🔹sent_packets:** 36547698
**🔹recv_packets:** 165455856
**===================**
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'hand$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
animation_chars = ['👈', '👉', 'â˜\x9dï¸\x8f', '👆', '🖕',
'👇', '✌ï¸\x8f', '🤞', '🖖', '🤘', '🤙',
'ðŸ–\x90ï¸\x8f', '👌']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f'gsg$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = ['🔟', '9ï¸\x8f⃣', '8ï¸\x8f⃣', '7ï¸\x8f⃣',
'6ï¸\x8f⃣', '5ï¸\x8f⃣', '4ï¸\x8f⃣', '3ï¸\x8f⃣',
'2ï¸\x8f⃣', '1ï¸\x8f⃣', '0ï¸\x8f⃣', '🆘']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern='theart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 54)
animation_chars = ['â\x9d¤ï¸\x8f', '🧡', '💛', '💚', '💙',
'💜', '🖤', '💘', 'ðŸ’\x9d', 'â\x9d¤ï¸\x8f', '🧡', '💛',
'💚', '💙', '💜', '🖤', '💘', 'ðŸ’\x9d']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 18])
@borg.on(admin_cmd(pattern='fdance'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 5)
await event.edit('Connecting..')
animation_chars = [
"""⠀⠀⠀⣶⣿⣶
⠀⠀⠀⣿⣿⣿⣀
⠀⣀⣿⣿⣿⣿⣿⣿
⣶⣿⠛â£â£¿â£¿â£¿â£¿
⠛⠛⠛⣿⣿⣿⣿⠿
⠀⠀⠀⠀⣿⣿⣿
⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€
⠀⠤⣿⣿⣿⣿⣿⣿⠉
⠀⣿⣿⣿⣿⣿⣿⠉
⣿⣿⣿⣿⣿⣿
⣿⣿⣶⣿⣿
⠉⠛⣿⣿⣶⣤
⠀⠀⠉⠿⣿⣿⣤
⠀⠀⣀⣤⣿⣿⣿
⠀⠒⠿⠛⠉⠿⣿
⠀⠀⠀⠀⠀⣀⣿⣿
⠀⠀⠀⠀⣶⠿⠿⠛
"""
,
"""⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿
⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀
⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀
⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤
⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿
⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉
⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉
⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€
⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿
⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿
⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿
⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛
"""
,
"""⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶
⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶
⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤
⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀
⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿
⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶
⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒
⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰
⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›
⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£
⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤
⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿
⠀⠀⠀⠀⠀⠀⣿⠛
⠀⠀⠀⠀⠀⠀â£â£¶
"""
,
"""⠀⠀⠀⠀⠀⠀⣶⣿⣶
⠀⠀⠀⣤⣤⣤⣿⣿⣿
⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶
⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿
⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶
⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿
⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶
⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤
⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿
⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉
⠀⠀⠀⣿⣿⣿⣿⣿⣶
⠀⠀⠀⠀⣿⠉⠿⣿⣿
⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿
⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶
⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿
⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉
"""
,
"""⠀⠀⠀⠀⠀⠀⣤⣶⣶
⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀
⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿
⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿
⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿
⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤
⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿
⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿
⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿
⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛
⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀
⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿
⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿
⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿
⠀⠀⠀⠀⠀⠀⣀⣿⣿
⠀⠀⠀⠀⠤⣿⠿⠿⠿
"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 5])
@borg.on(admin_cmd(pattern=f'snake$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 27)
await event.edit('snake..')
animation_chars = [
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
,
"""â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 27])
@borg.on(admin_cmd(pattern=f'human$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
await event.edit('human...')
animation_chars = [
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛🚗
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛🚗⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛🚗⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛🚗⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛🚗⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛🚗⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
🚗⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜😊⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬛⬜⬛
⬛⬛⬜⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬜⬜⬜⬜⬜⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬛⬛⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬜⬛😊⬛⬜⬛
⬛⬛⬜⬜⬜⬛⬛
⬛⬛⬛⬜⬛⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬜⬛⬛⬛⬜⬛
⬛⬛⬛⬛⬛⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛😊⬛⬛⬛
⬛⬛⬜⬜⬜⬛⬛
⬛⬜⬛⬜⬛⬜⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
⬛⬛⬜⬛⬜⬛⬛
🔲🔲🔲🔲🔲🔲🔲"""
,
"""⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛⬛
⬜⬜⬜😊⬜⬜⬜
⬜⬜⬜⬜⬜⬜⬜
🔲🔲🔲🔲🔲🔲🔲"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=f'mc$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 28)
await event.edit('mc..')
animation_chars = [
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 28])
@borg.on(admin_cmd(pattern='virus$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 30)
await event.edit('Injecting virus....')
animation_chars = [
"""🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
,
"""â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"""
, """â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸""",
"""â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸""", 'â—¼ï¸\x8f']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern='repe$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.2
animation_ttl = range(0, 30)
await event.edit('repe')
animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',
'**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',
'**rape_trai**', '**rape_train**', '**ape_train🚅**',
'**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',
'**_train🚅🚃🚃🚃🚃**',
'**train🚅🚃🚃🚃🚃🚃**',
'**rain🚅🚃🚃🚃🚃🚃🚃**',
'**ain🚅🚃🚃🚃🚃🚃🚃🚃**',
'**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',
'**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',
'🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',
'🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=f'isro$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 24)
await event.edit('Connecting..')
animation_chars = [
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
🚀⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛🚀⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🚀⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🚀⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛🚀⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛🚀
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""🛸⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
🛸⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛🛸⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🛸⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛🛸⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛"""
,
"""⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬛⬛⬛⬛⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛⬛
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸⬛🚶â€â™‚ï¸
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
👽⬛⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛👽⬛🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
,
"""⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛⬛⬛⬛⬛
⬛⬛👽🛸🚶â€â™‚ï¸â¬›
⬜⬜⬜⬜⬜⬜"""
, '__Signal Lost....__']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 24])
@borg.on(admin_cmd(pattern=f'nakal$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 6)
await event.edit('nakal')
animation_chars = [
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇
⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇
⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
,
"""`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀
⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷
⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ ⠀ ⡇
⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇
⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇
⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼
⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀
⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €
⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀
⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀
⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f'music$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.5
animation_ttl = range(0, 11)
await event.edit('starting player...')
animation_chars = [
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
,
"""⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`
⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)
⠀⠀⠀⠀**Now Playing:shape of u**
**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**
⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`
**â €Next Song:** __Alan Walker - Alone.__
⠀⠀⠀⠀**⠀Device: Nokia 1100**"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f'squ$', outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(1)
await event.edit(
"""â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•—
â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘
â•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•"""
)
await asyncio.sleep(6)
@borg.on(admin_cmd(pattern='star$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='boxs'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'rain$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🌬â˜\x81ï¸\x8f🌩🌨🌧🌦🌥⛅🌤'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='clol$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🤔ðŸ§\x90🤨🤔ðŸ§\x90🤨'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='odra$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🚶ðŸ\x8fƒðŸš¶ðŸ\x8fƒðŸš¶ðŸ\x8fƒðŸš¶ðŸ\x8fƒ'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='deploy$'))
async def _(event):
if event.fwd_from:
return
animation_interval = 3
animation_ttl = range(0, 12)
await event.edit('Deploying...')
animation_chars = ['**Heroku Connecting To Latest Github Build **',
f'**Build started by user** @Kraken_The_BadASS',
f'**Deploy** `535a74f0` for user by my master!!',
'**Restarting Heroku Server...**',
'**State changed from up to starting**',
'**Stopping all processes with SIGTERM**',
'**Process exited with** `status 143`',
'**Starting process with command** `python3 -m stdborg`',
'**State changed from starting to up**',
'__INFO:Userbot:Logged in as 557667062__',
'__INFO:Userbot:Successfully loaded all plugins__',
'**Build Succeeded**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern='dump ?(.*)'))
async def _(message):
try:
obj = message.pattern_match.group(1)
if len(obj) != 3:
raise IndexError
inp = ' '.join(obj)
except IndexError:
inp = '🥞 🎂 ðŸ\x8d«'
u, t, g, o, s, n = inp.split(
), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\xa0€ ', '\n'
h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]
for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,
s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +
(o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),
o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i
] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(
''), g, t))] for i, f in enumerate(reversed(h)))]):
for something_else in something:
await asyncio.sleep(0.3)
try:
await message.edit(something_else)
except errors.MessageIdInvalidError:
return
@borg.on(admin_cmd(pattern='fleaveme$'))
async def _(event):
animation_interval = 1
animation_ttl = range(0, 10)
animation_chars = ['⬛⬛⬛\n⬛⬛⬛\n⬛⬛⬛',
'⬛⬛⬛\n⬛🔄⬛\n⬛⬛⬛',
"""⬛⬆ï¸â¬›
⬛🔄⬛
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄⬛
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬛⬛""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬛↘ï¸""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
⬛⬇ï¸â†˜ï¸""",
"""⬛⬆ï¸â†—ï¸
⬛🔄➡ï¸
↙ï¸â¬‡ï¸â†˜ï¸""",
"""⬛⬆ï¸â†—ï¸
⬅ï¸ðŸ”„âž¡ï¸
↙ï¸â¬‡ï¸â†˜ï¸""",
"""↖ï¸â¬†ï¸â†—ï¸
⬅ï¸ðŸ”„âž¡ï¸
↙ï¸â¬‡ï¸â†˜ï¸"""]
if event.fwd_from:
return
await event.edit('fleaveme....')
await asyncio.sleep(2)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern='loveu', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 70)
await event.edit('loveu')
animation_chars = ['😀', '👩â€\x8d🎨', 'ðŸ˜\x81', '😂', '🤣',
'😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',
'ðŸ˜\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\x90',
'😯', '😴', '😔', '😕', '☹', 'ðŸ™\x81', '😖', '😞',
'😟', '😢', 'ðŸ˜\xad', '🤯', '💔', 'â\x9d¤', 'i Love Youâ\x9d¤'
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 35])
@borg.on(admin_cmd(pattern=f'plane', outgoing=True))
async def _(event):
if event.fwd_from:
retun
await event.edit('✈-------------')
await event.edit('-✈------------')
await event.edit('--✈-----------')
await event.edit('---✈----------')
await event.edit('----✈---------')
await event.edit('-----✈--------')
await event.edit('------✈-------')
await event.edit('-------✈------')
await event.edit('--------✈-----')
await event.edit('---------✈----')
await event.edit('----------✈---')
await event.edit('-----------✈--')
await event.edit('------------✈-')
await event.edit('-------------✈')
await asyncio.sleep(3)
await event.delete()
@borg.on(admin_cmd(pattern='pulis'))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 12)
await event.edit('Pulis')
animation_chars = [
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
,
"""🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴
🔵🔵🔵⬜⬜⬜🔴🔴🔴"""
,
"""🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵
🔴🔴🔴⬜⬜⬜🔵🔵🔵"""
, f'{DEFAULTUSER} **Police iz Here**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern=f'jio$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 19)
await event.edit('jio network boosting...')
animation_chars = ['`Connecting To JIO NETWORK ....`',
'`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–‡ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–† â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–… â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–„ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–’ â–‚ â–\x81`',
'`â–’ â–’ â–’ â–’ â–’ â–’ â–\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',
'*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–’ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–’ â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–’ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–‡ â–’`',
'`â–\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 19])
@borg.on(admin_cmd(pattern=f'solarsystem', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 80)
await event.edit('solarsystem')
animation_chars = [
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`"""
,
"""`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`"""
,
"""`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸
â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸
â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern='lul$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('😂🤣😂🤣😂🤣'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='nothappy$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('ðŸ˜\x81☹ï¸\x8fðŸ˜\x81☹ï¸\x8fðŸ˜\x81☹ï¸\x8fðŸ˜\x81')
)
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern='clock$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\x90🕛'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='muah$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('😗😙😚😚😘'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='heart$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('â\x9d¤ï¸\x8f🧡💛💚💙💜🖤'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='gym$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list(
'ðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8dðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8dðŸ\x8fƒâ€\x8dðŸ\x8f‹â€\x8d🤸â€\x8d'
))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'earth$', outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list('ðŸŒ\x8fðŸŒ\x8d🌎🌎ðŸŒ\x8dðŸŒ\x8fðŸŒ\x8d🌎'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern='moon$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern='candy$'))
async def _(event):
if event.fwd_from:
return
deq = deque(list(
'ðŸ\x8d¦ðŸ\x8d§ðŸ\x8d©ðŸ\x8dªðŸŽ‚ðŸ\x8d°ðŸ§\x81ðŸ\x8d«ðŸ\x8d¬ðŸ\x8d\xad'
))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit(''.join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f'smoon$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 101)
await event.edit('smoon..')
animation_chars = [
"""🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗"""
,
"""🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘"""
,
"""🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑"""
,
"""🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒"""
,
"""🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓
🌗🌗🌗🌗🌗
🌓🌓🌓🌓🌓"""
,
"""🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔
🌘🌘🌘🌘🌘
🌔🌔🌔🌔🌔"""
,
"""🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕
🌑🌑🌑🌑🌑
🌕🌕🌕🌕🌕"""
,
"""🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖
🌒🌒🌒🌒🌒
🌖🌖🌖🌖🌖"""
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=f'tmoon$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 117)
await event.edit('tmoon')
animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',
'🌕', '🌖']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 32])
@borg.on(admin_cmd(pattern=f'clown$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\x8f',
'🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',
'🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',
'🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',
'🤡🤡', '🤡', 'You', 'You Are', 'You Are A',
'You Are A Clown 🤡']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern='aheart$', outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.3
animation_ttl = range(0, 50)
animation_chars = ['â\x9d¤ï¸\x8f', '🧡', '💛', '💚', '💙',
'💜', '🖤', '💘', 'ðŸ’\x9d', '💔', 'â\x9d¤ï¸\x8f', '🧡',
'💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\x9d', '💔']
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 20])
<|reserved_special_token_1|>
#Credits To @maxprogrammer007 (for editing)
# Ported for Ultroid < https://github.com/TeamUltroid/Ultroid >
import os
import sys
import logging
from telethon import events
import asyncio
from userbot.utils import admin_cmd
from userbot import ALIVE_NAME
import random, re
from userbot import CMD_HELP
from collections import deque
import importlib.util
import random
DEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else "Cat"
@borg.on(admin_cmd(pattern="stupid$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
await event.edit("brain")
animation_chars = [
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <)🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑",
"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i %14 ])
@borg.on(admin_cmd(pattern=f"bombs$", outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n")
await asyncio.sleep(1)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n")
await asyncio.sleep(0.5)
await event.edit("â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n")
await asyncio.sleep(0.5)
await event.edit("`RIP PLOXXX......`")
await asyncio.sleep(2)
@borg.on(admin_cmd(pattern=f"kill$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.7
animation_ttl = range(0, 12)
await event.edit("ready to die dude.....")
animation_chars = [
"Ｆｉｉｉｉｉｒｅ",
"(　･ิω･ิ)︻デâ•ä¸€-->",
"---->____________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â ____",
"------------------>",
"------>;(^。^)ノ",
"(￣ー￣) DEAD",
"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern="ding$"))
async def _(event):
animation_interval = 0.3
animation_ttl = range(0, 30)
animation_chars = [
"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴",
"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴",
"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜",
"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜",
"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜"
]
if event.fwd_from:
return
await event.edit("ding..dong..ding..dong ...")
await asyncio.sleep(4)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern=f"hypno$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 15)
await event.edit("hypo....")
animation_chars = [
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛",
"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛",
"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛",
"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛",
"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜",
"[👉🔴👈])"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 15])
@borg.on(admin_cmd(pattern="gangasta$"))
async def _(event):
await event.edit("EVERyBOdy")
await asyncio.sleep(0.3)
await event.edit("iZ")
await asyncio.sleep(0.2)
await event.edit("GangSTur")
await asyncio.sleep(0.5)
await event.edit("UNtIL ")
await asyncio.sleep(0.2)
await event.edit("I")
await asyncio.sleep(0.3)
await event.edit("ArRivE")
await asyncio.sleep(0.3)
await event.edit("🔥🔥🔥")
await asyncio.sleep(0.3)
await event.edit("EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥")
@borg.on(admin_cmd(pattern=f"charging$"))
async def timer_blankx(e):
txt=e.text[10:] + '\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` '
j=10
k=j
for j in range(j):
await e.edit(txt + str(k))
k=k+10
await asyncio.sleep(1)
await asyncio.sleep(1)
await e.edit("`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) ", link_preview=True)
@borg.on(admin_cmd("bigoof"))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 7)
await event.edit("â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›")
animation_chars = [
"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ ",
"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯",
"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 7])
@borg.on(admin_cmd(pattern="g1 ?(.*)"))
async def payf(event):
paytext=event.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1)
await event.edit(pay)
@borg.on(admin_cmd(pattern="uff ?(.*)"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = [
"U",
"Uf",
"Uff",
"Ufffff",
"Uffffff",
"Ufffffff",
"Uffffffff",
"Ufffffffff",
"Uffffffffff",
"Ufffffffffff",
"Uffffffffffff",
"Ufffffffffffff",
"Uffffffffffffff"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern="ctext ?(.*)"))
async def payf(event):
paytext=event.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*8, paytext*8)
await event.edit(pay)
@borg.on(admin_cmd(pattern="ftext ?(.*)"))
async def payf(event):
paytext=event.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*6, paytext*6, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2)
await event.edit(pay)
@borg.on(admin_cmd(outgoing=True, pattern="kf$(.*)"))
async def _(event):
r = random.randint(0, 3)
logger.debug(r)
if r == 0:
await event.edit("â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›")
else:
r == 1
await event.edit("â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯")
@borg.on(admin_cmd(pattern="f (.*)"))
async def payf(e):
paytext = e.pattern_match.group(1)
pay = "{}\n{}\n{}\n{}\n{}\n{}\n{}".format(paytext*5, paytext*1,paytext*1, paytext*4, paytext*1, paytext*1, paytext*1)
await e.edit(pay)
@borg.on(admin_cmd(pattern=f"loading$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"â–®",
"â–¯",
"â–¬",
"â–",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"square$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"â—§",
"â—¨",
"â—§",
"â—¨",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"up$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"╹",
"â•»",
"╹",
"â•»",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"round$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 20)
animation_chars = [
"âš«",
"⬤",
"â—",
"∘",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"hart$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 20)
animation_chars = [
"🖤",
"â¤ï¸",
"🖤",
"â¤ï¸",
"‎"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 4])
@borg.on(admin_cmd(pattern=f"anim$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 11)
animation_chars = [
"ðŸ˜",
"😧",
"😡",
"😢",
"‎**HellBoy Bolte Public**",
"ðŸ˜",
"😧",
"😡",
"😢",
"[PAPA HERE](https://t.me/Kraken_The_BadASS)",
"__**Good to See you Guys....**__"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f"fnl$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = [
"ðŸ˜ðŸ¿",
"ðŸ˜ðŸ¾",
"ðŸ˜ðŸ½",
"ðŸ˜ðŸ¼",
"‎ðŸ˜",
"**Good to See you Guys....**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f"monkey$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 6)
animation_chars = [
"ðŸµ",
"🙉",
"🙈",
"🙊",
"🖕‎ðŸµðŸ–•",
"**Good to See you Guys....**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f"herber$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 2
animation_ttl = range(0, 11)
animation_chars = [
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n",
"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f"hand$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 14)
animation_chars = [
"👈",
"👉",
"â˜ï¸",
"👆",
"🖕",
"👇",
"✌ï¸",
"🤞",
"🖖",
"🤘",
"🤙",
"ðŸ–ï¸",
"👌"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 14])
@borg.on(admin_cmd(pattern=f"gsg$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 13)
animation_chars = [
"🔟",
"9ï¸âƒ£",
"8ï¸âƒ£",
"7ï¸âƒ£",
"6ï¸âƒ£",
"5ï¸âƒ£",
"4ï¸âƒ£",
"3ï¸âƒ£",
"2ï¸âƒ£",
"1ï¸âƒ£",
"0ï¸âƒ£",
"🆘"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 13])
@borg.on(admin_cmd(pattern=r"theart$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 54)
animation_chars = [
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’",
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 18])
@borg.on(admin_cmd(pattern=r"fdance"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 5)
await event.edit("Connecting..")
animation_chars = [
"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n",
"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n",
"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n",
"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n",
"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 5])
@borg.on(admin_cmd(pattern=f"snake$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 27)
await event.edit("snake..")
animation_chars = [
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸",
"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 27])
@borg.on(admin_cmd(pattern=f"human$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 16)
await event.edit("human...")
animation_chars = [
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲",
"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=f"mc$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 28)
await event.edit("mc..")
animation_chars = [
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 28])
@borg.on(admin_cmd(pattern="virus$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 30)
await event.edit("Injecting virus....")
animation_chars = [
"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸",
"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸",
"â—¼ï¸"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=r"repe$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.2
animation_ttl = range(0, 30)
await event.edit("repe")
animation_chars = [
"**r**",
"**ra**",
"**rap**",
"**rape**",
"**rape_**",
"**rape_t**",
"**rape_tr**",
"**rape_tra**",
"**rape_trai**",
"**rape_train**",
"**ape_train🚅**",
"**pe_train🚅🚃🚃**",
"**e_train🚅🚃🚃🚃**",
"**_train🚅🚃🚃🚃🚃**",
"**train🚅🚃🚃🚃🚃🚃**",
"**rain🚅🚃🚃🚃🚃🚃🚃**",
"**ain🚅🚃🚃🚃🚃🚃🚃🚃**",
"**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**",
"**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**",
"🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃🚃",
"🚃🚃🚃🚃",
"🚃🚃🚃",
"🚃🚃",
"🚃",
"**rApEd**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 30])
@borg.on(admin_cmd(pattern=f"isro$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 24)
await event.edit("Connecting..")
animation_chars = [
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛",
"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜",
"__Signal Lost....__"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 24])
@borg.on(admin_cmd(pattern=f"nakal$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 6)
await event.edit("nakal")
animation_chars = [
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 6])
@borg.on(admin_cmd(pattern=f"music$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.5
animation_ttl = range(0, 11)
await event.edit("starting player...")
animation_chars = [
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**",
"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 11])
@borg.on(admin_cmd(pattern=f"squ$",outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(1)
await event.edit("â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•")
await asyncio.sleep(6)
@borg.on(admin_cmd(pattern=r"star$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🦋✨🦋✨🦋✨🦋✨"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"boxs"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🟥🟧🟨🟩🟦🟪🟫⬛⬜"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f"rain$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🌬â˜ï¸ðŸŒ©ðŸŒ¨ðŸŒ§ðŸŒ¦ðŸŒ¥â›…🌤"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"clol$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🤔ðŸ§ðŸ¤¨ðŸ¤”ðŸ§ðŸ¤¨"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"odra$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🚶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒ"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"deploy$"))
async def _(event):
if event.fwd_from:
return
animation_interval = 3
animation_ttl = range(0, 12)
await event.edit("Deploying...")
animation_chars = [
"**Heroku Connecting To Latest Github Build **",
f"**Build started by user** @Kraken_The_BadASS",
f"**Deploy** `535a74f0` for user by my master!!",
"**Restarting Heroku Server...**",
"**State changed from up to starting**",
"**Stopping all processes with SIGTERM**",
"**Process exited with** `status 143`",
"**Starting process with command** `python3 -m stdborg`",
"**State changed from starting to up**",
"__INFO:Userbot:Logged in as 557667062__",
"__INFO:Userbot:Successfully loaded all plugins__",
"**Build Succeeded**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern="dump ?(.*)"))
async def _(message):
try:
obj = message.pattern_match.group(1)
if len(obj) != 3:
raise IndexError
inp = ' '.join(obj)
except IndexError:
inp = "🥞 🎂 ðŸ«"
u, t, g, o, s, n = inp.split(), '🗑', '<(^_^ <)', '(> ^_^)>', '⠀ ', '\n'
h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]
for something in reversed([y for y in ([''.join(x) for x in (
f + (s, g, s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t),
f[:i] + (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''), o, f[i], s, t),
f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i] + (s * 3 + s * f.count(''), o, t),
f[:i] + (s * 3 + s * f.count(''), g, t))] for i, f in enumerate(reversed(h)))]):
for something_else in something:
await asyncio.sleep(0.3)
try:
await message.edit(something_else)
except errors.MessageIdInvalidError:
return
@borg.on(admin_cmd(pattern="fleaveme$"))
async def _(event):
animation_interval = 1
animation_ttl = range(0, 10)
animation_chars = [
"⬛⬛⬛\n⬛⬛⬛\n⬛⬛⬛",
"⬛⬛⬛\n⬛🔄⬛\n⬛⬛⬛",
"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛",
"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸",
"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸",
"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸",
"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸"
]
if event.fwd_from:
return
await event.edit("fleaveme....")
await asyncio.sleep(2)
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 10])
@borg.on(admin_cmd(pattern="loveu", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.5
animation_ttl = range(0, 70)
await event.edit("loveu")
animation_chars = [
"😀",
"👩â€ðŸŽ¨",
"ðŸ˜",
"😂",
"🤣",
"😃",
"😄",
"😅",
"😊",
"☺",
"🙂",
"🤔",
"🤨",
"ðŸ˜",
"😑",
"😶",
"😣",
"😥",
"😮",
"ðŸ¤",
"😯",
"😴",
"😔",
"😕",
"☹",
"ðŸ™",
"😖",
"😞",
"😟",
"😢",
"ðŸ˜",
"🤯",
"💔",
"â¤",
"i Love Youâ¤",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 35])
@borg.on(admin_cmd(pattern=f"plane", outgoing=True))
async def _(event):
if event.fwd_from:
retun
await event.edit("✈-------------")
await event.edit("-✈------------")
await event.edit("--✈-----------")
await event.edit("---✈----------")
await event.edit("----✈---------")
await event.edit("-----✈--------")
await event.edit("------✈-------")
await event.edit("-------✈------")
await event.edit("--------✈-----")
await event.edit("---------✈----")
await event.edit("----------✈---")
await event.edit("-----------✈--")
await event.edit("------------✈-")
await event.edit("-------------✈")
await asyncio.sleep(3)
await event.delete()
@borg.on(admin_cmd(pattern=r"pulis"))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.3
animation_ttl = range(0, 12)
await event.edit("Pulis")
animation_chars = [
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴",
"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵",
f"{DEFAULTUSER} **Police iz Here**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 12])
@borg.on(admin_cmd(pattern=f"jio$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1
animation_ttl = range(0, 19)
await event.edit("jio network boosting...")
animation_chars = [
"`Connecting To JIO NETWORK ....`",
"`â–ˆ â–‡ â–† â–… â–„ â–‚ â–`",
"`â–’ â–‡ â–† â–… â–„ â–‚ â–`",
"`â–’ â–’ â–† â–… â–„ â–‚ â–`",
"`â–’ â–’ â–’ â–… â–„ â–‚ â–`",
"`â–’ â–’ â–’ â–’ â–„ â–‚ â–`",
"`â–’ â–’ â–’ â–’ â–’ â–‚ â–`",
"`â–’ â–’ â–’ â–’ â–’ â–’ â–`",
"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`",
"*Optimising JIO NETWORK...*",
"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`",
"`â– â–’ â–’ â–’ â–’ â–’ â–’`",
"`â– â–‚ â–’ â–’ â–’ â–’ â–’`",
"`â– â–‚ â–„ â–’ â–’ â–’ â–’`",
"`â– â–‚ â–„ â–… â–’ â–’ â–’`",
"`â– â–‚ â–„ â–… â–† â–’ â–’`",
"`â– â–‚ â–„ â–… â–† â–‡ â–’`",
"`â– â–‚ â–„ â–… â–† â–‡ â–ˆ`",
"**JIO NETWORK Boosted....**"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 19])
@borg.on(admin_cmd(pattern=f"solarsystem", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 80)
await event.edit("solarsystem")
animation_chars = [
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`",
"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`",
"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`",
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=r"lul$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("😂🤣😂🤣😂🤣"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"nothappy$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern="clock$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•ðŸ•›"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"muah$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("😗😙😚😚😘"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern="heart$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("â¤ï¸ðŸ§¡ðŸ’›ðŸ’šðŸ’™ðŸ’œðŸ–¤"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern="gym$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f"earth$", outgoing=True))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸŒðŸŒðŸŒŽðŸŒŽðŸŒðŸŒðŸŒðŸŒŽ"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(outgoing=True, pattern="moon$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("🌗🌘🌑🌒🌓🌔🌕🌖"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=r"candy$"))
async def _(event):
if event.fwd_from:
return
deq = deque(list("ðŸ¦ðŸ§ðŸ©ðŸªðŸŽ‚ðŸ°ðŸ§ðŸ«ðŸ¬ðŸ"))
for _ in range(48):
await asyncio.sleep(0.1)
await event.edit("".join(deq))
deq.rotate(1)
@borg.on(admin_cmd(pattern=f"smoon$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 101)
await event.edit("smoon..")
animation_chars = [
"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗",
"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘",
"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑",
"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒",
"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓",
"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔",
"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕",
"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 8])
@borg.on(admin_cmd(pattern=f"tmoon$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.1
animation_ttl = range(0, 117)
await event.edit("tmoon")
animation_chars = [
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖",
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖",
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖",
"🌗",
"🌘",
"🌑",
"🌒",
"🌓",
"🌔",
"🌕",
"🌖"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 32])
@borg.on(admin_cmd(pattern=f"clown$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 0.50
animation_ttl = range(0, 16)
animation_chars = [
"COMMAND CREATE BY @Kraken_The_BadASS",
"🤡ï¸",
"🤡🤡",
"🤡🤡🤡",
"🤡🤡🤡🤡",
"🤡🤡🤡🤡🤡",
"🤡🤡🤡🤡🤡🤡",
"🤡🤡🤡🤡🤡",
"🤡🤡🤡🤡",
"🤡🤡🤡",
"🤡🤡",
"🤡",
"You",
"You Are",
"You Are A",
"You Are A Clown 🤡"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 16])
@borg.on(admin_cmd(pattern=r"aheart$", outgoing=True))
async def _(event):
if event.fwd_from:
return
animation_interval = 1.3
animation_ttl = range(0, 50)
animation_chars = [
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’",
"💔",
"â¤ï¸",
"🧡",
"💛",
"💚",
"💙",
"💜",
"🖤",
"💘",
"ðŸ’",
"💔"
]
for i in animation_ttl:
await asyncio.sleep(animation_interval)
await event.edit(animation_chars[i % 20])
|
flexible
|
{
"blob_id": "51cff2f7dd1fd10c6f447d62db3e98075caebe51",
"index": 1708,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\n@borg.on(admin_cmd(pattern='stupid$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit('brain')\n animation_chars = [\n 'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\\x8f ðŸ§\\xa0\\n\\nðŸ§\\xa0 <(^_^ <)🗑'\n ,\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑\"\"\"]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\n@borg.on(admin_cmd(pattern=f'bombs$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit('`RIP PLOXXX......`')\n await asyncio.sleep(2)\n\n\n@borg.on(admin_cmd(pattern=f'kill$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit('ready to die dude.....')\n animation_chars = ['Ｆｉｉｉｉｉｒｅ',\n '(　･ิω･ิ)︻デâ•\\x90一-->',\n 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, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',\n \"\"\"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern='ding$'))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30)\n animation_chars = ['🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜',\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ]\n if event.fwd_from:\n return\n await event.edit('ding..dong..ding..dong ...')\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\n@borg.on(admin_cmd(pattern=f'hypno$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit('hypo....')\n animation_chars = [\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\"\"\"\n ,\n \"\"\"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛\"\"\"\n , \"\"\"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜\"\"\", '[👉🔴👈])']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\n\n@borg.on(admin_cmd(pattern='gangasta$'))\nasync def _(event):\n await event.edit('EVERyBOdy')\n await asyncio.sleep(0.3)\n await event.edit('iZ')\n await asyncio.sleep(0.2)\n await event.edit('GangSTur')\n await asyncio.sleep(0.5)\n await event.edit('UNtIL ')\n await asyncio.sleep(0.2)\n await event.edit('I')\n await asyncio.sleep(0.3)\n await event.edit('ArRivE')\n await asyncio.sleep(0.3)\n await event.edit('🔥🔥🔥')\n await asyncio.sleep(0.3)\n await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')\n\n\n@borg.on(admin_cmd(pattern=f'charging$'))\nasync def timer_blankx(e):\n txt = e.text[10:] + \"\"\"\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` \"\"\"\n j = 10\n k = j\n for j in range(j):\n await e.edit(txt + str(k))\n k = k + 10\n await asyncio.sleep(1)\n await asyncio.sleep(1)\n await e.edit(\n \"\"\"`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \"\"\"\n , link_preview=True)\n\n\n@borg.on(admin_cmd('bigoof'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\n \"\"\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\"\"\"\n )\n animation_chars = [\n \"\"\"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ \"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n\n@borg.on(admin_cmd(pattern='g1 ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = (\n \"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\"\"\"\n .format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *\n 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,\n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(pattern='uff ?(.*)'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',\n 'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',\n 'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\n@borg.on(admin_cmd(pattern='ctext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,\n paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8, \n paytext * 8)\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(pattern='ftext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,\n paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2, \n paytext * 2)\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='kf$(.*)'))\nasync def _(event):\n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\n \"\"\"â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›\"\"\"\n )\n else:\n r == 1\n await event.edit(\n \"\"\"â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯\"\"\"\n )\n\n\n@borg.on(admin_cmd(pattern='f (.*)'))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext * 5, paytext * 1, \n paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)\n await e.edit(pay)\n\n\n@borg.on(admin_cmd(pattern=f'loading$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\\xad', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'square$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â—§', 'â—¨', 'â—§', 'â—¨', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'up$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['╹', 'â•»', '╹', 'â•»', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'round$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['âš«', '⬤', 'â—\\x8f', '∘', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'hart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = ['🖤', 'â\\x9d¤ï¸\\x8f', '🖤', 'â\\x9d¤ï¸\\x8f', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'anim$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = ['ðŸ˜\\x81', '😧', '😡', '😢',\n '‎**HellBoy Bolte Public**', 'ðŸ˜\\x81', '😧', '😡', '😢',\n '[PAPA HERE](https://t.me/Kraken_The_BadASS)',\n '__**Good to See you Guys....**__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'fnl$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ˜\\x81ðŸ\\x8f¿', 'ðŸ˜\\x81ðŸ\\x8f¾', 'ðŸ˜\\x81ðŸ\\x8f½',\n 'ðŸ˜\\x81ðŸ\\x8f¼', '‎ðŸ˜\\x81', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'monkey$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ\\x90µ', '🙉', '🙈', '🙊',\n '🖕‎ðŸ\\x90µðŸ–•', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'herber$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'hand$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = ['👈', '👉', 'â˜\\x9dï¸\\x8f', '👆', '🖕',\n '👇', '✌ï¸\\x8f', '🤞', '🖖', '🤘', '🤙',\n 'ðŸ–\\x90ï¸\\x8f', '👌']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\n@borg.on(admin_cmd(pattern=f'gsg$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['🔟', '9ï¸\\x8f⃣', '8ï¸\\x8f⃣', '7ï¸\\x8f⃣',\n '6ï¸\\x8f⃣', '5ï¸\\x8f⃣', '4ï¸\\x8f⃣', '3ï¸\\x8f⃣',\n '2ï¸\\x8f⃣', '1ï¸\\x8f⃣', '0ï¸\\x8f⃣', '🆘']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\n@borg.on(admin_cmd(pattern='theart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', 'â\\x9d¤ï¸\\x8f', '🧡', '💛',\n '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n\n@borg.on(admin_cmd(pattern='fdance'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5])\n\n\n@borg.on(admin_cmd(pattern=f'snake$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit('snake..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27])\n\n\n@borg.on(admin_cmd(pattern=f'human$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit('human...')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\n@borg.on(admin_cmd(pattern=f'mc$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit('mc..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28])\n\n\n@borg.on(admin_cmd(pattern='virus$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit('Injecting virus....')\n animation_chars = [\n \"\"\"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n , \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\"\"\",\n \"\"\"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸\"\"\", 'â—¼ï¸\\x8f']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\n@borg.on(admin_cmd(pattern='repe$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit('repe')\n animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',\n '**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',\n '**rape_trai**', '**rape_train**', '**ape_train🚅**',\n '**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',\n '**_train🚅🚃🚃🚃🚃**',\n '**train🚅🚃🚃🚃🚃🚃**',\n '**rain🚅🚃🚃🚃🚃🚃🚃**',\n '**ain🚅🚃🚃🚃🚃🚃🚃🚃**',\n '**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',\n '**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',\n '🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\n@borg.on(admin_cmd(pattern=f'isro$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n , '__Signal Lost....__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\n\n\n@borg.on(admin_cmd(pattern=f'nakal$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit('nakal')\n animation_chars = [\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'music$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit('starting player...')\n animation_chars = [\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'squ$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(6)\n\n\n@borg.on(admin_cmd(pattern='star$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='boxs'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'rain$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌬â˜\\x81ï¸\\x8f🌩🌨🌧🌦🌥⛅🌤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='clol$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🤔ðŸ§\\x90🤨🤔ðŸ§\\x90🤨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='odra$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🚶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒ'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='deploy$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit('Deploying...')\n animation_chars = ['**Heroku Connecting To Latest Github Build **',\n f'**Build started by user** @Kraken_The_BadASS',\n f'**Deploy** `535a74f0` for user by my master!!',\n '**Restarting Heroku Server...**',\n '**State changed from up to starting**',\n '**Stopping all processes with SIGTERM**',\n '**Process exited with** `status 143`',\n '**Starting process with command** `python3 -m stdborg`',\n '**State changed from starting to up**',\n '__INFO:Userbot:Logged in as 557667062__',\n '__INFO:Userbot:Successfully loaded all plugins__',\n '**Build Succeeded**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern='dump ?(.*)'))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = '🥞 🎂 ðŸ\\x8d«'\n u, t, g, o, s, n = inp.split(\n ), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\\xa0€ ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,\n s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +\n (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),\n o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i\n ] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(\n ''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\n\n@borg.on(admin_cmd(pattern='fleaveme$'))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = ['⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛',\n '⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛',\n \"\"\"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\"]\n if event.fwd_from:\n return\n await event.edit('fleaveme....')\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\n@borg.on(admin_cmd(pattern='loveu', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit('loveu')\n animation_chars = ['😀', '👩â€\\x8d🎨', 'ðŸ˜\\x81', '😂', '🤣',\n '😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',\n 'ðŸ˜\\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\\x90',\n '😯', '😴', '😔', '😕', '☹', 'ðŸ™\\x81', '😖', '😞',\n '😟', '😢', 'ðŸ˜\\xad', '🤯', '💔', 'â\\x9d¤', 'i Love Youâ\\x9d¤'\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n\n\n@borg.on(admin_cmd(pattern=f'plane', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit('✈-------------')\n await event.edit('-✈------------')\n await event.edit('--✈-----------')\n await event.edit('---✈----------')\n await event.edit('----✈---------')\n await event.edit('-----✈--------')\n await event.edit('------✈-------')\n await event.edit('-------✈------')\n await event.edit('--------✈-----')\n await event.edit('---------✈----')\n await event.edit('----------✈---')\n await event.edit('-----------✈--')\n await event.edit('------------✈-')\n await event.edit('-------------✈')\n await asyncio.sleep(3)\n await event.delete()\n\n\n@borg.on(admin_cmd(pattern='pulis'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit('Pulis')\n animation_chars = [\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n , f'{DEFAULTUSER} **Police iz Here**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern=f'jio$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit('jio network boosting...')\n animation_chars = ['`Connecting To JIO NETWORK ....`',\n '`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–’ â–\\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19])\n\n\n@borg.on(admin_cmd(pattern=f'solarsystem', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit('solarsystem')\n animation_chars = [\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\n@borg.on(admin_cmd(pattern='lul$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😂🤣😂🤣😂🤣'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='nothappy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81')\n )\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='clock$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\\x90🕛'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='muah$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😗😙😚😚😘'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='heart$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('â\\x9d¤ï¸\\x8f🧡💛💚💙💜🖤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='gym$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8d'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'earth$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸŒ\\x8fðŸŒ\\x8d🌎🌎ðŸŒ\\x8dðŸŒ\\x8fðŸŒ\\x8d🌎'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='moon$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='candy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8d¦ðŸ\\x8d§ðŸ\\x8d©ðŸ\\x8dªðŸŽ‚ðŸ\\x8d°ðŸ§\\x81ðŸ\\x8d«ðŸ\\x8d¬ðŸ\\x8d\\xad'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'smoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit('smoon..')\n animation_chars = [\n \"\"\"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\"\"\"\n ,\n \"\"\"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\"\"\"\n ,\n \"\"\"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\"\"\"\n ,\n \"\"\"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\"\"\"\n ,\n \"\"\"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\"\"\"\n ,\n \"\"\"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\"\"\"\n ,\n \"\"\"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\"\"\"\n ,\n \"\"\"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\n@borg.on(admin_cmd(pattern=f'tmoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit('tmoon')\n animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n\n@borg.on(admin_cmd(pattern=f'clown$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\\x8f',\n '🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',\n '🤡🤡', '🤡', 'You', 'You Are', 'You Are A',\n 'You Are A Clown 🤡']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\n@borg.on(admin_cmd(pattern='aheart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔', 'â\\x9d¤ï¸\\x8f', '🧡',\n '💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20])\n",
"step-3": "<mask token>\nDEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else 'Cat'\n\n\n@borg.on(admin_cmd(pattern='stupid$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit('brain')\n animation_chars = [\n 'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\\x8f ðŸ§\\xa0\\n\\nðŸ§\\xa0 <(^_^ <)🗑'\n ,\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑\"\"\"]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\n@borg.on(admin_cmd(pattern=f'bombs$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit('`RIP PLOXXX......`')\n await asyncio.sleep(2)\n\n\n@borg.on(admin_cmd(pattern=f'kill$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit('ready to die dude.....')\n animation_chars = ['Ｆｉｉｉｉｉｒｅ',\n '(　･ิω･ิ)︻デâ•\\x90一-->',\n 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, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',\n \"\"\"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern='ding$'))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30)\n animation_chars = ['🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜',\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ]\n if event.fwd_from:\n return\n await event.edit('ding..dong..ding..dong ...')\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\n@borg.on(admin_cmd(pattern=f'hypno$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit('hypo....')\n animation_chars = [\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\"\"\"\n ,\n \"\"\"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛\"\"\"\n , \"\"\"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜\"\"\", '[👉🔴👈])']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\n\n@borg.on(admin_cmd(pattern='gangasta$'))\nasync def _(event):\n await event.edit('EVERyBOdy')\n await asyncio.sleep(0.3)\n await event.edit('iZ')\n await asyncio.sleep(0.2)\n await event.edit('GangSTur')\n await asyncio.sleep(0.5)\n await event.edit('UNtIL ')\n await asyncio.sleep(0.2)\n await event.edit('I')\n await asyncio.sleep(0.3)\n await event.edit('ArRivE')\n await asyncio.sleep(0.3)\n await event.edit('🔥🔥🔥')\n await asyncio.sleep(0.3)\n await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')\n\n\n@borg.on(admin_cmd(pattern=f'charging$'))\nasync def timer_blankx(e):\n txt = e.text[10:] + \"\"\"\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` \"\"\"\n j = 10\n k = j\n for j in range(j):\n await e.edit(txt + str(k))\n k = k + 10\n await asyncio.sleep(1)\n await asyncio.sleep(1)\n await e.edit(\n \"\"\"`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \"\"\"\n , link_preview=True)\n\n\n@borg.on(admin_cmd('bigoof'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\n \"\"\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\"\"\"\n )\n animation_chars = [\n \"\"\"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ \"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n\n@borg.on(admin_cmd(pattern='g1 ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = (\n \"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\"\"\"\n .format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *\n 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,\n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(pattern='uff ?(.*)'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',\n 'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',\n 'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\n@borg.on(admin_cmd(pattern='ctext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,\n paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8, \n paytext * 8)\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(pattern='ftext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,\n paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2, \n paytext * 2)\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='kf$(.*)'))\nasync def _(event):\n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\n \"\"\"â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›\"\"\"\n )\n else:\n r == 1\n await event.edit(\n \"\"\"â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯\"\"\"\n )\n\n\n@borg.on(admin_cmd(pattern='f (.*)'))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext * 5, paytext * 1, \n paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)\n await e.edit(pay)\n\n\n@borg.on(admin_cmd(pattern=f'loading$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\\xad', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'square$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â—§', 'â—¨', 'â—§', 'â—¨', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'up$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['╹', 'â•»', '╹', 'â•»', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'round$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['âš«', '⬤', 'â—\\x8f', '∘', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'hart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = ['🖤', 'â\\x9d¤ï¸\\x8f', '🖤', 'â\\x9d¤ï¸\\x8f', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'anim$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = ['ðŸ˜\\x81', '😧', '😡', '😢',\n '‎**HellBoy Bolte Public**', 'ðŸ˜\\x81', '😧', '😡', '😢',\n '[PAPA HERE](https://t.me/Kraken_The_BadASS)',\n '__**Good to See you Guys....**__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'fnl$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ˜\\x81ðŸ\\x8f¿', 'ðŸ˜\\x81ðŸ\\x8f¾', 'ðŸ˜\\x81ðŸ\\x8f½',\n 'ðŸ˜\\x81ðŸ\\x8f¼', '‎ðŸ˜\\x81', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'monkey$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ\\x90µ', '🙉', '🙈', '🙊',\n '🖕‎ðŸ\\x90µðŸ–•', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'herber$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'hand$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = ['👈', '👉', 'â˜\\x9dï¸\\x8f', '👆', '🖕',\n '👇', '✌ï¸\\x8f', '🤞', '🖖', '🤘', '🤙',\n 'ðŸ–\\x90ï¸\\x8f', '👌']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\n@borg.on(admin_cmd(pattern=f'gsg$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['🔟', '9ï¸\\x8f⃣', '8ï¸\\x8f⃣', '7ï¸\\x8f⃣',\n '6ï¸\\x8f⃣', '5ï¸\\x8f⃣', '4ï¸\\x8f⃣', '3ï¸\\x8f⃣',\n '2ï¸\\x8f⃣', '1ï¸\\x8f⃣', '0ï¸\\x8f⃣', '🆘']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\n@borg.on(admin_cmd(pattern='theart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', 'â\\x9d¤ï¸\\x8f', '🧡', '💛',\n '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n\n@borg.on(admin_cmd(pattern='fdance'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5])\n\n\n@borg.on(admin_cmd(pattern=f'snake$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit('snake..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27])\n\n\n@borg.on(admin_cmd(pattern=f'human$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit('human...')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\n@borg.on(admin_cmd(pattern=f'mc$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit('mc..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28])\n\n\n@borg.on(admin_cmd(pattern='virus$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit('Injecting virus....')\n animation_chars = [\n \"\"\"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n , \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\"\"\",\n \"\"\"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸\"\"\", 'â—¼ï¸\\x8f']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\n@borg.on(admin_cmd(pattern='repe$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit('repe')\n animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',\n '**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',\n '**rape_trai**', '**rape_train**', '**ape_train🚅**',\n '**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',\n '**_train🚅🚃🚃🚃🚃**',\n '**train🚅🚃🚃🚃🚃🚃**',\n '**rain🚅🚃🚃🚃🚃🚃🚃**',\n '**ain🚅🚃🚃🚃🚃🚃🚃🚃**',\n '**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',\n '**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',\n '🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\n@borg.on(admin_cmd(pattern=f'isro$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n , '__Signal Lost....__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\n\n\n@borg.on(admin_cmd(pattern=f'nakal$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit('nakal')\n animation_chars = [\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'music$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit('starting player...')\n animation_chars = [\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'squ$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(6)\n\n\n@borg.on(admin_cmd(pattern='star$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='boxs'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'rain$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌬â˜\\x81ï¸\\x8f🌩🌨🌧🌦🌥⛅🌤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='clol$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🤔ðŸ§\\x90🤨🤔ðŸ§\\x90🤨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='odra$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🚶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒ'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='deploy$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit('Deploying...')\n animation_chars = ['**Heroku Connecting To Latest Github Build **',\n f'**Build started by user** @Kraken_The_BadASS',\n f'**Deploy** `535a74f0` for user by my master!!',\n '**Restarting Heroku Server...**',\n '**State changed from up to starting**',\n '**Stopping all processes with SIGTERM**',\n '**Process exited with** `status 143`',\n '**Starting process with command** `python3 -m stdborg`',\n '**State changed from starting to up**',\n '__INFO:Userbot:Logged in as 557667062__',\n '__INFO:Userbot:Successfully loaded all plugins__',\n '**Build Succeeded**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern='dump ?(.*)'))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = '🥞 🎂 ðŸ\\x8d«'\n u, t, g, o, s, n = inp.split(\n ), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\\xa0€ ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,\n s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +\n (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),\n o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i\n ] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(\n ''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\n\n@borg.on(admin_cmd(pattern='fleaveme$'))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = ['⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛',\n '⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛',\n \"\"\"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\"]\n if event.fwd_from:\n return\n await event.edit('fleaveme....')\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\n@borg.on(admin_cmd(pattern='loveu', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit('loveu')\n animation_chars = ['😀', '👩â€\\x8d🎨', 'ðŸ˜\\x81', '😂', '🤣',\n '😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',\n 'ðŸ˜\\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\\x90',\n '😯', '😴', '😔', '😕', '☹', 'ðŸ™\\x81', '😖', '😞',\n '😟', '😢', 'ðŸ˜\\xad', '🤯', '💔', 'â\\x9d¤', 'i Love Youâ\\x9d¤'\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n\n\n@borg.on(admin_cmd(pattern=f'plane', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit('✈-------------')\n await event.edit('-✈------------')\n await event.edit('--✈-----------')\n await event.edit('---✈----------')\n await event.edit('----✈---------')\n await event.edit('-----✈--------')\n await event.edit('------✈-------')\n await event.edit('-------✈------')\n await event.edit('--------✈-----')\n await event.edit('---------✈----')\n await event.edit('----------✈---')\n await event.edit('-----------✈--')\n await event.edit('------------✈-')\n await event.edit('-------------✈')\n await asyncio.sleep(3)\n await event.delete()\n\n\n@borg.on(admin_cmd(pattern='pulis'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit('Pulis')\n animation_chars = [\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n , f'{DEFAULTUSER} **Police iz Here**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern=f'jio$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit('jio network boosting...')\n animation_chars = ['`Connecting To JIO NETWORK ....`',\n '`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–’ â–\\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19])\n\n\n@borg.on(admin_cmd(pattern=f'solarsystem', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit('solarsystem')\n animation_chars = [\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\n@borg.on(admin_cmd(pattern='lul$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😂🤣😂🤣😂🤣'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='nothappy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81')\n )\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='clock$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\\x90🕛'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='muah$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😗😙😚😚😘'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='heart$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('â\\x9d¤ï¸\\x8f🧡💛💚💙💜🖤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='gym$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8d'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'earth$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸŒ\\x8fðŸŒ\\x8d🌎🌎ðŸŒ\\x8dðŸŒ\\x8fðŸŒ\\x8d🌎'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='moon$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='candy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8d¦ðŸ\\x8d§ðŸ\\x8d©ðŸ\\x8dªðŸŽ‚ðŸ\\x8d°ðŸ§\\x81ðŸ\\x8d«ðŸ\\x8d¬ðŸ\\x8d\\xad'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'smoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit('smoon..')\n animation_chars = [\n \"\"\"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\"\"\"\n ,\n \"\"\"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\"\"\"\n ,\n \"\"\"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\"\"\"\n ,\n \"\"\"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\"\"\"\n ,\n \"\"\"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\"\"\"\n ,\n \"\"\"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\"\"\"\n ,\n \"\"\"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\"\"\"\n ,\n \"\"\"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\n@borg.on(admin_cmd(pattern=f'tmoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit('tmoon')\n animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n\n@borg.on(admin_cmd(pattern=f'clown$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\\x8f',\n '🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',\n '🤡🤡', '🤡', 'You', 'You Are', 'You Are A',\n 'You Are A Clown 🤡']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\n@borg.on(admin_cmd(pattern='aheart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔', 'â\\x9d¤ï¸\\x8f', '🧡',\n '💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20])\n",
