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train | _assert_input_is_valid | Called by the `validating_wrapper` in the first step (a) `apply_on_each_func_args` for each function input before
executing the function. It simply delegates to the validator. The signature of this function is hardcoded to
correspond to `apply_on_each_func_args`'s behaviour and should therefore not be changed.
... | valid8/entry_points_annotations.py | def _assert_input_is_valid(input_value, # type: Any
validators, # type: List[InputValidator]
validated_func, # type: Callable
input_name # type: str
):
"""
Called by the `validating_wrappe... | def _assert_input_is_valid(input_value, # type: Any
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input_name # type: str
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train | InputValidationError.get_what_txt | Overrides the base behaviour defined in ValidationError in order to add details about the function.
:return: | valid8/entry_points_annotations.py | def get_what_txt(self):
"""
Overrides the base behaviour defined in ValidationError in order to add details about the function.
:return:
"""
return 'input [{var}] for function [{func}]'.format(var=self.get_variable_str(),
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Overrides the base behaviour defined in ValidationError in order to add details about the function.
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train | ClassFieldValidationError.get_what_txt | Overrides the base behaviour defined in ValidationError in order to add details about the class field.
:return: | valid8/entry_points_annotations.py | def get_what_txt(self):
"""
Overrides the base behaviour defined in ValidationError in order to add details about the class field.
:return:
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return 'field [{field}] for class [{clazz}]'.format(field=self.get_variable_str(),
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train | generate_nonce_timestamp | Generate unique nonce with counter, uuid and rng. | cryptoshop/_nonce_engine.py | def generate_nonce_timestamp():
""" Generate unique nonce with counter, uuid and rng."""
global count
rng = botan.rng().get(30)
uuid4 = uuid.uuid4().bytes # 16 byte
tmpnonce = (bytes(str(count).encode('utf-8'))) + uuid4 + rng
nonce = tmpnonce[:41] # 41 byte (328 bit)
count += 1
return ... | def generate_nonce_timestamp():
""" Generate unique nonce with counter, uuid and rng."""
global count
rng = botan.rng().get(30)
uuid4 = uuid.uuid4().bytes # 16 byte
tmpnonce = (bytes(str(count).encode('utf-8'))) + uuid4 + rng
nonce = tmpnonce[:41] # 41 byte (328 bit)
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train | dict_merge | recursively merges dict's. not just simple a['key'] = b['key'], if
both a and bhave a key who's value is a dict then dict_merge is called
on both values and the result stored in the returned dictionary. | dci/common/schemas.py | def dict_merge(*dict_list):
"""recursively merges dict's. not just simple a['key'] = b['key'], if
both a and bhave a key who's value is a dict then dict_merge is called
on both values and the result stored in the returned dictionary.
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result = collections.defaultdict(dict)
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train | schedule_jobs | Dispatch jobs to remotecis.
The remoteci can use this method to request a new job.
Before a job is dispatched, the server will flag as 'killed' all the
running jobs that were associated with the remoteci. This is because they
will never be finished. | dci/api/v1/jobs.py | def schedule_jobs(user):
"""Dispatch jobs to remotecis.
The remoteci can use this method to request a new job.
Before a job is dispatched, the server will flag as 'killed' all the
running jobs that were associated with the remoteci. This is because they
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"""
values ... | def schedule_jobs(user):
"""Dispatch jobs to remotecis.
The remoteci can use this method to request a new job.
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running jobs that were associated with the remoteci. This is because they
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"""
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train | create_new_update_job_from_an_existing_job | Create a new job in the same topic as the job_id provided and
associate the latest components of this topic. | dci/api/v1/jobs.py | def create_new_update_job_from_an_existing_job(user, job_id):
"""Create a new job in the same topic as the job_id provided and
associate the latest components of this topic."""
values = {
'id': utils.gen_uuid(),
'created_at': datetime.datetime.utcnow().isoformat(),
'updated_at': dat... | def create_new_update_job_from_an_existing_job(user, job_id):
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train | create_new_upgrade_job_from_an_existing_job | Create a new job in the 'next topic' of the topic of
the provided job_id. | dci/api/v1/jobs.py | def create_new_upgrade_job_from_an_existing_job(user):
"""Create a new job in the 'next topic' of the topic of
the provided job_id."""
values = schemas.job_upgrade.post(flask.request.json)
values.update({
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'created_at': datetime.datetime.utcnow().isoformat(),
... | def create_new_upgrade_job_from_an_existing_job(user):
"""Create a new job in the 'next topic' of the topic of
the provided job_id."""
values = schemas.job_upgrade.post(flask.request.json)
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train | get_all_jobs | Get all jobs.
