hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
87d727fc783882a2a98a4efc514d6ecbfcce27e4
| 7,287
|
py
|
Python
|
patchwork/tests/test_feature_moco.py
|
jg10545/patchwork
|
6fe85ac46eef4e7763129b7f1e77700f939da738
|
[
"MIT"
] | 2
|
2020-07-14T00:51:50.000Z
|
2021-05-11T06:57:01.000Z
|
patchwork/tests/test_feature_moco.py
|
jg10545/patchwork
|
6fe85ac46eef4e7763129b7f1e77700f939da738
|
[
"MIT"
] | 43
|
2020-02-08T16:13:14.000Z
|
2022-03-13T14:14:16.000Z
|
patchwork/tests/test_feature_moco.py
|
jg10545/patchwork
|
6fe85ac46eef4e7763129b7f1e77700f939da738
|
[
"MIT"
] | 5
|
2020-02-24T01:47:40.000Z
|
2021-02-18T16:39:12.000Z
|
# -*- coding: utf-8 -*-
import numpy as np
import tensorflow as tf
from patchwork.feature._moco import copy_model, exponential_model_update
from patchwork.feature._moco import _build_augment_pair_dataset
from patchwork.feature._moco import _build_momentum_contrast_training_step
from patchwork.feature._moco import _build_logits
def test_copy_model():
orig = tf.keras.applications.VGG16(weights=None, include_top=False)
clone = copy_model(orig)
# number of layers should be the same
assert len(orig.layers) == len(clone.layers)
# weights should be identical
assert np.sum((orig.layers[1].get_weights()[0]-clone.layers[1].get_weights()[0])) == 0.
def test_exponenial_model_update():
test_inpt = np.ones((1,5), dtype=np.float32)
inpt = tf.keras.layers.Input((5))
net = tf.keras.layers.Dense(4)(inpt)
mod1 = tf.keras.Model(inpt, net)
out1 = mod1(test_inpt).numpy()
inpt = tf.keras.layers.Input((5))
net = tf.keras.layers.Dense(4)(inpt)
mod2 = tf.keras.Model(inpt, net)
out2 = mod2(test_inpt).numpy()
# updating model with itself should give rolling sum = 0
rollingsum = exponential_model_update(mod1, mod1).numpy()
assert rollingsum == 0.
# setting exponential parameter to 1 should return original model
rs = exponential_model_update(mod1, mod2, 1.)
out3 = mod1(test_inpt).numpy()
assert np.sum((out3 - out1)**2) < 1e-5
# setting exponential parameter to 0 should return second model
rs = exponential_model_update(mod1, mod2, 0.)
out4 = mod1(test_inpt).numpy()
assert np.sum((out4 - out2)**2) < 1e-5
def test_build_augment_pair_dataset(test_png_path):
filepaths = 10*[test_png_path]
ds = _build_augment_pair_dataset(filepaths, imshape=(32,32),
batch_size=5,
augment={"flip_left_right":True})
assert isinstance(ds, tf.data.Dataset)
for x,y in ds:
x = x.numpy()
y = y.numpy()
break
assert x.shape == (5,32,32,3)
assert y.shape == (5,32,32,3)
def test_build_augment_pair_dataset_with_custom_dataset():
rawdata = np.zeros((10,32,32,3)).astype(np.float32)
ds = tf.data.Dataset.from_tensor_slices(rawdata)
batch_size = 5
ds = _build_augment_pair_dataset(ds, imshape=(32,32),
num_channels=3, norm=255,
augment={"flip_left_right":True},
single_channel=False,
batch_size=batch_size)
assert isinstance(ds, tf.data.Dataset)
for x,y in ds:
x = x.numpy()
y = y.numpy()
break
assert x.shape == (5,32,32,3)
assert y.shape == (5,32,32,3)
def test_build_augment_pair_dataset_with_custom_pair_dataset():
rawdata = np.zeros((10,32,32,3)).astype(np.float32)
ds = tf.data.Dataset.from_tensor_slices((rawdata,rawdata))
batch_size = 5
ds = _build_augment_pair_dataset(ds, imshape=(32,32),
num_channels=3, norm=255,
augment={"flip_left_right":True},
single_channel=False,
batch_size=batch_size)
assert isinstance(ds, tf.data.Dataset)
for x,y in ds:
x = x.numpy()
y = y.numpy()
break
assert x.shape == (5,32,32,3)
assert y.shape == (5,32,32,3)
def test_build_logits_no_mochi():
batch_size = 7
embed_dim = 5
K = 13
q = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
k = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
buffer = tf.Variable(tf.nn.l2_normalize(np.random.normal(0, 1, size=(K,embed_dim)).astype(np.float32), axis=1))
all_logits = _build_logits(q, k, buffer)
assert len(all_logits.shape) == 2
assert all_logits.shape[0] == batch_size
assert all_logits.shape[1] == K +1
def test_build_logits_with_margin():
batch_size = 7
embed_dim = 5
K = 13
q = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
k = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
buffer = tf.Variable(tf.nn.l2_normalize(np.random.normal(0, 1, size=(K,embed_dim)).astype(np.float32), axis=1))
all_logits = _build_logits(q, k, buffer, margin=100)
assert len(all_logits.shape) == 2
assert all_logits.shape[0] == batch_size
assert all_logits.shape[1] == K +1
def test_build_logits_with_mochi():
batch_size = 7
embed_dim = 5
K = 13
N = 6
s = 2
q = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
k = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
buffer = tf.Variable(tf.nn.l2_normalize(np.random.normal(0, 1, size=(K,embed_dim)).astype(np.float32), axis=1))
all_logits = _build_logits(q, k, buffer, N, s)
assert len(all_logits.shape) == 2
assert all_logits.shape[0] == batch_size
assert all_logits.shape[1] == K +1 + s
def test_build_logits_with_mochi_and_query_mixing():
batch_size = 7
embed_dim = 5
K = 13
N = 6
s = 2
s_prime = 3
q = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
k = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
buffer = tf.Variable(tf.nn.l2_normalize(np.random.normal(0, 1, size=(K,embed_dim)).astype(np.float32), axis=1))
all_logits = _build_logits(q, k, buffer, N, s, s_prime)
assert len(all_logits.shape) == 2
assert all_logits.shape[0] == batch_size
assert all_logits.shape[1] == K +1 + s + s_prime
def test_build_logits_with_mochi_and_more_samples_than_N():
batch_size = 7
embed_dim = 5
K = 13
N = 6
s = 12
s_prime = 13
q = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
k = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
buffer = tf.Variable(tf.nn.l2_normalize(np.random.normal(0, 1, size=(K,embed_dim)).astype(np.float32), axis=1))
all_logits = _build_logits(q, k, buffer, N, s, s_prime)
assert len(all_logits.shape) == 2
assert all_logits.shape[0] == batch_size
assert all_logits.shape[1] == K +1 + s + s_prime
def test_build_logits_with_batch_comparison():
batch_size = 7
embed_dim = 5
K = 13
q = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
k = tf.nn.l2_normalize(np.random.normal(0, 1, size=(batch_size, embed_dim)).astype(np.float32), axis=1)
buffer = tf.Variable(tf.nn.l2_normalize(np.random.normal(0, 1, size=(K,embed_dim)).astype(np.float32), axis=1))
all_logits = _build_logits(q, k, buffer, compare_batch=True)
assert len(all_logits.shape) == 2
assert all_logits.shape[0] == batch_size
assert all_logits.shape[1] == K + batch_size
| 38.555556
| 115
| 0.644024
| 1,141
| 7,287
| 3.905346
| 0.130587
| 0.064632
| 0.067325
| 0.060592
| 0.811266
| 0.77693
| 0.746634
| 0.708932
| 0.708932
| 0.706688
| 0
| 0.051909
| 0.220118
| 7,287
| 189
| 116
| 38.555556
| 0.732184
| 0.036503
| 0
| 0.666667
| 0
| 0
| 0.006415
| 0
| 0
| 0
| 0
| 0
| 0.217687
| 1
| 0.07483
| false
| 0
| 0.040816
| 0
| 0.115646
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
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| 0
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| 0
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| null | 0
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| 0
| 0
|
0
| 6
|
e2135287ba71234d0cb1c77bd491463376ece8ed
| 6,643
|
py
|
Python
|
Ryven/packages/auto_generated/glob/nodes.py
|
tfroehlich82/Ryven
|
cb57c91d13949712844a4410a9302c4a90d28dcd
|
[
"MIT"
] | 2,872
|
2020-07-01T09:06:34.000Z
|
2022-03-31T05:52:32.000Z
|
Ryven/packages/auto_generated/glob/nodes.py
|
dhf327/Ryven
|
a11e361528d982a9dd3c489dd536f8b05ffd56e1
|
[
"MIT"
] | 59
|
2020-06-28T12:50:50.000Z
|
2022-03-27T19:07:54.000Z
|
Ryven/packages/auto_generated/glob/nodes.py
|
dhf327/Ryven
|
a11e361528d982a9dd3c489dd536f8b05ffd56e1
|
[
"MIT"
] | 339
|
2020-07-05T04:36:20.000Z
|
2022-03-24T07:25:18.000Z
|
from NENV import *
import glob
class NodeBase(Node):
pass
class _Glob0_Node(NodeBase):
"""
"""
title = '_glob0'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='basename'),
NodeInputBP(label='dironly'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._glob0(self.input(0), self.input(1), self.input(2)))
class _Glob1_Node(NodeBase):
"""
"""
title = '_glob1'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='pattern'),
NodeInputBP(label='dironly'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._glob1(self.input(0), self.input(1), self.input(2)))
class _Glob2_Node(NodeBase):
"""
"""
title = '_glob2'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='pattern'),
NodeInputBP(label='dironly'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._glob2(self.input(0), self.input(1), self.input(2)))
class _Iglob_Node(NodeBase):
"""
"""
title = '_iglob'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='pathname'),
NodeInputBP(label='recursive'),
NodeInputBP(label='dironly'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._iglob(self.input(0), self.input(1), self.input(2)))
class _Ishidden_Node(NodeBase):
"""
"""
title = '_ishidden'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='path'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._ishidden(self.input(0)))
class _Isrecursive_Node(NodeBase):
"""
"""
title = '_isrecursive'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='pattern'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._isrecursive(self.input(0)))
class _Iterdir_Node(NodeBase):
"""
"""
title = '_iterdir'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='dironly'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._iterdir(self.input(0), self.input(1)))
class _Rlistdir_Node(NodeBase):
"""
"""
title = '_rlistdir'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='dironly'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob._rlistdir(self.input(0), self.input(1)))
class Escape_Node(NodeBase):
"""
Escape all special characters.
"""
title = 'escape'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='pathname'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob.escape(self.input(0)))
class Glob_Node(NodeBase):
"""
Return a list of paths matching a pathname pattern.
The pattern may contain simple shell-style wildcards a la
fnmatch. However, unlike fnmatch, filenames starting with a
dot are special cases that are not matched by '*' and '?'
patterns.
If recursive is true, the pattern '**' will match any files and
zero or more directories and subdirectories.
"""
title = 'glob'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='pathname'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob.glob(self.input(0)))
class Glob0_Node(NodeBase):
"""
"""
title = 'glob0'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='pattern'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob.glob0(self.input(0), self.input(1)))
class Glob1_Node(NodeBase):
"""
"""
title = 'glob1'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='dirname'),
NodeInputBP(label='pattern'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob.glob1(self.input(0), self.input(1)))
class Has_Magic_Node(NodeBase):
"""
"""
title = 'has_magic'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='s'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob.has_magic(self.input(0)))
class Iglob_Node(NodeBase):
"""
Return an iterator which yields the paths matching a pathname pattern.
The pattern may contain simple shell-style wildcards a la
fnmatch. However, unlike fnmatch, filenames starting with a
dot are special cases that are not matched by '*' and '?'
patterns.
If recursive is true, the pattern '**' will match any files and
zero or more directories and subdirectories.
"""
title = 'iglob'
type_ = 'glob'
init_inputs = [
NodeInputBP(label='pathname'),
]
init_outputs = [
NodeOutputBP(type_='data'),
]
color = '#32DA22'
def update_event(self, inp=-1):
self.set_output_val(0, glob.iglob(self.input(0)))
export_nodes(
_Glob0_Node,
_Glob1_Node,
_Glob2_Node,
_Iglob_Node,
_Ishidden_Node,
_Isrecursive_Node,
_Iterdir_Node,
_Rlistdir_Node,
Escape_Node,
Glob_Node,
Glob0_Node,
Glob1_Node,
Has_Magic_Node,
Iglob_Node,
)
| 21.360129
| 88
| 0.574439
| 735
| 6,643
| 4.970068
| 0.136054
| 0.113879
| 0.04599
| 0.068984
| 0.805092
| 0.805092
| 0.781549
| 0.766493
| 0.766493
| 0.75089
| 0
| 0.027455
| 0.28722
| 6,643
| 310
| 89
| 21.429032
| 0.744034
| 0.114707
| 0
| 0.53
| 0
| 0
| 0.085563
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.07
| false
| 0.005
| 0.01
| 0
| 0.505
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| null | 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
357449a696d3eacbc9da1c1b7d0e21bc03d5c6e1
| 203
|
py
|
Python
|
odoo-14.0/odoo/addons/test_data_module_install/__manifest__.py
|
Yomy1996/P1
|
59e24cdd5f7f82005fe15bd7a7ff54dd5364dd29
|
[
"CC-BY-3.0"
] | null | null | null |
odoo-14.0/odoo/addons/test_data_module_install/__manifest__.py
|
Yomy1996/P1
|
59e24cdd5f7f82005fe15bd7a7ff54dd5364dd29
|
[
"CC-BY-3.0"
] | null | null | null |
odoo-14.0/odoo/addons/test_data_module_install/__manifest__.py
|
Yomy1996/P1
|
59e24cdd5f7f82005fe15bd7a7ff54dd5364dd29
|
[
"CC-BY-3.0"
] | null | null | null |
{
'name': 'test installation of data module',
'description': 'Test data module (see test_data_module) installation',
'version': '0.0.1',
'category': 'Hidden/Tests',
'sequence': 10,
}
| 25.375
| 74
| 0.625616
| 24
| 203
| 5.208333
| 0.666667
| 0.24
| 0.224
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.030864
| 0.20197
| 203
| 7
| 75
| 29
| 0.740741
| 0
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| 0
| 0
| 0.684729
| 0
| 0
| 0
| 0
| 0
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| 1
| 0
| true
| 0
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| null | 1
| 1
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| 0
| 0
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| 0
| 1
| 0
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| null | 0
| 0
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| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
357fb4b2a1b784b3f34fd5d4322083d52d14260f
| 726
|
py
|
Python
|
server/models/__init__.py
|
KohlbacherLab/deregnet-rest
|
d512e04b66556fbb52a49e9da465af01ebfdd78a
|
[
"BSD-3-Clause"
] | null | null | null |
server/models/__init__.py
|
KohlbacherLab/deregnet-rest
|
d512e04b66556fbb52a49e9da465af01ebfdd78a
|
[
"BSD-3-Clause"
] | null | null | null |
server/models/__init__.py
|
KohlbacherLab/deregnet-rest
|
d512e04b66556fbb52a49e9da465af01ebfdd78a
|
[
"BSD-3-Clause"
] | 1
|
2018-01-30T18:38:56.000Z
|
2018-01-30T18:38:56.000Z
|
# coding: utf-8
# flake8: noqa
from __future__ import absolute_import
# import models into model package
from deregnet_rest.models.graph_info import GraphInfo
from deregnet_rest.models.inital_graph_info import InitalGraphInfo
from deregnet_rest.models.node_set import NodeSet
from deregnet_rest.models.node_set_info import NodeSetInfo
from deregnet_rest.models.parameter_set import ParameterSet
from deregnet_rest.models.parameter_set_info import ParameterSetInfo
from deregnet_rest.models.run_info import RunInfo
from deregnet_rest.models.run_input import RunInput
from deregnet_rest.models.score import Score
from deregnet_rest.models.score_info import ScoreInfo
from deregnet_rest.models.subgraph_info import SubgraphInfo
| 42.705882
| 68
| 0.87741
| 105
| 726
| 5.790476
| 0.333333
| 0.217105
| 0.289474
| 0.398026
| 0.378289
| 0.207237
| 0
| 0
| 0
| 0
| 0
| 0.003008
| 0.084022
| 726
| 16
| 69
| 45.375
| 0.911278
| 0.081267
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
ea97c69a5e1bf99936a0161fc9c4be9f1b6955ec
| 106
|
py
|
Python
|
proxy/models.py
|
cklewar/wistar
|
e9bdbad641f083fdbe5d388a91a3d46bc20ae297
|
[
"Apache-2.0"
] | 152
|
2016-12-20T22:33:42.000Z
|
2022-02-10T03:46:00.000Z
|
proxy/models.py
|
cklewar/wistar
|
e9bdbad641f083fdbe5d388a91a3d46bc20ae297
|
[
"Apache-2.0"
] | 46
|
2016-12-28T15:35:12.000Z
|
2020-05-05T00:16:40.000Z
|
proxy/models.py
|
cklewar/wistar
|
e9bdbad641f083fdbe5d388a91a3d46bc20ae297
|
[
"Apache-2.0"
] | 48
|
2017-01-03T13:36:55.000Z
|
2022-02-10T03:51:01.000Z
|
from __future__ import unicode_literals
from django.db import models
from django.forms import ModelForm
| 17.666667
| 39
| 0.849057
| 15
| 106
| 5.666667
| 0.666667
| 0.235294
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132075
| 106
| 5
| 40
| 21.2
| 0.923913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
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| 1
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| 1
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| 1
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| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
578e8a155ca5e715d588c6d4d7713435e6ab0445
| 31
|
py
|
Python
|
function/_abc/__init__.py
|
alpavlenko/EvoGuess
|
19bc54e75cd959e445becda16fa6f488f0fb2367
|
[
"MIT"
] | 1
|
2021-12-12T15:09:56.000Z
|
2021-12-12T15:09:56.000Z
|
function/_abc/__init__.py
|
alpavlenko/EvoGuess
|
19bc54e75cd959e445becda16fa6f488f0fb2367
|
[
"MIT"
] | 1
|
2021-10-10T09:16:57.000Z
|
2021-10-10T09:16:57.000Z
|
function/_abc/__init__.py
|
alpavlenko/evoguess
|
e8510c32c8325c9fe66fc15899d378b7bf731557
|
[
"MIT"
] | null | null | null |
from .function import Function
| 15.5
| 30
| 0.83871
| 4
| 31
| 6.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129032
| 31
| 1
| 31
| 31
| 0.962963
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
aa3da181b4bdce4a87ff986b5557847ffd96732b
| 14,853
|
py
|
Python
|
analysisdatalink/datalink_ext.py
|
seung-lab/AnalysisDataLink
|
c3268c15f8b98d77074ae599c3c48db7c81aadc7
|
[
"MIT"
] | 1
|
2019-05-29T00:37:05.000Z
|
2019-05-29T00:37:05.000Z
|
analysisdatalink/datalink_ext.py
|
seung-lab/AnalysisDataLink
|
c3268c15f8b98d77074ae599c3c48db7c81aadc7
|
[
"MIT"
] | 6
|
2019-03-20T18:27:48.000Z
|
2019-12-16T19:23:59.000Z
|
analysisdatalink/datalink_ext.py
|
seung-lab/AnalysisDataLink
|
c3268c15f8b98d77074ae599c3c48db7c81aadc7
|
[
"MIT"
] | null | null | null |
import numpy as np
from analysisdatalink import datalink
from collections import defaultdict
class AnalysisDataLinkExt(datalink.AnalysisDataLink):
def __init__(self, dataset_name, materialization_version=None,
sqlalchemy_database_uri=None, verbose=True,
annotation_endpoint=None):
super().__init__(dataset_name, materialization_version,
sqlalchemy_database_uri, verbose=verbose,
annotation_endpoint=annotation_endpoint)
def query_synapses(self, synapse_table, pre_ids=None, post_ids=None,
compartment_include_filter=None,
include_autapses=False,
compartment_table=None, return_sql=False,
fix_wkb=True, fix_decimal=True, import_via_buffer=True,
n_threads=None):
"""Query a synapse table and return a dataframe
Parameters
----------
synapse_table : str
Table name with a synapse schema
pre_ids : collection of ints, optional
Object ids for presynaptic neurons, by default None
post_ids : collection of ints, optional
Object ids for postsynaptic neurons, by default None
compartment_include_filter : None, optional
Not currently implemented. By default None
include_autapses : bool, optional
Include synapses whose pre- and post-synaptic objects are the same, by default False
compartment_table : str, optional
Not currently implemented. Would be a table name for synapse compartments. By default None
return_sql : bool, optional
Return the sqlalchemy query object instead of the data itself, by default False
fix_wkb : bool, optional
Convert wkb-formatted spatial location columns to numpy 3-vectors. Setting to False
can be much faster, but spatial information is not easy to parse. These columns can be
parsed after the fact with analysisdatalink.fix_wkb_column. Optional, by default True
fix_decimal : bool, optional
Convert Decimal columns to ints. Not used if import_via_buffer is True. By default True
import_via_buffer : bool, optional
Flag to determine whether to use a fast csv and tempfile based SQL import (if True) or the pandas
native read_sql import (if False). If column formatting is odd, try setting to False. Optional, by default True.
n_threads : int or None, optional
Number of threads to use when parsing columns to convert wkb. Unused if fix_wkb is False. If set to 1,
multiprocessing is not used and slower numpy vectorization is used instead.
If None, uses the number of cpus available on the device. By default None
Returns
-------
pandas.DataFrame
DataFrame representation of the query results.
"""
filter_in_dict = defaultdict(dict)
filter_equal_dict = defaultdict(dict)
if pre_ids is not None:
filter_in_dict[synapse_table]["pre_pt_root_id"] = [int(pid) for pid in pre_ids]
if post_ids is not None:
filter_in_dict[synapse_table]["post_pt_root_id"] = [int(pid) for pid in post_ids]
if not include_autapses:
filter_equal_dict[synapse_table]["valid"] = True
if compartment_table is not None:
tables = [[synapse_table, "id"],
[compartment_table, "synapse_id"]]
if compartment_include_filter is not None:
filter_in_dict[compartment_table]['label'] = compartment_include_filter
else:
tables = [synapse_table]
df = self.specific_query(tables,
filter_in_dict=filter_in_dict,
filter_equal_dict=filter_equal_dict,
return_sql=return_sql,
fix_wkb=fix_wkb, fix_decimal=fix_decimal,
import_via_buffer=import_via_buffer,
n_threads=n_threads)
return df
def query_cell_types(self, cell_type_table, cell_type_include_filter=None,
cell_type_exclude_filter=None, return_only_ids=False,
exclude_zero_root_ids=False, fix_wkb=True, fix_decimal=True,
return_sql=False, import_via_buffer=True, n_threads=None):
"""Query a synapse table and return a dataframe
Parameters
----------
cell_type_table : str
Table name with a cell_type schema
cell_type_include_filter : collection of str, optional
Cell types to include
cell_type_exclude_filter : collection of str, optional
Cell types to exclude
return_only_ids : bool, optional
Process to include only root ids matching the query.
exclude_zero_root_ids : bool, optional
Fitler out points with a null segmentation id.
return_sql : bool, optional
Return the sqlalchemy query object instead of the data itself, by default False
fix_wkb : bool, optional
Convert wkb-formatted spatial location columns to numpy 3-vectors. Setting to False
can be much faster, but spatial information is not easy to parse. These columns can be
parsed after the fact with analysisdatalink.fix_wkb_column. Optional, by default True
fix_decimal : bool, optional
Convert Decimal columns to ints. Not used if import_via_buffer is True. By default True
import_via_buffer : bool, optional
Flag to determine whether to use a fast csv and tempfile based SQL import (if True) or the pandas
native read_sql import (if False). If column formatting is odd, try setting to False. Optional, by default True.
n_threads : int or None, optional
Number of threads to use when parsing columns to convert wkb. Unused if fix_wkb is False. If set to 1,
multiprocessing is not used and slower numpy vectorization is used instead.
If None, uses the number of cpus available on the device. By default None
Returns
-------
pandas.DataFrame
DataFrame representation of the query results.
"""
filter_in_dict = defaultdict(dict)
if cell_type_include_filter is not None:
filter_in_dict[cell_type_table]["cell_type"] = cell_type_include_filter
filter_notin_dict = defaultdict(dict)
if exclude_zero_root_ids:
filter_notin_dict[cell_type_table]["pt_root_id"] = [0]
if cell_type_exclude_filter is not None:
filter_notin_dict[cell_type_table]['cell_type'] = cell_type_exclude_filter
if return_only_ids:
select_columns = ["pt_root_id"]
else:
select_columns = None
df = self.specific_query(tables=[cell_type_table],
filter_in_dict=filter_in_dict,
filter_notin_dict=filter_notin_dict,
select_columns=select_columns,
fix_wkb=fix_wkb,
fix_decimal=fix_decimal,
return_sql=return_sql,
import_via_buffer=import_via_buffer,
n_threads=n_threads)
if return_only_ids:
return np.array(df, dtype = np.uint64).squeeze()
else:
return df
def query_cell_ids(self, cell_id_table, cell_id_filter=None,
cell_id_exclude_filter=None, return_only_ids=False,
exclude_zero_root_ids=False, fix_wkb=True, fix_decimal=True,
return_sql=False, import_via_buffer=True, n_threads=None):
""" Query cell id tables
Parameters
----------
cell_id_table : str
Table name for a microns_functional_coregistration table
cell_id_filter : list of uint64s, optional
List of root ids to include. Default is None.
cell_id_exclude_filter : list of uint64s, optional
List of root ids to exclude. Default is None.
return_only_ids : bool, optional
Process to include only root ids matching the query. Default is False.
exclude_zero_root_ids : bool, optional
Fitler out points with a null segmentation id. Default is False.
return_sql : bool, optional
Return the sqlalchemy query object instead of the data itself, by default False
fix_wkb : bool, optional
Convert wkb-formatted spatial location columns to numpy 3-vectors. Setting to False
can be much faster, but spatial information is not easy to parse. These columns can be
parsed after the fact with analysisdatalink.fix_wkb_column. Optional, by default True
fix_decimal : bool, optional
Convert Decimal columns to ints. Not used if import_via_buffer is True. By default True
import_via_buffer : bool, optional
Flag to determine whether to use a fast csv and tempfile based SQL import (if True) or the pandas
native read_sql import (if False). If column formatting is odd, try setting to False. Optional, by default True.
n_threads : int or None, optional
Number of threads to use when parsing columns to convert wkb. Unused if fix_wkb is False. If set to 1,
multiprocessing is not used and slower numpy vectorization is used instead.
If None, uses the number of cpus available on the device. By default None
Returns
-------
pandas.DataFrame
DataFrame representation of the query results.