"step-4": "import os\nimport sys\nimport logging\nfrom telethon import events\nimport asyncio\nfrom userbot.utils import admin_cmd\nfrom userbot import ALIVE_NAME\nimport random, re\nfrom userbot import CMD_HELP\nfrom collections import deque\nimport importlib.util\nimport random\nDEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else 'Cat'\n\n\n@borg.on(admin_cmd(pattern='stupid$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit('brain')\n animation_chars = [\n 'YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸\\x8f ðŸ§\\xa0\\n\\nðŸ§\\xa0 <(^_^ <)🗑'\n ,\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n🧠<(^_^ <) 🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n(> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🧠🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n (> ^_^)>🗑\"\"\",\n \"\"\"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \n\n <(^_^ <)🗑\"\"\"]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\n@borg.on(admin_cmd(pattern=f'bombs$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💣💣💣💣 \n\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n💥💥💥💥 \n💥💥💥💥 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit(\n \"\"\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \n😵😵😵😵 \n\"\"\"\n )\n await asyncio.sleep(0.5)\n await event.edit('`RIP PLOXXX......`')\n await asyncio.sleep(2)\n\n\n@borg.on(admin_cmd(pattern=f'kill$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit('ready to die dude.....')\n animation_chars = ['Ｆｉｉｉｉｉｒｅ',\n '(　･ิω･ิ)︻デâ•\\x90一-->',\n 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, '------------------>', '------>;(^。^)ノ', '(￣ー￣) DEAD',\n \"\"\"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\n '#Sad_Reacts_Online'\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern='ding$'))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30)\n animation_chars = ['🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜',\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬛🔴\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬜⬛⬜\n⬜⬜⬜⬜🔴\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬜⬛⬜⬜\n⬜⬜🔴⬜⬜\"\"\",\n \"\"\"⬜⬜⬛⬜⬜\n⬜⬛⬜⬜⬜\n🔴⬜⬜⬜⬜\"\"\",\n \"\"\"🔴⬛⬛⬜⬜\n⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜\"\"\",\n \"\"\"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ]\n if event.fwd_from:\n return\n await event.edit('ding..dong..ding..dong ...')\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\n@borg.on(admin_cmd(pattern=f'hypno$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit('hypo....')\n animation_chars = [\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬛⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬛⬜⬛⬜⬜\n⬜⬜⬛⬛⬛⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\"\"\"\n ,\n \"\"\"⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛⬜\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬜⬜⬜⬜⬜⬜⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬜⬛⬜⬛⬜\n⬜⬛⬜⬜⬜⬛⬜\n⬜⬛⬛⬛⬛⬛⬜\n⬜⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛\n⬛⬜⬜⬜⬛\n⬛⬜⬛⬜⬛\n⬛⬜⬜⬜⬛\n⬛⬛⬛⬛⬛\"\"\"\n , \"\"\"⬜⬜⬜\n⬜⬛⬜\n⬜⬜⬜\"\"\", '[👉🔴👈])']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\n\n@borg.on(admin_cmd(pattern='gangasta$'))\nasync def _(event):\n await event.edit('EVERyBOdy')\n await asyncio.sleep(0.3)\n await event.edit('iZ')\n await asyncio.sleep(0.2)\n await event.edit('GangSTur')\n await asyncio.sleep(0.5)\n await event.edit('UNtIL ')\n await asyncio.sleep(0.2)\n await event.edit('I')\n await asyncio.sleep(0.3)\n await event.edit('ArRivE')\n await asyncio.sleep(0.3)\n await event.edit('🔥🔥🔥')\n await asyncio.sleep(0.3)\n await event.edit('EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥')\n\n\n@borg.on(admin_cmd(pattern=f'charging$'))\nasync def timer_blankx(e):\n txt = e.text[10:] + \"\"\"\n\n`Tesla Wireless Charging (beta) Started...\nDevice Detected: Nokia 1100\nBattery Percentage:` \"\"\"\n j = 10\n k = j\n for j in range(j):\n await e.edit(txt + str(k))\n k = k + 10\n await asyncio.sleep(1)\n await asyncio.sleep(1)\n await e.edit(\n \"\"\"`Tesla Wireless Charging (beta) Completed...\nDevice Detected: Nokia 1100 (Space Grey Varient)\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \"\"\"\n , link_preview=True)\n\n\n@borg.on(admin_cmd('bigoof'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\n \"\"\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\"\"\"\n )\n animation_chars = [\n \"\"\"â•â”â”â”╮╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”╯╰╯ \"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃┃┃ \n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ,\n \"\"\"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n\n@borg.on(admin_cmd(pattern='g1 ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = (\n \"\"\"{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\n{}\"\"\"\n .format(paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext *\n 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1,\n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1, \n paytext * 1, paytext * 1, paytext * 1, paytext * 1, paytext * 1))\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(pattern='uff ?(.*)'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['U', 'Uf', 'Uff', 'Ufffff', 'Uffffff', 'Ufffffff',\n 'Uffffffff', 'Ufffffffff', 'Uffffffffff', 'Ufffffffffff',\n 'Uffffffffffff', 'Ufffffffffffff', 'Uffffffffffffff']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\n@borg.on(admin_cmd(pattern='ctext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 2,\n paytext * 2, paytext * 2, paytext * 2, paytext * 2, paytext * 8, \n paytext * 8)\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(pattern='ftext ?(.*)'))\nasync def payf(event):\n paytext = event.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext *\n 8, paytext * 8, paytext * 2, paytext * 2, paytext * 2, paytext * 6,\n paytext * 6, paytext * 2, paytext * 2, paytext * 2, paytext * 2, \n paytext * 2)\n await event.edit(pay)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='kf$(.*)'))\nasync def _(event):\n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\n \"\"\"â”â”â”â”┓\n┃â”â”â”â”›\n┃┗â”â”┓\n┃â”â”â”â”›\n┃┃\nâ”—â”›\"\"\"\n )\n else:\n r == 1\n await event.edit(\n \"\"\"â•â”â”â”â•®\n┃â•â”â”╯\n┃╰â”â”â•®\n┃â•â”â”╯\n┃┃\n╰╯\"\"\"\n )\n\n\n@borg.on(admin_cmd(pattern='f (.*)'))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = '{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}'.format(paytext * 5, paytext * 1, \n paytext * 1, paytext * 4, paytext * 1, paytext * 1, paytext * 1)\n await e.edit(pay)\n\n\n@borg.on(admin_cmd(pattern=f'loading$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â–®', 'â–¯', 'â–¬', 'â–\\xad', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'square$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['â—§', 'â—¨', 'â—§', 'â—¨', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'up$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['╹', 'â•»', '╹', 'â•»', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'round$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = ['âš«', '⬤', 'â—\\x8f', '∘', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'hart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = ['🖤', 'â\\x9d¤ï¸\\x8f', '🖤', 'â\\x9d¤ï¸\\x8f', '‎']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n\n@borg.on(admin_cmd(pattern=f'anim$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = ['ðŸ˜\\x81', '😧', '😡', '😢',\n '‎**HellBoy Bolte Public**', 'ðŸ˜\\x81', '😧', '😡', '😢',\n '[PAPA HERE](https://t.me/Kraken_The_BadASS)',\n '__**Good to See you Guys....**__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'fnl$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ˜\\x81ðŸ\\x8f¿', 'ðŸ˜\\x81ðŸ\\x8f¾', 'ðŸ˜\\x81ðŸ\\x8f½',\n 'ðŸ˜\\x81ðŸ\\x8f¼', '‎ðŸ˜\\x81', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'monkey$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = ['ðŸ\\x90µ', '🙉', '🙈', '🙊',\n '🖕‎ðŸ\\x90µðŸ–•', '**Good to See you Guys....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'herber$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 5.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.13GB\n **🔹used:** 33.77GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 158.98GB\n **🔹recv:** 146.27GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 159720314\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 20.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 7.18GB\n **🔹used:** 28.26GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 146.27GB\n **🔹recv:** 124.33GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 143565654\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 60.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 6.52GB\n **🔹used:** 35.78GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 124.33GB\n **🔹recv:** 162.48GB\n **🔹sent_packets:** 25655655\n **🔹recv_packets:** 165289456\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.81GB\n **🔹used:** 30.11GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 162.48GB\n **🔹recv:** 175.75GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 135345655\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 80.4%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.76GB\n **🔹used:** 29.35GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 175.75GB\n **🔹recv:** 118.55GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 185466554\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 60%\n\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 62.9%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.23GB\n **🔹used:** 33.32GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 118.55GB\n **🔹recv:** 168.65GB\n **🔹sent_packets:** 24786554\n **🔹recv_packets:** 156745865\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 30%\n\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 30.6%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 9.75GB\n **🔹used:** 36.54GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 168.65GB\n **🔹recv:** 128.35GB\n **🔹sent_packets:** 56565435\n **🔹recv_packets:** 1475823589\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 10%\n\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 10.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 10.20GB\n **🔹used:** 25.40GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 128.35GB\n **🔹recv:** 108.31GB\n **🔹sent_packets:** 54635686\n **🔹recv_packets:** 157865426\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 100%\n\n â—â—â—â—â—â—â—â—â—â—\n\n **🔹cpu core**\n\n **🔹core_usage:** 100.0%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 5.25GB\n **🔹used:** 31.14GB\n **🔹total:** 60.0GB\n \n â—â—â—â—â—â—â—â—â—â—\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 108.31GB\n **🔹recv:** 167.17GB\n **🔹sent_packets:** 84518799\n **🔹recv_packets:** 124575356\n\n\n**===================**\n\"\"\"\n ,\n \"\"\"**===================**\n **Server Details** \n**===================**\n\n\n**=>>> CPU <<<=**\n\n **🔹current_freq:** 2500.09MHz\n **🔹total_usage:** 70%\n\n â—â—â—â—â—â—â—â—‹â—‹â—‹\n\n **🔹cpu core**\n\n **🔹core_usage:** 76.2%\n **🔹current_freq:** 2500.09MHz\n |██████████▉ |\n \n**=>>> RAM <<<=**\n\n **🔹free:** 8.01GB\n **🔹used:** 33.27GB\n **🔹total:** 60.0GB\n \n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\n\n\n**=>>> DISK <<<=**\n\n **🔹free:** 224.12GB\n **🔹used:** 131.84GB\n **🔹total:** 375.02GB\n **🔹usage:** 37.0%\n\n |████■|\n\n\n**=>>> NETWORK <<<=**\n\n **🔹sent:** 167.17GB\n **🔹recv:** 158.98GB\n **🔹sent_packets:** 36547698\n **🔹recv_packets:** 165455856\n\n\n**===================**\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'hand$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = ['👈', '👉', 'â˜\\x9dï¸\\x8f', '👆', '🖕',\n '👇', '✌ï¸\\x8f', '🤞', '🖖', '🤘', '🤙',\n 'ðŸ–\\x90ï¸\\x8f', '👌']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n\n@borg.on(admin_cmd(pattern=f'gsg$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = ['🔟', '9ï¸\\x8f⃣', '8ï¸\\x8f⃣', '7ï¸\\x8f⃣',\n '6ï¸\\x8f⃣', '5ï¸\\x8f⃣', '4ï¸\\x8f⃣', '3ï¸\\x8f⃣',\n '2ï¸\\x8f⃣', '1ï¸\\x8f⃣', '0ï¸\\x8f⃣', '🆘']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n\n@borg.on(admin_cmd(pattern='theart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', 'â\\x9d¤ï¸\\x8f', '🧡', '💛',\n '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n\n@borg.on(admin_cmd(pattern='fdance'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣿⣿⣿⣀\n⠀⣀⣿⣿⣿⣿⣿⣿\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\n⠛⠛⠛⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\n⠀⣿⣿⣿⣿⣿⣿⠉\n⣿⣿⣿⣿⣿⣿\n⣿⣿⣶⣿⣿\n⠉⠛⣿⣿⣶⣤\n⠀⠀⠉⠿⣿⣿⣤\n⠀⠀⣀⣤⣿⣿⣿\n⠀⠒⠿⠛⠉⠿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⣶⠿⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\n⠀⠀⠀⠀⠀⠀⣿⠛\n⠀⠀⠀⠀⠀⠀â£â£¶\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣶⣿⣶\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\n\"\"\"\n ,\n \"\"\"⠀⠀⠀⠀⠀⠀⣤⣶⣶\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\n\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5])\n\n\n@borg.on(admin_cmd(pattern=f'snake$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit('snake..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27])\n\n\n@borg.on(admin_cmd(pattern=f'human$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit('human...')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛🚗\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛🚗⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚗⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚗⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛🚗⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛🚗⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n🚗⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬛⬜⬛\n⬛⬛⬜⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬜⬜⬜⬜⬜⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬜⬛😊⬛⬜⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬛⬛⬜⬛⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬜⬛⬛⬛⬜⬛\n⬛⬛⬛⬛⬛⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛😊⬛⬛⬛\n⬛⬛⬜⬜⬜⬛⬛\n⬛⬜⬛⬜⬛⬜⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n⬛⬛⬜⬛⬜⬛⬛\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛⬛\n⬜⬜⬜😊⬜⬜⬜\n⬜⬜⬜⬜⬜⬜⬜\n🔲🔲🔲🔲🔲🔲🔲\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\n@borg.on(admin_cmd(pattern=f'mc$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit('mc..')\n animation_chars = [\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28])\n\n\n@borg.on(admin_cmd(pattern='virus$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit('Injecting virus....')\n animation_chars = [\n \"\"\"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n ,\n \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\"\"\n , \"\"\"â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸\"\"\",\n \"\"\"â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸\"\"\", 'â—¼ï¸\\x8f']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\n@borg.on(admin_cmd(pattern='repe$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit('repe')\n animation_chars = ['**r**', '**ra**', '**rap**', '**rape**',\n '**rape_**', '**rape_t**', '**rape_tr**', '**rape_tra**',\n '**rape_trai**', '**rape_train**', '**ape_train🚅**',\n '**pe_train🚅🚃🚃**', '**e_train🚅🚃🚃🚃**',\n '**_train🚅🚃🚃🚃🚃**',\n '**train🚅🚃🚃🚃🚃🚃**',\n '**rain🚅🚃🚃🚃🚃🚃🚃**',\n '**ain🚅🚃🚃🚃🚃🚃🚃🚃**',\n '**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**',\n '**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**',\n '🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃🚃🚃', '🚃🚃🚃🚃🚃',\n '🚃🚃🚃🚃', '🚃🚃🚃', '🚃🚃', '🚃', '**rApEd**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n\n@borg.on(admin_cmd(pattern=f'isro$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit('Connecting..')\n animation_chars = [\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n🚀⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🚀⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🚀⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🚀⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛🚀⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛🚀\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n🛸⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛🛸⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛🛸⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛⬛\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n ,\n \"\"\"⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛⬛⬛⬛⬛\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\n⬜⬜⬜⬜⬜⬜\"\"\"\n , '__Signal Lost....__']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\n\n\n@borg.on(admin_cmd(pattern=f'nakal$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit('nakal')\n animation_chars = [\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ,\n \"\"\"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n\n@borg.on(admin_cmd(pattern=f'music$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit('starting player...')\n animation_chars = [\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ,\n \"\"\"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\n\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\n\n⠀⠀⠀⠀**Now Playing:shape of u**\n\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\n\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\n\n**â €Next Song:** __Alan Walker - Alone.__\n\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n\n@borg.on(admin_cmd(pattern=f'squ$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ \tâ–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(1)\n await event.edit(\n \"\"\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\"\"\"\n )\n await asyncio.sleep(6)\n\n\n@borg.on(admin_cmd(pattern='star$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🦋✨🦋✨🦋✨🦋✨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='boxs'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🟥🟧🟨🟩🟦🟪🟫⬛⬜'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'rain$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌬â˜\\x81ï¸\\x8f🌩🌨🌧🌦🌥⛅🌤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='clol$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🤔ðŸ§\\x90🤨🤔ðŸ§\\x90🤨'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='odra$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🚶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒðŸš¶ðŸ\\x8fƒ'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='deploy$'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit('Deploying...')\n animation_chars = ['**Heroku Connecting To Latest Github Build **',\n f'**Build started by user** @Kraken_The_BadASS',\n f'**Deploy** `535a74f0` for user by my master!!',\n '**Restarting Heroku Server...**',\n '**State changed from up to starting**',\n '**Stopping all processes with SIGTERM**',\n '**Process exited with** `status 143`',\n '**Starting process with command** `python3 -m stdborg`',\n '**State changed from starting to up**',\n '__INFO:Userbot:Logged in as 557667062__',\n '__INFO:Userbot:Successfully loaded all plugins__',\n '**Build Succeeded**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern='dump ?(.*)'))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = '🥞 🎂 ðŸ\\x8d«'\n u, t, g, o, s, n = inp.split(\n ), '🗑', '<(^_^ <)', '(> ^_^)>', 'â\\xa0€ ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (f + (s, g,\n s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t), f[:i] +\n (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''),\n o, f[i], s, t), f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i\n ] + (s * 3 + s * f.count(''), o, t), f[:i] + (s * 3 + s * f.count(\n ''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\n\n@borg.on(admin_cmd(pattern='fleaveme$'))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = ['⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛',\n '⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛',\n \"\"\"⬛⬆ï¸â¬›\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄⬛\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛⬛\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬛↘ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n⬛⬇ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬛🔄➡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"⬛⬆ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\",\n \"\"\"↖ï¸â¬†ï¸â†—ï¸\n⬅ï¸ðŸ”„âž¡ï¸\n↙ï¸â¬‡ï¸â†˜ï¸\"\"\"]\n if event.fwd_from:\n return\n await event.edit('fleaveme....')\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\n\n@borg.on(admin_cmd(pattern='loveu', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit('loveu')\n animation_chars = ['😀', '👩â€\\x8d🎨', 'ðŸ˜\\x81', '😂', '🤣',\n '😃', '😄', '😅', '😊', '☺', '🙂', '🤔', '🤨',\n 'ðŸ˜\\x90', '😑', '😶', '😣', '😥', '😮', 'ðŸ¤\\x90',\n '😯', '😴', '😔', '😕', '☹', 'ðŸ™\\x81', '😖', '😞',\n '😟', '😢', 'ðŸ˜\\xad', '🤯', '💔', 'â\\x9d¤', 'i Love Youâ\\x9d¤'\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n\n\n@borg.on(admin_cmd(pattern=f'plane', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit('✈-------------')\n await event.edit('-✈------------')\n await event.edit('--✈-----------')\n await event.edit('---✈----------')\n await event.edit('----✈---------')\n await event.edit('-----✈--------')\n await event.edit('------✈-------')\n await event.edit('-------✈------')\n await event.edit('--------✈-----')\n await event.edit('---------✈----')\n await event.edit('----------✈---')\n await event.edit('-----------✈--')\n await event.edit('------------✈-')\n await event.edit('-------------✈')\n await asyncio.sleep(3)\n await event.delete()\n\n\n@borg.on(admin_cmd(pattern='pulis'))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit('Pulis')\n animation_chars = [\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n ,\n \"\"\"🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\"\"\"\n ,\n \"\"\"🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\"\"\"\n , f'{DEFAULTUSER} **Police iz Here**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n\n@borg.on(admin_cmd(pattern=f'jio$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit('jio network boosting...')\n animation_chars = ['`Connecting To JIO NETWORK ....`',\n '`â–ˆ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–‡ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–† â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–… â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–„ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–‚ â–\\x81`',\n '`â–’ â–’ â–’ â–’ â–’ â–’ â–\\x81`', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '*Optimising JIO NETWORK...*', '`â–’ â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–’ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–’ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–’ â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–’ â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–’ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–’`',\n '`â–\\x81 â–‚ â–„ â–… â–† â–‡ â–ˆ`', '**JIO NETWORK Boosted....**']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19])\n\n\n@borg.on(admin_cmd(pattern=f'solarsystem', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit('solarsystem')\n animation_chars = [\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\"\"\"\n ,\n \"\"\"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\n@borg.on(admin_cmd(pattern='lul$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😂🤣😂🤣😂🤣'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='nothappy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81☹ï¸\\x8fðŸ˜\\x81')\n )\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='clock$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•\\x90🕛'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='muah$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('😗😙😚😚😘'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='heart$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('â\\x9d¤ï¸\\x8f🧡💛💚💙💜🖤'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='gym$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8dðŸ\\x8fƒâ€\\x8dðŸ\\x8f‹â€\\x8d🤸â€\\x8d'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'earth$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('ðŸŒ\\x8fðŸŒ\\x8d🌎🌎ðŸŒ\\x8dðŸŒ\\x8fðŸŒ\\x8d🌎'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(outgoing=True, pattern='moon$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list('🌗🌘🌑🌒🌓🌔🌕🌖'))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern='candy$'))\nasync def _(event):\n if event.fwd_from:\n return\n deq = deque(list(\n 'ðŸ\\x8d¦ðŸ\\x8d§ðŸ\\x8d©ðŸ\\x8dªðŸŽ‚ðŸ\\x8d°ðŸ§\\x81ðŸ\\x8d«ðŸ\\x8d¬ðŸ\\x8d\\xad'\n ))\n for _ in range(48):\n await asyncio.sleep(0.1)\n await event.edit(''.join(deq))\n deq.rotate(1)\n\n\n@borg.on(admin_cmd(pattern=f'smoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit('smoon..')\n animation_chars = [\n \"\"\"🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\"\"\"\n ,\n \"\"\"🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\"\"\"\n ,\n \"\"\"🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\"\"\"\n ,\n \"\"\"🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\"\"\"\n ,\n \"\"\"🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\n🌗🌗🌗🌗🌗\n🌓🌓🌓🌓🌓\"\"\"\n ,\n \"\"\"🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\n🌘🌘🌘🌘🌘\n🌔🌔🌔🌔🌔\"\"\"\n ,\n \"\"\"🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\n🌑🌑🌑🌑🌑\n🌕🌕🌕🌕🌕\"\"\"\n ,\n \"\"\"🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\n🌒🌒🌒🌒🌒\n🌖🌖🌖🌖🌖\"\"\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n\n@borg.on(admin_cmd(pattern=f'tmoon$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit('tmoon')\n animation_chars = ['🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖', '🌗', '🌘', '🌑', '🌒', '🌓', '🌔',\n '🌕', '🌖']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n\n@borg.on(admin_cmd(pattern=f'clown$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n animation_chars = ['COMMAND CREATE BY @Kraken_The_BadASS', '🤡ï¸\\x8f',\n '🤡🤡', '🤡🤡🤡', '🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡🤡🤡',\n '🤡🤡🤡🤡🤡', '🤡🤡🤡🤡', '🤡🤡🤡',\n '🤡🤡', '🤡', 'You', 'You Are', 'You Are A',\n 'You Are A Clown 🤡']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n\n@borg.on(admin_cmd(pattern='aheart$', outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = ['â\\x9d¤ï¸\\x8f', '🧡', '💛', '💚', '💙',\n '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔', 'â\\x9d¤ï¸\\x8f', '🧡',\n '💛', '💚', '💙', '💜', '🖤', '💘', 'ðŸ’\\x9d', '💔']\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20])\n",
"step-5": "#Credits To @maxprogrammer007 (for editing)\n# Ported for Ultroid < https://github.com/TeamUltroid/Ultroid > \n\n\nimport os\nimport sys\nimport logging\nfrom telethon import events\nimport asyncio\nfrom userbot.utils import admin_cmd\nfrom userbot import ALIVE_NAME\nimport random, re\nfrom userbot import CMD_HELP\nfrom collections import deque\nimport importlib.util\nimport random\nDEFAULTUSER = str(ALIVE_NAME) if ALIVE_NAME else \"Cat\"\n\n@borg.on(admin_cmd(pattern=\"stupid$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n await event.edit(\"brain\")\n animation_chars = [ \n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <)🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n🧠<(^_^ <) 🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n(> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🧠🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n (> ^_^)>🗑\",\n \"YOᑌᖇ ᗷᖇᗩIá‘Ž âž¡ï¸ ðŸ§ \\n\\n <(^_^ <)🗑\",\n ]\n for i in animation_ttl:\n \t\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i %14 ])\n\t\t\n@borg.on(admin_cmd(pattern=f\"bombs$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💣💣💣💣 \\n\")\n await asyncio.sleep(1)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💥💥💥💥 \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n💥💥💥💥 \\n💥💥💥💥 \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"â–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\nâ–ªï¸â–ªï¸â–ªï¸â–ªï¸ \\n😵😵😵😵 \\n\")\n await asyncio.sleep(0.5)\n await event.edit(\"`RIP PLOXXX......`\")\n await asyncio.sleep(2)\n \n \n \n@borg.on(admin_cmd(pattern=f\"kill$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.7\n animation_ttl = range(0, 12)\n await event.edit(\"ready to die dude.....\")\n animation_chars = [\n\n \"Ｆｉｉｉｉｉｒｅ\",\n \"(　･ิω･ิ)︻デâ•ä¸€-->\", \n \"---->____________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â \",\n \"------>__________â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â 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â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â â ____\",\n \"------------------>\", \n \"------>;(^。^)ノ\",\n \"(￣ー￣) DEAD\",\n \"`Targeted user killed by Headshot 😈.😈.😈.😈.😈.😈.😈......`\\n '#Sad_Reacts_Online'\\n\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12])\n\n \n@borg.on(admin_cmd(pattern=\"ding$\"))\nasync def _(event):\n animation_interval = 0.3\n animation_ttl = range(0, 30) \n animation_chars = [\n \n \"🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬛⬜⬜⬜\\n🔴⬜⬜⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬜⬛⬜⬜\\n⬜⬜🔴⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬜⬜⬛⬜\\n⬜⬜⬜⬜🔴\",\n \"⬜⬜⬛⬛🔴\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜\", \n \"⬜⬜⬛⬜⬜\\n⬜⬜⬜⬛⬜\\n⬜⬜⬜⬜🔴\",\n \"⬜⬜⬛⬜⬜\\n⬜⬜⬛⬜⬜\\n⬜⬜🔴⬜⬜\",\n \"⬜⬜⬛⬜⬜\\n⬜⬛⬜⬜⬜\\n🔴⬜⬜⬜⬜\",\n \"🔴⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜\",\n\t \"⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\\n⬜ [CAT IS BEST](https://github.com/Sur-vivor/CatUserbot) ⬜\\n⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜⬜\"\n \n ]\n if event.fwd_from:\n return\n await event.edit(\"ding..dong..ding..dong ...\")\n await asyncio.sleep(4)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n \n@borg.on(admin_cmd(pattern=f\"hypno$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 15)\n await event.edit(\"hypo....\")\n animation_chars = [\n \n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬛⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬛⬛⬛⬜⬜\\n⬜⬜⬛⬜⬛⬜⬜\\n⬜⬜⬛⬛⬛⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\",\n \"⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\",\n \"⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛⬜\", \n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬛⬜⬛⬜⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\",\n \"⬜⬜⬜⬜⬜⬜⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬜⬛⬜⬛⬜\\n⬜⬛⬜⬜⬜⬛⬜\\n⬜⬛⬛⬛⬛⬛⬜\\n⬜⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛\\n⬛⬜⬜⬜⬛\\n⬛⬜⬛⬜⬛\\n⬛⬜⬜⬜⬛\\n⬛⬛⬛⬛⬛\",\n \"⬜⬜⬜\\n⬜⬛⬜\\n⬜⬜⬜\",\n \"[👉🔴👈])\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 15])\n\t\t\t\t\n@borg.on(admin_cmd(pattern=\"gangasta$\"))\nasync def _(event):\n await event.edit(\"EVERyBOdy\")\n await asyncio.sleep(0.3)\n await event.edit(\"iZ\")\n await asyncio.sleep(0.2)\n await event.edit(\"GangSTur\")\n await asyncio.sleep(0.5)\n await event.edit(\"UNtIL \")\n await asyncio.sleep(0.2)\n await event.edit(\"I\")\n await asyncio.sleep(0.3)\n await event.edit(\"ArRivE\")\n await asyncio.sleep(0.3)\n await event.edit(\"🔥🔥🔥\")\n await asyncio.sleep(0.3)\n await event.edit(\"EVERyBOdy iZ GangSTur UNtIL I ArRivE 🔥🔥🔥\")\t\t\n\n@borg.on(admin_cmd(pattern=f\"charging$\"))\nasync def timer_blankx(e):\n txt=e.text[10:] + '\\n\\n`Tesla Wireless Charging (beta) Started...\\nDevice Detected: Nokia 1100\\nBattery Percentage:` '\n j=10\n k=j\n for j in range(j):\n await e.edit(txt + str(k))\n k=k+10\n await asyncio.sleep(1)\n await asyncio.sleep(1) \n await e.edit(\"`Tesla Wireless Charging (beta) Completed...\\nDevice Detected: Nokia 1100 (Space Grey Varient)\\nBattery Percentage:` [100%](https://telegra.ph/file/a45aa7450c8eefed599d9.mp4) \", link_preview=True)\n\n\n@borg.on(admin_cmd(\"bigoof\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 7)\n await event.edit(\"â”â”â”â”┓╋╋╋╋â”â”â”â”┓ \\n┃â”â”┓┃╋╋╋╋┃â”â”┓┃ \\n┃┃╋┃┣┓â”┓â”┫┃╋┃┃ \\n┃┃╋┃┃┗┛┗┛┃┃╋┃┃ \\n┃┗â”┛┣┓â”┓â”┫┗â”┛┃ \\nâ”—â”â”â”┛┗┛┗┛┗â”â”â”â”›\")\n animation_chars = [\n \"â•â”â”â”╮╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”╯╰╯ \",\n \"â•â”â”â”╮╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃┃┃ \\n â•°â”â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\",\n \"â•â”â”â”╮╱╱╱╱╱╱╱╱╱â•â”â•® \\n┃â•â”╮┃╱╱╱╱╱╱╱╱╱┃â•â•¯ \\n┃┃╱┃┣â”â”┳â”â”┳â”â”┳╯╰╮ \\n┃┃╱┃┃â•â•®â”ƒâ•â•®â”ƒâ•â•®â”£â•®â•â•¯ \\n┃╰â”╯┃╰╯┃╰╯┃╰╯┃┃┃ \\nâ•°â”â”â”â”»â”â”â”»â”â”â”»â”â”╯╰╯\"\n ]\n \n for i in animation_ttl: \t\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 7])\n\n@borg.on(admin_cmd(pattern=\"g1 ?(.*)\"))\nasync def payf(event):\n paytext=event.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1,paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1, paytext*1)\n await event.edit(pay)\n\n@borg.on(admin_cmd(pattern=\"uff ?(.*)\")) \nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1 \n animation_ttl = range(0, 13) \n animation_chars = [\n \"U\",\n \"Uf\", \n \"Uff\",\n \"Ufffff\",\n \"Uffffff\",\n \"Ufffffff\",\n \"Uffffffff\",\n \"Ufffffffff\",\n \"Uffffffffff\", \n \"Ufffffffffff\",\n \"Uffffffffffff\",\n \"Ufffffffffffff\",\n \"Uffffffffffffff\"\n ]\n for i in animation_ttl: \t\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n@borg.on(admin_cmd(pattern=\"ctext ?(.*)\"))\nasync def payf(event):\n paytext=event.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2, paytext*8, paytext*8)\n await event.edit(pay)\n \n@borg.on(admin_cmd(pattern=\"ftext ?(.*)\"))\nasync def payf(event):\n paytext=event.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*8, paytext*8, paytext*2, paytext*2, paytext*2, paytext*6, paytext*6, paytext*2, paytext*2, paytext*2, paytext*2, paytext*2)\n await event.edit(pay) \n\n@borg.on(admin_cmd(outgoing=True, pattern=\"kf$(.*)\"))\nasync def _(event): \n r = random.randint(0, 3)\n logger.debug(r)\n if r == 0:\n await event.edit(\"â”â”â”â”┓\\n┃â”â”â”â”›\\n┃┗â”â”┓\\n┃â”â”â”â”›\\n┃┃\\nâ”—â”›\")\n else:\n r == 1 \n await event.edit(\"â•â”â”â”â•®\\n┃â•â”â”╯\\n┃╰â”â”â•®\\n┃â•â”â”╯\\n┃┃\\n╰╯\") \n\n@borg.on(admin_cmd(pattern=\"f (.*)\"))\nasync def payf(e):\n paytext = e.pattern_match.group(1)\n pay = \"{}\\n{}\\n{}\\n{}\\n{}\\n{}\\n{}\".format(paytext*5, paytext*1,paytext*1, paytext*4, paytext*1, paytext*1, paytext*1)\n await e.edit(pay)\n\n@borg.on(admin_cmd(pattern=f\"loading$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"â–®\",\n \"â–¯\",\n \"â–¬\",\n \"â–\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n@borg.on(admin_cmd(pattern=f\"square$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"â—§\",\n \"â—¨\",\n \"â—§\",\n \"â—¨\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n@borg.on(admin_cmd(pattern=f\"up$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"╹\",\n \"â•»\",\n \"╹\",\n \"â•»\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n \n@borg.on(admin_cmd(pattern=f\"round$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 20)\n animation_chars = [\n \"âš«\",\n \"⬤\",\n \"â—\",\n \"∘\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n@borg.on(admin_cmd(pattern=f\"hart$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 20)\n animation_chars = [\n \"🖤\",\n \"â¤ï¸\",\n \"🖤\",\n \"â¤ï¸\",\n \"‎\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 4])\n\n@borg.on(admin_cmd(pattern=f\"anim$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 11)\n animation_chars = [\n \"ðŸ˜\",\n \"😧\",\n \"😡\",\n \"😢\",\n \"‎**HellBoy Bolte Public**\",\n \"ðŸ˜\",\n \"😧\",\n \"😡\",\n \"😢\",\n \"[PAPA HERE](https://t.me/Kraken_The_BadASS)\",\n \"__**Good to See you Guys....**__\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n \n@borg.on(admin_cmd(pattern=f\"fnl$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = [\n \"ðŸ˜ðŸ¿\",\n \"ðŸ˜ðŸ¾\",\n \"ðŸ˜ðŸ½\",\n \"ðŸ˜ðŸ¼\",\n \"‎ðŸ˜\",\n \"**Good to See you Guys....**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n\n@borg.on(admin_cmd(pattern=f\"monkey$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 6)\n animation_chars = [\n \"ðŸµ\",\n \"🙉\",\n \"🙈\",\n \"🙊\",\n \"🖕‎ðŸµðŸ–•\",\n \"**Good to See you Guys....**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\n \n@borg.on(admin_cmd(pattern=f\"herber$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 2\n animation_ttl = range(0, 11)\n animation_chars = [\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 10%\\n\\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 5.9%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 8.13GB\\n **🔹used:** 33.77GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 158.98GB\\n **🔹recv:** 146.27GB\\n **🔹sent_packets:** 84518799\\n **🔹recv_packets:** 159720314\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 30%\\n\\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 20.4%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 7.18GB\\n **🔹used:** 28.26GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 146.27GB\\n **🔹recv:** 124.33GB\\n **🔹sent_packets:** 54635686\\n **🔹recv_packets:** 143565654\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 60%\\n\\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 60.9%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 6.52GB\\n **🔹used:** 35.78GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 124.33GB\\n **🔹recv:** 162.48GB\\n **🔹sent_packets:** 25655655\\n **🔹recv_packets:** 165289456\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 100%\\n\\n â—â—â—â—â—â—â—â—â—â—\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 100.0%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 9.81GB\\n **🔹used:** 30.11GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 162.48GB\\n **🔹recv:** 175.75GB\\n **🔹sent_packets:** 56565435\\n **🔹recv_packets:** 135345655\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 70%\\n\\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 80.4%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 5.76GB\\n **🔹used:** 29.35GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 175.75GB\\n **🔹recv:** 118.55GB\\n **🔹sent_packets:** 36547698\\n **🔹recv_packets:** 185466554\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 60%\\n\\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 62.9%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 8.23GB\\n **🔹used:** 33.32GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 118.55GB\\n **🔹recv:** 168.65GB\\n **🔹sent_packets:** 24786554\\n **🔹recv_packets:** 156745865\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 30%\\n\\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 30.6%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 9.75GB\\n **🔹used:** 36.54GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 168.65GB\\n **🔹recv:** 128.35GB\\n **🔹sent_packets:** 56565435\\n **🔹recv_packets:** 1475823589\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 10%\\n\\n â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 10.2%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 10.20GB\\n **🔹used:** 25.40GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 128.35GB\\n **🔹recv:** 108.31GB\\n **🔹sent_packets:** 54635686\\n **🔹recv_packets:** 157865426\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 100%\\n\\n â—â—â—â—â—â—â—â—â—â—\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 100.0%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 5.25GB\\n **🔹used:** 31.14GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—â—â—â—â—â—â—\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 108.31GB\\n **🔹recv:** 167.17GB\\n **🔹sent_packets:** 84518799\\n **🔹recv_packets:** 124575356\\n\\n\\n**===================**\\n\",\n \"**===================**\\n **Server Details** \\n**===================**\\n\\n\\n**=>>> CPU <<<=**\\n\\n **🔹current_freq:** 2500.09MHz\\n **🔹total_usage:** 70%\\n\\n â—â—â—â—â—â—â—â—‹â—‹â—‹\\n\\n **🔹cpu core**\\n\\n **🔹core_usage:** 76.2%\\n **🔹current_freq:** 2500.09MHz\\n |██████████▉ |\\n \\n**=>>> RAM <<<=**\\n\\n **🔹free:** 8.01GB\\n **🔹used:** 33.27GB\\n **🔹total:** 60.0GB\\n \\n â—â—â—â—‹â—‹â—‹â—‹â—‹â—‹â—‹\\n\\n\\n**=>>> DISK <<<=**\\n\\n **🔹free:** 224.12GB\\n **🔹used:** 131.84GB\\n **🔹total:** 375.02GB\\n **🔹usage:** 37.0%\\n\\n |████■|\\n\\n\\n**=>>> NETWORK <<<=**\\n\\n **🔹sent:** 167.17GB\\n **🔹recv:** 158.98GB\\n **🔹sent_packets:** 36547698\\n **🔹recv_packets:** 165455856\\n\\n\\n**===================**\\n\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\n\n@borg.on(admin_cmd(pattern=f\"hand$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 14)\n animation_chars = [\n \"👈\",\n \"👉\",\n \"â˜ï¸\",\n \"👆\",\n \"🖕\",\n \"👇\",\n \"✌ï¸\",\n \"🤞\",\n \"🖖\",\n \"🤘\",\n \"🤙\",\n \"ðŸ–ï¸\",\n \"👌\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 14])\n\n@borg.on(admin_cmd(pattern=f\"gsg$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 13)\n animation_chars = [\n \"🔟\",\n \"9ï¸âƒ£\",\n \"8ï¸âƒ£\",\n \"7ï¸âƒ£\",\n \"6ï¸âƒ£\",\n \"5ï¸âƒ£\",\n \"4ï¸âƒ£\",\n \"3ï¸âƒ£\",\n \"2ï¸âƒ£\",\n \"1ï¸âƒ£\",\n \"0ï¸âƒ£\",\n \"🆘\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 13])\n\n@borg.on(admin_cmd(pattern=r\"theart$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 54)\n animation_chars = [\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\",\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 18])\n\n \n@borg.on(admin_cmd(pattern=r\"fdance\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 5) \n await event.edit(\"Connecting..\")\n animation_chars = [\n \n \"⠀⠀⠀⣶⣿⣶\\n⠀⠀⠀⣿⣿⣿⣀\\n⠀⣀⣿⣿⣿⣿⣿⣿\\n⣶⣿⠛â£â£¿â£¿â£¿â£¿\\n⠛⠛⠛⣿⣿⣿⣿⠿\\n⠀⠀⠀⠀⣿⣿⣿\\n⠀⠀⣀â£â£¿â£¿â£¿â£¿â£€\\n⠀⠤⣿⣿⣿⣿⣿⣿⠉\\n⠀⣿⣿⣿⣿⣿⣿⠉\\n⣿⣿⣿⣿⣿⣿\\n⣿⣿⣶⣿⣿\\n⠉⠛⣿⣿⣶⣤\\n⠀⠀⠉⠿⣿⣿⣤\\n⠀⠀⣀⣤⣿⣿⣿\\n⠀⠒⠿⠛⠉⠿⣿\\n⠀⠀⠀⠀⠀⣀⣿⣿\\n⠀⠀⠀⠀⣶⠿⠿⠛\\n\",\n \"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣤\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿\\n⠀⠀⣶⠀⠀⣀⣤⣶⣤⣉⣿⣿⣤⣀\\n⠤⣤⣿⣤⣿⠿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣀\\n⠀⠛⠿⠀⠀⠀⠀⠉⣿⣿⣿⣿⣿⠉⠛⠿⣿⣤\\n⠀⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⠛⠀⠀⠀⣶⠿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣤⠀⣿⠿\\n⠀⠀⠀⠀⠀⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⠀⠀⠿⣿⣿⣿⣿⣿⠿⠉⠉\\n⠀⠀⠀⠀⠀⠀⠀⠉⣿⣿⣿⣿⠿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⠉\\n⠀⠀⠀⠀⠀⠀⠀⠀⣛⣿â£â£¶â£€\\n⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⣿\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣿⠀⠀⣿⣿\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀⣿⣉⠀⣶⠿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣶⣿⠿\\n⠀⠀⠀⠀⠀⠀⠀⠛⠿⠛\\n\",\n \"⠀⠀⠀⠀⠀⠀⠀⠀⠀⣤⣶\\n⠀⠀⠀⠀⠀⣀⣀⠀⣶⣿⣿⠶\\n⣶⣿⠿⣿⣿⣿⣿⣿⣿⣿⣿⣤⣤\\n⠀⠉⠶⣶⣀⣿⣿⣿⣿⣿⣿⣿⠿⣿⣤⣀\\n⠀⠀⠀⣿⣿⠿⠉⣿⣿⣿⣿â£â €â ¶â ¿â ¿\\n⠀⠀⠛⠛⠿⠀⠀⣿⣿⣿⣉⠿⣿⠶\\n⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⣿⣿⣿⣿⣿⣿⣿⠒\\n⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⣿⣿⣿⠛â£â£â ‰\\n⠀⠀⠀⠀⠀⣿⣿â£â£¤â£¿â ›\\n⠀⠀⠀⠀⠀⠛⠿⣿⣿⣿â£\\n⠀⠀⠀⠀⠀⠀⠀⣿⣿⠉⠛⠿⣶⣤\\n⠀⠀⠀⠀⠀⠀⣀⣿⠀⠀⣶⣶⠿⠿⠿\\n⠀⠀⠀⠀⠀⠀⣿⠛\\n⠀⠀⠀⠀⠀⠀â£â£¶\\n\",\n \"⠀⠀⠀⠀⠀⠀⣶⣿⣶\\n⠀⠀⠀⣤⣤⣤⣿⣿⣿\\n⠀⠀⣶⣿⣿⣿⣿⣿⣿⣿⣶\\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⣿\\n⠀⠀⣿⣉⣿⣿⣿⣿⣉⠉⣿⣶\\n⠀⠀⣿⣿⣿⣿⣿⣿⣿⣿⠿⣿\\n⠀⣤⣿⣿⣿⣿⣿⣿⣿⠿⠀⣿⣶\\n⣤⣿⠿⣿⣿⣿⣿⣿⠿⠀⠀⣿⣿⣤\\n⠉⠉⠀⣿⣿⣿⣿⣿⠀⠀⠒⠛⠿⠿⠿\\n⠀⠀⠀⠉⣿⣿⣿⠀⠀⠀⠀⠀⠀⠉\\n⠀⠀⠀⣿⣿⣿⣿⣿⣶\\n⠀⠀⠀⠀⣿⠉⠿⣿⣿\\n⠀⠀⠀⠀⣿⣤⠀⠛⣿⣿\\n⠀⠀⠀⠀⣶⣿⠀⠀⠀⣿⣶\\n⠀⠀⠀⠀⠀⠀⠀⠀⠀â£â£¿â£¿\\n⠀⠀⠀⠀⠀⠀⠀⠀⣤⣿⣿⠉\\n\",\n \"⠀⠀⠀⠀⠀⠀⣤⣶⣶\\n⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣀⣀\\n⠀⠀⠀⠀⠀⣀⣶⣿⣿⣿⣿⣿⣿\\n⣤⣶⣀⠿⠶⣿⣿⣿⠿⣿⣿⣿⣿\\n⠉⠿⣿⣿⠿⠛⠉⠀⣿⣿⣿⣿⣿\\n⠀⠀⠉⠀⠀⠀⠀⠀⠀⣿⣿⣿⣿⣤⣤\\n⠀⠀⠀⠀⠀⠀⠀⣤⣶⣿⣿⣿⣿⣿⣿\\n⠀⠀⠀⠀⠀⣀⣿⣿⣿⣿⣿⠿⣿⣿⣿⣿\\n⠀⠀⠀⠀⣀⣿⣿⣿⠿⠉⠀⠀⣿⣿⣿⣿\\n⠀⠀⠀⠀⣿⣿⠿⠉⠀⠀⠀⠀⠿⣿⣿⠛\\n⠀⠀⠀⠀⠛⣿⣿⣀⠀⠀⠀⠀⠀⣿⣿⣀\\n⠀⠀⠀⠀⠀⣿⣿⣿⠀⠀⠀⠀⠀⠿⣿⣿\\n⠀⠀⠀⠀⠀⠉⣿⣿⠀⠀⠀⠀⠀⠀⠉⣿\\n⠀⠀⠀⠀⠀⠀⠀⣿⠀⠀⠀⠀⠀⠀⣀⣿\\n⠀⠀⠀⠀⠀⠀⣀⣿⣿\\n⠀⠀⠀⠀⠤⣿⠿⠿⠿\\n\", \n\n\n ]\n\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 5]) \n@borg.on(admin_cmd(pattern=f\"snake$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 27)\n await event.edit(\"snake..\")\n animation_chars = [\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"‎◻ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—¼ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\",\n \"â—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—»ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—»ï¸â—»ï¸â—»ï¸â—»ï¸â—»ï¸\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 27]) \n \n \n@borg.on(admin_cmd(pattern=f\"human$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 16)\n await event.edit(\"human...\")\n animation_chars = [\n \n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛🚗\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛🚗⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛🚗⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🚗⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛🚗⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛🚗⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n🚗⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜😊⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬛⬜⬛\\n⬛⬛⬜⬛⬛⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬜⬜⬜⬜⬜⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬜⬛😊⬛⬜⬛\\n⬛⬛⬜⬜⬜⬛⬛\\n⬛⬛⬛⬜⬛⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬜⬛⬛⬛⬜⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\",\n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛😊⬛⬛⬛\\n⬛⬛⬜⬜⬜⬛⬛\\n⬛⬜⬛⬜⬛⬜⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n⬛⬛⬜⬛⬜⬛⬛\\n🔲🔲🔲🔲🔲🔲🔲\", \n \"⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜😊⬜⬜⬜\\n⬜⬜⬜⬜⬜⬜⬜\\n🔲🔲🔲🔲🔲🔲🔲\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16]) \n \n \n@borg.on(admin_cmd(pattern=f\"mc$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 28)\n await event.edit(\"mc..\")\n animation_chars = [\n\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—»ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—¼ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—»ï¸â—»ï¸â—»ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 28]) \n\t\t\n@borg.on(admin_cmd(pattern=\"virus$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 30)\n await event.edit(\"Injecting virus....\")\n animation_chars = [\n \"🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"‎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎🔴🔵🌕♓♎⛎◼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎🔴🔵🌕♓♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸ”´ðŸ”µðŸŒ•â™“♎⛎◼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸\",\n \"â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸\",\n \"â—¼ï¸\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n@borg.on(admin_cmd(pattern=r\"repe$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.2\n animation_ttl = range(0, 30)\n await event.edit(\"repe\")\n animation_chars = [\n \n \"**r**\",\n \"**ra**\",\n \"**rap**\",\n \"**rape**\",\n \"**rape_**\", \n \"**rape_t**\",\n \"**rape_tr**\",\n \"**rape_tra**\",\n \"**rape_trai**\",\n \"**rape_train**\",\n \"**ape_train🚅**\",\n \"**pe_train🚅🚃🚃**\",\n \"**e_train🚅🚃🚃🚃**\",\n \"**_train🚅🚃🚃🚃🚃**\",\n \"**train🚅🚃🚃🚃🚃🚃**\",\n \"**rain🚅🚃🚃🚃🚃🚃🚃**\",\n \"**ain🚅🚃🚃🚃🚃🚃🚃🚃**\",\n \"**in🚅🚃🚃🚃🚃🚃🚃🚃🚃**\",\n \"**n🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃**\",\n \"🚅🚃🚃🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃🚃\",\n \"🚃🚃🚃🚃\",\n \"🚃🚃🚃\",\n \"🚃🚃\",\n \"🚃\",\n \"**rApEd**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 30])\n\n@borg.on(admin_cmd(pattern=f\"isro$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 24)\n await event.edit(\"Connecting..\")\n animation_chars = [\n \n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n🚀⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛🚀⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛🚀⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🚀⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\", \n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛🚀⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛🚀\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"🛸⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n🛸⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛🛸⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛🛸⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛🛸⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\",\n \"⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛⬛\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸⬛🚶â€â™‚ï¸\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n👽⬛⬛🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛👽⬛🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛⬛⬛⬛⬛\\n⬛⬛👽🛸🚶â€â™‚ï¸â¬›\\n⬜⬜⬜⬜⬜⬜\",\n \"__Signal Lost....__\"\n\n ]\n\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 24])\t\n\n@borg.on(admin_cmd(pattern=f\"nakal$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 6)\n await event.edit(\"nakal\")\n animation_chars = [\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀⠀__⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀ ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Lavde ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀|__|⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀⠀⠀ ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Pehli ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀(P)⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Fursat ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀⠀__ ⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Meeee ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â €â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀|__| ⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\", \n \"`⠀⠀⠀⣠⣶⡾â ⠉⠙⠳⢦⡀⠀⠀⠀⢠⠞⠉⠙⠲⡀⠀\\n ⠀⣴⠿â ⠀⠀⠀⠀⠀ ⠀⢳⡀⠀â¡â €â € ⠀⢷\\n⢠⣟⣋⡀⢀⣀⣀⡀⠀⣀⡀⣧⠀⢸⠀ â € ⡇\\n⢸⣯â¡â ⠸⣛⣟⠆⡴⣻⡲⣿ ⣸ Nikal ⡇\\n ⣟⣿â¡â €â €â €â €â €â¢±â € ⣿ ⢹⠀ ⡇\\n ⠙⢿⣯⠄⠀⠀lodu⠀⠀⡿ ⠀⡇⠀⠀⠀⠀ ⡼\\n⠀⠀⠀⠹⣶⠆⠀⠀⠀⠀⠀⡴⠃⠀ ⠘⠤⣄⣠⠞⠀\\n⠀⠀⠀⠀⢸⣷⡦⢤⡤⢤⣞â£â €â €â €â €â €â €â €â €â €â €\\n⠀⢀⣤⣴⣿â£â ⠀⠀⠸â£â¢¯â£·â£–⣦⡀⠀⠀⠀⠀⠀⠀\\n⢀⣾⣽⣿⣿⣿⣿⠛⢲⣶⣾⢉⡷⣿⣿⠵⣿⠀⠀⠀⠀⠀⠀\\n⣼⣿â ⠉⣿â¡â ‰â ™â¢ºâ£‡â£¼â¡â €â € ⠀⣄⢸⠀⠀⠀⠀⠀⠀`\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 6])\t\n\t\t\n@borg.on(admin_cmd(pattern=f\"music$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.5\n animation_ttl = range(0, 11)\n await event.edit(\"starting player...\")\n animation_chars = [\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:00** ▱▱▱▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â–¶ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:01** ▰▱▱▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:02** ▰▰▱▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤⬤ 81% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:03** ▰▰▰▱▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀ [Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:04** ▰▰▰▰▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:05** ▰▰▰▰▱▱▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\", \n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:06** ▰▰▰▰▰▰▱▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:07** ▰▰▰▰▰▰▰▱▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:08** ▰▰▰▰▰▰▰▰▱▱ **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:09** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–± **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `â¸ï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\",\n \"⬤⬤◯ 80% ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀`✖ï¸`\\n\\n⠀⠀⠀⠀⠀[Survivor Music Player](tg://user?id=916234223)\\n\\n⠀⠀⠀⠀**Now Playing:shape of u**\\n\\n**00:10** â–°â–°â–°â–°â–°â–°â–°â–°â–°â–° **00:10**\\n\\n⠀⠀⠀⠀⠀`🔂` `â®ï¸` `âªï¸` `âºï¸` `â©ï¸` `âï¸`\\n\\n**â €Next Song:** __Alan Walker - Alone.__\\n\\n⠀⠀⠀⠀**â €Device: Nokia 1100**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 11])\t\t\n\n@borg.on(admin_cmd(pattern=f\"squ$\",outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n\n\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n \\tâ–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ \\tâ–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\") \n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1) \n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(1)\n await event.edit(\"â•”â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•— \\n â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ â–‘ \\nâ•šâ•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•â•\")\n await asyncio.sleep(6)\t\n\t\n@borg.on(admin_cmd(pattern=r\"star$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🦋✨🦋✨🦋✨🦋✨\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\t\t\n@borg.on(admin_cmd(pattern=r\"boxs\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🟥🟧🟨🟩🟦🟪🟫⬛⬜\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\t\t\n@borg.on(admin_cmd(pattern=f\"rain$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🌬â˜ï¸ðŸŒ©ðŸŒ¨ðŸŒ§ðŸŒ¦ðŸŒ¥â›…🌤\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\n@borg.on(admin_cmd(pattern=r\"clol$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🤔ðŸ§ðŸ¤¨ðŸ¤”ðŸ§ðŸ¤¨\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\t\n\n@borg.on(admin_cmd(pattern=r\"odra$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"🚶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒðŸš¶ðŸƒ\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\t\n\t\t\n@borg.on(admin_cmd(pattern=r\"deploy$\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 3\n animation_ttl = range(0, 12)\n await event.edit(\"Deploying...\")\n animation_chars = [\n \n \"**Heroku Connecting To Latest Github Build **\",\n f\"**Build started by user** @Kraken_The_BadASS\",\n f\"**Deploy** `535a74f0` for user by my master!!\",\n \"**Restarting Heroku Server...**\",\n \"**State changed from up to starting**\", \n \"**Stopping all processes with SIGTERM**\",\n \"**Process exited with** `status 143`\",\n \"**Starting process with command** `python3 -m stdborg`\",\n \"**State changed from starting to up**\",\n \"__INFO:Userbot:Logged in as 557667062__\",\n \"__INFO:Userbot:Successfully loaded all plugins__\",\n \"**Build Succeeded**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12]) \n\n\n@borg.on(admin_cmd(pattern=\"dump ?(.*)\"))\nasync def _(message):\n try:\n obj = message.pattern_match.group(1)\n if len(obj) != 3:\n raise IndexError\n inp = ' '.join(obj)\n except IndexError:\n inp = \"🥞 🎂 ðŸ«\"\n u, t, g, o, s, n = inp.split(), '🗑', '<(^_^ <)', '(> ^_^)>', 'â € ', '\\n'\n h = [(u[0], u[1], u[2]), (u[0], u[1], ''), (u[0], '', '')]\n for something in reversed([y for y in ([''.join(x) for x in (\n f + (s, g, s + s * f.count(''), t), f + (g, s * 2 + s * f.count(''), t),\n f[:i] + (o, f[i], s * 2 + s * f.count(''), t), f[:i] + (s + s * f.count(''), o, f[i], s, t),\n f[:i] + (s * 2 + s * f.count(''), o, f[i], t), f[:i] + (s * 3 + s * f.count(''), o, t),\n f[:i] + (s * 3 + s * f.count(''), g, t))] for i, f in enumerate(reversed(h)))]):\n for something_else in something:\n await asyncio.sleep(0.3)\n try:\n await message.edit(something_else)\n except errors.MessageIdInvalidError:\n return\n\t\n@borg.on(admin_cmd(pattern=\"fleaveme$\"))\nasync def _(event):\n animation_interval = 1\n animation_ttl = range(0, 10)\n animation_chars = [\n \n \"⬛⬛⬛\\n⬛⬛⬛\\n⬛⬛⬛\",\n \"⬛⬛⬛\\n⬛🔄⬛\\n⬛⬛⬛\",\n \"⬛⬆ï¸â¬›\\n⬛🔄⬛\\n⬛⬛⬛\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄⬛\\n⬛⬛⬛\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n⬛⬛⬛\", \n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n⬛⬛↘ï¸\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n⬛⬇ï¸â†˜ï¸\",\n \"⬛⬆ï¸â†—ï¸\\n⬛🔄➡ï¸\\n↙ï¸â¬‡ï¸â†˜ï¸\",\n \"⬛⬆ï¸â†—ï¸\\n⬅ï¸ðŸ”„âž¡ï¸\\n↙ï¸â¬‡ï¸â†˜ï¸\",\n \"↖ï¸â¬†ï¸â†—ï¸\\n⬅ï¸ðŸ”„âž¡ï¸\\n↙ï¸â¬‡ï¸â†˜ï¸\"\n ]\n if event.fwd_from:\n return\n await event.edit(\"fleaveme....\")\n await asyncio.sleep(2)\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 10])\n\t\t\n@borg.on(admin_cmd(pattern=\"loveu\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.5\n animation_ttl = range(0, 70)\n await event.edit(\"loveu\")\n animation_chars = [\n \"😀\",\n \"👩â€ðŸŽ¨\",\n \"ðŸ˜\", \n \"😂\",\n \"🤣\",\n \"😃\",\n \"😄\",\n \"😅\",\n \"😊\",\n \"☺\",\n \"🙂\", \n \"🤔\",\n \"🤨\",\n \"ðŸ˜\",\n \"😑\",\n \"😶\",\n \"😣\",\n \"😥\",\n \"😮\", \n \"ðŸ¤\",\n \"😯\",\n \"😴\",\n \"😔\",\n \"😕\",\n \"☹\",\n \"ðŸ™\",\n \"😖\", \n \"😞\",\n \"😟\",\n \"😢\",\n \"ðŸ˜\",\n \"🤯\",\n \"💔\",\n \"â¤\",\n \"i Love Youâ¤\", \n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 35])\n \n@borg.on(admin_cmd(pattern=f\"plane\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n retun\n await event.edit(\"✈-------------\")\n await event.edit(\"-✈------------\")\n await event.edit(\"--✈-----------\")\n await event.edit(\"---✈----------\")\n await event.edit(\"----✈---------\")\n await event.edit(\"-----✈--------\")\n await event.edit(\"------✈-------\")\n await event.edit(\"-------✈------\")\n await event.edit(\"--------✈-----\") \n await event.edit(\"---------✈----\")\n await event.edit(\"----------✈---\")\n await event.edit(\"-----------✈--\")\n await event.edit(\"------------✈-\")\n await event.edit(\"-------------✈\")\n await asyncio.sleep(3)\n await event.delete() \n \n \n@borg.on(admin_cmd(pattern=r\"pulis\"))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.3\n animation_ttl = range(0, 12)\n await event.edit(\"Pulis\")\n animation_chars = [\n \n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\", \n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n \"🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\\n🔵🔵🔵⬜⬜⬜🔴🔴🔴\",\n \"🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\\n🔴🔴🔴⬜⬜⬜🔵🔵🔵\",\n f\"{DEFAULTUSER} **Police iz Here**\"\n\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 12]) \n\n\t\n@borg.on(admin_cmd(pattern=f\"jio$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1\n animation_ttl = range(0, 19)\n await event.edit(\"jio network boosting...\")\n animation_chars = [\n \"`Connecting To JIO NETWORK ....`\",\n \"`â–ˆ â–‡ â–† â–… â–„ â–‚ â–`\",\n \"`â–’ â–‡ â–† â–… â–„ â–‚ â–`\",\n \"`â–’ â–’ â–† â–… â–„ â–‚ â–`\",\n \"`â–’ â–’ â–’ â–… â–„ â–‚ â–`\", \n \"`â–’ â–’ â–’ â–’ â–„ â–‚ â–`\",\n \"`â–’ â–’ â–’ â–’ â–’ â–‚ â–`\",\n \"`â–’ â–’ â–’ â–’ â–’ â–’ â–`\",\n \"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`\",\n \"*Optimising JIO NETWORK...*\",\n \"`â–’ â–’ â–’ â–’ â–’ â–’ â–’`\",\n \"`â– â–’ â–’ â–’ â–’ â–’ â–’`\", \n \"`â– â–‚ â–’ â–’ â–’ â–’ â–’`\",\n \"`â– â–‚ â–„ â–’ â–’ â–’ â–’`\",\n \"`â– â–‚ â–„ â–… â–’ â–’ â–’`\",\n \"`â– â–‚ â–„ â–… â–† â–’ â–’`\",\n \"`â– â–‚ â–„ â–… â–† â–‡ â–’`\",\n \"`â– â–‚ â–„ â–… â–† â–‡ â–ˆ`\",\n \"**JIO NETWORK Boosted....**\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 19]) \n \n \n@borg.on(admin_cmd(pattern=f\"solarsystem\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 80)\n await event.edit(\"solarsystem\")\n animation_chars = [\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n🌕◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â˜€\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\", \n \"`â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\n☀◼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸`\",\n \"`â—¼ï¸â˜€â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸ðŸŒ•â—¼ï¸`\",\n \"`â—¼ï¸â—¼ï¸â—¼ï¸â˜€â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸ðŸŒŽâ—¼ï¸â—¼ï¸\\nâ—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸â—¼ï¸\\nâ—¼ï¸ðŸŒ•â—¼ï¸â—¼ï¸â—¼ï¸`\",\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n\n@borg.on(admin_cmd(pattern=r\"lul$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"😂🤣😂🤣😂🤣\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\n \n@borg.on(admin_cmd(pattern=r\"nothappy$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜â˜¹ï¸ðŸ˜\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n\t\t\n@borg.on(admin_cmd(outgoing=True, pattern=\"clock$\"))\nasync def _(event):\n\t if event.fwd_from:\n\t\t return\n\t deq = deque(list(\"🕙🕘🕗🕖🕕🕔🕓🕒🕑ðŸ•ðŸ•›\"))\n\t for _ in range(48):\n\t\t await asyncio.sleep(0.1)\n\t\t await event.edit(\"\".join(deq))\n\t\t deq.rotate(1)\n \n@borg.on(admin_cmd(pattern=r\"muah$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"😗😙😚😚😘\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\n \n@borg.on(admin_cmd(pattern=\"heart$\"))\t\t\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"â¤ï¸ðŸ§¡ðŸ’›ðŸ’šðŸ’™ðŸ’œðŸ–¤\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1) \n \n\t\t\n@borg.on(admin_cmd(pattern=\"gym$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€ðŸƒâ€ðŸ‹â€ðŸ¤¸â€\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n \n@borg.on(admin_cmd(pattern=f\"earth$\", outgoing=True))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸŒðŸŒðŸŒŽðŸŒŽðŸŒðŸŒðŸŒðŸŒŽ\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\n \n@borg.on(admin_cmd(outgoing=True, pattern=\"moon$\"))\nasync def _(event):\n\t if event.fwd_from:\n\t\t return\n\t deq = deque(list(\"🌗🌘🌑🌒🌓🌔🌕🌖\"))\n\t for _ in range(48):\n\t\t await asyncio.sleep(0.1)\n\t\t await event.edit(\"\".join(deq))\n\t\t deq.rotate(1)\n\t\t\t\n@borg.on(admin_cmd(pattern=r\"candy$\"))\nasync def _(event):\n\tif event.fwd_from:\n\t\treturn\n\tdeq = deque(list(\"ðŸ¦ðŸ§ðŸ©ðŸªðŸŽ‚ðŸ°ðŸ§ðŸ«ðŸ¬ðŸ\"))\n\tfor _ in range(48):\n\t\tawait asyncio.sleep(0.1)\n\t\tawait event.edit(\"\".join(deq))\n\t\tdeq.rotate(1)\t\t\t\n \n@borg.on(admin_cmd(pattern=f\"smoon$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 101)\n await event.edit(\"smoon..\")\n animation_chars = [\n\n \"🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\",\n \"🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\", \n \"🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\",\n \"🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\",\n \"🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\\n🌗🌗🌗🌗🌗\\n🌓🌓🌓🌓🌓\",\n \"🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\\n🌘🌘🌘🌘🌘\\n🌔🌔🌔🌔🌔\",\n \"🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\\n🌑🌑🌑🌑🌑\\n🌕🌕🌕🌕🌕\",\n \"🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\\n🌒🌒🌒🌒🌒\\n🌖🌖🌖🌖🌖\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 8])\n \n@borg.on(admin_cmd(pattern=f\"tmoon$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.1\n animation_ttl = range(0, 117)\n await event.edit(\"tmoon\")\n animation_chars = [\n\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\",\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\",\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\",\n \"🌗\",\n \"🌘\", \n \"🌑\",\n \"🌒\",\n \"🌓\",\n \"🌔\",\n \"🌕\",\n \"🌖\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 32])\n\n@borg.on(admin_cmd(pattern=f\"clown$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 0.50\n animation_ttl = range(0, 16)\n animation_chars = [\n \n\n \"COMMAND CREATE BY @Kraken_The_BadASS\",\n \"🤡ï¸\",\n \"🤡🤡\",\n \"🤡🤡🤡\",\n \"🤡🤡🤡🤡\",\n \"🤡🤡🤡🤡🤡\",\n \"🤡🤡🤡🤡🤡🤡\", \n \"🤡🤡🤡🤡🤡\",\n \"🤡🤡🤡🤡\",\n \"🤡🤡🤡\",\n \"🤡🤡\",\n \"🤡\",\n \"You\",\n \"You Are\",\n \"You Are A\",\n \"You Are A Clown 🤡\"\n ]\n\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 16])\n\n@borg.on(admin_cmd(pattern=r\"aheart$\", outgoing=True))\nasync def _(event):\n if event.fwd_from:\n return\n animation_interval = 1.3\n animation_ttl = range(0, 50)\n animation_chars = [\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\",\n \"💔\",\n \"â¤ï¸\",\n \"🧡\",\n \"💛\",\n \"💚\",\n \"💙\",\n \"💜\",\n \"🖤\",\n \"💘\",\n \"ðŸ’\",\n \"💔\"\n ]\n for i in animation_ttl:\n await asyncio.sleep(animation_interval)\n await event.edit(animation_chars[i % 20]) \n \n \n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
print('rap.sweeps.data_management level init')
<|reserved_special_token_1|>
print("rap.sweeps.data_management level init")
|
flexible
|
{
"blob_id": "7d138a0ad7e4d8f7047dd73ae503bdc7ae5aa065",
"index": 9801,
"step-1": "<mask token>\n",
"step-2": "print('rap.sweeps.data_management level init')\n",
"step-3": "print(\"rap.sweeps.data_management level init\")",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
#!/usr/bin/env python
#
# Copyright (C) 2016 The Android Open Source Project
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import os
import unittest
from vts.utils.python.archive import archive_parser
class ArchiveParserTest(unittest.TestCase):
"""Unit tests for archive_parser of vts.utils.python.archive.
"""
def testReadHeaderPass(self):
"""Tests that archive is read when header is correct.
Parses archive content containing only the signature.
"""
try:
archive = archive_parser.Archive(archive_parser.Archive.GLOBAL_SIG)
archive.Parse()
except ValueError:
self.fail('Archive reader read improperly.')
def testReadHeaderFail(self):
"""Tests that parser throws error when header is invalid.
Parses archive content lacking the correct signature.
"""
archive = archive_parser.Archive('Fail.')
self.assertRaises(ValueError, archive.Parse)
def testReadFile(self):
"""Tests that file is read correctly.
Tests that correctly formatted file in archive is read correctly.