If topic_id is not None, then return all the jobs with a topic
pointed by topic_id. | dci/api/v1/jobs.py | def get_all_jobs(user, topic_id=None):
"""Get all jobs.
If topic_id is not None, then return all the jobs with a topic
pointed by topic_id.
"""
# get the diverse parameters
args = schemas.args(flask.request.args.to_dict())
# build the query thanks to the QueryBuilder class
query = v1_u... | def get_all_jobs(user, topic_id=None):
"""Get all jobs.
If topic_id is not None, then return all the jobs with a topic
pointed by topic_id.
"""
# get the diverse parameters
args = schemas.args(flask.request.args.to_dict())
# build the query thanks to the QueryBuilder class
query = v1_u... | [
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train | update_job_by_id | Update a job | dci/api/v1/jobs.py | def update_job_by_id(user, job_id):
"""Update a job
"""
# get If-Match header
if_match_etag = utils.check_and_get_etag(flask.request.headers)
# get the diverse parameters
values = schemas.job.put(flask.request.json)
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
job = dict(job... | def update_job_by_id(user, job_id):
"""Update a job
"""
# get If-Match header
if_match_etag = utils.check_and_get_etag(flask.request.headers)
# get the diverse parameters
values = schemas.job.put(flask.request.json)
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
job = dict(job... | [
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train | get_all_results_from_jobs | Get all results from job. | dci/api/v1/jobs.py | def get_all_results_from_jobs(user, j_id):
"""Get all results from job.
"""
job = v1_utils.verify_existence_and_get(j_id, _TABLE)
if not user.is_in_team(job['team_id']) and not user.is_read_only_user():
raise dci_exc.Unauthorized()
# get testscases from tests_results
query = sql.selec... | def get_all_results_from_jobs(user, j_id):
"""Get all results from job.
"""
job = v1_utils.verify_existence_and_get(j_id, _TABLE)
if not user.is_in_team(job['team_id']) and not user.is_read_only_user():
raise dci_exc.Unauthorized()
# get testscases from tests_results
query = sql.selec... | [
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train | get_tags_from_job | Retrieve all tags attached to a job. | dci/api/v1/jobs.py | def get_tags_from_job(user, job_id):
"""Retrieve all tags attached to a job."""
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
if not user.is_in_team(job['team_id']) and not user.is_read_only_user():
raise dci_exc.Unauthorized()
JTT = models.JOIN_JOBS_TAGS
query = (sql.select([mod... | def get_tags_from_job(user, job_id):
"""Retrieve all tags attached to a job."""
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
if not user.is_in_team(job['team_id']) and not user.is_read_only_user():
raise dci_exc.Unauthorized()
JTT = models.JOIN_JOBS_TAGS
query = (sql.select([mod... | [
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train | add_tag_to_job | Add a tag to a job. | dci/api/v1/jobs.py | def add_tag_to_job(user, job_id):
"""Add a tag to a job."""
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
if not user.is_in_team(job['team_id']):
raise dci_exc.Unauthorized()
values = {
'job_id': job_id
}
job_tagged = tags.add_tag_to_resource(values, models.JOIN_JOBS... | def add_tag_to_job(user, job_id):
"""Add a tag to a job."""
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
if not user.is_in_team(job['team_id']):
raise dci_exc.Unauthorized()
values = {
'job_id': job_id
}
job_tagged = tags.add_tag_to_resource(values, models.JOIN_JOBS... | [
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train | delete_tag_from_job | Delete a tag from a job. | dci/api/v1/jobs.py | def delete_tag_from_job(user, job_id, tag_id):
"""Delete a tag from a job."""