"""
filter_in_dict = defaultdict(dict)
if cell_id_filter is not None:
filter_in_dict[cell_id_table]['func_id'] = [int(pid) for pid in cell_id_filter]
filter_notin_dict = defaultdict(dict)
if cell_id_exclude_filter is not None:
filter_notin_dict[cell_id_table]['func_id'] = [int(pid) for pid in cell_id_exclude_filter]
if exclude_zero_root_ids is not None:
filter_notin_dict[cell_id_table]['pt_root_id'] = [0]
if return_only_ids:
select_columns = ['pt_root_id']
else:
select_columns = None
df = self.specific_query(tables=[cell_id_table],
filter_in_dict=filter_in_dict,
filter_notin_dict=filter_notin_dict,
select_columns=select_columns,
fix_wkb=fix_wkb,
fix_decimal=fix_decimal,
return_sql=return_sql,
import_via_buffer=import_via_buffer, n_threads=n_threads)
if return_only_ids:
return np.array(df, dtype=np.uint64).squeeze()
else:
return df
def query_coreg(self, coreg_table, cell_id_filter=None,
cell_id_exclude_filter=None, return_only_mapping=False,
exclude_zero_root_ids=False,
fix_wkb=True, fix_decimal=True,
return_sql=False, import_via_buffer=True, n_threads=None):
""" Query cell id tables
Parameters
----------
coreg_table : str
Table name for a microns_functional_coregistration table
cell_id_filter : list of uint64s, optional
List of root ids to include. Default is None.
cell_id_exclude_filter : list of uint64s, optional
List of root ids to exclude. Default is None.
return_only_ids : bool, optional
Process to include only root ids matching the query. Default is False.
exclude_zero_root_ids : bool, optional
Fitler out points with a null segmentation id. Default is False.
return_sql : bool, optional
Return the sqlalchemy query object instead of the data itself, by default False
fix_wkb : bool, optional
Convert wkb-formatted spatial location columns to numpy 3-vectors. Setting to False
can be much faster, but spatial information is not easy to parse. These columns can be
parsed after the fact with analysisdatalink.fix_wkb_column. Optional, by default True
fix_decimal : bool, optional
Convert Decimal columns to ints. Not used if import_via_buffer is True. By default True
import_via_buffer : bool, optional
Flag to determine whether to use a fast csv and tempfile based SQL import (if True) or the pandas
native read_sql import (if False). If column formatting is odd, try setting to False. Optional, by default True.
n_threads : int or None, optional
Number of threads to use when parsing columns to convert wkb. Unused if fix_wkb is False. If set to 1,
multiprocessing is not used and slower numpy vectorization is used instead.
If None, uses the number of cpus available on the device. By default None
Returns
-------
pandas.DataFrame
DataFrame representation of the query results.
"""
filter_in_dict = defaultdict(dict)
if cell_id_filter is not None:
filter_in_dict[coreg_table]['func_id'] = [int(pid) for pid in cell_id_filter]
filter_notin_dict = defaultdict(dict)
if cell_id_exclude_filter is not None:
filter_notin_dict[coreg_table]['func_id'] = [int(pid) for pid in cell_id_exclude_filter]
if exclude_zero_root_ids is not None:
filter_notin_dict[coreg_table]['pt_root_id'] = [0]
if return_only_mapping:
select_columns = ['pt_root_id', 'func_id']
else:
select_columns = None
df = self.specific_query(tables=[coreg_table],
filter_in_dict=filter_in_dict,
filter_notin_dict=filter_notin_dict,
select_columns=select_columns,
fix_wkb=fix_wkb,
fix_decimal=fix_decimal,
return_sql=return_sql,
import_via_buffer=import_via_buffer, n_threads=n_threads)
if return_only_mapping:
return np.array(df, dtype=np.uint64).squeeze()
else:
return df
| 50.179054
| 124
| 0.622029
| 1,868
| 14,853
| 4.709315
| 0.09636
| 0.025577
| 0.034103
| 0.018756
| 0.853245
| 0.83358
| 0.824145
| 0.813118
| 0.768103
| 0.754007
| 0
| 0.002503
| 0.327543
| 14,853
| 295
| 125
| 50.349153
| 0.878254
| 0.46186
| 0
| 0.536
| 0
| 0
| 0.023903
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.04
| false
| 0
| 0.088
| 0
| 0.192
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
a4b9860bab28ff0968038fd6c919e4964777347e
| 40
|
py
|
Python
|
girder_worker_tasks/arbor_nova_tasks/arbor_tasks/core/__init__.py
|
knowledgevis/wsi_infer_web
|
f5201e767a502fde6f17dd17a70aabcd388d5cc2
|
[
"Apache-2.0"
] | null | null | null |
girder_worker_tasks/arbor_nova_tasks/arbor_tasks/core/__init__.py
|
knowledgevis/wsi_infer_web
|
f5201e767a502fde6f17dd17a70aabcd388d5cc2
|
[
"Apache-2.0"
] | null | null | null |
girder_worker_tasks/arbor_nova_tasks/arbor_tasks/core/__init__.py
|
knowledgevis/wsi_infer_web
|
f5201e767a502fde6f17dd17a70aabcd388d5cc2
|
[
"Apache-2.0"
] | null | null | null |
from .wsi_thumbnail import wsi_thumbnail
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a4cd6080443b295c1961311f00a8b8b0f11f3d6f
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py
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Python
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openarticlegauge/plugins/resources/elsevier_list.py
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CottageLabs/OpenArticleGauge
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58d29b4209a7b59041d61326ffe1cf03f98f3cff
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[
"BSD-3-Clause"
] | 1
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2016-04-07T18:29:27.000Z
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2016-04-07T18:29:27.000Z
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openarticlegauge/plugins/resources/elsevier_list.py
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CottageLabs/OpenArticleGauge
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58d29b4209a7b59041d61326ffe1cf03f98f3cff
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[
"BSD-3-Clause"
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2015-01-06T15:53:09.000Z
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2022-03-01T01:46:14.000Z
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openarticlegauge/plugins/resources/elsevier_list.py
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CottageLabs/OpenArticleGauge
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58d29b4209a7b59041d61326ffe1cf03f98f3cff
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[
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py
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Python
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seahub/group/settings.py
|
saukrIppl/newsea
|
0fd5ab2ade9a8fb16b1e7b43ba13dac32eb39603
|
[
"Apache-2.0"
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2017-06-21T09:46:55.000Z
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2018-05-30T10:07:32.000Z
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seahub/group/settings.py
|
saukrIppl/newsea
|
0fd5ab2ade9a8fb16b1e7b43ba13dac32eb39603
|
[
"Apache-2.0"
] | null | null | null |
seahub/group/settings.py
|
saukrIppl/newsea
|
0fd5ab2ade9a8fb16b1e7b43ba13dac32eb39603
|
[
"Apache-2.0"
] | 1
|
2020-10-01T04:11:41.000Z
|
2020-10-01T04:11:41.000Z
|
from django.conf import settings
GROUP_MEMBERS_DEFAULT_DISPLAY = getattr(settings, 'GROUP_MEMBERS_DEFAULT_DISPLAY', 10)
| 30.25
| 86
| 0.85124
| 16
| 121
| 6.0625
| 0.6875
| 0.268041
| 0.412371
| 0.556701
| 0.701031
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018018
| 0.082645
| 121
| 3
| 87
| 40.333333
| 0.855856
| 0
| 0
| 0
| 0
| 0
| 0.239669
| 0.239669
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
a4d50ecf2f6bb26a8afd3a9b9d13aa163fb372cb
| 2,095
|
py
|
Python
|
lib/third_party/cloud_ml_engine_sdk/prediction/__init__.py
|
bopopescu/Google-Cloud-SDK-1
|
c4683bacb2f6192d8a816932e438a0493085469b
|
[
"Apache-2.0"
] | null | null | null |
lib/third_party/cloud_ml_engine_sdk/prediction/__init__.py
|
bopopescu/Google-Cloud-SDK-1
|
c4683bacb2f6192d8a816932e438a0493085469b
|
[
"Apache-2.0"
] | null | null | null |
lib/third_party/cloud_ml_engine_sdk/prediction/__init__.py
|
bopopescu/Google-Cloud-SDK-1
|
c4683bacb2f6192d8a816932e438a0493085469b
|
[
"Apache-2.0"
] | 1
|
2020-07-24T20:13:29.000Z
|
2020-07-24T20:13:29.000Z
|
# Copyright 2016 Google 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.
# pylint: disable=g-import-not-at-top
"""Classes and methods for predictions on a trained machine learning model.
"""
from _interfaces import Model
from _interfaces import PredictionClient
from prediction_lib import BaseModel
from prediction_lib import canonicalize_single_tensor_input
from prediction_lib import columnarize
from prediction_lib import COLUMNARIZE_TIME
from prediction_lib import create_client
from prediction_lib import create_model
from prediction_lib import create_sklearn_model
from prediction_lib import create_xgboost_model
from prediction_lib import decode_base64
from prediction_lib import encode_base64
from prediction_lib import ENGINE
from prediction_lib import FRAMEWORK
from prediction_lib import INPUTS_KEY
from prediction_lib import load_model
from prediction_lib import local_predict
from prediction_lib import OUTPUTS_KEY
from prediction_lib import PredictionError
from prediction_lib import rowify
from prediction_lib import ROWIFY_TIME
from prediction_lib import SCIKIT_LEARN_FRAMEWORK_NAME
from prediction_lib import SESSION_RUN_ENGINE_NAME
from prediction_lib import SESSION_RUN_TIME
from prediction_lib import SessionClient
from prediction_lib import SklearnModel
from prediction_lib import Stats
from prediction_lib import TENSORFLOW_FRAMEWORK_NAME
from prediction_lib import TensorFlowClient
from prediction_lib import TensorFlowModel
from prediction_lib import Timer
from prediction_lib import XGBOOST_FRAMEWORK_NAME
from prediction_lib import XGBoostModel
| 41.078431
| 75
| 0.85537
| 303
| 2,095
| 5.709571
| 0.39604
| 0.250867
| 0.304624
| 0.412139
| 0.36474
| 0.128902
| 0.042775
| 0
| 0
| 0
| 0
| 0.006504
| 0.119332
| 2,095
| 50
| 76
| 41.9
| 0.931165
| 0.324105
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
a4fefeffbfe66de4adc2f3fa0b72f97cb2aef71f
| 90
|
py
|
Python
|
database/backends/__init__.py
|
zhouhongf/cleaner_pdf
|
4a01f17b5335571ea00935fdfb0db46ad164c16a
|
[
"MIT"
] | 1
|
2021-11-27T06:40:46.000Z
|
2021-11-27T06:40:46.000Z
|
database/backends/__init__.py
|
zhouhongf/cleaner_pdf
|
4a01f17b5335571ea00935fdfb0db46ad164c16a
|
[
"MIT"
] | null | null | null |
database/backends/__init__.py
|
zhouhongf/cleaner_pdf
|
4a01f17b5335571ea00935fdfb0db46ad164c16a
|
[
"MIT"
] | null | null | null |
from .mongo_database import MongoDatabase
from .elastic_database import ElasticDatabase
| 30
| 46
| 0.866667
| 10
| 90
| 7.6
| 0.7
| 0.368421
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 90
| 2
| 47
| 45
| 0.95
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
351128644fc3859d1897133c754d600209bcdc12
| 2,854
|
py
|
Python
|
Python/_todo/teste.py
|
danielbom/codewars
|
d45b5a813c6f1d952a50d22f0b2fcea4ef3d0e27
|
[
"MIT"
] | null | null | null |
Python/_todo/teste.py
|
danielbom/codewars
|
d45b5a813c6f1d952a50d22f0b2fcea4ef3d0e27
|
[
"MIT"
] | null | null | null |
Python/_todo/teste.py
|
danielbom/codewars
|
d45b5a813c6f1d952a50d22f0b2fcea4ef3d0e27
|
[
"MIT"
] | null | null | null |
from wagons import *
if False:
TRACK_EX = """\
/-------\
| |
| |
| |
\-------+-------------------------------------------------------------\
| |
| |
\-----------------------------------S-------------------------+--------\
| |
| |
| |
\--------/
"""
print(train_crash(TRACK_EX, "Dddddddddddddddd", 16, "xxxxxxxxxxX", 161, 30))
if False:
TRACK_EX = """\
/-----\\ /-----\\ /-----\\ /-----\\
| \\ / \\ / \\ / |
| X X X |
| / \\ / \\ / \\ |
\\-----/ \\-----/ \\-----/ \\-----/
"""
print(train_crash(TRACK_EX, "Bbb", 14, "aaaaA", 45, 30))
if False:
TRACK_EX = """\
/------------\\
/-------------\\ / |
| | / S
| | / |
| /----+--------------+------\\ |
\\ / | | | |
\\ | \\ | | |
| | \\-------------+------+--------+---\\
| | | | | |
\\------+--------------------+------/ / |
| | / |
\\------S-------------+-------------/ |
| |
/-------------\\ | |
| | | /-----+----\\
| | | | | \\
\\-------------+--------------+-----S-------+-----/ \\
| | | \\
| | | |
| \\-------------+-------------/
| |
\\----------------------------/
"""
print(train_crash(TRACK_EX, "Aaaa", 147, "Bbbbbbbbbbb", 288, 1000))
if False:
TRACK_EX = """\
/-------\\
| |
| |
| |
\-------+--------\\
| |
| |
| |
\--------/"""
print(train_crash(TRACK_EX, "Xx", 38, "Aaaaa", 6, 50))
if True:
TRACK_EX = """\
/---\\
| |
\\--\\|
||
|\\------\\
|/----\\ |
|| | |
/--/| | |
| | | |
\\---/ \\-/"""
print(train_crash(TRACK_EX, "Aaaa", 0, "Xxxxxxxxxxxxxxxx", 15, 50))
| 34.385542
| 81
| 0.114576
| 80
| 2,854
| 3.9
| 0.425
| 0.224359
| 0.240385
| 0.320513
| 0.580128
| 0.358974
| 0.185897
| 0
| 0
| 0
| 0
| 0.027615
| 0.581289
| 2,854
| 82
| 82
| 34.804878
| 0.233473
| 0
| 0
| 0.454545
| 0
| 0
| 0.841275
| 0.138402
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.012987
| 0
| 0.012987
| 0.064935
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
3534aafe9d75c2a2059da10057a9d63312a66dd9
| 4,285
|
py
|
Python
|
src/the_tale/the_tale/common/tt_api/tests/test_timers.py
|
devapromix/the-tale
|
2a10efd3270734f8cf482b4cfbc5353ef8f0494c
|
[
"BSD-3-Clause"
] | 1
|
2020-04-02T11:51:20.000Z
|
2020-04-02T11:51:20.000Z
|
src/the_tale/the_tale/common/tt_api/tests/test_timers.py
|
devapromix/the-tale
|
2a10efd3270734f8cf482b4cfbc5353ef8f0494c
|
[
"BSD-3-Clause"
] | null | null | null |
src/the_tale/the_tale/common/tt_api/tests/test_timers.py
|
devapromix/the-tale
|
2a10efd3270734f8cf482b4cfbc5353ef8f0494c
|
[
"BSD-3-Clause"
] | null | null | null |
import smart_imports
smart_imports.all()
class TestClient(timers.Client):
def protobuf_to_type(self, type):
return type
def type_to_protobuf(self, type):
return type
timers_client = TestClient(entry_point=accounts_conf.settings.TT_PLAYERS_TIMERS_EMPTY_POINTS)
class CreateTimerTests(utils_testcase.TestCase):
def setUp(self):
timers_client.cmd_debug_clear_service()
def test_create_timer(self):
timers_client.cmd_create_timer(owner_id=666,
type=0,
speed=14,
border=15,
entity_id=16,
resources=3,
callback_data='')
timers = timers_client.cmd_get_owner_timers(owner_id=666)
self.assertEqual(len(timers), 1)
self.assertEqual(timers[0].entity_id, 16)
self.assertEqual(timers[0].type, 0)
self.assertEqual(timers[0].speed, 14)
self.assertEqual(timers[0].border, 15)
self.assertEqual(timers[0].resources, 3)
def test_exception_in_error(self):
timers_client.cmd_create_timer(owner_id=666,
type=0,
speed=14,
border=15,
entity_id=16,
resources=3,
callback_data='')
with self.assertRaises(exceptions.CanNotCreateTimer):
timers_client.cmd_create_timer(owner_id=666,
type=0,
speed=14,
border=15,
entity_id=16,
resources=3,
callback_data='')
class ChangeCardsTimerSpeedTests(utils_testcase.TestCase):
def setUp(self):
timers_client.cmd_debug_clear_service()
def test_create_timer(self):
timers_client.cmd_create_timer(owner_id=666,
type=0,
speed=14,
border=15,
entity_id=16,
resources=3,
callback_data='')
timers_client.cmd_change_timer_speed(owner_id=666, speed=2, type=0, entity_id=16)
timers = timers_client.cmd_get_owner_timers(owner_id=666)
self.assertEqual(len(timers), 1)
self.assertEqual(timers[0].entity_id, 16)
self.assertEqual(timers[0].type, 0)
self.assertEqual(timers[0].speed, 2)
self.assertEqual(timers[0].border, 15)
def test_exception_in_error(self):
timers_client.cmd_create_timer(owner_id=666,
type=0,
speed=14,
border=15,
entity_id=16,
resources=3,
callback_data='')
with self.assertRaises(exceptions.CanNotChangeTimerSpeed):
timers_client.cmd_change_timer_speed(owner_id=777, speed=2, type=0)
class GetOwnerTimersTests(utils_testcase.TestCase):
def setUp(self):
timers_client.cmd_debug_clear_service()
def test_create_timer(self):
timers_client.cmd_create_timer(owner_id=666,
type=0,
speed=14,
border=15,
entity_id=16,
resources=3,
callback_data='')
timers = timers_client.cmd_get_owner_timers(owner_id=666)
self.assertEqual(len(timers), 1)
self.assertEqual(timers[0].entity_id, 16)
self.assertEqual(timers[0].type, 0)
self.assertEqual(timers[0].speed, 14)
self.assertEqual(timers[0].border, 15)
| 35.122951
| 93
| 0.476079
| 399
| 4,285
| 4.849624
| 0.162907
| 0.099225
| 0.108527
| 0.147804
| 0.796382
| 0.796382
| 0.780879
| 0.780879
| 0.744703
| 0.744703
| 0
| 0.052409
| 0.447841
| 4,285
| 121
| 94
| 35.413223
| 0.765427
| 0
| 0
| 0.827586
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206897
| 1
| 0.114943
| false
| 0
| 0.022989
| 0.022989
| 0.206897
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
353e2618dc8b19a6acb57b4cf974096b669bb3ff
| 98
|
py
|
Python
|
recnn/data/__init__.py
|
ihash5/reinforcement-learning
|
c72e9db33c6ed6abd34e9f48012189369b7cd5d0
|
[
"Apache-2.0"
] | 1
|
2021-04-10T08:21:21.000Z
|
2021-04-10T08:21:21.000Z
|
recnn/data/__init__.py
|
ihash5/reinforcement-learning
|
c72e9db33c6ed6abd34e9f48012189369b7cd5d0
|
[
"Apache-2.0"
] | null | null | null |
recnn/data/__init__.py
|
ihash5/reinforcement-learning
|
c72e9db33c6ed6abd34e9f48012189369b7cd5d0
|
[
"Apache-2.0"
] | null | null | null |
from . import utils, env
from .utils import *
from .env import *
from .dataset_functions import *
| 19.6
| 32
| 0.744898
| 14
| 98
| 5.142857
| 0.428571
| 0.277778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173469
| 98
| 4
| 33
| 24.5
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
102c024a395d315a35313cd313ed3b8996a22e4a
| 19
|
py
|
Python
|
M_utils/__init__.py
|
deskmel/pytorch_deepspeech
|
ad519c81cea498e2926390e735cb6d02681a3340
|
[
"MIT"
] | 5
|
2020-12-27T03:02:37.000Z
|
2022-03-30T06:59:14.000Z
|
M_utils/__init__.py
|
deskmel/pytorch_deepspeech
|
ad519c81cea498e2926390e735cb6d02681a3340
|
[
"MIT"
] | 1
|
2020-09-22T08:49:04.000Z
|
2020-09-22T08:49:04.000Z
|
M_utils/__init__.py
|
deskmel/pytorch_deepspeech
|
ad519c81cea498e2926390e735cb6d02681a3340
|
[
"MIT"
] | 3
|
2020-03-31T21:40:12.000Z
|
2021-06-09T02:26:43.000Z
|
from .loss import *
| 19
| 19
| 0.736842
| 3
| 19
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157895
| 19
| 1
| 19
| 19
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
104fade8dc032c45ee13e7ce44886d7860cf0034
| 78
|
py
|
Python
|
Inheritance/class_Inheritance/project_players_and_monsters/elf.py
|
vasetousa/OOP
|
e4fedc497dd149c9800613ea11846e0e770d122c
|
[
"MIT"
] | null | null | null |
Inheritance/class_Inheritance/project_players_and_monsters/elf.py
|
vasetousa/OOP
|
e4fedc497dd149c9800613ea11846e0e770d122c
|
[
"MIT"
] | null | null | null |
Inheritance/class_Inheritance/project_players_and_monsters/elf.py
|
vasetousa/OOP
|
e4fedc497dd149c9800613ea11846e0e770d122c
|
[
"MIT"
] | null | null | null |
from Encapsulation.project_wild_cat_zoo import Hero
class Elf(Hero):
pass
| 19.5
| 51
| 0.807692
| 12
| 78
| 5
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.141026
| 78
| 4
| 52
| 19.5
| 0.895522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
1051adb6b583ca2dfe1032358cead5d976654ff7
| 19,374
|
py
|
Python
|
data/typing/pandas.core.indexes.numeric.py
|
vfdev-5/python-record-api
|
006faf0bba9cd4cb55fbacc13d2bbda365f5bf0b
|
[
"MIT"
] | null | null | null |
data/typing/pandas.core.indexes.numeric.py
|
vfdev-5/python-record-api
|
006faf0bba9cd4cb55fbacc13d2bbda365f5bf0b
|
[
"MIT"
] | null | null | null |
data/typing/pandas.core.indexes.numeric.py
|
vfdev-5/python-record-api
|
006faf0bba9cd4cb55fbacc13d2bbda365f5bf0b
|
[
"MIT"
] | null | null | null |
from typing import *
class Float64Index:
# usage.dask: 1
__module__: ClassVar[object]
# usage.dask: 2
__name__: ClassVar[object]
# usage.dask: 1
array: object
# usage.dask: 7
# usage.xarray: 4
dtype: object
# usage.dask: 1
# usage.xarray: 2
is_monotonic: object
# usage.xarray: 3
is_unique: object
# usage.dask: 9
# usage.xarray: 1
name: Union[Literal["x"], None]
# usage.dask: 4
names: List[str]
# usage.xarray: 1
nlevels: object
# usage.xarray: 1
shape: object
# usage.xarray: 2
size: object
# usage.dask: 2
# usage.xarray: 3
values: object
def __add__(self, _0: Union[numpy.float64, numpy.timedelta64, numpy.datetime64], /):
"""
usage.pandas: 3
"""
...
@overload
def __contains__(self, _0: str, /):
"""
usage.dask: 2
"""
...
@overload
def __contains__(self, _0: Literal["divisions"], /):
"""
usage.dask: 1
"""
...
@overload
def __contains__(self, _0: Literal["dtype"], /):
"""
usage.dask: 1
"""
...
def __contains__(self, _0: str, /):
"""
usage.dask: 4
"""
...
def __eq__(self, _0: Union[numpy.ndarray, numpy.float64], /):
"""
usage.pandas: 9
"""
...
def __floordiv__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 4
"""
...
@overload
def __getitem__(self, _0: numpy.ndarray, /):
"""
usage.xarray: 3
"""
...
@overload
def __getitem__(self, _0: slice[None, int, None], /):
"""
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: slice[int, None, int], /):
"""
usage.xarray: 2
"""
...
@overload
def __getitem__(self, _0: slice[None, None, None], /):
"""
usage.xarray: 2
"""
...
@overload
def __getitem__(self, _0: int, /):
"""
usage.dask: 4
usage.xarray: 2
"""
...
@overload
def __getitem__(self, _0: slice[int, int, int], /):
"""
usage.dask: 1
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: slice[int, None, int], /):
"""
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: slice[int, int, int], /):
"""
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: slice[None, None, None], /):
"""
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: slice[None, int, None], /):
"""
usage.xarray: 1
"""
...
def __getitem__(
self,
_0: Union[
int,
numpy.ndarray,
slice[Union[None, int], Union[int, None], Union[None, int]],
],
/,
):
"""
usage.dask: 5
usage.xarray: 15
"""
...
def __mod__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 3
"""
...
def __mul__(self, _0: Union[numpy.ndarray, numpy.timedelta64], /):
"""
usage.pandas: 5
"""
...
def __radd__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 2
"""
...
def __rfloordiv__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 1
"""
...
def __rmul__(self, _0: Union[numpy.timedelta64, numpy.ndarray], /):
"""
usage.pandas: 2
"""
...
def __rsub__(
self, _0: Union[numpy.ndarray, numpy.timedelta64, numpy.datetime64], /
):
"""
usage.pandas: 4
"""
...
def __rtruediv__(self, _0: Union[numpy.timedelta64, numpy.ndarray], /):
"""
usage.pandas: 2
"""
...
def __sub__(
self,
_0: Union[numpy.ndarray, numpy.datetime64, numpy.timedelta64, numpy.float64],
/,
):
"""
usage.pandas: 5
"""
...
def __truediv__(self, _0: Union[numpy.ndarray, numpy.timedelta64], /):
"""
usage.pandas: 5
"""
...
def astype(self, /, dtype: pandas.core.dtypes.dtypes.CategoricalDtype):
"""
usage.dask: 1
"""
...
def copy(self, /, deep: bool):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(self, /, target: numpy.ndarray, method: None, tolerance: None):
"""
usage.xarray: 5
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["pad"], tolerance: None
):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["backfill"], tolerance: None
):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["nearest"], tolerance: None
):
"""
usage.xarray: 1
"""
...
def get_indexer(
self,
/,
target: numpy.ndarray,
method: Union[Literal["nearest", "backfill", "pad"], None],
tolerance: None,
):
"""
usage.xarray: 8
"""
...
@overload
def get_loc(self, /, key: float, method: Literal["nearest"], tolerance: None):
"""
usage.xarray: 1
"""
...
@overload
def get_loc(self, /, key: float, method: None, tolerance: None):
"""
usage.xarray: 1
"""
...
@overload
def get_loc(self, /, key: float, method: Literal["nearest"], tolerance: int):
"""
usage.xarray: 1
"""
...
@overload
def get_loc(self, /, key: numpy.float64, method: Literal["nearest"]):
"""
usage.xarray: 2
"""
...
@overload
def get_loc(self, /, key: numpy.int64, method: Literal["nearest"]):
"""
usage.xarray: 2
"""
...
def get_loc(
self,
/,
key: Union[numpy.int64, float, numpy.float64],
method: Union[Literal["nearest"], None],
tolerance: Union[int, None] = ...,
):
"""
usage.xarray: 7
"""
...
def identical(self, /, other: pandas.core.indexes.numeric.Float64Index):
"""
usage.xarray: 1
"""
...
def set_names(self, /, names: List[Literal["b"]], inplace: bool):
"""
usage.dask: 1
"""
...
class Int64Index:
# usage.dask: 1
__module__: ClassVar[object]
# usage.dask: 3
__name__: ClassVar[object]
# usage.dask: 1
__class__: object
# usage.dask: 1
array: object
# usage.dask: 11
# usage.xarray: 6
dtype: object
# usage.dask: 1
# usage.xarray: 2
is_monotonic: object
# usage.dask: 1
# usage.xarray: 5
is_unique: object
# usage.dask: 21
# usage.xarray: 13
name: Union[None, Literal["foo", "C", "b", "idx", "a"]]
# usage.dask: 6
names: Union[pandas.core.indexes.frozen.FrozenList, List[str]]
# usage.dask: 2
nbytes: object
# usage.dask: 1
# usage.xarray: 1
nlevels: object
# usage.xarray: 2
shape: object
# usage.dask: 2
# usage.xarray: 10
size: object
# usage.dask: 3
# usage.xarray: 3
values: object
def __add__(self, _0: Union[numpy.int64, numpy.timedelta64, numpy.datetime64], /):
"""
usage.pandas: 3
"""
...