"""
content = archive_parser.Archive.GLOBAL_SIG
file_name = 'test_file'
content += file_name + ' ' * (archive_parser.Archive.FILE_ID_LENGTH -
len(file_name))
content += ' ' * archive_parser.Archive.FILE_TIMESTAMP_LENGTH
content += ' ' * archive_parser.Archive.OWNER_ID_LENGTH
content += ' ' * archive_parser.Archive.GROUP_ID_LENGTH
content += ' ' * archive_parser.Archive.FILE_MODE_LENGTH
message = 'test file contents'
message_size = str(len(message))
content += message_size + ' ' * (archive_parser.Archive.CONTENT_SIZE_LENGTH -
len(message_size))
content += archive_parser.Archive.END_TAG
content += message
archive = archive_parser.Archive(content)
archive.Parse()
self.assertIn(file_name, archive.files)
self.assertEquals(archive.files[file_name], message)
if __name__ == "__main__":
unittest.main()
|
normal
|
{
"blob_id": "2ea335dd8d879731aad7713499440db6d1f60d36",
"index": 2427,
"step-1": "<mask token>\n\n\nclass ArchiveParserTest(unittest.TestCase):\n <mask token>\n <mask token>\n <mask token>\n\n def testReadFile(self):\n \"\"\"Tests that file is read correctly.\n\n Tests that correctly formatted file in archive is read correctly.\n \"\"\"\n content = archive_parser.Archive.GLOBAL_SIG\n file_name = 'test_file'\n content += file_name + ' ' * (archive_parser.Archive.FILE_ID_LENGTH -\n len(file_name))\n content += ' ' * archive_parser.Archive.FILE_TIMESTAMP_LENGTH\n content += ' ' * archive_parser.Archive.OWNER_ID_LENGTH\n content += ' ' * archive_parser.Archive.GROUP_ID_LENGTH\n content += ' ' * archive_parser.Archive.FILE_MODE_LENGTH\n message = 'test file contents'\n message_size = str(len(message))\n content += message_size + ' ' * (archive_parser.Archive.\n CONTENT_SIZE_LENGTH - len(message_size))\n content += archive_parser.Archive.END_TAG\n content += message\n archive = archive_parser.Archive(content)\n archive.Parse()\n self.assertIn(file_name, archive.files)\n self.assertEquals(archive.files[file_name], message)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass ArchiveParserTest(unittest.TestCase):\n <mask token>\n\n def testReadHeaderPass(self):\n \"\"\"Tests that archive is read when header is correct.\n\n Parses archive content containing only the signature.\n \"\"\"\n try:\n archive = archive_parser.Archive(archive_parser.Archive.GLOBAL_SIG)\n archive.Parse()\n except ValueError:\n self.fail('Archive reader read improperly.')\n <mask token>\n\n def testReadFile(self):\n \"\"\"Tests that file is read correctly.\n\n Tests that correctly formatted file in archive is read correctly.\n \"\"\"\n content = archive_parser.Archive.GLOBAL_SIG\n file_name = 'test_file'\n content += file_name + ' ' * (archive_parser.Archive.FILE_ID_LENGTH -\n len(file_name))\n content += ' ' * archive_parser.Archive.FILE_TIMESTAMP_LENGTH\n content += ' ' * archive_parser.Archive.OWNER_ID_LENGTH\n content += ' ' * archive_parser.Archive.GROUP_ID_LENGTH\n content += ' ' * archive_parser.Archive.FILE_MODE_LENGTH\n message = 'test file contents'\n message_size = str(len(message))\n content += message_size + ' ' * (archive_parser.Archive.\n CONTENT_SIZE_LENGTH - len(message_size))\n content += archive_parser.Archive.END_TAG\n content += message\n archive = archive_parser.Archive(content)\n archive.Parse()\n self.assertIn(file_name, archive.files)\n self.assertEquals(archive.files[file_name], message)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass ArchiveParserTest(unittest.TestCase):\n \"\"\"Unit tests for archive_parser of vts.utils.python.archive.\n \"\"\"\n\n def testReadHeaderPass(self):\n \"\"\"Tests that archive is read when header is correct.\n\n Parses archive content containing only the signature.\n \"\"\"\n try:\n archive = archive_parser.Archive(archive_parser.Archive.GLOBAL_SIG)\n archive.Parse()\n except ValueError:\n self.fail('Archive reader read improperly.')\n\n def testReadHeaderFail(self):\n \"\"\"Tests that parser throws error when header is invalid.\n\n Parses archive content lacking the correct signature.\n \"\"\"\n archive = archive_parser.Archive('Fail.')\n self.assertRaises(ValueError, archive.Parse)\n\n def testReadFile(self):\n \"\"\"Tests that file is read correctly.\n\n Tests that correctly formatted file in archive is read correctly.\n \"\"\"\n content = archive_parser.Archive.GLOBAL_SIG\n file_name = 'test_file'\n content += file_name + ' ' * (archive_parser.Archive.FILE_ID_LENGTH -\n len(file_name))\n content += ' ' * archive_parser.Archive.FILE_TIMESTAMP_LENGTH\n content += ' ' * archive_parser.Archive.OWNER_ID_LENGTH\n content += ' ' * archive_parser.Archive.GROUP_ID_LENGTH\n content += ' ' * archive_parser.Archive.FILE_MODE_LENGTH\n message = 'test file contents'\n message_size = str(len(message))\n content += message_size + ' ' * (archive_parser.Archive.\n CONTENT_SIZE_LENGTH - len(message_size))\n content += archive_parser.Archive.END_TAG\n content += message\n archive = archive_parser.Archive(content)\n archive.Parse()\n self.assertIn(file_name, archive.files)\n self.assertEquals(archive.files[file_name], message)\n\n\nif __name__ == '__main__':\n unittest.main()\n",
"step-4": "import os\nimport unittest\nfrom vts.utils.python.archive import archive_parser\n\n\nclass ArchiveParserTest(unittest.TestCase):\n \"\"\"Unit tests for archive_parser of vts.utils.python.archive.\n \"\"\"\n\n def testReadHeaderPass(self):\n \"\"\"Tests that archive is read when header is correct.\n\n Parses archive content containing only the signature.\n \"\"\"\n try:\n archive = archive_parser.Archive(archive_parser.Archive.GLOBAL_SIG)\n archive.Parse()\n except ValueError:\n self.fail('Archive reader read improperly.')\n\n def testReadHeaderFail(self):\n \"\"\"Tests that parser throws error when header is invalid.\n\n Parses archive content lacking the correct signature.\n \"\"\"\n archive = archive_parser.Archive('Fail.')\n self.assertRaises(ValueError, archive.Parse)\n\n def testReadFile(self):\n \"\"\"Tests that file is read correctly.\n\n Tests that correctly formatted file in archive is read correctly.\n \"\"\"\n content = archive_parser.Archive.GLOBAL_SIG\n file_name = 'test_file'\n content += file_name + ' ' * (archive_parser.Archive.FILE_ID_LENGTH -\n len(file_name))\n content += ' ' * archive_parser.Archive.FILE_TIMESTAMP_LENGTH\n content += ' ' * archive_parser.Archive.OWNER_ID_LENGTH\n content += ' ' * archive_parser.Archive.GROUP_ID_LENGTH\n content += ' ' * archive_parser.Archive.FILE_MODE_LENGTH\n message = 'test file contents'\n message_size = str(len(message))\n content += message_size + ' ' * (archive_parser.Archive.\n CONTENT_SIZE_LENGTH - len(message_size))\n content += archive_parser.Archive.END_TAG\n content += message\n archive = archive_parser.Archive(content)\n archive.Parse()\n self.assertIn(file_name, archive.files)\n self.assertEquals(archive.files[file_name], message)\n\n\nif __name__ == '__main__':\n unittest.main()\n",
"step-5": "#!/usr/bin/env python\n#\n# Copyright (C) 2016 The Android Open Source Project\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n#\n\nimport os\nimport unittest\n\nfrom vts.utils.python.archive import archive_parser\n\n\nclass ArchiveParserTest(unittest.TestCase):\n \"\"\"Unit tests for archive_parser of vts.utils.python.archive.\n \"\"\"\n\n def testReadHeaderPass(self):\n \"\"\"Tests that archive is read when header is correct.\n\n Parses archive content containing only the signature.\n \"\"\"\n try:\n archive = archive_parser.Archive(archive_parser.Archive.GLOBAL_SIG)\n archive.Parse()\n except ValueError:\n self.fail('Archive reader read improperly.')\n\n def testReadHeaderFail(self):\n \"\"\"Tests that parser throws error when header is invalid.\n\n Parses archive content lacking the correct signature.\n \"\"\"\n archive = archive_parser.Archive('Fail.')\n self.assertRaises(ValueError, archive.Parse)\n\n def testReadFile(self):\n \"\"\"Tests that file is read correctly.\n\n Tests that correctly formatted file in archive is read correctly.\n \"\"\"\n content = archive_parser.Archive.GLOBAL_SIG\n file_name = 'test_file'\n content += file_name + ' ' * (archive_parser.Archive.FILE_ID_LENGTH -\n len(file_name))\n content += ' ' * archive_parser.Archive.FILE_TIMESTAMP_LENGTH\n content += ' ' * archive_parser.Archive.OWNER_ID_LENGTH\n content += ' ' * archive_parser.Archive.GROUP_ID_LENGTH\n content += ' ' * archive_parser.Archive.FILE_MODE_LENGTH\n\n message = 'test file contents'\n message_size = str(len(message))\n content += message_size + ' ' * (archive_parser.Archive.CONTENT_SIZE_LENGTH -\n len(message_size))\n content += archive_parser.Archive.END_TAG\n content += message\n archive = archive_parser.Archive(content)\n archive.Parse()\n self.assertIn(file_name, archive.files)\n self.assertEquals(archive.files[file_name], message)\n\nif __name__ == \"__main__\":\n unittest.main()\n",
"step-ids": [
2,
3,
6,
7,
8
]
}
|
[
2,
3,
6,
7,
8
] |
import sqlite3
import pandas as pd
#%matplotlib inline
import matplotlib.pyplot as plt
db_filename = 'readonly/dinofunworld.db'
conn = sqlite3.connect(db_filename)
c = conn.cursor()
c.execute("SELECT a.Name, count(c.visitorID) \
FROM attraction as a, checkin c \
WHERE \
a.AttractionID = c.attraction \
AND a.Category like 'Thrill Rides%' \
GROUP BY a.AttractionID \
")
thrillRidesVisitsResult = c.fetchall()
print(thrillRidesVisitsResult)
thrillRidesVisitsDataFrame = pd.DataFrame.from_records(thrillRidesVisitsResult, columns=['ride_name', 'visits_count'])
c.close()
plt.pie(thrillRidesVisitsDataFrame['visits_count'], labels=thrillRidesVisitsDataFrame['ride_name'], autopct='%1.1f%%', shadow=False)
plt.axis('equal')
plt.show()
|
normal
|
{
"blob_id": "c19c3f580d7555379bd7e077b0264a3784179e93",
"index": 696,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nc.execute(\n \"SELECT a.Name, count(c.visitorID) FROM attraction as a, checkin c WHERE a.AttractionID = c.attraction AND a.Category like 'Thrill Rides%' GROUP BY a.AttractionID \"\n )\n<mask token>\nprint(thrillRidesVisitsResult)\n<mask token>\nc.close()\nplt.pie(thrillRidesVisitsDataFrame['visits_count'], labels=\n thrillRidesVisitsDataFrame['ride_name'], autopct='%1.1f%%', shadow=False)\nplt.axis('equal')\nplt.show()\n",
"step-3": "<mask token>\ndb_filename = 'readonly/dinofunworld.db'\nconn = sqlite3.connect(db_filename)\nc = conn.cursor()\nc.execute(\n \"SELECT a.Name, count(c.visitorID) FROM attraction as a, checkin c WHERE a.AttractionID = c.attraction AND a.Category like 'Thrill Rides%' GROUP BY a.AttractionID \"\n )\nthrillRidesVisitsResult = c.fetchall()\nprint(thrillRidesVisitsResult)\nthrillRidesVisitsDataFrame = pd.DataFrame.from_records(thrillRidesVisitsResult,\n columns=['ride_name', 'visits_count'])\nc.close()\nplt.pie(thrillRidesVisitsDataFrame['visits_count'], labels=\n thrillRidesVisitsDataFrame['ride_name'], autopct='%1.1f%%', shadow=False)\nplt.axis('equal')\nplt.show()\n",
"step-4": "import sqlite3\nimport pandas as pd\nimport matplotlib.pyplot as plt\ndb_filename = 'readonly/dinofunworld.db'\nconn = sqlite3.connect(db_filename)\nc = conn.cursor()\nc.execute(\n \"SELECT a.Name, count(c.visitorID) FROM attraction as a, checkin c WHERE a.AttractionID = c.attraction AND a.Category like 'Thrill Rides%' GROUP BY a.AttractionID \"\n )\nthrillRidesVisitsResult = c.fetchall()\nprint(thrillRidesVisitsResult)\nthrillRidesVisitsDataFrame = pd.DataFrame.from_records(thrillRidesVisitsResult,\n columns=['ride_name', 'visits_count'])\nc.close()\nplt.pie(thrillRidesVisitsDataFrame['visits_count'], labels=\n thrillRidesVisitsDataFrame['ride_name'], autopct='%1.1f%%', shadow=False)\nplt.axis('equal')\nplt.show()\n",
"step-5": "import sqlite3\nimport pandas as pd\n#%matplotlib inline\nimport matplotlib.pyplot as plt\n\ndb_filename = 'readonly/dinofunworld.db'\nconn = sqlite3.connect(db_filename)\nc = conn.cursor()\nc.execute(\"SELECT a.Name, count(c.visitorID) \\\nFROM attraction as a, checkin c \\\nWHERE \\\na.AttractionID = c.attraction \\\nAND a.Category like 'Thrill Rides%' \\\nGROUP BY a.AttractionID \\\n\")\nthrillRidesVisitsResult = c.fetchall()\nprint(thrillRidesVisitsResult)\nthrillRidesVisitsDataFrame = pd.DataFrame.from_records(thrillRidesVisitsResult, columns=['ride_name', 'visits_count'])\nc.close()\nplt.pie(thrillRidesVisitsDataFrame['visits_count'], labels=thrillRidesVisitsDataFrame['ride_name'], autopct='%1.1f%%', shadow=False)\nplt.axis('equal')\nplt.show()",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
application = Application('./', ['local.ini', 'production.ini'], server=
'main', logging='prodlogging.ini')
<|reserved_special_token_1|>
from __future__ import unicode_literals
from moya.wsgi import Application
application = Application('./', ['local.ini', 'production.ini'], server=
'main', logging='prodlogging.ini')
<|reserved_special_token_1|>
# encoding=UTF-8
# This file serves the project in production
# See http://wsgi.readthedocs.org/en/latest/
from __future__ import unicode_literals
from moya.wsgi import Application
application = Application(
"./", ["local.ini", "production.ini"], server="main", logging="prodlogging.ini"
)
|
flexible
|
{
"blob_id": "cb0be932813a144cfb51b3aa2f6e0792e49c4945",
"index": 3021,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napplication = Application('./', ['local.ini', 'production.ini'], server=\n 'main', logging='prodlogging.ini')\n",
"step-3": "from __future__ import unicode_literals\nfrom moya.wsgi import Application\napplication = Application('./', ['local.ini', 'production.ini'], server=\n 'main', logging='prodlogging.ini')\n",
"step-4": "# encoding=UTF-8\n\n# This file serves the project in production\n# See http://wsgi.readthedocs.org/en/latest/\n\nfrom __future__ import unicode_literals\nfrom moya.wsgi import Application\n\napplication = Application(\n \"./\", [\"local.ini\", \"production.ini\"], server=\"main\", logging=\"prodlogging.ini\"\n)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
for word in arr:
for a in word:
if a not in alphabet:
alphabet.append(a)
<|reserved_special_token_0|>
for a in alphabet:
value = 0
for word in arr:
if a not in word:
continue
s = ''
for w in word:
s += '1' if w == a else '0'
value += int(s)
value_list.append(value)
value_list.sort(reverse=True)
<|reserved_special_token_0|>
for s in value_list:
answer += value * s
value -= 1
print(answer)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
input = sys.stdin.readline
N = int(input())
arr = [list(input().strip()) for _ in range(N)]
alphabet = []
for word in arr:
for a in word:
if a not in alphabet:
alphabet.append(a)
value_list = []
for a in alphabet:
value = 0
for word in arr:
if a not in word:
continue
s = ''
for w in word:
s += '1' if w == a else '0'
value += int(s)
value_list.append(value)
value_list.sort(reverse=True)
answer = 0
value = 9
for s in value_list:
answer += value * s
value -= 1
print(answer)
<|reserved_special_token_1|>
<|reserved_special_token_0|>
import sys
input = sys.stdin.readline
N = int(input())
arr = [list(input().strip()) for _ in range(N)]
alphabet = []
for word in arr:
for a in word:
if a not in alphabet:
alphabet.append(a)
value_list = []
for a in alphabet:
value = 0
for word in arr:
if a not in word:
continue
s = ''
for w in word:
s += '1' if w == a else '0'
value += int(s)
value_list.append(value)
value_list.sort(reverse=True)
answer = 0
value = 9
for s in value_list:
answer += value * s
value -= 1
print(answer)
<|reserved_special_token_1|>
''' 단어 수학
시간 : 68ms (~2초), 메모리 : 29200KB (~256MB)
분류 : greedy
'''
import sys
input = sys.stdin.readline
# 입력
N = int(input()) # 단어의 개수
arr = [list(input().strip()) for _ in range(N)]
# 풀이
alphabet = []
for word in arr:
for a in word:
if a not in alphabet:
alphabet.append(a)
value_list = []
for a in alphabet:
value = 0
for word in arr:
if a not in word: # 알파벳 없으면 넘어감
continue
s = ""
for w in word:
s += "1" if w == a else "0"
value += int(s)
value_list.append(value)
value_list.sort(reverse=True) # 내림차순 정렬
answer = 0
value = 9
for s in value_list:
answer += value * s
value -= 1
# 출력
print(answer)
|
flexible
|
{
"blob_id": "6efc7ff304a05dfc5a7bed7d646e5d6ac034ce85",
"index": 4706,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor word in arr:\n for a in word:\n if a not in alphabet:\n alphabet.append(a)\n<mask token>\nfor a in alphabet:\n value = 0\n for word in arr:\n if a not in word:\n continue\n s = ''\n for w in word:\n s += '1' if w == a else '0'\n value += int(s)\n value_list.append(value)\nvalue_list.sort(reverse=True)\n<mask token>\nfor s in value_list:\n answer += value * s\n value -= 1\nprint(answer)\n",
"step-3": "<mask token>\ninput = sys.stdin.readline\nN = int(input())\narr = [list(input().strip()) for _ in range(N)]\nalphabet = []\nfor word in arr:\n for a in word:\n if a not in alphabet:\n alphabet.append(a)\nvalue_list = []\nfor a in alphabet:\n value = 0\n for word in arr:\n if a not in word:\n continue\n s = ''\n for w in word:\n s += '1' if w == a else '0'\n value += int(s)\n value_list.append(value)\nvalue_list.sort(reverse=True)\nanswer = 0\nvalue = 9\nfor s in value_list:\n answer += value * s\n value -= 1\nprint(answer)\n",
"step-4": "<mask token>\nimport sys\ninput = sys.stdin.readline\nN = int(input())\narr = [list(input().strip()) for _ in range(N)]\nalphabet = []\nfor word in arr:\n for a in word:\n if a not in alphabet:\n alphabet.append(a)\nvalue_list = []\nfor a in alphabet:\n value = 0\n for word in arr:\n if a not in word:\n continue\n s = ''\n for w in word:\n s += '1' if w == a else '0'\n value += int(s)\n value_list.append(value)\nvalue_list.sort(reverse=True)\nanswer = 0\nvalue = 9\nfor s in value_list:\n answer += value * s\n value -= 1\nprint(answer)\n",
"step-5": "''' 단어 수학\n시간 : 68ms (~2초), 메모리 : 29200KB (~256MB)\n분류 : greedy\n'''\n\nimport sys\ninput = sys.stdin.readline\n\n# 입력\nN = int(input()) # 단어의 개수\narr = [list(input().strip()) for _ in range(N)]\n\n# 풀이\nalphabet = []\nfor word in arr:\n for a in word:\n if a not in alphabet:\n alphabet.append(a)\n\nvalue_list = []\nfor a in alphabet:\n value = 0\n for word in arr:\n if a not in word: # 알파벳 없으면 넘어감\n continue\n\n s = \"\"\n for w in word:\n s += \"1\" if w == a else \"0\"\n value += int(s)\n\n value_list.append(value)\n\nvalue_list.sort(reverse=True) # 내림차순 정렬\n\nanswer = 0\nvalue = 9\nfor s in value_list:\n answer += value * s\n value -= 1\n\n# 출력\nprint(answer)\n\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
import requests
import os
import numpy as np
from bs4 import BeautifulSoup
from nltk import word_tokenize
from collections import Counter
import random
from utils import save_pickle
root = 'data'
ratios = [('train', 0.85), ('valid', 0.05), ('test', 0.1)]
max_len = 64
vocab_size = 16000
data = []
path = os.path.join(root,'main')
topics = os.listdir(path)
i = 0
for topic in topics:
i += 1
arts = os.listdir(os.path.join(path,topic))
j = 0
for art in arts:
j += 1
with open(os.path.join(path,topic,art),encoding='UTF-8') as f:
#lines = unicode(f.read(), errors='ignore')
lines = f.read()
#print(type(lines))
#print(i,j)
soup = BeautifulSoup(lines, 'html.parser')
for text in soup.find_all('p'):
# replace punctuation characters with spaces
text = text.get_text()
filters = '!"\'#$%&()*+,-./:;<=>?@[\\]^_`{|}~\t\n'
translate_dict = dict((c, " ") for c in filters)
translate_map = str.maketrans(translate_dict)
text = text.translate(translate_map)
tokens = word_tokenize(text)
lines = [str(i)] + [str(j)] + tokens
if(len(tokens)==0):
break
else:
data.append(' '.join(lines))
if True:
random.shuffle(data)
num_samples = len(data)
for split, ratio in ratios:
with open(os.path.join(root, "%s.txt"%split), 'w') as f:
length = int(num_samples * ratio)
f.write('\n'.join(data[:length]))
data = data[length:]
print("Building vocabulary from DUC data")
counter = Counter()
with open(os.path.join(root, 'train.txt')) as f:
for line in f:
words = line.strip().lower().split()[:max_len]
counter.update(words)
word_to_idx = {'<pad>': 0, '<unk>': 1, '<bos>': 2, '<eos>': 3}
vocab = [word for word, freq in counter.most_common() if freq > 5]
for word in vocab[:vocab_size - 2]:
word_to_idx[word] = len(word_to_idx)
# exclude <bos> and <pad> symbols
print("Vocabulary size: %d" % (len(word_to_idx) - 2))
save_pickle(word_to_idx, os.path.join(root, 'vocab.pkl'))
splits = ['train', 'valid', 'test']
num_sents, num_words = 0, 0
func = lambda seq: np.array([
word_to_idx.get(symbol, word_to_idx['<unk>']) for symbol in seq])
for split in splits:
print("Creating %s DUC data" % split)
data = []
with open(os.path.join(root, "%s.txt" % split)) as f:
for line in f:
words = line.strip().lower().split()[:max_len + 2]
topic, art, words = int(words[0]), int(words[1]), words[2:] ###
length = len(words)
paddings = ['<pad>'] * (max_len - length)
enc_input = func(words + paddings)
dec_input = func(['<bos>'] + words + paddings)
target = func(words + ['<eos>'] + paddings)
data.append((enc_input, dec_input, target, length, topic)) ###
num_words += length
print("%s samples: %d" %(split.capitalize(), len(data)))
save_pickle(data, os.path.join(root, "%s.pkl" % split))
num_sents += len(data)
print("Average length: %.2f" %(num_words / num_sents))
|
normal
|
{
"blob_id": "977841e0bb73cec879fbb1868f1e64102c6d8c1a",
"index": 2119,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nfor topic in topics:\n i += 1\n arts = os.listdir(os.path.join(path, topic))\n j = 0\n for art in arts:\n j += 1\n with open(os.path.join(path, topic, art), encoding='UTF-8') as f:\n lines = f.read()\n soup = BeautifulSoup(lines, 'html.parser')\n for text in soup.find_all('p'):\n text = text.get_text()\n filters = '!\"\\'#$%&()*+,-./:;<=>?@[\\\\]^_`{|}~\\t\\n'\n translate_dict = dict((c, ' ') for c in filters)\n translate_map = str.maketrans(translate_dict)\n text = text.translate(translate_map)\n tokens = word_tokenize(text)\n lines = [str(i)] + [str(j)] + tokens\n if len(tokens) == 0:\n break\n else:\n data.append(' '.join(lines))\nif True:\n random.shuffle(data)\n num_samples = len(data)\n for split, ratio in ratios:\n with open(os.path.join(root, '%s.txt' % split), 'w') as f:\n length = int(num_samples * ratio)\n f.write('\\n'.join(data[:length]))\n data = data[length:]\n print('Building vocabulary from DUC data')\n counter = Counter()\n with open(os.path.join(root, 'train.txt')) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len]\n counter.update(words)\n word_to_idx = {'<pad>': 0, '<unk>': 1, '<bos>': 2, '<eos>': 3}\n vocab = [word for word, freq in counter.most_common() if freq > 5]\n for word in vocab[:vocab_size - 2]:\n word_to_idx[word] = len(word_to_idx)\n print('Vocabulary size: %d' % (len(word_to_idx) - 2))\n save_pickle(word_to_idx, os.path.join(root, 'vocab.pkl'))\n splits = ['train', 'valid', 'test']\n num_sents, num_words = 0, 0\n func = lambda seq: np.array([word_to_idx.get(symbol, word_to_idx[\n '<unk>']) for symbol in seq])\n for split in splits:\n print('Creating %s DUC data' % split)\n data = []\n with open(os.path.join(root, '%s.txt' % split)) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len + 2]\n topic, art, words = int(words[0]), int(words[1]), words[2:]\n length = len(words)\n paddings = ['<pad>'] * (max_len - length)\n enc_input = func(words + paddings)\n dec_input = func(['<bos>'] + words + paddings)\n target = func(words + ['<eos>'] + paddings)\n data.append((enc_input, dec_input, target, length, topic))\n num_words += length\n print('%s samples: %d' % (split.capitalize(), len(data)))\n save_pickle(data, os.path.join(root, '%s.pkl' % split))\n num_sents += len(data)\n print('Average length: %.2f' % (num_words / num_sents))\n",
"step-3": "<mask token>\nroot = 'data'\nratios = [('train', 0.85), ('valid', 0.05), ('test', 0.1)]\nmax_len = 64\nvocab_size = 16000\ndata = []\npath = os.path.join(root, 'main')\ntopics = os.listdir(path)\ni = 0\nfor topic in topics:\n i += 1\n arts = os.listdir(os.path.join(path, topic))\n j = 0\n for art in arts:\n j += 1\n with open(os.path.join(path, topic, art), encoding='UTF-8') as f:\n lines = f.read()\n soup = BeautifulSoup(lines, 'html.parser')\n for text in soup.find_all('p'):\n text = text.get_text()\n filters = '!\"\\'#$%&()*+,-./:;<=>?@[\\\\]^_`{|}~\\t\\n'\n translate_dict = dict((c, ' ') for c in filters)\n translate_map = str.maketrans(translate_dict)\n text = text.translate(translate_map)\n tokens = word_tokenize(text)\n lines = [str(i)] + [str(j)] + tokens\n if len(tokens) == 0:\n break\n else:\n data.append(' '.join(lines))\nif True:\n random.shuffle(data)\n num_samples = len(data)\n for split, ratio in ratios:\n with open(os.path.join(root, '%s.txt' % split), 'w') as f:\n length = int(num_samples * ratio)\n f.write('\\n'.join(data[:length]))\n data = data[length:]\n print('Building vocabulary from DUC data')\n counter = Counter()\n with open(os.path.join(root, 'train.txt')) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len]\n counter.update(words)\n word_to_idx = {'<pad>': 0, '<unk>': 1, '<bos>': 2, '<eos>': 3}\n vocab = [word for word, freq in counter.most_common() if freq > 5]\n for word in vocab[:vocab_size - 2]:\n word_to_idx[word] = len(word_to_idx)\n print('Vocabulary size: %d' % (len(word_to_idx) - 2))\n save_pickle(word_to_idx, os.path.join(root, 'vocab.pkl'))\n splits = ['train', 'valid', 'test']\n num_sents, num_words = 0, 0\n func = lambda seq: np.array([word_to_idx.get(symbol, word_to_idx[\n '<unk>']) for symbol in seq])\n for split in splits:\n print('Creating %s DUC data' % split)\n data = []\n with open(os.path.join(root, '%s.txt' % split)) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len + 2]\n topic, art, words = int(words[0]), int(words[1]), words[2:]\n length = len(words)\n paddings = ['<pad>'] * (max_len - length)\n enc_input = func(words + paddings)\n dec_input = func(['<bos>'] + words + paddings)\n target = func(words + ['<eos>'] + paddings)\n data.append((enc_input, dec_input, target, length, topic))\n num_words += length\n print('%s samples: %d' % (split.capitalize(), len(data)))\n save_pickle(data, os.path.join(root, '%s.pkl' % split))\n num_sents += len(data)\n print('Average length: %.2f' % (num_words / num_sents))\n",
"step-4": "import requests\nimport os\nimport numpy as np\nfrom bs4 import BeautifulSoup\nfrom nltk import word_tokenize\nfrom collections import Counter\nimport random\nfrom utils import save_pickle\nroot = 'data'\nratios = [('train', 0.85), ('valid', 0.05), ('test', 0.1)]\nmax_len = 64\nvocab_size = 16000\ndata = []\npath = os.path.join(root, 'main')\ntopics = os.listdir(path)\ni = 0\nfor topic in topics:\n i += 1\n arts = os.listdir(os.path.join(path, topic))\n j = 0\n for art in arts:\n j += 1\n with open(os.path.join(path, topic, art), encoding='UTF-8') as f:\n lines = f.read()\n soup = BeautifulSoup(lines, 'html.parser')\n for text in soup.find_all('p'):\n text = text.get_text()\n filters = '!\"\\'#$%&()*+,-./:;<=>?@[\\\\]^_`{|}~\\t\\n'\n translate_dict = dict((c, ' ') for c in filters)\n translate_map = str.maketrans(translate_dict)\n text = text.translate(translate_map)\n tokens = word_tokenize(text)\n lines = [str(i)] + [str(j)] + tokens\n if len(tokens) == 0:\n break\n else:\n data.append(' '.join(lines))\nif True:\n random.shuffle(data)\n num_samples = len(data)\n for split, ratio in ratios:\n with open(os.path.join(root, '%s.txt' % split), 'w') as f:\n length = int(num_samples * ratio)\n f.write('\\n'.join(data[:length]))\n data = data[length:]\n print('Building vocabulary from DUC data')\n counter = Counter()\n with open(os.path.join(root, 'train.txt')) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len]\n counter.update(words)\n word_to_idx = {'<pad>': 0, '<unk>': 1, '<bos>': 2, '<eos>': 3}\n vocab = [word for word, freq in counter.most_common() if freq > 5]\n for word in vocab[:vocab_size - 2]:\n word_to_idx[word] = len(word_to_idx)\n print('Vocabulary size: %d' % (len(word_to_idx) - 2))\n save_pickle(word_to_idx, os.path.join(root, 'vocab.pkl'))\n splits = ['train', 'valid', 'test']\n num_sents, num_words = 0, 0\n func = lambda seq: np.array([word_to_idx.get(symbol, word_to_idx[\n '<unk>']) for symbol in seq])\n for split in splits:\n print('Creating %s DUC data' % split)\n data = []\n with open(os.path.join(root, '%s.txt' % split)) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len + 2]\n topic, art, words = int(words[0]), int(words[1]), words[2:]\n length = len(words)\n paddings = ['<pad>'] * (max_len - length)\n enc_input = func(words + paddings)\n dec_input = func(['<bos>'] + words + paddings)\n target = func(words + ['<eos>'] + paddings)\n data.append((enc_input, dec_input, target, length, topic))\n num_words += length\n print('%s samples: %d' % (split.capitalize(), len(data)))\n save_pickle(data, os.path.join(root, '%s.pkl' % split))\n num_sents += len(data)\n print('Average length: %.2f' % (num_words / num_sents))\n",
"step-5": "import requests\nimport os\nimport numpy as np\nfrom bs4 import BeautifulSoup\nfrom nltk import word_tokenize\nfrom collections import Counter\nimport random\n\nfrom utils import save_pickle\n\n\nroot = 'data'\nratios = [('train', 0.85), ('valid', 0.05), ('test', 0.1)]\nmax_len = 64\nvocab_size = 16000\n\n\ndata = []\npath = os.path.join(root,'main')\ntopics = os.listdir(path)\ni = 0\nfor topic in topics:\n i += 1\n arts = os.listdir(os.path.join(path,topic))\n j = 0\n for art in arts:\n j += 1\n with open(os.path.join(path,topic,art),encoding='UTF-8') as f:\n #lines = unicode(f.read(), errors='ignore')\n lines = f.read()\n #print(type(lines))\n #print(i,j)\n soup = BeautifulSoup(lines, 'html.parser')\n for text in soup.find_all('p'):\n # replace punctuation characters with spaces\n text = text.get_text()\n filters = '!\"\\'#$%&()*+,-./:;<=>?@[\\\\]^_`{|}~\\t\\n'\n translate_dict = dict((c, \" \") for c in filters)\n translate_map = str.maketrans(translate_dict)\n text = text.translate(translate_map)\n tokens = word_tokenize(text)\n lines = [str(i)] + [str(j)] + tokens\n if(len(tokens)==0):\n break\n else:\n data.append(' '.join(lines))\n\nif True:\n random.shuffle(data)\n\n num_samples = len(data)\n for split, ratio in ratios:\n with open(os.path.join(root, \"%s.txt\"%split), 'w') as f:\n length = int(num_samples * ratio)\n f.write('\\n'.join(data[:length]))\n data = data[length:]\n\n print(\"Building vocabulary from DUC data\")\n counter = Counter()\n with open(os.path.join(root, 'train.txt')) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len]\n counter.update(words)\n\n word_to_idx = {'<pad>': 0, '<unk>': 1, '<bos>': 2, '<eos>': 3}\n vocab = [word for word, freq in counter.most_common() if freq > 5]\n for word in vocab[:vocab_size - 2]:\n word_to_idx[word] = len(word_to_idx)\n\n # exclude <bos> and <pad> symbols\n print(\"Vocabulary size: %d\" % (len(word_to_idx) - 2))\n save_pickle(word_to_idx, os.path.join(root, 'vocab.pkl'))\n\n splits = ['train', 'valid', 'test']\n num_sents, num_words = 0, 0\n func = lambda seq: np.array([\n word_to_idx.get(symbol, word_to_idx['<unk>']) for symbol in seq])\n for split in splits:\n print(\"Creating %s DUC data\" % split)\n data = []\n with open(os.path.join(root, \"%s.txt\" % split)) as f:\n for line in f:\n words = line.strip().lower().split()[:max_len + 2]\n topic, art, words = int(words[0]), int(words[1]), words[2:] ###\n length = len(words)\n paddings = ['<pad>'] * (max_len - length)\n enc_input = func(words + paddings)\n dec_input = func(['<bos>'] + words + paddings)\n target = func(words + ['<eos>'] + paddings)\n data.append((enc_input, dec_input, target, length, topic)) ###\n num_words += length\n print(\"%s samples: %d\" %(split.capitalize(), len(data)))\n save_pickle(data, os.path.join(root, \"%s.pkl\" % split))\n num_sents += len(data)\n\n print(\"Average length: %.2f\" %(num_words / num_sents))",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
class Solution:
def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]:
def convert(word):
table = {}
count, converted = 0, ''
for w in word:
if w in table:
converted += table[w]
else:
converted += str(count)
table[w] = str(count)
count += 1
return converted
p = convert(pattern)
answer = []
for word in words:
if p == convert(word):
answer.append(word)
return answer
"""
[빠른 풀이]
- zip을 이용해서 길이만 비교!!!
class Solution:
def findAndReplacePattern(self, w: List[str], p: str) -> List[str]:
return [i for i in w if len(set(zip(p,i)))==len(set(p))==len(set(i))]
"""
|
normal
|
{
"blob_id": "e9ea48dec40e75f2fc73f8dcb3b5b975065cf8af",
"index": 5854,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n\n\n<mask token>\n",
"step-3": "class Solution:\n\n def findAndReplacePattern(self, words: List[str], pattern: str) ->List[str\n ]:\n\n def convert(word):\n table = {}\n count, converted = 0, ''\n for w in word:\n if w in table:\n converted += table[w]\n else:\n converted += str(count)\n table[w] = str(count)\n count += 1\n return converted\n p = convert(pattern)\n answer = []\n for word in words:\n if p == convert(word):\n answer.append(word)\n return answer\n\n\n<mask token>\n",
"step-4": "class Solution:\n def findAndReplacePattern(self, words: List[str], pattern: str) -> List[str]:\n def convert(word):\n table = {}\n count, converted = 0, ''\n \n for w in word:\n if w in table:\n converted += table[w]\n else:\n converted += str(count)\n table[w] = str(count)\n count += 1\n return converted\n \n p = convert(pattern)\n answer = []\n for word in words:\n if p == convert(word):\n answer.append(word)\n \n return answer\n\n\"\"\"\n[빠른 풀이]\n- zip을 이용해서 길이만 비교!!!\n\nclass Solution:\n def findAndReplacePattern(self, w: List[str], p: str) -> List[str]:\n\t\t\t\t\treturn [i for i in w if len(set(zip(p,i)))==len(set(p))==len(set(i))]\n\"\"\"",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Nov 1 11:06:35 2020
@author: fitec
"""
# version 1
print(" Début du projet covid-19 !! ")
print(" test repository distant")
|
normal
|
{
"blob_id": "3657d02271a27c150f4c67d67a2a25886b00c593",
"index": 3306,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(' Début du projet covid-19 !! ')\nprint(' test repository distant')\n",
"step-3": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Nov 1 11:06:35 2020\n\n@author: fitec\n\"\"\"\n\n# version 1 \n\nprint(\" Début du projet covid-19 !! \")\nprint(\" test repository distant\")\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n",
"step-4": null,
"step-5": null,
"step-ids": [
0,
1,
2
]
}
|
[
0,
1,
2
] |
""" Tests for `yatsm.utils`
"""
import numpy as np
import pytest
from yatsm import utils
@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])
def test_distribute_jobs_interlaced(nrow, njob):
assigned = []
for i in range(njob):
assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=True))
assigned = np.sort(np.asarray(assigned))
all_rows = np.arange(0, nrow)
np.testing.assert_equal(assigned, all_rows)
@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])
def test_distribute_jobs_sequential(nrow, njob):
assigned = []
for i in range(njob):
assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=False))
assigned = np.sort(np.asarray(assigned))
all_rows = np.arange(0, nrow)
np.testing.assert_equal(assigned, all_rows)
@pytest.mark.parametrize('nrow,njob', [(700, 1)])
def test_distribute_jobs_sequential_onejob(nrow, njob):
with pytest.raises(ValueError):
utils.distribute_jobs(nrow, nrow, njob, interlaced=False)
# mkdir_p
def test_mkdir_p_success(tmpdir):
utils.mkdir_p(tmpdir.join('test').strpath)
def test_mkdir_p_succcess_exists(tmpdir):
utils.mkdir_p(tmpdir.join('test').strpath)
utils.mkdir_p(tmpdir.join('test').strpath)
def test_mkdir_p_failure_permission(tmpdir):
with pytest.raises(OSError):
utils.mkdir_p('/asdf')
# np_promote_all_types
@pytest.mark.parametrize(('dtypes', 'ans'), [
((np.uint8, np.int16), np.int16),
((np.uint8, np.uint16, np.int16), np.int32),
((np.uint8, np.uint16, np.int16, np.float), np.float),
((np.uint8, np.float16, np.float32, np.float64), np.float64),
])
def test_np_promote_all_types(dtypes, ans):
test_ans = utils.np_promote_all_types(*dtypes)
assert test_ans == ans
|
normal
|
{
"blob_id": "a513dfd84b5d9267b7e96fedc88e5b6dabeea19e",
"index": 640,
"step-1": "<mask token>\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_sequential(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=False))\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n<mask token>\n\n\ndef test_mkdir_p_success(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\n<mask token>\n\n\ndef test_mkdir_p_failure_permission(tmpdir):\n with pytest.raises(OSError):\n utils.mkdir_p('/asdf')\n\n\n@pytest.mark.parametrize(('dtypes', 'ans'), [((np.uint8, np.int16), np.\n int16), ((np.uint8, np.uint16, np.int16), np.int32), ((np.uint8, np.\n uint16, np.int16, np.float), np.float), ((np.uint8, np.float16, np.\n float32, np.float64), np.float64)])\ndef test_np_promote_all_types(dtypes, ans):\n test_ans = utils.np_promote_all_types(*dtypes)\n assert test_ans == ans\n",
"step-2": "<mask token>\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_sequential(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=False))\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(700, 1)])\ndef test_distribute_jobs_sequential_onejob(nrow, njob):\n with pytest.raises(ValueError):\n utils.distribute_jobs(nrow, nrow, njob, interlaced=False)\n\n\ndef test_mkdir_p_success(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_succcess_exists(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_failure_permission(tmpdir):\n with pytest.raises(OSError):\n utils.mkdir_p('/asdf')\n\n\n@pytest.mark.parametrize(('dtypes', 'ans'), [((np.uint8, np.int16), np.\n int16), ((np.uint8, np.uint16, np.int16), np.int32), ((np.uint8, np.\n uint16, np.int16, np.float), np.float), ((np.uint8, np.float16, np.\n float32, np.float64), np.float64)])\ndef test_np_promote_all_types(dtypes, ans):\n test_ans = utils.np_promote_all_types(*dtypes)\n assert test_ans == ans\n",
"step-3": "<mask token>\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_interlaced(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=True))\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_sequential(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=False))\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(700, 1)])\ndef test_distribute_jobs_sequential_onejob(nrow, njob):\n with pytest.raises(ValueError):\n utils.distribute_jobs(nrow, nrow, njob, interlaced=False)\n\n\ndef test_mkdir_p_success(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_succcess_exists(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_failure_permission(tmpdir):\n with pytest.raises(OSError):\n utils.mkdir_p('/asdf')\n\n\n@pytest.mark.parametrize(('dtypes', 'ans'), [((np.uint8, np.int16), np.\n int16), ((np.uint8, np.uint16, np.int16), np.int32), ((np.uint8, np.\n uint16, np.int16, np.float), np.float), ((np.uint8, np.float16, np.\n float32, np.float64), np.float64)])\ndef test_np_promote_all_types(dtypes, ans):\n test_ans = utils.np_promote_all_types(*dtypes)\n assert test_ans == ans\n",
"step-4": "<mask token>\nimport numpy as np\nimport pytest\nfrom yatsm import utils\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_interlaced(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=True))\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_sequential(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=False))\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(700, 1)])\ndef test_distribute_jobs_sequential_onejob(nrow, njob):\n with pytest.raises(ValueError):\n utils.distribute_jobs(nrow, nrow, njob, interlaced=False)\n\n\ndef test_mkdir_p_success(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_succcess_exists(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_failure_permission(tmpdir):\n with pytest.raises(OSError):\n utils.mkdir_p('/asdf')\n\n\n@pytest.mark.parametrize(('dtypes', 'ans'), [((np.uint8, np.int16), np.\n int16), ((np.uint8, np.uint16, np.int16), np.int32), ((np.uint8, np.\n uint16, np.int16, np.float), np.float), ((np.uint8, np.float16, np.\n float32, np.float64), np.float64)])\ndef test_np_promote_all_types(dtypes, ans):\n test_ans = utils.np_promote_all_types(*dtypes)\n assert test_ans == ans\n",
"step-5": "\"\"\" Tests for `yatsm.utils`\n\"\"\"\nimport numpy as np\nimport pytest\n\nfrom yatsm import utils\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_interlaced(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=True))\n\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(793, 13), (700, 1), (700, 700)])\ndef test_distribute_jobs_sequential(nrow, njob):\n assigned = []\n for i in range(njob):\n assigned.extend(utils.distribute_jobs(i, njob, nrow, interlaced=False))\n\n assigned = np.sort(np.asarray(assigned))\n all_rows = np.arange(0, nrow)\n np.testing.assert_equal(assigned, all_rows)\n\n\n@pytest.mark.parametrize('nrow,njob', [(700, 1)])\ndef test_distribute_jobs_sequential_onejob(nrow, njob):\n with pytest.raises(ValueError):\n utils.distribute_jobs(nrow, nrow, njob, interlaced=False)\n\n\n# mkdir_p\ndef test_mkdir_p_success(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_succcess_exists(tmpdir):\n utils.mkdir_p(tmpdir.join('test').strpath)\n utils.mkdir_p(tmpdir.join('test').strpath)\n\n\ndef test_mkdir_p_failure_permission(tmpdir):\n with pytest.raises(OSError):\n utils.mkdir_p('/asdf')\n\n\n# np_promote_all_types\n@pytest.mark.parametrize(('dtypes', 'ans'), [\n ((np.uint8, np.int16), np.int16),\n ((np.uint8, np.uint16, np.int16), np.int32),\n ((np.uint8, np.uint16, np.int16, np.float), np.float),\n ((np.uint8, np.float16, np.float32, np.float64), np.float64),\n])\ndef test_np_promote_all_types(dtypes, ans):\n test_ans = utils.np_promote_all_types(*dtypes)\n assert test_ans == ans\n",
"step-ids": [
4,
6,
7,
8,
9
]
}
|
[
4,
6,
7,
8,
9
] |
# This is an auto-generated Django model module.
# You'll have to do the following manually to clean this up:
# * Rearrange models' order
# * Make sure each model has one field with primary_key=True
# * Make sure each ForeignKey and OneToOneField has `on_delete` set to the desired behavior
# * Remove `managed = False` lines if you wish to allow Django to create, modify, and delete the table
# Feel free to rename the models, but don't rename db_table values or field names.
from django.db import models
class Agentname(models.Model):
name_id = models.IntegerField(primary_key=True)
firstname = models.CharField(max_length=255)
lastname = models.CharField(max_length=255)
email = models.CharField(max_length=255, blank=True, null=True)
phone = models.CharField(max_length=13)
pollingunit_uniqueid = models.IntegerField()
class Meta:
managed = False
db_table = 'agentname'
class AnnouncedLgaResults(models.Model):
result_id = models.IntegerField(primary_key=True)
lga_name = models.CharField(max_length=50)
party_abbreviation = models.CharField(max_length=4)
party_score = models.IntegerField()
entered_by_user = models.CharField(max_length=50)
date_entered = models.DateTimeField()
user_ip_address = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'announced_lga_results'
class AnnouncedPuResults(models.Model):
result_id = models.IntegerField(primary_key=True)
polling_unit_uniqueid = models.CharField(max_length=50)
party_abbreviation = models.CharField(max_length=4)
party_score = models.IntegerField()
entered_by_user = models.CharField(max_length=50)
date_entered = models.DateTimeField()
user_ip_address = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'announced_pu_results'
class AnnouncedStateResults(models.Model):
result_id = models.IntegerField(primary_key=True)
state_name = models.CharField(max_length=50)
party_abbreviation = models.CharField(max_length=4)
party_score = models.IntegerField()
entered_by_user = models.CharField(max_length=50)
date_entered = models.DateTimeField()
user_ip_address = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'announced_state_results'
class AnnouncedWardResults(models.Model):
result_id = models.IntegerField(primary_key=True)
ward_name = models.CharField(max_length=50)
party_abbreviation = models.CharField(max_length=4)
party_score = models.IntegerField()
entered_by_user = models.CharField(max_length=50)
date_entered = models.DateTimeField()
user_ip_address = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'announced_ward_results'
class Lga(models.Model):
uniqueid = models.IntegerField(primary_key=True)
lga_id = models.IntegerField()
lga_name = models.CharField(max_length=50)
state_id = models.IntegerField()
lga_description = models.TextField(blank=True, null=True)
entered_by_user = models.CharField(max_length=50)
date_entered = models.DateTimeField()
user_ip_address = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'lga'
class Party(models.Model):
id = models.IntegerField(primary_key=True)
partyid = models.CharField(max_length=11)
partyname = models.CharField(max_length=11)
class Meta:
managed = False
db_table = 'party'
class PollingUnit(models.Model):
uniqueid = models.IntegerField(primary_key=True)
polling_unit_id = models.IntegerField()
ward_id = models.IntegerField()
lga_id = models.IntegerField()
uniquewardid = models.IntegerField(blank=True, null=True)
polling_unit_number = models.CharField(max_length=50, blank=True, null=True)
polling_unit_name = models.CharField(max_length=50, blank=True, null=True)
polling_unit_description = models.TextField(blank=True, null=True)
lat = models.CharField(max_length=255, blank=True, null=True)
lon = models.CharField(max_length=255, blank=True, null=True)
entered_by_user = models.CharField(max_length=50, blank=True, null=True)
date_entered = models.DateTimeField(blank=True, null=True)
user_ip_address = models.CharField(max_length=50, blank=True, null=True)
class Meta:
managed = False
db_table = 'polling_unit'
class States(models.Model):
state_id = models.IntegerField(primary_key=True)
state_name = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'states'
class Ward(models.Model):
uniqueid = models.IntegerField(primary_key=True)
ward_id = models.IntegerField()
ward_name = models.CharField(max_length=50)
lga_id = models.IntegerField()
ward_description = models.TextField(blank=True, null=True)
entered_by_user = models.CharField(max_length=50)
date_entered = models.DateTimeField()
user_ip_address = models.CharField(max_length=50)
class Meta:
managed = False
db_table = 'ward'
|
normal
|
{
"blob_id": "5ce5fbfa33c241fc316d5e414df01a39bfc9be18",
"index": 7063,
"step-1": "<mask token>\n\n\nclass AnnouncedPuResults(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n managed = False\n db_table = 'announced_pu_results'\n\n\nclass AnnouncedStateResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_state_results'\n\n\nclass AnnouncedWardResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n ward_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_ward_results'\n\n\nclass Lga(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n lga_id = models.IntegerField()\n lga_name = models.CharField(max_length=50)\n state_id = models.IntegerField()\n lga_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'lga'\n\n\nclass Party(models.Model):\n id = models.IntegerField(primary_key=True)\n partyid = models.CharField(max_length=11)\n partyname = models.CharField(max_length=11)\n\n\n class Meta:\n managed = False\n db_table = 'party'\n\n\nclass PollingUnit(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n polling_unit_id = models.IntegerField()\n ward_id = models.IntegerField()\n lga_id = models.IntegerField()\n uniquewardid = models.IntegerField(blank=True, null=True)\n polling_unit_number = models.CharField(max_length=50, blank=True, null=True\n )\n polling_unit_name = models.CharField(max_length=50, blank=True, null=True)\n polling_unit_description = models.TextField(blank=True, null=True)\n lat = models.CharField(max_length=255, blank=True, null=True)\n lon = models.CharField(max_length=255, blank=True, null=True)\n entered_by_user = models.CharField(max_length=50, blank=True, null=True)\n date_entered = models.DateTimeField(blank=True, null=True)\n user_ip_address = models.CharField(max_length=50, blank=True, null=True)\n\n\n class Meta:\n managed = False\n db_table = 'polling_unit'\n\n\nclass States(models.Model):\n state_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'states'\n\n\nclass Ward(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n ward_id = models.IntegerField()\n ward_name = models.CharField(max_length=50)\n lga_id = models.IntegerField()\n ward_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'ward'\n",
"step-2": "<mask token>\n\n\nclass AnnouncedLgaResults(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n managed = False\n db_table = 'announced_lga_results'\n\n\nclass AnnouncedPuResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n polling_unit_uniqueid = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_pu_results'\n\n\nclass AnnouncedStateResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_state_results'\n\n\nclass AnnouncedWardResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n ward_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_ward_results'\n\n\nclass Lga(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n lga_id = models.IntegerField()\n lga_name = models.CharField(max_length=50)\n state_id = models.IntegerField()\n lga_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'lga'\n\n\nclass Party(models.Model):\n id = models.IntegerField(primary_key=True)\n partyid = models.CharField(max_length=11)\n partyname = models.CharField(max_length=11)\n\n\n class Meta:\n managed = False\n db_table = 'party'\n\n\nclass PollingUnit(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n polling_unit_id = models.IntegerField()\n ward_id = models.IntegerField()\n lga_id = models.IntegerField()\n uniquewardid = models.IntegerField(blank=True, null=True)\n polling_unit_number = models.CharField(max_length=50, blank=True, null=True\n )\n polling_unit_name = models.CharField(max_length=50, blank=True, null=True)\n polling_unit_description = models.TextField(blank=True, null=True)\n lat = models.CharField(max_length=255, blank=True, null=True)\n lon = models.CharField(max_length=255, blank=True, null=True)\n entered_by_user = models.CharField(max_length=50, blank=True, null=True)\n date_entered = models.DateTimeField(blank=True, null=True)\n user_ip_address = models.CharField(max_length=50, blank=True, null=True)\n\n\n class Meta:\n managed = False\n db_table = 'polling_unit'\n\n\nclass States(models.Model):\n state_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'states'\n\n\nclass Ward(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n ward_id = models.IntegerField()\n ward_name = models.CharField(max_length=50)\n lga_id = models.IntegerField()\n ward_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'ward'\n",
"step-3": "<mask token>\n\n\nclass Agentname(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\n class Meta:\n managed = False\n db_table = 'agentname'\n\n\nclass AnnouncedLgaResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n lga_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_lga_results'\n\n\nclass AnnouncedPuResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n polling_unit_uniqueid = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_pu_results'\n\n\nclass AnnouncedStateResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_state_results'\n\n\nclass AnnouncedWardResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n ward_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_ward_results'\n\n\nclass Lga(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n lga_id = models.IntegerField()\n lga_name = models.CharField(max_length=50)\n state_id = models.IntegerField()\n lga_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'lga'\n\n\nclass Party(models.Model):\n id = models.IntegerField(primary_key=True)\n partyid = models.CharField(max_length=11)\n partyname = models.CharField(max_length=11)\n\n\n class Meta:\n managed = False\n db_table = 'party'\n\n\nclass PollingUnit(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n polling_unit_id = models.IntegerField()\n ward_id = models.IntegerField()\n lga_id = models.IntegerField()\n uniquewardid = models.IntegerField(blank=True, null=True)\n polling_unit_number = models.CharField(max_length=50, blank=True, null=True\n )\n polling_unit_name = models.CharField(max_length=50, blank=True, null=True)\n polling_unit_description = models.TextField(blank=True, null=True)\n lat = models.CharField(max_length=255, blank=True, null=True)\n lon = models.CharField(max_length=255, blank=True, null=True)\n entered_by_user = models.CharField(max_length=50, blank=True, null=True)\n date_entered = models.DateTimeField(blank=True, null=True)\n user_ip_address = models.CharField(max_length=50, blank=True, null=True)\n\n\n class Meta:\n managed = False\n db_table = 'polling_unit'\n\n\nclass States(models.Model):\n state_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'states'\n\n\nclass Ward(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n ward_id = models.IntegerField()\n ward_name = models.CharField(max_length=50)\n lga_id = models.IntegerField()\n ward_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'ward'\n",
"step-4": "from django.db import models\n\n\nclass Agentname(models.Model):\n name_id = models.IntegerField(primary_key=True)\n firstname = models.CharField(max_length=255)\n lastname = models.CharField(max_length=255)\n email = models.CharField(max_length=255, blank=True, null=True)\n phone = models.CharField(max_length=13)\n pollingunit_uniqueid = models.IntegerField()\n\n\n class Meta:\n managed = False\n db_table = 'agentname'\n\n\nclass AnnouncedLgaResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n lga_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_lga_results'\n\n\nclass AnnouncedPuResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n polling_unit_uniqueid = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_pu_results'\n\n\nclass AnnouncedStateResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_state_results'\n\n\nclass AnnouncedWardResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n ward_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'announced_ward_results'\n\n\nclass Lga(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n lga_id = models.IntegerField()\n lga_name = models.CharField(max_length=50)\n state_id = models.IntegerField()\n lga_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'lga'\n\n\nclass Party(models.Model):\n id = models.IntegerField(primary_key=True)\n partyid = models.CharField(max_length=11)\n partyname = models.CharField(max_length=11)\n\n\n class Meta:\n managed = False\n db_table = 'party'\n\n\nclass PollingUnit(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n polling_unit_id = models.IntegerField()\n ward_id = models.IntegerField()\n lga_id = models.IntegerField()\n uniquewardid = models.IntegerField(blank=True, null=True)\n polling_unit_number = models.CharField(max_length=50, blank=True, null=True\n )\n polling_unit_name = models.CharField(max_length=50, blank=True, null=True)\n polling_unit_description = models.TextField(blank=True, null=True)\n lat = models.CharField(max_length=255, blank=True, null=True)\n lon = models.CharField(max_length=255, blank=True, null=True)\n entered_by_user = models.CharField(max_length=50, blank=True, null=True)\n date_entered = models.DateTimeField(blank=True, null=True)\n user_ip_address = models.CharField(max_length=50, blank=True, null=True)\n\n\n class Meta:\n managed = False\n db_table = 'polling_unit'\n\n\nclass States(models.Model):\n state_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'states'\n\n\nclass Ward(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n ward_id = models.IntegerField()\n ward_name = models.CharField(max_length=50)\n lga_id = models.IntegerField()\n ward_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n\n class Meta:\n managed = False\n db_table = 'ward'\n",
"step-5": "# This is an auto-generated Django model module.\n# You'll have to do the following manually to clean this up:\n# * Rearrange models' order\n# * Make sure each model has one field with primary_key=True\n# * Make sure each ForeignKey and OneToOneField has `on_delete` set to the desired behavior\n# * Remove `managed = False` lines if you wish to allow Django to create, modify, and delete the table\n# Feel free to rename the models, but don't rename db_table values or field names.\nfrom django.db import models\n\n\nclass Agentname(models.Model):\n name_id = models.IntegerField(primary_key=True)\n firstname = models.CharField(max_length=255)\n lastname = models.CharField(max_length=255)\n email = models.CharField(max_length=255, blank=True, null=True)\n phone = models.CharField(max_length=13)\n pollingunit_uniqueid = models.IntegerField()\n\n class Meta:\n managed = False\n db_table = 'agentname'\n\n\nclass AnnouncedLgaResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n lga_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'announced_lga_results'\n\n\nclass AnnouncedPuResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n polling_unit_uniqueid = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'announced_pu_results'\n\n\nclass AnnouncedStateResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'announced_state_results'\n\n\nclass AnnouncedWardResults(models.Model):\n result_id = models.IntegerField(primary_key=True)\n ward_name = models.CharField(max_length=50)\n party_abbreviation = models.CharField(max_length=4)\n party_score = models.IntegerField()\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'announced_ward_results'\n\n\nclass Lga(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n lga_id = models.IntegerField()\n lga_name = models.CharField(max_length=50)\n state_id = models.IntegerField()\n lga_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'lga'\n\n\nclass Party(models.Model):\n id = models.IntegerField(primary_key=True)\n partyid = models.CharField(max_length=11)\n partyname = models.CharField(max_length=11)\n\n class Meta:\n managed = False\n db_table = 'party'\n\n\nclass PollingUnit(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n polling_unit_id = models.IntegerField()\n ward_id = models.IntegerField()\n lga_id = models.IntegerField()\n uniquewardid = models.IntegerField(blank=True, null=True)\n polling_unit_number = models.CharField(max_length=50, blank=True, null=True)\n polling_unit_name = models.CharField(max_length=50, blank=True, null=True)\n polling_unit_description = models.TextField(blank=True, null=True)\n lat = models.CharField(max_length=255, blank=True, null=True)\n lon = models.CharField(max_length=255, blank=True, null=True)\n entered_by_user = models.CharField(max_length=50, blank=True, null=True)\n date_entered = models.DateTimeField(blank=True, null=True)\n user_ip_address = models.CharField(max_length=50, blank=True, null=True)\n\n class Meta:\n managed = False\n db_table = 'polling_unit'\n\n\nclass States(models.Model):\n state_id = models.IntegerField(primary_key=True)\n state_name = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'states'\n\n\nclass Ward(models.Model):\n uniqueid = models.IntegerField(primary_key=True)\n ward_id = models.IntegerField()\n ward_name = models.CharField(max_length=50)\n lga_id = models.IntegerField()\n ward_description = models.TextField(blank=True, null=True)\n entered_by_user = models.CharField(max_length=50)\n date_entered = models.DateTimeField()\n user_ip_address = models.CharField(max_length=50)\n\n class Meta:\n managed = False\n db_table = 'ward'\n",
"step-ids": [
15,
17,
19,
21,
22
]
}
|
[
15,
17,
19,
21,
22
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
if __name__ == '__main__':
logger = Log()
conf = Configuration('configuration/configuration.yaml'
).load_configuration()
ph = ProductsHandler(conf['products_path'])
logger.info('Configuration loaded')
products = ph.load_products()
logger.info('Products loaded from {}'.format(conf['products_path']))
update, msg = spider.Spider(products, conf).crawl()
if len(update) > 0:
logger.info('Products to report')
mail_helper = MailHelper()
mail_helper.send_mail('', msg, 'New prices lower')
logger.info('Mail sent')
mail_helper.close_connection()
else:
logger.info('Nothing to report')
ph.save_products(products)
logger.info('Configuration saved')
else:
print('Exec this file as the main entrypoint! -> python3 init.py')
<|reserved_special_token_1|>
from helper.logger_helper import Log
from helper.mail_helper import MailHelper
import spider.spider as spider
from configuration.configuration_handler import Configuration
from configuration.products_handler import ProductsHandler
if __name__ == '__main__':
logger = Log()
conf = Configuration('configuration/configuration.yaml'
).load_configuration()
ph = ProductsHandler(conf['products_path'])
logger.info('Configuration loaded')
products = ph.load_products()
logger.info('Products loaded from {}'.format(conf['products_path']))
update, msg = spider.Spider(products, conf).crawl()
if len(update) > 0:
logger.info('Products to report')
mail_helper = MailHelper()
mail_helper.send_mail('', msg, 'New prices lower')
logger.info('Mail sent')
mail_helper.close_connection()
else:
logger.info('Nothing to report')
ph.save_products(products)
logger.info('Configuration saved')
else:
print('Exec this file as the main entrypoint! -> python3 init.py')
<|reserved_special_token_1|>
from helper.logger_helper import Log
from helper.mail_helper import MailHelper
import spider.spider as spider
from configuration.configuration_handler import Configuration
from configuration.products_handler import ProductsHandler
if __name__ == "__main__":
logger = Log()
conf = Configuration('configuration/configuration.yaml').load_configuration()
ph = ProductsHandler(conf["products_path"])
logger.info("Configuration loaded")
products = ph.load_products()
logger.info("Products loaded from {}".format(conf["products_path"]))
update, msg = spider.Spider(products, conf).crawl()
if len(update) > 0:
logger.info("Products to report")
mail_helper = MailHelper()
mail_helper.send_mail('', msg, "New prices lower")
logger.info("Mail sent")
mail_helper.close_connection()
else:
logger.info("Nothing to report")
ph.save_products(products)
logger.info("Configuration saved")
else:
print("Exec this file as the main entrypoint! -> python3 init.py")
|
flexible
|
{
"blob_id": "2e140d1174e0b2d8a97df880b1bffdf84dc0d236",
"index": 1029,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif __name__ == '__main__':\n logger = Log()\n conf = Configuration('configuration/configuration.yaml'\n ).load_configuration()\n ph = ProductsHandler(conf['products_path'])\n logger.info('Configuration loaded')\n products = ph.load_products()\n logger.info('Products loaded from {}'.format(conf['products_path']))\n update, msg = spider.Spider(products, conf).crawl()\n if len(update) > 0:\n logger.info('Products to report')\n mail_helper = MailHelper()\n mail_helper.send_mail('', msg, 'New prices lower')\n logger.info('Mail sent')\n mail_helper.close_connection()\n else:\n logger.info('Nothing to report')\n ph.save_products(products)\n logger.info('Configuration saved')\nelse:\n print('Exec this file as the main entrypoint! -> python3 init.py')\n",
"step-3": "from helper.logger_helper import Log\nfrom helper.mail_helper import MailHelper\nimport spider.spider as spider\nfrom configuration.configuration_handler import Configuration\nfrom configuration.products_handler import ProductsHandler\nif __name__ == '__main__':\n logger = Log()\n conf = Configuration('configuration/configuration.yaml'\n ).load_configuration()\n ph = ProductsHandler(conf['products_path'])\n logger.info('Configuration loaded')\n products = ph.load_products()\n logger.info('Products loaded from {}'.format(conf['products_path']))\n update, msg = spider.Spider(products, conf).crawl()\n if len(update) > 0:\n logger.info('Products to report')\n mail_helper = MailHelper()\n mail_helper.send_mail('', msg, 'New prices lower')\n logger.info('Mail sent')\n mail_helper.close_connection()\n else:\n logger.info('Nothing to report')\n ph.save_products(products)\n logger.info('Configuration saved')\nelse:\n print('Exec this file as the main entrypoint! -> python3 init.py')\n",
"step-4": "from helper.logger_helper import Log\nfrom helper.mail_helper import MailHelper\nimport spider.spider as spider\nfrom configuration.configuration_handler import Configuration\nfrom configuration.products_handler import ProductsHandler\n\nif __name__ == \"__main__\":\n logger = Log()\n conf = Configuration('configuration/configuration.yaml').load_configuration()\n ph = ProductsHandler(conf[\"products_path\"]) \n logger.info(\"Configuration loaded\")\n products = ph.load_products()\n logger.info(\"Products loaded from {}\".format(conf[\"products_path\"]))\n\n update, msg = spider.Spider(products, conf).crawl()\n if len(update) > 0:\n logger.info(\"Products to report\")\n mail_helper = MailHelper()\n mail_helper.send_mail('', msg, \"New prices lower\")\n \n logger.info(\"Mail sent\")\n mail_helper.close_connection()\n\n else:\n logger.info(\"Nothing to report\")\n \n ph.save_products(products)\n logger.info(\"Configuration saved\")\nelse:\n print(\"Exec this file as the main entrypoint! -> python3 init.py\")",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
workspace.obstacles.append(box)
workspace.obstacles.append(segment)
workspace.obstacles.append(circle)
<|reserved_special_token_0|>
viewer.draw_ws_img(signed_distance_field)
viewer.draw_ws_obstacles()
viewer.show_once()
<|reserved_special_token_1|>
<|reserved_special_token_0|>
env = EnvBox(dim=np.array([2.0, 2.0]))
box = Box(origin=np.array([-0.2, -0.2]))
segment = Segment(origin=np.array([0.4, -0.1]), orientation=0.2)
circle = Circle(origin=np.array([0.5, 0.5]), radius=0.2)
workspace = Workspace(env)
workspace.obstacles.append(box)
workspace.obstacles.append(segment)
workspace.obstacles.append(circle)
nb_points = 20
occupancy_map = occupancy_map(nb_points, workspace)
signed_distance_field = sdf(occupancy_map)
viewer = WorkspaceDrawer(workspace, wait_for_keyboard=True)
viewer.draw_ws_img(signed_distance_field)
viewer.draw_ws_obstacles()
viewer.show_once()
<|reserved_special_token_1|>
import demos_common_imports
from pyrieef.geometry.workspace import *
from pyrieef.geometry.pixel_map import sdf
from pyrieef.rendering.workspace_planar import WorkspaceDrawer
env = EnvBox(dim=np.array([2.0, 2.0]))
box = Box(origin=np.array([-0.2, -0.2]))
segment = Segment(origin=np.array([0.4, -0.1]), orientation=0.2)
circle = Circle(origin=np.array([0.5, 0.5]), radius=0.2)
workspace = Workspace(env)
workspace.obstacles.append(box)
workspace.obstacles.append(segment)
workspace.obstacles.append(circle)
nb_points = 20
occupancy_map = occupancy_map(nb_points, workspace)
signed_distance_field = sdf(occupancy_map)
viewer = WorkspaceDrawer(workspace, wait_for_keyboard=True)
viewer.draw_ws_img(signed_distance_field)
viewer.draw_ws_obstacles()
viewer.show_once()
<|reserved_special_token_1|>
#!/usr/bin/env python
# Copyright (c) 2018, University of Stuttgart
# All rights reserved.
#
# Permission to use, copy, modify, and distribute this software for any purpose
# with or without fee is hereby granted, provided that the above copyright
# notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
# REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
# AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
# INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
# LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
# OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
# PERFORMANCE OF THIS SOFTWARE.
#
# Jim Mainprice on Sunday June 13 2018
import demos_common_imports
from pyrieef.geometry.workspace import *
from pyrieef.geometry.pixel_map import sdf
from pyrieef.rendering.workspace_planar import WorkspaceDrawer
env = EnvBox(dim=np.array([2., 2.]))