_JJT = models.JOIN_JOBS_TAGS
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
if not user.is_in_team(job['team_id']):
raise dci_exc.Unauthorized()
v1_utils.verify_existence_and_get(tag_id, models.TAGS)
... | def delete_tag_from_job(user, job_id, tag_id):
"""Delete a tag from a job."""
_JJT = models.JOIN_JOBS_TAGS
job = v1_utils.verify_existence_and_get(job_id, _TABLE)
if not user.is_in_team(job['team_id']):
raise dci_exc.Unauthorized()
v1_utils.verify_existence_and_get(tag_id, models.TAGS)
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train | ElementTreeAdapter._lookup_node_parent | Return the parent of the given node, based on an internal dictionary
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train | get_to_purge_archived_resources | List the entries to be purged from the database. | dci/api/v1/base.py | def get_to_purge_archived_resources(user, table):
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if user.is_not_super_admin():
raise dci_exc.Unauthorized()
archived_resources = get_archived_resources(table)
return flask.jsonify({table.name: archived_resources,
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archived_resources = get_archived_resources(table)
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train | purge_archived_resources | Remove the entries to be purged from the database. | dci/api/v1/base.py | def purge_archived_resources(user, table):
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train | refresh_api_secret | Refresh the resource API Secret. | dci/api/v1/base.py | def refresh_api_secret(user, resource, table):
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train | npm | Generate a package.json file. | invenio_assets/cli.py | def npm(package_json, output_file, pinned_file):
"""Generate a package.json file."""
amd_build_deprecation_warning()
try:
version = get_distribution(current_app.name).version
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version = ''
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amd_build_deprecation_warning()
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train | PingdomCheck.getAnalyses | Returns a list of the latest root cause analysis results for a
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* limit -- Limits the number of returned results to the
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Type: Integer
Default: 100
* offset -- O... | pingdomlib/check.py | def getAnalyses(self, **kwargs):
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specified check.
Optional Parameters:
* limit -- Limits the number of returned results to the
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Type: Integer
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train | PingdomCheck.getDetails | Update check details, returns dictionary of details | pingdomlib/check.py | def getDetails(self):
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response = self.pingdom.request('GET', 'checks/%s' % self.id)
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train | PingdomCheck.probes | Get a list of probes that performed tests for a specified check
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"""Get a list of probes that performed tests for a specified check
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train | PingdomCheck.publishPublicReport | Activate public report for this check.
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"""Activate public report for this check.
Returns status message"""
response = self.pingdom.request('PUT', 'reports.public/%s' % self.id)
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train | PingdomCheck.removePublicReport | Deactivate public report for this check.
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"""Deactivate public report for this check.
Returns status message"""
response = self.pingdom.request('DELETE',
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return response.json()['message'] | def removePublicReport(self):
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response = self.pingdom.request('DELETE',
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train | extract_deps | Extract the dependencies from the bundle and its sub-bundles. | invenio_assets/npm.py | def extract_deps(bundles, log=None):
"""Extract the dependencies from the bundle and its sub-bundles."""
def _flatten(bundle):
deps = []
if hasattr(bundle, 'npm'):
deps.append(bundle.npm)
for content in bundle.contents:
if isinstance(content, BundleBase):
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"""Extract the dependencies from the bundle and its sub-bundles."""
def _flatten(bundle):
deps = []
if hasattr(bundle, 'npm'):
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train | make_semver | Make a semantic version from Python PEP440 version.
Semantic versions does not handle post-releases. | invenio_assets/npm.py | def make_semver(version_str):
"""Make a semantic version from Python PEP440 version.
Semantic versions does not handle post-releases.
"""
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try:
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"""Make a semantic version from Python PEP440 version.
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"""
v = parse_version(version_str)
major = v._version.release[0]
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minor = v._version.release[1]
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train | get_max_size | Calculate the max number of item that an option can stored in the pool at give time.
This is to limit the pool size to POOL_SIZE
Args:
option_index (int): the index of the option to calculate the size for
pool (dict): answer pool
num_option (int): total number of options available for ... | ubcpi/answer_pool.py | def get_max_size(pool, num_option, item_length):
"""
Calculate the max number of item that an option can stored in the pool at give time.