@overload
def __contains__(self, _0: Literal["divisions"], /):
"""
usage.dask: 1
"""
...
@overload
def __contains__(self, _0: Literal["dtype"], /):
"""
usage.dask: 1
"""
...
@overload
def __contains__(self, _0: str, /):
"""
usage.dask: 2
"""
...
@overload
def __contains__(self, _0: int, /):
"""
usage.dask: 3
"""
...
@overload
def __contains__(self, _0: None, /):
"""
usage.dask: 1
"""
...
def __contains__(self, _0: Union[None, str, int], /):
"""
usage.dask: 8
"""
...
def __eq__(self, _0: Union[numpy.ndarray, numpy.int64], /):
"""
usage.pandas: 9
"""
...
def __floordiv__(
self, _0: Union[numpy.float64, numpy.int64, numpy.ndarray, numpy.uint64], /
):
"""
usage.pandas: 11
"""
...
@overload
def __ge__(self, _0: int, /):
"""
usage.dask: 2
"""
...
@overload
def __ge__(self, _0: float, /):
"""
usage.dask: 1
"""
...
def __ge__(self, _0: Union[float, int], /):
"""
usage.dask: 3
"""
...
@overload
def __getitem__(self, _0: numpy.ndarray, /):
"""
usage.xarray: 4
"""
...
@overload
def __getitem__(self, _0: slice[None, None, None], /):
"""
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: int, /):
"""
usage.dask: 8
usage.xarray: 3
"""
...
@overload
def __getitem__(self, _0: slice[None, int, None], /):
"""
usage.dask: 2
usage.xarray: 3
"""
...
@overload
def __getitem__(self, _0: slice[int, int, int], /):
"""
usage.dask: 1
usage.xarray: 1
"""
...
@overload
def __getitem__(self, _0: slice[int, None, int], /):
"""
usage.xarray: 3
"""
...
@overload
def __getitem__(self, _0: slice[None, None, None], /):
"""
usage.xarray: 1
"""
...
def __getitem__(
self,
_0: Union[
int,
numpy.ndarray,
slice[Union[int, None], Union[None, int], Union[int, None]],
],
/,
):
"""
usage.dask: 11
usage.xarray: 16
"""
...
@overload
def __gt__(self, _0: int, /):
"""
usage.dask: 1
"""
...
@overload
def __gt__(self, _0: float, /):
"""
usage.dask: 1
"""
...
def __gt__(self, _0: Union[float, int], /):
"""
usage.dask: 2
"""
...
def __iter__(self, /):
"""
usage.dask: 4
usage.xarray: 2
"""
...
@overload
def __le__(self, _0: int, /):
"""
usage.dask: 1
"""
...
@overload
def __le__(self, _0: float, /):
"""
usage.dask: 1
"""
...
def __le__(self, _0: Union[float, int], /):
"""
usage.dask: 2
"""
...
@overload
def __lt__(self, _0: int, /):
"""
usage.dask: 2
"""
...
@overload
def __lt__(self, _0: float, /):
"""
usage.dask: 1
"""
...
def __lt__(self, _0: Union[float, int], /):
"""
usage.dask: 3
"""
...
def __mod__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 3
"""
...
def __mul__(self, _0: Union[numpy.ndarray, numpy.timedelta64], /):
"""
usage.pandas: 6
"""
...
def __radd__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 4
"""
...
def __rfloordiv__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 1
"""
...
def __rmul__(self, _0: Union[numpy.timedelta64, numpy.ndarray], /):
"""
usage.pandas: 5
"""
...
def __rsub__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 4
"""
...
def __rtruediv__(self, _0: Union[numpy.timedelta64, numpy.ndarray], /):
"""
usage.pandas: 4
"""
...
def __sub__(self, _0: Union[numpy.int64, numpy.timedelta64, numpy.datetime64], /):
"""
usage.pandas: 3
"""
...
def __truediv__(self, _0: Union[numpy.ndarray, numpy.timedelta64], /):
"""
usage.pandas: 5
"""
...
def copy(self, /, deep: bool):
"""
usage.xarray: 1
"""
...
@overload
def drop(self, /, labels: numpy.ndarray, errors: Literal["raise"]):
"""
usage.xarray: 2
"""
...
@overload
def drop(self, /, labels: numpy.ndarray, errors: Literal["ignore"]):
"""
usage.xarray: 1
"""
...
def drop(self, /, labels: numpy.ndarray, errors: Literal["raise", "ignore"]):
"""
usage.xarray: 3
"""
...
def drop_duplicates(self, /):
"""
usage.dask: 2
"""
...
def dropna(self, /):
"""
usage.dask: 1
"""
...
def equals(self, /, other: pandas.core.indexes.numeric.Int64Index):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(self, /, target: numpy.ndarray, method: None, tolerance: None):
"""
usage.xarray: 3
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["backfill"], tolerance: int
):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["backfill"], tolerance: float
):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["backfill"], tolerance: None
):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["pad"], tolerance: None
):
"""
usage.xarray: 1
"""
...
@overload
def get_indexer(
self, /, target: numpy.ndarray, method: Literal["pad"], tolerance: float
):
"""
usage.xarray: 1
"""
...
def get_indexer(
self,
/,
target: numpy.ndarray,
method: Union[Literal["pad", "backfill"], None],
tolerance: Union[float, int, None],
):
"""
usage.xarray: 8
"""
...
@overload
def get_loc(self, /, key: int, method: None, tolerance: None):
"""
usage.xarray: 1
"""
...
@overload
def get_loc(self, /, key: numpy.int64, method: Literal["nearest"]):
"""
usage.xarray: 2
"""
...
@overload
def get_loc(self, /, key: numpy.float64, method: Literal["nearest"]):
"""
usage.xarray: 2
"""
...
@overload
def get_loc(self, /, key: float, method: None, tolerance: None):
"""
usage.xarray: 1
"""
...
def get_loc(
self,
/,
key: Union[float, numpy.int64, int, numpy.float64],
method: Union[None, Literal["nearest"]],
tolerance: None = ...,
):
"""
usage.xarray: 6
"""
...
@overload
def isin(self, /, values: dask.delayed.Delayed):
"""
usage.dask: 1
"""
...
@overload
def isin(self, /, values: List[int]):
"""
usage.dask: 1
"""
...
@overload
def isin(self, /, values: dask.delayed.DelayedLeaf):
"""
usage.dask: 1
"""
...
@overload
def isin(self, /, values: pandas.core.series.Series):
"""
usage.dask: 1
"""
...
def isin(
self,
/,
values: Union[
pandas.core.series.Series,
dask.delayed.Delayed,
dask.delayed.DelayedLeaf,
List[int],
],
):
"""
usage.dask: 4
"""
...
def max(self, /):
"""
usage.dask: 1
"""
...
def min(self, /):
"""
usage.dask: 1
"""
...
@overload
def set_names(self, /, names: List[Literal["a"]], inplace: bool):
"""
usage.dask: 1
"""
...
@overload
def set_names(self, /, names: List[Literal["b"]], inplace: bool):
"""
usage.dask: 1
"""
...
@overload
def set_names(self, /, names: List[Literal["key"]], inplace: bool):
"""
usage.dask: 1
"""
...
def set_names(self, /, names: List[Literal["a", "b", "key"]], inplace: bool):
"""
usage.dask: 3
"""
...
@overload
def to_frame(self, /, index: bool, name: None):
"""
usage.dask: 1
"""
...
@overload
def to_frame(self, /, index: bool, name: Literal["bar"]):
"""
usage.dask: 1
"""
...
def to_frame(self, /, index: bool, name: Union[Literal["bar"], None]):
"""
usage.dask: 2
"""
...
def to_series(self, /):
"""
usage.dask: 1
"""
...
class UInt64Index:
# usage.dask: 1
__module__: ClassVar[object]
# usage.dask: 2
name: object
def __add__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 2
"""
...
def __eq__(self, _0: Union[numpy.ndarray, numpy.uint64], /):
"""
usage.pandas: 7
"""
...
def __floordiv__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 4
"""
...
def __mod__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 3
"""
...
def __mul__(self, _0: Union[numpy.ndarray, numpy.timedelta64], /):
"""
usage.pandas: 5
"""
...
def __radd__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 2
"""
...
def __rfloordiv__(self, _0: numpy.ndarray, /):
"""
usage.pandas: 1
"""
...
def __rmul__(self, _0: Union[numpy.timedelta64, numpy.ndarray], /):
"""
usage.pandas: 2
"""
...
def __rsub__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 2
"""
...
def __rtruediv__(self, _0: Union[numpy.timedelta64, numpy.ndarray], /):
"""
usage.pandas: 2
"""
...
def __sub__(self, _0: Union[numpy.datetime64, numpy.timedelta64], /):
"""
usage.pandas: 2
"""
...
def __truediv__(self, _0: Union[numpy.ndarray, numpy.timedelta64], /):
"""
usage.pandas: 5
"""
...
| 19.144269
| 88
| 0.440436
| 1,773
| 19,374
| 4.55894
| 0.072758
| 0.047631
| 0.047012
| 0.051961
| 0.863664
| 0.833725
| 0.775207
| 0.72968
| 0.642088
| 0.593963
| 0
| 0.032162
| 0.394962
| 19,374
| 1,011
| 89
| 19.163205
| 0.657396
| 0.136678
| 0
| 0.793839
| 0
| 0
| 0.015326
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.300948
| false
| 0
| 0.00237
| 0
| 0.376777
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
105ced1c528f3771a7473835a43a69b778faed0c
| 153
|
py
|
Python
|
wikiracer/__init__.py
|
tyler-a-cox/wiki-bot
|
f108692ccbad7e35ca1c00020ec74743dffea109
|
[
"MIT"
] | null | null | null |
wikiracer/__init__.py
|
tyler-a-cox/wiki-bot
|
f108692ccbad7e35ca1c00020ec74743dffea109
|
[
"MIT"
] | null | null | null |
wikiracer/__init__.py
|
tyler-a-cox/wiki-bot
|
f108692ccbad7e35ca1c00020ec74743dffea109
|
[
"MIT"
] | null | null | null |
from .query import *
from .graph import *
from .fetch import *
from .analysis import *
from .database import *
from .utils import load_graph, save_graph
| 21.857143
| 41
| 0.75817
| 22
| 153
| 5.181818
| 0.454545
| 0.438596
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163399
| 153
| 6
| 42
| 25.5
| 0.890625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
10657c1bb32606a4a5cc7fa68278115bb703cfd6
| 69
|
py
|
Python
|
test/integration/expected_out_single_line/percent_numerics.py
|
krajkumard/flynt
|
ebe437edf5b3d812d43d2e8662eef36cc230dcd9
|
[
"MIT"
] | null | null | null |
test/integration/expected_out_single_line/percent_numerics.py
|
krajkumard/flynt
|
ebe437edf5b3d812d43d2e8662eef36cc230dcd9
|
[
"MIT"
] | null | null | null |
test/integration/expected_out_single_line/percent_numerics.py
|
krajkumard/flynt
|
ebe437edf5b3d812d43d2e8662eef36cc230dcd9
|
[
"MIT"
] | null | null | null |
a, b, c, d, e = tuple(range(5))
print(f'{a:d} {b:f} {c:e} {d:g} {e}')
| 34.5
| 37
| 0.449275
| 19
| 69
| 1.631579
| 0.578947
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017241
| 0.15942
| 69
| 2
| 37
| 34.5
| 0.517241
| 0
| 0
| 0
| 0
| 0.5
| 0.385714
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
1071f85e5662e6cd11c2e9ec2292bcf5c46ca776
| 36
|
py
|
Python
|
async_websocket_client/__init__.py
|
pluzmedia/micropython_async_websocket_client
|
5a8c7976291a15602df24bfa7f38b7cf26721c8d
|
[
"Apache-2.0"
] | null | null | null |
async_websocket_client/__init__.py
|
pluzmedia/micropython_async_websocket_client
|
5a8c7976291a15602df24bfa7f38b7cf26721c8d
|
[
"Apache-2.0"
] | 1
|
2022-02-17T10:56:14.000Z
|
2022-02-17T20:00:50.000Z
|
async_websocket_client/__init__.py
|
pluzmedia/micropython_async_websocket_client
|
5a8c7976291a15602df24bfa7f38b7cf26721c8d
|
[
"Apache-2.0"
] | 1
|
2022-02-13T15:28:45.000Z
|
2022-02-13T15:28:45.000Z
|
from .ws import AsyncWebsocketClient
| 36
| 36
| 0.888889
| 4
| 36
| 8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 36
| 1
| 36
| 36
| 0.969697
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 1
| 1
| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
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| null | 0
| 0
| 0
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| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
52b02db8cf62dd6dbc85183f25a22f17b410be0f
| 14,579
|
py
|
Python
|
tests/integration/test_redis_integration.py
|
nhausman1/python-client
|
b15f76977dc3178634ee8e007b53f613ddd2ac7c
|
[
"Apache-2.0"
] | 13
|
2017-03-17T15:15:20.000Z
|
2022-03-14T22:24:10.000Z
|
tests/integration/test_redis_integration.py
|
nhausman1/python-client
|
b15f76977dc3178634ee8e007b53f613ddd2ac7c
|
[
"Apache-2.0"
] | 81
|
2017-01-12T23:06:48.000Z
|
2022-02-21T18:20:23.000Z
|
tests/integration/test_redis_integration.py
|
nhausman1/python-client
|
b15f76977dc3178634ee8e007b53f613ddd2ac7c
|
[
"Apache-2.0"
] | 14
|
2017-05-25T10:49:13.000Z
|
2021-12-27T16:39:20.000Z
|
"""Redis storage end to end tests."""
#pylint: disable=no-self-use,protected-access,line-too-long,too-few-public-methods
import json
import os
from splitio.client.util import get_metadata
from splitio.models import splits, impressions, events
from splitio.storage.redis import RedisSplitStorage, RedisSegmentStorage, RedisImpressionsStorage, \
RedisEventsStorage, RedisTelemetryStorage
from splitio.storage.adapters.redis import _build_default_client
from splitio.client.config import DEFAULT_CONFIG
class SplitStorageTests(object):
"""Redis Split storage e2e tests."""
def test_put_fetch(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
try:
storage = RedisSplitStorage(adapter)
with open(os.path.join(os.path.dirname(__file__), 'files', 'split_changes.json'), 'r') as flo:
split_changes = json.load(flo)
split_objects = [splits.from_raw(raw) for raw in split_changes['splits']]
for split_object in split_objects:
raw = split_object.to_json()
adapter.set(RedisSplitStorage._SPLIT_KEY.format(split_name=split_object.name), json.dumps(raw))
adapter.incr(RedisSplitStorage._TRAFFIC_TYPE_KEY.format(traffic_type_name=split_object.traffic_type_name))
original_splits = {split.name: split for split in split_objects}
fetched_splits = {name: storage.get(name) for name in original_splits.keys()}
assert set(original_splits.keys()) == set(fetched_splits.keys())
for original_split in original_splits.values():
fetched_split = fetched_splits[original_split.name]
assert original_split.traffic_type_name == fetched_split.traffic_type_name
assert original_split.seed == fetched_split.seed
assert original_split.algo == fetched_split.algo
assert original_split.status == fetched_split.status
assert original_split.change_number == fetched_split.change_number
assert original_split.killed == fetched_split.killed
assert original_split.default_treatment == fetched_split.default_treatment
for index, original_condition in enumerate(original_split.conditions):
fetched_condition = fetched_split.conditions[index]
assert original_condition.label == fetched_condition.label
assert original_condition.condition_type == fetched_condition.condition_type
assert len(original_condition.matchers) == len(fetched_condition.matchers)
assert len(original_condition.partitions) == len(fetched_condition.partitions)
adapter.set(RedisSplitStorage._SPLIT_TILL_KEY, split_changes['till'])
assert storage.get_change_number() == split_changes['till']
assert storage.is_valid_traffic_type('user') is True
assert storage.is_valid_traffic_type('account') is True
assert storage.is_valid_traffic_type('anything-else') is False
finally:
to_delete = [
"SPLITIO.split.sample_feature",
"SPLITIO.splits.till",
"SPLITIO.split.all_feature",
"SPLITIO.split.killed_feature",
"SPLITIO.split.Risk_Max_Deductible",
"SPLITIO.split.whitelist_feature",
"SPLITIO.split.regex_test",
"SPLITIO.split.boolean_test",
"SPLITIO.split.dependency_test",
"SPLITIO.trafficType.user",
"SPLITIO.trafficType.account"
]
for item in to_delete:
adapter.delete(item)
storage = RedisSplitStorage(adapter)
assert storage.is_valid_traffic_type('user') is False
assert storage.is_valid_traffic_type('account') is False
def test_get_all(self):
"""Test get all names & splits."""
adapter = _build_default_client({})
try:
storage = RedisSplitStorage(adapter)
with open(os.path.join(os.path.dirname(__file__), 'files', 'split_changes.json'), 'r') as flo:
split_changes = json.load(flo)
split_objects = [splits.from_raw(raw) for raw in split_changes['splits']]
for split_object in split_objects:
raw = split_object.to_json()
adapter.set(RedisSplitStorage._SPLIT_KEY.format(split_name=split_object.name), json.dumps(raw))
original_splits = {split.name: split for split in split_objects}
fetched_names = storage.get_split_names()
fetched_splits = {split.name: split for split in storage.get_all_splits()}
assert set(fetched_names) == set(fetched_splits.keys())
for original_split in original_splits.values():
fetched_split = fetched_splits[original_split.name]
assert original_split.traffic_type_name == fetched_split.traffic_type_name
assert original_split.seed == fetched_split.seed
assert original_split.algo == fetched_split.algo
assert original_split.status == fetched_split.status
assert original_split.change_number == fetched_split.change_number
assert original_split.killed == fetched_split.killed
assert original_split.default_treatment == fetched_split.default_treatment
for index, original_condition in enumerate(original_split.conditions):
fetched_condition = fetched_split.conditions[index]
assert original_condition.label == fetched_condition.label
assert original_condition.condition_type == fetched_condition.condition_type
assert len(original_condition.matchers) == len(fetched_condition.matchers)
assert len(original_condition.partitions) == len(fetched_condition.partitions)
finally:
adapter.delete(
'SPLITIO.split.sample_feature',
'SPLITIO.splits.till',
'SPLITIO.split.all_feature',
'SPLITIO.split.killed_feature',
'SPLITIO.split.Risk_Max_Deductible',
'SPLITIO.split.whitelist_feature',
'SPLITIO.split.regex_test',
'SPLITIO.split.boolean_test',
'SPLITIO.split.dependency_test'
)
class SegmentStorageTests(object):
"""Redis Segment storage e2e tests."""
def test_put_fetch_contains(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
try:
storage = RedisSegmentStorage(adapter)
adapter.sadd(storage._get_key('some_segment'), 'key1', 'key2', 'key3', 'key4')
adapter.set(storage._get_till_key('some_segment'), 123)
assert storage.segment_contains('some_segment', 'key0') is False
assert storage.segment_contains('some_segment', 'key1') is True
assert storage.segment_contains('some_segment', 'key2') is True
assert storage.segment_contains('some_segment', 'key3') is True
assert storage.segment_contains('some_segment', 'key4') is True
assert storage.segment_contains('some_segment', 'key5') is False
fetched = storage.get('some_segment')
assert fetched.keys == set(['key1', 'key2', 'key3', 'key4'])
assert fetched.change_number == 123
finally:
adapter.delete('SPLITIO.segment.some_segment', 'SPLITIO.segment.some_segment.till')
class ImpressionsStorageTests(object):
"""Redis Impressions storage e2e tests."""
def _put_impressions(self, adapter, metadata):
storage = RedisImpressionsStorage(adapter, metadata)
storage.put([
impressions.Impression('key1', 'feature1', 'on', 'l1', 123456, 'b1', 321654),
impressions.Impression('key2', 'feature1', 'on', 'l1', 123456, 'b1', 321654),
impressions.Impression('key3', 'feature1', 'on', 'l1', 123456, 'b1', 321654)
])
def test_put_fetch_contains(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
try:
self._put_impressions(adapter, get_metadata({}))
imps = adapter.lrange('SPLITIO.impressions', 0, 2)
assert len(imps) == 3
for rawImpression in imps:
impression = json.loads(rawImpression)
assert impression['m']['i'] != 'NA'
assert impression['m']['n'] != 'NA'
finally:
adapter.delete('SPLITIO.impressions')
def test_put_fetch_contains_ip_address_disabled(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
try:
cfg = DEFAULT_CONFIG.copy()
cfg.update({'IPAddressesEnabled': False})
self._put_impressions(adapter, get_metadata(cfg))
imps = adapter.lrange('SPLITIO.impressions', 0, 2)
assert len(imps) == 3
for rawImpression in imps:
impression = json.loads(rawImpression)
assert impression['m']['i'] == 'NA'
assert impression['m']['n'] == 'NA'
finally:
adapter.delete('SPLITIO.impressions')
class EventsStorageTests(object):
"""Redis Events storage e2e tests."""
def _put_events(self, adapter, metadata):
storage = RedisEventsStorage(adapter, metadata)
storage.put([
events.EventWrapper(
event=events.Event('key1', 'user', 'purchase', 3.5, 123456, None),
size=1024,
),
events.EventWrapper(
event=events.Event('key2', 'user', 'purchase', 3.5, 123456, None),
size=1024,
),
events.EventWrapper(
event=events.Event('key3', 'user', 'purchase', 3.5, 123456, None),
size=1024,
),
])
def test_put_fetch_contains(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
try:
self._put_events(adapter, get_metadata({}))
evts = adapter.lrange('SPLITIO.events', 0, 2)
assert len(evts) == 3
for rawEvent in evts:
event = json.loads(rawEvent)
assert event['m']['i'] != 'NA'
assert event['m']['n'] != 'NA'
finally:
adapter.delete('SPLITIO.events')
def test_put_fetch_contains_ip_address_disabled(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
try:
cfg = DEFAULT_CONFIG.copy()
cfg.update({'IPAddressesEnabled': False})
self._put_events(adapter, get_metadata(cfg))
evts = adapter.lrange('SPLITIO.events', 0, 2)
assert len(evts) == 3
for rawEvent in evts:
event = json.loads(rawEvent)
assert event['m']['i'] == 'NA'
assert event['m']['n'] == 'NA'
finally:
adapter.delete('SPLITIO.events')
class TelemetryStorageTests(object):
"""Redis Telemetry storage e2e tests."""
def test_put_fetch_contains(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
cfg = DEFAULT_CONFIG.copy()
cfg.update({'IPAddressesEnabled': False})
metadata = get_metadata(cfg)
storage = RedisTelemetryStorage(adapter, metadata)
try:
storage.inc_counter('counter1')
storage.inc_counter('counter1')
storage.inc_counter('counter2')
assert adapter.get(storage._get_counter_key('counter1')) == '2'
assert adapter.get(storage._get_counter_key('counter2')) == '1'
storage.inc_latency('latency1', 3)
storage.inc_latency('latency1', 3)
storage.inc_latency('latency2', 6)
assert adapter.get(storage._get_latency_key('latency1', 3)) == '2'
assert adapter.get(storage._get_latency_key('latency2', 6)) == '1'
storage.put_gauge('gauge1', 3)
storage.put_gauge('gauge2', 1)
assert adapter.get(storage._get_gauge_key('gauge1')) == '3'
assert adapter.get(storage._get_gauge_key('gauge2')) == '1'
finally:
adapter.delete(
storage._get_counter_key('counter1'),
storage._get_counter_key('counter2'),
storage._get_latency_key('latency1', 3),
storage._get_latency_key('latency2', 6),
storage._get_gauge_key('gauge1'),
storage._get_gauge_key('gauge2')
)
def test_put_fetch_contains_ip_address_disabled(self):
"""Test storing and retrieving splits in redis."""