box = Box(origin=np.array([-.2, -.2]))
segment = Segment(origin=np.array([.4, -.1]), orientation=0.2)
circle = Circle(origin=np.array([.5, .5]), radius=0.2)
workspace = Workspace(env)
workspace.obstacles.append(box)
workspace.obstacles.append(segment)
workspace.obstacles.append(circle)
# Compute Occupancy map and SDF
nb_points = 20
occupancy_map = occupancy_map(nb_points, workspace)
signed_distance_field = sdf(occupancy_map)
# Setup viewer
viewer = WorkspaceDrawer(workspace, wait_for_keyboard=True)
viewer.draw_ws_img(signed_distance_field)
# viewer.draw_ws_img(occupancy_map)
# import cv2
# Draw blured image
# viewer.draw_ws_img(
# ndimage.gaussian_filter(
# cv2.resize(src=signed_distance_field,
# dsize=(300, 300),
# interpolation=cv2.INTER_NEAREST), sigma=3))
viewer.draw_ws_obstacles()
viewer.show_once()
|
flexible
|
{
"blob_id": "0d6177660a9b9c22bcf6eb11763e7fe1ee03b46a",
"index": 3454,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nworkspace.obstacles.append(box)\nworkspace.obstacles.append(segment)\nworkspace.obstacles.append(circle)\n<mask token>\nviewer.draw_ws_img(signed_distance_field)\nviewer.draw_ws_obstacles()\nviewer.show_once()\n",
"step-3": "<mask token>\nenv = EnvBox(dim=np.array([2.0, 2.0]))\nbox = Box(origin=np.array([-0.2, -0.2]))\nsegment = Segment(origin=np.array([0.4, -0.1]), orientation=0.2)\ncircle = Circle(origin=np.array([0.5, 0.5]), radius=0.2)\nworkspace = Workspace(env)\nworkspace.obstacles.append(box)\nworkspace.obstacles.append(segment)\nworkspace.obstacles.append(circle)\nnb_points = 20\noccupancy_map = occupancy_map(nb_points, workspace)\nsigned_distance_field = sdf(occupancy_map)\nviewer = WorkspaceDrawer(workspace, wait_for_keyboard=True)\nviewer.draw_ws_img(signed_distance_field)\nviewer.draw_ws_obstacles()\nviewer.show_once()\n",
"step-4": "import demos_common_imports\nfrom pyrieef.geometry.workspace import *\nfrom pyrieef.geometry.pixel_map import sdf\nfrom pyrieef.rendering.workspace_planar import WorkspaceDrawer\nenv = EnvBox(dim=np.array([2.0, 2.0]))\nbox = Box(origin=np.array([-0.2, -0.2]))\nsegment = Segment(origin=np.array([0.4, -0.1]), orientation=0.2)\ncircle = Circle(origin=np.array([0.5, 0.5]), radius=0.2)\nworkspace = Workspace(env)\nworkspace.obstacles.append(box)\nworkspace.obstacles.append(segment)\nworkspace.obstacles.append(circle)\nnb_points = 20\noccupancy_map = occupancy_map(nb_points, workspace)\nsigned_distance_field = sdf(occupancy_map)\nviewer = WorkspaceDrawer(workspace, wait_for_keyboard=True)\nviewer.draw_ws_img(signed_distance_field)\nviewer.draw_ws_obstacles()\nviewer.show_once()\n",
"step-5": "#!/usr/bin/env python\n\n# Copyright (c) 2018, University of Stuttgart\n# All rights reserved.\n#\n# Permission to use, copy, modify, and distribute this software for any purpose\n# with or without fee is hereby granted, provided that the above copyright\n# notice and this permission notice appear in all copies.\n#\n# THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n# REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n# AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\n# INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\n# LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\n# OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\n# PERFORMANCE OF THIS SOFTWARE.\n#\n# Jim Mainprice on Sunday June 13 2018\n\nimport demos_common_imports\nfrom pyrieef.geometry.workspace import *\nfrom pyrieef.geometry.pixel_map import sdf\nfrom pyrieef.rendering.workspace_planar import WorkspaceDrawer\n\nenv = EnvBox(dim=np.array([2., 2.]))\nbox = Box(origin=np.array([-.2, -.2]))\nsegment = Segment(origin=np.array([.4, -.1]), orientation=0.2)\ncircle = Circle(origin=np.array([.5, .5]), radius=0.2)\nworkspace = Workspace(env)\nworkspace.obstacles.append(box)\nworkspace.obstacles.append(segment)\nworkspace.obstacles.append(circle)\n\n# Compute Occupancy map and SDF\nnb_points = 20\noccupancy_map = occupancy_map(nb_points, workspace)\nsigned_distance_field = sdf(occupancy_map)\n\n# Setup viewer\nviewer = WorkspaceDrawer(workspace, wait_for_keyboard=True)\nviewer.draw_ws_img(signed_distance_field)\n# viewer.draw_ws_img(occupancy_map)\n\n# import cv2\n# Draw blured image\n# viewer.draw_ws_img(\n# ndimage.gaussian_filter(\n# cv2.resize(src=signed_distance_field,\n# dsize=(300, 300),\n# interpolation=cv2.INTER_NEAREST), sigma=3))\n\nviewer.draw_ws_obstacles()\nviewer.show_once()\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
from django.urls import path
from .consumers import NotificationsConsumer
websocket_urlpatterns = [
path('ws/notifications', NotificationsConsumer),
]
|
normal
|
{
"blob_id": "31e5b249516f4e9d57d8fd82713966a69e0516b4",
"index": 9185,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwebsocket_urlpatterns = [path('ws/notifications', NotificationsConsumer)]\n",
"step-3": "from django.urls import path\nfrom .consumers import NotificationsConsumer\nwebsocket_urlpatterns = [path('ws/notifications', NotificationsConsumer)]\n",
"step-4": "from django.urls import path\n\nfrom .consumers import NotificationsConsumer\n\nwebsocket_urlpatterns = [\n path('ws/notifications', NotificationsConsumer),\n]\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Extractor(object):
"""docstring for Parser"""
def __init__(self, html, base_url):
self.soup = BeautifulSoup(html, 'html5lib')
self.base_url = base_url
def get_album(self):
galaries = self.soup.find('div', {'id': 'galleries'})
table = galaries.find('table')
families = table.find_all('a', href=True)
for family in families:
family_name = family.text.strip()
if family_name != '':
yield family_name, urljoin(self.base_url, family['href'])
def get_image_table(self):
tables = self.soup.find('table')
for td in tables.find_all('td'):
image_atag = td.find('a', href=True)
if image_atag is not None:
yield image_atag['href']
def get_pages(self):
pages = self.soup.find_all('a', href=True)
seen = list()
for page in pages:
if page is not None:
if 'index' in page['href']:
page_url = page['href']
if page_url not in seen:
seen.append(page_url)
yield page_url
def get_image_link(self):
"""
return downloadable image's url
"""
table = self.soup.find('table')
image_tag = table.find('img')
image_name = self.soup.find_all('b')[1].text
return image_tag['src'], image_name
def fetch(image_url, image_name, folder):
r = requests.get(image_url, stream=True)
image_file = os.path.join(folder, image_name)
with open(image_file, 'wb') as f:
for chunk in r.iter_content(1024):
f.write(chunk)
del r
def extract_image(page_html, family_url, folder):
"""
Extract image from page
"""
image_extractor = Extractor(page_html, family_url)
for url in image_extractor.get_image_table():
image_page_url = urljoin(family_url, url)
imres = requests.get(image_page_url)
image_page_extractor = Extractor(imres.text, image_page_url)
image_src, image_name = image_page_extractor.get_image_link()
image_link = urljoin(image_page_url, image_src)
print(image_link, image_name)
fetch(image_link, image_name, folder)
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Extractor(object):
"""docstring for Parser"""
def __init__(self, html, base_url):
self.soup = BeautifulSoup(html, 'html5lib')
self.base_url = base_url
def get_album(self):
galaries = self.soup.find('div', {'id': 'galleries'})
table = galaries.find('table')
families = table.find_all('a', href=True)
for family in families:
family_name = family.text.strip()
if family_name != '':
yield family_name, urljoin(self.base_url, family['href'])
def get_image_table(self):
tables = self.soup.find('table')
for td in tables.find_all('td'):
image_atag = td.find('a', href=True)
if image_atag is not None:
yield image_atag['href']
def get_pages(self):
pages = self.soup.find_all('a', href=True)
seen = list()
for page in pages:
if page is not None:
if 'index' in page['href']:
page_url = page['href']
if page_url not in seen:
seen.append(page_url)
yield page_url
def get_image_link(self):
"""
return downloadable image's url
"""
table = self.soup.find('table')
image_tag = table.find('img')
image_name = self.soup.find_all('b')[1].text
return image_tag['src'], image_name
def fetch(image_url, image_name, folder):
r = requests.get(image_url, stream=True)
image_file = os.path.join(folder, image_name)
with open(image_file, 'wb') as f:
for chunk in r.iter_content(1024):
f.write(chunk)
del r
def extract_image(page_html, family_url, folder):
"""
Extract image from page
"""
image_extractor = Extractor(page_html, family_url)
for url in image_extractor.get_image_table():
image_page_url = urljoin(family_url, url)
imres = requests.get(image_page_url)
image_page_extractor = Extractor(imres.text, image_page_url)
image_src, image_name = image_page_extractor.get_image_link()
image_link = urljoin(image_page_url, image_src)
print(image_link, image_name)
fetch(image_link, image_name, folder)
def download(url):
res = requests.get(url)
parser = Extractor(res.text, url)
for family, family_url in parser.get_album():
family_folder = os.path.join(DOWNLOAD_DIR, family)
print(family_folder)
os.makedirs(family_folder)
res = requests.get(family_url)
if res.status_code == 200:
page_extractor = Extractor(res.text, family_url)
count = 1
print('Page ', count)
extract_image(res.text, family_url, family_folder)
for page in page_extractor.get_pages():
page_url = urljoin(family_url, page)
count += 1
print('Page ', count)
r = requests.get(page_url)
extract_image(r.text, family_url, family_folder)
else:
print('%s has status code: %s' % (family, res.status_code))
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
os.makedirs(DOWNLOAD_DIR, exist_ok=True)
<|reserved_special_token_0|>
class Extractor(object):
"""docstring for Parser"""
def __init__(self, html, base_url):
self.soup = BeautifulSoup(html, 'html5lib')
self.base_url = base_url
def get_album(self):
galaries = self.soup.find('div', {'id': 'galleries'})
table = galaries.find('table')
families = table.find_all('a', href=True)
for family in families:
family_name = family.text.strip()
if family_name != '':
yield family_name, urljoin(self.base_url, family['href'])
def get_image_table(self):
tables = self.soup.find('table')
for td in tables.find_all('td'):
image_atag = td.find('a', href=True)
if image_atag is not None:
yield image_atag['href']
def get_pages(self):
pages = self.soup.find_all('a', href=True)
seen = list()
for page in pages:
if page is not None:
if 'index' in page['href']:
page_url = page['href']
if page_url not in seen:
seen.append(page_url)
yield page_url
def get_image_link(self):
"""
return downloadable image's url
"""
table = self.soup.find('table')
image_tag = table.find('img')
image_name = self.soup.find_all('b')[1].text
return image_tag['src'], image_name
def fetch(image_url, image_name, folder):
r = requests.get(image_url, stream=True)
image_file = os.path.join(folder, image_name)
with open(image_file, 'wb') as f:
for chunk in r.iter_content(1024):
f.write(chunk)
del r
def extract_image(page_html, family_url, folder):
"""
Extract image from page
"""
image_extractor = Extractor(page_html, family_url)
for url in image_extractor.get_image_table():
image_page_url = urljoin(family_url, url)
imres = requests.get(image_page_url)
image_page_extractor = Extractor(imres.text, image_page_url)
image_src, image_name = image_page_extractor.get_image_link()
image_link = urljoin(image_page_url, image_src)
print(image_link, image_name)
fetch(image_link, image_name, folder)
def download(url):
res = requests.get(url)
parser = Extractor(res.text, url)
for family, family_url in parser.get_album():
family_folder = os.path.join(DOWNLOAD_DIR, family)
print(family_folder)
os.makedirs(family_folder)
res = requests.get(family_url)
if res.status_code == 200:
page_extractor = Extractor(res.text, family_url)
count = 1
print('Page ', count)
extract_image(res.text, family_url, family_folder)
for page in page_extractor.get_pages():
page_url = urljoin(family_url, page)
count += 1
print('Page ', count)
r = requests.get(page_url)
extract_image(r.text, family_url, family_folder)
else:
print('%s has status code: %s' % (family, res.status_code))
if __name__ == '__main__':
download(url)
<|reserved_special_token_1|>
import requests
import os
from bs4 import BeautifulSoup
from urllib.parse import urljoin
CURRENT_DIR = os.getcwd()
DOWNLOAD_DIR = os.path.join(CURRENT_DIR, 'malware_album')
os.makedirs(DOWNLOAD_DIR, exist_ok=True)
url = 'http://old.vision.ece.ucsb.edu/~lakshman/malware_images/album/'
class Extractor(object):
"""docstring for Parser"""
def __init__(self, html, base_url):
self.soup = BeautifulSoup(html, 'html5lib')
self.base_url = base_url
def get_album(self):
galaries = self.soup.find('div', {'id': 'galleries'})
table = galaries.find('table')
families = table.find_all('a', href=True)
for family in families:
family_name = family.text.strip()
if family_name != '':
yield family_name, urljoin(self.base_url, family['href'])
def get_image_table(self):
tables = self.soup.find('table')
for td in tables.find_all('td'):
image_atag = td.find('a', href=True)
if image_atag is not None:
yield image_atag['href']
def get_pages(self):
pages = self.soup.find_all('a', href=True)
seen = list()
for page in pages:
if page is not None:
if 'index' in page['href']:
page_url = page['href']
if page_url not in seen:
seen.append(page_url)
yield page_url
def get_image_link(self):
"""
return downloadable image's url
"""
table = self.soup.find('table')
image_tag = table.find('img')
image_name = self.soup.find_all('b')[1].text
return image_tag['src'], image_name
def fetch(image_url, image_name, folder):
r = requests.get(image_url, stream=True)
image_file = os.path.join(folder, image_name)
with open(image_file, 'wb') as f:
for chunk in r.iter_content(1024):
f.write(chunk)
del r
def extract_image(page_html, family_url, folder):
"""
Extract image from page
"""
image_extractor = Extractor(page_html, family_url)
for url in image_extractor.get_image_table():
image_page_url = urljoin(family_url, url)
imres = requests.get(image_page_url)
image_page_extractor = Extractor(imres.text, image_page_url)
image_src, image_name = image_page_extractor.get_image_link()
image_link = urljoin(image_page_url, image_src)
print(image_link, image_name)
fetch(image_link, image_name, folder)
def download(url):
res = requests.get(url)
parser = Extractor(res.text, url)
for family, family_url in parser.get_album():
family_folder = os.path.join(DOWNLOAD_DIR, family)
print(family_folder)
os.makedirs(family_folder)
res = requests.get(family_url)
if res.status_code == 200:
page_extractor = Extractor(res.text, family_url)
count = 1
print('Page ', count)
extract_image(res.text, family_url, family_folder)
for page in page_extractor.get_pages():
page_url = urljoin(family_url, page)
count += 1
print('Page ', count)
r = requests.get(page_url)
extract_image(r.text, family_url, family_folder)
else:
print('%s has status code: %s' % (family, res.status_code))
if __name__ == '__main__':
download(url)
<|reserved_special_token_1|>
import requests
import os
from bs4 import BeautifulSoup
from urllib.parse import urljoin
CURRENT_DIR = os.getcwd()
DOWNLOAD_DIR = os.path.join(CURRENT_DIR, 'malware_album')
os.makedirs(DOWNLOAD_DIR, exist_ok=True)
url = 'http://old.vision.ece.ucsb.edu/~lakshman/malware_images/album/'
class Extractor(object):
"""docstring for Parser"""
def __init__(self, html, base_url):
self.soup = BeautifulSoup(html, "html5lib")
self.base_url = base_url
def get_album(self):
galaries = self.soup.find("div", {"id": "galleries"})
table = galaries.find("table")
families = table.find_all('a', href=True)
for family in families:
family_name = family.text.strip()
if family_name != "":
yield family_name, urljoin(self.base_url, family['href'])
def get_image_table(self):
tables = self.soup.find('table')
for td in tables.find_all('td'):
image_atag = td.find('a', href=True)
if image_atag is not None:
yield image_atag['href']
def get_pages(self):
pages = self.soup.find_all('a', href=True)
seen = list()
for page in pages:
if page is not None:
if 'index' in page['href']:
page_url = page['href']
if page_url not in seen:
seen.append(page_url)
yield page_url
def get_image_link(self):
"""
return downloadable image's url
"""
table = self.soup.find('table')
image_tag = table.find('img')
image_name = self.soup.find_all("b")[1].text
return image_tag['src'], image_name
# image = td.find_all('img')
# print(image)
# if image is not None:
# return urljoin(self.base_url, image['src'])
def fetch(image_url, image_name, folder):
r = requests.get(image_url, stream=True)
image_file = os.path.join(folder, image_name)
with open(image_file, 'wb') as f:
for chunk in r.iter_content(1024):
f.write(chunk)
del r
def extract_image(page_html, family_url, folder):
"""
Extract image from page
"""
image_extractor = Extractor(page_html, family_url)
for url in image_extractor.get_image_table():
image_page_url = urljoin(family_url, url)
# print(image_page_url)
imres = requests.get(image_page_url)
image_page_extractor = Extractor(imres.text, image_page_url)
image_src, image_name = image_page_extractor.get_image_link()
image_link = urljoin(image_page_url, image_src)
print(image_link, image_name)
# Download image
fetch(image_link, image_name, folder)
def download(url):
res = requests.get(url)
parser = Extractor(res.text, url)
# for each family, fetch image
for family, family_url in parser.get_album():
family_folder = os.path.join(DOWNLOAD_DIR, family)
print(family_folder)
os.makedirs(family_folder)
# print(os.path.join(DOWNLOAD_DIR, family_folder))
res = requests.get(family_url)
if res.status_code == 200:
page_extractor = Extractor(res.text, family_url)
count = 1
print('Page ', count)
extract_image(res.text, family_url, family_folder) # Extract on first page
for page in page_extractor.get_pages():
page_url = urljoin(family_url, page)
count += 1
print("Page ", count)
r = requests.get(page_url)
extract_image(r.text, family_url, family_folder)
# print('>', image_extractor.get_image_link())
else:
print('%s has status code: %s' % (family, res.status_code))
if __name__ == '__main__':
download(url)
|
flexible
|
{
"blob_id": "a53d7b4c93fa49fb0162138d4a262fe7a5546148",
"index": 5215,
"step-1": "<mask token>\n\n\nclass Extractor(object):\n \"\"\"docstring for Parser\"\"\"\n\n def __init__(self, html, base_url):\n self.soup = BeautifulSoup(html, 'html5lib')\n self.base_url = base_url\n\n def get_album(self):\n galaries = self.soup.find('div', {'id': 'galleries'})\n table = galaries.find('table')\n families = table.find_all('a', href=True)\n for family in families:\n family_name = family.text.strip()\n if family_name != '':\n yield family_name, urljoin(self.base_url, family['href'])\n\n def get_image_table(self):\n tables = self.soup.find('table')\n for td in tables.find_all('td'):\n image_atag = td.find('a', href=True)\n if image_atag is not None:\n yield image_atag['href']\n\n def get_pages(self):\n pages = self.soup.find_all('a', href=True)\n seen = list()\n for page in pages:\n if page is not None:\n if 'index' in page['href']:\n page_url = page['href']\n if page_url not in seen:\n seen.append(page_url)\n yield page_url\n\n def get_image_link(self):\n \"\"\"\n return downloadable image's url\n \"\"\"\n table = self.soup.find('table')\n image_tag = table.find('img')\n image_name = self.soup.find_all('b')[1].text\n return image_tag['src'], image_name\n\n\ndef fetch(image_url, image_name, folder):\n r = requests.get(image_url, stream=True)\n image_file = os.path.join(folder, image_name)\n with open(image_file, 'wb') as f:\n for chunk in r.iter_content(1024):\n f.write(chunk)\n del r\n\n\ndef extract_image(page_html, family_url, folder):\n \"\"\"\n Extract image from page\n \"\"\"\n image_extractor = Extractor(page_html, family_url)\n for url in image_extractor.get_image_table():\n image_page_url = urljoin(family_url, url)\n imres = requests.get(image_page_url)\n image_page_extractor = Extractor(imres.text, image_page_url)\n image_src, image_name = image_page_extractor.get_image_link()\n image_link = urljoin(image_page_url, image_src)\n print(image_link, image_name)\n fetch(image_link, image_name, folder)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass Extractor(object):\n \"\"\"docstring for Parser\"\"\"\n\n def __init__(self, html, base_url):\n self.soup = BeautifulSoup(html, 'html5lib')\n self.base_url = base_url\n\n def get_album(self):\n galaries = self.soup.find('div', {'id': 'galleries'})\n table = galaries.find('table')\n families = table.find_all('a', href=True)\n for family in families:\n family_name = family.text.strip()\n if family_name != '':\n yield family_name, urljoin(self.base_url, family['href'])\n\n def get_image_table(self):\n tables = self.soup.find('table')\n for td in tables.find_all('td'):\n image_atag = td.find('a', href=True)\n if image_atag is not None:\n yield image_atag['href']\n\n def get_pages(self):\n pages = self.soup.find_all('a', href=True)\n seen = list()\n for page in pages:\n if page is not None:\n if 'index' in page['href']:\n page_url = page['href']\n if page_url not in seen:\n seen.append(page_url)\n yield page_url\n\n def get_image_link(self):\n \"\"\"\n return downloadable image's url\n \"\"\"\n table = self.soup.find('table')\n image_tag = table.find('img')\n image_name = self.soup.find_all('b')[1].text\n return image_tag['src'], image_name\n\n\ndef fetch(image_url, image_name, folder):\n r = requests.get(image_url, stream=True)\n image_file = os.path.join(folder, image_name)\n with open(image_file, 'wb') as f:\n for chunk in r.iter_content(1024):\n f.write(chunk)\n del r\n\n\ndef extract_image(page_html, family_url, folder):\n \"\"\"\n Extract image from page\n \"\"\"\n image_extractor = Extractor(page_html, family_url)\n for url in image_extractor.get_image_table():\n image_page_url = urljoin(family_url, url)\n imres = requests.get(image_page_url)\n image_page_extractor = Extractor(imres.text, image_page_url)\n image_src, image_name = image_page_extractor.get_image_link()\n image_link = urljoin(image_page_url, image_src)\n print(image_link, image_name)\n fetch(image_link, image_name, folder)\n\n\ndef download(url):\n res = requests.get(url)\n parser = Extractor(res.text, url)\n for family, family_url in parser.get_album():\n family_folder = os.path.join(DOWNLOAD_DIR, family)\n print(family_folder)\n os.makedirs(family_folder)\n res = requests.get(family_url)\n if res.status_code == 200:\n page_extractor = Extractor(res.text, family_url)\n count = 1\n print('Page ', count)\n extract_image(res.text, family_url, family_folder)\n for page in page_extractor.get_pages():\n page_url = urljoin(family_url, page)\n count += 1\n print('Page ', count)\n r = requests.get(page_url)\n extract_image(r.text, family_url, family_folder)\n else:\n print('%s has status code: %s' % (family, res.status_code))\n\n\n<mask token>\n",
"step-3": "<mask token>\nos.makedirs(DOWNLOAD_DIR, exist_ok=True)\n<mask token>\n\n\nclass Extractor(object):\n \"\"\"docstring for Parser\"\"\"\n\n def __init__(self, html, base_url):\n self.soup = BeautifulSoup(html, 'html5lib')\n self.base_url = base_url\n\n def get_album(self):\n galaries = self.soup.find('div', {'id': 'galleries'})\n table = galaries.find('table')\n families = table.find_all('a', href=True)\n for family in families:\n family_name = family.text.strip()\n if family_name != '':\n yield family_name, urljoin(self.base_url, family['href'])\n\n def get_image_table(self):\n tables = self.soup.find('table')\n for td in tables.find_all('td'):\n image_atag = td.find('a', href=True)\n if image_atag is not None:\n yield image_atag['href']\n\n def get_pages(self):\n pages = self.soup.find_all('a', href=True)\n seen = list()\n for page in pages:\n if page is not None:\n if 'index' in page['href']:\n page_url = page['href']\n if page_url not in seen:\n seen.append(page_url)\n yield page_url\n\n def get_image_link(self):\n \"\"\"\n return downloadable image's url\n \"\"\"\n table = self.soup.find('table')\n image_tag = table.find('img')\n image_name = self.soup.find_all('b')[1].text\n return image_tag['src'], image_name\n\n\ndef fetch(image_url, image_name, folder):\n r = requests.get(image_url, stream=True)\n image_file = os.path.join(folder, image_name)\n with open(image_file, 'wb') as f:\n for chunk in r.iter_content(1024):\n f.write(chunk)\n del r\n\n\ndef extract_image(page_html, family_url, folder):\n \"\"\"\n Extract image from page\n \"\"\"\n image_extractor = Extractor(page_html, family_url)\n for url in image_extractor.get_image_table():\n image_page_url = urljoin(family_url, url)\n imres = requests.get(image_page_url)\n image_page_extractor = Extractor(imres.text, image_page_url)\n image_src, image_name = image_page_extractor.get_image_link()\n image_link = urljoin(image_page_url, image_src)\n print(image_link, image_name)\n fetch(image_link, image_name, folder)\n\n\ndef download(url):\n res = requests.get(url)\n parser = Extractor(res.text, url)\n for family, family_url in parser.get_album():\n family_folder = os.path.join(DOWNLOAD_DIR, family)\n print(family_folder)\n os.makedirs(family_folder)\n res = requests.get(family_url)\n if res.status_code == 200:\n page_extractor = Extractor(res.text, family_url)\n count = 1\n print('Page ', count)\n extract_image(res.text, family_url, family_folder)\n for page in page_extractor.get_pages():\n page_url = urljoin(family_url, page)\n count += 1\n print('Page ', count)\n r = requests.get(page_url)\n extract_image(r.text, family_url, family_folder)\n else:\n print('%s has status code: %s' % (family, res.status_code))\n\n\nif __name__ == '__main__':\n download(url)\n",
"step-4": "import requests\nimport os\nfrom bs4 import BeautifulSoup\nfrom urllib.parse import urljoin\nCURRENT_DIR = os.getcwd()\nDOWNLOAD_DIR = os.path.join(CURRENT_DIR, 'malware_album')\nos.makedirs(DOWNLOAD_DIR, exist_ok=True)\nurl = 'http://old.vision.ece.ucsb.edu/~lakshman/malware_images/album/'\n\n\nclass Extractor(object):\n \"\"\"docstring for Parser\"\"\"\n\n def __init__(self, html, base_url):\n self.soup = BeautifulSoup(html, 'html5lib')\n self.base_url = base_url\n\n def get_album(self):\n galaries = self.soup.find('div', {'id': 'galleries'})\n table = galaries.find('table')\n families = table.find_all('a', href=True)\n for family in families:\n family_name = family.text.strip()\n if family_name != '':\n yield family_name, urljoin(self.base_url, family['href'])\n\n def get_image_table(self):\n tables = self.soup.find('table')\n for td in tables.find_all('td'):\n image_atag = td.find('a', href=True)\n if image_atag is not None:\n yield image_atag['href']\n\n def get_pages(self):\n pages = self.soup.find_all('a', href=True)\n seen = list()\n for page in pages:\n if page is not None:\n if 'index' in page['href']:\n page_url = page['href']\n if page_url not in seen:\n seen.append(page_url)\n yield page_url\n\n def get_image_link(self):\n \"\"\"\n return downloadable image's url\n \"\"\"\n table = self.soup.find('table')\n image_tag = table.find('img')\n image_name = self.soup.find_all('b')[1].text\n return image_tag['src'], image_name\n\n\ndef fetch(image_url, image_name, folder):\n r = requests.get(image_url, stream=True)\n image_file = os.path.join(folder, image_name)\n with open(image_file, 'wb') as f:\n for chunk in r.iter_content(1024):\n f.write(chunk)\n del r\n\n\ndef extract_image(page_html, family_url, folder):\n \"\"\"\n Extract image from page\n \"\"\"\n image_extractor = Extractor(page_html, family_url)\n for url in image_extractor.get_image_table():\n image_page_url = urljoin(family_url, url)\n imres = requests.get(image_page_url)\n image_page_extractor = Extractor(imres.text, image_page_url)\n image_src, image_name = image_page_extractor.get_image_link()\n image_link = urljoin(image_page_url, image_src)\n print(image_link, image_name)\n fetch(image_link, image_name, folder)\n\n\ndef download(url):\n res = requests.get(url)\n parser = Extractor(res.text, url)\n for family, family_url in parser.get_album():\n family_folder = os.path.join(DOWNLOAD_DIR, family)\n print(family_folder)\n os.makedirs(family_folder)\n res = requests.get(family_url)\n if res.status_code == 200:\n page_extractor = Extractor(res.text, family_url)\n count = 1\n print('Page ', count)\n extract_image(res.text, family_url, family_folder)\n for page in page_extractor.get_pages():\n page_url = urljoin(family_url, page)\n count += 1\n print('Page ', count)\n r = requests.get(page_url)\n extract_image(r.text, family_url, family_folder)\n else:\n print('%s has status code: %s' % (family, res.status_code))\n\n\nif __name__ == '__main__':\n download(url)\n",
"step-5": "import requests\nimport os\nfrom bs4 import BeautifulSoup\nfrom urllib.parse import urljoin\n\nCURRENT_DIR = os.getcwd()\nDOWNLOAD_DIR = os.path.join(CURRENT_DIR, 'malware_album')\n\nos.makedirs(DOWNLOAD_DIR, exist_ok=True)\n\nurl = 'http://old.vision.ece.ucsb.edu/~lakshman/malware_images/album/'\n\n\nclass Extractor(object):\n \"\"\"docstring for Parser\"\"\"\n def __init__(self, html, base_url):\n self.soup = BeautifulSoup(html, \"html5lib\")\n self.base_url = base_url\n\n def get_album(self):\n galaries = self.soup.find(\"div\", {\"id\": \"galleries\"})\n table = galaries.find(\"table\")\n families = table.find_all('a', href=True)\n for family in families:\n family_name = family.text.strip()\n if family_name != \"\":\n yield family_name, urljoin(self.base_url, family['href'])\n\n\n def get_image_table(self):\n tables = self.soup.find('table')\n for td in tables.find_all('td'):\n image_atag = td.find('a', href=True)\n if image_atag is not None:\n yield image_atag['href']\n\n def get_pages(self):\n pages = self.soup.find_all('a', href=True)\n seen = list()\n for page in pages:\n if page is not None:\n if 'index' in page['href']:\n page_url = page['href']\n if page_url not in seen:\n seen.append(page_url)\n yield page_url\n\n def get_image_link(self):\n \"\"\"\n return downloadable image's url\n \"\"\"\n table = self.soup.find('table')\n image_tag = table.find('img')\n image_name = self.soup.find_all(\"b\")[1].text\n return image_tag['src'], image_name\n\n # image = td.find_all('img')\n # print(image)\n # if image is not None:\n # return urljoin(self.base_url, image['src'])\n\n\n\ndef fetch(image_url, image_name, folder):\n r = requests.get(image_url, stream=True)\n image_file = os.path.join(folder, image_name)\n with open(image_file, 'wb') as f:\n for chunk in r.iter_content(1024):\n f.write(chunk)\n del r\n\n\ndef extract_image(page_html, family_url, folder):\n \"\"\"\n Extract image from page\n \"\"\"\n image_extractor = Extractor(page_html, family_url)\n for url in image_extractor.get_image_table():\n image_page_url = urljoin(family_url, url)\n # print(image_page_url)\n imres = requests.get(image_page_url)\n image_page_extractor = Extractor(imres.text, image_page_url)\n image_src, image_name = image_page_extractor.get_image_link()\n\n image_link = urljoin(image_page_url, image_src)\n\n print(image_link, image_name)\n # Download image\n fetch(image_link, image_name, folder)\n\n\n\ndef download(url):\n res = requests.get(url)\n parser = Extractor(res.text, url)\n # for each family, fetch image\n for family, family_url in parser.get_album():\n family_folder = os.path.join(DOWNLOAD_DIR, family)\n print(family_folder)\n os.makedirs(family_folder)\n # print(os.path.join(DOWNLOAD_DIR, family_folder))\n\n res = requests.get(family_url)\n if res.status_code == 200:\n page_extractor = Extractor(res.text, family_url)\n count = 1\n print('Page ', count)\n extract_image(res.text, family_url, family_folder) # Extract on first page\n for page in page_extractor.get_pages():\n page_url = urljoin(family_url, page)\n\n count += 1\n print(\"Page \", count)\n\n r = requests.get(page_url)\n extract_image(r.text, family_url, family_folder)\n\n\n # print('>', image_extractor.get_image_link())\n else:\n print('%s has status code: %s' % (family, res.status_code))\n\n\n\n\n\nif __name__ == '__main__':\n download(url)\n\n\n\n",
"step-ids": [
9,
10,
11,
13,
14
]
}
|
[
9,
10,
11,
13,
14
] |
from huobi import RequestClient
from huobi.constant.test import *
request_client = RequestClient(api_key=g_api_key, secret_key=g_secret_key)
obj_list = request_client.get_cross_margin_loan_orders()
if len(obj_list):
for obj in obj_list:
obj.print_object()
print()
|
normal
|
{
"blob_id": "c65969bba72142f4a328f978d78e0235cd56e393",
"index": 8618,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif len(obj_list):\n for obj in obj_list:\n obj.print_object()\n print()\n",
"step-3": "<mask token>\nrequest_client = RequestClient(api_key=g_api_key, secret_key=g_secret_key)\nobj_list = request_client.get_cross_margin_loan_orders()\nif len(obj_list):\n for obj in obj_list:\n obj.print_object()\n print()\n",
"step-4": "from huobi import RequestClient\nfrom huobi.constant.test import *\nrequest_client = RequestClient(api_key=g_api_key, secret_key=g_secret_key)\nobj_list = request_client.get_cross_margin_loan_orders()\nif len(obj_list):\n for obj in obj_list:\n obj.print_object()\n print()\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
def get_exact(x, y, t, trunc):
"""Get the exact solution at a set t
"""
Z = 0
for n in range(1, trunc):
for m in range(1, trunc):
Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n **
2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-
2 + 2 * (-1) ** m))
Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(
-(n ** 2 + m ** 2) * np.pi ** 2 * k * t)
Z_denom = n ** 7 * np.pi ** 10 * m ** 3
Z += Z_num * Z_num_xy / Z_denom
return Z
<|reserved_special_token_0|>
def do_timestep(u0, u):
u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,
1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +
u0[1:-1, :-2]) / dy2)
u0 = u.copy()
return u0, u
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def get_exact(x, y, t, trunc):
"""Get the exact solution at a set t
"""
Z = 0
for n in range(1, trunc):
for m in range(1, trunc):
Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n **
2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-
2 + 2 * (-1) ** m))
Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(
-(n ** 2 + m ** 2) * np.pi ** 2 * k * t)
Z_denom = n ** 7 * np.pi ** 10 * m ** 3
Z += Z_num * Z_num_xy / Z_denom
return Z
def get_L_norm(exact, u):
diffs = abs(exact - u)
l_diffs = []
for row in diffs:
l_diffs.append(max(row))
return max(l_diffs), diffs
for i in range(nx):
for j in range(ny):
x = i * dx
y = j * dy
u0[i, j] = x * (1 - x ** 5) * y * (1 - y)
u_exact[i, j] = get_exact(x, y, t_end, 10)
def do_timestep(u0, u):
u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,
1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +
u0[1:-1, :-2]) / dy2)
u0 = u.copy()
return u0, u
<|reserved_special_token_0|>
ax.set_title('2D distribution after 80 time steps using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_plot.png')
<|reserved_special_token_0|>
ax.set_title('|f_exact - f_ftcs| Using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
<|reserved_special_token_0|>
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_error.png')
print('The L_infinity error for FTCS is: ' + str(l_inf_norm))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
x_bound = y_bound = 1.0
dx = dy = 0.05
k = 0.1
nx, ny = int(x_bound / dx), int(y_bound / dy)
dx2, dy2 = dx * dx, dy * dy
dt = dx2 / k / 4.0
t_end = 80 * dt
u0 = np.zeros((nx, ny))
u_exact = np.zeros((nx, ny))
u = np.zeros((nx, ny))
def get_exact(x, y, t, trunc):
"""Get the exact solution at a set t
"""
Z = 0
for n in range(1, trunc):
for m in range(1, trunc):
Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n **
2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-
2 + 2 * (-1) ** m))
Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(
-(n ** 2 + m ** 2) * np.pi ** 2 * k * t)
Z_denom = n ** 7 * np.pi ** 10 * m ** 3
Z += Z_num * Z_num_xy / Z_denom
return Z
def get_L_norm(exact, u):
diffs = abs(exact - u)
l_diffs = []
for row in diffs:
l_diffs.append(max(row))
return max(l_diffs), diffs
for i in range(nx):
for j in range(ny):
x = i * dx
y = j * dy
u0[i, j] = x * (1 - x ** 5) * y * (1 - y)
u_exact[i, j] = get_exact(x, y, t_end, 10)
def do_timestep(u0, u):
u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,
1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +
u0[1:-1, :-2]) / dy2)
u0 = u.copy()
return u0, u
u0, u = do_timestep(u0, u)
l_inf_norm, norm_diff_vals = get_L_norm(u_exact, u0)
fig = plt.figure(1)
ax = fig.add_subplot(111)
im = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=0, vmax=0.06)
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
ax.set_title('2D distribution after 80 time steps using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_plot.png')
fig = plt.figure(2)
ax = fig.add_subplot(111)
ax.set_title('|f_exact - f_ftcs| Using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
im = ax.imshow(norm_diff_vals.copy(), cmap=plt.get_cmap('hot'), vmin=0,
vmax=l_inf_norm)
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_error.png')
print('The L_infinity error for FTCS is: ' + str(l_inf_norm))
<|reserved_special_token_1|>
import numpy as np
import matplotlib.pyplot as plt
x_bound = y_bound = 1.0
dx = dy = 0.05
k = 0.1
nx, ny = int(x_bound / dx), int(y_bound / dy)
dx2, dy2 = dx * dx, dy * dy
dt = dx2 / k / 4.0
t_end = 80 * dt
u0 = np.zeros((nx, ny))
u_exact = np.zeros((nx, ny))
u = np.zeros((nx, ny))
def get_exact(x, y, t, trunc):
"""Get the exact solution at a set t
"""
Z = 0
for n in range(1, trunc):
for m in range(1, trunc):
Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n **
2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-
2 + 2 * (-1) ** m))
Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(
-(n ** 2 + m ** 2) * np.pi ** 2 * k * t)
Z_denom = n ** 7 * np.pi ** 10 * m ** 3
Z += Z_num * Z_num_xy / Z_denom
return Z
def get_L_norm(exact, u):
diffs = abs(exact - u)
l_diffs = []
for row in diffs:
l_diffs.append(max(row))
return max(l_diffs), diffs
for i in range(nx):
for j in range(ny):
x = i * dx
y = j * dy
u0[i, j] = x * (1 - x ** 5) * y * (1 - y)
u_exact[i, j] = get_exact(x, y, t_end, 10)
def do_timestep(u0, u):
u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,
1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +
u0[1:-1, :-2]) / dy2)
u0 = u.copy()
return u0, u
u0, u = do_timestep(u0, u)
l_inf_norm, norm_diff_vals = get_L_norm(u_exact, u0)
fig = plt.figure(1)
ax = fig.add_subplot(111)
im = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=0, vmax=0.06)
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
ax.set_title('2D distribution after 80 time steps using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_plot.png')
fig = plt.figure(2)
ax = fig.add_subplot(111)
ax.set_title('|f_exact - f_ftcs| Using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
im = ax.imshow(norm_diff_vals.copy(), cmap=plt.get_cmap('hot'), vmin=0,
vmax=l_inf_norm)
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_error.png')
print('The L_infinity error for FTCS is: ' + str(l_inf_norm))
<|reserved_special_token_1|>
import numpy as np
import matplotlib.pyplot as plt
# some important constants
x_bound = y_bound = 1.