This is to limit the pool size to POOL_SIZE
Args:
option_index (int): the index of the option to calculate the size for
pool (dict): answer pool
... | def get_max_size(pool, num_option, item_length):
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Calculate the max number of item that an option can stored in the pool at give time.
This is to limit the pool size to POOL_SIZE
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option_index (int): the index of the option to calculate the size for
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train | offer_answer | submit a student answer to the answer pool
The answer maybe selected to stay in the pool depending on the selection algorithm
Args:
pool (dict): answer pool
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{
option1_index: {
'student_id': { can store algorithm specific i... | ubcpi/answer_pool.py | def offer_answer(pool, answer, rationale, student_id, algo, options):
"""
submit a student answer to the answer pool
The answer maybe selected to stay in the pool depending on the selection algorithm
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pool (dict): answer pool
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submit a student answer to the answer pool
The answer maybe selected to stay in the pool depending on the selection algorithm
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pool (dict): answer pool
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train | offer_simple | The simple selection algorithm.
This algorithm randomly select an answer from the pool to discard and add the new one when the pool reaches
the limit | ubcpi/answer_pool.py | def offer_simple(pool, answer, rationale, student_id, options):
"""
The simple selection algorithm.
This algorithm randomly select an answer from the pool to discard and add the new one when the pool reaches
the limit
"""
existing = pool.setdefault(answer, {})
if len(existing) >= get_max_si... | def offer_simple(pool, answer, rationale, student_id, options):
"""
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train | offer_random | The random selection algorithm. The same as simple algorithm | ubcpi/answer_pool.py | def offer_random(pool, answer, rationale, student_id, options):
"""
The random selection algorithm. The same as simple algorithm
"""
offer_simple(pool, answer, rationale, student_id, options) | def offer_random(pool, answer, rationale, student_id, options):
"""
The random selection algorithm. The same as simple algorithm
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train | validate_seeded_answers_simple | This validator checks if the answers includes all possible options
Args:
answers (str): the answers to be checked
options (dict): all options that should exist in the answers
algo (str): selection algorithm
Returns:
None if everything is good. Otherwise, the missing option erro... | ubcpi/answer_pool.py | def validate_seeded_answers_simple(answers, options, algo):
"""
This validator checks if the answers includes all possible options
Args:
answers (str): the answers to be checked
options (dict): all options that should exist in the answers
algo (str): selection algorithm
Returns... | def validate_seeded_answers_simple(answers, options, algo):
"""
This validator checks if the answers includes all possible options
Args:
answers (str): the answers to be checked
options (dict): all options that should exist in the answers
algo (str): selection algorithm
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train | validate_seeded_answers | Validate answers based on selection algorithm
This is called when instructor setup the tool and providing seeded answers to the question.
This function is trying to validate if instructor provided enough seeds for a give algorithm.
e.g. we require 1 seed for each option in simple algorithm and at least 1 s... | ubcpi/answer_pool.py | def validate_seeded_answers(answers, options, algo):
"""
Validate answers based on selection algorithm
This is called when instructor setup the tool and providing seeded answers to the question.
This function is trying to validate if instructor provided enough seeds for a give algorithm.
e.g. we re... | def validate_seeded_answers(answers, options, algo):
"""
Validate answers based on selection algorithm
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train | get_other_answers | Select other student's answers from answer pool or seeded answers based on the selection algorithm
Args:
pool (dict): answer pool, format:
{
option1_index: {
student_id: { can store algorithm specific info here }
},
option2_ind... | ubcpi/answer_pool.py | def get_other_answers(pool, seeded_answers, get_student_item_dict, algo, options):
"""
Select other student's answers from answer pool or seeded answers based on the selection algorithm
Args:
pool (dict): answer pool, format:
{
option1_index: {
studen... | def get_other_answers(pool, seeded_answers, get_student_item_dict, algo, options):
"""
Select other student's answers from answer pool or seeded answers based on the selection algorithm
Args:
pool (dict): answer pool, format:
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Args:
see `get_other_answers`
num_responses (int): the number of responses to be returned. This value may not be
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"""
Get answers from others with simple algorithm, which picks one answer for each option.