adapter = _build_default_client({})
cfg = DEFAULT_CONFIG.copy()
cfg.update({'IPAddressesEnabled': False})
metadata = get_metadata(cfg)
storage = RedisTelemetryStorage(adapter, metadata)
try:
storage.inc_counter('counter1')
storage.inc_counter('counter1')
storage.inc_counter('counter2')
assert adapter.get(storage._get_counter_key('counter1')) == '2'
assert adapter.get(storage._get_counter_key('counter2')) == '1'
storage.inc_latency('latency1', 3)
storage.inc_latency('latency1', 3)
storage.inc_latency('latency2', 6)
assert adapter.get(storage._get_latency_key('latency1', 3)) == '2'
assert adapter.get(storage._get_latency_key('latency2', 6)) == '1'
storage.put_gauge('gauge1', 3)
storage.put_gauge('gauge2', 1)
assert adapter.get(storage._get_gauge_key('gauge1')) == '3'
assert adapter.get(storage._get_gauge_key('gauge2')) == '1'
finally:
adapter.delete(
storage._get_counter_key('counter1'),
storage._get_counter_key('counter2'),
storage._get_latency_key('latency1', 3),
storage._get_latency_key('latency2', 6),
storage._get_gauge_key('gauge1'),
storage._get_gauge_key('gauge2')
)
| 45.417445
| 122
| 0.61225
| 1,539
| 14,579
| 5.552307
| 0.119558
| 0.036279
| 0.031129
| 0.0323
| 0.8055
| 0.79134
| 0.766764
| 0.759743
| 0.701346
| 0.701346
| 0
| 0.018457
| 0.279031
| 14,579
| 320
| 123
| 45.559375
| 0.794501
| 0.045957
| 0
| 0.65251
| 0
| 0
| 0.109232
| 0.040483
| 0
| 0
| 0
| 0
| 0.239382
| 1
| 0.042471
| false
| 0
| 0.027027
| 0
| 0.088803
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
52b2297aa09a3e996e857ab31f5bec159dcfa434
| 11,936
|
py
|
Python
|
test/test_slipharden.py
|
lynnmunday/neml
|
2c0e3db9f849345dba01d64fc8488e2b97e477dd
|
[
"MIT"
] | null | null | null |
test/test_slipharden.py
|
lynnmunday/neml
|
2c0e3db9f849345dba01d64fc8488e2b97e477dd
|
[
"MIT"
] | null | null | null |
test/test_slipharden.py
|
lynnmunday/neml
|
2c0e3db9f849345dba01d64fc8488e2b97e477dd
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
from neml import history, interpolate
from neml.math import tensors, rotations
from neml.cp import crystallography, slipharden, sliprules
from common import differentiate
from nicediff import *
import unittest
import numpy as np
import numpy.linalg as la
class CommonSlipHardening():
def test_d_hist_d_stress(self):
d = np.array(self.model.d_hist_d_s(self.S, self.Q, self.H, self.L, self.T, self.sliprule, self.fixed))
nd = diff_history_symmetric(lambda s: self.model.hist(s, self.Q, self.H, self.L, self.T,
self.sliprule, self.fixed), self.S)
self.assertTrue(np.allclose(nd.reshape(d.shape), d))
def test_d_hist_d_hist(self):
d = np.array(self.model.d_hist_d_h(self.S, self.Q, self.H, self.L, self.T, self.sliprule,
self.fixed))
nd = diff_history_history(lambda h: self.model.hist(self.S, self.Q, h, self.L, self.T,
self.sliprule, self.fixed), self.H)
print(d)
print(nd)
self.assertTrue(np.allclose(nd.reshape(d.shape), d))
def test_d_hist_to_tau_d_hist(self):
for g in range(self.L.ngroup):
for i in range(self.L.nslip(g)):
nd = diff_history_scalar(lambda h: self.model.hist_to_tau(g, i, h, self.T, self.fixed), self.H)
d = self.model.d_hist_to_tau(g, i, self.H, self.T, self.fixed)
self.assertTrue(np.allclose(np.array(nd), np.array(d)))
class CommonSlipSingleHardening():
def test_d_hist_map(self):
nd = diff_history_scalar(lambda h: self.model.hist_map(h, self.T,
self.fixed), self.H)
H = self.model.d_hist_map(self.H, self.T, self.fixed)
self.assertTrue(np.allclose(np.array(H), np.array(nd)))
def test_hist_to_tau(self):
for g in range(self.L.ngroup):
for i in range(self.L.nslip(g)):
self.assertTrue(np.isclose(self.strength + self.static + self.nye_part,
self.model.hist_to_tau(g, i, self.H, self.T, self.fixed)))
class CommonSlipSingleStrengthHardening():
def test_hist_map(self):
self.assertTrue(np.isclose(self.model.hist_map(self.H, self.T,
self.fixed), self.strength + self.static + self.nye_part))
def test_hist(self):
h = self.model.hist(self.S, self.Q, self.H, self.L, self.T, self.sliprule, self.fixed)
self.assertTrue(np.isclose(h.get_scalar("strength"), self.model.hist_rate(
self.S, self.Q, self.H, self.L, self.T, self.sliprule, self.fixed)))
def test_d_hist_rate_d_stress(self):
dfn = lambda s: self.model.hist_rate(s, self.Q, self.H,
self.L, self.T, self.sliprule, self.fixed)
nd = diff_scalar_symmetric(dfn, self.S)
d = self.model.d_hist_rate_d_stress(self.S, self.Q, self.H, self.L,
self.T, self.sliprule, self.fixed)
self.assertEqual(d,nd)
def test_d_hist_rate_d_hist(self):
dfn = lambda h: self.model.hist_rate(self.S, self.Q, h,
self.L, self.T, self.sliprule, self.fixed)
nd = diff_history_scalar(dfn, self.H)
d = self.model.d_hist_rate_d_hist(self.S, self.Q, self.H, self.L,
self.T, self.sliprule, self.fixed)
self.assertTrue(np.isclose(d.get_scalar("strength"), nd.get_scalar("strength")))
def test_nye_parts_match(self):
self.assertTrue(np.isclose(self.model.nye_part(self.nye, self.T),
self.model.nye_contribution(self.fixed, self.T)))
def test_no_nye_works(self):
self.assertTrue(np.isclose(self.model.nye_contribution(history.History(), self.T),
0.0))
class CommonPlasticSlipHardening():
def sum_slip(self):
return sum(np.abs(self.sliprule.slip(g, i, self.S, self.Q, self.H, self.L,
self.T, self.fixed)) for g in range(self.L.ngroup) for i in range(self.L.nslip(g)))
def test_hist_rate(self):
ss = self.sum_slip()
self.assertTrue(np.isclose(self.model.hist_rate(self.S, self.Q, self.H,
self.L, self.T, self.sliprule, self.fixed), self.model.hist_factor(self.H.get_scalar("strength"),
self.L, self.T, self.fixed) * ss))
def test_d_factor(self):
nd = differentiate(lambda s: self.model.hist_factor(s, self.L, self.T, self.fixed),
self.strength)
d = self.model.d_hist_factor(self.strength, self.L, self.T, self.fixed)
self.assertTrue(np.isclose(nd, d))
class TestVoceHardening(unittest.TestCase, CommonPlasticSlipHardening,
CommonSlipSingleStrengthHardening, CommonSlipSingleHardening, CommonSlipHardening):
def setUp(self):
self.L = crystallography.CubicLattice(1.0)
self.L.add_slip_system([1,1,0],[1,1,1])
self.Q = rotations.Orientation(35.0,17.0,14.0, angle_type = "degrees")
self.S = tensors.Symmetric(np.array([
[100.0,-25.0,10.0],
[-25.0,-17.0,15.0],
[10.0, 15.0,35.0]]))
self.strength = 35.0
self.H = history.History()
self.H.add_scalar("strength")
self.H.set_scalar("strength", self.strength)
self.T = 300.0
self.tau0 = 10.0
self.tau_sat = 50.0
self.b = 2.5
self.static = self.tau0
self.model = slipharden.VoceSlipHardening(self.tau_sat, self.b, self.tau0)
self.g0 = 1.0
self.n = 3.0
self.sliprule = sliprules.PowerLawSlipRule(self.model, self.g0, self.n)
self.fixed = history.History()
self.nye = tensors.RankTwo([[1.1,1.2,1.3],[2.1,2.2,2.3],[3.1,3.2,3.3]])
self.nye_part = 0.0
def test_initialize_hist(self):
H = history.History()
self.model.populate_history(H)
self.model.init_history(H)
self.assertTrue(np.isclose(H.get_scalar('strength'), 0.0))
def test_static_strength(self):
self.assertTrue(np.isclose(self.model.static_strength(self.T), self.tau0))
def test_factor(self):
self.assertTrue(np.isclose(
self.model.hist_factor(self.strength, self.L, self.T, self.fixed),
self.b * (self.tau_sat - self.strength)))
def test_nye_factor(self):
self.assertTrue(np.isclose(
self.model.nye_part(self.nye, self.T), 0.0))
def test_use_nye(self):
self.assertFalse(self.model.use_nye)
class TestNyeVoceHardening(unittest.TestCase, CommonPlasticSlipHardening,
CommonSlipSingleStrengthHardening, CommonSlipSingleHardening, CommonSlipHardening):
def setUp(self):
self.L = crystallography.CubicLattice(1.0)
self.L.add_slip_system([1,1,0],[1,1,1])
self.Q = rotations.Orientation(35.0,17.0,14.0, angle_type = "degrees")
self.S = tensors.Symmetric(np.array([
[100.0,-25.0,10.0],
[-25.0,-17.0,15.0],
[10.0, 15.0,35.0]]))
self.strength = 35.0
self.H = history.History()
self.H.add_scalar("strength")
self.H.set_scalar("strength", self.strength)
self.T = 300.0
self.tau0 = 10.0
self.tau_sat = 50.0
self.b = 2.5
self.static = self.tau0
self.k = 1.2
self.model = slipharden.VoceSlipHardening(self.tau_sat, self.b, self.tau0,
k = self.k)
self.g0 = 1.0
self.n = 3.0
self.sliprule = sliprules.PowerLawSlipRule(self.model, self.g0, self.n)
self.nye = tensors.RankTwo([[1.1,1.2,1.3],[2.1,2.2,2.3],[3.1,3.2,3.3]])
self.nye_part = self.k * np.sqrt(la.norm(self.nye.data.reshape((3,3)), ord = 'fro'))
self.fixed = history.History()
self.fixed.add_ranktwo("nye")
self.fixed.set_ranktwo("nye", self.nye)
def test_initialize_hist(self):
H = history.History()
self.model.populate_history(H)
self.model.init_history(H)
self.assertTrue(np.isclose(H.get_scalar('strength'), 0.0))
def test_static_strength(self):
self.assertTrue(np.isclose(self.model.static_strength(self.T), self.tau0))
def test_factor(self):
self.assertTrue(np.isclose(
self.model.hist_factor(self.strength, self.L, self.T, self.fixed),
self.b * (self.tau_sat - self.strength)))
def test_nye_factor(self):
self.assertTrue(np.isclose(
self.model.nye_part(self.nye, self.T), self.nye_part))
def test_use_nye(self):
self.assertTrue(self.model.use_nye)
class TestMultiVoceHardening(unittest.TestCase,
CommonSlipSingleHardening, CommonSlipHardening):
def setUp(self):
self.L = crystallography.CubicLattice(1.0)
self.L.add_slip_system([1,1,0],[1,1,1])
self.Q = rotations.Orientation(35.0,17.0,14.0, angle_type = "degrees")
self.S = tensors.Symmetric(np.array([
[100.0,-25.0,10.0],
[-25.0,-17.0,15.0],
[10.0, 15.0,35.0]]))
self.strength_0 = 35.0
self.strength_1 = -5.0
self.H = history.History()
self.H.add_scalar("strength0")
self.H.set_scalar("strength0", self.strength_0)
self.H.add_scalar("strength1")
self.H.set_scalar("strength1", self.strength_1)
self.T = 300.0
self.tau0_1 = 10.0
self.tau_sat_1 = 50.0
self.b_1 = 2.5
self.tau0_2 = 5.0
self.tau_sat_2 = -25.0
self.b_2 = 1.5
self.static = self.tau0_1 + self.tau0_2
self.strength = self.strength_0 + self.strength_1
self.model1 = slipharden.VoceSlipHardening(self.tau_sat_1, self.b_1, self.tau0_1)
self.model2 = slipharden.VoceSlipHardening(self.tau_sat_2, self.b_2, self.tau0_2)
self.model = slipharden.SumSlipSingleStrengthHardening([self.model1,
self.model2])
self.g0 = 1.0
self.n = 3.0
self.sliprule = sliprules.PowerLawSlipRule(self.model, self.g0, self.n)
self.fixed = history.History()
self.nye = tensors.RankTwo([[1.1,1.2,1.3],[2.1,2.2,2.3],[3.1,3.2,3.3]])
self.nye_part = 0.0
def test_initialize_hist(self):
H = history.History()
self.model.populate_history(H)
self.model.init_history(H)
self.assertTrue(np.isclose(H.get_scalar('strength0'), 0.0))
self.assertTrue(np.isclose(H.get_scalar('strength1'), 0.0))
def test_hist_def(self):
hrate_1 = self.b_1 * (self.tau_sat_1 - self.strength_0) * self.sliprule.sum_slip(self.S, self.Q,
self.H, self.L, self.T, self.fixed)
hrate_2 = self.b_2 * (self.tau_sat_2 - self.strength_1) * self.sliprule.sum_slip(self.S, self.Q,
self.H, self.L, self.T, self.fixed)
hrates = np.array([hrate_1, hrate_2])
hist = self.model.hist(self.S, self.Q, self.H, self.L, self.T, self.sliprule, self.fixed)
self.assertTrue(np.allclose(hrates, hist))
def test_use_nye(self):
self.assertFalse(self.model.use_nye)
class TestLinearSlipHardening(unittest.TestCase, CommonPlasticSlipHardening,
CommonSlipSingleStrengthHardening, CommonSlipSingleHardening, CommonSlipHardening):
def setUp(self):
self.L = crystallography.CubicLattice(1.0)
self.L.add_slip_system([1,1,0],[1,1,1])
self.Q = rotations.Orientation(35.0,17.0,14.0, angle_type = "degrees")
self.S = tensors.Symmetric(np.array([
[100.0,-25.0,10.0],
[-25.0,-17.0,15.0],
[10.0, 15.0,35.0]]))
self.strength = 35.0
self.H = history.History()
self.H.add_scalar("strength")
self.H.set_scalar("strength", self.strength)
self.T = 300.0
self.tau0 = 10.0
self.k1 = 2.0
self.k2 = 3.0
self.static = self.tau0
self.model = slipharden.LinearSlipHardening(self.tau0, self.k1, self.k2)
self.g0 = 1.0
self.n = 3.0
self.sliprule = sliprules.PowerLawSlipRule(self.model, self.g0, self.n)
self.nye = tensors.RankTwo([[1.1,1.2,1.3],[2.1,2.2,2.3],[3.1,3.2,3.3]])
self.nye_part = self.k2 * la.norm(self.nye.data.reshape((3,3)), ord = 'fro')
self.fixed = history.History()
self.fixed.add_ranktwo("nye")
self.fixed.set_ranktwo("nye", self.nye)
def test_initialize_hist(self):
H = history.History()
self.model.populate_history(H)
self.model.init_history(H)
self.assertTrue(np.isclose(H.get_scalar('strength'), 0.0))
def test_static_strength(self):
self.assertTrue(np.isclose(self.model.static_strength(self.T), self.tau0))
def test_factor(self):
self.assertTrue(np.isclose(
self.model.hist_factor(self.strength, self.L, self.T, self.fixed),
self.k1))
def test_nye_factor(self):
self.assertTrue(np.isclose(
self.model.nye_part(self.nye, self.T), self.nye_part))
def test_use_nye(self):
self.assertTrue(self.model.use_nye)
| 33.909091
| 106
| 0.671247
| 1,949
| 11,936
| 3.990764
| 0.072858
| 0.061327
| 0.038185
| 0.065055
| 0.820391
| 0.775392
| 0.762792
| 0.720494
| 0.704423
| 0.678323
| 0
| 0.043724
| 0.170325
| 11,936
| 351
| 107
| 34.005698
| 0.741694
| 0.001759
| 0
| 0.573585
| 0
| 0
| 0.017124
| 0
| 0
| 0
| 0
| 0
| 0.120755
| 1
| 0.135849
| false
| 0
| 0.030189
| 0.003774
| 0.2
| 0.007547
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
52b310530564de0befb12d18100ed302b415e17f
| 88
|
py
|
Python
|
Core/Mail/mail_config.py
|
dikshita-mehta/Sahaay
|
368826cb0b9f7085f901895a29b1df0895f90f5b
|
[
"MIT"
] | 4
|
2021-09-29T13:53:10.000Z
|
2021-11-08T09:35:22.000Z
|
Core/Mail/mail_config.py
|
dikshita-mehta/Sahaay
|
368826cb0b9f7085f901895a29b1df0895f90f5b
|
[
"MIT"
] | 23
|
2021-08-23T04:39:20.000Z
|
2022-01-13T06:57:14.000Z
|
Core/Mail/mail_config.py
|
dikshita-mehta/Sahaay
|
368826cb0b9f7085f901895a29b1df0895f90f5b
|
[
"MIT"
] | 6
|
2021-08-18T08:24:34.000Z
|
2021-11-23T05:40:41.000Z
|
import smtplib
"""
#Add SMTP files here and other related config files here
"""
| 12.571429
| 57
| 0.670455
| 12
| 88
| 4.916667
| 0.833333
| 0.305085
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.25
| 88
| 6
| 58
| 14.666667
| 0.893939
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
52dc019ecfbdaf34e137a160ff5b6855067138d7
| 26
|
py
|
Python
|
src/language/__init__.py
|
easygittool/EasyGitTool
|
55ce8aaa6756715e864afdfb3b420d62eef84437
|
[
"Apache-2.0"
] | 1
|
2019-02-09T11:18:29.000Z
|
2019-02-09T11:18:29.000Z
|
src/language/__init__.py
|
easygittool/EasyGitTool
|
55ce8aaa6756715e864afdfb3b420d62eef84437
|
[
"Apache-2.0"
] | null | null | null |
src/language/__init__.py
|
easygittool/EasyGitTool
|
55ce8aaa6756715e864afdfb3b420d62eef84437
|
[
"Apache-2.0"
] | null | null | null |
from src.language import *
| 26
| 26
| 0.807692
| 4
| 26
| 5.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.115385
| 26
| 1
| 26
| 26
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
52ec2c7db51e620e81678a46defd97cdbc90f4df
| 89
|
py
|
Python
|
lapidary/config/__init__.py
|
efeslab/lapidary
|
8746e208fc5757ec0076ddbdc86a96808418c830
|
[
"MIT"
] | 30
|
2019-07-12T02:35:33.000Z
|
2022-02-22T03:34:35.000Z
|
lapidary/config/__init__.py
|
efeslab/lapidary
|
8746e208fc5757ec0076ddbdc86a96808418c830
|
[
"MIT"
] | 1
|
2020-08-27T14:52:56.000Z
|
2020-08-28T14:58:30.000Z
|
lapidary/config/__init__.py
|
efeslab/lapidary
|
8746e208fc5757ec0076ddbdc86a96808418c830
|
[
"MIT"
] | 7
|
2019-07-14T09:08:29.000Z
|
2021-04-16T17:01:08.000Z
|
from .LapidaryConfig import *
from .FlagConfigure import *
from .Gem5FlagConfig import *
| 22.25
| 29
| 0.797753
| 9
| 89
| 7.888889
| 0.555556
| 0.28169
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012987
| 0.134831
| 89
| 3
| 30
| 29.666667
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
52fab14bd65f635d919782b860f5266e35f88a81
| 48
|
py
|
Python
|
PikaBotTg/resources/__init__.py
|
ItzSjDude/miniature-journey
|
06d7315a4b4ee064ad7348d91849f6220351a3a7
|
[
"MIT"
] | null | null | null |
PikaBotTg/resources/__init__.py
|
ItzSjDude/miniature-journey
|
06d7315a4b4ee064ad7348d91849f6220351a3a7
|
[
"MIT"
] | null | null | null |
PikaBotTg/resources/__init__.py
|
ItzSjDude/miniature-journey
|
06d7315a4b4ee064ad7348d91849f6220351a3a7
|
[
"MIT"
] | null | null | null |
from .get_client import get_client as GetClient
| 24
| 47
| 0.854167
| 8
| 48
| 4.875
| 0.75
| 0.461538
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 48
| 1
| 48
| 48
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
5e18975862083eeb09c85c539bc71e48dfbebb64
| 25
|
py
|
Python
|
demo.py
|
Desaiakshata/CovidTracker
|
5609b67b7c48abf308e12e8d29cb7cf49cb24866
|
[
"MIT"
] | null | null | null |
demo.py
|
Desaiakshata/CovidTracker
|
5609b67b7c48abf308e12e8d29cb7cf49cb24866
|
[
"MIT"
] | null | null | null |
demo.py
|
Desaiakshata/CovidTracker
|
5609b67b7c48abf308e12e8d29cb7cf49cb24866
|
[
"MIT"
] | null | null | null |
from program import app
| 12.5
| 24
| 0.8
| 4
| 25
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 25
| 1
| 25
| 25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
eabf6ba6e49b92e56fb2d3b0d81bd851541797e9
| 134
|
py
|
Python
|
Day8/Check same case.py
|
ColdTears619/My100DaysOfCode
|
aa33d721a0fa71b2e2c5ebf5b22594f40e443f68
|
[
"MIT"
] | 1
|
2021-12-25T16:18:42.000Z
|
2021-12-25T16:18:42.000Z
|
Day8/Check same case.py
|
ColdTears619/My100DaysOfCode
|
aa33d721a0fa71b2e2c5ebf5b22594f40e443f68
|
[
"MIT"
] | null | null | null |
Day8/Check same case.py
|
ColdTears619/My100DaysOfCode
|
aa33d721a0fa71b2e2c5ebf5b22594f40e443f68
|
[
"MIT"
] | null | null | null |
def same_case(a, b):
return a.isupper() == b.isupper() if a.isalpha() and b.isalpha() else -1
print(same_case('H', 'C'))
| 33.5
| 80
| 0.58209
| 23
| 134
| 3.304348
| 0.652174
| 0.210526
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.009434
| 0.208955
| 134
| 4
| 81
| 33.5
| 0.707547
| 0
| 0
| 0
| 0
| 0
| 0.014815
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0.333333
| 0.666667
| 0.333333
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
dc2ba1cfd97c48ab5d57d309546fb5c50acdad38
| 58
|
py
|
Python
|
datasets/__init__.py
|
atomicoo/Tacotron2-PyTorch
|
71eadf2abafa201648dc16cbfb742ab0032077c9
|
[
"MIT"
] | 9
|
2021-05-16T01:21:01.000Z
|
2021-12-20T13:57:49.000Z
|
datasets/__init__.py
|
atomicoo/Tacotron2-PyTorch
|
71eadf2abafa201648dc16cbfb742ab0032077c9
|
[
"MIT"
] | 1
|
2021-11-05T01:36:27.000Z
|
2021-11-05T01:36:27.000Z
|
datasets/__init__.py
|
atomicoo/Tacotron2-PyTorch
|
71eadf2abafa201648dc16cbfb742ab0032077c9
|
[
"MIT"
] | 2
|
2021-05-16T01:21:24.000Z
|
2021-09-04T02:41:06.000Z
|
from .text2mel import Text2MelDataset, Text2MelDataLoader
| 29
| 57
| 0.87931
| 5
| 58
| 10.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.056604
| 0.086207
| 58
| 1
| 58
| 58
| 0.90566
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dc67b01ed16fcb8f41b03b96a8c941317f29275b
| 2,266
|
py
|
Python
|
utils/transform.py
|
uta-smile/TVT
|
f4f7a0c7021d8bbd4cb214f5f97b57004944cef5
|
[
"MIT"
] | 23
|
2021-11-26T08:34:53.000Z
|
2022-03-14T13:37:41.000Z
|
utils/transform.py
|
uta-smile/TVT
|
f4f7a0c7021d8bbd4cb214f5f97b57004944cef5
|
[
"MIT"
] | 6
|
2021-12-30T01:51:46.000Z
|
2022-03-16T15:28:31.000Z
|
utils/transform.py
|
uta-smile/TVT
|
f4f7a0c7021d8bbd4cb214f5f97b57004944cef5
|
[
"MIT"
] | 2
|
2022-03-08T08:45:41.000Z
|
2022-03-14T02:25:20.000Z
|
# coding=utf-8
from __future__ import absolute_import, division, print_function
from torchvision import transforms
from data.data_list_image import Normalize
def get_transform(dataset, img_size):
if dataset in ['svhn2mnist', 'usps2mnist', 'mnist2usps']:
transform_source = transforms.Compose([
transforms.RandomResizedCrop((img_size, img_size), scale=(0.75, 1.2)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
])
transform_target = transforms.Compose([
transforms.RandomResizedCrop((img_size, img_size), scale=(0.75, 1.2)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
])
transform_test = transforms.Compose([
transforms.Resize((img_size, img_size)),
transforms.ToTensor(),
transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
])
elif dataset in ['visda17', 'office-home']:
transform_source = transforms.Compose([
transforms.Resize((img_size+32, img_size+32)),
transforms.RandomCrop(img_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
Normalize(meanfile='./data/ilsvrc_2012_mean.npy')
])
transform_test = transforms.Compose([
transforms.Resize((img_size, img_size)),
transforms.ToTensor(),
Normalize(meanfile='./data/ilsvrc_2012_mean.npy')
])
else:
transform_source = transforms.Compose([
transforms.Resize((img_size+32, img_size+32)),
transforms.RandomCrop(img_size),
transforms.RandomHorizontalFlip(),
transforms.ToTensor(),
Normalize(meanfile='./data/ilsvrc_2012_mean.npy')
])
transform_test = transforms.Compose([
transforms.Resize((img_size, img_size)),
transforms.ToTensor(),
Normalize(meanfile='./data/ilsvrc_2012_mean.npy')
])
return transform_source, transform_source, transform_test
| 38.40678
| 86
| 0.57767
| 234
| 2,266
| 5.405983
| 0.235043
| 0.028459
| 0.028459
| 0.037945
| 0.773123
| 0.761265
| 0.761265
| 0.761265
| 0.761265
| 0.761265
| 0
| 0.047679
| 0.296558
| 2,266
| 58
| 87
| 39.068966
| 0.745922
| 0.005296
| 0
| 0.808511
| 0
| 0
| 0.069426
| 0.048064
| 0
| 0
| 0
| 0
| 0
| 1
| 0.021277
| false
| 0
| 0.06383
| 0
| 0.106383
| 0.021277
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
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| 0
| 0
| 1
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dc7b6808ed3f7a5d214a3fdb0105f8fed27b01c7
| 153
|
py
|
Python
|
ivf/core/sfs/isophote.py
|
tody411/ImageViewerFramework
|
5c183c34e65494b6af1287e70152b995a868c6ac
|
[
"MIT"
] | null | null | null |
ivf/core/sfs/isophote.py
|
tody411/ImageViewerFramework
|
5c183c34e65494b6af1287e70152b995a868c6ac
|
[
"MIT"