dx = dy = 0.05
k = 0.1
nx, ny = int(x_bound/dx), int(y_bound/dy)
dx2, dy2 = dx*dx, dy*dy
dt = (dx2 / k) / 4.0
t_end = 80 * dt
# set the grid
u0 = np.zeros((nx, ny))
u_exact = np.zeros((nx, ny))
u = np.zeros((nx, ny))
def get_exact(x, y, t, trunc):
"""Get the exact solution at a set t
"""
Z=0
for n in range(1, trunc):
for m in range(1, trunc):
Z_num = -120 * ( ((-n)**4 * np.pi**4 * (-1)**n) +\
(12 * n**2 * np.pi ** 2 * (-1)**n)\
+ 24 + (24 * (-1)**(1+n))\
*(-2 + (2*(-1)**m) ) )
Z_num_xy = np.sin(n*x*np.pi)*np.sin(m*y*np.pi)\
* np.exp(-(n**2 + m**2) * np.pi**2 * k * t)
Z_denom = n**7 * np.pi**10 * m**3
Z += Z_num * Z_num_xy / Z_denom
return Z
def get_L_norm(exact, u):
diffs = abs(exact - u)
l_diffs = []
for row in diffs:
l_diffs.append(max(row))
return max(l_diffs), diffs
# Initial conditions
for i in range(nx):
for j in range(ny):
x = i*dx
y = j*dy
u0[i,j] = x * (1-x**5) * y * (1-y)
u_exact[i,j] = get_exact(x, y, t_end, 10)
def do_timestep(u0, u):
# Propagate with forward-difference in time, central-difference in space
u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * (
(u0[2:, 1:-1] - 2*u0[1:-1, 1:-1] + u0[:-2, 1:-1])/dx2
+ (u0[1:-1, 2:] - 2*u0[1:-1, 1:-1] + u0[1:-1, :-2])/dy2 )
u0 = u.copy()
return u0, u
u0, u = do_timestep(u0, u)
l_inf_norm, norm_diff_vals = get_L_norm(u_exact, u0)
fig = plt.figure(1)
ax = fig.add_subplot(111)
im = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=0, vmax=0.06)
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
ax.set_title('2D distribution after 80 time steps using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_plot.png')
fig = plt.figure(2)
ax = fig.add_subplot(111)
ax.set_title('|f_exact - f_ftcs| Using FTCS')
plt.xlabel('x node [-]')
plt.ylabel('y node [-]')
im = ax.imshow(norm_diff_vals.copy(), cmap=plt.get_cmap('hot'), vmin=0,\
vmax=l_inf_norm)
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
fig.colorbar(im, cax=cbar_ax)
plt.savefig('./writeup/problem2_error.png')
print("The L_infinity error for FTCS is: " + str(l_inf_norm))
|
flexible
|
{
"blob_id": "c556aaf6aecb3c91d9574e0a158a9fa954108d70",
"index": 8193,
"step-1": "<mask token>\n\n\ndef get_exact(x, y, t, trunc):\n \"\"\"Get the exact solution at a set t\n \"\"\"\n Z = 0\n for n in range(1, trunc):\n for m in range(1, trunc):\n Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n ** \n 2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-\n 2 + 2 * (-1) ** m))\n Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(\n -(n ** 2 + m ** 2) * np.pi ** 2 * k * t)\n Z_denom = n ** 7 * np.pi ** 10 * m ** 3\n Z += Z_num * Z_num_xy / Z_denom\n return Z\n\n\n<mask token>\n\n\ndef do_timestep(u0, u):\n u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,\n 1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +\n u0[1:-1, :-2]) / dy2)\n u0 = u.copy()\n return u0, u\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_exact(x, y, t, trunc):\n \"\"\"Get the exact solution at a set t\n \"\"\"\n Z = 0\n for n in range(1, trunc):\n for m in range(1, trunc):\n Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n ** \n 2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-\n 2 + 2 * (-1) ** m))\n Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(\n -(n ** 2 + m ** 2) * np.pi ** 2 * k * t)\n Z_denom = n ** 7 * np.pi ** 10 * m ** 3\n Z += Z_num * Z_num_xy / Z_denom\n return Z\n\n\ndef get_L_norm(exact, u):\n diffs = abs(exact - u)\n l_diffs = []\n for row in diffs:\n l_diffs.append(max(row))\n return max(l_diffs), diffs\n\n\nfor i in range(nx):\n for j in range(ny):\n x = i * dx\n y = j * dy\n u0[i, j] = x * (1 - x ** 5) * y * (1 - y)\n u_exact[i, j] = get_exact(x, y, t_end, 10)\n\n\ndef do_timestep(u0, u):\n u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,\n 1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +\n u0[1:-1, :-2]) / dy2)\n u0 = u.copy()\n return u0, u\n\n\n<mask token>\nax.set_title('2D distribution after 80 time steps using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_plot.png')\n<mask token>\nax.set_title('|f_exact - f_ftcs| Using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\n<mask token>\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_error.png')\nprint('The L_infinity error for FTCS is: ' + str(l_inf_norm))\n",
"step-3": "<mask token>\nx_bound = y_bound = 1.0\ndx = dy = 0.05\nk = 0.1\nnx, ny = int(x_bound / dx), int(y_bound / dy)\ndx2, dy2 = dx * dx, dy * dy\ndt = dx2 / k / 4.0\nt_end = 80 * dt\nu0 = np.zeros((nx, ny))\nu_exact = np.zeros((nx, ny))\nu = np.zeros((nx, ny))\n\n\ndef get_exact(x, y, t, trunc):\n \"\"\"Get the exact solution at a set t\n \"\"\"\n Z = 0\n for n in range(1, trunc):\n for m in range(1, trunc):\n Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n ** \n 2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-\n 2 + 2 * (-1) ** m))\n Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(\n -(n ** 2 + m ** 2) * np.pi ** 2 * k * t)\n Z_denom = n ** 7 * np.pi ** 10 * m ** 3\n Z += Z_num * Z_num_xy / Z_denom\n return Z\n\n\ndef get_L_norm(exact, u):\n diffs = abs(exact - u)\n l_diffs = []\n for row in diffs:\n l_diffs.append(max(row))\n return max(l_diffs), diffs\n\n\nfor i in range(nx):\n for j in range(ny):\n x = i * dx\n y = j * dy\n u0[i, j] = x * (1 - x ** 5) * y * (1 - y)\n u_exact[i, j] = get_exact(x, y, t_end, 10)\n\n\ndef do_timestep(u0, u):\n u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,\n 1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +\n u0[1:-1, :-2]) / dy2)\n u0 = u.copy()\n return u0, u\n\n\nu0, u = do_timestep(u0, u)\nl_inf_norm, norm_diff_vals = get_L_norm(u_exact, u0)\nfig = plt.figure(1)\nax = fig.add_subplot(111)\nim = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=0, vmax=0.06)\ncbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])\nax.set_title('2D distribution after 80 time steps using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_plot.png')\nfig = plt.figure(2)\nax = fig.add_subplot(111)\nax.set_title('|f_exact - f_ftcs| Using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nim = ax.imshow(norm_diff_vals.copy(), cmap=plt.get_cmap('hot'), vmin=0,\n vmax=l_inf_norm)\ncbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_error.png')\nprint('The L_infinity error for FTCS is: ' + str(l_inf_norm))\n",
"step-4": "import numpy as np\nimport matplotlib.pyplot as plt\nx_bound = y_bound = 1.0\ndx = dy = 0.05\nk = 0.1\nnx, ny = int(x_bound / dx), int(y_bound / dy)\ndx2, dy2 = dx * dx, dy * dy\ndt = dx2 / k / 4.0\nt_end = 80 * dt\nu0 = np.zeros((nx, ny))\nu_exact = np.zeros((nx, ny))\nu = np.zeros((nx, ny))\n\n\ndef get_exact(x, y, t, trunc):\n \"\"\"Get the exact solution at a set t\n \"\"\"\n Z = 0\n for n in range(1, trunc):\n for m in range(1, trunc):\n Z_num = -120 * ((-n) ** 4 * np.pi ** 4 * (-1) ** n + 12 * n ** \n 2 * np.pi ** 2 * (-1) ** n + 24 + 24 * (-1) ** (1 + n) * (-\n 2 + 2 * (-1) ** m))\n Z_num_xy = np.sin(n * x * np.pi) * np.sin(m * y * np.pi) * np.exp(\n -(n ** 2 + m ** 2) * np.pi ** 2 * k * t)\n Z_denom = n ** 7 * np.pi ** 10 * m ** 3\n Z += Z_num * Z_num_xy / Z_denom\n return Z\n\n\ndef get_L_norm(exact, u):\n diffs = abs(exact - u)\n l_diffs = []\n for row in diffs:\n l_diffs.append(max(row))\n return max(l_diffs), diffs\n\n\nfor i in range(nx):\n for j in range(ny):\n x = i * dx\n y = j * dy\n u0[i, j] = x * (1 - x ** 5) * y * (1 - y)\n u_exact[i, j] = get_exact(x, y, t_end, 10)\n\n\ndef do_timestep(u0, u):\n u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * ((u0[2:, 1:-1] - 2 * u0[1:-1,\n 1:-1] + u0[:-2, 1:-1]) / dx2 + (u0[1:-1, 2:] - 2 * u0[1:-1, 1:-1] +\n u0[1:-1, :-2]) / dy2)\n u0 = u.copy()\n return u0, u\n\n\nu0, u = do_timestep(u0, u)\nl_inf_norm, norm_diff_vals = get_L_norm(u_exact, u0)\nfig = plt.figure(1)\nax = fig.add_subplot(111)\nim = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=0, vmax=0.06)\ncbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])\nax.set_title('2D distribution after 80 time steps using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_plot.png')\nfig = plt.figure(2)\nax = fig.add_subplot(111)\nax.set_title('|f_exact - f_ftcs| Using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nim = ax.imshow(norm_diff_vals.copy(), cmap=plt.get_cmap('hot'), vmin=0,\n vmax=l_inf_norm)\ncbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_error.png')\nprint('The L_infinity error for FTCS is: ' + str(l_inf_norm))\n",
"step-5": "import numpy as np\nimport matplotlib.pyplot as plt\n\n# some important constants \nx_bound = y_bound = 1.\ndx = dy = 0.05\nk = 0.1\nnx, ny = int(x_bound/dx), int(y_bound/dy)\ndx2, dy2 = dx*dx, dy*dy\ndt = (dx2 / k) / 4.0\nt_end = 80 * dt\n\n# set the grid\nu0 = np.zeros((nx, ny))\nu_exact = np.zeros((nx, ny))\nu = np.zeros((nx, ny))\n\ndef get_exact(x, y, t, trunc):\n \"\"\"Get the exact solution at a set t\n \"\"\"\n Z=0\n for n in range(1, trunc):\n for m in range(1, trunc):\n Z_num = -120 * ( ((-n)**4 * np.pi**4 * (-1)**n) +\\\n (12 * n**2 * np.pi ** 2 * (-1)**n)\\\n + 24 + (24 * (-1)**(1+n))\\\n *(-2 + (2*(-1)**m) ) )\n Z_num_xy = np.sin(n*x*np.pi)*np.sin(m*y*np.pi)\\\n * np.exp(-(n**2 + m**2) * np.pi**2 * k * t)\n Z_denom = n**7 * np.pi**10 * m**3\n\n Z += Z_num * Z_num_xy / Z_denom\n \n return Z\n\ndef get_L_norm(exact, u):\n \n diffs = abs(exact - u)\n l_diffs = []\n for row in diffs:\n l_diffs.append(max(row))\n return max(l_diffs), diffs\n\n# Initial conditions\n\nfor i in range(nx):\n for j in range(ny):\n x = i*dx\n y = j*dy\n u0[i,j] = x * (1-x**5) * y * (1-y)\n u_exact[i,j] = get_exact(x, y, t_end, 10)\n\n\ndef do_timestep(u0, u):\n # Propagate with forward-difference in time, central-difference in space\n u[1:-1, 1:-1] = u0[1:-1, 1:-1] + k * dt * (\n (u0[2:, 1:-1] - 2*u0[1:-1, 1:-1] + u0[:-2, 1:-1])/dx2\n + (u0[1:-1, 2:] - 2*u0[1:-1, 1:-1] + u0[1:-1, :-2])/dy2 )\n\n u0 = u.copy()\n return u0, u\n\nu0, u = do_timestep(u0, u)\nl_inf_norm, norm_diff_vals = get_L_norm(u_exact, u0)\n\nfig = plt.figure(1)\nax = fig.add_subplot(111)\nim = ax.imshow(u.copy(), cmap=plt.get_cmap('hot'), vmin=0, vmax=0.06)\ncbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])\nax.set_title('2D distribution after 80 time steps using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_plot.png')\n\nfig = plt.figure(2)\nax = fig.add_subplot(111)\nax.set_title('|f_exact - f_ftcs| Using FTCS')\nplt.xlabel('x node [-]')\nplt.ylabel('y node [-]')\nim = ax.imshow(norm_diff_vals.copy(), cmap=plt.get_cmap('hot'), vmin=0,\\\n vmax=l_inf_norm)\ncbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])\nfig.colorbar(im, cax=cbar_ax)\nplt.savefig('./writeup/problem2_error.png')\n\nprint(\"The L_infinity error for FTCS is: \" + str(l_inf_norm))\n",
"step-ids": [
2,
4,
5,
6,
7
]
}
|
[
2,
4,
5,
6,
7
] |
from arma_scipy.fit import fit, predict
|
normal
|
{
"blob_id": "0f6512bb734336a67eab2f13949dd960f5ffc1d5",
"index": 7758,
"step-1": "<mask token>\n",
"step-2": "from arma_scipy.fit import fit, predict\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
from dbmanager import DbManager
from message import Message
def list_returner(f):
def wrapper(*args, **kwargs):
result = f(*args, **kwargs)
if result:
return result
else:
return [dict()]
return wrapper
class Messenger:
def __init__(self, messages_count=20):
self.messages_count = messages_count
self.message_manager = DbManager()
def add_message(self, message):
self.message_manager.add(message)
@list_returner
def get_room_messages(self):
messages = []
i = 6
found_messages = []
for message in self.message_manager.find({}, self.messages_count):
found_messages.append(Message(**message))
for message in sorted(found_messages):
message_dict = message.as_dict()
message_dict['id'] = i
messages.append(message_dict)
i += 1
return messages
def read_messages(self):
output = list()
messages = self.get_room_messages()
output.append('[' + ', '.join([str(message).replace("'", '"') for
message in messages]) + ']')
return output
def delete_message(self, message):
try:
self.message_manager.delete(message)
except:
print('No message')
def update_message(self, old_message, message):
self.message_manager.update(old_message, message)
|
normal
|
{
"blob_id": "4d1ea6522a01603f0159a1f27da70b65c4f387cb",
"index": 7093,
"step-1": "<mask token>\n\n\nclass Messenger:\n <mask token>\n\n def add_message(self, message):\n self.message_manager.add(message)\n\n @list_returner\n def get_room_messages(self):\n messages = []\n i = 6\n found_messages = []\n for message in self.message_manager.find({}, self.messages_count):\n found_messages.append(Message(**message))\n for message in sorted(found_messages):\n message_dict = message.as_dict()\n message_dict['id'] = i\n messages.append(message_dict)\n i += 1\n return messages\n\n def read_messages(self):\n output = list()\n messages = self.get_room_messages()\n output.append('[' + ', '.join([str(message).replace(\"'\", '\"') for\n message in messages]) + ']')\n return output\n <mask token>\n\n def update_message(self, old_message, message):\n self.message_manager.update(old_message, message)\n",
"step-2": "<mask token>\n\n\nclass Messenger:\n\n def __init__(self, messages_count=20):\n self.messages_count = messages_count\n self.message_manager = DbManager()\n\n def add_message(self, message):\n self.message_manager.add(message)\n\n @list_returner\n def get_room_messages(self):\n messages = []\n i = 6\n found_messages = []\n for message in self.message_manager.find({}, self.messages_count):\n found_messages.append(Message(**message))\n for message in sorted(found_messages):\n message_dict = message.as_dict()\n message_dict['id'] = i\n messages.append(message_dict)\n i += 1\n return messages\n\n def read_messages(self):\n output = list()\n messages = self.get_room_messages()\n output.append('[' + ', '.join([str(message).replace(\"'\", '\"') for\n message in messages]) + ']')\n return output\n\n def delete_message(self, message):\n try:\n self.message_manager.delete(message)\n except:\n print('No message')\n\n def update_message(self, old_message, message):\n self.message_manager.update(old_message, message)\n",
"step-3": "<mask token>\n\n\ndef list_returner(f):\n\n def wrapper(*args, **kwargs):\n result = f(*args, **kwargs)\n if result:\n return result\n else:\n return [dict()]\n return wrapper\n\n\nclass Messenger:\n\n def __init__(self, messages_count=20):\n self.messages_count = messages_count\n self.message_manager = DbManager()\n\n def add_message(self, message):\n self.message_manager.add(message)\n\n @list_returner\n def get_room_messages(self):\n messages = []\n i = 6\n found_messages = []\n for message in self.message_manager.find({}, self.messages_count):\n found_messages.append(Message(**message))\n for message in sorted(found_messages):\n message_dict = message.as_dict()\n message_dict['id'] = i\n messages.append(message_dict)\n i += 1\n return messages\n\n def read_messages(self):\n output = list()\n messages = self.get_room_messages()\n output.append('[' + ', '.join([str(message).replace(\"'\", '\"') for\n message in messages]) + ']')\n return output\n\n def delete_message(self, message):\n try:\n self.message_manager.delete(message)\n except:\n print('No message')\n\n def update_message(self, old_message, message):\n self.message_manager.update(old_message, message)\n",
"step-4": "from dbmanager import DbManager\nfrom message import Message\n\n\ndef list_returner(f):\n\n def wrapper(*args, **kwargs):\n result = f(*args, **kwargs)\n if result:\n return result\n else:\n return [dict()]\n return wrapper\n\n\nclass Messenger:\n\n def __init__(self, messages_count=20):\n self.messages_count = messages_count\n self.message_manager = DbManager()\n\n def add_message(self, message):\n self.message_manager.add(message)\n\n @list_returner\n def get_room_messages(self):\n messages = []\n i = 6\n found_messages = []\n for message in self.message_manager.find({}, self.messages_count):\n found_messages.append(Message(**message))\n for message in sorted(found_messages):\n message_dict = message.as_dict()\n message_dict['id'] = i\n messages.append(message_dict)\n i += 1\n return messages\n\n def read_messages(self):\n output = list()\n messages = self.get_room_messages()\n output.append('[' + ', '.join([str(message).replace(\"'\", '\"') for\n message in messages]) + ']')\n return output\n\n def delete_message(self, message):\n try:\n self.message_manager.delete(message)\n except:\n print('No message')\n\n def update_message(self, old_message, message):\n self.message_manager.update(old_message, message)\n",
"step-5": null,
"step-ids": [
5,
7,
8,
9
]
}
|
[
5,
7,
8,
9
] |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 17 22:28:30 2019
@author: donsdev
"""
arr = []
sub = []
n = int(input())
while n > 0:
arr.append(n)
n-=1
while len(arr) + len(sub) > 1:
while len(arr) > 1:
arr.pop()
sub.append(arr.pop())
arr = sub[::-1] + arr
sub = []
print(arr[0])
|
normal
|
{
"blob_id": "d5d31920f7fd4ed2913c5880dba61c2015181be9",
"index": 5760,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nwhile n > 0:\n arr.append(n)\n n -= 1\nwhile len(arr) + len(sub) > 1:\n while len(arr) > 1:\n arr.pop()\n sub.append(arr.pop())\n arr = sub[::-1] + arr\n sub = []\nprint(arr[0])\n",
"step-3": "<mask token>\narr = []\nsub = []\nn = int(input())\nwhile n > 0:\n arr.append(n)\n n -= 1\nwhile len(arr) + len(sub) > 1:\n while len(arr) > 1:\n arr.pop()\n sub.append(arr.pop())\n arr = sub[::-1] + arr\n sub = []\nprint(arr[0])\n",
"step-4": "#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jan 17 22:28:30 2019\n\n@author: donsdev\n\"\"\"\n\narr = []\nsub = []\nn = int(input())\nwhile n > 0:\n arr.append(n)\n n-=1\nwhile len(arr) + len(sub) > 1:\n while len(arr) > 1:\n arr.pop()\n sub.append(arr.pop())\n arr = sub[::-1] + arr\n sub = []\nprint(arr[0])",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
from network import WLAN
import machine
import pycom
import time
import request
def wifiConnect():
wlan = WLAN(mode=WLAN.STA)
pycom.heartbeat(False)
wlan.connect(ssid="telenet-4D87F74", auth=(WLAN.WPA2, "x2UcakjTsryz"))
while not wlan.isconnected():
time.sleep(1)
print("WiFi not connected")
pycom.rgbled(0xFF0000)
print("WiFi connected succesfully")
pycom.rgbled(0x00FF00)
print("test")
print(wlan.ifconfig())
print("hond")
while not wlan.isconnected():
print("WiFi not connected2.0")
pycom.rgbled(0xFF0000)
|
normal
|
{
"blob_id": "099396a75060ad0388f5a852c4c3cb148febd8a3",
"index": 4048,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef wifiConnect():\n wlan = WLAN(mode=WLAN.STA)\n pycom.heartbeat(False)\n wlan.connect(ssid='telenet-4D87F74', auth=(WLAN.WPA2, 'x2UcakjTsryz'))\n while not wlan.isconnected():\n time.sleep(1)\n print('WiFi not connected')\n pycom.rgbled(16711680)\n print('WiFi connected succesfully')\n pycom.rgbled(65280)\n print('test')\n print(wlan.ifconfig())\n print('hond')\n while not wlan.isconnected():\n print('WiFi not connected2.0')\n pycom.rgbled(16711680)\n",
"step-3": "from network import WLAN\nimport machine\nimport pycom\nimport time\nimport request\n\n\ndef wifiConnect():\n wlan = WLAN(mode=WLAN.STA)\n pycom.heartbeat(False)\n wlan.connect(ssid='telenet-4D87F74', auth=(WLAN.WPA2, 'x2UcakjTsryz'))\n while not wlan.isconnected():\n time.sleep(1)\n print('WiFi not connected')\n pycom.rgbled(16711680)\n print('WiFi connected succesfully')\n pycom.rgbled(65280)\n print('test')\n print(wlan.ifconfig())\n print('hond')\n while not wlan.isconnected():\n print('WiFi not connected2.0')\n pycom.rgbled(16711680)\n",
"step-4": "from network import WLAN\r\nimport machine\r\nimport pycom\r\nimport time\r\nimport request\r\n\r\ndef wifiConnect():\r\n wlan = WLAN(mode=WLAN.STA)\r\n pycom.heartbeat(False)\r\n\r\n wlan.connect(ssid=\"telenet-4D87F74\", auth=(WLAN.WPA2, \"x2UcakjTsryz\"))\r\n\r\n while not wlan.isconnected():\r\n time.sleep(1)\r\n print(\"WiFi not connected\")\r\n pycom.rgbled(0xFF0000)\r\n print(\"WiFi connected succesfully\")\r\n pycom.rgbled(0x00FF00)\r\n print(\"test\")\r\n print(wlan.ifconfig())\r\n print(\"hond\")\r\n while not wlan.isconnected():\r\n print(\"WiFi not connected2.0\")\r\n pycom.rgbled(0xFF0000)\r\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
def best_rank_selection(generation):
max_selected = len(generation) // 10
sorted_by_fitness = sorted(generation, key=lambda x: x.fitness, reverse
=True)
return sorted_by_fitness[:max_selected]
|
normal
|
{
"blob_id": "05a80a904548e90bea635469b94264f219062560",
"index": 7968,
"step-1": "<mask token>\n",
"step-2": "def best_rank_selection(generation):\n max_selected = len(generation) // 10\n sorted_by_fitness = sorted(generation, key=lambda x: x.fitness, reverse\n =True)\n return sorted_by_fitness[:max_selected]\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
import os
from sources.lol.status import LOLServerStatusCollector
from util.abstract.feed import Feed
from util.abstract.handler import Handler
from util.functions.load_json import load_json
class LoLServerStatusHandler(Handler):
def load_servers(self):
servers_filepath = os.path.join(os.path.dirname(__file__),
'../../data/lol/status.json')
return load_json(servers_filepath)
def get_filepath(self, server):
return '/lol/{region}/status.{locale}.xml'.format(region=server[
'region'], locale=server['locale'])
def process_server(self, server):
collector = LOLServerStatusCollector(server)
items = collector.collect()
alternateLink = collector.construct_alternate_link()
feed = Feed()
feed.setTitle(server['title'])
feed.setAlternateLink(alternateLink)
feed.setLanguage(server['locale'])
feed.setItems(items)
return feed
def handle(event={}, context={}):
"""Handler for AWS Lambda - LoL Server Status"""
LoLServerStatusHandler().run()
return 'ok'
|
normal
|
{
"blob_id": "493552469943e9f9f0e57bf92b874c8b67943de5",
"index": 6751,
"step-1": "<mask token>\n\n\nclass LoLServerStatusHandler(Handler):\n\n def load_servers(self):\n servers_filepath = os.path.join(os.path.dirname(__file__),\n '../../data/lol/status.json')\n return load_json(servers_filepath)\n\n def get_filepath(self, server):\n return '/lol/{region}/status.{locale}.xml'.format(region=server[\n 'region'], locale=server['locale'])\n <mask token>\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass LoLServerStatusHandler(Handler):\n\n def load_servers(self):\n servers_filepath = os.path.join(os.path.dirname(__file__),\n '../../data/lol/status.json')\n return load_json(servers_filepath)\n\n def get_filepath(self, server):\n return '/lol/{region}/status.{locale}.xml'.format(region=server[\n 'region'], locale=server['locale'])\n\n def process_server(self, server):\n collector = LOLServerStatusCollector(server)\n items = collector.collect()\n alternateLink = collector.construct_alternate_link()\n feed = Feed()\n feed.setTitle(server['title'])\n feed.setAlternateLink(alternateLink)\n feed.setLanguage(server['locale'])\n feed.setItems(items)\n return feed\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass LoLServerStatusHandler(Handler):\n\n def load_servers(self):\n servers_filepath = os.path.join(os.path.dirname(__file__),\n '../../data/lol/status.json')\n return load_json(servers_filepath)\n\n def get_filepath(self, server):\n return '/lol/{region}/status.{locale}.xml'.format(region=server[\n 'region'], locale=server['locale'])\n\n def process_server(self, server):\n collector = LOLServerStatusCollector(server)\n items = collector.collect()\n alternateLink = collector.construct_alternate_link()\n feed = Feed()\n feed.setTitle(server['title'])\n feed.setAlternateLink(alternateLink)\n feed.setLanguage(server['locale'])\n feed.setItems(items)\n return feed\n\n\ndef handle(event={}, context={}):\n \"\"\"Handler for AWS Lambda - LoL Server Status\"\"\"\n LoLServerStatusHandler().run()\n return 'ok'\n",
"step-4": "import os\nfrom sources.lol.status import LOLServerStatusCollector\nfrom util.abstract.feed import Feed\nfrom util.abstract.handler import Handler\nfrom util.functions.load_json import load_json\n\n\nclass LoLServerStatusHandler(Handler):\n\n def load_servers(self):\n servers_filepath = os.path.join(os.path.dirname(__file__),\n '../../data/lol/status.json')\n return load_json(servers_filepath)\n\n def get_filepath(self, server):\n return '/lol/{region}/status.{locale}.xml'.format(region=server[\n 'region'], locale=server['locale'])\n\n def process_server(self, server):\n collector = LOLServerStatusCollector(server)\n items = collector.collect()\n alternateLink = collector.construct_alternate_link()\n feed = Feed()\n feed.setTitle(server['title'])\n feed.setAlternateLink(alternateLink)\n feed.setLanguage(server['locale'])\n feed.setItems(items)\n return feed\n\n\ndef handle(event={}, context={}):\n \"\"\"Handler for AWS Lambda - LoL Server Status\"\"\"\n LoLServerStatusHandler().run()\n return 'ok'\n",
"step-5": null,
"step-ids": [
3,
4,
5,
6
]
}
|
[
3,
4,
5,
6
] |
from django.db import models
from django.utils import timezone
from django.utils.text import slugify
from django.db.models.signals import pre_save
from NetFlix.db.models import PublishStateOptions
from NetFlix.db.receivers import publicado_stado_pre_save, slugify_pre_save
class VideoQuerySet(models.QuerySet):
def publicado(self):
ahora = timezone.now()
return self.filter(
stado = PublishStateOptions.PUBLISH,
tiempo_publicado__lte=ahora
)
class VideoManager(models.Manager):
def get_queryset(self):
return VideoQuerySet(self.model, using=self._db)
def publicado(self):
return self.get_queryset().publicado()
class Video(models.Model):
titulo = models.CharField(max_length=120)
descripcion = models.TextField(blank=True, null=True)
slug = models.SlugField(blank=True, null=True)
activo = models.BooleanField(default=True)
video_id = models.CharField(max_length=120, unique=True)
timestamp = models.DateTimeField(auto_now_add=True)
update = models.DateTimeField(auto_now=True)
stado = models.CharField(max_length=2, choices=PublishStateOptions.choices, default=PublishStateOptions.DRAFT)
tiempo_publicado = models.DateTimeField(auto_now_add=False, auto_now=False, blank=True, null=True)
objects = VideoManager()
def __str__(self):
return self.titulo
def get_video_id(self):
if not self.es_publicado:
return None
return self.video_id
def get_descripcion_trailer(self):
return self.descripcion
@property
def es_publicado(self):
if self.activo is False:
return False
estado = self.stado
if estado != PublishStateOptions.PUBLISH:
return False
tiempo_publicado = self.tiempo_publicado
if tiempo_publicado is None:
return False
ahora = timezone.now()
return tiempo_publicado <= ahora
def get_playlista_ids(self):
#self.<foreingkey_obj>_set.all()
#return list(self.playlist_set.all().values_list('id', flat=True))playlist_destacado
return list(self.playlist_destacado.all().values_list('id', flat=True))
#def save(self, *args, **kwargs):
# if self.stado == self.PublishStateOptions.PUBLISH and self.tiempo_publicado is None:
# print("Guardado el tiempo de publicado")
# self.tiempo_publicado = timezone.now()
# elif self.stado == self.PublishStateOptions.DRAFT:
# self.tiempo_publicado = None
# if self.slug is None:
# self.slug = slugify(self.titulo)
# super().save(*args, **kwargs)
class ProxiTodoLosVideo(Video):
class Meta:
proxy = True
verbose_name = "Todo los Video"
verbose_name_plural="Todos los Publicados"
class VideoPublicadoProxy(Video):
class Meta:
proxy =True
verbose_name ='Video Publicado'
verbose_name_plural = 'Videos Publicados'
pre_save.connect(publicado_stado_pre_save, sender=Video)
pre_save.connect(slugify_pre_save, sender=Video)
pre_save.connect(publicado_stado_pre_save, sender=ProxiTodoLosVideo)
pre_save.connect(slugify_pre_save, sender=ProxiTodoLosVideo)
pre_save.connect(publicado_stado_pre_save, sender=VideoPublicadoProxy)
pre_save.connect(slugify_pre_save, sender=VideoPublicadoProxy)
|
normal
|
{
"blob_id": "9c98ecde2e8aac00a33da7db6e5e6023519e4b84",
"index": 7731,
"step-1": "<mask token>\n\n\nclass Video(models.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n def __str__(self):\n return self.titulo\n\n def get_video_id(self):\n if not self.es_publicado:\n return None\n return self.video_id\n\n def get_descripcion_trailer(self):\n return self.descripcion\n\n @property\n def es_publicado(self):\n if self.activo is False:\n return False\n estado = self.stado\n if estado != PublishStateOptions.PUBLISH:\n return False\n tiempo_publicado = self.tiempo_publicado\n if tiempo_publicado is None:\n return False\n ahora = timezone.now()\n return tiempo_publicado <= ahora\n\n def get_playlista_ids(self):\n return list(self.playlist_destacado.all().values_list('id', flat=True))\n\n\nclass ProxiTodoLosVideo(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Todo los Video'\n verbose_name_plural = 'Todos los Publicados'\n\n\nclass VideoPublicadoProxy(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Video Publicado'\n verbose_name_plural = 'Videos Publicados'\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\nclass VideoQuerySet(models.QuerySet):\n\n def publicado(self):\n ahora = timezone.now()\n return self.filter(stado=PublishStateOptions.PUBLISH,\n tiempo_publicado__lte=ahora)\n\n\nclass VideoManager(models.Manager):\n\n def get_queryset(self):\n return VideoQuerySet(self.model, using=self._db)\n\n def publicado(self):\n return self.get_queryset().publicado()\n\n\nclass Video(models.Model):\n titulo = models.CharField(max_length=120)\n descripcion = models.TextField(blank=True, null=True)\n slug = models.SlugField(blank=True, null=True)\n activo = models.BooleanField(default=True)\n video_id = models.CharField(max_length=120, unique=True)\n timestamp = models.DateTimeField(auto_now_add=True)\n update = models.DateTimeField(auto_now=True)\n stado = models.CharField(max_length=2, choices=PublishStateOptions.\n choices, default=PublishStateOptions.DRAFT)\n tiempo_publicado = models.DateTimeField(auto_now_add=False, auto_now=\n False, blank=True, null=True)\n objects = VideoManager()\n\n def __str__(self):\n return self.titulo\n\n def get_video_id(self):\n if not self.es_publicado:\n return None\n return self.video_id\n\n def get_descripcion_trailer(self):\n return self.descripcion\n\n @property\n def es_publicado(self):\n if self.activo is False:\n return False\n estado = self.stado\n if estado != PublishStateOptions.PUBLISH:\n return False\n tiempo_publicado = self.tiempo_publicado\n if tiempo_publicado is None:\n return False\n ahora = timezone.now()\n return tiempo_publicado <= ahora\n\n def get_playlista_ids(self):\n return list(self.playlist_destacado.all().values_list('id', flat=True))\n\n\nclass ProxiTodoLosVideo(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Todo los Video'\n verbose_name_plural = 'Todos los Publicados'\n\n\nclass VideoPublicadoProxy(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Video Publicado'\n verbose_name_plural = 'Videos Publicados'\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\nclass VideoQuerySet(models.QuerySet):\n\n def publicado(self):\n ahora = timezone.now()\n return self.filter(stado=PublishStateOptions.PUBLISH,\n tiempo_publicado__lte=ahora)\n\n\nclass VideoManager(models.Manager):\n\n def get_queryset(self):\n return VideoQuerySet(self.model, using=self._db)\n\n def publicado(self):\n return self.get_queryset().publicado()\n\n\nclass Video(models.Model):\n titulo = models.CharField(max_length=120)\n descripcion = models.TextField(blank=True, null=True)\n slug = models.SlugField(blank=True, null=True)\n activo = models.BooleanField(default=True)\n video_id = models.CharField(max_length=120, unique=True)\n timestamp = models.DateTimeField(auto_now_add=True)\n update = models.DateTimeField(auto_now=True)\n stado = models.CharField(max_length=2, choices=PublishStateOptions.\n choices, default=PublishStateOptions.DRAFT)\n tiempo_publicado = models.DateTimeField(auto_now_add=False, auto_now=\n False, blank=True, null=True)\n objects = VideoManager()\n\n def __str__(self):\n return self.titulo\n\n def get_video_id(self):\n if not self.es_publicado:\n return None\n return self.video_id\n\n def get_descripcion_trailer(self):\n return self.descripcion\n\n @property\n def es_publicado(self):\n if self.activo is False:\n return False\n estado = self.stado\n if estado != PublishStateOptions.PUBLISH:\n return False\n tiempo_publicado = self.tiempo_publicado\n if tiempo_publicado is None:\n return False\n ahora = timezone.now()\n return tiempo_publicado <= ahora\n\n def get_playlista_ids(self):\n return list(self.playlist_destacado.all().values_list('id', flat=True))\n\n\nclass ProxiTodoLosVideo(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Todo los Video'\n verbose_name_plural = 'Todos los Publicados'\n\n\nclass VideoPublicadoProxy(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Video Publicado'\n verbose_name_plural = 'Videos Publicados'\n\n\npre_save.connect(publicado_stado_pre_save, sender=Video)\npre_save.connect(slugify_pre_save, sender=Video)\npre_save.connect(publicado_stado_pre_save, sender=ProxiTodoLosVideo)\npre_save.connect(slugify_pre_save, sender=ProxiTodoLosVideo)\npre_save.connect(publicado_stado_pre_save, sender=VideoPublicadoProxy)\npre_save.connect(slugify_pre_save, sender=VideoPublicadoProxy)\n",
"step-4": "from django.db import models\nfrom django.utils import timezone\nfrom django.utils.text import slugify\nfrom django.db.models.signals import pre_save\nfrom NetFlix.db.models import PublishStateOptions\nfrom NetFlix.db.receivers import publicado_stado_pre_save, slugify_pre_save\n\n\nclass VideoQuerySet(models.QuerySet):\n\n def publicado(self):\n ahora = timezone.now()\n return self.filter(stado=PublishStateOptions.PUBLISH,\n tiempo_publicado__lte=ahora)\n\n\nclass VideoManager(models.Manager):\n\n def get_queryset(self):\n return VideoQuerySet(self.model, using=self._db)\n\n def publicado(self):\n return self.get_queryset().publicado()\n\n\nclass Video(models.Model):\n titulo = models.CharField(max_length=120)\n descripcion = models.TextField(blank=True, null=True)\n slug = models.SlugField(blank=True, null=True)\n activo = models.BooleanField(default=True)\n video_id = models.CharField(max_length=120, unique=True)\n timestamp = models.DateTimeField(auto_now_add=True)\n update = models.DateTimeField(auto_now=True)\n stado = models.CharField(max_length=2, choices=PublishStateOptions.\n choices, default=PublishStateOptions.DRAFT)\n tiempo_publicado = models.DateTimeField(auto_now_add=False, auto_now=\n False, blank=True, null=True)\n objects = VideoManager()\n\n def __str__(self):\n return self.titulo\n\n def get_video_id(self):\n if not self.es_publicado:\n return None\n return self.video_id\n\n def get_descripcion_trailer(self):\n return self.descripcion\n\n @property\n def es_publicado(self):\n if self.activo is False:\n return False\n estado = self.stado\n if estado != PublishStateOptions.PUBLISH:\n return False\n tiempo_publicado = self.tiempo_publicado\n if tiempo_publicado is None:\n return False\n ahora = timezone.now()\n return tiempo_publicado <= ahora\n\n def get_playlista_ids(self):\n return list(self.playlist_destacado.all().values_list('id', flat=True))\n\n\nclass ProxiTodoLosVideo(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Todo los Video'\n verbose_name_plural = 'Todos los Publicados'\n\n\nclass VideoPublicadoProxy(Video):\n\n\n class Meta:\n proxy = True\n verbose_name = 'Video Publicado'\n verbose_name_plural = 'Videos Publicados'\n\n\npre_save.connect(publicado_stado_pre_save, sender=Video)\npre_save.connect(slugify_pre_save, sender=Video)\npre_save.connect(publicado_stado_pre_save, sender=ProxiTodoLosVideo)\npre_save.connect(slugify_pre_save, sender=ProxiTodoLosVideo)\npre_save.connect(publicado_stado_pre_save, sender=VideoPublicadoProxy)\npre_save.connect(slugify_pre_save, sender=VideoPublicadoProxy)\n",
"step-5": "from django.db import models\n\nfrom django.utils import timezone\nfrom django.utils.text import slugify\n\nfrom django.db.models.signals import pre_save\n\nfrom NetFlix.db.models import PublishStateOptions\nfrom NetFlix.db.receivers import publicado_stado_pre_save, slugify_pre_save\n\n\nclass VideoQuerySet(models.QuerySet):\n\tdef publicado(self):\n\t\tahora = timezone.now()\n\t\treturn self.filter(\n\t\t\tstado = PublishStateOptions.PUBLISH,\n\t\t\ttiempo_publicado__lte=ahora\n\t\t)\n\n\nclass VideoManager(models.Manager):\n\tdef get_queryset(self):\n\t\treturn VideoQuerySet(self.model, using=self._db)\n\n\tdef publicado(self):\n\t\treturn self.get_queryset().publicado()\n\n\nclass Video(models.Model):\n\n\ttitulo = models.CharField(max_length=120)\n\tdescripcion = models.TextField(blank=True, null=True)\n\tslug = models.SlugField(blank=True, null=True)\n\tactivo = models.BooleanField(default=True)\n\tvideo_id = models.CharField(max_length=120, unique=True)\n\n\ttimestamp = models.DateTimeField(auto_now_add=True)\n\tupdate = models.DateTimeField(auto_now=True)\n\n\tstado = models.CharField(max_length=2, choices=PublishStateOptions.choices, default=PublishStateOptions.DRAFT)\n\n\ttiempo_publicado = models.DateTimeField(auto_now_add=False, auto_now=False, blank=True, null=True)\n\n\tobjects = VideoManager()\n\n\tdef __str__(self):\n\t\treturn self.titulo\n\n\tdef get_video_id(self):\n\t\tif not self.es_publicado:\n\t\t\treturn None\n\t\treturn self.video_id\n\n\tdef get_descripcion_trailer(self):\n\t\treturn self.descripcion\n\n\t@property\n\tdef es_publicado(self):\n\t\tif self.activo is False:\n\t\t\treturn False\n\t\testado = self.stado\n\t\tif estado != PublishStateOptions.PUBLISH:\n\t\t\treturn False\n\t\ttiempo_publicado = self.tiempo_publicado\n\t\tif tiempo_publicado is None:\n\t\t\treturn False\n\t\tahora = timezone.now()\n\t\treturn tiempo_publicado <= ahora\n\n\tdef get_playlista_ids(self):\n\t\t#self.<foreingkey_obj>_set.all()\n\t\t#return list(self.playlist_set.all().values_list('id', flat=True))playlist_destacado\n\t\treturn list(self.playlist_destacado.all().values_list('id', flat=True))\n\n\t#def save(self, *args, **kwargs):\n\t#\tif self.stado == self.PublishStateOptions.PUBLISH and self.tiempo_publicado is None:\n\t#\t\tprint(\"Guardado el tiempo de publicado\")\n\t#\t\tself.tiempo_publicado = timezone.now()\n\n\t#\telif self.stado == self.PublishStateOptions.DRAFT:\n\t#\t\tself.tiempo_publicado = None\n\t#\tif self.slug is None:\n\t#\t\tself.slug = slugify(self.titulo)\n\t#\tsuper().save(*args, **kwargs)\n\nclass ProxiTodoLosVideo(Video):\n\tclass Meta:\n\t\tproxy = True\n\t\tverbose_name = \"Todo los Video\"\n\t\tverbose_name_plural=\"Todos los Publicados\"\n\nclass VideoPublicadoProxy(Video):\n\tclass Meta:\n\t\tproxy =True\n\t\tverbose_name ='Video Publicado'\n\t\tverbose_name_plural = 'Videos Publicados'\n\npre_save.connect(publicado_stado_pre_save, sender=Video)\npre_save.connect(slugify_pre_save, sender=Video)\n\npre_save.connect(publicado_stado_pre_save, sender=ProxiTodoLosVideo)\npre_save.connect(slugify_pre_save, sender=ProxiTodoLosVideo)\n\npre_save.connect(publicado_stado_pre_save, sender=VideoPublicadoProxy)\npre_save.connect(slugify_pre_save, sender=VideoPublicadoProxy)\n\n",
"step-ids": [
8,
14,
15,
16,
17
]
}
|
[
8,
14,
15,
16,
17
] |
import sys
from google.appengine.ext import blobstore
from google.appengine.ext.webapp import blobstore_handlers
from google.appengine.ext import ndb
from helpers import *
def valid_pw(name, password, h):
salt = h.split(',')[0]
return h == make_pw_hash(name, password, salt)
class CVEProfile(ndb.Model):
profile_name = ndb.StringProperty(default="N/A")
cve_id = ndb.StringProperty(required=True)
cwe_id = ndb.StringProperty(required=True)
cwe_name = ndb.StringProperty(required=True)
summary = ndb.TextProperty()
cvss_score = ndb.FloatProperty()
exploit_count = ndb.IntegerProperty()
publish_date = ndb.StringProperty()
update_date = ndb.StringProperty()
cve_url = ndb.StringProperty()
created = ndb.DateTimeProperty(auto_now_add=True)
access_params = ndb.StringProperty()
confidentiality_impact = ndb.IntegerProperty()
integrity_impact = ndb.IntegerProperty()
availability_impact = ndb.IntegerProperty()
access_complexity = ndb.IntegerProperty()
gained_access = ndb.IntegerProperty()
authentication = ndb.IntegerProperty()
@classmethod
def createProfile(cls, cve_id , cwe_id , cwe_name, summary, cvss_score, exploit_count, publish_date, update_date, cve_url, confidentiality_impact, integrity_impact, availability_impact, access_complexity, gained_access, authentication):
access_params = create_params()
return CVEProfile( cve_id = cve_id,
cwe_id = cwe_id,
cwe_name = cwe_name,
summary = summary,
cvss_score = cvss_score,
exploit_count = exploit_count,
publish_date = publish_date,
update_date = update_date,
cve_url = cve_url,
confidentiality_impact = confidentiality_impact,
integrity_impact = integrity_impact,
availability_impact = availability_impact,
access_complexity = access_complexity,
gained_access = gained_access,
authentication = authentication,
access_params = access_params )
class Service(ndb.Model):
serviceID=ndb.IntegerProperty(required=True)
name=ndb.StringProperty()
status=ndb.StringProperty()
impact=ndb.IntegerProperty()
machineID=ndb.IntegerProperty()
@classmethod
def add_new_service(cls,serviceID,name,status,impact,machineID):
return Service( serviceID = serviceID,
name = name,
status = status,
impact = impact,
machineID = machineID)
class Machine(ndb.Model):
machineID=ndb.IntegerProperty(required=True)
name=ndb.StringProperty()
status=ndb.StringProperty()
impact=ndb.IntegerProperty()
@classmethod
def add_new_machine(cls,machineID,name,status,impact):
return Machine( machineID = machineID,
name = name,
status = status,
impact = impact)
class Path(ndb.Model):
pathID=ndb.IntegerProperty(required=True)
name=ndb.StringProperty()
status=ndb.StringProperty()
src=ndb.IntegerProperty()
dest=ndb.IntegerProperty()
#cvss=ndb.StringProperty()
cve_id = ndb.StringProperty()
confidentiality_impact = ndb.IntegerProperty()
integrity_impact = ndb.IntegerProperty()
availability_impact = ndb.IntegerProperty()
access_complexity = ndb.IntegerProperty()
gained_access = ndb.IntegerProperty()
authentication = ndb.IntegerProperty()
@classmethod
def add_new_path(cls,pathID,name,status,src,dest,cve_id,c_imp,i_imp,a_imp,acc_com,g_acc,auth):
return Path( pathID = pathID,
name = name,
status = status,
src = src,
dest = dest,
cve_id = cve_id,
confidentiality_impact = c_imp,
integrity_impact = i_imp,
availability_impact = a_imp,
access_complexity = acc_com,
gained_access = g_acc,
authentication = auth )
class Graph(ndb.Model):
name=ndb.StringProperty(required=True)
graphID=ndb.IntegerProperty(required=True)
#owner=ndb.KeyProperty(kind='User') #GUI push
owner_id=ndb.IntegerProperty(required=True) #JSON push
machines=ndb.StructuredProperty(Machine, repeated=True)
services=ndb.StructuredProperty(Service, repeated=True)
paths=ndb.StructuredProperty(Path, repeated=True)
# keep track for reporting
machine_hold = ndb.IntegerProperty(default=0)
service_hold = ndb.IntegerProperty(default=0)
path_hold = ndb.IntegerProperty(default=0)
class CharacterImage(ndb.Model):
blob = ndb.BlobKeyProperty()
owner = ndb.StringProperty()
access_params = ndb.StringProperty()
class FacebookUser(ndb.Model):
displayname = ndb.StringProperty(required=True)
user_id = ndb.StringProperty()
profile_url = ndb.StringProperty(required=True)
access_token = ndb.StringProperty(required=True)
access_params = ndb.StringProperty()
email = ndb.StringProperty()
joined_date = ndb.DateTimeProperty(auto_now_add=True)
last_visited = ndb.DateTimeProperty(auto_now=True)
avatar = ndb.StringProperty()
class User(ndb.Model):
user_id=ndb.IntegerProperty(required=True)
email = ndb.StringProperty()
#displayname = ndb.StringProperty()
username = ndb.StringProperty(required=True)
org = ndb.StringProperty()
access_params = ndb.StringProperty()
pw_hash = ndb.StringProperty()
last_visited = ndb.DateTimeProperty(auto_now=True)
joined_date = ndb.DateTimeProperty(auto_now_add=True)
APIkey = ndb.StringProperty()
graph_created = ndb.IntegerProperty(default=0)
@classmethod
def by_id(cls, uid):
return User.get_by_id(uid)
@classmethod
def by_username(cls, username):
u = User.query(User.username == username).get()
return u
@classmethod
def by_login(cls, user_id):
u = User.query(User.user_id == user_id).get()
return u
@classmethod
def by_email(cls, email):
u = User.query(User.email == email).get()
return u
@classmethod
def register(cls, username,email, password, org, user_id):
pw_hash = make_pw_hash(username, password)
access_params = create_params()
api_key = generate_key()
return User( user_id = user_id,
username = username,
email = email,
pw_hash = pw_hash,
org = org,
access_params = access_params,
APIkey = api_key )
@classmethod
def add_test_user(cls, user_id , username ):
return User( user_id = user_id,
username = username )
@classmethod
def login(cls, username, password):
u = cls.by_username(username)
if u and valid_pw(username, password, u.pw_hash):
return u
@classmethod
def bypass_login(cls, user_id):
u = cls.by_user_id(user_id)
if u:
return u
#check unauthorized post
class APIDatabase(ndb.Model):
api_id = ndb.IntegerProperty(required=True)
api_key = ndb.StringProperty(required=True)
@classmethod
def add_new_key(cls,api_id,api_key):
return APIDatabase(api_id = api_id, api_key = api_key)
class Step(ndb.Model):
startTurn = ndb.IntegerProperty()
endTurn = ndb.IntegerProperty()
solType = ndb.StringProperty()
cost = ndb.IntegerProperty()
fromCity = ndb.IntegerProperty()
toCity = ndb.IntegerProperty()
pathID = ndb.IntegerProperty()
score = ndb.IntegerProperty()
ai = ndb.IntegerProperty()
ci = ndb.IntegerProperty()
ii = ndb.IntegerProperty()
class WayPoints(ndb.Model):
waypointsID = ndb.IntegerProperty()
#just a graph
status = ndb.StringProperty()
mapID = ndb.IntegerProperty()
playerID = ndb.StringProperty()
score = ndb.IntegerProperty()
step = ndb.StructuredProperty(Step, repeated=True)
savedTurn = ndb.IntegerProperty()
graphStat = ndb.TextProperty()
class WaypointReport(ndb.Model):
waypointID = ndb.IntegerProperty(required=True)
play_by = ndb.StringProperty(required=True)
score = ndb.IntegerProperty(required=True)
total_turn = ndb.IntegerProperty(required=True)
total_impact = ndb.IntegerProperty(required=True)
# query without exhausted joining
graph_id = ndb.IntegerProperty(required=True)
owner_id = ndb.IntegerProperty(required=True)
play_count = ndb.IntegerProperty(default=0)
maximum_impact = ndb.FloatProperty(required=True)
#newly add
#status = ndb.StringProperty(required=True)
@classmethod
def add_new_waypoint_report(cls,waypointID,play_by,score,total_turn,total_impact,owner_id,graph_id,maximum_impact,status):
return WaypointReport( waypointID = waypointID,
play_by = play_by,
score = score,
total_turn = total_turn,
total_impact = total_impact,
graph_id = graph_id,
owner_id = owner_id,
play_count = 1,
maximum_impact = maximum_impact )
class MapReport(ndb.Model):
mapID = ndb.IntegerProperty(required=True)
# map name doesn't exist?
#map_name = ndb.IntegerProperty(required=True)
play_count = ndb.IntegerProperty()
score = ndb.IntegerProperty()
avg_score = ndb.FloatProperty()
total_turn = ndb.IntegerProperty()
avg_total_turn = ndb.FloatProperty()
total_impact = ndb.IntegerProperty()
top_score = ndb.IntegerProperty(default=0)
avg_total_impact = ndb.FloatProperty()
maximum_impact = ndb.FloatProperty()
# query without exhausted joining
graph_id = ndb.IntegerProperty(required=True)
owner_id = ndb.IntegerProperty(required=True)
@classmethod
def add_new_map_report(cls,mapID,play_count,score,avg_score,total_turn,avg_total_turn,total_impact,avg_total_impact,owner_id,graph_id,maximum_impact):
return MapReport( mapID = mapID,
play_count = play_count,
score = score,
avg_score = avg_score,
total_turn = total_turn,
avg_total_turn = avg_total_turn,
total_impact = total_impact,
avg_total_impact = avg_total_impact,
graph_id = graph_id,
owner_id = owner_id,
maximum_impact = maximum_impact)
class PathReport(ndb.Model):
mapID = ndb.IntegerProperty(required=True)
graph_id = ndb.IntegerProperty(required=True)
owner_id = ndb.IntegerProperty(required=True)
pathID = ndb.IntegerProperty(required=True)
srcMachine = ndb.StringProperty()
dstMachine = ndb.StringProperty()
srcService = ndb.StringProperty()
dstService = ndb.StringProperty()
### what for ???
ai = ndb.IntegerProperty(required=True)
ii = ndb.IntegerProperty(required=True)
ci = ndb.IntegerProperty(required=True)
### newly added
av = ndb.IntegerProperty(required=True)
ac = ndb.IntegerProperty(required=True)
au = ndb.IntegerProperty(required=True)
counting = ndb.IntegerProperty(default=0)
name = ndb.StringProperty()
@classmethod
def add_new_path_report(cls,mapID,graph_id,owner_id,pathID,srcM,dstM,srcS,dstS,ai,ii,ci,av,ac,au,counting):
return PathReport(
mapID=mapID,
graph_id=graph_id,
owner_id=owner_id,
pathID=pathID,
srcMachine=srcM,
dstMachine=dstM,
srcService=srcS,
dstService=dstS,
ai=ai,ii=ii,ci=ci,
av=av,au=au,ac=ac,
counting=counting
)
class Solution(ndb.Model):
cve_id = ndb.StringProperty(required=True)
cwe_name = ndb.StringProperty(required=True)
from_map = ndb.IntegerProperty(required=True)
counting = ndb.IntegerProperty(default=0)
@classmethod
def add_new_solution(cls,solution_id,cve_id,cwe_name,from_map):
return Solution( solution_id=solution_id,cve_id=cve_id,cwe_name=cwe_name,from_map=from_map,counting=1)
class SolTypeReport(ndb.Model):
owner_id = ndb.IntegerProperty(required=True)
mapID = ndb.IntegerProperty(required=True)
cve_id = ndb.StringProperty(required=True)
service_name = ndb.StringProperty()
solType_impact = ndb.IntegerProperty()
cwe_name = ndb.StringProperty(required=True)
counting = ndb.IntegerProperty(default=0)
avg_hit = ndb.FloatProperty(default=1)
@classmethod
def add_new_soltype(cls,owner_id,mapID,cve_id,cwe_name,service_name,solType_impact):
return SolTypeReport( owner_id = owner_id,
mapID = mapID,
cve_id = cve_id,
cwe_name = cwe_name,
counting = 1,
service_name = service_name,
solType_impact = solType_impact)
|
normal
|
{
"blob_id": "ac60fd79d7fb15624cf79adc7e456960e7523e2e",
"index": 9131,
"step-1": "<mask token>\n\n\nclass Graph(ndb.Model):\n name = ndb.StringProperty(required=True)\n graphID = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n machines = ndb.StructuredProperty(Machine, repeated=True)\n services = ndb.StructuredProperty(Service, repeated=True)\n paths = ndb.StructuredProperty(Path, repeated=True)\n machine_hold = ndb.IntegerProperty(default=0)\n service_hold = ndb.IntegerProperty(default=0)\n path_hold = ndb.IntegerProperty(default=0)\n\n\nclass CharacterImage(ndb.Model):\n blob = ndb.BlobKeyProperty()\n owner = ndb.StringProperty()\n access_params = ndb.StringProperty()\n\n\nclass FacebookUser(ndb.Model):\n displayname = ndb.StringProperty(required=True)\n user_id = ndb.StringProperty()\n profile_url = ndb.StringProperty(required=True)\n access_token = ndb.StringProperty(required=True)\n access_params = ndb.StringProperty()\n email = ndb.StringProperty()\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n last_visited = ndb.DateTimeProperty(auto_now=True)\n avatar = ndb.StringProperty()\n\n\nclass User(ndb.Model):\n user_id = ndb.IntegerProperty(required=True)\n email = ndb.StringProperty()\n username = ndb.StringProperty(required=True)\n org = ndb.StringProperty()\n access_params = ndb.StringProperty()\n pw_hash = ndb.StringProperty()\n last_visited = ndb.DateTimeProperty(auto_now=True)\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n APIkey = ndb.StringProperty()\n graph_created = ndb.IntegerProperty(default=0)\n\n @classmethod\n def by_id(cls, uid):\n return User.get_by_id(uid)\n\n @classmethod\n def by_username(cls, username):\n u = User.query(User.username == username).get()\n return u\n\n @classmethod\n def by_login(cls, user_id):\n u = User.query(User.user_id == user_id).get()\n return u\n\n @classmethod\n def by_email(cls, email):\n u = User.query(User.email == email).get()\n return u\n\n @classmethod\n def register(cls, username, email, password, org, user_id):\n pw_hash = make_pw_hash(username, password)\n access_params = create_params()\n api_key = generate_key()\n return User(user_id=user_id, username=username, email=email,\n pw_hash=pw_hash, org=org, access_params=access_params, APIkey=\n api_key)\n\n @classmethod\n def add_test_user(cls, user_id, username):\n return User(user_id=user_id, username=username)\n\n @classmethod\n def login(cls, username, password):\n u = cls.by_username(username)\n if u and valid_pw(username, password, u.pw_hash):\n return u\n\n @classmethod\n def bypass_login(cls, user_id):\n u = cls.by_user_id(user_id)\n if u:\n return u\n\n\nclass APIDatabase(ndb.Model):\n api_id = ndb.IntegerProperty(required=True)\n api_key = ndb.StringProperty(required=True)\n\n @classmethod\n def add_new_key(cls, api_id, api_key):\n return APIDatabase(api_id=api_id, api_key=api_key)\n\n\nclass Step(ndb.Model):\n startTurn = ndb.IntegerProperty()\n endTurn = ndb.IntegerProperty()\n solType = ndb.StringProperty()\n cost = ndb.IntegerProperty()\n fromCity = ndb.IntegerProperty()\n toCity = ndb.IntegerProperty()\n pathID = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n ai = ndb.IntegerProperty()\n ci = ndb.IntegerProperty()\n ii = ndb.IntegerProperty()\n\n\nclass WayPoints(ndb.Model):\n waypointsID = ndb.IntegerProperty()\n status = ndb.StringProperty()\n mapID = ndb.IntegerProperty()\n playerID = ndb.StringProperty()\n score = ndb.IntegerProperty()\n step = ndb.StructuredProperty(Step, repeated=True)\n savedTurn = ndb.IntegerProperty()\n graphStat = ndb.TextProperty()\n\n\nclass WaypointReport(ndb.Model):\n waypointID = ndb.IntegerProperty(required=True)\n play_by = ndb.StringProperty(required=True)\n score = ndb.IntegerProperty(required=True)\n total_turn = ndb.IntegerProperty(required=True)\n total_impact = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty(default=0)\n maximum_impact = ndb.FloatProperty(required=True)\n\n @classmethod\n def add_new_waypoint_report(cls, waypointID, play_by, score, total_turn,\n total_impact, owner_id, graph_id, maximum_impact, status):\n return WaypointReport(waypointID=waypointID, play_by=play_by, score\n =score, total_turn=total_turn, total_impact=total_impact,\n graph_id=graph_id, owner_id=owner_id, play_count=1,\n maximum_impact=maximum_impact)\n\n\nclass MapReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n avg_score = ndb.FloatProperty()\n total_turn = ndb.IntegerProperty()\n avg_total_turn = ndb.FloatProperty()\n total_impact = ndb.IntegerProperty()\n top_score = ndb.IntegerProperty(default=0)\n avg_total_impact = ndb.FloatProperty()\n maximum_impact = ndb.FloatProperty()\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n\n @classmethod\n def add_new_map_report(cls, mapID, play_count, score, avg_score,\n total_turn, avg_total_turn, total_impact, avg_total_impact,\n owner_id, graph_id, maximum_impact):\n return MapReport(mapID=mapID, play_count=play_count, score=score,\n avg_score=avg_score, total_turn=total_turn, avg_total_turn=\n avg_total_turn, total_impact=total_impact, avg_total_impact=\n avg_total_impact, graph_id=graph_id, owner_id=owner_id,\n maximum_impact=maximum_impact)\n\n\nclass PathReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n pathID = ndb.IntegerProperty(required=True)\n srcMachine = ndb.StringProperty()\n dstMachine = ndb.StringProperty()\n srcService = ndb.StringProperty()\n dstService = ndb.StringProperty()\n ai = ndb.IntegerProperty(required=True)\n ii = ndb.IntegerProperty(required=True)\n ci = ndb.IntegerProperty(required=True)\n av = ndb.IntegerProperty(required=True)\n ac = ndb.IntegerProperty(required=True)\n au = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n name = ndb.StringProperty()\n\n @classmethod\n def add_new_path_report(cls, mapID, graph_id, owner_id, pathID, srcM,\n dstM, srcS, dstS, ai, ii, ci, av, ac, au, counting):\n return PathReport(mapID=mapID, graph_id=graph_id, owner_id=owner_id,\n pathID=pathID, srcMachine=srcM, dstMachine=dstM, srcService=\n srcS, dstService=dstS, ai=ai, ii=ii, ci=ci, av=av, au=au, ac=ac,\n counting=counting)\n\n\nclass Solution(ndb.Model):\n cve_id = ndb.StringProperty(required=True)\n cwe_name = ndb.StringProperty(required=True)\n from_map = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n\n @classmethod\n def add_new_solution(cls, solution_id, cve_id, cwe_name, from_map):\n return Solution(solution_id=solution_id, cve_id=cve_id, cwe_name=\n cwe_name, from_map=from_map, counting=1)\n\n\nclass SolTypeReport(ndb.Model):\n owner_id = ndb.IntegerProperty(required=True)\n mapID = ndb.IntegerProperty(required=True)\n cve_id = ndb.StringProperty(required=True)\n service_name = ndb.StringProperty()\n solType_impact = ndb.IntegerProperty()\n cwe_name = ndb.StringProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n avg_hit = ndb.FloatProperty(default=1)\n\n @classmethod\n def add_new_soltype(cls, owner_id, mapID, cve_id, cwe_name,\n service_name, solType_impact):\n return SolTypeReport(owner_id=owner_id, mapID=mapID, cve_id=cve_id,\n cwe_name=cwe_name, counting=1, service_name=service_name,\n solType_impact=solType_impact)\n",