Args:
see `get_other_answers`
num_responses (int): the number of responses to be returned. This value may not ... | def get_other_answers_simple(pool, seeded_answers, get_student_item_dict, num_responses):
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Get answers from others with simple algorithm, which picks one answer for each option.
Args:
see `get_other_answers`
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train | get_other_answers_random | Get answers from others with random algorithm, which randomly select answer from the pool.
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Args:
see `get_other_answers`
num_responses (int): the number of responses to be returned. This value m... | ubcpi/answer_pool.py | def get_other_answers_random(pool, seeded_answers, get_student_item_dict, num_responses):
"""
Get answers from others with random algorithm, which randomly select answer from the pool.
Student may get three answers for option 1 or one answer for option 1 and two answers for option 2.
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train | convert_seeded_answers | Convert seeded answers into the format that can be merged into student answers.
Args:
answers (list): seeded answers
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dict: seeded answers with student answers format:
{
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'seeded0': 'rationaleA'
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1: {
... | ubcpi/answer_pool.py | def convert_seeded_answers(answers):
"""
Convert seeded answers into the format that can be merged into student answers.
Args:
answers (list): seeded answers
Returns:
dict: seeded answers with student answers format:
{
0: {
'seeded0': 'ra... | def convert_seeded_answers(answers):
"""
Convert seeded answers into the format that can be merged into student answers.
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answers (list): seeded answers
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dict: seeded answers with student answers format:
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we also set them up as a timed event here to make sure that they don't
silently disa... | axiom/batch.py | def upgradeProcessor1to2(oldProcessor):
"""
Batch processors stopped polling at version 2, so they no longer needed the
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we also set them up as a timed event... | def upgradeProcessor1to2(oldProcessor):
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train | processor | Create an Axiom Item type which is suitable to use as a batch processor for
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@type forType: L{item.MetaItem}
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Processors created this way depend on a L{iaxiom.IScheduler} powerup on the
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@type forType: L{item.MetaItem}
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train | storeBatchServiceSpecialCase | Adapt a L{Store} to L{IBatchService}.
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train | _ProcessingFailure.mark | Mark the unit of work as failed in the database and update the listener
so as to skip it next time. | axiom/batch.py | def mark(self):
"""
Mark the unit of work as failed in the database and update the listener
so as to skip it next time.
"""
self.reliableListener.lastRun = extime.Time()
BatchProcessingError(
store=self.reliableListener.store,
processor=self.reliab... | def mark(self):
"""
Mark the unit of work as failed in the database and update the listener
so as to skip it next time.
"""
self.reliableListener.lastRun = extime.Time()
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processor=self.reliab... | [
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@rtype: L{extime.Time} or C{None}
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C{self.busyInterval} milliseconds, otherwise unschedule it.
@rtype: L{extime.Time} or C{None}
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Note: Each Item is processed synchronously. Adding too many
listeners to a single batch processor will cause the L{step}
method to block while it sends notification to each listener.
@param... | axiom/batch.py | def addReliableListener(self, listener, style=iaxiom.LOCAL):
"""
Add the given Item to the set which will be notified of Items
available for processing.
Note: Each Item is processed synchronously. Adding too many
listeners to a single batch processor will cause the L{step}
... | def addReliableListener(self, listener, style=iaxiom.LOCAL):
"""
Add the given Item to the set which will be notified of Items
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Note: Each Item is processed synchronously. Adding too many
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train | _BatchProcessorMixin.removeReliableListener | Remove a previously added listener. | axiom/batch.py | def removeReliableListener(self, listener):
"""
Remove a previously added listener.
"""
self.store.query(_ReliableListener,
attributes.AND(_ReliableListener.processor == self,
_ReliableListener.listener == listener)).delete... | def removeReliableListener(self, listener):
"""
Remove a previously added listener.
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train | _BatchProcessorMixin.getReliableListeners | Return an iterable of the listeners which have been added to
this batch processor. | axiom/batch.py | def getReliableListeners(self):
"""
Return an iterable of the listeners which have been added to
this batch processor.