] | null | null | null |
ivf/core/sfs/isophote.py
|
tody411/ImageViewerFramework
|
5c183c34e65494b6af1287e70152b995a868c6ac
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
## @package ivf.core.sfs.isophote
#
# ivf.core.sfs.isophote utility package.
# @author tody
# @date 2016/02/08
| 15.3
| 41
| 0.581699
| 20
| 153
| 4.45
| 0.75
| 0.157303
| 0.224719
| 0.404494
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.077586
| 0.24183
| 153
| 9
| 42
| 17
| 0.689655
| 0.888889
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dc7c2ca15fa68007cb2ed8e89ca8b110c26adc54
| 7,867
|
py
|
Python
|
GameOfLife.py
|
Nzuri-hpp/GameOfLife
|
796d7a61f9483e1bc15c1af4d5dc3b60cde72ea2
|
[
"MIT"
] | 1
|
2019-11-01T06:21:47.000Z
|
2019-11-01T06:21:47.000Z
|
GameOfLife.py
|
Nzuri-hpp/GameOfLife
|
796d7a61f9483e1bc15c1af4d5dc3b60cde72ea2
|
[
"MIT"
] | null | null | null |
GameOfLife.py
|
Nzuri-hpp/GameOfLife
|
796d7a61f9483e1bc15c1af4d5dc3b60cde72ea2
|
[
"MIT"
] | null | null | null |
import numpy as np
import matplotlib
from matplotlib import pyplot as plt
import matplotlib.animation as animation
from matplotlib.widgets import Button
from scipy.ndimage import convolve
matplotlib.rcParams['interactive'] == True
plt.rcParams["figure.figsize"] = [4,3]
try:
from IPython import get_ipython
get_ipython().run_line_magic('matplotlib', 'qt')
except Exception:
print('-- IPython get error')
def genesis(gField):
gKernel = np.array([[1,1,1],[1,0,1],[1,1,1]])
gNeighbors = convolve(gField, gKernel)
gN_Living = gNeighbors * gField
gN_Dead = gNeighbors * (1 - gField)
gField_genesis = gField + (gN_Dead == 3)
gField_genesis = gField_genesis - (gN_Living < 2)*gField - (gN_Living > 3)
return gField_genesis
gSize = 38
gField = np.zeros((gSize, gSize))
gField[5,5]=1
gField[5,6]=1
gField[6,5]=1
gField[7,5]=1
gSteps = 10000
gTime = 50
fig = plt.figure()
axes = fig.add_subplot(1,1,1)
axes.matshow(gField)
def animate(i):
global gField
if i == 0:
axes.matshow(gField)
return
axes.clear()
axes.matshow(gField)
fig.canvas.draw()
fig.canvas.flush_events()
#plt.show()
gField = genesis(gField)
print(f"Iteration: {i}")
def onclick(event):
global gField
global axes
if not event.inaxes == axes:
return
if event.xdata is None or event.ydata is None:
print(f"-- Event: Touch Out_of_Field")
return
x, y = int(round(event.xdata)), int(round(event.ydata))
gField[y,x] = not gField[y,x]
axes.clear()
axes.matshow(gField)
fig.canvas.draw()
fig.canvas.flush_events()
print(f"-- Event: Touch {(x,y)}")
cid = fig.canvas.mpl_connect('button_press_event', onclick)
def playCallback(event):
ani = animation.FuncAnimation(fig, animate, interval=gTime, frames=gSteps, repeat=False)
fig.canvas.draw()
fig.canvas.flush_events()
#plt.show()
return ani
gGunField = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0],
[0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
def ggunCallback(event):
global gField
global gGunField
gField = gGunField
axes.clear()
axes.matshow(gField)
fig.canvas.draw()
fig.canvas.flush_events()
axggun = plt.axes([0.4, 0.03, 0.1, 0.075])
axplay = plt.axes([0.5, 0.03, 0.1, 0.075])
bnPlay = Button(axplay, 'Play')
bnGGun = Button(axggun, 'Gun')
bnPlay.on_clicked(playCallback)
bnGGun.on_clicked(ggunCallback)
plt.show()
| 48.263804
| 139
| 0.384263
| 1,785
| 7,867
| 1.679552
| 0.062745
| 0.921281
| 1.357905
| 1.779853
| 0.562375
| 0.562375
| 0.556371
| 0.555704
| 0.555704
| 0.540027
| 0
| 0.308986
| 0.38045
| 7,867
| 162
| 140
| 48.561728
| 0.306114
| 0.002542
| 0
| 0.418803
| 0
| 0
| 0.019171
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.042735
| false
| 0
| 0.059829
| 0
| 0.145299
| 0.034188
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dc7e9fb859c9d8e8a7949dbbbdba1e66f061cc5d
| 267
|
py
|
Python
|
code/code.py
|
CedarGroveStudios/Scale
|
c3ac07319f08790a8f6fe3b904f3adc93c2c94fd
|
[
"MIT-0"
] | 1
|
2021-12-08T12:37:18.000Z
|
2021-12-08T12:37:18.000Z
|
code/code.py
|
CedarGroveStudios/Scale
|
c3ac07319f08790a8f6fe3b904f3adc93c2c94fd
|
[
"MIT-0"
] | null | null | null |
code/code.py
|
CedarGroveStudios/Scale
|
c3ac07319f08790a8f6fe3b904f3adc93c2c94fd
|
[
"MIT-0"
] | null | null | null |
import scale_code
#import touch_calibrator_built_in
#import touch_calibrator_stmpe610
# uncomment the following import line to run the load cell calibration method
# (this may eventually become part of a setup process)
# import cedargrove_scale.load_cell_calibrator
| 33.375
| 77
| 0.846442
| 39
| 267
| 5.564103
| 0.717949
| 0.101382
| 0.193548
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012821
| 0.123596
| 267
| 7
| 78
| 38.142857
| 0.91453
| 0.891386
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f491f9027834eabab5d6bf192b8494e4f954df98
| 114
|
py
|
Python
|
modules/rcir.py
|
anirudhRowjee/atlas
|
6443ad100434f02dbeaf969ff99363dd8fdc32bb
|
[
"MIT"
] | 7
|
2020-12-13T03:27:42.000Z
|
2021-03-08T19:01:18.000Z
|
modules/rcir.py
|
anirudhRowjee/atlas
|
6443ad100434f02dbeaf969ff99363dd8fdc32bb
|
[
"MIT"
] | 4
|
2020-12-12T18:07:07.000Z
|
2020-12-16T07:58:09.000Z
|
modules/rcir.py
|
anirudhRowjee/atlas
|
6443ad100434f02dbeaf969ff99363dd8fdc32bb
|
[
"MIT"
] | null | null | null |
"""
RCIR Module
Consits of representations for Candidate, Voter and Election
"""
print("This is the RCIR module")
| 19
| 60
| 0.754386
| 16
| 114
| 5.375
| 0.875
| 0.232558
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149123
| 114
| 5
| 61
| 22.8
| 0.886598
| 0.631579
| 0
| 0
| 0
| 0
| 0.676471
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
f496db8ad20dbd2111185141ca5ead8df38f7fcb
| 231
|
py
|
Python
|
vel/api/metrics/__init__.py
|
tigerwlin/vel
|
00e4fbb7b612e888e2cbb5d8455146664638cd0b
|
[
"MIT"
] | 273
|
2018-09-01T08:54:34.000Z
|
2022-02-02T13:22:51.000Z
|
vel/api/metrics/__init__.py
|
tigerwlin/vel
|
00e4fbb7b612e888e2cbb5d8455146664638cd0b
|
[
"MIT"
] | 47
|
2018-08-17T11:27:08.000Z
|
2022-03-11T23:26:55.000Z
|
vel/api/metrics/__init__.py
|
tigerwlin/vel
|
00e4fbb7b612e888e2cbb5d8455146664638cd0b
|
[
"MIT"
] | 37
|
2018-10-11T22:56:57.000Z
|
2020-10-06T19:53:05.000Z
|
from .base_metric import BaseMetric
from .averaging_metric import AveragingMetric, AveragingNamedMetric, AveragingSupervisedMetric
from .value_metric import ValueMetric
from .summing_metric import SummingMetric, SummingNamedMetric
| 46.2
| 94
| 0.887446
| 23
| 231
| 8.73913
| 0.608696
| 0.238806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.082251
| 231
| 4
| 95
| 57.75
| 0.948113
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f49e9347f9db44522466e735ba4977b7098db3dd
| 24,214
|
py
|
Python
|
sdk/python/pulumi_google_native/jobs/v4/company.py
|
AaronFriel/pulumi-google-native
|
75d1cda425e33d4610348972cd70bddf35f1770d
|
[
"Apache-2.0"
] | 44
|
2021-04-18T23:00:48.000Z
|
2022-02-14T17:43:15.000Z
|
sdk/python/pulumi_google_native/jobs/v4/company.py
|
AaronFriel/pulumi-google-native
|
75d1cda425e33d4610348972cd70bddf35f1770d
|
[
"Apache-2.0"
] | 354
|
2021-04-16T16:48:39.000Z
|
2022-03-31T17:16:39.000Z
|
sdk/python/pulumi_google_native/jobs/v4/company.py
|
AaronFriel/pulumi-google-native
|
75d1cda425e33d4610348972cd70bddf35f1770d
|
[
"Apache-2.0"
] | 8
|
2021-04-24T17:46:51.000Z
|
2022-01-05T10:40:21.000Z
|
# coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
from ._enums import *
__all__ = ['CompanyArgs', 'Company']
@pulumi.input_type
class CompanyArgs:
def __init__(__self__, *,
display_name: pulumi.Input[str],
external_id: pulumi.Input[str],
tenant_id: pulumi.Input[str],
career_site_uri: Optional[pulumi.Input[str]] = None,
eeo_text: Optional[pulumi.Input[str]] = None,
headquarters_address: Optional[pulumi.Input[str]] = None,
hiring_agency: Optional[pulumi.Input[bool]] = None,
image_uri: Optional[pulumi.Input[str]] = None,
keyword_searchable_job_custom_attributes: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
size: Optional[pulumi.Input['CompanySize']] = None,
website_uri: Optional[pulumi.Input[str]] = None):
"""
The set of arguments for constructing a Company resource.
:param pulumi.Input[str] display_name: The display name of the company, for example, "Google LLC".
:param pulumi.Input[str] external_id: Client side company identifier, used to uniquely identify the company. The maximum number of allowed characters is 255.
:param pulumi.Input[str] career_site_uri: The URI to employer's career site or careers page on the employer's web site, for example, "https://careers.google.com".
:param pulumi.Input[str] eeo_text: Equal Employment Opportunity legal disclaimer text to be associated with all jobs, and typically to be displayed in all roles. The maximum number of allowed characters is 500.
:param pulumi.Input[str] headquarters_address: The street address of the company's main headquarters, which may be different from the job location. The service attempts to geolocate the provided address, and populates a more specific location wherever possible in DerivedInfo.headquarters_location.
:param pulumi.Input[bool] hiring_agency: Set to true if it is the hiring agency that post jobs for other employers. Defaults to false if not provided.
:param pulumi.Input[str] image_uri: A URI that hosts the employer's company logo.
:param pulumi.Input[Sequence[pulumi.Input[str]]] keyword_searchable_job_custom_attributes: A list of keys of filterable Job.custom_attributes, whose corresponding `string_values` are used in keyword searches. Jobs with `string_values` under these specified field keys are returned if any of the values match the search keyword. Custom field values with parenthesis, brackets and special symbols are not searchable as-is, and those keyword queries must be surrounded by quotes.
:param pulumi.Input[str] name: Required during company update. The resource name for a company. This is generated by the service when a company is created. The format is "projects/{project_id}/tenants/{tenant_id}/companies/{company_id}", for example, "projects/foo/tenants/bar/companies/baz".
:param pulumi.Input['CompanySize'] size: The employer's company size.
:param pulumi.Input[str] website_uri: The URI representing the company's primary web site or home page, for example, "https://www.google.com". The maximum number of allowed characters is 255.
"""
pulumi.set(__self__, "display_name", display_name)
pulumi.set(__self__, "external_id", external_id)
pulumi.set(__self__, "tenant_id", tenant_id)
if career_site_uri is not None:
pulumi.set(__self__, "career_site_uri", career_site_uri)
if eeo_text is not None:
pulumi.set(__self__, "eeo_text", eeo_text)
if headquarters_address is not None:
pulumi.set(__self__, "headquarters_address", headquarters_address)
if hiring_agency is not None:
pulumi.set(__self__, "hiring_agency", hiring_agency)
if image_uri is not None:
pulumi.set(__self__, "image_uri", image_uri)
if keyword_searchable_job_custom_attributes is not None:
pulumi.set(__self__, "keyword_searchable_job_custom_attributes", keyword_searchable_job_custom_attributes)
if name is not None:
pulumi.set(__self__, "name", name)
if project is not None:
pulumi.set(__self__, "project", project)
if size is not None:
pulumi.set(__self__, "size", size)
if website_uri is not None:
pulumi.set(__self__, "website_uri", website_uri)
@property
@pulumi.getter(name="displayName")
def display_name(self) -> pulumi.Input[str]:
"""
The display name of the company, for example, "Google LLC".
"""
return pulumi.get(self, "display_name")
@display_name.setter
def display_name(self, value: pulumi.Input[str]):
pulumi.set(self, "display_name", value)
@property
@pulumi.getter(name="externalId")
def external_id(self) -> pulumi.Input[str]:
"""
Client side company identifier, used to uniquely identify the company. The maximum number of allowed characters is 255.
"""
return pulumi.get(self, "external_id")
@external_id.setter
def external_id(self, value: pulumi.Input[str]):
pulumi.set(self, "external_id", value)
@property
@pulumi.getter(name="tenantId")
def tenant_id(self) -> pulumi.Input[str]:
return pulumi.get(self, "tenant_id")
@tenant_id.setter
def tenant_id(self, value: pulumi.Input[str]):
pulumi.set(self, "tenant_id", value)
@property
@pulumi.getter(name="careerSiteUri")
def career_site_uri(self) -> Optional[pulumi.Input[str]]:
"""
The URI to employer's career site or careers page on the employer's web site, for example, "https://careers.google.com".
"""
return pulumi.get(self, "career_site_uri")
@career_site_uri.setter
def career_site_uri(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "career_site_uri", value)
@property
@pulumi.getter(name="eeoText")
def eeo_text(self) -> Optional[pulumi.Input[str]]:
"""
Equal Employment Opportunity legal disclaimer text to be associated with all jobs, and typically to be displayed in all roles. The maximum number of allowed characters is 500.
"""
return pulumi.get(self, "eeo_text")
@eeo_text.setter
def eeo_text(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "eeo_text", value)
@property
@pulumi.getter(name="headquartersAddress")
def headquarters_address(self) -> Optional[pulumi.Input[str]]:
"""
The street address of the company's main headquarters, which may be different from the job location. The service attempts to geolocate the provided address, and populates a more specific location wherever possible in DerivedInfo.headquarters_location.
"""
return pulumi.get(self, "headquarters_address")
@headquarters_address.setter
def headquarters_address(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "headquarters_address", value)
@property
@pulumi.getter(name="hiringAgency")
def hiring_agency(self) -> Optional[pulumi.Input[bool]]:
"""
Set to true if it is the hiring agency that post jobs for other employers. Defaults to false if not provided.
"""
return pulumi.get(self, "hiring_agency")
@hiring_agency.setter
def hiring_agency(self, value: Optional[pulumi.Input[bool]]):
pulumi.set(self, "hiring_agency", value)
@property
@pulumi.getter(name="imageUri")
def image_uri(self) -> Optional[pulumi.Input[str]]:
"""
A URI that hosts the employer's company logo.
"""
return pulumi.get(self, "image_uri")
@image_uri.setter
def image_uri(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "image_uri", value)
@property
@pulumi.getter(name="keywordSearchableJobCustomAttributes")
def keyword_searchable_job_custom_attributes(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]:
"""
A list of keys of filterable Job.custom_attributes, whose corresponding `string_values` are used in keyword searches. Jobs with `string_values` under these specified field keys are returned if any of the values match the search keyword. Custom field values with parenthesis, brackets and special symbols are not searchable as-is, and those keyword queries must be surrounded by quotes.
"""
return pulumi.get(self, "keyword_searchable_job_custom_attributes")
@keyword_searchable_job_custom_attributes.setter
def keyword_searchable_job_custom_attributes(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]):
pulumi.set(self, "keyword_searchable_job_custom_attributes", value)
@property
@pulumi.getter
def name(self) -> Optional[pulumi.Input[str]]:
"""
Required during company update. The resource name for a company. This is generated by the service when a company is created. The format is "projects/{project_id}/tenants/{tenant_id}/companies/{company_id}", for example, "projects/foo/tenants/bar/companies/baz".
"""
return pulumi.get(self, "name")
@name.setter
def name(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "name", value)
@property
@pulumi.getter
def project(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "project")
@project.setter
def project(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "project", value)
@property
@pulumi.getter
def size(self) -> Optional[pulumi.Input['CompanySize']]:
"""
The employer's company size.
"""
return pulumi.get(self, "size")
@size.setter
def size(self, value: Optional[pulumi.Input['CompanySize']]):
pulumi.set(self, "size", value)
@property
@pulumi.getter(name="websiteUri")
def website_uri(self) -> Optional[pulumi.Input[str]]:
"""
The URI representing the company's primary web site or home page, for example, "https://www.google.com". The maximum number of allowed characters is 255.
"""
return pulumi.get(self, "website_uri")
@website_uri.setter
def website_uri(self, value: Optional[pulumi.Input[str]]):
pulumi.set(self, "website_uri", value)
class Company(pulumi.CustomResource):
@overload
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
career_site_uri: Optional[pulumi.Input[str]] = None,
display_name: Optional[pulumi.Input[str]] = None,
eeo_text: Optional[pulumi.Input[str]] = None,
external_id: Optional[pulumi.Input[str]] = None,
headquarters_address: Optional[pulumi.Input[str]] = None,
hiring_agency: Optional[pulumi.Input[bool]] = None,
image_uri: Optional[pulumi.Input[str]] = None,
keyword_searchable_job_custom_attributes: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
size: Optional[pulumi.Input['CompanySize']] = None,
tenant_id: Optional[pulumi.Input[str]] = None,
website_uri: Optional[pulumi.Input[str]] = None,
__props__=None):
"""
Creates a new company entity.
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] career_site_uri: The URI to employer's career site or careers page on the employer's web site, for example, "https://careers.google.com".
:param pulumi.Input[str] display_name: The display name of the company, for example, "Google LLC".
:param pulumi.Input[str] eeo_text: Equal Employment Opportunity legal disclaimer text to be associated with all jobs, and typically to be displayed in all roles. The maximum number of allowed characters is 500.
:param pulumi.Input[str] external_id: Client side company identifier, used to uniquely identify the company. The maximum number of allowed characters is 255.
:param pulumi.Input[str] headquarters_address: The street address of the company's main headquarters, which may be different from the job location. The service attempts to geolocate the provided address, and populates a more specific location wherever possible in DerivedInfo.headquarters_location.
:param pulumi.Input[bool] hiring_agency: Set to true if it is the hiring agency that post jobs for other employers. Defaults to false if not provided.
:param pulumi.Input[str] image_uri: A URI that hosts the employer's company logo.
:param pulumi.Input[Sequence[pulumi.Input[str]]] keyword_searchable_job_custom_attributes: A list of keys of filterable Job.custom_attributes, whose corresponding `string_values` are used in keyword searches. Jobs with `string_values` under these specified field keys are returned if any of the values match the search keyword. Custom field values with parenthesis, brackets and special symbols are not searchable as-is, and those keyword queries must be surrounded by quotes.
:param pulumi.Input[str] name: Required during company update. The resource name for a company. This is generated by the service when a company is created. The format is "projects/{project_id}/tenants/{tenant_id}/companies/{company_id}", for example, "projects/foo/tenants/bar/companies/baz".
:param pulumi.Input['CompanySize'] size: The employer's company size.
:param pulumi.Input[str] website_uri: The URI representing the company's primary web site or home page, for example, "https://www.google.com". The maximum number of allowed characters is 255.
"""
...
@overload
def __init__(__self__,
resource_name: str,
args: CompanyArgs,
opts: Optional[pulumi.ResourceOptions] = None):
"""
Creates a new company entity.
:param str resource_name: The name of the resource.
:param CompanyArgs args: The arguments to use to populate this resource's properties.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
...
def __init__(__self__, resource_name: str, *args, **kwargs):
resource_args, opts = _utilities.get_resource_args_opts(CompanyArgs, pulumi.ResourceOptions, *args, **kwargs)
if resource_args is not None:
__self__._internal_init(resource_name, opts, **resource_args.__dict__)
else:
__self__._internal_init(resource_name, *args, **kwargs)
def _internal_init(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
career_site_uri: Optional[pulumi.Input[str]] = None,
display_name: Optional[pulumi.Input[str]] = None,
eeo_text: Optional[pulumi.Input[str]] = None,
external_id: Optional[pulumi.Input[str]] = None,
headquarters_address: Optional[pulumi.Input[str]] = None,
hiring_agency: Optional[pulumi.Input[bool]] = None,
image_uri: Optional[pulumi.Input[str]] = None,
keyword_searchable_job_custom_attributes: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None,
name: Optional[pulumi.Input[str]] = None,
project: Optional[pulumi.Input[str]] = None,
size: Optional[pulumi.Input['CompanySize']] = None,
tenant_id: Optional[pulumi.Input[str]] = None,
website_uri: Optional[pulumi.Input[str]] = None,
__props__=None):
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = CompanyArgs.__new__(CompanyArgs)
__props__.__dict__["career_site_uri"] = career_site_uri
if display_name is None and not opts.urn:
raise TypeError("Missing required property 'display_name'")
__props__.__dict__["display_name"] = display_name
__props__.__dict__["eeo_text"] = eeo_text
if external_id is None and not opts.urn:
raise TypeError("Missing required property 'external_id'")
__props__.__dict__["external_id"] = external_id
__props__.__dict__["headquarters_address"] = headquarters_address
__props__.__dict__["hiring_agency"] = hiring_agency
__props__.__dict__["image_uri"] = image_uri
__props__.__dict__["keyword_searchable_job_custom_attributes"] = keyword_searchable_job_custom_attributes
__props__.__dict__["name"] = name
__props__.__dict__["project"] = project
__props__.__dict__["size"] = size
if tenant_id is None and not opts.urn:
raise TypeError("Missing required property 'tenant_id'")
__props__.__dict__["tenant_id"] = tenant_id
__props__.__dict__["website_uri"] = website_uri
__props__.__dict__["derived_info"] = None
__props__.__dict__["suspended"] = None
super(Company, __self__).__init__(
'google-native:jobs/v4:Company',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None) -> 'Company':
"""
Get an existing Company resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = CompanyArgs.__new__(CompanyArgs)
__props__.__dict__["career_site_uri"] = None
__props__.__dict__["derived_info"] = None
__props__.__dict__["display_name"] = None
__props__.__dict__["eeo_text"] = None
__props__.__dict__["external_id"] = None
__props__.__dict__["headquarters_address"] = None
__props__.__dict__["hiring_agency"] = None
__props__.__dict__["image_uri"] = None
__props__.__dict__["keyword_searchable_job_custom_attributes"] = None
__props__.__dict__["name"] = None
__props__.__dict__["size"] = None
__props__.__dict__["suspended"] = None
__props__.__dict__["website_uri"] = None
return Company(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter(name="careerSiteUri")
def career_site_uri(self) -> pulumi.Output[str]:
"""
The URI to employer's career site or careers page on the employer's web site, for example, "https://careers.google.com".
"""
return pulumi.get(self, "career_site_uri")
@property
@pulumi.getter(name="derivedInfo")
def derived_info(self) -> pulumi.Output['outputs.CompanyDerivedInfoResponse']:
"""
Derived details about the company.
"""
return pulumi.get(self, "derived_info")
@property
@pulumi.getter(name="displayName")
def display_name(self) -> pulumi.Output[str]:
"""
The display name of the company, for example, "Google LLC".
"""
return pulumi.get(self, "display_name")
@property
@pulumi.getter(name="eeoText")
def eeo_text(self) -> pulumi.Output[str]:
"""
Equal Employment Opportunity legal disclaimer text to be associated with all jobs, and typically to be displayed in all roles. The maximum number of allowed characters is 500.
"""
return pulumi.get(self, "eeo_text")
@property
@pulumi.getter(name="externalId")
def external_id(self) -> pulumi.Output[str]:
"""
Client side company identifier, used to uniquely identify the company. The maximum number of allowed characters is 255.
"""
return pulumi.get(self, "external_id")
@property
@pulumi.getter(name="headquartersAddress")
def headquarters_address(self) -> pulumi.Output[str]:
"""
The street address of the company's main headquarters, which may be different from the job location. The service attempts to geolocate the provided address, and populates a more specific location wherever possible in DerivedInfo.headquarters_location.
"""
return pulumi.get(self, "headquarters_address")
@property
@pulumi.getter(name="hiringAgency")
def hiring_agency(self) -> pulumi.Output[bool]:
"""
Set to true if it is the hiring agency that post jobs for other employers. Defaults to false if not provided.
"""
return pulumi.get(self, "hiring_agency")
@property
@pulumi.getter(name="imageUri")
def image_uri(self) -> pulumi.Output[str]:
"""
A URI that hosts the employer's company logo.
"""
return pulumi.get(self, "image_uri")
@property
@pulumi.getter(name="keywordSearchableJobCustomAttributes")
def keyword_searchable_job_custom_attributes(self) -> pulumi.Output[Sequence[str]]:
"""
A list of keys of filterable Job.custom_attributes, whose corresponding `string_values` are used in keyword searches. Jobs with `string_values` under these specified field keys are returned if any of the values match the search keyword. Custom field values with parenthesis, brackets and special symbols are not searchable as-is, and those keyword queries must be surrounded by quotes.
"""
return pulumi.get(self, "keyword_searchable_job_custom_attributes")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
Required during company update. The resource name for a company. This is generated by the service when a company is created. The format is "projects/{project_id}/tenants/{tenant_id}/companies/{company_id}", for example, "projects/foo/tenants/bar/companies/baz".
"""
return pulumi.get(self, "name")
@property
@pulumi.getter
def size(self) -> pulumi.Output[str]:
"""
The employer's company size.
"""
return pulumi.get(self, "size")
@property
@pulumi.getter
def suspended(self) -> pulumi.Output[bool]:
"""
Indicates whether a company is flagged to be suspended from public availability by the service when job content appears suspicious, abusive, or spammy.
"""
return pulumi.get(self, "suspended")
@property
@pulumi.getter(name="websiteUri")
def website_uri(self) -> pulumi.Output[str]:
"""
The URI representing the company's primary web site or home page, for example, "https://www.google.com". The maximum number of allowed characters is 255.