"step-2": "<mask token>\n\n\nclass Service(ndb.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Machine(ndb.Model):\n machineID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n impact = ndb.IntegerProperty()\n\n @classmethod\n def add_new_machine(cls, machineID, name, status, impact):\n return Machine(machineID=machineID, name=name, status=status,\n impact=impact)\n\n\nclass Path(ndb.Model):\n pathID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n src = ndb.IntegerProperty()\n dest = ndb.IntegerProperty()\n cve_id = ndb.StringProperty()\n confidentiality_impact = ndb.IntegerProperty()\n integrity_impact = ndb.IntegerProperty()\n availability_impact = ndb.IntegerProperty()\n access_complexity = ndb.IntegerProperty()\n gained_access = ndb.IntegerProperty()\n authentication = ndb.IntegerProperty()\n\n @classmethod\n def add_new_path(cls, pathID, name, status, src, dest, cve_id, c_imp,\n i_imp, a_imp, acc_com, g_acc, auth):\n return Path(pathID=pathID, name=name, status=status, src=src, dest=\n dest, cve_id=cve_id, confidentiality_impact=c_imp,\n integrity_impact=i_imp, availability_impact=a_imp,\n access_complexity=acc_com, gained_access=g_acc, authentication=auth\n )\n\n\nclass Graph(ndb.Model):\n name = ndb.StringProperty(required=True)\n graphID = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n machines = ndb.StructuredProperty(Machine, repeated=True)\n services = ndb.StructuredProperty(Service, repeated=True)\n paths = ndb.StructuredProperty(Path, repeated=True)\n machine_hold = ndb.IntegerProperty(default=0)\n service_hold = ndb.IntegerProperty(default=0)\n path_hold = ndb.IntegerProperty(default=0)\n\n\nclass CharacterImage(ndb.Model):\n blob = ndb.BlobKeyProperty()\n owner = ndb.StringProperty()\n access_params = ndb.StringProperty()\n\n\nclass FacebookUser(ndb.Model):\n displayname = ndb.StringProperty(required=True)\n user_id = ndb.StringProperty()\n profile_url = ndb.StringProperty(required=True)\n access_token = ndb.StringProperty(required=True)\n access_params = ndb.StringProperty()\n email = ndb.StringProperty()\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n last_visited = ndb.DateTimeProperty(auto_now=True)\n avatar = ndb.StringProperty()\n\n\nclass User(ndb.Model):\n user_id = ndb.IntegerProperty(required=True)\n email = ndb.StringProperty()\n username = ndb.StringProperty(required=True)\n org = ndb.StringProperty()\n access_params = ndb.StringProperty()\n pw_hash = ndb.StringProperty()\n last_visited = ndb.DateTimeProperty(auto_now=True)\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n APIkey = ndb.StringProperty()\n graph_created = ndb.IntegerProperty(default=0)\n\n @classmethod\n def by_id(cls, uid):\n return User.get_by_id(uid)\n\n @classmethod\n def by_username(cls, username):\n u = User.query(User.username == username).get()\n return u\n\n @classmethod\n def by_login(cls, user_id):\n u = User.query(User.user_id == user_id).get()\n return u\n\n @classmethod\n def by_email(cls, email):\n u = User.query(User.email == email).get()\n return u\n\n @classmethod\n def register(cls, username, email, password, org, user_id):\n pw_hash = make_pw_hash(username, password)\n access_params = create_params()\n api_key = generate_key()\n return User(user_id=user_id, username=username, email=email,\n pw_hash=pw_hash, org=org, access_params=access_params, APIkey=\n api_key)\n\n @classmethod\n def add_test_user(cls, user_id, username):\n return User(user_id=user_id, username=username)\n\n @classmethod\n def login(cls, username, password):\n u = cls.by_username(username)\n if u and valid_pw(username, password, u.pw_hash):\n return u\n\n @classmethod\n def bypass_login(cls, user_id):\n u = cls.by_user_id(user_id)\n if u:\n return u\n\n\nclass APIDatabase(ndb.Model):\n api_id = ndb.IntegerProperty(required=True)\n api_key = ndb.StringProperty(required=True)\n\n @classmethod\n def add_new_key(cls, api_id, api_key):\n return APIDatabase(api_id=api_id, api_key=api_key)\n\n\nclass Step(ndb.Model):\n startTurn = ndb.IntegerProperty()\n endTurn = ndb.IntegerProperty()\n solType = ndb.StringProperty()\n cost = ndb.IntegerProperty()\n fromCity = ndb.IntegerProperty()\n toCity = ndb.IntegerProperty()\n pathID = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n ai = ndb.IntegerProperty()\n ci = ndb.IntegerProperty()\n ii = ndb.IntegerProperty()\n\n\nclass WayPoints(ndb.Model):\n waypointsID = ndb.IntegerProperty()\n status = ndb.StringProperty()\n mapID = ndb.IntegerProperty()\n playerID = ndb.StringProperty()\n score = ndb.IntegerProperty()\n step = ndb.StructuredProperty(Step, repeated=True)\n savedTurn = ndb.IntegerProperty()\n graphStat = ndb.TextProperty()\n\n\nclass WaypointReport(ndb.Model):\n waypointID = ndb.IntegerProperty(required=True)\n play_by = ndb.StringProperty(required=True)\n score = ndb.IntegerProperty(required=True)\n total_turn = ndb.IntegerProperty(required=True)\n total_impact = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty(default=0)\n maximum_impact = ndb.FloatProperty(required=True)\n\n @classmethod\n def add_new_waypoint_report(cls, waypointID, play_by, score, total_turn,\n total_impact, owner_id, graph_id, maximum_impact, status):\n return WaypointReport(waypointID=waypointID, play_by=play_by, score\n =score, total_turn=total_turn, total_impact=total_impact,\n graph_id=graph_id, owner_id=owner_id, play_count=1,\n maximum_impact=maximum_impact)\n\n\nclass MapReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n avg_score = ndb.FloatProperty()\n total_turn = ndb.IntegerProperty()\n avg_total_turn = ndb.FloatProperty()\n total_impact = ndb.IntegerProperty()\n top_score = ndb.IntegerProperty(default=0)\n avg_total_impact = ndb.FloatProperty()\n maximum_impact = ndb.FloatProperty()\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n\n @classmethod\n def add_new_map_report(cls, mapID, play_count, score, avg_score,\n total_turn, avg_total_turn, total_impact, avg_total_impact,\n owner_id, graph_id, maximum_impact):\n return MapReport(mapID=mapID, play_count=play_count, score=score,\n avg_score=avg_score, total_turn=total_turn, avg_total_turn=\n avg_total_turn, total_impact=total_impact, avg_total_impact=\n avg_total_impact, graph_id=graph_id, owner_id=owner_id,\n maximum_impact=maximum_impact)\n\n\nclass PathReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n pathID = ndb.IntegerProperty(required=True)\n srcMachine = ndb.StringProperty()\n dstMachine = ndb.StringProperty()\n srcService = ndb.StringProperty()\n dstService = ndb.StringProperty()\n ai = ndb.IntegerProperty(required=True)\n ii = ndb.IntegerProperty(required=True)\n ci = ndb.IntegerProperty(required=True)\n av = ndb.IntegerProperty(required=True)\n ac = ndb.IntegerProperty(required=True)\n au = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n name = ndb.StringProperty()\n\n @classmethod\n def add_new_path_report(cls, mapID, graph_id, owner_id, pathID, srcM,\n dstM, srcS, dstS, ai, ii, ci, av, ac, au, counting):\n return PathReport(mapID=mapID, graph_id=graph_id, owner_id=owner_id,\n pathID=pathID, srcMachine=srcM, dstMachine=dstM, srcService=\n srcS, dstService=dstS, ai=ai, ii=ii, ci=ci, av=av, au=au, ac=ac,\n counting=counting)\n\n\nclass Solution(ndb.Model):\n cve_id = ndb.StringProperty(required=True)\n cwe_name = ndb.StringProperty(required=True)\n from_map = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n\n @classmethod\n def add_new_solution(cls, solution_id, cve_id, cwe_name, from_map):\n return Solution(solution_id=solution_id, cve_id=cve_id, cwe_name=\n cwe_name, from_map=from_map, counting=1)\n\n\nclass SolTypeReport(ndb.Model):\n owner_id = ndb.IntegerProperty(required=True)\n mapID = ndb.IntegerProperty(required=True)\n cve_id = ndb.StringProperty(required=True)\n service_name = ndb.StringProperty()\n solType_impact = ndb.IntegerProperty()\n cwe_name = ndb.StringProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n avg_hit = ndb.FloatProperty(default=1)\n\n @classmethod\n def add_new_soltype(cls, owner_id, mapID, cve_id, cwe_name,\n service_name, solType_impact):\n return SolTypeReport(owner_id=owner_id, mapID=mapID, cve_id=cve_id,\n cwe_name=cwe_name, counting=1, service_name=service_name,\n solType_impact=solType_impact)\n",
"step-3": "<mask token>\n\n\nclass CVEProfile(ndb.Model):\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n <mask token>\n\n @classmethod\n def createProfile(cls, cve_id, cwe_id, cwe_name, summary, cvss_score,\n exploit_count, publish_date, update_date, cve_url,\n confidentiality_impact, integrity_impact, availability_impact,\n access_complexity, gained_access, authentication):\n access_params = create_params()\n return CVEProfile(cve_id=cve_id, cwe_id=cwe_id, cwe_name=cwe_name,\n summary=summary, cvss_score=cvss_score, exploit_count=\n exploit_count, publish_date=publish_date, update_date=\n update_date, cve_url=cve_url, confidentiality_impact=\n confidentiality_impact, integrity_impact=integrity_impact,\n availability_impact=availability_impact, access_complexity=\n access_complexity, gained_access=gained_access, authentication=\n authentication, access_params=access_params)\n\n\nclass Service(ndb.Model):\n serviceID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n impact = ndb.IntegerProperty()\n machineID = ndb.IntegerProperty()\n\n @classmethod\n def add_new_service(cls, serviceID, name, status, impact, machineID):\n return Service(serviceID=serviceID, name=name, status=status,\n impact=impact, machineID=machineID)\n\n\nclass Machine(ndb.Model):\n machineID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n impact = ndb.IntegerProperty()\n\n @classmethod\n def add_new_machine(cls, machineID, name, status, impact):\n return Machine(machineID=machineID, name=name, status=status,\n impact=impact)\n\n\nclass Path(ndb.Model):\n pathID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n src = ndb.IntegerProperty()\n dest = ndb.IntegerProperty()\n cve_id = ndb.StringProperty()\n confidentiality_impact = ndb.IntegerProperty()\n integrity_impact = ndb.IntegerProperty()\n availability_impact = ndb.IntegerProperty()\n access_complexity = ndb.IntegerProperty()\n gained_access = ndb.IntegerProperty()\n authentication = ndb.IntegerProperty()\n\n @classmethod\n def add_new_path(cls, pathID, name, status, src, dest, cve_id, c_imp,\n i_imp, a_imp, acc_com, g_acc, auth):\n return Path(pathID=pathID, name=name, status=status, src=src, dest=\n dest, cve_id=cve_id, confidentiality_impact=c_imp,\n integrity_impact=i_imp, availability_impact=a_imp,\n access_complexity=acc_com, gained_access=g_acc, authentication=auth\n )\n\n\nclass Graph(ndb.Model):\n name = ndb.StringProperty(required=True)\n graphID = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n machines = ndb.StructuredProperty(Machine, repeated=True)\n services = ndb.StructuredProperty(Service, repeated=True)\n paths = ndb.StructuredProperty(Path, repeated=True)\n machine_hold = ndb.IntegerProperty(default=0)\n service_hold = ndb.IntegerProperty(default=0)\n path_hold = ndb.IntegerProperty(default=0)\n\n\nclass CharacterImage(ndb.Model):\n blob = ndb.BlobKeyProperty()\n owner = ndb.StringProperty()\n access_params = ndb.StringProperty()\n\n\nclass FacebookUser(ndb.Model):\n displayname = ndb.StringProperty(required=True)\n user_id = ndb.StringProperty()\n profile_url = ndb.StringProperty(required=True)\n access_token = ndb.StringProperty(required=True)\n access_params = ndb.StringProperty()\n email = ndb.StringProperty()\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n last_visited = ndb.DateTimeProperty(auto_now=True)\n avatar = ndb.StringProperty()\n\n\nclass User(ndb.Model):\n user_id = ndb.IntegerProperty(required=True)\n email = ndb.StringProperty()\n username = ndb.StringProperty(required=True)\n org = ndb.StringProperty()\n access_params = ndb.StringProperty()\n pw_hash = ndb.StringProperty()\n last_visited = ndb.DateTimeProperty(auto_now=True)\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n APIkey = ndb.StringProperty()\n graph_created = ndb.IntegerProperty(default=0)\n\n @classmethod\n def by_id(cls, uid):\n return User.get_by_id(uid)\n\n @classmethod\n def by_username(cls, username):\n u = User.query(User.username == username).get()\n return u\n\n @classmethod\n def by_login(cls, user_id):\n u = User.query(User.user_id == user_id).get()\n return u\n\n @classmethod\n def by_email(cls, email):\n u = User.query(User.email == email).get()\n return u\n\n @classmethod\n def register(cls, username, email, password, org, user_id):\n pw_hash = make_pw_hash(username, password)\n access_params = create_params()\n api_key = generate_key()\n return User(user_id=user_id, username=username, email=email,\n pw_hash=pw_hash, org=org, access_params=access_params, APIkey=\n api_key)\n\n @classmethod\n def add_test_user(cls, user_id, username):\n return User(user_id=user_id, username=username)\n\n @classmethod\n def login(cls, username, password):\n u = cls.by_username(username)\n if u and valid_pw(username, password, u.pw_hash):\n return u\n\n @classmethod\n def bypass_login(cls, user_id):\n u = cls.by_user_id(user_id)\n if u:\n return u\n\n\nclass APIDatabase(ndb.Model):\n api_id = ndb.IntegerProperty(required=True)\n api_key = ndb.StringProperty(required=True)\n\n @classmethod\n def add_new_key(cls, api_id, api_key):\n return APIDatabase(api_id=api_id, api_key=api_key)\n\n\nclass Step(ndb.Model):\n startTurn = ndb.IntegerProperty()\n endTurn = ndb.IntegerProperty()\n solType = ndb.StringProperty()\n cost = ndb.IntegerProperty()\n fromCity = ndb.IntegerProperty()\n toCity = ndb.IntegerProperty()\n pathID = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n ai = ndb.IntegerProperty()\n ci = ndb.IntegerProperty()\n ii = ndb.IntegerProperty()\n\n\nclass WayPoints(ndb.Model):\n waypointsID = ndb.IntegerProperty()\n status = ndb.StringProperty()\n mapID = ndb.IntegerProperty()\n playerID = ndb.StringProperty()\n score = ndb.IntegerProperty()\n step = ndb.StructuredProperty(Step, repeated=True)\n savedTurn = ndb.IntegerProperty()\n graphStat = ndb.TextProperty()\n\n\nclass WaypointReport(ndb.Model):\n waypointID = ndb.IntegerProperty(required=True)\n play_by = ndb.StringProperty(required=True)\n score = ndb.IntegerProperty(required=True)\n total_turn = ndb.IntegerProperty(required=True)\n total_impact = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty(default=0)\n maximum_impact = ndb.FloatProperty(required=True)\n\n @classmethod\n def add_new_waypoint_report(cls, waypointID, play_by, score, total_turn,\n total_impact, owner_id, graph_id, maximum_impact, status):\n return WaypointReport(waypointID=waypointID, play_by=play_by, score\n =score, total_turn=total_turn, total_impact=total_impact,\n graph_id=graph_id, owner_id=owner_id, play_count=1,\n maximum_impact=maximum_impact)\n\n\nclass MapReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n avg_score = ndb.FloatProperty()\n total_turn = ndb.IntegerProperty()\n avg_total_turn = ndb.FloatProperty()\n total_impact = ndb.IntegerProperty()\n top_score = ndb.IntegerProperty(default=0)\n avg_total_impact = ndb.FloatProperty()\n maximum_impact = ndb.FloatProperty()\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n\n @classmethod\n def add_new_map_report(cls, mapID, play_count, score, avg_score,\n total_turn, avg_total_turn, total_impact, avg_total_impact,\n owner_id, graph_id, maximum_impact):\n return MapReport(mapID=mapID, play_count=play_count, score=score,\n avg_score=avg_score, total_turn=total_turn, avg_total_turn=\n avg_total_turn, total_impact=total_impact, avg_total_impact=\n avg_total_impact, graph_id=graph_id, owner_id=owner_id,\n maximum_impact=maximum_impact)\n\n\nclass PathReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n pathID = ndb.IntegerProperty(required=True)\n srcMachine = ndb.StringProperty()\n dstMachine = ndb.StringProperty()\n srcService = ndb.StringProperty()\n dstService = ndb.StringProperty()\n ai = ndb.IntegerProperty(required=True)\n ii = ndb.IntegerProperty(required=True)\n ci = ndb.IntegerProperty(required=True)\n av = ndb.IntegerProperty(required=True)\n ac = ndb.IntegerProperty(required=True)\n au = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n name = ndb.StringProperty()\n\n @classmethod\n def add_new_path_report(cls, mapID, graph_id, owner_id, pathID, srcM,\n dstM, srcS, dstS, ai, ii, ci, av, ac, au, counting):\n return PathReport(mapID=mapID, graph_id=graph_id, owner_id=owner_id,\n pathID=pathID, srcMachine=srcM, dstMachine=dstM, srcService=\n srcS, dstService=dstS, ai=ai, ii=ii, ci=ci, av=av, au=au, ac=ac,\n counting=counting)\n\n\nclass Solution(ndb.Model):\n cve_id = ndb.StringProperty(required=True)\n cwe_name = ndb.StringProperty(required=True)\n from_map = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n\n @classmethod\n def add_new_solution(cls, solution_id, cve_id, cwe_name, from_map):\n return Solution(solution_id=solution_id, cve_id=cve_id, cwe_name=\n cwe_name, from_map=from_map, counting=1)\n\n\nclass SolTypeReport(ndb.Model):\n owner_id = ndb.IntegerProperty(required=True)\n mapID = ndb.IntegerProperty(required=True)\n cve_id = ndb.StringProperty(required=True)\n service_name = ndb.StringProperty()\n solType_impact = ndb.IntegerProperty()\n cwe_name = ndb.StringProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n avg_hit = ndb.FloatProperty(default=1)\n\n @classmethod\n def add_new_soltype(cls, owner_id, mapID, cve_id, cwe_name,\n service_name, solType_impact):\n return SolTypeReport(owner_id=owner_id, mapID=mapID, cve_id=cve_id,\n cwe_name=cwe_name, counting=1, service_name=service_name,\n solType_impact=solType_impact)\n",
"step-4": "import sys\nfrom google.appengine.ext import blobstore\nfrom google.appengine.ext.webapp import blobstore_handlers\nfrom google.appengine.ext import ndb\nfrom helpers import *\n\n\ndef valid_pw(name, password, h):\n salt = h.split(',')[0]\n return h == make_pw_hash(name, password, salt)\n\n\nclass CVEProfile(ndb.Model):\n profile_name = ndb.StringProperty(default='N/A')\n cve_id = ndb.StringProperty(required=True)\n cwe_id = ndb.StringProperty(required=True)\n cwe_name = ndb.StringProperty(required=True)\n summary = ndb.TextProperty()\n cvss_score = ndb.FloatProperty()\n exploit_count = ndb.IntegerProperty()\n publish_date = ndb.StringProperty()\n update_date = ndb.StringProperty()\n cve_url = ndb.StringProperty()\n created = ndb.DateTimeProperty(auto_now_add=True)\n access_params = ndb.StringProperty()\n confidentiality_impact = ndb.IntegerProperty()\n integrity_impact = ndb.IntegerProperty()\n availability_impact = ndb.IntegerProperty()\n access_complexity = ndb.IntegerProperty()\n gained_access = ndb.IntegerProperty()\n authentication = ndb.IntegerProperty()\n\n @classmethod\n def createProfile(cls, cve_id, cwe_id, cwe_name, summary, cvss_score,\n exploit_count, publish_date, update_date, cve_url,\n confidentiality_impact, integrity_impact, availability_impact,\n access_complexity, gained_access, authentication):\n access_params = create_params()\n return CVEProfile(cve_id=cve_id, cwe_id=cwe_id, cwe_name=cwe_name,\n summary=summary, cvss_score=cvss_score, exploit_count=\n exploit_count, publish_date=publish_date, update_date=\n update_date, cve_url=cve_url, confidentiality_impact=\n confidentiality_impact, integrity_impact=integrity_impact,\n availability_impact=availability_impact, access_complexity=\n access_complexity, gained_access=gained_access, authentication=\n authentication, access_params=access_params)\n\n\nclass Service(ndb.Model):\n serviceID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n impact = ndb.IntegerProperty()\n machineID = ndb.IntegerProperty()\n\n @classmethod\n def add_new_service(cls, serviceID, name, status, impact, machineID):\n return Service(serviceID=serviceID, name=name, status=status,\n impact=impact, machineID=machineID)\n\n\nclass Machine(ndb.Model):\n machineID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n impact = ndb.IntegerProperty()\n\n @classmethod\n def add_new_machine(cls, machineID, name, status, impact):\n return Machine(machineID=machineID, name=name, status=status,\n impact=impact)\n\n\nclass Path(ndb.Model):\n pathID = ndb.IntegerProperty(required=True)\n name = ndb.StringProperty()\n status = ndb.StringProperty()\n src = ndb.IntegerProperty()\n dest = ndb.IntegerProperty()\n cve_id = ndb.StringProperty()\n confidentiality_impact = ndb.IntegerProperty()\n integrity_impact = ndb.IntegerProperty()\n availability_impact = ndb.IntegerProperty()\n access_complexity = ndb.IntegerProperty()\n gained_access = ndb.IntegerProperty()\n authentication = ndb.IntegerProperty()\n\n @classmethod\n def add_new_path(cls, pathID, name, status, src, dest, cve_id, c_imp,\n i_imp, a_imp, acc_com, g_acc, auth):\n return Path(pathID=pathID, name=name, status=status, src=src, dest=\n dest, cve_id=cve_id, confidentiality_impact=c_imp,\n integrity_impact=i_imp, availability_impact=a_imp,\n access_complexity=acc_com, gained_access=g_acc, authentication=auth\n )\n\n\nclass Graph(ndb.Model):\n name = ndb.StringProperty(required=True)\n graphID = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n machines = ndb.StructuredProperty(Machine, repeated=True)\n services = ndb.StructuredProperty(Service, repeated=True)\n paths = ndb.StructuredProperty(Path, repeated=True)\n machine_hold = ndb.IntegerProperty(default=0)\n service_hold = ndb.IntegerProperty(default=0)\n path_hold = ndb.IntegerProperty(default=0)\n\n\nclass CharacterImage(ndb.Model):\n blob = ndb.BlobKeyProperty()\n owner = ndb.StringProperty()\n access_params = ndb.StringProperty()\n\n\nclass FacebookUser(ndb.Model):\n displayname = ndb.StringProperty(required=True)\n user_id = ndb.StringProperty()\n profile_url = ndb.StringProperty(required=True)\n access_token = ndb.StringProperty(required=True)\n access_params = ndb.StringProperty()\n email = ndb.StringProperty()\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n last_visited = ndb.DateTimeProperty(auto_now=True)\n avatar = ndb.StringProperty()\n\n\nclass User(ndb.Model):\n user_id = ndb.IntegerProperty(required=True)\n email = ndb.StringProperty()\n username = ndb.StringProperty(required=True)\n org = ndb.StringProperty()\n access_params = ndb.StringProperty()\n pw_hash = ndb.StringProperty()\n last_visited = ndb.DateTimeProperty(auto_now=True)\n joined_date = ndb.DateTimeProperty(auto_now_add=True)\n APIkey = ndb.StringProperty()\n graph_created = ndb.IntegerProperty(default=0)\n\n @classmethod\n def by_id(cls, uid):\n return User.get_by_id(uid)\n\n @classmethod\n def by_username(cls, username):\n u = User.query(User.username == username).get()\n return u\n\n @classmethod\n def by_login(cls, user_id):\n u = User.query(User.user_id == user_id).get()\n return u\n\n @classmethod\n def by_email(cls, email):\n u = User.query(User.email == email).get()\n return u\n\n @classmethod\n def register(cls, username, email, password, org, user_id):\n pw_hash = make_pw_hash(username, password)\n access_params = create_params()\n api_key = generate_key()\n return User(user_id=user_id, username=username, email=email,\n pw_hash=pw_hash, org=org, access_params=access_params, APIkey=\n api_key)\n\n @classmethod\n def add_test_user(cls, user_id, username):\n return User(user_id=user_id, username=username)\n\n @classmethod\n def login(cls, username, password):\n u = cls.by_username(username)\n if u and valid_pw(username, password, u.pw_hash):\n return u\n\n @classmethod\n def bypass_login(cls, user_id):\n u = cls.by_user_id(user_id)\n if u:\n return u\n\n\nclass APIDatabase(ndb.Model):\n api_id = ndb.IntegerProperty(required=True)\n api_key = ndb.StringProperty(required=True)\n\n @classmethod\n def add_new_key(cls, api_id, api_key):\n return APIDatabase(api_id=api_id, api_key=api_key)\n\n\nclass Step(ndb.Model):\n startTurn = ndb.IntegerProperty()\n endTurn = ndb.IntegerProperty()\n solType = ndb.StringProperty()\n cost = ndb.IntegerProperty()\n fromCity = ndb.IntegerProperty()\n toCity = ndb.IntegerProperty()\n pathID = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n ai = ndb.IntegerProperty()\n ci = ndb.IntegerProperty()\n ii = ndb.IntegerProperty()\n\n\nclass WayPoints(ndb.Model):\n waypointsID = ndb.IntegerProperty()\n status = ndb.StringProperty()\n mapID = ndb.IntegerProperty()\n playerID = ndb.StringProperty()\n score = ndb.IntegerProperty()\n step = ndb.StructuredProperty(Step, repeated=True)\n savedTurn = ndb.IntegerProperty()\n graphStat = ndb.TextProperty()\n\n\nclass WaypointReport(ndb.Model):\n waypointID = ndb.IntegerProperty(required=True)\n play_by = ndb.StringProperty(required=True)\n score = ndb.IntegerProperty(required=True)\n total_turn = ndb.IntegerProperty(required=True)\n total_impact = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty(default=0)\n maximum_impact = ndb.FloatProperty(required=True)\n\n @classmethod\n def add_new_waypoint_report(cls, waypointID, play_by, score, total_turn,\n total_impact, owner_id, graph_id, maximum_impact, status):\n return WaypointReport(waypointID=waypointID, play_by=play_by, score\n =score, total_turn=total_turn, total_impact=total_impact,\n graph_id=graph_id, owner_id=owner_id, play_count=1,\n maximum_impact=maximum_impact)\n\n\nclass MapReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n play_count = ndb.IntegerProperty()\n score = ndb.IntegerProperty()\n avg_score = ndb.FloatProperty()\n total_turn = ndb.IntegerProperty()\n avg_total_turn = ndb.FloatProperty()\n total_impact = ndb.IntegerProperty()\n top_score = ndb.IntegerProperty(default=0)\n avg_total_impact = ndb.FloatProperty()\n maximum_impact = ndb.FloatProperty()\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n\n @classmethod\n def add_new_map_report(cls, mapID, play_count, score, avg_score,\n total_turn, avg_total_turn, total_impact, avg_total_impact,\n owner_id, graph_id, maximum_impact):\n return MapReport(mapID=mapID, play_count=play_count, score=score,\n avg_score=avg_score, total_turn=total_turn, avg_total_turn=\n avg_total_turn, total_impact=total_impact, avg_total_impact=\n avg_total_impact, graph_id=graph_id, owner_id=owner_id,\n maximum_impact=maximum_impact)\n\n\nclass PathReport(ndb.Model):\n mapID = ndb.IntegerProperty(required=True)\n graph_id = ndb.IntegerProperty(required=True)\n owner_id = ndb.IntegerProperty(required=True)\n pathID = ndb.IntegerProperty(required=True)\n srcMachine = ndb.StringProperty()\n dstMachine = ndb.StringProperty()\n srcService = ndb.StringProperty()\n dstService = ndb.StringProperty()\n ai = ndb.IntegerProperty(required=True)\n ii = ndb.IntegerProperty(required=True)\n ci = ndb.IntegerProperty(required=True)\n av = ndb.IntegerProperty(required=True)\n ac = ndb.IntegerProperty(required=True)\n au = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n name = ndb.StringProperty()\n\n @classmethod\n def add_new_path_report(cls, mapID, graph_id, owner_id, pathID, srcM,\n dstM, srcS, dstS, ai, ii, ci, av, ac, au, counting):\n return PathReport(mapID=mapID, graph_id=graph_id, owner_id=owner_id,\n pathID=pathID, srcMachine=srcM, dstMachine=dstM, srcService=\n srcS, dstService=dstS, ai=ai, ii=ii, ci=ci, av=av, au=au, ac=ac,\n counting=counting)\n\n\nclass Solution(ndb.Model):\n cve_id = ndb.StringProperty(required=True)\n cwe_name = ndb.StringProperty(required=True)\n from_map = ndb.IntegerProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n\n @classmethod\n def add_new_solution(cls, solution_id, cve_id, cwe_name, from_map):\n return Solution(solution_id=solution_id, cve_id=cve_id, cwe_name=\n cwe_name, from_map=from_map, counting=1)\n\n\nclass SolTypeReport(ndb.Model):\n owner_id = ndb.IntegerProperty(required=True)\n mapID = ndb.IntegerProperty(required=True)\n cve_id = ndb.StringProperty(required=True)\n service_name = ndb.StringProperty()\n solType_impact = ndb.IntegerProperty()\n cwe_name = ndb.StringProperty(required=True)\n counting = ndb.IntegerProperty(default=0)\n avg_hit = ndb.FloatProperty(default=1)\n\n @classmethod\n def add_new_soltype(cls, owner_id, mapID, cve_id, cwe_name,\n service_name, solType_impact):\n return SolTypeReport(owner_id=owner_id, mapID=mapID, cve_id=cve_id,\n cwe_name=cwe_name, counting=1, service_name=service_name,\n solType_impact=solType_impact)\n",
"step-5": "import sys\nfrom google.appengine.ext import blobstore\nfrom google.appengine.ext.webapp import blobstore_handlers\nfrom google.appengine.ext import ndb\nfrom helpers import *\n\ndef valid_pw(name, password, h):\n\tsalt = h.split(',')[0]\n\treturn h == make_pw_hash(name, password, salt)\n\nclass CVEProfile(ndb.Model):\n\tprofile_name = ndb.StringProperty(default=\"N/A\")\n\tcve_id = ndb.StringProperty(required=True)\n\tcwe_id = ndb.StringProperty(required=True)\n\tcwe_name = ndb.StringProperty(required=True)\n\tsummary = ndb.TextProperty()\n\tcvss_score = ndb.FloatProperty()\n\texploit_count = ndb.IntegerProperty()\n\tpublish_date = ndb.StringProperty()\n\tupdate_date = ndb.StringProperty()\t\n\tcve_url = ndb.StringProperty()\n\tcreated = ndb.DateTimeProperty(auto_now_add=True)\n\taccess_params = ndb.StringProperty()\n\tconfidentiality_impact = ndb.IntegerProperty()\n\tintegrity_impact = ndb.IntegerProperty()\n\tavailability_impact = ndb.IntegerProperty()\n\taccess_complexity = ndb.IntegerProperty()\n\tgained_access = ndb.IntegerProperty()\n\tauthentication = ndb.IntegerProperty()\n\t\n\t@classmethod\n\tdef createProfile(cls, cve_id , cwe_id , cwe_name, summary, cvss_score, exploit_count, publish_date, update_date, cve_url, confidentiality_impact, integrity_impact, availability_impact, access_complexity, gained_access, authentication):\n\t\taccess_params = create_params()\n\t\treturn CVEProfile(\tcve_id = cve_id,\n\t\t\t\t\t\t\tcwe_id = cwe_id,\n\t\t\t\t\t\t\tcwe_name = cwe_name,\n\t\t\t\t\t\t\tsummary = summary,\n\t\t\t\t\t\t\tcvss_score = cvss_score,\n\t\t\t\t\t\t\texploit_count = exploit_count,\n\t\t\t\t\t\t\tpublish_date = publish_date,\n\t\t\t\t\t\t\tupdate_date = update_date,\n\t\t\t\t\t\t\tcve_url = cve_url,\n\t\t\t\t\t\t\tconfidentiality_impact = confidentiality_impact,\n\t\t\t\t\t\t\tintegrity_impact = integrity_impact,\n\t\t\t\t\t\t\tavailability_impact = availability_impact,\n\t\t\t\t\t\t\taccess_complexity = access_complexity,\n\t\t\t\t\t\t\tgained_access = gained_access,\n\t\t\t\t\t\t\tauthentication = authentication,\n\t\t\t\t\t\t\taccess_params = access_params\t\t\t\t\t)\n\nclass Service(ndb.Model):\n\tserviceID=ndb.IntegerProperty(required=True)\n\tname=ndb.StringProperty()\n\tstatus=ndb.StringProperty()\n\timpact=ndb.IntegerProperty()\n\tmachineID=ndb.IntegerProperty()\n\t\n\t@classmethod\n\tdef add_new_service(cls,serviceID,name,status,impact,machineID):\n\t\treturn Service(\t\tserviceID \t= \tserviceID,\n\t\t\t\t\t\t\tname \t\t= \tname,\n\t\t\t\t\t\t\tstatus \t\t=\tstatus,\n\t\t\t\t\t\t\timpact \t\t= \timpact,\n\t\t\t\t\t\t\tmachineID\t=\tmachineID)\n\nclass Machine(ndb.Model):\n\tmachineID=ndb.IntegerProperty(required=True)\n\tname=ndb.StringProperty()\n\tstatus=ndb.StringProperty()\n\timpact=ndb.IntegerProperty()\n\t\n\t@classmethod\n\tdef add_new_machine(cls,machineID,name,status,impact):\n\t\treturn Machine(\t\tmachineID \t= \tmachineID,\n\t\t\t\t\t\t\tname \t\t= \tname,\n\t\t\t\t\t\t\tstatus \t\t=\tstatus,\n\t\t\t\t\t\t\timpact \t\t= \timpact)\n\nclass Path(ndb.Model):\n\tpathID=ndb.IntegerProperty(required=True)\n\tname=ndb.StringProperty()\n\tstatus=ndb.StringProperty()\n\tsrc=ndb.IntegerProperty()\n\tdest=ndb.IntegerProperty()\n\t#cvss=ndb.StringProperty()\n\tcve_id = ndb.StringProperty()\n\tconfidentiality_impact = ndb.IntegerProperty()\n\tintegrity_impact = ndb.IntegerProperty()\n\tavailability_impact = ndb.IntegerProperty()\n\taccess_complexity = ndb.IntegerProperty()\n\tgained_access = ndb.IntegerProperty()\n\tauthentication = ndb.IntegerProperty()\n\t\n\t@classmethod\n\tdef add_new_path(cls,pathID,name,status,src,dest,cve_id,c_imp,i_imp,a_imp,acc_com,g_acc,auth):\n\t\treturn Path(\t\tpathID \t\t\t\t\t\t= \tpathID,\n\t\t\t\t\t\t\tname \t\t\t\t\t\t= \tname,\n\t\t\t\t\t\t\tstatus \t\t\t\t\t\t=\tstatus,\n\t\t\t\t\t\t\tsrc \t\t\t\t\t\t= \tsrc,\n\t\t\t\t\t\t\tdest\t\t\t\t\t\t=\tdest,\n\t\t\t\t\t\t\tcve_id = cve_id,\n\t\t\t\t\t\t\tconfidentiality_impact \t\t= \tc_imp,\n\t\t\t\t\t\t\tintegrity_impact \t\t\t= \ti_imp,\n\t\t\t\t\t\t\tavailability_impact \t\t= \ta_imp,\n\t\t\t\t\t\t\taccess_complexity \t\t\t= \tacc_com,\n\t\t\t\t\t\t\tgained_access \t\t\t\t= \tg_acc,\n\t\t\t\t\t\t\tauthentication \t\t\t\t= \tauth )\n\nclass Graph(ndb.Model):\n\tname=ndb.StringProperty(required=True)\n\tgraphID=ndb.IntegerProperty(required=True)\t\n\t#owner=ndb.KeyProperty(kind='User') #GUI push\t\n\towner_id=ndb.IntegerProperty(required=True) #JSON push\n\tmachines=ndb.StructuredProperty(Machine, repeated=True)\n\tservices=ndb.StructuredProperty(Service, repeated=True)\n\tpaths=ndb.StructuredProperty(Path, repeated=True)\t\n\t# keep track for reporting\n\tmachine_hold = ndb.IntegerProperty(default=0)\n\tservice_hold = ndb.IntegerProperty(default=0)\n\tpath_hold = ndb.IntegerProperty(default=0)\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\nclass CharacterImage(ndb.Model):\n\tblob = ndb.BlobKeyProperty()\n\towner = ndb.StringProperty()\n\taccess_params = ndb.StringProperty()\t\n\nclass FacebookUser(ndb.Model):\n\tdisplayname = ndb.StringProperty(required=True)\n\tuser_id = ndb.StringProperty()\n\tprofile_url = ndb.StringProperty(required=True)\n\taccess_token = ndb.StringProperty(required=True)\n\taccess_params = ndb.StringProperty()\n\temail = ndb.StringProperty()\n\tjoined_date = ndb.DateTimeProperty(auto_now_add=True)\n\tlast_visited = ndb.DateTimeProperty(auto_now=True)\n\tavatar = ndb.StringProperty()\n\n\t\nclass User(ndb.Model):\n\tuser_id=ndb.IntegerProperty(required=True)\n\temail = ndb.StringProperty()\n\t#displayname = ndb.StringProperty()\n\tusername = ndb.StringProperty(required=True)\n\torg = ndb.StringProperty()\n\taccess_params = ndb.StringProperty()\t\n\tpw_hash = ndb.StringProperty()\n\tlast_visited = ndb.DateTimeProperty(auto_now=True)\n\tjoined_date = ndb.DateTimeProperty(auto_now_add=True)\n\tAPIkey = ndb.StringProperty()\n\tgraph_created = ndb.IntegerProperty(default=0)\n\t\n\t@classmethod\n\tdef by_id(cls, uid):\n\t\treturn User.get_by_id(uid)\n\t\n\t\t\n\t@classmethod\n\tdef by_username(cls, username):\n\t\tu = User.query(User.username == username).get()\n\t\treturn u\n\t\n\t@classmethod\n\tdef by_login(cls, user_id):\n\t\tu = User.query(User.user_id == user_id).get()\n\t\treturn u\n\t\t\n\t@classmethod\n\tdef by_email(cls, email):\n\t\tu = User.query(User.email == email).get()\n\t\treturn u\n\n\t@classmethod\n\tdef register(cls, username,email, password, org, user_id):\n\t\tpw_hash = make_pw_hash(username, password)\n\t\taccess_params = create_params()\n\t\tapi_key = generate_key()\n\t\treturn User(\tuser_id = user_id,\n\t\t\t\t\t\tusername = username,\n\t\t\t\t\t\temail = email,\n\t\t\t\t\t\tpw_hash = pw_hash,\n\t\t\t\t\t\torg = org,\n\t\t\t\t\t\taccess_params = access_params,\n\t\t\t\t\t\tAPIkey = api_key\t)\n\t\n\t@classmethod\n\tdef add_test_user(cls, user_id , username ):\n\t\treturn User(\tuser_id = user_id,\n\t\t\t\t\t\tusername = username\t\t)\t\t\t\t\t\n\t\t\t\t\t\n\t@classmethod\n\tdef login(cls, username, password):\n\t\tu = cls.by_username(username)\n\t\tif u and valid_pw(username, password, u.pw_hash):\n\t\t\treturn u\n\n\t@classmethod\n\tdef bypass_login(cls, user_id):\n\t\tu = cls.by_user_id(user_id)\n\t\tif u:\n\t\t\treturn u\t\t\n\n#check unauthorized post\nclass APIDatabase(ndb.Model):\n\tapi_id = ndb.IntegerProperty(required=True)\n\tapi_key = ndb.StringProperty(required=True)\n\n\t@classmethod\n\tdef add_new_key(cls,api_id,api_key):\n\t\treturn APIDatabase(api_id = api_id, api_key = api_key)\n\t\nclass Step(ndb.Model):\n\tstartTurn = ndb.IntegerProperty()\n\tendTurn = ndb.IntegerProperty()\n\tsolType = ndb.StringProperty()\n\tcost = ndb.IntegerProperty()\n\tfromCity = ndb.IntegerProperty()\n\ttoCity = ndb.IntegerProperty()\n\tpathID = ndb.IntegerProperty()\n\tscore = ndb.IntegerProperty()\n\tai = ndb.IntegerProperty()\n\tci = ndb.IntegerProperty()\n\tii = ndb.IntegerProperty()\n\t\n\nclass WayPoints(ndb.Model):\n\twaypointsID = ndb.IntegerProperty()\t\n\t#just a graph\n\tstatus = ndb.StringProperty()\n\tmapID = ndb.IntegerProperty()\n\tplayerID = ndb.StringProperty()\n\tscore = ndb.IntegerProperty()\n\tstep = ndb.StructuredProperty(Step, repeated=True)\n\tsavedTurn = ndb.IntegerProperty()\n\tgraphStat = ndb.TextProperty()\n\nclass WaypointReport(ndb.Model):\n\twaypointID = ndb.IntegerProperty(required=True)\n\tplay_by = ndb.StringProperty(required=True)\n\tscore = ndb.IntegerProperty(required=True)\n\ttotal_turn = ndb.IntegerProperty(required=True)\n\ttotal_impact = ndb.IntegerProperty(required=True)\n\t# query without exhausted joining\n\tgraph_id = ndb.IntegerProperty(required=True)\n\towner_id = ndb.IntegerProperty(required=True)\n\tplay_count = ndb.IntegerProperty(default=0)\n\tmaximum_impact = ndb.FloatProperty(required=True)\n\t#newly add \n\t#status = ndb.StringProperty(required=True)\n\t@classmethod\n\tdef add_new_waypoint_report(cls,waypointID,play_by,score,total_turn,total_impact,owner_id,graph_id,maximum_impact,status):\n\t\treturn WaypointReport(\twaypointID = waypointID, \n\t\t\t\t\t\t\t\tplay_by = play_by,\n\t\t\t\t\t\t\t\tscore = score,\n\t\t\t\t\t\t\t\ttotal_turn = total_turn,\n\t\t\t\t\t\t\t\ttotal_impact = total_impact,\n\t\t\t\t\t\t\t\tgraph_id = graph_id,\n\t\t\t\t\t\t\t\towner_id = owner_id,\n\t\t\t\t\t\t\t\tplay_count = 1,\n\t\t\t\t\t\t\t\tmaximum_impact = maximum_impact )\n\nclass MapReport(ndb.Model):\n\tmapID = ndb.IntegerProperty(required=True)\n\t# map name doesn't exist?\n\t#map_name = ndb.IntegerProperty(required=True)\n\tplay_count = ndb.IntegerProperty()\n\tscore = ndb.IntegerProperty()\n\tavg_score = ndb.FloatProperty()\n\ttotal_turn = ndb.IntegerProperty()\n\tavg_total_turn = ndb.FloatProperty()\n\ttotal_impact = ndb.IntegerProperty()\n\n\ttop_score = ndb.IntegerProperty(default=0)\n\n\tavg_total_impact = ndb.FloatProperty()\n\tmaximum_impact = ndb.FloatProperty()\n\t# query without exhausted joining\n\tgraph_id = ndb.IntegerProperty(required=True)\n\towner_id = ndb.IntegerProperty(required=True)\n\n\t@classmethod\n\tdef add_new_map_report(cls,mapID,play_count,score,avg_score,total_turn,avg_total_turn,total_impact,avg_total_impact,owner_id,graph_id,maximum_impact):\n\t\treturn MapReport(\tmapID = mapID, \n\t\t\t\t\t\t\t\tplay_count = play_count,\n\t\t\t\t\t\t\t\tscore = score,\n\t\t\t\t\t\t\t\tavg_score = avg_score,\n\t\t\t\t\t\t\t\ttotal_turn = total_turn,\n\t\t\t\t\t\t\t\tavg_total_turn = avg_total_turn,\n\t\t\t\t\t\t\t\ttotal_impact = total_impact,\n\t\t\t\t\t\t\t\tavg_total_impact = avg_total_impact,\n\t\t\t\t\t\t\t\tgraph_id = graph_id,\n\t\t\t\t\t\t\t\towner_id = owner_id,\n\t\t\t\t\t\t\t\tmaximum_impact = maximum_impact)\n\nclass PathReport(ndb.Model):\n\tmapID = ndb.IntegerProperty(required=True)\n\tgraph_id = ndb.IntegerProperty(required=True)\n\towner_id = ndb.IntegerProperty(required=True)\n\tpathID = ndb.IntegerProperty(required=True)\n\tsrcMachine = ndb.StringProperty()\n\tdstMachine = ndb.StringProperty()\n\tsrcService = ndb.StringProperty()\n\tdstService = ndb.StringProperty()\n\t### what for ???\n\tai = ndb.IntegerProperty(required=True)\n\tii = ndb.IntegerProperty(required=True)\n\tci = ndb.IntegerProperty(required=True)\n\t### newly added\n\tav = ndb.IntegerProperty(required=True)\n\tac = ndb.IntegerProperty(required=True)\n\tau = ndb.IntegerProperty(required=True)\n\tcounting = ndb.IntegerProperty(default=0)\n\tname = ndb.StringProperty()\n\n\t@classmethod\n\tdef add_new_path_report(cls,mapID,graph_id,owner_id,pathID,srcM,dstM,srcS,dstS,ai,ii,ci,av,ac,au,counting):\n\t\treturn PathReport(\n\t\t\tmapID=mapID,\n\t\t\tgraph_id=graph_id,\n\t\t\towner_id=owner_id,\n\t\t\tpathID=pathID,\n\t\t\tsrcMachine=srcM,\n\t\t\tdstMachine=dstM,\n\t\t\tsrcService=srcS,\n\t\t\tdstService=dstS,\n\t\t\tai=ai,ii=ii,ci=ci,\n\t\t\tav=av,au=au,ac=ac,\n\t\t\tcounting=counting\n\t\t)\n\nclass Solution(ndb.Model):\n\tcve_id = ndb.StringProperty(required=True)\n\tcwe_name = ndb.StringProperty(required=True)\n\tfrom_map = ndb.IntegerProperty(required=True)\n\tcounting = ndb.IntegerProperty(default=0)\n\n\t@classmethod\n\tdef add_new_solution(cls,solution_id,cve_id,cwe_name,from_map):\n\t\treturn Solution( solution_id=solution_id,cve_id=cve_id,cwe_name=cwe_name,from_map=from_map,counting=1)\n\nclass SolTypeReport(ndb.Model):\n\towner_id = ndb.IntegerProperty(required=True)\n\tmapID = ndb.IntegerProperty(required=True)\n\tcve_id = ndb.StringProperty(required=True)\n\tservice_name = ndb.StringProperty()\n\tsolType_impact = ndb.IntegerProperty()\n\tcwe_name = ndb.StringProperty(required=True)\n\tcounting = ndb.IntegerProperty(default=0)\n\tavg_hit = ndb.FloatProperty(default=1)\n\t@classmethod\n\tdef add_new_soltype(cls,owner_id,mapID,cve_id,cwe_name,service_name,solType_impact):\n\t\treturn SolTypeReport( \towner_id = owner_id, \n\t\t\t\t\t\t\t\tmapID = mapID,\n\t\t\t\t\t\t\t\tcve_id = cve_id,\n\t\t\t\t\t\t\t\tcwe_name = cwe_name,\n\t\t\t\t\t\t\t\tcounting = 1,\n\t\t\t\t\t\t\t\tservice_name = service_name,\n\t\t\t\t\t\t\t\tsolType_impact = solType_impact)",
"step-ids": [
38,
45,
49,
52,
53
]
}
|
[
38,
45,
49,
52,
53
] |
<|reserved_special_token_0|>
class Motorcycle(GroundVehicle):
pass
class FlightVehicle(Vehicle):
pass
class Starship(FlightVehicle):
pass
class Airplane(FlightVehicle):
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class GroundVehicle(Vehicle):
pass
class Car(GroundVehicle):
pass
class Motorcycle(GroundVehicle):
pass
class FlightVehicle(Vehicle):
pass
class Starship(FlightVehicle):
pass
class Airplane(FlightVehicle):
pass
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Vehicle(ABC):
pass
class GroundVehicle(Vehicle):
pass
class Car(GroundVehicle):
pass
class Motorcycle(GroundVehicle):
pass
class FlightVehicle(Vehicle):
pass
class Starship(FlightVehicle):
pass
class Airplane(FlightVehicle):
pass
<|reserved_special_token_1|>
from abc import ABC
class Vehicle(ABC):
pass
class GroundVehicle(Vehicle):
pass
class Car(GroundVehicle):
pass
class Motorcycle(GroundVehicle):
pass
class FlightVehicle(Vehicle):
pass
class Starship(FlightVehicle):
pass
class Airplane(FlightVehicle):
pass
<|reserved_special_token_1|>
from abc import ABC
# This is base class
class Vehicle(ABC):
pass
# GroundVehicle inherits from Vehicle
class GroundVehicle(Vehicle):
pass
# Car inherits from GroundVehicle
class Car(GroundVehicle):
pass
# Motorcycle inherits from GroundVehicle
class Motorcycle(GroundVehicle):
pass
# FlightVehicle inherits from Vehicle
class FlightVehicle(Vehicle):
pass
# Starship inherits from FlightVehicle
class Starship(FlightVehicle):
pass
# Airplane inherits from FlightVehicle
class Airplane(FlightVehicle):
pass
|
flexible
|
{
"blob_id": "d7db617131bf6e72c7aa808030f7286ddb609cc2",
"index": 4579,
"step-1": "<mask token>\n\n\nclass Motorcycle(GroundVehicle):\n pass\n\n\nclass FlightVehicle(Vehicle):\n pass\n\n\nclass Starship(FlightVehicle):\n pass\n\n\nclass Airplane(FlightVehicle):\n pass\n",
"step-2": "<mask token>\n\n\nclass GroundVehicle(Vehicle):\n pass\n\n\nclass Car(GroundVehicle):\n pass\n\n\nclass Motorcycle(GroundVehicle):\n pass\n\n\nclass FlightVehicle(Vehicle):\n pass\n\n\nclass Starship(FlightVehicle):\n pass\n\n\nclass Airplane(FlightVehicle):\n pass\n",
"step-3": "<mask token>\n\n\nclass Vehicle(ABC):\n pass\n\n\nclass GroundVehicle(Vehicle):\n pass\n\n\nclass Car(GroundVehicle):\n pass\n\n\nclass Motorcycle(GroundVehicle):\n pass\n\n\nclass FlightVehicle(Vehicle):\n pass\n\n\nclass Starship(FlightVehicle):\n pass\n\n\nclass Airplane(FlightVehicle):\n pass\n",
"step-4": "from abc import ABC\n\n\nclass Vehicle(ABC):\n pass\n\n\nclass GroundVehicle(Vehicle):\n pass\n\n\nclass Car(GroundVehicle):\n pass\n\n\nclass Motorcycle(GroundVehicle):\n pass\n\n\nclass FlightVehicle(Vehicle):\n pass\n\n\nclass Starship(FlightVehicle):\n pass\n\n\nclass Airplane(FlightVehicle):\n pass\n",
"step-5": "from abc import ABC\n\n# This is base class\nclass Vehicle(ABC):\n pass\n\n# GroundVehicle inherits from Vehicle\nclass GroundVehicle(Vehicle):\n pass\n\n# Car inherits from GroundVehicle\nclass Car(GroundVehicle):\n pass\n\n# Motorcycle inherits from GroundVehicle\nclass Motorcycle(GroundVehicle):\n pass\n\n# FlightVehicle inherits from Vehicle\nclass FlightVehicle(Vehicle):\n pass\n\n# Starship inherits from FlightVehicle\nclass Starship(FlightVehicle):\n pass\n\n# Airplane inherits from FlightVehicle\nclass Airplane(FlightVehicle):\n pass\n",
"step-ids": [
4,
6,
7,
8,
9
]
}
|
[
4,
6,
7,
8,
9
] |
import numpy as np
def get_train_batches(data_dir='/home/yunhan/batchified'):
"""
return a list or generator of (large) ndarrays,
in order to efficiently utilize GPU
"""
# todo: read in data that is preoprocessed
# Use batch 1 - 52 as train (60%), 53 - 71 as validation (20%), 72 - 89 as test (20%)
n = 53
idx = np.random.permutation(n)
idx = idx + 1
for i in range(n):
X = np.load("%s/X%d.npy" % (data_dir, idx[i]))/255.
Y = np.load("%s/y%d.npy" % (data_dir, idx[i])).reshape(-1)
yield X, Y
def get_evaluate_batches(data_dir='/home/yunhan/batchified'):
"""
return a list or generator of (large) ndarrays,
in order to efficiently utilize GPU
"""
# train 3 valid 1
# Use batch 1 - 53 as train (60%), 54 - 71 as validation (20%), 72 - 89 as test (20%)
n = 18
idx = np.random.permutation(n)
idx = idx + 54
for i in range(n):
X = np.load("%s/X%d.npy" % (data_dir, idx[i]))/255.
Y = np.load("%s/y%d.npy" % (data_dir, idx[i])).reshape(-1)
yield X, Y
def get_test_batches(data_dir='/home/yunhan/batchified'):
"""
return a list or generator of (large) ndarrays,
in order to efficiently utilize GPU
"""
# train 3 valid 1
# Use batch 1 - 53 as train (60%), 54 - 71 as validation (20%), 72 - 89 as test (20%)
n = 18
idx = np.random.permutation(n)
idx = idx + 72
for i in range(n):
X = np.load("%s/X%d.npy" % (data_dir, idx[i]))/255.
Y = np.load("%s/y%d.npy" % (data_dir, idx[i])).reshape(-1)
yield X, Y
def get_batches_mono(data_dir):
"""
return a list or generator of (large) ndarrays,
in order to efficiently utilize GPU
"""
X = np.load('/home/yunhan/data_dir/train_x_224.npy')
# X = np.load('train_x_sample.npy')
X = X / 255
# X = np.load('/home/yunhan/data_dir/train_x_224.npy')
Y = np.load('/home/yunhan/data_dir/train_y_224.npy')
# Y = np.load('train_y_sample.npy')
return [(X, Y, 32, 0.2), ]
def get_test_data_batches(data_dir='/home/yunhan/data_dir'):
for i in range(17):
X = np.load("%s/X_%d.npy" % (data_dir, 3000*(i+1)))/255.
yield X
|
normal
|
{
"blob_id": "c04c38d78144b6f5d3e5af4ebe9ce430e882a367",
"index": 8014,
"step-1": "<mask token>\n\n\ndef get_evaluate_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 54\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_test_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 72\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef get_evaluate_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 54\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_test_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 72\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_batches_mono(data_dir):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n X = np.load('/home/yunhan/data_dir/train_x_224.npy')\n X = X / 255\n Y = np.load('/home/yunhan/data_dir/train_y_224.npy')\n return [(X, Y, 32, 0.2)]\n\n\ndef get_test_data_batches(data_dir='/home/yunhan/data_dir'):\n for i in range(17):\n X = np.load('%s/X_%d.npy' % (data_dir, 3000 * (i + 1))) / 255.0\n yield X\n",
"step-3": "<mask token>\n\n\ndef get_train_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 53\n idx = np.random.permutation(n)\n idx = idx + 1\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_evaluate_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 54\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_test_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 72\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_batches_mono(data_dir):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n X = np.load('/home/yunhan/data_dir/train_x_224.npy')\n X = X / 255\n Y = np.load('/home/yunhan/data_dir/train_y_224.npy')\n return [(X, Y, 32, 0.2)]\n\n\ndef get_test_data_batches(data_dir='/home/yunhan/data_dir'):\n for i in range(17):\n X = np.load('%s/X_%d.npy' % (data_dir, 3000 * (i + 1))) / 255.0\n yield X\n",
"step-4": "import numpy as np\n\n\ndef get_train_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 53\n idx = np.random.permutation(n)\n idx = idx + 1\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_evaluate_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 54\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_test_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 72\n for i in range(n):\n X = np.load('%s/X%d.npy' % (data_dir, idx[i])) / 255.0\n Y = np.load('%s/y%d.npy' % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_batches_mono(data_dir):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n X = np.load('/home/yunhan/data_dir/train_x_224.npy')\n X = X / 255\n Y = np.load('/home/yunhan/data_dir/train_y_224.npy')\n return [(X, Y, 32, 0.2)]\n\n\ndef get_test_data_batches(data_dir='/home/yunhan/data_dir'):\n for i in range(17):\n X = np.load('%s/X_%d.npy' % (data_dir, 3000 * (i + 1))) / 255.0\n yield X\n",
"step-5": "import numpy as np\n\n\ndef get_train_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n # todo: read in data that is preoprocessed\n # Use batch 1 - 52 as train (60%), 53 - 71 as validation (20%), 72 - 89 as test (20%)\n n = 53\n idx = np.random.permutation(n)\n idx = idx + 1\n for i in range(n):\n X = np.load(\"%s/X%d.npy\" % (data_dir, idx[i]))/255.\n Y = np.load(\"%s/y%d.npy\" % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_evaluate_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n # train 3 valid 1\n # Use batch 1 - 53 as train (60%), 54 - 71 as validation (20%), 72 - 89 as test (20%)\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 54\n for i in range(n):\n X = np.load(\"%s/X%d.npy\" % (data_dir, idx[i]))/255.\n Y = np.load(\"%s/y%d.npy\" % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_test_batches(data_dir='/home/yunhan/batchified'):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n # train 3 valid 1\n # Use batch 1 - 53 as train (60%), 54 - 71 as validation (20%), 72 - 89 as test (20%)\n n = 18\n idx = np.random.permutation(n)\n idx = idx + 72\n for i in range(n):\n X = np.load(\"%s/X%d.npy\" % (data_dir, idx[i]))/255.\n Y = np.load(\"%s/y%d.npy\" % (data_dir, idx[i])).reshape(-1)\n yield X, Y\n\n\ndef get_batches_mono(data_dir):\n \"\"\"\n return a list or generator of (large) ndarrays,\n in order to efficiently utilize GPU\n \"\"\"\n X = np.load('/home/yunhan/data_dir/train_x_224.npy')\n # X = np.load('train_x_sample.npy')\n X = X / 255\n # X = np.load('/home/yunhan/data_dir/train_x_224.npy')\n Y = np.load('/home/yunhan/data_dir/train_y_224.npy')\n # Y = np.load('train_y_sample.npy')\n return [(X, Y, 32, 0.2), ]\n\n\ndef get_test_data_batches(data_dir='/home/yunhan/data_dir'):\n for i in range(17):\n X = np.load(\"%s/X_%d.npy\" % (data_dir, 3000*(i+1)))/255.\n yield X\n",
"step-ids": [
2,
4,
5,
6,
7
]
}
|
[
2,
4,
5,
6,
7
] |
import tkinter as tk
from tkinter import ttk
win = tk.Tk()
win.title('Loop')
############ Time consuming :
# nameLable1 = ttk.Label(win,text="Enter your name : ")
# nameLable1.grid(row=0,column=0,sticky=tk.W)
# ageLable1 = ttk.Label(win,text="Enter your age: ")
# ageLable1.grid(row=1,column=0,sticky=tk.W)
# countryLable1 = ttk.Label(win,text="Enter your country: ")
# countryLable1.grid(row=2,column=0,sticky=tk.W)
# mailLable1 = ttk.Label(win,text="Enter your mail ID : ")
# mailLable1.grid(row=3,column=0,sticky=tk.W)
############ Loop :
labels = [f"name : ","age : ","mail ID : ","city : " ,"country : ","phone number : "]
for i in range(len(labels)):
# currentLabel = f"label{i}" # without declaring also it will work fine
currentLabel = ttk.Label(win,text=labels[i])
currentLabel.grid(row=i,column=0,sticky=tk.W)
userDict = {
'name':tk.StringVar(),
'age':tk.StringVar(),
'mail':tk.StringVar(),
'city':tk.StringVar(),
'country':tk.StringVar(),
'phone':tk.StringVar(),
}
index = 0
for i in userDict:
# currentEntryBox = f"entry{i}"
currentEntryBox = ttk.Entry(win,width = 16,textvariable = userDict[i])
currentEntryBox.grid(row = index,column = 1)
index+=1
def submitAction():
for i in userDict:
# print(f"{userDict[i].get()}")
print(f"{userDict.get(i).get()}") # their is get() method in dictionary too
exit()
submitButton = tk.Button(win,text="Submit",command = submitAction)
submitButton.grid(row = index,column = 0)
submitButton.configure(foreground = "#ffffff",background = "#000000")
################################################
win.mainloop()
###########################################################################################################
##########################################################################################################
|
normal
|
{
"blob_id": "2eb49d08136c3540e1305310f03255e2ecbf0c40",
"index": 3175,
"step-1": "<mask token>\n\n\ndef submitAction():\n for i in userDict:\n print(f'{userDict.get(i).get()}')\n exit()\n\n\n<mask token>\n",
"step-2": "<mask token>\nwin.title('Loop')\n<mask token>\nfor i in range(len(labels)):\n currentLabel = ttk.Label(win, text=labels[i])\n currentLabel.grid(row=i, column=0, sticky=tk.W)\n<mask token>\nfor i in userDict:\n currentEntryBox = ttk.Entry(win, width=16, textvariable=userDict[i])\n currentEntryBox.grid(row=index, column=1)\n index += 1\n\n\ndef submitAction():\n for i in userDict:\n print(f'{userDict.get(i).get()}')\n exit()\n\n\n<mask token>\nsubmitButton.grid(row=index, column=0)\nsubmitButton.configure(foreground='#ffffff', background='#000000')\nwin.mainloop()\n",
"step-3": "<mask token>\nwin = tk.Tk()\nwin.title('Loop')\nlabels = [f'name : ', 'age : ', 'mail ID : ', 'city : ', 'country : ',\n 'phone number : ']\nfor i in range(len(labels)):\n currentLabel = ttk.Label(win, text=labels[i])\n currentLabel.grid(row=i, column=0, sticky=tk.W)\nuserDict = {'name': tk.StringVar(), 'age': tk.StringVar(), 'mail': tk.\n StringVar(), 'city': tk.StringVar(), 'country': tk.StringVar(), 'phone':\n tk.StringVar()}\nindex = 0\nfor i in userDict:\n currentEntryBox = ttk.Entry(win, width=16, textvariable=userDict[i])\n currentEntryBox.grid(row=index, column=1)\n index += 1\n\n\ndef submitAction():\n for i in userDict:\n print(f'{userDict.get(i).get()}')\n exit()\n\n\nsubmitButton = tk.Button(win, text='Submit', command=submitAction)\nsubmitButton.grid(row=index, column=0)\nsubmitButton.configure(foreground='#ffffff', background='#000000')\nwin.mainloop()\n",
"step-4": "import tkinter as tk\nfrom tkinter import ttk\nwin = tk.Tk()\nwin.title('Loop')\nlabels = [f'name : ', 'age : ', 'mail ID : ', 'city : ', 'country : ',\n 'phone number : ']\nfor i in range(len(labels)):\n currentLabel = ttk.Label(win, text=labels[i])\n currentLabel.grid(row=i, column=0, sticky=tk.W)\nuserDict = {'name': tk.StringVar(), 'age': tk.StringVar(), 'mail': tk.\n StringVar(), 'city': tk.StringVar(), 'country': tk.StringVar(), 'phone':\n tk.StringVar()}\nindex = 0\nfor i in userDict:\n currentEntryBox = ttk.Entry(win, width=16, textvariable=userDict[i])\n currentEntryBox.grid(row=index, column=1)\n index += 1\n\n\ndef submitAction():\n for i in userDict:\n print(f'{userDict.get(i).get()}')\n exit()\n\n\nsubmitButton = tk.Button(win, text='Submit', command=submitAction)\nsubmitButton.grid(row=index, column=0)\nsubmitButton.configure(foreground='#ffffff', background='#000000')\nwin.mainloop()\n",
"step-5": "import tkinter as tk\nfrom tkinter import ttk\n\n\nwin = tk.Tk()\n\nwin.title('Loop')\n\n\n############ Time consuming :\n\n# nameLable1 = ttk.Label(win,text=\"Enter your name : \") \n# nameLable1.grid(row=0,column=0,sticky=tk.W) \n\n# ageLable1 = ttk.Label(win,text=\"Enter your age: \") \n# ageLable1.grid(row=1,column=0,sticky=tk.W) \n\n# countryLable1 = ttk.Label(win,text=\"Enter your country: \") \n# countryLable1.grid(row=2,column=0,sticky=tk.W)\n\n# mailLable1 = ttk.Label(win,text=\"Enter your mail ID : \") \n# mailLable1.grid(row=3,column=0,sticky=tk.W) \n\n\n############ Loop :\n\n\nlabels = [f\"name : \",\"age : \",\"mail ID : \",\"city : \" ,\"country : \",\"phone number : \"]\n\nfor i in range(len(labels)):\n # currentLabel = f\"label{i}\" # without declaring also it will work fine\n currentLabel = ttk.Label(win,text=labels[i]) \n currentLabel.grid(row=i,column=0,sticky=tk.W) \n\nuserDict = {\n 'name':tk.StringVar(),\n 'age':tk.StringVar(),\n 'mail':tk.StringVar(),\n 'city':tk.StringVar(),\n 'country':tk.StringVar(),\n 'phone':tk.StringVar(),\n}\n\nindex = 0\n\nfor i in userDict:\n # currentEntryBox = f\"entry{i}\"\n currentEntryBox = ttk.Entry(win,width = 16,textvariable = userDict[i])\n currentEntryBox.grid(row = index,column = 1)\n index+=1\n\ndef submitAction():\n for i in userDict:\n # print(f\"{userDict[i].get()}\")\n print(f\"{userDict.get(i).get()}\") # their is get() method in dictionary too\n exit()\n\n\nsubmitButton = tk.Button(win,text=\"Submit\",command = submitAction)\nsubmitButton.grid(row = index,column = 0)\nsubmitButton.configure(foreground = \"#ffffff\",background = \"#000000\")\n\n################################################\n\nwin.mainloop()\n\n\n###########################################################################################################\n##########################################################################################################",
"step-ids": [
1,
2,
3,
4,
5
]
}
|
[
1,
2,
3,
4,
5
] |
"""
Tests for the Transformer RNNCell.
"""
import pytest
import numpy as np
import tensorflow as tf
from .transformer import positional_encoding, transformer_layer
from .cell import (LimitedTransformerCell, UnlimitedTransformerCell,
inject_at_timestep, sequence_masks)
def test_inject_at_timestep():
with tf.Graph().as_default():
with tf.Session() as sess:
in_seq = tf.constant(np.array([
[
[1, 2, 3, 4],
[5, 6, 7, 8],
],
[
[9, 10, 11, 12],
[13, 14, 15, 16],
],
[
[17, 18, 19, 20],
[21, 22, 23, 24],
],
], dtype='float32'))
injection = tf.constant(np.array([
[-1, -2, -3, -4],
[-5, -6, -7, -8],
[-9, -10, -11, -12],
], dtype='float32'))
indices = np.array([0, 1, 0], dtype='int32')
injected = sess.run(inject_at_timestep(indices, in_seq, injection))
expected = np.array([
[
[-1, -2, -3, -4],
[5, 6, 7, 8],
],
[
[9, 10, 11, 12],
[-5, -6, -7, -8],
],
[
[-9, -10, -11, -12],
[21, 22, 23, 24],
],
], dtype='float32')
assert (injected == expected).all()
def test_sequence_masks():
with tf.Graph().as_default():
with tf.Session() as sess:
indices = tf.constant(np.array([3, 1, 2], dtype='int32'))
actual = sess.run(sequence_masks(indices, tf.constant(4, dtype=tf.int32), tf.float32))
expected = np.array([
[0, 0, 0, 0],
[0, 0, -np.inf, -np.inf],
[0, 0, 0, -np.inf],
], dtype='float32')
assert (actual == expected).all()
@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell, UnlimitedTransformerCell])
@pytest.mark.parametrize('num_layers', [1, 2, 6])
def test_basic_equivalence(cell_cls, num_layers):
"""
Test that both transformer implementations produce the
same outputs when applied to a properly-sized
sequence.
"""
with tf.Graph().as_default():
with tf.Session() as sess:
pos_enc = positional_encoding(4, 6, dtype=tf.float64)
in_seq = tf.get_variable('in_seq',
shape=(3, 4, 6),
initializer=tf.truncated_normal_initializer(),
dtype=tf.float64)
cell = cell_cls(pos_enc, num_layers=num_layers, num_heads=2, hidden=24)
actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)
with tf.variable_scope('rnn', reuse=True):
with tf.variable_scope('transformer', reuse=True):
expected = in_seq + pos_enc
for _ in range(num_layers):
expected = transformer_layer(expected, num_heads=2, hidden=24)
sess.run(tf.global_variables_initializer())
actual, expected = sess.run((actual, expected))
assert not np.isnan(actual).any()
assert not np.isnan(expected).any()
assert actual.shape == expected.shape
assert np.allclose(actual, expected)
@pytest.mark.parametrize('cell_cls', [UnlimitedTransformerCell])
def test_past_horizon(cell_cls):
"""
Test the cell when the input sequence is longer than
the time horizon.
"""
with tf.Graph().as_default():
with tf.Session() as sess:
pos_enc = positional_encoding(4, 6, dtype=tf.float64)
in_seq = tf.get_variable('in_seq',
shape=(3, 5, 6),
initializer=tf.truncated_normal_initializer(),
dtype=tf.float64)
cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)
actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)
def apply_regular(sequence):
with tf.variable_scope('rnn', reuse=True):
with tf.variable_scope('transformer', reuse=True):
expected = sequence + pos_enc
for _ in range(3):
expected = transformer_layer(expected, num_heads=2, hidden=24)
return expected
expected = tf.concat([apply_regular(in_seq[:, :-1]),
apply_regular(in_seq[:, 1:])[:, -1:]], axis=1)
sess.run(tf.global_variables_initializer())
actual, expected = sess.run((actual, expected))
assert not np.isnan(actual).any()
assert not np.isnan(expected).any()
assert actual.shape == expected.shape
assert np.allclose(actual, expected)
@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell, UnlimitedTransformerCell])
def test_mismatched_starts(cell_cls):
"""
Test the cell when the states are split up and
recombined from different timesteps.