"""
for rellist in self.store.query(_ReliableListener, _ReliableListener.processor == self):
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Return an iterable of the listeners which have been added to
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train | _BatchProcessorMixin.getFailedItems | Return an iterable of two-tuples of listeners which raised an
exception from C{processItem} and the item which was passed as
the argument to that method. | axiom/batch.py | def getFailedItems(self):
"""
Return an iterable of two-tuples of listeners which raised an
exception from C{processItem} and the item which was passed as
the argument to that method.
"""
for failed in self.store.query(BatchProcessingError, BatchProcessingError.processor ... | def getFailedItems(self):
"""
Return an iterable of two-tuples of listeners which raised an
exception from C{processItem} and the item which was passed as
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"""
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train | _BatchProcessorMixin.itemAdded | Called to indicate that a new item of the type monitored by this batch
processor is being added to the database.
If this processor is not already scheduled to run, this will schedule
it. It will also start the batch process if it is not yet running and
there are any registered remote l... | axiom/batch.py | def itemAdded(self):
"""
Called to indicate that a new item of the type monitored by this batch
processor is being added to the database.
If this processor is not already scheduled to run, this will schedule
it. It will also start the batch process if it is not yet running and
... | def itemAdded(self):
"""
Called to indicate that a new item of the type monitored by this batch
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train | BatchProcessingControllerService.call | Invoke the given bound item method in the batch process.
Return a Deferred which fires when the method has been invoked. | axiom/batch.py | def call(self, itemMethod):
"""
Invoke the given bound item method in the batch process.
Return a Deferred which fires when the method has been invoked.
"""
item = itemMethod.im_self
method = itemMethod.im_func.func_name
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"""
Invoke the given bound item method in the batch process.
Return a Deferred which fires when the method has been invoked.
"""
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train | BatchProcessingService.processWhileRunning | Run tasks until stopService is called. | axiom/batch.py | def processWhileRunning(self):
"""
Run tasks until stopService is called.
"""
work = self.step()
for result, more in work:
yield result
if not self.running:
break
if more:
delay = 0.1
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train | getcols | find every column in every sheet and put it in a new sheet or book. | PyOriginTools/scratch.py | def getcols(sheetMatch=None,colMatch="Decay"):
"""find every column in every sheet and put it in a new sheet or book."""
book=BOOK()
if sheetMatch is None:
matchingSheets=book.sheetNames
print('all %d sheets selected '%(len(matchingSheets)))
else:
matchingSheets=[x for x in book.... | def getcols(sheetMatch=None,colMatch="Decay"):
"""find every column in every sheet and put it in a new sheet or book."""
book=BOOK()
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matchingSheets=book.sheetNames
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train | Upgrade.upgradeStore | Recursively upgrade C{store}. | axiom/plugins/axiom_plugins.py | def upgradeStore(self, store):
"""
Recursively upgrade C{store}.
"""
self.upgradeEverything(store)
upgradeExplicitOid(store)
for substore in store.query(SubStore):
print 'Upgrading: {!r}'.format(substore)
self.upgradeStore(substore.open()) | def upgradeStore(self, store):
"""
Recursively upgrade C{store}.
"""
self.upgradeEverything(store)
upgradeExplicitOid(store)
for substore in store.query(SubStore):
print 'Upgrading: {!r}'.format(substore)
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train | Upgrade.perform | Upgrade C{store} performing C{count} upgrades per transaction.
Also, catch any exceptions and print out something useful. | axiom/plugins/axiom_plugins.py | def perform(self, store, count):
"""
Upgrade C{store} performing C{count} upgrades per transaction.
Also, catch any exceptions and print out something useful.
"""
self.count = count
try:
self.upgradeStore(store)
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e... | def perform(self, store, count):
"""
Upgrade C{store} performing C{count} upgrades per transaction.
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"""
self.count = count
try:
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train | AxiomConsole.runcode | Override L{code.InteractiveConsole.runcode} to run the code in a
transaction unless the local C{autocommit} is currently set to a true
value. | axiom/plugins/axiom_plugins.py | def runcode(self, code):
"""
Override L{code.InteractiveConsole.runcode} to run the code in a
transaction unless the local C{autocommit} is currently set to a true
value.