"""
return pulumi.get(self, "website_uri")
| 51.850107
| 484
| 0.67304
| 3,021
| 24,214
| 5.165508
| 0.088381
| 0.068376
| 0.067286
| 0.057802
| 0.822941
| 0.762704
| 0.735726
| 0.700993
| 0.67991
| 0.622877
| 0
| 0.002039
| 0.23028
| 24,214
| 466
| 485
| 51.961373
| 0.835229
| 0.369208
| 0
| 0.427119
| 1
| 0
| 0.117958
| 0.026082
| 0
| 0
| 0
| 0
| 0
| 1
| 0.152542
| false
| 0.00339
| 0.023729
| 0.00678
| 0.274576
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
f4e18dd00673a99aff7c154f6933bd71c10b9c0b
| 78
|
py
|
Python
|
libs/uix/baseclasses/settings_.py
|
mkbeh/CRyptoLab
|
424c938c16c9264e99eff71e4c1a27ca65314d42
|
[
"MIT"
] | null | null | null |
libs/uix/baseclasses/settings_.py
|
mkbeh/CRyptoLab
|
424c938c16c9264e99eff71e4c1a27ca65314d42
|
[
"MIT"
] | 1
|
2021-06-01T22:30:24.000Z
|
2021-06-01T22:30:24.000Z
|
libs/uix/baseclasses/settings_.py
|
mkbeh/CRyptoLab
|
424c938c16c9264e99eff71e4c1a27ca65314d42
|
[
"MIT"
] | 1
|
2021-05-11T23:06:20.000Z
|
2021-05-11T23:06:20.000Z
|
from kivy.uix.screenmanager import Screen
class Settings_(Screen):
pass
| 13
| 41
| 0.769231
| 10
| 78
| 5.9
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 78
| 5
| 42
| 15.6
| 0.907692
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
f4e75a9e1bb09fd6f08e60d92fcc963f3742ba92
| 29
|
py
|
Python
|
src/platform/fileUseCases/core/FileUseCaseProvider.py
|
behrad-kzm/LocationBrain
|
44ef5e03cc9b240bfabad5c3c14635ef812a39ae
|
[
"MIT"
] | null | null | null |
src/platform/fileUseCases/core/FileUseCaseProvider.py
|
behrad-kzm/LocationBrain
|
44ef5e03cc9b240bfabad5c3c14635ef812a39ae
|
[
"MIT"
] | null | null | null |
src/platform/fileUseCases/core/FileUseCaseProvider.py
|
behrad-kzm/LocationBrain
|
44ef5e03cc9b240bfabad5c3c14635ef812a39ae
|
[
"MIT"
] | null | null | null |
# class FileUseCaseProvider:
| 14.5
| 28
| 0.827586
| 2
| 29
| 12
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.103448
| 29
| 1
| 29
| 29
| 0.923077
| 0.896552
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
7606f612f1c4f2110a3944dfddea8e6f02f122b3
| 149
|
py
|
Python
|
antenna_diversity/__init__.py
|
jbjjbjjbj/eittek651
|
3f735eb1836fc6e144b885654f71d3fe2b4e2c03
|
[
"MIT"
] | null | null | null |
antenna_diversity/__init__.py
|
jbjjbjjbj/eittek651
|
3f735eb1836fc6e144b885654f71d3fe2b4e2c03
|
[
"MIT"
] | 1
|
2021-05-27T17:24:01.000Z
|
2021-05-27T17:24:01.000Z
|
antenna_diversity/__init__.py
|
jbjjbjjbj/eittek651
|
3f735eb1836fc6e144b885654f71d3fe2b4e2c03
|
[
"MIT"
] | null | null | null |
from . import channel
from . import diversity_technique
from . import encoding
from . import modulation
from . import protocols
from . import common
| 21.285714
| 33
| 0.798658
| 19
| 149
| 6.210526
| 0.473684
| 0.508475
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.161074
| 149
| 6
| 34
| 24.833333
| 0.944
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
760dff32289498063ba82261d94be50502224b78
| 125
|
py
|
Python
|
app/roles/__init__.py
|
DzhonPetrus/Treatment-Management
|
6b08c59d2d4e79181bbae4e951b7a5fd2e3162f1
|
[
"MIT"
] | null | null | null |
app/roles/__init__.py
|
DzhonPetrus/Treatment-Management
|
6b08c59d2d4e79181bbae4e951b7a5fd2e3162f1
|
[
"MIT"
] | null | null | null |
app/roles/__init__.py
|
DzhonPetrus/Treatment-Management
|
6b08c59d2d4e79181bbae4e951b7a5fd2e3162f1
|
[
"MIT"
] | null | null | null |
from . import admin, lab_receptionist, lab_technician, medical_specialist, surgeon, surgery_scheduler, surgical_nurse, public
| 125
| 125
| 0.856
| 15
| 125
| 6.8
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 125
| 1
| 125
| 125
| 0.886957
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
5230c2f64b34857c8ccd24d781afaaeb63bb9bc2
| 41
|
py
|
Python
|
submissions/code-festival-2016-quala/a.py
|
m-star18/atcoder
|
08e475810516602fa088f87daf1eba590b4e07cc
|
[
"Unlicense"
] | 1
|
2021-05-10T01:16:28.000Z
|
2021-05-10T01:16:28.000Z
|
submissions/code-festival-2016-quala/a.py
|
m-star18/atcoder
|
08e475810516602fa088f87daf1eba590b4e07cc
|
[
"Unlicense"
] | 3
|
2021-05-11T06:14:15.000Z
|
2021-06-19T08:18:36.000Z
|
submissions/code-festival-2016-quala/a.py
|
m-star18/atcoder
|
08e475810516602fa088f87daf1eba590b4e07cc
|
[
"Unlicense"
] | null | null | null |
s = input()
s = s[:4]+' '+s[4:]
print(s)
| 10.25
| 19
| 0.414634
| 9
| 41
| 1.888889
| 0.444444
| 0.235294
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.060606
| 0.195122
| 41
| 3
| 20
| 13.666667
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0.02439
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
525a6e3fdba485eec850aaf20537a871fa4320ef
| 34
|
py
|
Python
|
cride/users/views/__init__.py
|
devmiguelangel/cride
|
8593eb76291ff8af46a93b5625304766f95b2347
|
[
"MIT"
] | null | null | null |
cride/users/views/__init__.py
|
devmiguelangel/cride
|
8593eb76291ff8af46a93b5625304766f95b2347
|
[
"MIT"
] | null | null | null |
cride/users/views/__init__.py
|
devmiguelangel/cride
|
8593eb76291ff8af46a93b5625304766f95b2347
|
[
"MIT"
] | null | null | null |
# User views
from .users import *
| 11.333333
| 20
| 0.705882
| 5
| 34
| 4.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205882
| 34
| 2
| 21
| 17
| 0.888889
| 0.294118
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
5262a47c5edd98e0c2811ba7876360c0f3f2aa6a
| 28
|
py
|
Python
|
__init__.py
|
Sequelcommerce/BoxPackingAPI
|
48cfbd9c7b82c6f7640386523627d7911ff9089b
|
[
"MIT"
] | 23
|
2019-11-08T15:29:29.000Z
|
2022-01-11T20:27:04.000Z
|
__init__.py
|
Sequelcommerce/BoxPackingAPI
|
48cfbd9c7b82c6f7640386523627d7911ff9089b
|
[
"MIT"
] | 3
|
2020-10-05T10:09:23.000Z
|
2021-08-12T15:38:45.000Z
|
__init__.py
|
Sequelcommerce/BoxPackingAPI
|
48cfbd9c7b82c6f7640386523627d7911ff9089b
|
[
"MIT"
] | 17
|
2019-09-10T20:03:56.000Z
|
2021-08-17T06:55:09.000Z
|
from . import usps_shipping
| 14
| 27
| 0.821429
| 4
| 28
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 28
| 1
| 28
| 28
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
528b2810d0f113a9fcb1a80fc7f2eb234dec9b28
| 231
|
py
|
Python
|
bvc/admin/__init__.py
|
Vayel/GUCEM-BVC
|
e5645dec332756d3c9db083abf2c8f3625a10d4d
|
[
"WTFPL"
] | 2
|
2016-09-23T18:02:40.000Z
|
2017-04-28T18:35:59.000Z
|
bvc/admin/__init__.py
|
Vayel/GUCEM-BVC
|
e5645dec332756d3c9db083abf2c8f3625a10d4d
|
[
"WTFPL"
] | 82
|
2016-09-26T14:38:31.000Z
|
2018-02-12T18:47:12.000Z
|
bvc/admin/__init__.py
|
Vayel/GUCEM-BVC
|
e5645dec332756d3c9db083abf2c8f3625a10d4d
|
[
"WTFPL"
] | null | null | null |
from . import bank_deposit
from . import commission_command
from . import configuration
from . import email
from . import grouped_command
from . import member_command
from . import treasury
from . import user
from . import voucher
| 23.1
| 32
| 0.805195
| 31
| 231
| 5.870968
| 0.419355
| 0.494505
| 0.28022
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155844
| 231
| 9
| 33
| 25.666667
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
873aed8dd179516e68e0ef672c209fd1d00d0898
| 303
|
py
|
Python
|
referenceqvm/tests/conftest.py
|
markf94/reference-qvm
|
e4ca313928f72b3d2348a3f9abfec6607944c59e
|
[
"Apache-2.0"
] | 28
|
2017-09-30T22:04:51.000Z
|
2018-11-07T11:23:17.000Z
|
referenceqvm/tests/conftest.py
|
markf94/reference-qvm
|
e4ca313928f72b3d2348a3f9abfec6607944c59e
|
[
"Apache-2.0"
] | 8
|
2017-09-30T21:32:33.000Z
|
2018-10-15T16:36:57.000Z
|
referenceqvm/tests/conftest.py
|
markf94/reference-qvm
|
e4ca313928f72b3d2348a3f9abfec6607944c59e
|
[
"Apache-2.0"
] | 12
|
2017-10-05T16:55:55.000Z
|
2018-11-06T17:42:47.000Z
|
import pytest
@pytest.fixture(scope="module")
def qvm():
from referenceqvm.api import QVMConnection
return QVMConnection(type_trans='wavefunction')
@pytest.fixture(scope="module")
def qvm_unitary():
from referenceqvm.api import QVMConnection
return QVMConnection(type_trans='unitary')
| 25.25
| 51
| 0.768977
| 35
| 303
| 6.571429
| 0.457143
| 0.113043
| 0.156522
| 0.208696
| 0.834783
| 0.834783
| 0.573913
| 0.573913
| 0.573913
| 0
| 0
| 0
| 0.125413
| 303
| 11
| 52
| 27.545455
| 0.867925
| 0
| 0
| 0.444444
| 0
| 0
| 0.10231
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| true
| 0
| 0.333333
| 0
| 0.777778
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
5e54d5f6cd704a67211166bb7e951b93e3847c67
| 106
|
py
|
Python
|
django_blog_api/views.py
|
itsSayantan/django-blog-api
|
6956125c8f21baeaabc82260c0c75d8f4ee7270b
|
[
"MIT"
] | null | null | null |
django_blog_api/views.py
|
itsSayantan/django-blog-api
|
6956125c8f21baeaabc82260c0c75d8f4ee7270b
|
[
"MIT"
] | null | null | null |
django_blog_api/views.py
|
itsSayantan/django-blog-api
|
6956125c8f21baeaabc82260c0c75d8f4ee7270b
|
[
"MIT"
] | null | null | null |
from django.http import HttpResponse
def homepage(request):
return HttpResponse('Home page received')
| 26.5
| 45
| 0.792453
| 13
| 106
| 6.461538
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132075
| 106
| 4
| 45
| 26.5
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0.168224
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
5e9223bc360182e13d94f0cd113a8da30ada1576
| 36
|
py
|
Python
|
v1/index.py
|
tommeagher/alva
|
e256b23c37c38d8bd193ba8ce1ef3ef10a66a9ef
|
[
"MIT"
] | null | null | null |
v1/index.py
|
tommeagher/alva
|
e256b23c37c38d8bd193ba8ce1ef3ef10a66a9ef
|
[
"MIT"
] | 6
|
2015-04-21T01:54:02.000Z
|
2015-04-21T01:54:03.000Z
|
v1/index.py
|
tommeagher/alva
|
e256b23c37c38d8bd193ba8ce1ef3ef10a66a9ef
|
[
"MIT"
] | null | null | null |
from alva import app as application
| 18
| 35
| 0.833333
| 6
| 36
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 36
| 1
| 36
| 36
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
5e94ec259103a490ddd2bc6d714950d7438d0c02
| 87
|
py
|
Python
|
app/chat/__init__.py
|
YoungYJMaze/TongQu
|
00951b85aab549230a6f4089a838ec362a6c5126
|
[
"MIT"
] | 2
|
2020-03-29T08:20:17.000Z
|
2020-03-29T08:20:19.000Z
|
app/chat/__init__.py
|
YoungYJMaze/TongQu
|
00951b85aab549230a6f4089a838ec362a6c5126
|
[
"MIT"
] | 3
|
2020-03-24T16:39:46.000Z
|
2021-02-02T21:53:35.000Z
|
app/chat/__init__.py
|
YoungYJMaze/TongQu
|
00951b85aab549230a6f4089a838ec362a6c5126
|
[
"MIT"
] | null | null | null |
from flask import Blueprint
chat = Blueprint('chat', __name__)
from . import views
| 10.875
| 34
| 0.735632
| 11
| 87
| 5.454545
| 0.636364
| 0.433333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.183908
| 87
| 7
| 35
| 12.428571
| 0.84507
| 0
| 0
| 0
| 0
| 0
| 0.047059
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0.666667
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
|
0
| 6
|
5ed09d30ff2f8af2bdc2b2e64c95a5e0ede360db
| 34
|
py
|
Python
|
HelloWorld/__init__.py
|
EliasEriksson/HelloWorld
|
8fd9e33126eca8bb8d492df525c7ba7ba698c8b8
|
[
"MIT"
] | null | null | null |
HelloWorld/__init__.py
|
EliasEriksson/HelloWorld
|
8fd9e33126eca8bb8d492df525c7ba7ba698c8b8
|
[
"MIT"
] | null | null | null |
HelloWorld/__init__.py
|
EliasEriksson/HelloWorld
|
8fd9e33126eca8bb8d492df525c7ba7ba698c8b8
|
[
"MIT"
] | null | null | null |
print("hello world! in package.")
| 17
| 33
| 0.705882
| 5
| 34
| 4.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 34
| 1
| 34
| 34
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0.705882
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
0da3f7b602fa950508351be90e951ef3146397fe
| 8,810
|
py
|
Python
|
pyqir-tests/tests/test_if.py
|
nilslice/pyqir
|
9ae0395e5a0fe52221be16322256629e891d63c6
|
[
"MIT"
] | 22
|
2021-11-30T21:52:30.000Z
|
2022-03-17T02:05:17.000Z
|
pyqir-tests/tests/test_if.py
|
nilslice/pyqir
|
9ae0395e5a0fe52221be16322256629e891d63c6
|
[
"MIT"
] | 51
|
2021-11-24T03:42:49.000Z
|
2022-03-25T20:51:24.000Z
|
pyqir-tests/tests/test_if.py
|
nilslice/pyqir
|
9ae0395e5a0fe52221be16322256629e891d63c6
|
[
"MIT"
] | 6
|
2021-11-30T22:36:49.000Z
|
2022-03-17T17:21:16.000Z
|
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from pyqir.generator import BasicQisBuilder, SimpleModule
from pyqir.evaluator import GateLogger, GateSet, NonadaptiveEvaluator
import tempfile
from typing import List, Optional
import unittest
import pytest
# Combinations of static qubit and result code generation
# first element => use_static_qubit_alloc
# second element => use_static_result_alloc
static_generator_variations = [
[False, False],
[False, True],
[True, False],
[True, True]
]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_one_block_executes_on_one(matrix) -> None:
module = SimpleModule("test_if", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0], lambda: qis.x(module.qubits[0]))
print(module.ir())
logger = GateLogger()
_eval(module, logger, [True])
assert logger.instructions == ["m qubit[0] => out[0]", "x qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_zero_block_executes_on_zero(matrix) -> None:
module = SimpleModule("test_if_not", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0], zero=lambda: qis.x(module.qubits[0]))
logger = GateLogger()
_eval(module, logger)
assert logger.instructions == ["m qubit[0] => out[0]", "x qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_execution_continues_after_hit_conditional_one(matrix) -> None:
module = SimpleModule("test_if", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0], lambda: qis.x(module.qubits[0]))
qis.h(module.qubits[0])
logger = GateLogger()
_eval(module, logger, [True])
assert logger.instructions == ["m qubit[0] => out[0]", "x qubit[0]", "h qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_execution_continues_after_missed_conditional_one(matrix) -> None:
module = SimpleModule("test_if", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0], lambda: qis.x(module.qubits[0]))
qis.h(module.qubits[0])
logger = GateLogger()
_eval(module, logger, [False])
assert logger.instructions == ["m qubit[0] => out[0]", "h qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_execution_continues_after_hit_conditional_zero(matrix) -> None:
module = SimpleModule("test_if_not", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0], zero=lambda: qis.x(module.qubits[0]))
qis.h(module.qubits[0])
logger = GateLogger()
_eval(module, logger, [False])
assert logger.instructions == ["m qubit[0] => out[0]", "x qubit[0]", "h qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_execution_continues_after_missed_conditional_zero(matrix) -> None:
module = SimpleModule("test_if_not", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0], zero=lambda: qis.x(module.qubits[0]))
qis.h(module.qubits[0])
logger = GateLogger()
_eval(module, logger, [True])
assert logger.instructions == ["m qubit[0] => out[0]", "h qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_execution_continues_after_conditional_if_else(matrix) -> None:
module = SimpleModule("test_if_not", num_qubits=1, num_results=1)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.if_result(module.results[0],
lambda: qis.x(module.qubits[0]),
lambda: qis.y(module.qubits[0]))
qis.h(module.qubits[0])
logger = GateLogger()
_eval(module, logger)
assert logger.instructions == ["m qubit[0] => out[0]", "y qubit[0]", "h qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_nested_if(matrix) -> None:
module = SimpleModule("test_if", num_qubits=1, num_results=2)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.m(module.qubits[0], module.results[1])
qis.if_result(
module.results[0],
lambda: qis.if_result(
module.results[1],
lambda: qis.x(module.qubits[0])
)
)
logger = GateLogger()
_eval(module, logger, [True, True])
assert logger.instructions == ["m qubit[0] => out[0]", "m qubit[0] => out[1]", "x qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_nested_if_not(matrix) -> None:
module = SimpleModule("test_if", num_qubits=1, num_results=2)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.m(module.qubits[0], module.results[1])
qis.if_result(
module.results[0],
zero=lambda: qis.if_result(
module.results[1],
zero=lambda: qis.x(module.qubits[0])
)
)
logger = GateLogger()
_eval(module, logger, [False, False])
assert logger.instructions == ["m qubit[0] => out[0]", "m qubit[0] => out[1]", "x qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_nested_if_then_else(matrix) -> None:
module = SimpleModule("test_if_then_else", num_qubits=1, num_results=2)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.m(module.qubits[0], module.results[1])
qis.if_result(
module.results[0],
one=lambda: qis.if_result(
module.results[1],
zero=lambda: qis.x(module.qubits[0])
)
)
logger = GateLogger()
_eval(module, logger, [True, False])
assert logger.instructions == ["m qubit[0] => out[0]", "m qubit[0] => out[1]", "x qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_nested_else_then_if(matrix) -> None:
module = SimpleModule("test_else_then_if", num_qubits=1, num_results=2)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.m(module.qubits[0], module.results[0])
qis.m(module.qubits[0], module.results[1])
qis.if_result(
module.results[0],
zero=lambda: qis.if_result(
module.results[1],
one=lambda: qis.x(module.qubits[0])
)
)
logger = GateLogger()
_eval(module, logger, [False, True])
assert logger.instructions == ["m qubit[0] => out[0]", "m qubit[0] => out[1]", "x qubit[0]"]
@pytest.mark.parametrize("matrix", static_generator_variations)
def test_results_default_to_zero_if_not_measured(matrix) -> None:
module = SimpleModule(
"test_if_not_measured", num_qubits=1, num_results=1
)
module.use_static_qubit_alloc(matrix[0])
module.use_static_result_alloc(matrix[1])
qis = BasicQisBuilder(module.builder)
qis.if_result(
module.results[0],
one=lambda: qis.x(module.qubits[0]),
zero=lambda: qis.h(module.qubits[0])
)
logger = GateLogger()
_eval(module, logger)
assert logger.instructions == ["h qubit[0]"]
def _eval(module: SimpleModule,
gates: GateSet,
result_stream: Optional[List[bool]] = None) -> None:
with tempfile.NamedTemporaryFile(suffix=".ll") as f:
f.write(module.ir().encode("utf-8"))
f.flush()
NonadaptiveEvaluator().eval(f.name, gates, None, result_stream)
| 38.304348
| 96
| 0.691146
| 1,211
| 8,810
| 4.829067
| 0.084228
| 0.069767
| 0.075581
| 0.046512
| 0.869015
| 0.869015
| 0.863201
| 0.843023
| 0.841484
| 0.825068
| 0
| 0.021551
| 0.162543
| 8,810
| 229
| 97
| 38.471616
| 0.771076
| 0.023383
| 0
| 0.682292
| 0
| 0
| 0.077111
| 0
| 0
| 0
| 0
| 0
| 0.0625
| 1
| 0.067708
| false
| 0
| 0.03125
| 0
| 0.098958
| 0.005208
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
2197db26d5b892574b851abdc3a4292cbcb330f1
| 129
|
py
|
Python
|
app/blueprint/registration/__init__.py
|
NTUT-108-SE/CMS-Backend
|
1daa37960ba61f935da5174516f0a2e411b68706
|
[
"MIT"
] | null | null | null |
app/blueprint/registration/__init__.py
|
NTUT-108-SE/CMS-Backend
|
1daa37960ba61f935da5174516f0a2e411b68706
|
[
"MIT"
] | null | null | null |
app/blueprint/registration/__init__.py
|
NTUT-108-SE/CMS-Backend
|
1daa37960ba61f935da5174516f0a2e411b68706
|
[
"MIT"
] | 1
|
2019-10-12T02:48:16.000Z
|
2019-10-12T02:48:16.000Z
|
from flask import Blueprint
registration = Blueprint('registration', __name__, url_prefix='/registration')
from . import index
| 21.5
| 78
| 0.790698
| 14
| 129
| 6.928571
| 0.642857
| 0.43299
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116279
| 129
| 5
| 79
| 25.8
| 0.850877
| 0
| 0
| 0
| 0
| 0
| 0.193798
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0.666667
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
|
0
| 6
|
219a181c0e1b518ebd3a632f4c016bce2504111f
| 162
|
py
|
Python
|
tests/mockprog.py
|
realead/exetest
|
7143c04de8f857f556ff0396b4fa8afc147720a5
|
[
"MIT"
] | null | null | null |
tests/mockprog.py
|
realead/exetest
|
7143c04de8f857f556ff0396b4fa8afc147720a5
|
[
"MIT"
] | null | null | null |
tests/mockprog.py
|
realead/exetest
|
7143c04de8f857f556ff0396b4fa8afc147720a5
|
[
"MIT"
] | null | null | null |
from __future__ import print_function
import sys
if len(sys.argv) == 1:
exit(42)
print(sys.argv[1])
print(sys.argv[1]+sys.argv[1], file=sys.stderr)
exit(0)
| 16.2
| 47
| 0.703704
| 30
| 162
| 3.633333
| 0.5
| 0.256881
| 0.293578
| 0.238532
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.049645
| 0.12963
| 162
| 9
| 48
| 18
| 0.723404
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.285714
| 0
| 0.285714
| 0.428571
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
21b36e1bcae1e9d1aa0971cd8b567b122abf7cf1
| 13
|
py
|
Python
|
requirements/requirements_dev.py
|
HilbertsSpace/AsciiEngine
|
f904baae7040f61d3514cdd91368144c4b158074
|
[
"MIT"
] | null | null | null |
requirements/requirements_dev.py
|
HilbertsSpace/AsciiEngine
|
f904baae7040f61d3514cdd91368144c4b158074
|
[
"MIT"
] | null | null | null |
requirements/requirements_dev.py
|
HilbertsSpace/AsciiEngine
|
f904baae7040f61d3514cdd91368144c4b158074
|
[
"MIT"
] | null | null | null |
pdbpp==0.10.2
| 13
| 13
| 0.692308
| 4
| 13
| 2.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.307692
| 0
| 13
| 1
| 13
| 13
| 0.384615
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
21e9b343709273f42c39aad64d38b88b4bbea984
| 11
|
py
|
Python
|
print.py
|
verrrooon/tensor1
|
85beb58044e0bbdef564cb5817da4b68ca8c872d
|
[
"CC0-1.0"
] | null | null | null |
print.py
|
verrrooon/tensor1
|
85beb58044e0bbdef564cb5817da4b68ca8c872d
|
[
"CC0-1.0"
] | null | null | null |
print.py
|
verrrooon/tensor1
|
85beb58044e0bbdef564cb5817da4b68ca8c872d
|
[
"CC0-1.0"
] | null | null | null |
print(4**5)
| 11
| 11
| 0.636364
| 3
| 11
| 2.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 0
| 11
| 1
| 11
| 11
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
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| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
21f16b59dbe50a17b6bf0cb7540b3442725f1f63
| 2,598
|
py
|
Python
|
tests/test_games.py
|
aequitas/munerator
|
deb1d2ed6c06d17bf3005d75a03e4f2eb7a9938e
|
[
"MIT"
] | null | null | null |
tests/test_games.py
|
aequitas/munerator
|
deb1d2ed6c06d17bf3005d75a03e4f2eb7a9938e
|
[
"MIT"
] | null | null | null |
tests/test_games.py
|
aequitas/munerator
|
deb1d2ed6c06d17bf3005d75a03e4f2eb7a9938e
|
[
"MIT"
] | null | null | null |
from munerator.games import Game
def test_game_mapstring():
expected_mapstring = ("set g_warmup 0;set g_doWarmup 0;set g_spawnprotect 2000;set g_speed 320;"
"set g_gravity 800;set g_knockback 1000;set map_restart 0;set g_instantgib 0;"
"set g_vampire 0;set g_regen 0;set g_rockets 0;set g_catchup 0;set g_respawntime 0;"
"g_catchup 5;set g_motd no special mode;set fraglimit 16;set g_gametype 0;"
"map mapname")
game = Game('mapname', 0, 4)
assert game.mapstring() == expected_mapstring
def test_game_mapstring_special():
expected_mapstring = ("set g_warmup 0;set g_doWarmup 0;set g_spawnprotect 2000;set g_speed 320;"
"set g_gravity 800;set g_knockback 1000;set map_restart 0;set g_instantgib 0;"
"set g_vampire 0;set g_regen 0;set g_rockets 0;set g_catchup 0;set g_respawntime 0;"
"g_catchup 5;set g_instantgib 2;set g_motd instagib;set fraglimit 16;"
"set g_gametype 0;map mapname")
game = Game('mapname', 0, 4, 'instagib')
assert game.mapstring() == expected_mapstring
def test_game_mapstring_team():
expected_mapstring = ("set g_warmup 0;set g_doWarmup 0;set g_spawnprotect 2000;set g_speed 320;"
"set g_gravity 800;set g_knockback 1000;set map_restart 0;set g_instantgib 0;"
"set g_vampire 0;set g_regen 0;set g_rockets 0;set g_catchup 0;set g_respawntime 0;"
"set g_teamAutoJoin 0;set g_teamForceBalance 1;set capturelimit 5;set g_respawntime 5;"
"set g_motd no special mode;set fraglimit 16;set g_gametype 4;map mapname")
game = Game('mapname', 4, 4)
assert game.mapstring() == expected_mapstring
def test_replace_nextmap():
expected_mapstring = ("set nextmap \"set g_warmup 0;set g_doWarmup 0;set g_spawnprotect 2000;set g_speed 320;"
"set g_gravity 800;set g_knockback 1000;set map_restart 0;set g_instantgib 0;"
"set g_vampire 0;set g_regen 0;set g_rockets 0;set g_catchup 0;set g_respawntime 0;"
"set g_teamAutoJoin 0;set g_teamForceBalance 1;set capturelimit 5;set g_respawntime 5;"
"set g_motd no special mode;set fraglimit 16;set g_gametype 4;map mapname;"
"set nextmap vstr map01\";")
game = Game('mapname', 4, 4)
assert game.nextmapstring('vstr map01') == expected_mapstring
| 50.941176
| 114
| 0.634719
| 386
| 2,598
| 4.046632
| 0.137306
| 0.161332
| 0.115237
| 0.076825
| 0.87644
| 0.87644
| 0.87644
| 0.848912
| 0.820743
| 0.74904
| 0
| 0.068649
| 0.287914
| 2,598
| 50
| 115
| 51.96
| 0.775676
| 0
| 0
| 0.529412
| 0
| 0
| 0.548499
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 1
| 0.117647
| false
| 0
| 0.029412
| 0
| 0.147059
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
df1463331b8b2379f9ea72853adfd406b93cd99b
| 30
|
py
|
Python
|
main/parse_data/__init__.py
|
anonymous203030/Tele_Source
|
cb8a591bdca2d3d73690ba8c277816b7f38447d7
|
[
"MIT"
] | null | null | null |
main/parse_data/__init__.py
|
anonymous203030/Tele_Source
|
cb8a591bdca2d3d73690ba8c277816b7f38447d7
|
[
"MIT"
] | null | null | null |
main/parse_data/__init__.py
|
anonymous203030/Tele_Source
|
cb8a591bdca2d3d73690ba8c277816b7f38447d7
|
[
"MIT"
] | null | null | null |
from .parse import parse_data
| 15
| 29
| 0.833333
| 5
| 30
| 4.8
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 30
| 1
| 30
| 30
| 0.923077
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
df547bc5a8710395ef4feccc9ed9bf377eae9474