"""
with tf.Graph().as_default():
with tf.Session() as sess:
pos_enc = positional_encoding(5, 6, dtype=tf.float64)
in_seq = tf.get_variable('in_seq',
shape=(3, 5, 6),
initializer=tf.truncated_normal_initializer(),
dtype=tf.float64)
cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)
_, states_1 = tf.nn.dynamic_rnn(cell, in_seq[:, :1], dtype=tf.float64)
_, states_2 = tf.nn.dynamic_rnn(cell, in_seq[:, :2], dtype=tf.float64)
_, states_3 = tf.nn.dynamic_rnn(cell, in_seq[:, :3], dtype=tf.float64)
new_states = tuple(tf.stack([s2[0], s3[1], s1[2]], axis=0)
for s1, s2, s3 in zip(states_1, states_2, states_3))
full_seq, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)
expected = tf.stack([full_seq[0, 2:4], full_seq[1, 3:5], full_seq[2, 1:3]], axis=0)
inputs = tf.stack([in_seq[0, 2:4], in_seq[1, 3:5], in_seq[2, 1:3]], axis=0)
actual, _ = tf.nn.dynamic_rnn(cell, inputs, initial_state=new_states)
sess.run(tf.global_variables_initializer())
actual, expected = sess.run((actual, expected))
assert not np.isnan(actual).any()
assert not np.isnan(expected).any()
assert actual.shape == expected.shape
assert np.allclose(actual, expected)
|
normal
|
{
"blob_id": "958f6e539f9f68892d77b6becc387581c6adfa16",
"index": 3366,
"step-1": "<mask token>\n\n\ndef test_inject_at_timestep():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n in_seq = tf.constant(np.array([[[1, 2, 3, 4], [5, 6, 7, 8]], [[\n 9, 10, 11, 12], [13, 14, 15, 16]], [[17, 18, 19, 20], [21, \n 22, 23, 24]]], dtype='float32'))\n injection = tf.constant(np.array([[-1, -2, -3, -4], [-5, -6, -7,\n -8], [-9, -10, -11, -12]], dtype='float32'))\n indices = np.array([0, 1, 0], dtype='int32')\n injected = sess.run(inject_at_timestep(indices, in_seq, injection))\n expected = np.array([[[-1, -2, -3, -4], [5, 6, 7, 8]], [[9, 10,\n 11, 12], [-5, -6, -7, -8]], [[-9, -10, -11, -12], [21, 22, \n 23, 24]]], dtype='float32')\n assert (injected == expected).all()\n\n\ndef test_sequence_masks():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n indices = tf.constant(np.array([3, 1, 2], dtype='int32'))\n actual = sess.run(sequence_masks(indices, tf.constant(4, dtype=\n tf.int32), tf.float32))\n expected = np.array([[0, 0, 0, 0], [0, 0, -np.inf, -np.inf], [0,\n 0, 0, -np.inf]], dtype='float32')\n assert (actual == expected).all()\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell,\n UnlimitedTransformerCell])\n@pytest.mark.parametrize('num_layers', [1, 2, 6])\ndef test_basic_equivalence(cell_cls, num_layers):\n \"\"\"\n Test that both transformer implementations produce the\n same outputs when applied to a properly-sized\n sequence.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 4, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=num_layers, num_heads=2,\n hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = in_seq + pos_enc\n for _ in range(num_layers):\n expected = transformer_layer(expected, num_heads=2,\n hidden=24)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n<mask token>\n",
"step-2": "<mask token>\n\n\ndef test_inject_at_timestep():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n in_seq = tf.constant(np.array([[[1, 2, 3, 4], [5, 6, 7, 8]], [[\n 9, 10, 11, 12], [13, 14, 15, 16]], [[17, 18, 19, 20], [21, \n 22, 23, 24]]], dtype='float32'))\n injection = tf.constant(np.array([[-1, -2, -3, -4], [-5, -6, -7,\n -8], [-9, -10, -11, -12]], dtype='float32'))\n indices = np.array([0, 1, 0], dtype='int32')\n injected = sess.run(inject_at_timestep(indices, in_seq, injection))\n expected = np.array([[[-1, -2, -3, -4], [5, 6, 7, 8]], [[9, 10,\n 11, 12], [-5, -6, -7, -8]], [[-9, -10, -11, -12], [21, 22, \n 23, 24]]], dtype='float32')\n assert (injected == expected).all()\n\n\ndef test_sequence_masks():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n indices = tf.constant(np.array([3, 1, 2], dtype='int32'))\n actual = sess.run(sequence_masks(indices, tf.constant(4, dtype=\n tf.int32), tf.float32))\n expected = np.array([[0, 0, 0, 0], [0, 0, -np.inf, -np.inf], [0,\n 0, 0, -np.inf]], dtype='float32')\n assert (actual == expected).all()\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell,\n UnlimitedTransformerCell])\n@pytest.mark.parametrize('num_layers', [1, 2, 6])\ndef test_basic_equivalence(cell_cls, num_layers):\n \"\"\"\n Test that both transformer implementations produce the\n same outputs when applied to a properly-sized\n sequence.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 4, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=num_layers, num_heads=2,\n hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = in_seq + pos_enc\n for _ in range(num_layers):\n expected = transformer_layer(expected, num_heads=2,\n hidden=24)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [UnlimitedTransformerCell])\ndef test_past_horizon(cell_cls):\n \"\"\"\n Test the cell when the input sequence is longer than\n the time horizon.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 5, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n\n def apply_regular(sequence):\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = sequence + pos_enc\n for _ in range(3):\n expected = transformer_layer(expected,\n num_heads=2, hidden=24)\n return expected\n expected = tf.concat([apply_regular(in_seq[:, :-1]),\n apply_regular(in_seq[:, 1:])[:, -1:]], axis=1)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n<mask token>\n",
"step-3": "<mask token>\n\n\ndef test_inject_at_timestep():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n in_seq = tf.constant(np.array([[[1, 2, 3, 4], [5, 6, 7, 8]], [[\n 9, 10, 11, 12], [13, 14, 15, 16]], [[17, 18, 19, 20], [21, \n 22, 23, 24]]], dtype='float32'))\n injection = tf.constant(np.array([[-1, -2, -3, -4], [-5, -6, -7,\n -8], [-9, -10, -11, -12]], dtype='float32'))\n indices = np.array([0, 1, 0], dtype='int32')\n injected = sess.run(inject_at_timestep(indices, in_seq, injection))\n expected = np.array([[[-1, -2, -3, -4], [5, 6, 7, 8]], [[9, 10,\n 11, 12], [-5, -6, -7, -8]], [[-9, -10, -11, -12], [21, 22, \n 23, 24]]], dtype='float32')\n assert (injected == expected).all()\n\n\ndef test_sequence_masks():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n indices = tf.constant(np.array([3, 1, 2], dtype='int32'))\n actual = sess.run(sequence_masks(indices, tf.constant(4, dtype=\n tf.int32), tf.float32))\n expected = np.array([[0, 0, 0, 0], [0, 0, -np.inf, -np.inf], [0,\n 0, 0, -np.inf]], dtype='float32')\n assert (actual == expected).all()\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell,\n UnlimitedTransformerCell])\n@pytest.mark.parametrize('num_layers', [1, 2, 6])\ndef test_basic_equivalence(cell_cls, num_layers):\n \"\"\"\n Test that both transformer implementations produce the\n same outputs when applied to a properly-sized\n sequence.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 4, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=num_layers, num_heads=2,\n hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = in_seq + pos_enc\n for _ in range(num_layers):\n expected = transformer_layer(expected, num_heads=2,\n hidden=24)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [UnlimitedTransformerCell])\ndef test_past_horizon(cell_cls):\n \"\"\"\n Test the cell when the input sequence is longer than\n the time horizon.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 5, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n\n def apply_regular(sequence):\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = sequence + pos_enc\n for _ in range(3):\n expected = transformer_layer(expected,\n num_heads=2, hidden=24)\n return expected\n expected = tf.concat([apply_regular(in_seq[:, :-1]),\n apply_regular(in_seq[:, 1:])[:, -1:]], axis=1)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell,\n UnlimitedTransformerCell])\ndef test_mismatched_starts(cell_cls):\n \"\"\"\n Test the cell when the states are split up and\n recombined from different timesteps.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(5, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 5, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n _, states_1 = tf.nn.dynamic_rnn(cell, in_seq[:, :1], dtype=tf.\n float64)\n _, states_2 = tf.nn.dynamic_rnn(cell, in_seq[:, :2], dtype=tf.\n float64)\n _, states_3 = tf.nn.dynamic_rnn(cell, in_seq[:, :3], dtype=tf.\n float64)\n new_states = tuple(tf.stack([s2[0], s3[1], s1[2]], axis=0) for \n s1, s2, s3 in zip(states_1, states_2, states_3))\n full_seq, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n expected = tf.stack([full_seq[0, 2:4], full_seq[1, 3:5],\n full_seq[2, 1:3]], axis=0)\n inputs = tf.stack([in_seq[0, 2:4], in_seq[1, 3:5], in_seq[2, 1:\n 3]], axis=0)\n actual, _ = tf.nn.dynamic_rnn(cell, inputs, initial_state=\n new_states)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n",
"step-4": "<mask token>\nimport pytest\nimport numpy as np\nimport tensorflow as tf\nfrom .transformer import positional_encoding, transformer_layer\nfrom .cell import LimitedTransformerCell, UnlimitedTransformerCell, inject_at_timestep, sequence_masks\n\n\ndef test_inject_at_timestep():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n in_seq = tf.constant(np.array([[[1, 2, 3, 4], [5, 6, 7, 8]], [[\n 9, 10, 11, 12], [13, 14, 15, 16]], [[17, 18, 19, 20], [21, \n 22, 23, 24]]], dtype='float32'))\n injection = tf.constant(np.array([[-1, -2, -3, -4], [-5, -6, -7,\n -8], [-9, -10, -11, -12]], dtype='float32'))\n indices = np.array([0, 1, 0], dtype='int32')\n injected = sess.run(inject_at_timestep(indices, in_seq, injection))\n expected = np.array([[[-1, -2, -3, -4], [5, 6, 7, 8]], [[9, 10,\n 11, 12], [-5, -6, -7, -8]], [[-9, -10, -11, -12], [21, 22, \n 23, 24]]], dtype='float32')\n assert (injected == expected).all()\n\n\ndef test_sequence_masks():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n indices = tf.constant(np.array([3, 1, 2], dtype='int32'))\n actual = sess.run(sequence_masks(indices, tf.constant(4, dtype=\n tf.int32), tf.float32))\n expected = np.array([[0, 0, 0, 0], [0, 0, -np.inf, -np.inf], [0,\n 0, 0, -np.inf]], dtype='float32')\n assert (actual == expected).all()\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell,\n UnlimitedTransformerCell])\n@pytest.mark.parametrize('num_layers', [1, 2, 6])\ndef test_basic_equivalence(cell_cls, num_layers):\n \"\"\"\n Test that both transformer implementations produce the\n same outputs when applied to a properly-sized\n sequence.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 4, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=num_layers, num_heads=2,\n hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = in_seq + pos_enc\n for _ in range(num_layers):\n expected = transformer_layer(expected, num_heads=2,\n hidden=24)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [UnlimitedTransformerCell])\ndef test_past_horizon(cell_cls):\n \"\"\"\n Test the cell when the input sequence is longer than\n the time horizon.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 5, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n\n def apply_regular(sequence):\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = sequence + pos_enc\n for _ in range(3):\n expected = transformer_layer(expected,\n num_heads=2, hidden=24)\n return expected\n expected = tf.concat([apply_regular(in_seq[:, :-1]),\n apply_regular(in_seq[:, 1:])[:, -1:]], axis=1)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell,\n UnlimitedTransformerCell])\ndef test_mismatched_starts(cell_cls):\n \"\"\"\n Test the cell when the states are split up and\n recombined from different timesteps.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(5, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq', shape=(3, 5, 6), initializer\n =tf.truncated_normal_initializer(), dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n _, states_1 = tf.nn.dynamic_rnn(cell, in_seq[:, :1], dtype=tf.\n float64)\n _, states_2 = tf.nn.dynamic_rnn(cell, in_seq[:, :2], dtype=tf.\n float64)\n _, states_3 = tf.nn.dynamic_rnn(cell, in_seq[:, :3], dtype=tf.\n float64)\n new_states = tuple(tf.stack([s2[0], s3[1], s1[2]], axis=0) for \n s1, s2, s3 in zip(states_1, states_2, states_3))\n full_seq, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n expected = tf.stack([full_seq[0, 2:4], full_seq[1, 3:5],\n full_seq[2, 1:3]], axis=0)\n inputs = tf.stack([in_seq[0, 2:4], in_seq[1, 3:5], in_seq[2, 1:\n 3]], axis=0)\n actual, _ = tf.nn.dynamic_rnn(cell, inputs, initial_state=\n new_states)\n sess.run(tf.global_variables_initializer())\n actual, expected = sess.run((actual, expected))\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n",
"step-5": "\"\"\"\nTests for the Transformer RNNCell.\n\"\"\"\n\nimport pytest\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom .transformer import positional_encoding, transformer_layer\nfrom .cell import (LimitedTransformerCell, UnlimitedTransformerCell,\n inject_at_timestep, sequence_masks)\n\n\ndef test_inject_at_timestep():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n in_seq = tf.constant(np.array([\n [\n [1, 2, 3, 4],\n [5, 6, 7, 8],\n ],\n [\n [9, 10, 11, 12],\n [13, 14, 15, 16],\n ],\n [\n [17, 18, 19, 20],\n [21, 22, 23, 24],\n ],\n ], dtype='float32'))\n injection = tf.constant(np.array([\n [-1, -2, -3, -4],\n [-5, -6, -7, -8],\n [-9, -10, -11, -12],\n ], dtype='float32'))\n\n indices = np.array([0, 1, 0], dtype='int32')\n injected = sess.run(inject_at_timestep(indices, in_seq, injection))\n\n expected = np.array([\n [\n [-1, -2, -3, -4],\n [5, 6, 7, 8],\n ],\n [\n [9, 10, 11, 12],\n [-5, -6, -7, -8],\n ],\n [\n [-9, -10, -11, -12],\n [21, 22, 23, 24],\n ],\n ], dtype='float32')\n assert (injected == expected).all()\n\n\ndef test_sequence_masks():\n with tf.Graph().as_default():\n with tf.Session() as sess:\n indices = tf.constant(np.array([3, 1, 2], dtype='int32'))\n actual = sess.run(sequence_masks(indices, tf.constant(4, dtype=tf.int32), tf.float32))\n expected = np.array([\n [0, 0, 0, 0],\n [0, 0, -np.inf, -np.inf],\n [0, 0, 0, -np.inf],\n ], dtype='float32')\n assert (actual == expected).all()\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell, UnlimitedTransformerCell])\n@pytest.mark.parametrize('num_layers', [1, 2, 6])\ndef test_basic_equivalence(cell_cls, num_layers):\n \"\"\"\n Test that both transformer implementations produce the\n same outputs when applied to a properly-sized\n sequence.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq',\n shape=(3, 4, 6),\n initializer=tf.truncated_normal_initializer(),\n dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=num_layers, num_heads=2, hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = in_seq + pos_enc\n for _ in range(num_layers):\n expected = transformer_layer(expected, num_heads=2, hidden=24)\n sess.run(tf.global_variables_initializer())\n\n actual, expected = sess.run((actual, expected))\n\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [UnlimitedTransformerCell])\ndef test_past_horizon(cell_cls):\n \"\"\"\n Test the cell when the input sequence is longer than\n the time horizon.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(4, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq',\n shape=(3, 5, 6),\n initializer=tf.truncated_normal_initializer(),\n dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n actual, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n\n def apply_regular(sequence):\n with tf.variable_scope('rnn', reuse=True):\n with tf.variable_scope('transformer', reuse=True):\n expected = sequence + pos_enc\n for _ in range(3):\n expected = transformer_layer(expected, num_heads=2, hidden=24)\n return expected\n expected = tf.concat([apply_regular(in_seq[:, :-1]),\n apply_regular(in_seq[:, 1:])[:, -1:]], axis=1)\n sess.run(tf.global_variables_initializer())\n\n actual, expected = sess.run((actual, expected))\n\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n\n\n@pytest.mark.parametrize('cell_cls', [LimitedTransformerCell, UnlimitedTransformerCell])\ndef test_mismatched_starts(cell_cls):\n \"\"\"\n Test the cell when the states are split up and\n recombined from different timesteps.\n \"\"\"\n with tf.Graph().as_default():\n with tf.Session() as sess:\n pos_enc = positional_encoding(5, 6, dtype=tf.float64)\n in_seq = tf.get_variable('in_seq',\n shape=(3, 5, 6),\n initializer=tf.truncated_normal_initializer(),\n dtype=tf.float64)\n cell = cell_cls(pos_enc, num_layers=3, num_heads=2, hidden=24)\n _, states_1 = tf.nn.dynamic_rnn(cell, in_seq[:, :1], dtype=tf.float64)\n _, states_2 = tf.nn.dynamic_rnn(cell, in_seq[:, :2], dtype=tf.float64)\n _, states_3 = tf.nn.dynamic_rnn(cell, in_seq[:, :3], dtype=tf.float64)\n new_states = tuple(tf.stack([s2[0], s3[1], s1[2]], axis=0)\n for s1, s2, s3 in zip(states_1, states_2, states_3))\n\n full_seq, _ = tf.nn.dynamic_rnn(cell, in_seq, dtype=tf.float64)\n expected = tf.stack([full_seq[0, 2:4], full_seq[1, 3:5], full_seq[2, 1:3]], axis=0)\n\n inputs = tf.stack([in_seq[0, 2:4], in_seq[1, 3:5], in_seq[2, 1:3]], axis=0)\n actual, _ = tf.nn.dynamic_rnn(cell, inputs, initial_state=new_states)\n\n sess.run(tf.global_variables_initializer())\n\n actual, expected = sess.run((actual, expected))\n\n assert not np.isnan(actual).any()\n assert not np.isnan(expected).any()\n assert actual.shape == expected.shape\n assert np.allclose(actual, expected)\n",
"step-ids": [
3,
4,
5,
6,
7
]
}
|
[
3,
4,
5,
6,
7
] |
../pyline/pyline.py
|
normal
|
{
"blob_id": "3fe98c865632c75c0ba0e1357379590f072bf662",
"index": 7840,
"step-1": "../pyline/pyline.py",
"step-2": null,
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0
]
}
|
[
0
] |
'''
BMI=weight*0.45259227/(hei*0.0254)**
'''
wht=2
if wht==0:
print("wht is",wht)
else:
print("whtsdsb")
#今天也完成了100波比跳
wei=float(input("wei="))
hei=float(input("hei="))
bmi=(wei*0.45259227)/((hei*0.0254)**2)
print("BMI=",bmi)
if bmi<18.5:
print("too light")
elif bmi<25:
print("normal")
elif bmi<30:
print("over")
else:
print("wanghantangshidssb")
|
normal
|
{
"blob_id": "48d0bfdc607a4605ef82f5c7dc7fd6fc85c4255f",
"index": 377,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nif wht == 0:\n print('wht is', wht)\nelse:\n print('whtsdsb')\n<mask token>\nprint('BMI=', bmi)\nif bmi < 18.5:\n print('too light')\nelif bmi < 25:\n print('normal')\nelif bmi < 30:\n print('over')\nelse:\n print('wanghantangshidssb')\n",
"step-3": "<mask token>\nwht = 2\nif wht == 0:\n print('wht is', wht)\nelse:\n print('whtsdsb')\nwei = float(input('wei='))\nhei = float(input('hei='))\nbmi = wei * 0.45259227 / (hei * 0.0254) ** 2\nprint('BMI=', bmi)\nif bmi < 18.5:\n print('too light')\nelif bmi < 25:\n print('normal')\nelif bmi < 30:\n print('over')\nelse:\n print('wanghantangshidssb')\n",
"step-4": "\n'''\nBMI=weight*0.45259227/(hei*0.0254)**\n'''\nwht=2\nif wht==0:\n print(\"wht is\",wht)\nelse:\n print(\"whtsdsb\")\n#今天也完成了100波比跳\nwei=float(input(\"wei=\"))\nhei=float(input(\"hei=\"))\nbmi=(wei*0.45259227)/((hei*0.0254)**2)\nprint(\"BMI=\",bmi)\nif bmi<18.5:\n print(\"too light\")\nelif bmi<25:\n print(\"normal\")\nelif bmi<30:\n print(\"over\")\nelse:\n print(\"wanghantangshidssb\")\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
class Production(Config):
<|reserved_special_token_0|>
class Development(Config):
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
class Testing(Config):
TESTING = True
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
<|reserved_special_token_1|>
<|reserved_special_token_0|>
class Production(Config):
SQLALCHEMY_DATABASE_URI = '<Production DB URL>'
class Development(Config):
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
class Testing(Config):
TESTING = True
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
<|reserved_special_token_1|>
class Config(object):
<|reserved_special_token_0|>
<|reserved_special_token_0|>
<|reserved_special_token_0|>
class Production(Config):
SQLALCHEMY_DATABASE_URI = '<Production DB URL>'
class Development(Config):
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
class Testing(Config):
TESTING = True
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
<|reserved_special_token_1|>
class Config(object):
DEBUG = False
TESTING = False
SQLALCHEMY_TRACK_MODIFICATIONS = False
class Production(Config):
SQLALCHEMY_DATABASE_URI = '<Production DB URL>'
class Development(Config):
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
class Testing(Config):
TESTING = True
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
<|reserved_special_token_1|>
class Config(object):
DEBUG = False
TESTING = False
SQLALCHEMY_TRACK_MODIFICATIONS = False
class Production(Config):
SQLALCHEMY_DATABASE_URI = '<Production DB URL>'
class Development(Config):
# psql postgresql://Nghi:nghi1996@localhost/postgres
DEBUG = True
SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
class Testing(Config):
TESTING = True
# SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres_test'
SQLALCHEMY_ECHO = False
JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'
SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'
SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'
MAIL_DEFAULT_SENDER = 'dev2020@localhost'
MAIL_SERVER = 'smtp.gmail.com'
MAIL_PORT = 465
MAIL_USERNAME = 'nghidev2020@gmail.com'
MAIL_PASSWORD = 'nghi1996'
MAIL_USE_TLS = False
MAIL_USE_SSL = True
UPLOAD_FOLDER = 'images'
|
flexible
|
{
"blob_id": "e99d557808c7ae32ebfef7e7fb2fddb04f45b13a",
"index": 6091,
"step-1": "<mask token>\n\n\nclass Production(Config):\n <mask token>\n\n\nclass Development(Config):\n DEBUG = True\n SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n\n\nclass Testing(Config):\n TESTING = True\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n",
"step-2": "<mask token>\n\n\nclass Production(Config):\n SQLALCHEMY_DATABASE_URI = '<Production DB URL>'\n\n\nclass Development(Config):\n DEBUG = True\n SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n\n\nclass Testing(Config):\n TESTING = True\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n",
"step-3": "class Config(object):\n <mask token>\n <mask token>\n <mask token>\n\n\nclass Production(Config):\n SQLALCHEMY_DATABASE_URI = '<Production DB URL>'\n\n\nclass Development(Config):\n DEBUG = True\n SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n\n\nclass Testing(Config):\n TESTING = True\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n",
"step-4": "class Config(object):\n DEBUG = False\n TESTING = False\n SQLALCHEMY_TRACK_MODIFICATIONS = False\n\n\nclass Production(Config):\n SQLALCHEMY_DATABASE_URI = '<Production DB URL>'\n\n\nclass Development(Config):\n DEBUG = True\n SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n\n\nclass Testing(Config):\n TESTING = True\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n",
"step-5": "class Config(object):\n DEBUG = False\n TESTING = False\n SQLALCHEMY_TRACK_MODIFICATIONS = False\n\n\nclass Production(Config):\n SQLALCHEMY_DATABASE_URI = '<Production DB URL>'\n\n\nclass Development(Config):\n # psql postgresql://Nghi:nghi1996@localhost/postgres\n DEBUG = True\n SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres'\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n\n\nclass Testing(Config):\n TESTING = True\n # SQLALCHEMY_DATABASE_URI = 'postgresql://Nghi:nghi1996@localhost/postgres_test'\n SQLALCHEMY_ECHO = False\n JWT_SECRET_KEY = 'JWT_SECRET_NGHI!123'\n SECRET_KEY = 'SECRET_KEY_NGHI_ABC!123'\n SECURITY_PASSWORD_SALT = 'SECURITY_PASSWORD_SALT_NGHI_ABC!123'\n MAIL_DEFAULT_SENDER = 'dev2020@localhost'\n MAIL_SERVER = 'smtp.gmail.com'\n MAIL_PORT = 465\n MAIL_USERNAME = 'nghidev2020@gmail.com'\n MAIL_PASSWORD = 'nghi1996'\n MAIL_USE_TLS = False\n MAIL_USE_SSL = True\n UPLOAD_FOLDER = 'images'\n",
"step-ids": [
5,
6,
7,
8,
9
]
}
|
[
5,
6,
7,
8,
9
] |
import os
import math
import shutil
from evoplotter import utils
from evoplotter.dims import *
from evoplotter import printer
import numpy as np
CHECK_CORRECTNESS_OF_FILES = 1
STATUS_FILE_NAME = "results/status.txt"
OPT_SOLUTIONS_FILE_NAME = "opt_solutions.txt"
class TableGenerator:
"""Generates table from data."""
def __init__(self, f_cell, dim_rows, dim_cols, headerRowNames, title="", color_scheme=None,
table_postprocessor=None, vertical_border=1, table_variants=None,
default_color_thresholds=None, layered_headline=True,
only_nonempty_rows=True, **kwargs):
self.f_cell = f_cell
self.dim_rows = dim_rows
self.dim_cols = dim_cols
self.title = title
self.color_scheme = color_scheme
self.table_postprocessor = table_postprocessor
self.vertical_border = vertical_border
self.headerRowNames = headerRowNames
# create a table for each variant and put them next to each other
self.table_variants = table_variants if table_variants is not None else [lambda p: True]
self.default_color_thresholds = default_color_thresholds
self.layered_headline = layered_headline
self.only_nonempty_rows = only_nonempty_rows
self.init_kwargs = kwargs.copy()
def apply(self, props, new_color_thresholds=None):
text = ""
for variant in self.table_variants: # each variant is some predicate on data
props_variant = [p for p in props if variant(p)]
if self.only_nonempty_rows:
dim_rows_variant = Dim([c for c in self.dim_rows.configs if len(c.filter_props(props_variant)) > 0])
else:
dim_rows_variant = self.dim_rows
txt = printer.latex_table(props_variant, dim_rows_variant, self.dim_cols, self.f_cell,
layered_headline=self.layered_headline, vertical_border=self.vertical_border,
headerRowNames=self.headerRowNames, **self.init_kwargs)
txt = self.table_postprocessor(txt)
ct = new_color_thresholds if new_color_thresholds is not None else self.default_color_thresholds
if self.color_scheme is not None and ct is not None:
cv0, cv1, cv2 = ct
txt = printer.table_color_map(txt, cv0, cv1, cv2, "colorLow", "colorMedium", "colorHigh")
text += r"\noindent"
text += txt
return text
class Experiment:
def __init__(self):
self.tables = []
self.listings = []
def delete_logs(props, pred, verbose=True, simulate=False):
for p in props:
if "evoplotter.file" in p and pred(p):
path = p["evoplotter.file"]
if not simulate:
os.remove(path)
if verbose:
print("File removed: {0}".format(path))
def print_props_filenames(props):
for p in props:
if "thisFileName" in p:
print(p["thisFileName"])
else:
print("'thisFileName' not specified! Printing content instead: " + str(p))
def create_errors_listing(error_props, filename):
f = open("results/listings/{0}".format(filename), "w")
print("Creating log of errors ({0})...".format(filename))
for i, p in enumerate(error_props):
if i > 0:
f.write("\n" + ("-" * 50) + "\n")
for k in sorted(p.keys()):
v = p[k]
f.write("{0} = {1}\n".format(k, v))
f.close()
def create_errors_solver_listing(error_props, filename, pred=None):
if pred is None:
pred = lambda x: True
f = open("results/listings/{0}".format(filename), "w")
print("Creating log of errors ({0})...".format(filename))
for i, p in enumerate(error_props):
if not pred(p): # ignore properties with certain features, e.g., types of errors
continue
if i > 0:
f.write("\n" + ("-" * 50) + "\n\n")
# read the whole original file, because multiline error messages are not preserved in dicts
with open(p["evoplotter.file"], 'r') as content_file:
content = content_file.read()
f.write(content)
f.close()
def load_correct_props(folders):
props_cdgpError = utils.load_properties_dirs(folders, exts=[".cdgp.error"], add_file_path=True)
exts = [".cdgp"]
props0 = utils.load_properties_dirs(folders, exts=exts, add_file_path=True)
def is_correct(p):
return "result.best.verificationDecision" in p
# Filtering props so only correct ones are left
props = [p for p in props0 if is_correct(p)]
# print("Filtered (props):")
# for p in props:
# if "resistance_par3_c1_10" in p["benchmark"] and p["method"] == "CDGP":
# print(p["evoplotter.file"])
# print("Filtered (props_cdgpError):")
# for p in props_cdgpError:
# if "resistance_par3_c1_10" in p["benchmark"] and p["method"] == "CDGP":
# print(p["evoplotter.file"])
# Clear log file
# print("[del] props")
# fun = lambda p: p["method"] == "CDGP" and p["partialConstraintsInFitness"] == "true"
# delete_logs(props, fun, simulate=True)
# print("[del] props_cdgpError")
# delete_logs(props_cdgpError, fun, simulate=True)
create_errors_solver_listing(props_cdgpError, "errors_solver.txt")
# Printing names of files which finished with error status or are incomplete.
if CHECK_CORRECTNESS_OF_FILES:
props_errors = [p for p in props0 if not is_correct(p)]
create_errors_listing(props_errors, "errors_run.txt")
if len(props_errors) > 0:
print("Files with error status:")
print_props_filenames(props_errors)
print("Loaded: {0} correct property files, {1} incorrect; All log files: {2}".format(len(props), len(props_errors), len(props) + len
(props_errors)))
print("Runs that ended with '.cdgp.error': {0}".format(len(props_cdgpError)))
print_props_filenames(props_cdgpError)
return props
def produce_status_matrix(dim, props):
"""Generates a status data in the form of a python list. It can be
later used to retry missing runs.
:param dim: (Dimension) dimensions on which data are to be divided.
:param props: (dict[str,str]) properties files.
:return: (str) Python code of a list containing specified data.
"""
text = "["
for config in dim:
numRuns = len(config.filter_props(props))
text += "({0}, {1}), ".format(config.stored_values, numRuns)
return text + "]"
def save_listings(props, dim_rows, dim_cols):
"""Saves listings of various useful info to separate text files."""
assert isinstance(dim_rows, Dim)
assert isinstance(dim_cols, Dim)
utils.ensure_dir("results/listings/errors/")
# Saving optimal verified solutions
for dr in dim_rows:
bench = dr.get_caption()
bench = bench[:bench.rfind(".")] if "." in bench else bench
f = open("results/listings/verified_{0}.txt".format(bench), "w")
f_errors = open("results/listings/errors/verified_{0}.txt".format(bench), "w")
props_bench = dr.filter_props(props)
for dc in dim_cols:
f.write("{0}\n".format(dc.get_caption()))
f_errors.write("{0}\n".format(dc.get_caption())) # TODO: finish
props_final = [p for p in dc.filter_props(props_bench) if is_verified_solution(p)]
for p in props_final:
fname = p["thisFileName"].replace("/home/ibladek/workspace/GECCO19/gecco19/", "")
best = p["result.best"]
fit = float(p["result.best.mse"])
if fit >= 1e-15:
f.write("{0}\t\t\t(FILE: {1}) (MSE: {2})\n".format(best, fname, fit))
else:
f.write("{0}\t\t\t(FILE: {1})\n".format(best, fname))
f.write("\n\n")
f.close()
f_errors.close()
def normalized_total_time(p, max_time=3600000):
"""If time was longer than max_time, then return max_time, otherwise return time. Time is counted in miliseconds."""
if "cdgp.wasTimeout" in p and p["cdgp.wasTimeout"] == "true":
v = 3600000
else:
v = int(float(p["result.totalTimeSystem"]))
return max_time if v > max_time else v
def is_verified_solution(p):
k = "result.best.verificationDecision"
return p["result.best.isOptimal"] == "true" and p[k] == "unsat"
def is_approximated_solution(p):
"""Checks if the MSE was below the threshold."""
tr = float(p["optThreshold"])
# TODO: finish
k = "result.best.verificationDecision"
return p["result.best.isOptimal"] == "true" and p[k] == "unsat"
def get_num_optimal(props):
props2 = [p for p in props if is_verified_solution(p)]
return len(props2)
def get_num_optimalOnlyMse(props):
# "cdgp.optThreshold" in p and
for p in props:
if "optThreshold" not in p:
print(str(p))
# Sometimes it is 'optThreshold', and sometimes 'cdgp.optThreshold'...
# props2 = [p for p in props if float(p["result.best.mse"]) <= float(p["optThreshold"])]
num = 0
for p in props:
if "optThreshold" in p:
tr = p["optThreshold"]
elif "optThreshold" in p:
tr = p["cdgp.optThreshold"]
else:
raise Exception("No optThreshold in log file")
if float(p["result.best.mse"]) <= tr:
num += 1
return num
def get_num_allPropertiesMet(props):
props2 = [p for p in props if p["result.best.verificationDecision"] == "unsat"]
return len(props2)
def get_num_computed(filtered):
return len(filtered)
def fun_successRate_full(filtered):
if len(filtered) == 0:
return "-"
num_opt = get_num_optimal(filtered)
return "{0}/{1}".format(str(num_opt), str(len(filtered)))
def get_successRate(filtered):
num_opt = get_num_optimal(filtered)
return float(num_opt) / float(len(filtered))
def fun_successRateMseOnly(filtered):
if len(filtered) == 0:
return "-"
n = get_num_optimalOnlyMse(filtered)
if n == 0:
return "-"
else:
sr = n / float(len(filtered))
return "{0}".format("%0.2f" % round(sr, 2))
def fun_average_mse(filtered):
res = 0.0
num = 0
# Sometimes there was "inf" in the results. We will ignore those elements.
for p in filtered:
x = float(p["result.best.mse"])
if not "n" in str(x):
res += x
num += 1
else:
print("Nan encountered")
if num == 0:
return "-"
else:
return res / num
def fun_average_mse_sd(filtered):
"""Returns average together with standard deviation."""
res = 0.0
num = 0
# Sometimes there was "inf" in the results. We will ignore those elements.
for p in filtered:
x = float(p["result.best.mse"])
if not "n" in str(x):
res += x
num += 1
else:
print("Nan encountered")
avg = res / num
sd = 0.0
for p in filtered:
x = float(p["result.best.mse"])
if not "n" in str(x):
sd += (x - avg) ** 2.0
sd = math.sqrt(sd / num)
if num == 0:
return "-"
else:
return r"${0} \pm{1}$".format(avg, sd)
def fun_successRate(filtered):
if len(filtered) == 0:
return "-"
sr = get_successRate(filtered)
return "{0}".format("%0.2f" % round(sr, 2))
def fun_allPropertiesMet(filtered):
if len(filtered) == 0:
return "-"
num_opt = get_num_allPropertiesMet(filtered)
sr = float(num_opt) / float(len(filtered))
return "{0}".format("%0.2f" % round(sr, 2))
def get_stats_size(props):
vals = [float(p["result.best.size"]) for p in props]
if len(vals) == 0:
return "-"#-1.0, -1.0
else:
return str(int(round(np.mean(vals)))) #, np.std(vals)
def get_stats_sizeOnlySuccessful(props):
vals = [float(p["result.best.size"]) for p in props if is_verified_solution(p)]
if len(vals) == 0:
return "-"#-1.0, -1.0
else:
return str(int(round(np.mean(vals)))) #, np.std(vals)
def get_stats_maxSolverTime(props):
if len(props) == 0 or "solver.allTimesCountMap" not in props[0]:
return "-"
times = []
for p in props:
timesMap = p["solver.allTimesCountMap"]
parts = timesMap.split(", ")[-1].split(",")
times.append(float(parts[0].replace("(", "")))
return "%0.3f" % max(times)
def get_stats_avgSolverTime(props):
if len(props) == 0 or "solver.allTimesCountMap" not in props[0] or props[0]["method"] != "CDGP":
return "-"
sum = 0.0
sumWeights = 0.0
for p in props:
timesMap = p["solver.allTimesCountMap"]
pairs = timesMap.split(", ")
if len(pairs) == 0:
continue
for x in pairs:
time = float(x.split(",")[0].replace("(", ""))
weight = float(x.split(",")[1].replace(")", ""))
sum += time * weight
sumWeights += weight
if sumWeights == 0.0:
return "%0.3f" % 0.0
else:
return "%0.3f" % (sum / sumWeights)
def get_avgSolverTotalCalls(props):
if len(props) == 0 or "solver.totalCalls" not in props[0]:
return "-"
vals = [float(p["solver.totalCalls"]) / 1000.0 for p in props]
return "%0.1f" % round(np.mean(vals), 1) # "%d"
def get_numSolverCallsOverXs(props):
if len(props) == 0 or "solver.allTimesCountMap" not in props[0]:
return "-"
TRESHOLD = 0.5
sum = 0
for p in props:
timesMap = p["solver.allTimesCountMap"]
pairs = timesMap.split(", ")
if len(pairs) == 0:
continue
for x in pairs:
time = float(x.split(",")[0].replace("(", ""))
if time > TRESHOLD:
# print("Name of file: " + p["thisFileName"])
weight = int(x.split(",")[1].replace(")", ""))
sum += weight
return sum
def get_avg_totalTests(props):
vals = [float(p["tests.total"]) for p in props]
if len(vals) == 0:
return "-" # -1.0, -1.0
else:
x = np.mean(vals)
if x < 1e-5:
x = 0.0
return str(int(round(x))) #"%0.1f" % x
def get_avg_mse(props):
vals = []
for p in props:
vals.append(float(p["result.best.mse"]))
if len(vals) == 0:
return "-" # -1.0, -1.0
else:
return "%0.5f" % np.mean(vals) # , np.std(vals)
def get_avg_runtime_helper(vals):
if len(vals) == 0:
return "n/a" # -1.0, -1.0
else:
x = np.mean(vals)
if x >= 10.0:
return "%d" % x
else:
return "%0.1f" % x # , np.std(vals)
def get_avg_runtimeOnlySuccessful(props):
if len(props) == 0:
return "-"
else:
vals = [float(normalized_total_time(p, max_time=1800000)) / 1000.0 for p in props if is_verified_solution(p)]
return get_avg_runtime_helper(vals)
def get_avg_runtime(props):
if len(props) == 0:
return "-"
else:
vals = [float(normalized_total_time(p, max_time=1800000)) / 1000.0 for p in props]
return get_avg_runtime_helper(vals)
def get_avg_generation(props):
if len(props) == 0:
return "-"
if len(props) > 0 and "result.totalGenerations" not in props[0]:
return "-"
vals = [float(p["result.totalGenerations"]) for p in props]
if len(vals) == 0:
return "-"
else:
return str(int(round(np.mean(vals)))) #"%0.1f" % np.mean(vals) # , np.std(vals)
def get_avg_generationSuccessful(props):
if len(props) == 0:
return "-"
else:
vals = [float(p["result.best.generation"]) for p in props if is_verified_solution(p)]
if len(vals) == 0:
return "n/a" # -1.0, -1.0
else:
return str(int(round(np.mean(vals)))) # "%0.1f" % np.mean(vals) # , np.std(vals)
def get_avg_evaluated(props):
if len(props) == 0:
return "-"
vals = []
for p in props:
if p["evolutionMode"] == "steadyState":
vals.append(float(p["result.totalGenerations"]))
else:
vals.append(float(p["result.totalGenerations"]) * float(p["populationSize"]))
return str(int(round(np.mean(vals)))) #"%0.1f" % np.mean(vals) # , np.std(vals)
def get_avg_evaluatedSuccessful(props):
if len(props) == 0:
return "-"
vals = []
for p in props:
if is_verified_solution(p):
if p["evolutionMode"] == "steadyState":
vals.append(float(p["result.totalGenerations"]))
else:
vals.append(float(p["result.totalGenerations"]) * float(p["populationSize"]))
if len(vals) == 0:
return "n/a" # -1.0, -1.0
else:
return str(int(round(np.mean(vals)))) # "%0.1f" % np.mean(vals) # , np.std(vals)
def get_avg_runtimePerProgram(props):
if len(props) == 0:
return "-" # -1.0, -1.0
sAvgGen = get_avg_generation(props)
if sAvgGen == "-" or sAvgGen is None:
return "-"
avgGen = float(sAvgGen) # avg number of generations in all runs
avgRuntime = float(get_avg_runtime(props)) # avg runtime of all runs
populationSize = float(props[0]["populationSize"])
if props[0]["evolutionMode"] == "steadyState":
approxNumPrograms = populationSize + avgGen # in steady state we have many generations, but in each of them created is one new program
else:
approxNumPrograms = populationSize * avgGen
approxTimePerProgram = avgRuntime / approxNumPrograms
return "%0.3f" % approxTimePerProgram
def get_sum_solverRestarts(props):
if len(props) == 0:
return "-"
vals = [int(p["solver.totalRestarts"]) for p in props if "solver.totalRestarts" in p]
if len(vals) != len(props):
print("WARNING: solver.totalRestarts was not present in all files.")
if len(vals) == 0:
return "0"
else:
return str(np.sum(vals))
def print_solved_in_time(props, upper_time):
if len(props) == 0:
return
# totalTimeSystem is in miliseconds
solved = 0
solvedRuns = 0
num = 0
for p in props:
if p["result.best.isOptimal"] == "false":
continue
num += 1
if int(normalized_total_time(p, max_time=1800000)) <= upper_time:
solved += 1
for p in props:
if int(normalized_total_time(p, max_time=1800000)) <= upper_time:
solvedRuns += 1
print("\nRuns which ended under {0} s: {1} / {2} ({3} %)".format(upper_time / 1000.0, solvedRuns, len(props), solvedRuns / len(props)))
print("Optimal solutions found under {0} s: {1} / {2} ({3} %)\n".format(upper_time / 1000.0, solved, num, solved / num))
|
normal
|
{
"blob_id": "b3cb94a44f64091714650efb81c4cad27b211cef",
"index": 8804,
"step-1": "<mask token>\n\n\nclass TableGenerator:\n \"\"\"Generates table from data.\"\"\"\n\n def __init__(self, f_cell, dim_rows, dim_cols, headerRowNames, title='',\n color_scheme=None, table_postprocessor=None, vertical_border=1,\n table_variants=None, default_color_thresholds=None,\n layered_headline=True, only_nonempty_rows=True, **kwargs):\n self.f_cell = f_cell\n self.dim_rows = dim_rows\n self.dim_cols = dim_cols\n self.title = title\n self.color_scheme = color_scheme\n self.table_postprocessor = table_postprocessor\n self.vertical_border = vertical_border\n self.headerRowNames = headerRowNames\n self.table_variants = (table_variants if table_variants is not None\n else [lambda p: True])\n self.default_color_thresholds = default_color_thresholds\n self.layered_headline = layered_headline\n self.only_nonempty_rows = only_nonempty_rows\n self.init_kwargs = kwargs.copy()\n\n def apply(self, props, new_color_thresholds=None):\n text = ''\n for variant in self.table_variants:\n props_variant = [p for p in props if variant(p)]\n if self.only_nonempty_rows:\n dim_rows_variant = Dim([c for c in self.dim_rows.configs if\n len(c.filter_props(props_variant)) > 0])\n else:\n dim_rows_variant = self.dim_rows\n txt = printer.latex_table(props_variant, dim_rows_variant, self\n .dim_cols, self.f_cell, layered_headline=self.\n layered_headline, vertical_border=self.vertical_border,\n headerRowNames=self.headerRowNames, **self.init_kwargs)\n txt = self.table_postprocessor(txt)\n ct = (new_color_thresholds if new_color_thresholds is not None else\n self.default_color_thresholds)\n if self.color_scheme is not None and ct is not None:\n cv0, cv1, cv2 = ct\n txt = printer.table_color_map(txt, cv0, cv1, cv2,\n 'colorLow', 'colorMedium', 'colorHigh')\n text += '\\\\noindent'\n text += txt\n return text\n\n\nclass Experiment:\n\n def __init__(self):\n self.tables = []\n self.listings = []\n\n\n<mask token>\n\n\ndef print_props_filenames(props):\n for p in props:\n if 'thisFileName' in p:\n print(p['thisFileName'])\n else:\n print(\n \"'thisFileName' not specified! Printing content instead: \" +\n str(p))\n\n\n<mask token>\n\n\ndef create_errors_solver_listing(error_props, filename, pred=None):\n if pred is None:\n pred = lambda x: True\n f = open('results/listings/{0}'.format(filename), 'w')\n print('Creating log of errors ({0})...'.format(filename))\n for i, p in enumerate(error_props):\n if not pred(p):\n continue\n if i > 0:\n f.write('\\n' + '-' * 50 + '\\n\\n')\n with open(p['evoplotter.file'], 'r') as content_file:\n content = content_file.read()\n f.write(content)\n f.close()\n\n\n<mask token>\n\n\ndef produce_status_matrix(dim, props):\n \"\"\"Generates a status data in the form of a python list. It can be\n later used to retry missing runs.\n\n :param dim: (Dimension) dimensions on which data are to be divided.\n :param props: (dict[str,str]) properties files.\n :return: (str) Python code of a list containing specified data.\n \"\"\"\n text = '['\n for config in dim:\n numRuns = len(config.filter_props(props))\n text += '({0}, {1}), '.format(config.stored_values, numRuns)\n return text + ']'\n\n\n<mask token>\n\n\ndef get_num_optimal(props):\n props2 = [p for p in props if is_verified_solution(p)]\n return len(props2)\n\n\n<mask token>\n\n\ndef fun_successRate_full(filtered):\n if len(filtered) == 0:\n return '-'\n num_opt = get_num_optimal(filtered)\n return '{0}/{1}'.format(str(num_opt), str(len(filtered)))\n\n\ndef get_successRate(filtered):\n num_opt = get_num_optimal(filtered)\n return float(num_opt) / float(len(filtered))\n\n\n<mask token>\n\n\ndef fun_average_mse_sd(filtered):\n \"\"\"Returns average together with standard deviation.\"\"\"\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n avg = res / num\n sd = 0.0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n sd += (x - avg) ** 2.0\n sd = math.sqrt(sd / num)\n if num == 0:\n return '-'\n else:\n return '${0} \\\\pm{1}$'.format(avg, sd)\n\n\n<mask token>\n\n\ndef get_stats_maxSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0]:\n return '-'\n times = []\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n parts = timesMap.split(', ')[-1].split(',')\n times.append(float(parts[0].replace('(', '')))\n return '%0.3f' % max(times)\n\n\n<mask token>\n\n\ndef get_avgSolverTotalCalls(props):\n if len(props) == 0 or 'solver.totalCalls' not in props[0]:\n return '-'\n vals = [(float(p['solver.totalCalls']) / 1000.0) for p in props]\n return '%0.1f' % round(np.mean(vals), 1)\n\n\n<mask token>\n\n\ndef get_avg_runtime_helper(vals):\n if len(vals) == 0:\n return 'n/a'\n else:\n x = np.mean(vals)\n if x >= 10.0:\n return '%d' % x\n else:\n return '%0.1f' % x\n\n\ndef get_avg_runtimeOnlySuccessful(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [(float(normalized_total_time(p, max_time=1800000)) / 1000.0\n ) for p in props if is_verified_solution(p)]\n return get_avg_runtime_helper(vals)\n\n\n<mask token>\n\n\ndef get_avg_generation(props):\n if len(props) == 0:\n return '-'\n if len(props) > 0 and 'result.totalGenerations' not in props[0]:\n return '-'\n vals = [float(p['result.totalGenerations']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\n<mask token>\n\n\ndef get_avg_evaluated(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_evaluatedSuccessful(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if is_verified_solution(p):\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n if len(vals) == 0:\n return 'n/a'\n else:\n return str(int(round(np.mean(vals))))\n\n\n<mask token>\n\n\ndef get_sum_solverRestarts(props):\n if len(props) == 0:\n return '-'\n vals = [int(p['solver.totalRestarts']) for p in props if \n 'solver.totalRestarts' in p]\n if len(vals) != len(props):\n print('WARNING: solver.totalRestarts was not present in all files.')\n if len(vals) == 0:\n return '0'\n else:\n return str(np.sum(vals))\n\n\ndef print_solved_in_time(props, upper_time):\n if len(props) == 0:\n return\n solved = 0\n solvedRuns = 0\n num = 0\n for p in props:\n if p['result.best.isOptimal'] == 'false':\n continue\n num += 1\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solved += 1\n for p in props:\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solvedRuns += 1\n print('\\nRuns which ended under {0} s: {1} / {2} ({3} %)'.format(\n upper_time / 1000.0, solvedRuns, len(props), solvedRuns / len(props)))\n print('Optimal solutions found under {0} s: {1} / {2} ({3} %)\\n'.\n format(upper_time / 1000.0, solved, num, solved / num))\n",
"step-2": "<mask token>\n\n\nclass TableGenerator:\n \"\"\"Generates table from data.\"\"\"\n\n def __init__(self, f_cell, dim_rows, dim_cols, headerRowNames, title='',\n color_scheme=None, table_postprocessor=None, vertical_border=1,\n table_variants=None, default_color_thresholds=None,\n layered_headline=True, only_nonempty_rows=True, **kwargs):\n self.f_cell = f_cell\n self.dim_rows = dim_rows\n self.dim_cols = dim_cols\n self.title = title\n self.color_scheme = color_scheme\n self.table_postprocessor = table_postprocessor\n self.vertical_border = vertical_border\n self.headerRowNames = headerRowNames\n self.table_variants = (table_variants if table_variants is not None\n else [lambda p: True])\n self.default_color_thresholds = default_color_thresholds\n self.layered_headline = layered_headline\n self.only_nonempty_rows = only_nonempty_rows\n self.init_kwargs = kwargs.copy()\n\n def apply(self, props, new_color_thresholds=None):\n text = ''\n for variant in self.table_variants:\n props_variant = [p for p in props if variant(p)]\n if self.only_nonempty_rows:\n dim_rows_variant = Dim([c for c in self.dim_rows.configs if\n len(c.filter_props(props_variant)) > 0])\n else:\n dim_rows_variant = self.dim_rows\n txt = printer.latex_table(props_variant, dim_rows_variant, self\n .dim_cols, self.f_cell, layered_headline=self.\n layered_headline, vertical_border=self.vertical_border,\n headerRowNames=self.headerRowNames, **self.init_kwargs)\n txt = self.table_postprocessor(txt)\n ct = (new_color_thresholds if new_color_thresholds is not None else\n self.default_color_thresholds)\n if self.color_scheme is not None and ct is not None:\n cv0, cv1, cv2 = ct\n txt = printer.table_color_map(txt, cv0, cv1, cv2,\n 'colorLow', 'colorMedium', 'colorHigh')\n text += '\\\\noindent'\n text += txt\n return text\n\n\nclass Experiment:\n\n def __init__(self):\n self.tables = []\n self.listings = []\n\n\n<mask token>\n\n\ndef print_props_filenames(props):\n for p in props:\n if 'thisFileName' in p:\n print(p['thisFileName'])\n else:\n print(\n \"'thisFileName' not specified! Printing content instead: \" +\n str(p))\n\n\n<mask token>\n\n\ndef create_errors_solver_listing(error_props, filename, pred=None):\n if pred is None:\n pred = lambda x: True\n f = open('results/listings/{0}'.format(filename), 'w')\n print('Creating log of errors ({0})...'.format(filename))\n for i, p in enumerate(error_props):\n if not pred(p):\n continue\n if i > 0:\n f.write('\\n' + '-' * 50 + '\\n\\n')\n with open(p['evoplotter.file'], 'r') as content_file:\n content = content_file.read()\n f.write(content)\n f.close()\n\n\n<mask token>\n\n\ndef produce_status_matrix(dim, props):\n \"\"\"Generates a status data in the form of a python list. It can be\n later used to retry missing runs.\n\n :param dim: (Dimension) dimensions on which data are to be divided.\n :param props: (dict[str,str]) properties files.\n :return: (str) Python code of a list containing specified data.\n \"\"\"\n text = '['\n for config in dim:\n numRuns = len(config.filter_props(props))\n text += '({0}, {1}), '.format(config.stored_values, numRuns)\n return text + ']'\n\n\n<mask token>\n\n\ndef normalized_total_time(p, max_time=3600000):\n \"\"\"If time was longer than max_time, then return max_time, otherwise return time. Time is counted in miliseconds.\"\"\"\n if 'cdgp.wasTimeout' in p and p['cdgp.wasTimeout'] == 'true':\n v = 3600000\n else:\n v = int(float(p['result.totalTimeSystem']))\n return max_time if v > max_time else v\n\n\n<mask token>\n\n\ndef get_num_optimal(props):\n props2 = [p for p in props if is_verified_solution(p)]\n return len(props2)\n\n\n<mask token>\n\n\ndef get_num_computed(filtered):\n return len(filtered)\n\n\ndef fun_successRate_full(filtered):\n if len(filtered) == 0:\n return '-'\n num_opt = get_num_optimal(filtered)\n return '{0}/{1}'.format(str(num_opt), str(len(filtered)))\n\n\ndef get_successRate(filtered):\n num_opt = get_num_optimal(filtered)\n return float(num_opt) / float(len(filtered))\n\n\ndef fun_successRateMseOnly(filtered):\n if len(filtered) == 0:\n return '-'\n n = get_num_optimalOnlyMse(filtered)\n if n == 0:\n return '-'\n else:\n sr = n / float(len(filtered))\n return '{0}'.format('%0.2f' % round(sr, 2))\n\n\ndef fun_average_mse(filtered):\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n if num == 0:\n return '-'\n else:\n return res / num\n\n\ndef fun_average_mse_sd(filtered):\n \"\"\"Returns average together with standard deviation.\"\"\"\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n avg = res / num\n sd = 0.0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n sd += (x - avg) ** 2.0\n sd = math.sqrt(sd / num)\n if num == 0:\n return '-'\n else:\n return '${0} \\\\pm{1}$'.format(avg, sd)\n\n\n<mask token>\n\n\ndef get_stats_size(props):\n vals = [float(p['result.best.size']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_stats_sizeOnlySuccessful(props):\n vals = [float(p['result.best.size']) for p in props if\n is_verified_solution(p)]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_stats_maxSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0]:\n return '-'\n times = []\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n parts = timesMap.split(', ')[-1].split(',')\n times.append(float(parts[0].replace('(', '')))\n return '%0.3f' % max(times)\n\n\ndef get_stats_avgSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0] or props[0\n ]['method'] != 'CDGP':\n return '-'\n sum = 0.0\n sumWeights = 0.0\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n pairs = timesMap.split(', ')\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(',')[0].replace('(', ''))\n weight = float(x.split(',')[1].replace(')', ''))\n sum += time * weight\n sumWeights += weight\n if sumWeights == 0.0:\n return '%0.3f' % 0.0\n else:\n return '%0.3f' % (sum / sumWeights)\n\n\ndef get_avgSolverTotalCalls(props):\n if len(props) == 0 or 'solver.totalCalls' not in props[0]:\n return '-'\n vals = [(float(p['solver.totalCalls']) / 1000.0) for p in props]\n return '%0.1f' % round(np.mean(vals), 1)\n\n\n<mask token>\n\n\ndef get_avg_totalTests(props):\n vals = [float(p['tests.total']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n x = np.mean(vals)\n if x < 1e-05:\n x = 0.0\n return str(int(round(x)))\n\n\n<mask token>\n\n\ndef get_avg_runtime_helper(vals):\n if len(vals) == 0:\n return 'n/a'\n else:\n x = np.mean(vals)\n if x >= 10.0:\n return '%d' % x\n else:\n return '%0.1f' % x\n\n\ndef get_avg_runtimeOnlySuccessful(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [(float(normalized_total_time(p, max_time=1800000)) / 1000.0\n ) for p in props if is_verified_solution(p)]\n return get_avg_runtime_helper(vals)\n\n\n<mask token>\n\n\ndef get_avg_generation(props):\n if len(props) == 0:\n return '-'\n if len(props) > 0 and 'result.totalGenerations' not in props[0]:\n return '-'\n vals = [float(p['result.totalGenerations']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\n<mask token>\n\n\ndef get_avg_evaluated(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_evaluatedSuccessful(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if is_verified_solution(p):\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n if len(vals) == 0:\n return 'n/a'\n else:\n return str(int(round(np.mean(vals))))\n\n\n<mask token>\n\n\ndef get_sum_solverRestarts(props):\n if len(props) == 0:\n return '-'\n vals = [int(p['solver.totalRestarts']) for p in props if \n 'solver.totalRestarts' in p]\n if len(vals) != len(props):\n print('WARNING: solver.totalRestarts was not present in all files.')\n if len(vals) == 0:\n return '0'\n else:\n return str(np.sum(vals))\n\n\ndef print_solved_in_time(props, upper_time):\n if len(props) == 0:\n return\n solved = 0\n solvedRuns = 0\n num = 0\n for p in props:\n if p['result.best.isOptimal'] == 'false':\n continue\n num += 1\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solved += 1\n for p in props:\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solvedRuns += 1\n print('\\nRuns which ended under {0} s: {1} / {2} ({3} %)'.format(\n upper_time / 1000.0, solvedRuns, len(props), solvedRuns / len(props)))\n print('Optimal solutions found under {0} s: {1} / {2} ({3} %)\\n'.\n format(upper_time / 1000.0, solved, num, solved / num))\n",
"step-3": "<mask token>\n\n\nclass TableGenerator:\n \"\"\"Generates table from data.\"\"\"\n\n def __init__(self, f_cell, dim_rows, dim_cols, headerRowNames, title='',\n color_scheme=None, table_postprocessor=None, vertical_border=1,\n table_variants=None, default_color_thresholds=None,\n layered_headline=True, only_nonempty_rows=True, **kwargs):\n self.f_cell = f_cell\n self.dim_rows = dim_rows\n self.dim_cols = dim_cols\n self.title = title\n self.color_scheme = color_scheme\n self.table_postprocessor = table_postprocessor\n self.vertical_border = vertical_border\n self.headerRowNames = headerRowNames\n self.table_variants = (table_variants if table_variants is not None\n else [lambda p: True])\n self.default_color_thresholds = default_color_thresholds\n self.layered_headline = layered_headline\n self.only_nonempty_rows = only_nonempty_rows\n self.init_kwargs = kwargs.copy()\n\n def apply(self, props, new_color_thresholds=None):\n text = ''\n for variant in self.table_variants:\n props_variant = [p for p in props if variant(p)]\n if self.only_nonempty_rows:\n dim_rows_variant = Dim([c for c in self.dim_rows.configs if\n len(c.filter_props(props_variant)) > 0])\n else:\n dim_rows_variant = self.dim_rows\n txt = printer.latex_table(props_variant, dim_rows_variant, self\n .dim_cols, self.f_cell, layered_headline=self.\n layered_headline, vertical_border=self.vertical_border,\n headerRowNames=self.headerRowNames, **self.init_kwargs)\n txt = self.table_postprocessor(txt)\n ct = (new_color_thresholds if new_color_thresholds is not None else\n self.default_color_thresholds)\n if self.color_scheme is not None and ct is not None:\n cv0, cv1, cv2 = ct\n txt = printer.table_color_map(txt, cv0, cv1, cv2,\n 'colorLow', 'colorMedium', 'colorHigh')\n text += '\\\\noindent'\n text += txt\n return text\n\n\nclass Experiment:\n\n def __init__(self):\n self.tables = []\n self.listings = []\n\n\n<mask token>\n\n\ndef print_props_filenames(props):\n for p in props:\n if 'thisFileName' in p:\n print(p['thisFileName'])\n else:\n print(\n \"'thisFileName' not specified! Printing content instead: \" +\n str(p))\n\n\n<mask token>\n\n\ndef create_errors_solver_listing(error_props, filename, pred=None):\n if pred is None:\n pred = lambda x: True\n f = open('results/listings/{0}'.format(filename), 'w')\n print('Creating log of errors ({0})...'.format(filename))\n for i, p in enumerate(error_props):\n if not pred(p):\n continue\n if i > 0:\n f.write('\\n' + '-' * 50 + '\\n\\n')\n with open(p['evoplotter.file'], 'r') as content_file:\n content = content_file.read()\n f.write(content)\n f.close()\n\n\n<mask token>\n\n\ndef produce_status_matrix(dim, props):\n \"\"\"Generates a status data in the form of a python list. It can be\n later used to retry missing runs.\n\n :param dim: (Dimension) dimensions on which data are to be divided.\n :param props: (dict[str,str]) properties files.\n :return: (str) Python code of a list containing specified data.\n \"\"\"\n text = '['\n for config in dim:\n numRuns = len(config.filter_props(props))\n text += '({0}, {1}), '.format(config.stored_values, numRuns)\n return text + ']'\n\n\n<mask token>\n\n\ndef normalized_total_time(p, max_time=3600000):\n \"\"\"If time was longer than max_time, then return max_time, otherwise return time. Time is counted in miliseconds.\"\"\"\n if 'cdgp.wasTimeout' in p and p['cdgp.wasTimeout'] == 'true':\n v = 3600000\n else:\n v = int(float(p['result.totalTimeSystem']))\n return max_time if v > max_time else v\n\n\n<mask token>\n\n\ndef is_approximated_solution(p):\n \"\"\"Checks if the MSE was below the threshold.\"\"\"\n tr = float(p['optThreshold'])\n k = 'result.best.verificationDecision'\n return p['result.best.isOptimal'] == 'true' and p[k] == 'unsat'\n\n\ndef get_num_optimal(props):\n props2 = [p for p in props if is_verified_solution(p)]\n return len(props2)\n\n\n<mask token>\n\n\ndef get_num_computed(filtered):\n return len(filtered)\n\n\ndef fun_successRate_full(filtered):\n if len(filtered) == 0:\n return '-'\n num_opt = get_num_optimal(filtered)\n return '{0}/{1}'.format(str(num_opt), str(len(filtered)))\n\n\ndef get_successRate(filtered):\n num_opt = get_num_optimal(filtered)\n return float(num_opt) / float(len(filtered))\n\n\ndef fun_successRateMseOnly(filtered):\n if len(filtered) == 0:\n return '-'\n n = get_num_optimalOnlyMse(filtered)\n if n == 0:\n return '-'\n else:\n sr = n / float(len(filtered))\n return '{0}'.format('%0.2f' % round(sr, 2))\n\n\ndef fun_average_mse(filtered):\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n if num == 0:\n return '-'\n else:\n return res / num\n\n\ndef fun_average_mse_sd(filtered):\n \"\"\"Returns average together with standard deviation.\"\"\"\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n avg = res / num\n sd = 0.0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n sd += (x - avg) ** 2.0\n sd = math.sqrt(sd / num)\n if num == 0:\n return '-'\n else:\n return '${0} \\\\pm{1}$'.format(avg, sd)\n\n\ndef fun_successRate(filtered):\n if len(filtered) == 0:\n return '-'\n sr = get_successRate(filtered)\n return '{0}'.format('%0.2f' % round(sr, 2))\n\n\n<mask token>\n\n\ndef get_stats_size(props):\n vals = [float(p['result.best.size']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_stats_sizeOnlySuccessful(props):\n vals = [float(p['result.best.size']) for p in props if\n is_verified_solution(p)]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_stats_maxSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0]:\n return '-'\n times = []\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n parts = timesMap.split(', ')[-1].split(',')\n times.append(float(parts[0].replace('(', '')))\n return '%0.3f' % max(times)\n\n\ndef get_stats_avgSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0] or props[0\n ]['method'] != 'CDGP':\n return '-'\n sum = 0.0\n sumWeights = 0.0\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n pairs = timesMap.split(', ')\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(',')[0].replace('(', ''))\n weight = float(x.split(',')[1].replace(')', ''))\n sum += time * weight\n sumWeights += weight\n if sumWeights == 0.0:\n return '%0.3f' % 0.0\n else:\n return '%0.3f' % (sum / sumWeights)\n\n\ndef get_avgSolverTotalCalls(props):\n if len(props) == 0 or 'solver.totalCalls' not in props[0]:\n return '-'\n vals = [(float(p['solver.totalCalls']) / 1000.0) for p in props]\n return '%0.1f' % round(np.mean(vals), 1)\n\n\ndef get_numSolverCallsOverXs(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0]:\n return '-'\n TRESHOLD = 0.5\n sum = 0\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n pairs = timesMap.split(', ')\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(',')[0].replace('(', ''))\n if time > TRESHOLD:\n weight = int(x.split(',')[1].replace(')', ''))\n sum += weight\n return sum\n\n\ndef get_avg_totalTests(props):\n vals = [float(p['tests.total']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n x = np.mean(vals)\n if x < 1e-05:\n x = 0.0\n return str(int(round(x)))\n\n\ndef get_avg_mse(props):\n vals = []\n for p in props:\n vals.append(float(p['result.best.mse']))\n if len(vals) == 0:\n return '-'\n else:\n return '%0.5f' % np.mean(vals)\n\n\ndef get_avg_runtime_helper(vals):\n if len(vals) == 0:\n return 'n/a'\n else:\n x = np.mean(vals)\n if x >= 10.0:\n return '%d' % x\n else:\n return '%0.1f' % x\n\n\ndef get_avg_runtimeOnlySuccessful(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [(float(normalized_total_time(p, max_time=1800000)) / 1000.0\n ) for p in props if is_verified_solution(p)]\n return get_avg_runtime_helper(vals)\n\n\ndef get_avg_runtime(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [(float(normalized_total_time(p, max_time=1800000)) / 1000.0\n ) for p in props]\n return get_avg_runtime_helper(vals)\n\n\ndef get_avg_generation(props):\n if len(props) == 0:\n return '-'\n if len(props) > 0 and 'result.totalGenerations' not in props[0]:\n return '-'\n vals = [float(p['result.totalGenerations']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_generationSuccessful(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [float(p['result.best.generation']) for p in props if\n is_verified_solution(p)]\n if len(vals) == 0:\n return 'n/a'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_evaluated(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_evaluatedSuccessful(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if is_verified_solution(p):\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n if len(vals) == 0:\n return 'n/a'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_runtimePerProgram(props):\n if len(props) == 0:\n return '-'\n sAvgGen = get_avg_generation(props)\n if sAvgGen == '-' or sAvgGen is None:\n return '-'\n avgGen = float(sAvgGen)\n avgRuntime = float(get_avg_runtime(props))\n populationSize = float(props[0]['populationSize'])\n if props[0]['evolutionMode'] == 'steadyState':\n approxNumPrograms = populationSize + avgGen\n else:\n approxNumPrograms = populationSize * avgGen\n approxTimePerProgram = avgRuntime / approxNumPrograms\n return '%0.3f' % approxTimePerProgram\n\n\ndef get_sum_solverRestarts(props):\n if len(props) == 0:\n return '-'\n vals = [int(p['solver.totalRestarts']) for p in props if \n 'solver.totalRestarts' in p]\n if len(vals) != len(props):\n print('WARNING: solver.totalRestarts was not present in all files.')\n if len(vals) == 0:\n return '0'\n else:\n return str(np.sum(vals))\n\n\ndef print_solved_in_time(props, upper_time):\n if len(props) == 0:\n return\n solved = 0\n solvedRuns = 0\n num = 0\n for p in props:\n if p['result.best.isOptimal'] == 'false':\n continue\n num += 1\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solved += 1\n for p in props:\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solvedRuns += 1\n print('\\nRuns which ended under {0} s: {1} / {2} ({3} %)'.format(\n upper_time / 1000.0, solvedRuns, len(props), solvedRuns / len(props)))\n print('Optimal solutions found under {0} s: {1} / {2} ({3} %)\\n'.\n format(upper_time / 1000.0, solved, num, solved / num))\n",