"""
if not self.locals.get('autocommit', None):
return self.locals['db'].transact(code.In... | def runcode(self, code):
"""
Override L{code.InteractiveConsole.runcode} to run the code in a
transaction unless the local C{autocommit} is currently set to a true
value.
"""
if not self.locals.get('autocommit', None):
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train | Browse.namespace | Return a dictionary representing the namespace which should be
available to the user. | axiom/plugins/axiom_plugins.py | def namespace(self):
"""
Return a dictionary representing the namespace which should be
available to the user.
"""
self._ns = {
'db': self.store,
'store': store,
'autocommit': False,
}
return self._ns | def namespace(self):
"""
Return a dictionary representing the namespace which should be
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"""
self._ns = {
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train | Create.addAccount | Create a new account in the given store.
@param siteStore: A site Store to which login credentials will be
added.
@param username: Local part of the username for the credentials to add.
@param domain: Domain part of the username for the credentials to add.
@param password: Passw... | axiom/plugins/axiom_plugins.py | def addAccount(self, siteStore, username, domain, password):
"""
Create a new account in the given store.
@param siteStore: A site Store to which login credentials will be
added.
@param username: Local part of the username for the credentials to add.
@param domain: Domai... | def addAccount(self, siteStore, username, domain, password):
"""
Create a new account in the given store.
@param siteStore: A site Store to which login credentials will be
added.
@param username: Local part of the username for the credentials to add.
@param domain: Domai... | [
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train | itemTypeWithSomeAttributes | Create a new L{Item} subclass with L{numAttributes} integers in its
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"""
Create a new L{Item} subclass with L{numAttributes} integers in its
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"""
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typeName = 'someitem_' + str(typeNameCounter())
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train | createSomeItems | Create some instances of a particular type in a store. | benchmark/benchlib.py | def createSomeItems(store, itemType, values, counter):
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train | MongoForm.save | save the instance or create a new one.. | mongoforms/forms.py | def save(self, commit=True):
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train | empowerment | Class decorator for indicating a powerup's powerup interfaces.
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train | Empowered._getPowerupInterfaces | Collect powerup interfaces this object declares that it can be
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train | Item._currentlyValidAsReferentFor | Is this object currently valid as a reference? Objects which will be
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"""
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Prepare each attribute in my schema for insertion into a given store,
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train | Item.existingInStore | Create and return a new instance from a row from the store. | axiom/item.py | def existingInStore(cls, store, storeID, attrs):
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Return a dictionary of all attributes which will be/have been/are being
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"""
Called after the database is brought into a consistent state with this
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"""
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"""
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train | registerUpgrader | Register a callable which can perform a schema upgrade between two
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@param upgrader: A one-argument callable which will upgrade an object. It
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@param typeName: The database typename for which this is an upgrader.
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"""
Register a callable which can perform a schema upgrade between two
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@param upgrader: A one-argument callable which will upgrade an object. It
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"""
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train | registerDeletionUpgrader | Register an upgrader for C{itemType}, from C{fromVersion} to C{toVersion},
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@param itemType: L{axiom.item.Item} subclass
@return: None | axiom/upgrade.py | def registerDeletionUpgrader(itemType, fromVersion, toVersion):
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Register an upgrader for C{itemType}, from C{fromVersion} to C{toVersion},
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@param itemType: L{axiom.item.Item} subclass
@return: None
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# XXX This should actually do something... | def registerDeletionUpgrader(itemType, fromVersion, toVersion):
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Register an upgrader for C{itemType}, from C{fromVersion} to C{toVersion},
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train | _hasExplicitOid | Does the given table have an explicit oid column? | axiom/upgrade.py | def _hasExplicitOid(store, table):
"""
Does the given table have an explicit oid column?
"""
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train | _upgradeTableOid | Upgrade a table to have an explicit oid.
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train | upgradeSystemOid | Upgrade the system tables to use explicit oid columns. | axiom/upgrade.py | def upgradeSystemOid(store):
"""
Upgrade the system tables to use explicit oid columns.