| 168
|
py
|
Python
|
mtcnn/modeling/model_builder.py
|
tkhe/simple-mtcnn
|
f39b66ec958efc745e1af8a4e0c65a63e0d4a6d8
|
[
"MIT"
] | null | null | null |
mtcnn/modeling/model_builder.py
|
tkhe/simple-mtcnn
|
f39b66ec958efc745e1af8a4e0c65a63e0d4a6d8
|
[
"MIT"
] | null | null | null |
mtcnn/modeling/model_builder.py
|
tkhe/simple-mtcnn
|
f39b66ec958efc745e1af8a4e0c65a63e0d4a6d8
|
[
"MIT"
] | null | null | null |
from mtcnn.modeling.pnet import PNet
from mtcnn.modeling.rnet import RNet
net_type = {'pnet': PNet, 'rnet': RNet}
def build_model(type):
return net_type[type]()
| 18.666667
| 39
| 0.72619
| 26
| 168
| 4.576923
| 0.461538
| 0.151261
| 0.285714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.14881
| 168
| 8
| 40
| 21
| 0.832168
| 0
| 0
| 0
| 0
| 0
| 0.047619
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.4
| 0.2
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
10d9d3ac58db57dd95331a29bac95bb79fd407ce
| 21,687
|
py
|
Python
|
auxiliary.py
|
Jackcfchow/Microeconometrics-Paper
|
0e0324932d3029a2d8adf3a898e0b0754a31277c
|
[
"MIT"
] | 1
|
2021-04-27T14:54:06.000Z
|
2021-04-27T14:54:06.000Z
|
auxiliary.py
|
Jackcfchow/Microeconometrics-Paper
|
0e0324932d3029a2d8adf3a898e0b0754a31277c
|
[
"MIT"
] | null | null | null |
auxiliary.py
|
Jackcfchow/Microeconometrics-Paper
|
0e0324932d3029a2d8adf3a898e0b0754a31277c
|
[
"MIT"
] | null | null | null |
import numpy as np
import pandas as pd
from statsmodels.formula.api import wls
import statsmodels.api as sm
def get_table2_result(df_data, dep, result_dataframe ):
df_data[dep].replace(' ', np.nan, inplace=True)
data = df_data.dropna(subset=[dep])
result = result_dataframe
print(dep)
fit = wls(dep + " ~ tr9 +C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=True)
result.loc[result["Dependent variable St"] == dep, "Parameter"] = fit.params["tr9"].round(3)
result.loc[result["Dependent variable St"] == dep, "SE"] = fit.bse["tr9"].round(3)
result.loc[result["Dependent variable St"] == dep, "P Value"] = fit.pvalues["tr9"]
return(fit)
def get_1st_stage_result(data):
#remember to setup a dataframe to write result
#result = result.set_index('Dependent variable')
# 2SLS: first stage esti: use idvar as IV of eng
fit_st1 = wls( "eng ~ idvar + C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
data['eng_hat'] = fit_st1.predict(data)
return(data)
def get_ols_tsls_result(df_data, dep, result_dataframe ):
#remember to setup a dataframe to write result
#result = result.set_index('Dependent variable')
df_data[dep].replace(' ', np.nan, inplace=True)
data = df_data.dropna(subset=[dep])
result = result_dataframe
print(dep)
# get the ols result
ols = wls(dep + " ~ eng +C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
# 2SLS: first stage esti: use idvar as IV of eng; and second stage
# fit_st1 = wls( "eng ~ idvar + C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
# data['eng_hat'] = fit_st1.predict(data)
fit_st2 = wls(dep + " ~ eng_hat +C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
# fit_st2.summary()
result.loc[result["Dependent variable St"] == dep, "OLS Parameter"] = ols.params["eng"].round(3)
result.loc[result["Dependent variable St"] == dep, "OLS SE"] = ols.bse["eng"].round(3)
result.loc[result["Dependent variable St"] == dep, "OLS P Value"] = ols.pvalues["eng"]
result.loc[result["Dependent variable St"] == dep, "2SLS Parameter"] = fit_st2.params["eng_hat"].round(3)
result.loc[result["Dependent variable St"] == dep, "2SLS SE"] = fit_st2.bse["eng_hat"].round(3)
result.loc[result["Dependent variable St"] == dep, "2SLS P Value"] = fit_st2.pvalues["eng_hat"]
result.loc[result["Dependent variable St"] == dep, "2SLS Adj R sq"] = fit_st2.rsquared_adj
return(ols,fit_st2)
def get_asterisk(data,P_value_col_name, Reg_name):
Text = Reg_name +" Sig. level"
data.loc[data[P_value_col_name] < 1, Text] = " "
data.loc[data[P_value_col_name] <= 0.1, Text] = "*"
data.loc[data[P_value_col_name] <= 0.05, Text] = "**"
data.loc[data[P_value_col_name] <= 0.01, Text] = "***"
def get_asteris_and_coef(data,P_value_col_name, Reg_name, New_col_name):
sig_level_name = Reg_name +" Sig. level"
parameter_name = Reg_name +" Parameter"
se_name = Reg_name +" SE"
data.loc[data[P_value_col_name] < 1, sig_level_name] = " "
data.loc[data[P_value_col_name] <= 0.1, sig_level_name] = "*"
data.loc[data[P_value_col_name] <= 0.05, sig_level_name] = "**"
data.loc[data[P_value_col_name] <= 0.01, sig_level_name] = "***"
data[New_col_name] = (data[parameter_name].astype(str) + data[sig_level_name])
#data.loc = data.loc.drop(columns=[parameter_level_name, "OLS P Value", "Coef Sig. level"])
def get_variable_full_name(data_full):
# combine the result
dictionary = dict([
("eng1", "Speaks English not well or better"),
("eng2", "Speaks English well or better"),
("eng3", "Speaks English very well"),
("eng", "English-speaking ability ordinal measure"),
("marriedpresent", "Is currently married with spouse present"),
("divorced", "Is currently divorced"),
("evermarried", "Has ever married"),
("spouseeng", "Spouse English-speaking ability ordinal measure"),
("marriednative", "Spouse is US-born"),
("couplesamebpld", "Spouse has the same country of birth"),
("couplesameancestry1", "Spouse has the same ancestry"),
("spouseage", "Spouse age"),
("spouseyrssch", "Spouse years of schooling"),
("spouselnwage", "Spouse log(wages last year)"),
("spouseworkedly", "Spouse worked last year"),
("bothworked", "Both worked last year"),
("nchild", "Number of children living in same household"),
("haskid", "Has a child living in same household"),
("nchild_spouse", "Number of children living in same household, only individuals married spouse present"),
("haskid_spouse", "Has a child living in same household, only individuals married with spouse present"),
("singleparent", "Is a single parent"),
("nevermarried_haskid", "Is a never married, single parent"),
("share_bpld_minusself", "Fraction of PUMA population from same country of birth"),
("abovemean_bpld2", "Fraction from same country of birth is above national mean for the country of birth"),
("ancestpct_minusself", "Fraction of PUMA population with same primary ancestry"),
("abovemean_ancestry2", "Fraction with same ancestry is above national mean for the primary ancestry")
])
Dict_for_sumlist2 = dict([
("English-speaking ability ordinal measure", "Panel A. Regressors"),
("Age", "Panel A. Regressors"),
("Female", "Panel A. Regressors"),
("White", "Panel A. Regressors"),
("Black", "Panel A. Regressors"),
("Other", "Panel A. Regressors"),
("Asian/Pacific Islander", "Panel A. Regressors"),
("Multi", "Panel A. Regressors"),
("Hispdum", "Panel A. Regressors"),
("Years of schooling", "Panel A. Regressors"),
("Is currently married with spouse present", "Panel B. Marriage outcomes"),
("Is currently divorced", "Panel B. Marriage outcomes"),
("Has ever married", "Panel B. Marriage outcomes"),
("Spouse English-speaking ability ordinal measure", "Panel B. Marriage outcomes"),
("Spouse is US-born", "Panel B. Marriage outcomes"),
("Spouse has the same country of birth", "Panel B. Marriage outcomes"),
("Spouse has the same ancestry", "Panel B. Marriage outcomes"),
("Spouse age", "Panel B. Marriage outcomes"),
("Spouse years of schooling", "Panel B. Marriage outcomes"),
("Spouse log(wages last year)", "Panel B. Marriage outcomes"),
("Spouse worked last year", "Panel B. Marriage outcomes"),
("Both worked last year", "Panel B. Marriage outcomes"),
("Number of children living in same household", "Panel C. Fertility outcomes"),
("Has a child living in same household", "Panel C. Fertility outcomes"),
("Number of children living in same household, only individuals married spouse present",
"Panel C. Fertility outcomes"),
("Has a child living in same household, only individuals married with spouse present",
"Panel C. Fertility outcomes"),
("Is a single parent", "Panel C. Fertility outcomes"),
("Is a never married, single parent", "Panel C. Fertility outcomes"),
("Fraction of PUMA population from same country of birth", "Panel D. Residential location outcomes"),
("Fraction from same country of birth is above national mean for the country of birth",
"Panel D. Residential location outcomes"),
("Fraction of PUMA population with same primary ancestry", "Panel D. Residential location outcomes"),
("Fraction with same ancestry is above national mean for the primary ancestry",
"Panel D. Residential location outcomes")
])
for i in data_full["Dependent variable St"]:
data_full.loc[data_full["Dependent variable St"] == i, "Dependent variable"] = dictionary[i]
data_full.loc[data_full["Dependent variable St"] == i, "Panel"] = Dict_for_sumlist2[i]
data_full = data_full.set_index('Dependent variable')
data_full = data_full.drop(columns=['Dependent variable St'])
return (data_full)
def get_first_stage_result_table4(data ,extra_contorl=""):
#remember to setup a dataframe to write result
#result = result.set_index('Dependent variable')
if extra_contorl =="":
fit_st1 = wls( "eng ~ idvar + C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum" +extra_contorl, data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
data['eng_hat'] = fit_st1.predict(data)
else:
fit_st1 = wls( "eng ~ idvar + C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum" +"+"+ extra_contorl, data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
data['eng_hat'] = fit_st1.predict(data)
return(data)
def get_tsls_result_table4(df_data, dep , result_dataframe ,extra_contorl=""):
#remember to setup a dataframe to write result
#result = result.set_index('Dependent variable')
df_data[dep].replace(' ', np.nan, inplace=True)
data = df_data.dropna(subset=[dep])
result = result_dataframe
print(dep)
if extra_contorl =="":
fit_st2 = wls(dep + " ~ eng_hat +C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum" + extra_contorl, data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
else:
fit_st2 = wls(dep + " ~ eng_hat +C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum" +"+" + extra_contorl, data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
result.loc[result["Dependent variable St"] == dep, "2SLS Parameter"] = fit_st2.params["eng_hat"].round(3)
result.loc[result["Dependent variable St"] == dep, "2SLS SE"] = fit_st2.bse["eng_hat"].round(3)
result.loc[result["Dependent variable St"] == dep, "2SLS P Value"] = fit_st2.pvalues["eng_hat"]
return(fit_st2)
def get_Durbin_Wu_Hausman_result(df, dep,result_frame):
#setup a dataframe to write result
#result = result.set_index('Dependent variable')
df[dep].replace(' ', np.nan, inplace=True)
data = df.dropna(subset=[dep])
result_DWH= result_frame
print(dep)
test_reg = wls(dep + " ~ eng + Epsilon +C(agearr) + C(age) + C(bpld) + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
result_DWH.loc[result_DWH["Dependent variable St"] == dep, "Epsilon Parameter"] = test_reg.params["Epsilon"].round(3)
result_DWH.loc[result_DWH["Dependent variable St"] == dep, "Epsilon SE"] = test_reg.bse["Epsilon"].round(3)
result_DWH.loc[result_DWH["Dependent variable St"] == dep, "Epsilon P Value"] = test_reg.pvalues["Epsilon"]
def get_ols_tsls_result_Robust2(df_data, dep, result_dataframe ):
#remember to setup a dataframe to write result
df_data[dep].replace(' ', np.nan, inplace=True)
data = df_data.dropna(subset=[dep])
result = result_dataframe
print(dep)
# 2SLS: first stage esti: use idvar as IV of eng; and second stage
fit_st2 = wls(dep + " ~ eng_hat +C(agearr) + C(age) + C(bpld)+ C(statefip)*pwlinear + female + black + asianpi + other + multi + hispdum", data=data, weights=data["perwt2"] ).fit(cov_type='cluster', cov_kwds={'groups': data['bpld']}, use_t=False)
# fit_st2.summary()
result.loc[result["Dependent variable St"] == dep, "2SLS Parameter"] = fit_st2.params["eng_hat"].round(3)
result.loc[result["Dependent variable St"] == dep, "2SLS SE"] = fit_st2.bse["eng_hat"].round(3)
result.loc[result["Dependent variable St"] == dep, "2SLS P Value"] = fit_st2.pvalues["eng_hat"]
result.loc[result["Dependent variable St"] == dep, "Adj R sq"] = fit_st2.rsquared_adj
return(fit_st2)
def get_variable_full_name_table2(data_full):
dictionary = dict([
("eng1", "1. Speaks English not well or better"),
("eng2", "2. Speaks English well or better"),
("eng3", "3. Speaks English very well"),
("eng", "4. English-speaking ability ordinal measure"),
("marriedpresent", "1. Is currently married with spouse present"),
("divorced", "2. Is currently divorced"),
("evermarried", "3. Has ever married"),
("spouseeng", "1. Spouse English-speaking ability ordinal measure"),
("marriednative", "2. Spouse is US-born"),
("couplesamebpld", "3. Spouse has the same country of birth"),
("couplesameancestry1", "4. Spouse has the same ancestry"),
("spouseage", "1. Spouse age"),
("spouseyrssch", "2. Spouse years of schooling"),
("spouselnwage", "1. Spouse log(wages last year)"),
("spouseworkedly", "2. Spouse worked last year"),
("bothworked", "3. Both worked last year"),
("nchild", "1. Number of children living in same household"),
("haskid", "2. Has a child living in same household"),
("nchild_spouse", "3. Number of children living in same household, only individuals married spouse present"),
("haskid_spouse", "4. Has a child living in same household, only individuals married with spouse present"),
("singleparent", "5. Is a single parent"),
("nevermarried_haskid", "6. Is a never married, single parent"),
("share_bpld_minusself", "1. Fraction of PUMA population from same country of birth"),
("abovemean_bpld2", "2. Fraction from same country of birth is above national mean for the country of birth"),
("ancestpct_minusself", "3. Fraction of PUMA population with same primary ancestry"),
("abovemean_ancestry2", "4. Fraction with same ancestry is above national mean for the primary ancestry")
])
dictionary2 = dict([
("1. Speaks English not well or better", "Panel A. English proficiency measures"),
("2. Speaks English well or better", "Panel A. English proficiency measures"),
("3. Speaks English very well", "Panel A. English proficiency measures"),
("4. English-speaking ability ordinal measure", "Panel A. English proficiency measures"),
("1. Is currently married with spouse present", "Panel B. Marital status"),
("2. Is currently divorced", "Panel B. Marital status"),
("3. Has ever married", "Panel B. Marital status"),
("1. Spouse English-speaking ability ordinal measure", "Panel C. Spouse’s nativity and ethnicity"),
("2. Spouse is US-born", "Panel C. Spouse’s nativity and ethnicity"),
("3. Spouse has the same country of birth", "Panel C. Spouse’s nativity and ethnicity"),
("4. Spouse has the same ancestry", "Panel C. Spouse’s nativity and ethnicity"),
("1. Spouse age", "Panel D. Spouse’s age and education"),
("2. Spouse years of schooling", "Panel D. Spouse’s age and education"),
("1. Spouse log(wages last year)", "Panel E. Spouse’s labor market outcomes"),
("2. Spouse worked last year", "Panel E. Spouse’s labor market outcomes"),
("3. Both worked last year", "Panel E. Spouse’s labor market outcomes"),
("1. Number of children living in same household", "Panel F. Fertility"),
("2. Has a child living in same household", "Panel F. Fertility"),
("3. Number of children living in same household, only individuals married spouse present",
"Panel F. Fertility"),
("4. Has a child living in same household, only individuals married with spouse present",
"Panel F. Fertility"),
("5. Is a single parent", "Panel F. Fertility"),
("6. Is a never married, single parent", "Panel F. Fertility"),
("1. Fraction of PUMA population from same country of birth", "Panel G. Residential location"),
("2. Fraction from same country of birth is above national mean for the country of birth",
"Panel G. Residential location"),
("3. Fraction of PUMA population with same primary ancestry", "Panel G. Residential location"),
("4. Fraction with same ancestry is above national mean for the primary ancestry",
"Panel G. Residential location")
])
for i in data_full["Dependent variable St"]:
data_full.loc[data_full["Dependent variable St"] == i, "Dependent variable"] = dictionary[i]
for j in data_full["Dependent variable"]:
data_full.loc[data_full["Dependent variable"] == j, "Panel"] = dictionary2[j]
data_full = data_full.drop(columns=['Dependent variable St'])
data_full = data_full.set_index(['Panel',"Dependent variable"],inplace=False)
return (data_full)
def get_variable_full_name_table3(data_full):
dictionary = dict([
("marriedpresent", "1. Is currently married with spouse present"),
("divorced", "2. Is currently divorced"),
("evermarried", "3. Has ever married"),
("spouseeng", "1. Spouse English-speaking ability ordinal measure"),
("marriednative", "2. Spouse is US-born"),
("couplesamebpld", "3. Spouse has the same country of birth"),
("couplesameancestry1", "4. Spouse has the same ancestry"),
("spouseage", "1. Spouse age"),
("spouseyrssch", "2. Spouse years of schooling"),
("spouselnwage", "1. Spouse log(wages last year)"),
("spouseworkedly", "2. Spouse worked last year"),
("bothworked", "3. Both worked last year"),
("nchild", "1. Number of children living in same household"),
("haskid", "2. Has a child living in same household"),
("nchild_spouse", "3. Number of children living in same household, only individuals married spouse present"),
("haskid_spouse", "4. Has a child living in same household, only individuals married with spouse present"),
("singleparent", "5. Is a single parent"),
("nevermarried_haskid", "6. Is a never married, single parent"),
("share_bpld_minusself", "1. Fraction of PUMA population from same country of birth"),
("abovemean_bpld2", "2. Fraction from same country of birth is above national mean for the country of birth"),
("ancestpct_minusself", "3. Fraction of PUMA population with same primary ancestry"),
("abovemean_ancestry2", "4. Fraction with same ancestry is above national mean for the primary ancestry")
])
dictionary2 = dict([
("1. Is currently married with spouse present", "Panel A. Marital status"),
("2. Is currently divorced", "Panel A. Marital status"),
("3. Has ever married", "Panel A. Marital status"),
("1. Spouse English-speaking ability ordinal measure", "Panel B. Spouse’s nativity and ethnicity"),
("2. Spouse is US-born", "Panel B. Spouse’s nativity and ethnicity"),
("3. Spouse has the same country of birth", "Panel B. Spouse’s nativity and ethnicity"),
("4. Spouse has the same ancestry", "Panel B. Spouse’s nativity and ethnicity"),
("1. Spouse age", "Panel C. Spouse’s age and education"),
("2. Spouse years of schooling", "Panel C. Spouse’s age and education"),
("1. Spouse log(wages last year)", "Panel D. Spouse’s labor market outcomes"),
("2. Spouse worked last year", "Panel D. Spouse’s labor market outcomes"),
("3. Both worked last year", "Panel D. Spouse’s labor market outcomes"),
("1. Number of children living in same household", "Panel E. Fertility"),
("2. Has a child living in same household", "Panel E. Fertility"),
("3. Number of children living in same household, only individuals married spouse present",
"Panel E. Fertility"),
("4. Has a child living in same household, only individuals married with spouse present",
"Panel E. Fertility"),
("5. Is a single parent", "Panel E. Fertility"),
("6. Is a never married, single parent", "Panel E. Fertility"),
("1. Fraction of PUMA population from same country of birth", "Panel F. Residential location"),
("2. Fraction from same country of birth is above national mean for the country of birth",
"Panel F. Residential location"),
("3. Fraction of PUMA population with same primary ancestry", "Panel F. Residential location"),
("4. Fraction with same ancestry is above national mean for the primary ancestry",
"Panel F. Residential location")
])
for i in data_full["Dependent variable St"]:
data_full.loc[data_full["Dependent variable St"] == i, "Dependent variable"] = dictionary[i]
for j in data_full["Dependent variable"]:
data_full.loc[data_full["Dependent variable"] == j, "Panel"] = dictionary2[j]
data_full = data_full.set_index(['Panel',"Dependent variable"],inplace=False)
data_full = data_full.drop(columns=['Dependent variable St'])
return (data_full)
| 61.262712
| 254
| 0.6562
| 2,929
| 21,687
| 4.760669
| 0.082622
| 0.054862
| 0.040878
| 0.036145
| 0.907774
| 0.865462
| 0.830895
| 0.778256
| 0.733864
| 0.697433
| 0
| 0.012147
| 0.20284
| 21,687
| 353
| 255
| 61.436261
| 0.794424
| 0.050906
| 0
| 0.427586
| 0
| 0.034483
| 0.563105
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.041379
| false
| 0
| 0.013793
| 0
| 0.065517
| 0.017241
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
10db0f983e263cca2788af8d5cda8c3d7ab0c00d
| 258
|
py
|
Python
|
src/recipy/providers/exceptions.py
|
emilywilder/recipy
|
fb64978a120ef62c372ccc96fbed8760b7abf1e4
|
[
"Apache-2.0"
] | null | null | null |
src/recipy/providers/exceptions.py
|
emilywilder/recipy
|
fb64978a120ef62c372ccc96fbed8760b7abf1e4
|
[
"Apache-2.0"
] | null | null | null |
src/recipy/providers/exceptions.py
|
emilywilder/recipy
|
fb64978a120ef62c372ccc96fbed8760b7abf1e4
|
[
"Apache-2.0"
] | null | null | null |
class ProviderException(Exception):
pass
class NoProviderException(ProviderException):
def __init__(self, hostname) -> None:
self.hostname = hostname
def __str__(self) -> str:
return "No provider for {0}".format(self.hostname)
| 23.454545
| 58
| 0.689922
| 27
| 258
| 6.296296
| 0.62963
| 0.211765
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004878
| 0.205426
| 258
| 10
| 59
| 25.8
| 0.82439
| 0
| 0
| 0
| 0
| 0
| 0.073643
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0.142857
| 0
| 0.142857
| 0.714286
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 6
|
337c60abc309b77269c2fc2b8231dbc59e0915c4
| 4,095
|
py
|
Python
|
tests/commons/big_query/copy_job_async/result_check/job_result_example.py
|
Morgenz/bbq
|
f0fd3f626841c610aee80ad08a61123b7cccb775
|
[
"Apache-2.0"
] | 41
|
2018-05-08T11:54:37.000Z
|
2022-02-09T21:19:17.000Z
|
tests/commons/big_query/copy_job_async/result_check/job_result_example.py
|
Morgenz/bbq
|
f0fd3f626841c610aee80ad08a61123b7cccb775
|
[
"Apache-2.0"
] | 139
|
2018-06-07T13:45:21.000Z
|
2021-04-30T20:44:06.000Z
|
tests/commons/big_query/copy_job_async/result_check/job_result_example.py
|
Morgenz/bbq
|
f0fd3f626841c610aee80ad08a61123b7cccb775
|
[
"Apache-2.0"
] | 5
|
2019-09-11T12:28:24.000Z
|
2022-02-04T21:38:29.000Z
|
class JobResultExample(object):
IN_PROGRESS = {
"status": {
"state": "IN PROGRESS"
},
"configuration": {
"copy": {
"sourceTable": {
"projectId": "source_project_id",
"tableId": "source_table_id$123",
"datasetId": "source_dataset_id"
},
"destinationTable": {
"projectId": "target_project_id",
"tableId": "target_table_id",
"datasetId": "target_dataset_id"
},
"createDisposition": "CREATE_IF_NEEDED",
"writeDisposition": "WRITE_TRUNCATE"
}
}
}
DONE = {
"status": {
"state": "DONE"
},
"statistics": {
"startTime": "1511356638992",
"endTime": "1511356648992"
},
"configuration": {
"copy": {
"sourceTable": {
"projectId": "source_project_id",
"tableId": "source_table_id$123",
"datasetId": "source_dataset_id"
},
"destinationTable": {
"projectId": "target_project_id",
"tableId": "target_table_id",
"datasetId": "target_dataset_id"
},
"createDisposition": "CREATE_IF_NEEDED",
"writeDisposition": "WRITE_TRUNCATE"
}
}
}
DONE_WITH_RETRY_ERRORS = {
"status": {
"state": "DONE",
"errors": [
{
"reason": "invalid",
"message": "Cannot read a table without a schema"
},
{
"reason": "backendError",
"message": "Backend error"
}
],
"errorResult": {
"reason": "backendError",
"message": "Backend error"
}
},
"statistics": {
"startTime": "1511356638992",
"endTime": "1511356648992"
},
"configuration": {
"copy": {
"sourceTable": {
"projectId": "source_project_id",
"tableId": "source_table_id$123",
"datasetId": "source_dataset_id"
},
"destinationTable": {
"projectId": "target_project_id",
"tableId": "target_table_id",
"datasetId": "target_dataset_id"
},
"createDisposition": "CREATE_NEVER",
"writeDisposition": "WRITE_TRUNCATE"
}
}
}
DONE_WITH_NOT_REPETITIVE_ERRORS = {
"status": {
"state": "DONE",
"errors": [
{
"reason": "invalid",
"message": "Cannot read a table without a schema"
},
{
"reason": "backendError",
"message": "Backend error"
}
],
"errorResult": {
"reason": "invalid",
"message": "Cannot read a table without a schema"
}
},
"statistics": {
"startTime": "1511356638992",
"endTime": "1511356648992"
},
"configuration": {
"copy": {
"sourceTable": {
"projectId": "source_project_id",
"tableId": "source_table_id$123",
"datasetId": "source_dataset_id"
},
"destinationTable": {
"projectId": "target_project_id",
"tableId": "target_table_id",
"datasetId": "target_dataset_id"
},
"createDisposition": "CREATE_IF_NEEDED",
"writeDisposition": "WRITE_TRUNCATE"
}
}
}
| 32.5
| 69
| 0.400488
| 235
| 4,095
| 6.693617
| 0.221277
| 0.045772
| 0.081373
| 0.094088
| 0.93897
| 0.893198
| 0.893198
| 0.893198
| 0.893198
| 0.893198
| 0
| 0.042413
| 0.481807
| 4,095
| 125
| 70
| 32.76
| 0.698869
| 0
| 0
| 0.64
| 0
| 0
| 0.383639
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0.04
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
33ef356d346b786c1077b9015247fc8a9b4cfd44
| 86
|
py
|
Python
|
raven/utilities/__init__.py