"step-4": "<mask token>\n\n\nclass TableGenerator:\n \"\"\"Generates table from data.\"\"\"\n\n def __init__(self, f_cell, dim_rows, dim_cols, headerRowNames, title='',\n color_scheme=None, table_postprocessor=None, vertical_border=1,\n table_variants=None, default_color_thresholds=None,\n layered_headline=True, only_nonempty_rows=True, **kwargs):\n self.f_cell = f_cell\n self.dim_rows = dim_rows\n self.dim_cols = dim_cols\n self.title = title\n self.color_scheme = color_scheme\n self.table_postprocessor = table_postprocessor\n self.vertical_border = vertical_border\n self.headerRowNames = headerRowNames\n self.table_variants = (table_variants if table_variants is not None\n else [lambda p: True])\n self.default_color_thresholds = default_color_thresholds\n self.layered_headline = layered_headline\n self.only_nonempty_rows = only_nonempty_rows\n self.init_kwargs = kwargs.copy()\n\n def apply(self, props, new_color_thresholds=None):\n text = ''\n for variant in self.table_variants:\n props_variant = [p for p in props if variant(p)]\n if self.only_nonempty_rows:\n dim_rows_variant = Dim([c for c in self.dim_rows.configs if\n len(c.filter_props(props_variant)) > 0])\n else:\n dim_rows_variant = self.dim_rows\n txt = printer.latex_table(props_variant, dim_rows_variant, self\n .dim_cols, self.f_cell, layered_headline=self.\n layered_headline, vertical_border=self.vertical_border,\n headerRowNames=self.headerRowNames, **self.init_kwargs)\n txt = self.table_postprocessor(txt)\n ct = (new_color_thresholds if new_color_thresholds is not None else\n self.default_color_thresholds)\n if self.color_scheme is not None and ct is not None:\n cv0, cv1, cv2 = ct\n txt = printer.table_color_map(txt, cv0, cv1, cv2,\n 'colorLow', 'colorMedium', 'colorHigh')\n text += '\\\\noindent'\n text += txt\n return text\n\n\nclass Experiment:\n\n def __init__(self):\n self.tables = []\n self.listings = []\n\n\ndef delete_logs(props, pred, verbose=True, simulate=False):\n for p in props:\n if 'evoplotter.file' in p and pred(p):\n path = p['evoplotter.file']\n if not simulate:\n os.remove(path)\n if verbose:\n print('File removed: {0}'.format(path))\n\n\ndef print_props_filenames(props):\n for p in props:\n if 'thisFileName' in p:\n print(p['thisFileName'])\n else:\n print(\n \"'thisFileName' not specified! Printing content instead: \" +\n str(p))\n\n\ndef create_errors_listing(error_props, filename):\n f = open('results/listings/{0}'.format(filename), 'w')\n print('Creating log of errors ({0})...'.format(filename))\n for i, p in enumerate(error_props):\n if i > 0:\n f.write('\\n' + '-' * 50 + '\\n')\n for k in sorted(p.keys()):\n v = p[k]\n f.write('{0} = {1}\\n'.format(k, v))\n f.close()\n\n\ndef create_errors_solver_listing(error_props, filename, pred=None):\n if pred is None:\n pred = lambda x: True\n f = open('results/listings/{0}'.format(filename), 'w')\n print('Creating log of errors ({0})...'.format(filename))\n for i, p in enumerate(error_props):\n if not pred(p):\n continue\n if i > 0:\n f.write('\\n' + '-' * 50 + '\\n\\n')\n with open(p['evoplotter.file'], 'r') as content_file:\n content = content_file.read()\n f.write(content)\n f.close()\n\n\ndef load_correct_props(folders):\n props_cdgpError = utils.load_properties_dirs(folders, exts=[\n '.cdgp.error'], add_file_path=True)\n exts = ['.cdgp']\n props0 = utils.load_properties_dirs(folders, exts=exts, add_file_path=True)\n\n def is_correct(p):\n return 'result.best.verificationDecision' in p\n props = [p for p in props0 if is_correct(p)]\n create_errors_solver_listing(props_cdgpError, 'errors_solver.txt')\n if CHECK_CORRECTNESS_OF_FILES:\n props_errors = [p for p in props0 if not is_correct(p)]\n create_errors_listing(props_errors, 'errors_run.txt')\n if len(props_errors) > 0:\n print('Files with error status:')\n print_props_filenames(props_errors)\n print(\n 'Loaded: {0} correct property files, {1} incorrect; All log files: {2}'\n .format(len(props), len(props_errors), len(props) + len(\n props_errors)))\n print(\"Runs that ended with '.cdgp.error': {0}\".format(len(\n props_cdgpError)))\n print_props_filenames(props_cdgpError)\n return props\n\n\ndef produce_status_matrix(dim, props):\n \"\"\"Generates a status data in the form of a python list. It can be\n later used to retry missing runs.\n\n :param dim: (Dimension) dimensions on which data are to be divided.\n :param props: (dict[str,str]) properties files.\n :return: (str) Python code of a list containing specified data.\n \"\"\"\n text = '['\n for config in dim:\n numRuns = len(config.filter_props(props))\n text += '({0}, {1}), '.format(config.stored_values, numRuns)\n return text + ']'\n\n\ndef save_listings(props, dim_rows, dim_cols):\n \"\"\"Saves listings of various useful info to separate text files.\"\"\"\n assert isinstance(dim_rows, Dim)\n assert isinstance(dim_cols, Dim)\n utils.ensure_dir('results/listings/errors/')\n for dr in dim_rows:\n bench = dr.get_caption()\n bench = bench[:bench.rfind('.')] if '.' in bench else bench\n f = open('results/listings/verified_{0}.txt'.format(bench), 'w')\n f_errors = open('results/listings/errors/verified_{0}.txt'.format(\n bench), 'w')\n props_bench = dr.filter_props(props)\n for dc in dim_cols:\n f.write('{0}\\n'.format(dc.get_caption()))\n f_errors.write('{0}\\n'.format(dc.get_caption()))\n props_final = [p for p in dc.filter_props(props_bench) if\n is_verified_solution(p)]\n for p in props_final:\n fname = p['thisFileName'].replace(\n '/home/ibladek/workspace/GECCO19/gecco19/', '')\n best = p['result.best']\n fit = float(p['result.best.mse'])\n if fit >= 1e-15:\n f.write('{0}\\t\\t\\t(FILE: {1}) (MSE: {2})\\n'.format(best,\n fname, fit))\n else:\n f.write('{0}\\t\\t\\t(FILE: {1})\\n'.format(best, fname))\n f.write('\\n\\n')\n f.close()\n f_errors.close()\n\n\ndef normalized_total_time(p, max_time=3600000):\n \"\"\"If time was longer than max_time, then return max_time, otherwise return time. Time is counted in miliseconds.\"\"\"\n if 'cdgp.wasTimeout' in p and p['cdgp.wasTimeout'] == 'true':\n v = 3600000\n else:\n v = int(float(p['result.totalTimeSystem']))\n return max_time if v > max_time else v\n\n\n<mask token>\n\n\ndef is_approximated_solution(p):\n \"\"\"Checks if the MSE was below the threshold.\"\"\"\n tr = float(p['optThreshold'])\n k = 'result.best.verificationDecision'\n return p['result.best.isOptimal'] == 'true' and p[k] == 'unsat'\n\n\ndef get_num_optimal(props):\n props2 = [p for p in props if is_verified_solution(p)]\n return len(props2)\n\n\ndef get_num_optimalOnlyMse(props):\n for p in props:\n if 'optThreshold' not in p:\n print(str(p))\n num = 0\n for p in props:\n if 'optThreshold' in p:\n tr = p['optThreshold']\n elif 'optThreshold' in p:\n tr = p['cdgp.optThreshold']\n else:\n raise Exception('No optThreshold in log file')\n if float(p['result.best.mse']) <= tr:\n num += 1\n return num\n\n\ndef get_num_allPropertiesMet(props):\n props2 = [p for p in props if p['result.best.verificationDecision'] ==\n 'unsat']\n return len(props2)\n\n\ndef get_num_computed(filtered):\n return len(filtered)\n\n\ndef fun_successRate_full(filtered):\n if len(filtered) == 0:\n return '-'\n num_opt = get_num_optimal(filtered)\n return '{0}/{1}'.format(str(num_opt), str(len(filtered)))\n\n\ndef get_successRate(filtered):\n num_opt = get_num_optimal(filtered)\n return float(num_opt) / float(len(filtered))\n\n\ndef fun_successRateMseOnly(filtered):\n if len(filtered) == 0:\n return '-'\n n = get_num_optimalOnlyMse(filtered)\n if n == 0:\n return '-'\n else:\n sr = n / float(len(filtered))\n return '{0}'.format('%0.2f' % round(sr, 2))\n\n\ndef fun_average_mse(filtered):\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n if num == 0:\n return '-'\n else:\n return res / num\n\n\ndef fun_average_mse_sd(filtered):\n \"\"\"Returns average together with standard deviation.\"\"\"\n res = 0.0\n num = 0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n res += x\n num += 1\n else:\n print('Nan encountered')\n avg = res / num\n sd = 0.0\n for p in filtered:\n x = float(p['result.best.mse'])\n if not 'n' in str(x):\n sd += (x - avg) ** 2.0\n sd = math.sqrt(sd / num)\n if num == 0:\n return '-'\n else:\n return '${0} \\\\pm{1}$'.format(avg, sd)\n\n\ndef fun_successRate(filtered):\n if len(filtered) == 0:\n return '-'\n sr = get_successRate(filtered)\n return '{0}'.format('%0.2f' % round(sr, 2))\n\n\ndef fun_allPropertiesMet(filtered):\n if len(filtered) == 0:\n return '-'\n num_opt = get_num_allPropertiesMet(filtered)\n sr = float(num_opt) / float(len(filtered))\n return '{0}'.format('%0.2f' % round(sr, 2))\n\n\ndef get_stats_size(props):\n vals = [float(p['result.best.size']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_stats_sizeOnlySuccessful(props):\n vals = [float(p['result.best.size']) for p in props if\n is_verified_solution(p)]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_stats_maxSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0]:\n return '-'\n times = []\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n parts = timesMap.split(', ')[-1].split(',')\n times.append(float(parts[0].replace('(', '')))\n return '%0.3f' % max(times)\n\n\ndef get_stats_avgSolverTime(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0] or props[0\n ]['method'] != 'CDGP':\n return '-'\n sum = 0.0\n sumWeights = 0.0\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n pairs = timesMap.split(', ')\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(',')[0].replace('(', ''))\n weight = float(x.split(',')[1].replace(')', ''))\n sum += time * weight\n sumWeights += weight\n if sumWeights == 0.0:\n return '%0.3f' % 0.0\n else:\n return '%0.3f' % (sum / sumWeights)\n\n\ndef get_avgSolverTotalCalls(props):\n if len(props) == 0 or 'solver.totalCalls' not in props[0]:\n return '-'\n vals = [(float(p['solver.totalCalls']) / 1000.0) for p in props]\n return '%0.1f' % round(np.mean(vals), 1)\n\n\ndef get_numSolverCallsOverXs(props):\n if len(props) == 0 or 'solver.allTimesCountMap' not in props[0]:\n return '-'\n TRESHOLD = 0.5\n sum = 0\n for p in props:\n timesMap = p['solver.allTimesCountMap']\n pairs = timesMap.split(', ')\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(',')[0].replace('(', ''))\n if time > TRESHOLD:\n weight = int(x.split(',')[1].replace(')', ''))\n sum += weight\n return sum\n\n\ndef get_avg_totalTests(props):\n vals = [float(p['tests.total']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n x = np.mean(vals)\n if x < 1e-05:\n x = 0.0\n return str(int(round(x)))\n\n\ndef get_avg_mse(props):\n vals = []\n for p in props:\n vals.append(float(p['result.best.mse']))\n if len(vals) == 0:\n return '-'\n else:\n return '%0.5f' % np.mean(vals)\n\n\ndef get_avg_runtime_helper(vals):\n if len(vals) == 0:\n return 'n/a'\n else:\n x = np.mean(vals)\n if x >= 10.0:\n return '%d' % x\n else:\n return '%0.1f' % x\n\n\ndef get_avg_runtimeOnlySuccessful(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [(float(normalized_total_time(p, max_time=1800000)) / 1000.0\n ) for p in props if is_verified_solution(p)]\n return get_avg_runtime_helper(vals)\n\n\ndef get_avg_runtime(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [(float(normalized_total_time(p, max_time=1800000)) / 1000.0\n ) for p in props]\n return get_avg_runtime_helper(vals)\n\n\ndef get_avg_generation(props):\n if len(props) == 0:\n return '-'\n if len(props) > 0 and 'result.totalGenerations' not in props[0]:\n return '-'\n vals = [float(p['result.totalGenerations']) for p in props]\n if len(vals) == 0:\n return '-'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_generationSuccessful(props):\n if len(props) == 0:\n return '-'\n else:\n vals = [float(p['result.best.generation']) for p in props if\n is_verified_solution(p)]\n if len(vals) == 0:\n return 'n/a'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_evaluated(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_evaluatedSuccessful(props):\n if len(props) == 0:\n return '-'\n vals = []\n for p in props:\n if is_verified_solution(p):\n if p['evolutionMode'] == 'steadyState':\n vals.append(float(p['result.totalGenerations']))\n else:\n vals.append(float(p['result.totalGenerations']) * float(p[\n 'populationSize']))\n if len(vals) == 0:\n return 'n/a'\n else:\n return str(int(round(np.mean(vals))))\n\n\ndef get_avg_runtimePerProgram(props):\n if len(props) == 0:\n return '-'\n sAvgGen = get_avg_generation(props)\n if sAvgGen == '-' or sAvgGen is None:\n return '-'\n avgGen = float(sAvgGen)\n avgRuntime = float(get_avg_runtime(props))\n populationSize = float(props[0]['populationSize'])\n if props[0]['evolutionMode'] == 'steadyState':\n approxNumPrograms = populationSize + avgGen\n else:\n approxNumPrograms = populationSize * avgGen\n approxTimePerProgram = avgRuntime / approxNumPrograms\n return '%0.3f' % approxTimePerProgram\n\n\ndef get_sum_solverRestarts(props):\n if len(props) == 0:\n return '-'\n vals = [int(p['solver.totalRestarts']) for p in props if \n 'solver.totalRestarts' in p]\n if len(vals) != len(props):\n print('WARNING: solver.totalRestarts was not present in all files.')\n if len(vals) == 0:\n return '0'\n else:\n return str(np.sum(vals))\n\n\ndef print_solved_in_time(props, upper_time):\n if len(props) == 0:\n return\n solved = 0\n solvedRuns = 0\n num = 0\n for p in props:\n if p['result.best.isOptimal'] == 'false':\n continue\n num += 1\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solved += 1\n for p in props:\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solvedRuns += 1\n print('\\nRuns which ended under {0} s: {1} / {2} ({3} %)'.format(\n upper_time / 1000.0, solvedRuns, len(props), solvedRuns / len(props)))\n print('Optimal solutions found under {0} s: {1} / {2} ({3} %)\\n'.\n format(upper_time / 1000.0, solved, num, solved / num))\n",
"step-5": "import os\nimport math\nimport shutil\nfrom evoplotter import utils\nfrom evoplotter.dims import *\nfrom evoplotter import printer\nimport numpy as np\n\n\nCHECK_CORRECTNESS_OF_FILES = 1\nSTATUS_FILE_NAME = \"results/status.txt\"\nOPT_SOLUTIONS_FILE_NAME = \"opt_solutions.txt\"\n\n\n\nclass TableGenerator:\n \"\"\"Generates table from data.\"\"\"\n def __init__(self, f_cell, dim_rows, dim_cols, headerRowNames, title=\"\", color_scheme=None,\n table_postprocessor=None, vertical_border=1, table_variants=None,\n default_color_thresholds=None, layered_headline=True,\n only_nonempty_rows=True, **kwargs):\n self.f_cell = f_cell\n self.dim_rows = dim_rows\n self.dim_cols = dim_cols\n self.title = title\n self.color_scheme = color_scheme\n self.table_postprocessor = table_postprocessor\n self.vertical_border = vertical_border\n self.headerRowNames = headerRowNames\n # create a table for each variant and put them next to each other\n self.table_variants = table_variants if table_variants is not None else [lambda p: True]\n self.default_color_thresholds = default_color_thresholds\n self.layered_headline = layered_headline\n self.only_nonempty_rows = only_nonempty_rows\n self.init_kwargs = kwargs.copy()\n\n\n def apply(self, props, new_color_thresholds=None):\n text = \"\"\n for variant in self.table_variants: # each variant is some predicate on data\n props_variant = [p for p in props if variant(p)]\n if self.only_nonempty_rows:\n dim_rows_variant = Dim([c for c in self.dim_rows.configs if len(c.filter_props(props_variant)) > 0])\n else:\n dim_rows_variant = self.dim_rows\n\n txt = printer.latex_table(props_variant, dim_rows_variant, self.dim_cols, self.f_cell,\n layered_headline=self.layered_headline, vertical_border=self.vertical_border,\n headerRowNames=self.headerRowNames, **self.init_kwargs)\n txt = self.table_postprocessor(txt)\n ct = new_color_thresholds if new_color_thresholds is not None else self.default_color_thresholds\n if self.color_scheme is not None and ct is not None:\n cv0, cv1, cv2 = ct\n txt = printer.table_color_map(txt, cv0, cv1, cv2, \"colorLow\", \"colorMedium\", \"colorHigh\")\n\n text += r\"\\noindent\"\n text += txt\n return text\n\n\n\nclass Experiment:\n def __init__(self):\n self.tables = []\n self.listings = []\n\n\n\ndef delete_logs(props, pred, verbose=True, simulate=False):\n for p in props:\n if \"evoplotter.file\" in p and pred(p):\n path = p[\"evoplotter.file\"]\n if not simulate:\n os.remove(path)\n if verbose:\n print(\"File removed: {0}\".format(path))\n\n\ndef print_props_filenames(props):\n for p in props:\n if \"thisFileName\" in p:\n print(p[\"thisFileName\"])\n else:\n print(\"'thisFileName' not specified! Printing content instead: \" + str(p))\n\n\ndef create_errors_listing(error_props, filename):\n f = open(\"results/listings/{0}\".format(filename), \"w\")\n print(\"Creating log of errors ({0})...\".format(filename))\n for i, p in enumerate(error_props):\n if i > 0:\n f.write(\"\\n\" + (\"-\" * 50) + \"\\n\")\n for k in sorted(p.keys()):\n v = p[k]\n f.write(\"{0} = {1}\\n\".format(k, v))\n f.close()\n\n\ndef create_errors_solver_listing(error_props, filename, pred=None):\n if pred is None:\n pred = lambda x: True\n f = open(\"results/listings/{0}\".format(filename), \"w\")\n print(\"Creating log of errors ({0})...\".format(filename))\n for i, p in enumerate(error_props):\n if not pred(p): # ignore properties with certain features, e.g., types of errors\n continue\n\n if i > 0:\n f.write(\"\\n\" + (\"-\" * 50) + \"\\n\\n\")\n\n # read the whole original file, because multiline error messages are not preserved in dicts\n with open(p[\"evoplotter.file\"], 'r') as content_file:\n content = content_file.read()\n f.write(content)\n f.close()\n\n\ndef load_correct_props(folders):\n props_cdgpError = utils.load_properties_dirs(folders, exts=[\".cdgp.error\"], add_file_path=True)\n exts = [\".cdgp\"]\n props0 = utils.load_properties_dirs(folders, exts=exts, add_file_path=True)\n\n def is_correct(p):\n return \"result.best.verificationDecision\" in p\n\n # Filtering props so only correct ones are left\n props = [p for p in props0 if is_correct(p)]\n\n # print(\"Filtered (props):\")\n # for p in props:\n # if \"resistance_par3_c1_10\" in p[\"benchmark\"] and p[\"method\"] == \"CDGP\":\n # print(p[\"evoplotter.file\"])\n # print(\"Filtered (props_cdgpError):\")\n # for p in props_cdgpError:\n # if \"resistance_par3_c1_10\" in p[\"benchmark\"] and p[\"method\"] == \"CDGP\":\n # print(p[\"evoplotter.file\"])\n\n # Clear log file\n # print(\"[del] props\")\n # fun = lambda p: p[\"method\"] == \"CDGP\" and p[\"partialConstraintsInFitness\"] == \"true\"\n # delete_logs(props, fun, simulate=True)\n # print(\"[del] props_cdgpError\")\n # delete_logs(props_cdgpError, fun, simulate=True)\n\n\n create_errors_solver_listing(props_cdgpError, \"errors_solver.txt\")\n\n # Printing names of files which finished with error status or are incomplete.\n if CHECK_CORRECTNESS_OF_FILES:\n props_errors = [p for p in props0 if not is_correct(p)]\n create_errors_listing(props_errors, \"errors_run.txt\")\n if len(props_errors) > 0:\n print(\"Files with error status:\")\n print_props_filenames(props_errors)\n print(\"Loaded: {0} correct property files, {1} incorrect; All log files: {2}\".format(len(props), len(props_errors), len(props) + len\n (props_errors)))\n print(\"Runs that ended with '.cdgp.error': {0}\".format(len(props_cdgpError)))\n print_props_filenames(props_cdgpError)\n return props\n\n\ndef produce_status_matrix(dim, props):\n \"\"\"Generates a status data in the form of a python list. It can be\n later used to retry missing runs.\n\n :param dim: (Dimension) dimensions on which data are to be divided.\n :param props: (dict[str,str]) properties files.\n :return: (str) Python code of a list containing specified data.\n \"\"\"\n text = \"[\"\n for config in dim:\n numRuns = len(config.filter_props(props))\n text += \"({0}, {1}), \".format(config.stored_values, numRuns)\n return text + \"]\"\n\n\n\ndef save_listings(props, dim_rows, dim_cols):\n \"\"\"Saves listings of various useful info to separate text files.\"\"\"\n assert isinstance(dim_rows, Dim)\n assert isinstance(dim_cols, Dim)\n utils.ensure_dir(\"results/listings/errors/\")\n\n # Saving optimal verified solutions\n for dr in dim_rows:\n bench = dr.get_caption()\n bench = bench[:bench.rfind(\".\")] if \".\" in bench else bench\n f = open(\"results/listings/verified_{0}.txt\".format(bench), \"w\")\n f_errors = open(\"results/listings/errors/verified_{0}.txt\".format(bench), \"w\")\n\n props_bench = dr.filter_props(props)\n for dc in dim_cols:\n f.write(\"{0}\\n\".format(dc.get_caption()))\n f_errors.write(\"{0}\\n\".format(dc.get_caption())) # TODO: finish\n props_final = [p for p in dc.filter_props(props_bench) if is_verified_solution(p)]\n\n for p in props_final:\n fname = p[\"thisFileName\"].replace(\"/home/ibladek/workspace/GECCO19/gecco19/\", \"\")\n best = p[\"result.best\"]\n fit = float(p[\"result.best.mse\"])\n if fit >= 1e-15:\n f.write(\"{0}\\t\\t\\t(FILE: {1}) (MSE: {2})\\n\".format(best, fname, fit))\n else:\n f.write(\"{0}\\t\\t\\t(FILE: {1})\\n\".format(best, fname))\n\n f.write(\"\\n\\n\")\n f.close()\n f_errors.close()\n\n\n\ndef normalized_total_time(p, max_time=3600000):\n \"\"\"If time was longer than max_time, then return max_time, otherwise return time. Time is counted in miliseconds.\"\"\"\n if \"cdgp.wasTimeout\" in p and p[\"cdgp.wasTimeout\"] == \"true\":\n v = 3600000\n else:\n v = int(float(p[\"result.totalTimeSystem\"]))\n return max_time if v > max_time else v\n\ndef is_verified_solution(p):\n k = \"result.best.verificationDecision\"\n return p[\"result.best.isOptimal\"] == \"true\" and p[k] == \"unsat\"\n\ndef is_approximated_solution(p):\n \"\"\"Checks if the MSE was below the threshold.\"\"\"\n tr = float(p[\"optThreshold\"])\n # TODO: finish\n k = \"result.best.verificationDecision\"\n return p[\"result.best.isOptimal\"] == \"true\" and p[k] == \"unsat\"\n\ndef get_num_optimal(props):\n props2 = [p for p in props if is_verified_solution(p)]\n return len(props2)\ndef get_num_optimalOnlyMse(props):\n # \"cdgp.optThreshold\" in p and\n for p in props:\n if \"optThreshold\" not in p:\n print(str(p))\n # Sometimes it is 'optThreshold', and sometimes 'cdgp.optThreshold'...\n # props2 = [p for p in props if float(p[\"result.best.mse\"]) <= float(p[\"optThreshold\"])]\n num = 0\n for p in props:\n if \"optThreshold\" in p:\n tr = p[\"optThreshold\"]\n elif \"optThreshold\" in p:\n tr = p[\"cdgp.optThreshold\"]\n else:\n raise Exception(\"No optThreshold in log file\")\n if float(p[\"result.best.mse\"]) <= tr:\n num += 1\n return num\n\ndef get_num_allPropertiesMet(props):\n props2 = [p for p in props if p[\"result.best.verificationDecision\"] == \"unsat\"]\n return len(props2)\n\ndef get_num_computed(filtered):\n return len(filtered)\ndef fun_successRate_full(filtered):\n if len(filtered) == 0:\n return \"-\"\n num_opt = get_num_optimal(filtered)\n return \"{0}/{1}\".format(str(num_opt), str(len(filtered)))\ndef get_successRate(filtered):\n num_opt = get_num_optimal(filtered)\n return float(num_opt) / float(len(filtered))\ndef fun_successRateMseOnly(filtered):\n if len(filtered) == 0:\n return \"-\"\n n = get_num_optimalOnlyMse(filtered)\n if n == 0:\n return \"-\"\n else:\n sr = n / float(len(filtered))\n return \"{0}\".format(\"%0.2f\" % round(sr, 2))\ndef fun_average_mse(filtered):\n res = 0.0\n num = 0\n # Sometimes there was \"inf\" in the results. We will ignore those elements.\n for p in filtered:\n x = float(p[\"result.best.mse\"])\n if not \"n\" in str(x):\n res += x\n num += 1\n else:\n print(\"Nan encountered\")\n if num == 0:\n return \"-\"\n else:\n return res / num\ndef fun_average_mse_sd(filtered):\n \"\"\"Returns average together with standard deviation.\"\"\"\n res = 0.0\n num = 0\n # Sometimes there was \"inf\" in the results. We will ignore those elements.\n for p in filtered:\n x = float(p[\"result.best.mse\"])\n if not \"n\" in str(x):\n res += x\n num += 1\n else:\n print(\"Nan encountered\")\n avg = res / num\n sd = 0.0\n for p in filtered:\n x = float(p[\"result.best.mse\"])\n if not \"n\" in str(x):\n sd += (x - avg) ** 2.0\n sd = math.sqrt(sd / num)\n if num == 0:\n return \"-\"\n else:\n return r\"${0} \\pm{1}$\".format(avg, sd)\n\ndef fun_successRate(filtered):\n if len(filtered) == 0:\n return \"-\"\n sr = get_successRate(filtered)\n return \"{0}\".format(\"%0.2f\" % round(sr, 2))\ndef fun_allPropertiesMet(filtered):\n if len(filtered) == 0:\n return \"-\"\n num_opt = get_num_allPropertiesMet(filtered)\n sr = float(num_opt) / float(len(filtered))\n return \"{0}\".format(\"%0.2f\" % round(sr, 2))\ndef get_stats_size(props):\n vals = [float(p[\"result.best.size\"]) for p in props]\n if len(vals) == 0:\n return \"-\"#-1.0, -1.0\n else:\n return str(int(round(np.mean(vals)))) #, np.std(vals)\ndef get_stats_sizeOnlySuccessful(props):\n vals = [float(p[\"result.best.size\"]) for p in props if is_verified_solution(p)]\n if len(vals) == 0:\n return \"-\"#-1.0, -1.0\n else:\n return str(int(round(np.mean(vals)))) #, np.std(vals)\ndef get_stats_maxSolverTime(props):\n if len(props) == 0 or \"solver.allTimesCountMap\" not in props[0]:\n return \"-\"\n times = []\n for p in props:\n timesMap = p[\"solver.allTimesCountMap\"]\n parts = timesMap.split(\", \")[-1].split(\",\")\n times.append(float(parts[0].replace(\"(\", \"\")))\n return \"%0.3f\" % max(times)\ndef get_stats_avgSolverTime(props):\n if len(props) == 0 or \"solver.allTimesCountMap\" not in props[0] or props[0][\"method\"] != \"CDGP\":\n return \"-\"\n sum = 0.0\n sumWeights = 0.0\n for p in props:\n timesMap = p[\"solver.allTimesCountMap\"]\n pairs = timesMap.split(\", \")\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(\",\")[0].replace(\"(\", \"\"))\n weight = float(x.split(\",\")[1].replace(\")\", \"\"))\n sum += time * weight\n sumWeights += weight\n if sumWeights == 0.0:\n return \"%0.3f\" % 0.0\n else:\n return \"%0.3f\" % (sum / sumWeights)\ndef get_avgSolverTotalCalls(props):\n if len(props) == 0 or \"solver.totalCalls\" not in props[0]:\n return \"-\"\n vals = [float(p[\"solver.totalCalls\"]) / 1000.0 for p in props]\n return \"%0.1f\" % round(np.mean(vals), 1) # \"%d\"\ndef get_numSolverCallsOverXs(props):\n if len(props) == 0 or \"solver.allTimesCountMap\" not in props[0]:\n return \"-\"\n TRESHOLD = 0.5\n sum = 0\n for p in props:\n timesMap = p[\"solver.allTimesCountMap\"]\n pairs = timesMap.split(\", \")\n if len(pairs) == 0:\n continue\n for x in pairs:\n time = float(x.split(\",\")[0].replace(\"(\", \"\"))\n if time > TRESHOLD:\n # print(\"Name of file: \" + p[\"thisFileName\"])\n weight = int(x.split(\",\")[1].replace(\")\", \"\"))\n sum += weight\n return sum\ndef get_avg_totalTests(props):\n vals = [float(p[\"tests.total\"]) for p in props]\n if len(vals) == 0:\n return \"-\" # -1.0, -1.0\n else:\n x = np.mean(vals)\n if x < 1e-5:\n x = 0.0\n return str(int(round(x))) #\"%0.1f\" % x\ndef get_avg_mse(props):\n vals = []\n for p in props:\n vals.append(float(p[\"result.best.mse\"]))\n if len(vals) == 0:\n return \"-\" # -1.0, -1.0\n else:\n return \"%0.5f\" % np.mean(vals) # , np.std(vals)\ndef get_avg_runtime_helper(vals):\n if len(vals) == 0:\n return \"n/a\" # -1.0, -1.0\n else:\n x = np.mean(vals)\n if x >= 10.0:\n return \"%d\" % x\n else:\n return \"%0.1f\" % x # , np.std(vals)\ndef get_avg_runtimeOnlySuccessful(props):\n if len(props) == 0:\n return \"-\"\n else:\n vals = [float(normalized_total_time(p, max_time=1800000)) / 1000.0 for p in props if is_verified_solution(p)]\n return get_avg_runtime_helper(vals)\ndef get_avg_runtime(props):\n if len(props) == 0:\n return \"-\"\n else:\n vals = [float(normalized_total_time(p, max_time=1800000)) / 1000.0 for p in props]\n return get_avg_runtime_helper(vals)\ndef get_avg_generation(props):\n if len(props) == 0:\n return \"-\"\n if len(props) > 0 and \"result.totalGenerations\" not in props[0]:\n return \"-\"\n vals = [float(p[\"result.totalGenerations\"]) for p in props]\n if len(vals) == 0:\n return \"-\"\n else:\n return str(int(round(np.mean(vals)))) #\"%0.1f\" % np.mean(vals) # , np.std(vals)\ndef get_avg_generationSuccessful(props):\n if len(props) == 0:\n return \"-\"\n else:\n vals = [float(p[\"result.best.generation\"]) for p in props if is_verified_solution(p)]\n if len(vals) == 0:\n return \"n/a\" # -1.0, -1.0\n else:\n return str(int(round(np.mean(vals)))) # \"%0.1f\" % np.mean(vals) # , np.std(vals)\ndef get_avg_evaluated(props):\n if len(props) == 0:\n return \"-\"\n vals = []\n for p in props:\n if p[\"evolutionMode\"] == \"steadyState\":\n vals.append(float(p[\"result.totalGenerations\"]))\n else:\n vals.append(float(p[\"result.totalGenerations\"]) * float(p[\"populationSize\"]))\n return str(int(round(np.mean(vals)))) #\"%0.1f\" % np.mean(vals) # , np.std(vals)\ndef get_avg_evaluatedSuccessful(props):\n if len(props) == 0:\n return \"-\"\n vals = []\n for p in props:\n if is_verified_solution(p):\n if p[\"evolutionMode\"] == \"steadyState\":\n vals.append(float(p[\"result.totalGenerations\"]))\n else:\n vals.append(float(p[\"result.totalGenerations\"]) * float(p[\"populationSize\"]))\n if len(vals) == 0:\n return \"n/a\" # -1.0, -1.0\n else:\n return str(int(round(np.mean(vals)))) # \"%0.1f\" % np.mean(vals) # , np.std(vals)\ndef get_avg_runtimePerProgram(props):\n if len(props) == 0:\n return \"-\" # -1.0, -1.0\n sAvgGen = get_avg_generation(props)\n if sAvgGen == \"-\" or sAvgGen is None:\n return \"-\"\n avgGen = float(sAvgGen) # avg number of generations in all runs\n avgRuntime = float(get_avg_runtime(props)) # avg runtime of all runs\n populationSize = float(props[0][\"populationSize\"])\n if props[0][\"evolutionMode\"] == \"steadyState\":\n approxNumPrograms = populationSize + avgGen # in steady state we have many generations, but in each of them created is one new program\n else:\n approxNumPrograms = populationSize * avgGen\n approxTimePerProgram = avgRuntime / approxNumPrograms\n return \"%0.3f\" % approxTimePerProgram\ndef get_sum_solverRestarts(props):\n if len(props) == 0:\n return \"-\"\n vals = [int(p[\"solver.totalRestarts\"]) for p in props if \"solver.totalRestarts\" in p]\n if len(vals) != len(props):\n print(\"WARNING: solver.totalRestarts was not present in all files.\")\n if len(vals) == 0:\n return \"0\"\n else:\n return str(np.sum(vals))\n\ndef print_solved_in_time(props, upper_time):\n if len(props) == 0:\n return\n # totalTimeSystem is in miliseconds\n solved = 0\n solvedRuns = 0\n num = 0\n for p in props:\n if p[\"result.best.isOptimal\"] == \"false\":\n continue\n num += 1\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solved += 1\n\n for p in props:\n if int(normalized_total_time(p, max_time=1800000)) <= upper_time:\n solvedRuns += 1\n print(\"\\nRuns which ended under {0} s: {1} / {2} ({3} %)\".format(upper_time / 1000.0, solvedRuns, len(props), solvedRuns / len(props)))\n print(\"Optimal solutions found under {0} s: {1} / {2} ({3} %)\\n\".format(upper_time / 1000.0, solved, num, solved / num))\n",
"step-ids": [
22,
30,
37,
44,
48
]
}
|
[
22,
30,
37,
44,
48
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def generate_modal():
return html.Div(id='markdown', className='modal', children=html.Div(id=
'markdown-container', className='markdown-container', children=[
html.Div(className='close-container', children=html.Button('Close',
id='markdown_close', n_clicks=0, className='closeButton')), html.
Div(className='markdown-text', children=dcc.Markdown(children=
"""
###### What is this mock app about?
This is a dashboard for monitoring real-time process quality along manufacture production line.
###### What does this app shows
Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.
The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.
The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will
trigger alerts instantly for a detailed checkup.
Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.
"""
))]))
<|reserved_special_token_1|>
<|reserved_special_token_0|>
def build_navbar():
return html.Div(id='banner', children=[html.Div(id='banner-text',
className='banner', children=[dbc.Row([dbc.Col(html.Div(html.H2(
'CBPM real-time display')), width=11), dbc.Col(html.Div(id=
'banner-logo', children=[html.Button(id='learn-more-button',
children='INFORMATION', n_clicks=0)]))])]), html.Div(className=
'banner2', children=[dbc.Row([dbc.Col(html.Div(daq.PowerButton(id=
'live_update_switch', on='True', size=50, color='#079407'), id=
'test_button', style={'padding': '10px 0px 0px 0px'}), width={
'size': 1}), dbc.Col(html.Div(children=[html.H2('Live update is:'),
html.H2(id='live_update_running', style={'margin-left': '1.0%',
'color': '#079407', 'font-weight': 'bold'}), html.H2(id=
'live_update_paused', style={'margin-left': '0.5%', 'color':
'#e0392a', 'font-weight': 'bold'})])), dbc.Col(html.Div(id=
'offline_store_df', style={'display': 'none'})), dbc.Col(
layout_common.dropdown_menu(), width=2)], no_gutters=True, justify=
'start')])])
def generate_modal():
return html.Div(id='markdown', className='modal', children=html.Div(id=
'markdown-container', className='markdown-container', children=[
html.Div(className='close-container', children=html.Button('Close',
id='markdown_close', n_clicks=0, className='closeButton')), html.
Div(className='markdown-text', children=dcc.Markdown(children=
"""
###### What is this mock app about?
This is a dashboard for monitoring real-time process quality along manufacture production line.
###### What does this app shows
Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.
The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.
The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will
trigger alerts instantly for a detailed checkup.
Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.
"""
))]))
<|reserved_special_token_1|>
import dash_html_components as html
import dash_core_components as dcc
import dash_daq as daq
import dash_bootstrap_components as dbc
import src.common.common_layout as layout_common
def build_navbar():
return html.Div(id='banner', children=[html.Div(id='banner-text',
className='banner', children=[dbc.Row([dbc.Col(html.Div(html.H2(
'CBPM real-time display')), width=11), dbc.Col(html.Div(id=
'banner-logo', children=[html.Button(id='learn-more-button',
children='INFORMATION', n_clicks=0)]))])]), html.Div(className=
'banner2', children=[dbc.Row([dbc.Col(html.Div(daq.PowerButton(id=
'live_update_switch', on='True', size=50, color='#079407'), id=
'test_button', style={'padding': '10px 0px 0px 0px'}), width={
'size': 1}), dbc.Col(html.Div(children=[html.H2('Live update is:'),
html.H2(id='live_update_running', style={'margin-left': '1.0%',
'color': '#079407', 'font-weight': 'bold'}), html.H2(id=
'live_update_paused', style={'margin-left': '0.5%', 'color':
'#e0392a', 'font-weight': 'bold'})])), dbc.Col(html.Div(id=
'offline_store_df', style={'display': 'none'})), dbc.Col(
layout_common.dropdown_menu(), width=2)], no_gutters=True, justify=
'start')])])
def generate_modal():
return html.Div(id='markdown', className='modal', children=html.Div(id=
'markdown-container', className='markdown-container', children=[
html.Div(className='close-container', children=html.Button('Close',
id='markdown_close', n_clicks=0, className='closeButton')), html.
Div(className='markdown-text', children=dcc.Markdown(children=
"""
###### What is this mock app about?
This is a dashboard for monitoring real-time process quality along manufacture production line.
###### What does this app shows
Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.
The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.
The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will
trigger alerts instantly for a detailed checkup.
Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.
"""
))]))
<|reserved_special_token_1|>
import dash_html_components as html
import dash_core_components as dcc
import dash_daq as daq
import dash_bootstrap_components as dbc
import src.common.common_layout as layout_common
def build_navbar():
return html.Div(
id="banner",
children=[
html.Div(
id="banner-text",
className="banner",
children=[
dbc.Row(
[
dbc.Col(html.Div(html.H2("CBPM real-time display")), width=11),
dbc.Col(
html.Div(
id="banner-logo",
children=[
html.Button(
id="learn-more-button", children="INFORMATION", n_clicks=0
),
],
),
)
],
),
],
),
html.Div(
className="banner2",
children=[
dbc.Row(
[
dbc.Col(
html.Div(
daq.PowerButton(
id='live_update_switch',
on='True',
size=50,
color='#079407',
# label='Label',
# labelPosition='top'
),
id='test_button',
style={'padding': '10px 0px 0px 0px'},
), width={"size": 1},
),
dbc.Col(
html.Div(
children=[
html.H2("Live update is:"),
html.H2(
id='live_update_running',
style={'margin-left': '1.0%', 'color': '#079407', 'font-weight': 'bold'},
),
html.H2(
id='live_update_paused',
style={'margin-left': '0.5%', 'color': '#e0392a', 'font-weight': 'bold'},
),
],
), #style={'padding': '0px 1000px 0px 0px'},
),
dbc.Col(
html.Div(id='offline_store_df', style={'display': 'none'}),
),
dbc.Col(
layout_common.dropdown_menu(), width=2,
)
], no_gutters=True, justify='start',
)
]
)
],
)
def generate_modal():
return html.Div(
id="markdown",
className="modal",
children=(
html.Div(
id="markdown-container",
className="markdown-container",
children=[
html.Div(
className="close-container",
children=html.Button(
"Close",
id="markdown_close",
n_clicks=0,
className="closeButton",
),
),
html.Div(
className="markdown-text",
children=dcc.Markdown(
children=(
"""
###### What is this mock app about?
This is a dashboard for monitoring real-time process quality along manufacture production line.
###### What does this app shows
Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.
The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.
The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will
trigger alerts instantly for a detailed checkup.
Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.
"""
)
),
),
],
)
),
)
|
flexible
|
{
"blob_id": "f9dd20a3b72c0c8e72029459244486f31eaff536",
"index": 9411,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\ndef generate_modal():\n return html.Div(id='markdown', className='modal', children=html.Div(id=\n 'markdown-container', className='markdown-container', children=[\n html.Div(className='close-container', children=html.Button('Close',\n id='markdown_close', n_clicks=0, className='closeButton')), html.\n Div(className='markdown-text', children=dcc.Markdown(children=\n \"\"\"\n ###### What is this mock app about?\n This is a dashboard for monitoring real-time process quality along manufacture production line.\n ###### What does this app shows\n Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.\n The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.\n The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will\n trigger alerts instantly for a detailed checkup.\n\n Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.\n \"\"\"\n ))]))\n",
"step-3": "<mask token>\n\n\ndef build_navbar():\n return html.Div(id='banner', children=[html.Div(id='banner-text',\n className='banner', children=[dbc.Row([dbc.Col(html.Div(html.H2(\n 'CBPM real-time display')), width=11), dbc.Col(html.Div(id=\n 'banner-logo', children=[html.Button(id='learn-more-button',\n children='INFORMATION', n_clicks=0)]))])]), html.Div(className=\n 'banner2', children=[dbc.Row([dbc.Col(html.Div(daq.PowerButton(id=\n 'live_update_switch', on='True', size=50, color='#079407'), id=\n 'test_button', style={'padding': '10px 0px 0px 0px'}), width={\n 'size': 1}), dbc.Col(html.Div(children=[html.H2('Live update is:'),\n html.H2(id='live_update_running', style={'margin-left': '1.0%',\n 'color': '#079407', 'font-weight': 'bold'}), html.H2(id=\n 'live_update_paused', style={'margin-left': '0.5%', 'color':\n '#e0392a', 'font-weight': 'bold'})])), dbc.Col(html.Div(id=\n 'offline_store_df', style={'display': 'none'})), dbc.Col(\n layout_common.dropdown_menu(), width=2)], no_gutters=True, justify=\n 'start')])])\n\n\ndef generate_modal():\n return html.Div(id='markdown', className='modal', children=html.Div(id=\n 'markdown-container', className='markdown-container', children=[\n html.Div(className='close-container', children=html.Button('Close',\n id='markdown_close', n_clicks=0, className='closeButton')), html.\n Div(className='markdown-text', children=dcc.Markdown(children=\n \"\"\"\n ###### What is this mock app about?\n This is a dashboard for monitoring real-time process quality along manufacture production line.\n ###### What does this app shows\n Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.\n The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.\n The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will\n trigger alerts instantly for a detailed checkup.\n\n Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.\n \"\"\"\n ))]))\n",
"step-4": "import dash_html_components as html\nimport dash_core_components as dcc\nimport dash_daq as daq\nimport dash_bootstrap_components as dbc\nimport src.common.common_layout as layout_common\n\n\ndef build_navbar():\n return html.Div(id='banner', children=[html.Div(id='banner-text',\n className='banner', children=[dbc.Row([dbc.Col(html.Div(html.H2(\n 'CBPM real-time display')), width=11), dbc.Col(html.Div(id=\n 'banner-logo', children=[html.Button(id='learn-more-button',\n children='INFORMATION', n_clicks=0)]))])]), html.Div(className=\n 'banner2', children=[dbc.Row([dbc.Col(html.Div(daq.PowerButton(id=\n 'live_update_switch', on='True', size=50, color='#079407'), id=\n 'test_button', style={'padding': '10px 0px 0px 0px'}), width={\n 'size': 1}), dbc.Col(html.Div(children=[html.H2('Live update is:'),\n html.H2(id='live_update_running', style={'margin-left': '1.0%',\n 'color': '#079407', 'font-weight': 'bold'}), html.H2(id=\n 'live_update_paused', style={'margin-left': '0.5%', 'color':\n '#e0392a', 'font-weight': 'bold'})])), dbc.Col(html.Div(id=\n 'offline_store_df', style={'display': 'none'})), dbc.Col(\n layout_common.dropdown_menu(), width=2)], no_gutters=True, justify=\n 'start')])])\n\n\ndef generate_modal():\n return html.Div(id='markdown', className='modal', children=html.Div(id=\n 'markdown-container', className='markdown-container', children=[\n html.Div(className='close-container', children=html.Button('Close',\n id='markdown_close', n_clicks=0, className='closeButton')), html.\n Div(className='markdown-text', children=dcc.Markdown(children=\n \"\"\"\n ###### What is this mock app about?\n This is a dashboard for monitoring real-time process quality along manufacture production line.\n ###### What does this app shows\n Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.\n The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.\n The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will\n trigger alerts instantly for a detailed checkup.\n\n Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.\n \"\"\"\n ))]))\n",
"step-5": "import dash_html_components as html\nimport dash_core_components as dcc\nimport dash_daq as daq\nimport dash_bootstrap_components as dbc\n\nimport src.common.common_layout as layout_common\n\n\ndef build_navbar():\n return html.Div(\n id=\"banner\",\n children=[\n html.Div(\n id=\"banner-text\",\n className=\"banner\",\n children=[\n dbc.Row(\n [\n dbc.Col(html.Div(html.H2(\"CBPM real-time display\")), width=11),\n dbc.Col(\n html.Div(\n id=\"banner-logo\",\n children=[\n html.Button(\n id=\"learn-more-button\", children=\"INFORMATION\", n_clicks=0\n ),\n ],\n ),\n )\n ],\n ),\n ],\n ),\n html.Div(\n className=\"banner2\",\n children=[\n dbc.Row(\n [\n dbc.Col(\n html.Div(\n daq.PowerButton(\n id='live_update_switch',\n on='True',\n size=50,\n color='#079407',\n # label='Label',\n # labelPosition='top'\n ),\n id='test_button',\n style={'padding': '10px 0px 0px 0px'},\n ), width={\"size\": 1},\n ),\n dbc.Col(\n html.Div(\n children=[\n html.H2(\"Live update is:\"),\n html.H2(\n id='live_update_running',\n style={'margin-left': '1.0%', 'color': '#079407', 'font-weight': 'bold'},\n ),\n html.H2(\n id='live_update_paused',\n style={'margin-left': '0.5%', 'color': '#e0392a', 'font-weight': 'bold'},\n ),\n ],\n ), #style={'padding': '0px 1000px 0px 0px'},\n ),\n dbc.Col(\n html.Div(id='offline_store_df', style={'display': 'none'}),\n ),\n dbc.Col(\n layout_common.dropdown_menu(), width=2,\n )\n ], no_gutters=True, justify='start',\n )\n ]\n )\n ],\n )\n\ndef generate_modal():\n return html.Div(\n id=\"markdown\",\n className=\"modal\",\n children=(\n html.Div(\n id=\"markdown-container\",\n className=\"markdown-container\",\n children=[\n html.Div(\n className=\"close-container\",\n children=html.Button(\n \"Close\",\n id=\"markdown_close\",\n n_clicks=0,\n className=\"closeButton\",\n ),\n ),\n html.Div(\n className=\"markdown-text\",\n children=dcc.Markdown(\n children=(\n \"\"\"\n ###### What is this mock app about?\n This is a dashboard for monitoring real-time process quality along manufacture production line.\n ###### What does this app shows\n Click on buttons in `Parameter` column to visualize details of measurement trendlines on the bottom panel.\n The sparkline on top panel and control chart on bottom panel show Shewhart process monitor using mock data.\n The trend is updated every other second to simulate real-time measurements. Data falling outside of six-sigma control limit are signals indicating 'Out of Control(OOC)', and will\n trigger alerts instantly for a detailed checkup.\n\n Operators may stop measurement by clicking on `Stop` button, and edit specification parameters by clicking specification tab.\n \"\"\"\n )\n ),\n ),\n ],\n )\n ),\n )",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
from .auth import Auth
from .banDetection import BanDetectionThread
from .botLogging import BotLoggingThread
from .clientLauncher import ClientLauncher
from .log import LogThread, Log
from .mainThread import MainThread
from .nexonServer import NexonServer
from .tmLogging import TMLoggingThread
from .worldCheckboxStatus import WorldCheckBoxThread
from .setStartup import setStartupThread
|
normal
|
{
"blob_id": "b7038ad73bf0e284474f0d89d6c34967d39541c0",
"index": 6566,
"step-1": "<mask token>\n",
"step-2": "from .auth import Auth\nfrom .banDetection import BanDetectionThread\nfrom .botLogging import BotLoggingThread\nfrom .clientLauncher import ClientLauncher\nfrom .log import LogThread, Log\nfrom .mainThread import MainThread\nfrom .nexonServer import NexonServer\nfrom .tmLogging import TMLoggingThread\nfrom .worldCheckboxStatus import WorldCheckBoxThread\nfrom .setStartup import setStartupThread\n",
"step-3": null,
"step-4": null,
"step-5": null,
"step-ids": [
0,
1
]
}
|
[
0,
1
] |
from rest_framework import serializers
from .models import data
from django.contrib.auth.models import User
class dataSerializer(serializers.ModelSerializer):
class Meta:
model = data
fields = ['id', 'task', 'duedate', 'person', 'done', 'task_user']
class userSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = ['username', 'password', 'email']
|
normal
|
{
"blob_id": "972c479ea40232e14fbf678ca2ccf9716e473fe8",
"index": 9736,
"step-1": "<mask token>\n",
"step-2": "<mask token>\n\n\nclass userSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = User\n fields = ['username', 'password', 'email']\n",
"step-3": "<mask token>\n\n\nclass dataSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = data\n fields = ['id', 'task', 'duedate', 'person', 'done', 'task_user']\n\n\nclass userSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = User\n fields = ['username', 'password', 'email']\n",
"step-4": "from rest_framework import serializers\nfrom .models import data\nfrom django.contrib.auth.models import User\n\n\nclass dataSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = data\n fields = ['id', 'task', 'duedate', 'person', 'done', 'task_user']\n\n\nclass userSerializer(serializers.ModelSerializer):\n\n\n class Meta:\n model = User\n fields = ['username', 'password', 'email']\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
<|reserved_special_token_0|>
setup(name='sk_processor', packages=find_packages())
<|reserved_special_token_1|>
from setuptools import setup, find_packages
setup(name='sk_processor', packages=find_packages())
<|reserved_special_token_1|>
from setuptools import setup, find_packages
setup(name="sk_processor", packages=find_packages())
|
flexible
|
{
"blob_id": "de884413dcbd0e89e8bfcf5657fe189156d9a661",
"index": 1837,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nsetup(name='sk_processor', packages=find_packages())\n",
"step-3": "from setuptools import setup, find_packages\nsetup(name='sk_processor', packages=find_packages())\n",
"step-4": "from setuptools import setup, find_packages\n\nsetup(name=\"sk_processor\", packages=find_packages())",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
# Filename : var.py
#整数
i = 5
print(i)
i = i + 1
print(i)
#浮点数
i = 1.1
print(i)
#python的弱语言特性，可以随时改变变量的类型
i = 'change i to a string '
print(i)
s = 'hello'#单引号
print(s)
s = "hello"#双引号
print(s)
#三引号为多行字符串
s = '''This is a "multi-line" string.
This is the second line.'''
print(s)
s = '\''#斜杠用于转义
print(s)
#r或R开头的字符串表示自然字符串，后面的斜杠不转义
s = r'\n'
print(s)
s = '这是一个行\
连接符的例子'
print(s)
#斜杠在这里是行连接符，可以把一行中太长的代码分为多行不影响实际意义
#强烈建议坚持在每个物理行只写一句逻辑行。仅仅当逻辑行太长的时候，在多于一个物理行写一个逻辑行
#有一种暗示的假设，可以使你不需要使用反斜杠。这种情况出现在逻辑行中使用了圆括号、方括号或波形括号的时候。这被称为暗示的行连接
i = \
55
print(i)
#同一层次的语句必须有相同的缩进。每一组这样的语句称为一个块,错误的缩进会引发错误
print('value is',i)
print('value is',i)
|
normal
|
{
"blob_id": "bea7853d1f3eac50825bc6eb10438f3f656d6d04",
"index": 1947,
"step-1": "<mask token>\n",
"step-2": "<mask token>\nprint(i)\n<mask token>\nprint(i)\n<mask token>\nprint(i)\n<mask token>\nprint(i)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(s)\n<mask token>\nprint(i)\nprint('value is', i)\nprint('value is', i)\n",
"step-3": "i = 5\nprint(i)\ni = i + 1\nprint(i)\ni = 1.1\nprint(i)\ni = 'change i to a string '\nprint(i)\ns = 'hello'\nprint(s)\ns = 'hello'\nprint(s)\ns = \"\"\"This is a \"multi-line\" string.\nThis is the second line.\"\"\"\nprint(s)\ns = \"'\"\nprint(s)\ns = '\\\\n'\nprint(s)\ns = '这是一个行连接符的例子'\nprint(s)\ni = 55\nprint(i)\nprint('value is', i)\nprint('value is', i)\n",
"step-4": "# Filename : var.py\n\n#整数\ni = 5\nprint(i)\ni = i + 1\nprint(i)\n\n#浮点数\ni = 1.1\nprint(i)\n\n#python的弱语言特性，可以随时改变变量的类型\ni = 'change i to a string '\nprint(i)\n\n\ns = 'hello'#单引号\nprint(s)\ns = \"hello\"#双引号\nprint(s)\n\n#三引号为多行字符串\ns = '''This is a \"multi-line\" string.\nThis is the second line.'''\nprint(s)\n\ns = '\\''#斜杠用于转义\nprint(s)\n#r或R开头的字符串表示自然字符串，后面的斜杠不转义\ns = r'\\n'\nprint(s)\n\ns = '这是一个行\\\n连接符的例子'\nprint(s)\n\n#斜杠在这里是行连接符，可以把一行中太长的代码分为多行不影响实际意义\n#强烈建议坚持在每个物理行只写一句逻辑行。仅仅当逻辑行太长的时候，在多于一个物理行写一个逻辑行\n#有一种暗示的假设，可以使你不需要使用反斜杠。这种情况出现在逻辑行中使用了圆括号、方括号或波形括号的时候。这被称为暗示的行连接\ni = \\\n55\nprint(i)\n\n#同一层次的语句必须有相同的缩进。每一组这样的语句称为一个块,错误的缩进会引发错误\nprint('value is',i)\nprint('value is',i)\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
<|reserved_special_token_0|>
<|reserved_special_token_1|>
class Solution:
def swapPairs(self, head: ListNode) ->ListNode:
dummy_head = ListNode(0)
dummy_head.next = head
pre = dummy_head
cur = head
while cur and cur.next:
next = cur.next
next_next = next.next
pre.next = next
next.next = cur
cur.next = next_next
pre = cur
cur = next_next
return dummy_head.next
<|reserved_special_token_1|>
# Definition for singly-linked list.
# class ListNode:
# def __init__(self, val=0, next=None):
# self.val = val
# self.next = next
class Solution:
def swapPairs(self, head: ListNode) -> ListNode:
dummy_head=ListNode(0)
dummy_head.next=head
pre=dummy_head
cur=head
while cur and cur.next:
next=cur.next
next_next=next.next
pre.next=next
next.next=cur
cur.next=next_next
pre=cur
cur=next_next
return dummy_head.next
# ！！！！！！！！！！！！！！反转链表套路：
# 虚拟头结点
# 在循环外定义pre cur，在循环内求next和next_next(如果有需要)，这样就可以cur and cur.next作为判断while条件
|
flexible
|
{
"blob_id": "4afc2ceed860c20af071e1d9ccaca17973cb9a8e",
"index": 7553,
"step-1": "<mask token>\n",
"step-2": "class Solution:\n <mask token>\n",
"step-3": "class Solution:\n\n def swapPairs(self, head: ListNode) ->ListNode:\n dummy_head = ListNode(0)\n dummy_head.next = head\n pre = dummy_head\n cur = head\n while cur and cur.next:\n next = cur.next\n next_next = next.next\n pre.next = next\n next.next = cur\n cur.next = next_next\n pre = cur\n cur = next_next\n return dummy_head.next\n",
"step-4": "# Definition for singly-linked list.\n# class ListNode:\n# def __init__(self, val=0, next=None):\n# self.val = val\n# self.next = next\nclass Solution:\n def swapPairs(self, head: ListNode) -> ListNode:\n dummy_head=ListNode(0)\n dummy_head.next=head\n pre=dummy_head\n cur=head\n while cur and cur.next:\n next=cur.next\n next_next=next.next\n pre.next=next\n next.next=cur\n cur.next=next_next\n pre=cur\n cur=next_next\n return dummy_head.next\n# ！！！！！！！！！！！！！！反转链表套路： \n# 虚拟头结点\n# 在循环外定义pre cur，在循环内求next和next_next(如果有需要)，这样就可以cur and cur.next作为判断while条件\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
from flask import Flask
import rq
from redis import Redis
from app.lib.job import Job
from app.config import Config
app = Flask(__name__)
app.config.from_object(Config)
app.redis = Redis.from_url('redis://')
app.task_queue = rq.Queue('ocr-tasks', connection=app.redis,
default_timeout=43200)
app.task_queue.empty()
app.eval_queue = rq.Queue('ocr-evals', connection=app.redis,
default_timeout=43200)
app.eval_queue.empty()
app.job_id2file = {}
app.job_file2id = {}
app.job_id2err = {}
app.eval_id2file = {}
app.eval_file2id = {}
app.eval_id2err = {}
from app import routes
from app.api import bp as api_bp
app.register_blueprint(api_bp, url_prefix='/api')
|
normal
|
{
"blob_id": "14e336005da1f1f3f54ea5f2892c27b58f2babf0",
"index": 4794,
"step-1": "<mask token>\n",
"step-2": "<mask token>\napp.config.from_object(Config)\n<mask token>\napp.task_queue.empty()\n<mask token>\napp.eval_queue.empty()\n<mask token>\napp.register_blueprint(api_bp, url_prefix='/api')\n",
"step-3": "<mask token>\napp = Flask(__name__)\napp.config.from_object(Config)\napp.redis = Redis.from_url('redis://')\napp.task_queue = rq.Queue('ocr-tasks', connection=app.redis,\n default_timeout=43200)\napp.task_queue.empty()\napp.eval_queue = rq.Queue('ocr-evals', connection=app.redis,\n default_timeout=43200)\napp.eval_queue.empty()\napp.job_id2file = {}\napp.job_file2id = {}\napp.job_id2err = {}\napp.eval_id2file = {}\napp.eval_file2id = {}\napp.eval_id2err = {}\n<mask token>\napp.register_blueprint(api_bp, url_prefix='/api')\n",
"step-4": "from flask import Flask\nimport rq\nfrom redis import Redis\nfrom app.lib.job import Job\nfrom app.config import Config\napp = Flask(__name__)\napp.config.from_object(Config)\napp.redis = Redis.from_url('redis://')\napp.task_queue = rq.Queue('ocr-tasks', connection=app.redis,\n default_timeout=43200)\napp.task_queue.empty()\napp.eval_queue = rq.Queue('ocr-evals', connection=app.redis,\n default_timeout=43200)\napp.eval_queue.empty()\napp.job_id2file = {}\napp.job_file2id = {}\napp.job_id2err = {}\napp.eval_id2file = {}\napp.eval_file2id = {}\napp.eval_id2err = {}\nfrom app import routes\nfrom app.api import bp as api_bp\napp.register_blueprint(api_bp, url_prefix='/api')\n",
"step-5": null,
"step-ids": [
0,
1,
2,
3
]
}
|
[
0,
1,
2,
3
] |
#!/usr/bin/env python3
import os
import subprocess
import emailgen
#
# Header information
#
recipient = input("recipient: ")
sender = input("sender: ")
password = input("sender password: ")
subject = "hdd temp alert"
#
# Get hdd temp, format for email
#
output = subprocess.check_output('sudo hddtemp /dev/sda /dev/sdb /dev/sdc', shell=True)
text = output.decode('utf-8')
#
# Email requires ascii
#
text = text.encode('ascii','ignore')
text = text.decode('ascii')
#
# Add descriptive information to text
#
text += "\nHostname: " + os.uname().nodename
#
# Call sendAlert function
#
emailgen.sendAlert(recipient, subject, text, sender, password)
|
normal
|
{
"blob_id": "26a6fe0b2a98aa77b63a336cd6c2afcfe81d9058",
"index": 7680,
"step-1": "<mask token>\n",
"step-2": "<mask token>\ntext += '\\nHostname: ' + os.uname().nodename\nemailgen.sendAlert(recipient, subject, text, sender, password)\n",
"step-3": "<mask token>\nrecipient = input('recipient: ')\nsender = input('sender: ')\npassword = input('sender password: ')\nsubject = 'hdd temp alert'\noutput = subprocess.check_output('sudo hddtemp /dev/sda /dev/sdb /dev/sdc',\n shell=True)\ntext = output.decode('utf-8')\ntext = text.encode('ascii', 'ignore')\ntext = text.decode('ascii')\ntext += '\\nHostname: ' + os.uname().nodename\nemailgen.sendAlert(recipient, subject, text, sender, password)\n",
"step-4": "import os\nimport subprocess\nimport emailgen\nrecipient = input('recipient: ')\nsender = input('sender: ')\npassword = input('sender password: ')\nsubject = 'hdd temp alert'\noutput = subprocess.check_output('sudo hddtemp /dev/sda /dev/sdb /dev/sdc',\n shell=True)\ntext = output.decode('utf-8')\ntext = text.encode('ascii', 'ignore')\ntext = text.decode('ascii')\ntext += '\\nHostname: ' + os.uname().nodename\nemailgen.sendAlert(recipient, subject, text, sender, password)\n",
"step-5": "#!/usr/bin/env python3\nimport os\nimport subprocess\nimport emailgen\n\n\n#\n# Header information\n#\nrecipient = input(\"recipient: \")\nsender = input(\"sender: \")\npassword = input(\"sender password: \")\nsubject = \"hdd temp alert\"\n\n#\n# Get hdd temp, format for email\n#\noutput = subprocess.check_output('sudo hddtemp /dev/sda /dev/sdb /dev/sdc', shell=True)\ntext = output.decode('utf-8')\n\n#\n# Email requires ascii\n#\ntext = text.encode('ascii','ignore')\ntext = text.decode('ascii')\n\n#\n# Add descriptive information to text\n#\ntext += \"\\nHostname: \" + os.uname().nodename\n\n#\n# Call sendAlert function\n#\nemailgen.sendAlert(recipient, subject, text, sender, password)\n",
"step-ids": [
0,
1,
2,
3,
4
]
}
|
[
0,
1,
2,
3,
4
] |
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