"""
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This requires copying all of axiom_objects and axiom_types, as well as all
item tables that have not yet been upgraded. Consider VACUUMing the
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train | _StoreUpgrade.checkUpgradePaths | Check that all of the accumulated old Item types have a way to get
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train | _StoreUpgrade.queueTypeUpgrade | Queue a type upgrade for C{oldtype}. | axiom/upgrade.py | def queueTypeUpgrade(self, oldtype):
"""
Queue a type upgrade for C{oldtype}.
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if oldtype not in self._oldTypesRemaining:
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train | _StoreUpgrade.upgradeItem | Upgrade a legacy item.
@raise axiom.errors.UpgraderRecursion: If the given item is already in
the process of being upgraded. | axiom/upgrade.py | def upgradeItem(self, thisItem):
"""
Upgrade a legacy item.
@raise axiom.errors.UpgraderRecursion: If the given item is already in
the process of being upgraded.
"""
sid = thisItem.storeID
if sid in self._currentlyUpgrading:
raise UpgraderRecursio... | def upgradeItem(self, thisItem):
"""
Upgrade a legacy item.
@raise axiom.errors.UpgraderRecursion: If the given item is already in
the process of being upgraded.
"""
sid = thisItem.storeID
if sid in self._currentlyUpgrading:
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train | LogicalVolume.open | Obtains the lvm, vg_t and lv_t handle. Usually you would never need to use this
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Obtains the lvm, vg_t and lv_t handle. Usually you would never need to use this
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*Raises:*
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train | LogicalVolume.name | Returns the logical volume name. | lvm2py/lv.py | def name(self):
"""
Returns the logical volume name.
"""
self.open()
name = lvm_lv_get_name(self.__lvh)
self.close()
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"""
Returns the logical volume name.
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train | LogicalVolume.is_active | Returns True if the logical volume is active, False otherwise. | lvm2py/lv.py | def is_active(self):
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Returns True if the logical volume is active, False otherwise.
"""
self.open()
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self.close()
return bool(active) | def is_active(self):
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train | LogicalVolume.is_suspended | Returns True if the logical volume is suspended, False otherwise. | lvm2py/lv.py | def is_suspended(self):
"""
Returns True if the logical volume is suspended, False otherwise.
"""
self.open()
susp = lvm_lv_is_suspended(self.__lvh)
self.close()
return bool(susp) | def is_suspended(self):
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Returns True if the logical volume is suspended, False otherwise.
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train | LogicalVolume.size | Returns the logical volume size in the given units. Default units are MiB.
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Returns the logical volume size in the given units. Default units are MiB.
*Args:*
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"""
self.open()
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train | LogicalVolume.activate | Activates the logical volume.
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"""
Activates the logical volume.
*Raises:*
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"""
self.open()
a = lvm_lv_activate(self.handle)
self.close()
if a != 0:
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Activates the logical volume.
*Raises:*
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train | LogicalVolume.deactivate | Deactivates the logical volume.
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"""
Deactivates the logical volume.
*Raises:*
* HandleError
"""
self.open()
d = lvm_lv_deactivate(self.handle)
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if d != 0:
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Deactivates the logical volume.
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train | PhysicalVolume.open | Obtains the lvm, vg_t and pv_t handle. Usually you would never need to use this
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"""
Obtains the lvm, vg_t and pv_t handle. Usually you would never need to use this
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conversion.py
*Raises:*
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Obtains the lvm, vg_t and pv_t handle. Usually you would never need to use this
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train | PhysicalVolume.name | Returns the physical volume device path. | lvm2py/pv.py | def name(self):
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Returns the physical volume device path.
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self.open()
name = lvm_pv_get_name(self.handle)
self.close()
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"""
Returns the physical volume device path.
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train | PhysicalVolume.mda_count | Returns the physical volume mda count. | lvm2py/pv.py | def mda_count(self):
"""
Returns the physical volume mda count.
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self.open()
mda = lvm_pv_get_mda_count(self.handle)
self.close()
return mda | def mda_count(self):
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Returns the physical volume mda count.
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self.open()
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self.close()
return mda | [
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train | PhysicalVolume.size | Returns the physical volume size in the given units. Default units are MiB.
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* units (str): Unit label ('MiB', 'GiB', etc...). Default is MiB. | lvm2py/pv.py | def size(self, units="MiB"):
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