|
davidcaron/raven
|
c8dd818e42b81120acf57cef0a340f42785074cf
|
[
"MIT"
] | null | null | null |
raven/utilities/__init__.py
|
davidcaron/raven
|
c8dd818e42b81120acf57cef0a340f42785074cf
|
[
"MIT"
] | null | null | null |
raven/utilities/__init__.py
|
davidcaron/raven
|
c8dd818e42b81120acf57cef0a340f42785074cf
|
[
"MIT"
] | null | null | null |
from .regionalization import regionalize, read_gauged_properties, read_gauged_params
| 28.666667
| 84
| 0.883721
| 10
| 86
| 7.2
| 0.8
| 0.277778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.081395
| 86
| 2
| 85
| 43
| 0.911392
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d56ca53d063b300b97c9b3519a8bcb3e0c9fac8f
| 539
|
py
|
Python
|
pytorch_lightning/accelerator_backends/__init__.py
|
Alicegaz/pytorch-lightning
|
96b45f15aa04e0ad7e0ed20b8717ab1599148966
|
[
"Apache-2.0"
] | 1
|
2021-04-09T08:32:21.000Z
|
2021-04-09T08:32:21.000Z
|
pytorch_lightning/accelerator_backends/__init__.py
|
Alicegaz/pytorch-lightning
|
96b45f15aa04e0ad7e0ed20b8717ab1599148966
|
[
"Apache-2.0"
] | null | null | null |
pytorch_lightning/accelerator_backends/__init__.py
|
Alicegaz/pytorch-lightning
|
96b45f15aa04e0ad7e0ed20b8717ab1599148966
|
[
"Apache-2.0"
] | null | null | null |
from pytorch_lightning.accelerator_backends.gpu_backend import GPUBackend
from pytorch_lightning.accelerator_backends.tpu_backend import TPUBackend
from pytorch_lightning.accelerator_backends.dp_backend import DataParallelBackend
from pytorch_lightning.accelerator_backends.ddp_spawn_backend import DDPSpawnBackend
from pytorch_lightning.accelerator_backends.cpu_backend import CPUBackend
from pytorch_lightning.accelerator_backends.ddp_backend import DDPBackend
from pytorch_lightning.accelerator_backends.ddp2_backend import DDP2Backend
| 67.375
| 84
| 0.922078
| 64
| 539
| 7.421875
| 0.328125
| 0.162105
| 0.294737
| 0.456842
| 0.587368
| 0.176842
| 0
| 0
| 0
| 0
| 0
| 0.003914
| 0.051948
| 539
| 7
| 85
| 77
| 0.925636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d5a19b7a4b30d42b60b0e30b952e694775028f78
| 8,052
|
py
|
Python
|
posts/test.py
|
taxidriver77/django-angular
|
f8d9dc58e05c99b6abe694e6be4b4de769664657
|
[
"0BSD"
] | 8
|
2016-01-11T11:01:29.000Z
|
2019-05-26T18:00:06.000Z
|
posts/test.py
|
sv1jsb/django-angular
|
d527e812e02227c0b7151b9211c8248e6298c4df
|
[
"0BSD"
] | 3
|
2020-02-11T23:41:57.000Z
|
2021-06-10T19:13:54.000Z
|
posts/test.py
|
taxidriver77/django-angular
|
f8d9dc58e05c99b6abe694e6be4b4de769664657
|
[
"0BSD"
] | 8
|
2016-12-19T00:02:26.000Z
|
2022-01-11T13:52:43.000Z
|
# -*- coding: utf-8 -*-
import json
from bson import ObjectId
from django.test.client import Client
from tests.drf.cases import MongoengineCase
from tests.drf.mocks import mock_user1, mock_user2
from authentication.models import User
from posts.models import Post
class PostsCase(MongoengineCase):
@classmethod
def setUpClassData(cls):
cls.user = User(email=mock_user1["email"], username=mock_user1["username"])
cls.user.set_password(mock_user1["password"])
cls.user.save()
cls.post = Post(content="post1", author=cls.user.pk)
cls.post.save()
def setUp(self):
self.client = Client()
def test_get_posts_auth(self):
response = self.client.post('/api/v1/auth/login/',
data=json.dumps({"email": mock_user1["email"], "password": mock_user1["password"]}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.get('/api/v1/posts/', content_type="application/json")
posts = json.loads(response.content)
self.assertGreaterEqual(len(posts), 1)
self.assertContains(response, 'email')
def test_get_posts_non_auth(self):
response = self.client.get('/api/v1/posts/', content_type="application/json")
posts = json.loads(response.content)
self.assertGreaterEqual(len(posts), 1)
self.assertNotContains(response, 'email')
def test_get_user_posts(self):
response = self.client.get('/api/v1/posts/', data={"author_id": self.user["id"]}, content_type="application/json")
posts = json.loads(response.content)
self.assertGreaterEqual(len(posts), 1)
self.assertNotContains(response, 'email')
def test_create_post(self):
response = self.client.post('/api/v1/auth/login/',
data=json.dumps({"email": mock_user1["email"], "password": mock_user1["password"]}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.post('/api/v1/posts/', data=json.dumps({"content": "new post from test"}), content_type="application/json")
self.assertEquals(response.status_code, 201)
response = self.client.post('/api/v1/posts/', data=json.dumps({"wrong_data": "sure"}), content_type="application/json")
self.assertEquals(response.status_code, 400)
def test_create_post_error(self):
response = self.client.post('/api/v1/auth/login/',
data=json.dumps({"email": mock_user1["email"], "password": mock_user1["password"]}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.post('/api/v1/posts/', data=json.dumps({"content": "new post from test", "author": "5688edf51166aa49ea2eb074"}), content_type="application/json")
post = json.loads(response.content)
self.assertEqual(post["author"]["id"], str(self.user["id"]))
def test_update_post(self):
response = self.client.post('/api/v1/auth/login/',
data=json.dumps({"email": mock_user1["email"], "password": mock_user1["password"]}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.put('/api/v1/posts/%s/' % self.post["id"], data=json.dumps({"content": "updated post"}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.put('/api/v1/posts/%s/' % self.post["id"], data=json.dumps({"wrong_data": "sure"}),
content_type="application/json")
self.assertEquals(response.status_code, 400)
self.assertEquals(unicode(self.post), u"post1")
def test_delete_post(self):
response = self.client.post('/api/v1/auth/login/',
data=json.dumps({"email": mock_user1["email"], "password": mock_user1["password"]}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.post('/api/v1/posts/', data=json.dumps({"content": "new post for delete"}), content_type="application/json")
self.assertEquals(response.status_code, 201)
post = json.loads(response.content)
response = self.client.delete('/api/v1/posts/%s/' % post["id"])
self.assertEquals(response.status_code, 204)
def test_errors(self):
u = User(email=mock_user2["email"], username=mock_user2["username"])
u.set_password(mock_user2["password"])
u.save()
response = self.client.post('/api/v1/auth/login/',
data=json.dumps({"email": mock_user2["email"], "password": mock_user2["password"]}),
content_type="application/json")
self.assertEquals(response.status_code, 200)
response = self.client.delete('/api/v1/posts/%s/' % self.post["id"])
self.assertEquals(response.status_code, 403)
response = self.client.put('/api/v1/posts/%s/' % self.post["id"], data=json.dumps({"content": "new content"}), content_type="application/json")
self.assertEquals(response.status_code, 403)
# response = self.client.post('/api/v1/users/', data=json.dumps(mock_user2), content_type="application/json")
# self.assertEquals(response.status_code, 201)
# user_id = json.loads(response.content)["id"]
# response = self.client.get('/api/v1/users/%s/' % user_id)
# self.assertEquals(response.status_code, 200)
# self.assertNotContains(response, 'email')
#
# def test_update_delete_user(self):
# response = self.client.post('/api/v1/auth/login/',
# data=json.dumps({"email": mock_user2["email"], "password": mock_user2["password"]}),
# content_type="application/json")
# self.assertEquals(response.status_code, 200)
# user = json.loads(response.content)
# self.assertEquals(user["username"], mock_user2["password"])
# user["password"] = "new"
# user["confirm_password"] = "new"
# user["tagline"] = "new tagline"
# response = self.client.put('/api/v1/users/%s/' % user["id"], data=json.dumps(user), content_type="application/json")
# self.assertEquals(response.status_code, 200)
# self.assertContains(response, 'new tagline')
# response = self.client.delete('/api/v1/users/%s/' % user["id"])
# self.assertEquals(response.status_code, 204)
#
# def test_errors(self):
# response = self.client.get('/api/v1/users/%s/' % ObjectId())
# self.assertEquals(response.status_code, 404)
# response = self.client.post('/api/v1/users/', data=json.dumps({"wrong_data": "sure"}), content_type="application/json")
# self.assertEquals(response.status_code, 400)
# response = self.client.post('/api/v1/auth/login/',
# data=json.dumps({"email": mock_user2["email"], "password": mock_user2["password"]}),
# content_type="application/json")
# self.assertEquals(response.status_code, 200)
# user = json.loads(response.content)
# response = self.client.put('/api/v1/users/%s/' % user["id"], data=json.dumps({"wrong_data": "sure"}), content_type="application/json")
# self.assertEquals(response.status_code, 400)
# response = self.client.post('/api/v1/auth/logout/')
# self.assertEquals(response.status_code, 204)
# response = self.client.put('/api/v1/users/%s/' % user["id"], data=json.dumps(user), content_type="application/json")
# self.assertEquals(response.status_code, 403)
| 57.514286
| 176
| 0.61463
| 929
| 8,052
| 5.21098
| 0.095802
| 0.061971
| 0.107829
| 0.154927
| 0.794257
| 0.767197
| 0.746953
| 0.736831
| 0.707085
| 0.699442
| 0
| 0.024241
| 0.226403
| 8,052
| 140
| 177
| 57.514286
| 0.75293
| 0.291853
| 0
| 0.505747
| 0
| 0
| 0.17273
| 0.004239
| 0
| 0
| 0
| 0
| 0.252874
| 1
| 0.114943
| false
| 0.091954
| 0.08046
| 0
| 0.206897
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
63ceb6a638662cb76b5d7730ad88355aec9b6f96
| 159
|
py
|
Python
|
Lista_dicionarios/Ex01/Test_Ex01.py
|
SpaceTheArcher/LP2_2s2017
|
6616b3ecfe5838d1cfac1dac1c8e66b1b661486e
|
[
"Apache-2.0"
] | 1
|
2017-08-27T03:45:37.000Z
|
2017-08-27T03:45:37.000Z
|
Lista_dicionarios/Ex01/Test_Ex01.py
|
SpaceTheArcher/LP2_2s2017
|
6616b3ecfe5838d1cfac1dac1c8e66b1b661486e
|
[
"Apache-2.0"
] | null | null | null |
Lista_dicionarios/Ex01/Test_Ex01.py
|
SpaceTheArcher/LP2_2s2017
|
6616b3ecfe5838d1cfac1dac1c8e66b1b661486e
|
[
"Apache-2.0"
] | null | null | null |
from Ex01 import MDC
def test_ex01():
assert MDC(10, 15) == 5
assert MDC(20, 30) == 10
assert MDC(45, 450) == 45
assert MDC(12, 18) == 6
| 22.714286
| 30
| 0.553459
| 27
| 159
| 3.222222
| 0.62963
| 0.413793
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.243243
| 0.301887
| 159
| 7
| 31
| 22.714286
| 0.540541
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.666667
| 1
| 0.166667
| true
| 0
| 0.166667
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
895acc41c8d2e9c555b0b1aeb08c5500e68404a3
| 1,535
|
py
|
Python
|
usone/posts/migrations/0003_auto_20181106_0531.py
|
jpark2320/bbalmu
|
03cb56e141ed1e5ab84ec4cd0d55b68724d4650e
|
[
"MIT"
] | null | null | null |
usone/posts/migrations/0003_auto_20181106_0531.py
|
jpark2320/bbalmu
|
03cb56e141ed1e5ab84ec4cd0d55b68724d4650e
|
[
"MIT"
] | 17
|
2019-02-02T02:46:59.000Z
|
2022-03-08T22:53:30.000Z
|
usone/posts/migrations/0003_auto_20181106_0531.py
|
jpark2320/usone
|
03cb56e141ed1e5ab84ec4cd0d55b68724d4650e
|
[
"MIT"
] | null | null | null |
# Generated by Django 2.0.9 on 2018-11-06 05:31
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('posts', '0002_auto_20181106_0439'),
]
operations = [
migrations.AlterField(
model_name='image',
name='created_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='image_created_by', to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='image',
name='updated_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='image_updated_by', to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='post',
name='created_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='post_created_by', to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='post',
name='updated_by',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, related_name='post_updated_by', to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='post',
name='view_count',
field=models.IntegerField(default=0),
),
]
| 37.439024
| 166
| 0.647557
| 180
| 1,535
| 5.316667
| 0.283333
| 0.050157
| 0.073145
| 0.114943
| 0.745037
| 0.745037
| 0.704284
| 0.704284
| 0.704284
| 0.704284
| 0
| 0.027257
| 0.235179
| 1,535
| 40
| 167
| 38.375
| 0.787905
| 0.029316
| 0
| 0.558824
| 1
| 0
| 0.108871
| 0.015457
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.088235
| 0
| 0.176471
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
89692fea16c911c27c771c68a93c4770fe17d22b
| 36
|
py
|
Python
|
core/common/__init__.py
|
srcc-msu/job_statistics
|
74680a4e4c105ebcff94f089e07fcb44dbcc12d9
|
[
"MIT"
] | null | null | null |
core/common/__init__.py
|
srcc-msu/job_statistics
|
74680a4e4c105ebcff94f089e07fcb44dbcc12d9
|
[
"MIT"
] | null | null | null |
core/common/__init__.py
|
srcc-msu/job_statistics
|
74680a4e4c105ebcff94f089e07fcb44dbcc12d9
|
[
"MIT"
] | null | null | null |
from core.common import controllers
| 18
| 35
| 0.861111
| 5
| 36
| 6.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 36
| 1
| 36
| 36
| 0.96875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
983593b5a833f676c33eca49078536060b7c3fde
| 363
|
py
|
Python
|
pkg/settings.py
|
snackattas/ShutTheBox
|
1d69347968847528888c4c792d4c426bc3d11c4f
|
[
"MIT"
] | 1
|
2016-09-14T18:38:13.000Z
|
2016-09-14T18:38:13.000Z
|
pkg/settings.py
|
snackattas/ShutTheBox
|
1d69347968847528888c4c792d4c426bc3d11c4f
|
[
"MIT"
] | null | null | null |
pkg/settings.py
|
snackattas/ShutTheBox
|
1d69347968847528888c4c792d4c426bc3d11c4f
|
[
"MIT"
] | null | null | null |
"""settings.py - Contains MAILGUN settings"""
MAILGUN_DOMAIN_NAME = "sandbox301369dd8c464b87b7874ba72a5e3039.mailgun.org"
MAILGUN_PRIVATE_API_KEY = "key-de714a26093d427c84abcb980d3f3f0a"
MAILGUN_PUBLIC_API_KEY = "pubkey-2b308844086ef26cee582ce10ac7303b"
MAILGUN_SANDBOX_SENDER = "Mailgun Sandbox <postmaster@sandbox301369dd8c464b87b7874ba72a5e3039.mailgun.org>"
| 51.857143
| 107
| 0.865014
| 32
| 363
| 9.5
| 0.5625
| 0.302632
| 0.322368
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.250729
| 0.055096
| 363
| 6
| 108
| 60.5
| 0.635569
| 0.107438
| 0
| 0
| 0
| 0
| 0.647799
| 0.597484
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
985fd69e6bc70754038457ea40ed5db8a6e11c5a
| 35
|
py
|
Python
|
polygon_crop/__init__.py
|
chiang9/polygon_crop
|
dc7393457b29a500316741325cbe3daf678a1c2f
|
[
"MIT"
] | 1
|
2022-03-07T19:26:39.000Z
|
2022-03-07T19:26:39.000Z
|
polygon_crop/__init__.py
|
chiang9/polygon_crop
|
dc7393457b29a500316741325cbe3daf678a1c2f
|
[
"MIT"
] | null | null | null |
polygon_crop/__init__.py
|
chiang9/polygon_crop
|
dc7393457b29a500316741325cbe3daf678a1c2f
|
[
"MIT"
] | null | null | null |
from polygon_crop.img_crop import *
| 35
| 35
| 0.857143
| 6
| 35
| 4.666667
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085714
| 35
| 1
| 35
| 35
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
9899bd64b4d5206ccc431afe9f2e223bd0afdbf6
| 1,992
|
py
|
Python
|
pizza_cutter/des_pizza_cutter/tests/test_se_image_slice_bnds.py
|
beckermr/pizza-cutter
|
04eefd2d4b2a63975fe809c60b5c8e7e3fcf26c6
|
[
"BSD-3-Clause"
] | null | null | null |
pizza_cutter/des_pizza_cutter/tests/test_se_image_slice_bnds.py
|
beckermr/pizza-cutter
|
04eefd2d4b2a63975fe809c60b5c8e7e3fcf26c6
|
[
"BSD-3-Clause"
] | 194
|
2018-10-24T23:40:47.000Z
|
2021-11-17T16:02:35.000Z
|
pizza_cutter/des_pizza_cutter/tests/test_se_image_slice_bnds.py
|
beckermr/pizza-cutter
|
04eefd2d4b2a63975fe809c60b5c8e7e3fcf26c6
|
[
"BSD-3-Clause"
] | null | null | null |
import os
import pytest
from .._se_image import SEImageSlice
@pytest.mark.skipif(
os.environ.get('TEST_DESDATA', None) is None,
reason=(
'SEImageSlice can only be tested if '
'test data is at TEST_DESDATA'))
@pytest.mark.parametrize('eps', [-0.499999, -0.1, 0, 0.1, 0.499999])
def test_se_image_slice_bnds_odd(se_image_data, eps):
se_im = SEImageSlice(
source_info=se_image_data['source_info'],
psf_model=None,
wcs=se_image_data['eu_wcs'],
wcs_position_offset=1,
wcs_color=0,
psf_kwargs=None,
noise_seeds=[10],
mask_tape_bumps=False,
)
row_cen = 16
col_cen = 19
box_size = 21
box_cen = (box_size - 1) / 2
ra, dec = se_im.image2sky(col_cen+eps, row_cen+eps)
bnds = se_im.compute_slice_bounds(ra, dec, box_size, 1)
assert bnds.rowmin == row_cen - box_cen
assert bnds.rowmax == row_cen + box_cen
assert bnds.colmin == col_cen - box_cen
assert bnds.colmax == col_cen + box_cen
@pytest.mark.skipif(
os.environ.get('TEST_DESDATA', None) is None,
reason=(
'SEImageSlice can only be tested if '
'test data is at TEST_DESDATA'))
@pytest.mark.parametrize('eps', [0.0000001, 0.1, 0.5, 0.7, 0.99999])
def test_se_image_slice_bnds_even(se_image_data, eps):
se_im = SEImageSlice(
source_info=se_image_data['source_info'],
psf_model=None,
wcs=se_image_data['eu_wcs'],
wcs_position_offset=1,
wcs_color=0,
psf_kwargs=None,
noise_seeds=[10],
mask_tape_bumps=False,
)
row_cen = 16
col_cen = 19
box_size = 20
box_cen = (box_size - 1) / 2
ra, dec = se_im.image2sky(col_cen+eps, row_cen+eps)
bnds = se_im.compute_slice_bounds(ra, dec, box_size, 1)
assert bnds.rowmin == row_cen - box_cen + 0.5
assert bnds.rowmax == row_cen + box_cen + 0.5
assert bnds.colmin == col_cen - box_cen + 0.5
assert bnds.colmax == col_cen + box_cen + 0.5
| 29.294118
| 68
| 0.643072
| 316
| 1,992
| 3.762658
| 0.237342
| 0.050463
| 0.060555
| 0.04037
| 0.918419
| 0.918419
| 0.878049
| 0.761985
| 0.731707
| 0.731707
| 0
| 0.049538
| 0.23996
| 1,992
| 67
| 69
| 29.731343
| 0.735799
| 0
| 0
| 0.666667
| 0
| 0
| 0.095382
| 0
| 0
| 0
| 0
| 0
| 0.140351
| 1
| 0.035088
| false
| 0
| 0.052632
| 0
| 0.087719
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
989ef99fd00238735f1d6579adac02fa1a55a3ad
| 5,305
|
py
|
Python
|
numpy/typing/tests/data/reveal/mod.py
|
alexhenrie/numpy
|
662f973ba58563b268d009e67806aa1150ca1cb2
|
[
"BSD-3-Clause"
] | 1
|
2020-12-26T21:54:41.000Z
|
2020-12-26T21:54:41.000Z
|
numpy/typing/tests/data/reveal/mod.py
|
alexhenrie/numpy
|
662f973ba58563b268d009e67806aa1150ca1cb2
|
[
"BSD-3-Clause"
] | 67
|
2021-01-15T04:34:26.000Z
|
2021-08-02T06:29:18.000Z
|
numpy/typing/tests/data/reveal/mod.py
|
alexhenrie/numpy
|
662f973ba58563b268d009e67806aa1150ca1cb2
|
[
"BSD-3-Clause"
] | null | null | null |
import numpy as np
f8 = np.float64()
i8 = np.int64()
u8 = np.uint64()
f4 = np.float32()
i4 = np.int32()
u4 = np.uint32()
td = np.timedelta64(0, "D")
b_ = np.bool_()
b = bool()
f = float()
i = int()
AR = np.array([1], dtype=np.bool_)
AR.setflags(write=False)
AR2 = np.array([1], dtype=np.timedelta64)
AR2.setflags(write=False)
# Time structures
reveal_type(td % td) # E: numpy.timedelta64
reveal_type(AR2 % td) # E: Any
reveal_type(td % AR2) # E: Any
reveal_type(divmod(td, td)) # E: Tuple[{int64}, numpy.timedelta64]
reveal_type(divmod(AR2, td)) # E: Tuple[Any, Any]
reveal_type(divmod(td, AR2)) # E: Tuple[Any, Any]
# Bool
reveal_type(b_ % b) # E: {int8}
reveal_type(b_ % i) # E: {int_}
reveal_type(b_ % f) # E: {float64}
reveal_type(b_ % b_) # E: {int8}
reveal_type(b_ % i8) # E: {int64}
reveal_type(b_ % u8) # E: {uint64}
reveal_type(b_ % f8) # E: {float64}
reveal_type(b_ % AR) # E: Any
reveal_type(divmod(b_, b)) # E: Tuple[{int8}, {int8}]
reveal_type(divmod(b_, i)) # E: Tuple[{int_}, {int_}]
reveal_type(divmod(b_, f)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(b_, b_)) # E: Tuple[{int8}, {int8}]
reveal_type(divmod(b_, i8)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(b_, u8)) # E: Tuple[{uint64}, {uint64}]
reveal_type(divmod(b_, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(b_, AR)) # E: Tuple[Any, Any]
reveal_type(b % b_) # E: {int8}
reveal_type(i % b_) # E: {int_}
reveal_type(f % b_) # E: {float64}
reveal_type(b_ % b_) # E: {int8}
reveal_type(i8 % b_) # E: {int64}
reveal_type(u8 % b_) # E: {uint64}
reveal_type(f8 % b_) # E: {float64}
reveal_type(AR % b_) # E: Any
reveal_type(divmod(b, b_)) # E: Tuple[{int8}, {int8}]
reveal_type(divmod(i, b_)) # E: Tuple[{int_}, {int_}]
reveal_type(divmod(f, b_)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(b_, b_)) # E: Tuple[{int8}, {int8}]
reveal_type(divmod(i8, b_)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(u8, b_)) # E: Tuple[{uint64}, {uint64}]
reveal_type(divmod(f8, b_)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(AR, b_)) # E: Tuple[Any, Any]
# int
reveal_type(i8 % b) # E: {int64}
reveal_type(i8 % i) # E: {int64}
reveal_type(i8 % f) # E: {float64}
reveal_type(i8 % i8) # E: {int64}
reveal_type(i8 % f8) # E: {float64}
reveal_type(i4 % i8) # E: {int64}
reveal_type(i4 % f8) # E: {float64}
reveal_type(i4 % i4) # E: {int32}
reveal_type(i4 % f4) # E: {float32}
reveal_type(i8 % AR) # E: Any
reveal_type(divmod(i8, b)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(i8, i)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(i8, f)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i8, i8)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(i8, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i8, i4)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(i8, f4)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i4, i4)) # E: Tuple[{int32}, {int32}]
reveal_type(divmod(i4, f4)) # E: Tuple[{float32}, {float32}]
reveal_type(divmod(i8, AR)) # E: Tuple[Any, Any]
reveal_type(b % i8) # E: {int64}
reveal_type(i % i8) # E: {int64}
reveal_type(f % i8) # E: {float64}
reveal_type(i8 % i8) # E: {int64}
reveal_type(f8 % i8) # E: {float64}
reveal_type(i8 % i4) # E: {int64}
reveal_type(f8 % i4) # E: {float64}
reveal_type(i4 % i4) # E: {int32}
reveal_type(f4 % i4) # E: {float32}
reveal_type(AR % i8) # E: Any
reveal_type(divmod(b, i8)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(i, i8)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(f, i8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i8, i8)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(f8, i8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i4, i8)) # E: Tuple[{int64}, {int64}]
reveal_type(divmod(f4, i8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i4, i4)) # E: Tuple[{int32}, {int32}]
reveal_type(divmod(f4, i4)) # E: Tuple[{float32}, {float32}]
reveal_type(divmod(AR, i8)) # E: Tuple[Any, Any]
# float
reveal_type(f8 % b) # E: {float64}
reveal_type(f8 % i) # E: {float64}
reveal_type(f8 % f) # E: {float64}
reveal_type(i8 % f4) # E: {float64}
reveal_type(f4 % f4) # E: {float32}
reveal_type(f8 % AR) # E: Any
reveal_type(divmod(f8, b)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f8, i)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f8, f)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f8, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f8, f4)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f4, f4)) # E: Tuple[{float32}, {float32}]
reveal_type(divmod(f8, AR)) # E: Tuple[Any, Any]
reveal_type(b % f8) # E: {float64}
reveal_type(i % f8) # E: {float64}
reveal_type(f % f8) # E: {float64}
reveal_type(f8 % f8) # E: {float64}
reveal_type(f8 % f8) # E: {float64}
reveal_type(f4 % f4) # E: {float32}
reveal_type(AR % f8) # E: Any
reveal_type(divmod(b, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(i, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f8, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f4, f8)) # E: Tuple[{float64}, {float64}]
reveal_type(divmod(f4, f4)) # E: Tuple[{float32}, {float32}]
reveal_type(divmod(AR, f8)) # E: Tuple[Any, Any]
| 35.366667
| 67
| 0.633176
| 854
| 5,305
| 3.757611
| 0.050351
| 0.327205
| 0.264257
| 0.124649
| 0.846993
| 0.776878
| 0.741352
| 0.712683
| 0.514802
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| 0
| 0.086656
| 0.153817
| 5,305
| 149
| 68
| 35.604027
| 0.628202
| 0.393402
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|
0
| 6
|
7f537a50a9d223ce9c2cc4fdbfb4848d26cff976
| 88
|
py
|
Python
|
backend/userInfoapp/views.py
|
Lenend-KPU/LBS-Platform
|
75ba24db8969248e74e9d974638977de1c0bc36a
|
[
"MIT"
] | 15
|
2020-12-23T13:56:49.000Z
|
2021-12-10T11:04:23.000Z
|
backend/pathapp/views.py
|
Lenend-KPU/LBS-Platform
|
75ba24db8969248e74e9d974638977de1c0bc36a
|
[
"MIT"
] | 41
|
2021-03-19T07:51:48.000Z
|
2021-11-22T09:45:46.000Z
|
backend/userInfoapp/views.py
|
Lenend-KPU/LBS-Platform
|
75ba24db8969248e74e9d974638977de1c0bc36a
|
[
"MIT"
] | 3
|
2021-03-24T15:18:24.000Z
|
2021-09-11T14:51:35.000Z
|
from django.views import View
# Create your views here.
class ChildView(View):
pass
| 17.6
| 29
| 0.75
| 13
| 88
| 5.076923
| 0.846154
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| 88
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|
0
| 6
|
7f8860b3b5c3a569f770680d164494165fd89ad5
| 6,407
|
py
|
Python
|
loldib/getratings/models/NA/na_vayne/na_vayne_jng.py
|
koliupy/loldib
|
c9ab94deb07213cdc42b5a7c26467cdafaf81b7f
|
[
"Apache-2.0"
] | null | null | null |
loldib/getratings/models/NA/na_vayne/na_vayne_jng.py
|
koliupy/loldib
|
c9ab94deb07213cdc42b5a7c26467cdafaf81b7f
|
[
"Apache-2.0"
] | null | null | null |
loldib/getratings/models/NA/na_vayne/na_vayne_jng.py
|
koliupy/loldib
|
c9ab94deb07213cdc42b5a7c26467cdafaf81b7f
|
[
"Apache-2.0"
] | null | null | null |
from getratings.models.ratings import Ratings
class NA_Vayne_Jng_Aatrox(Ratings):
pass
class NA_Vayne_Jng_Ahri(Ratings):
pass
class NA_Vayne_Jng_Akali(Ratings):
pass
class NA_Vayne_Jng_Alistar(Ratings):
pass
class NA_Vayne_Jng_Amumu(Ratings):
pass
class NA_Vayne_Jng_Anivia(Ratings):
pass
class NA_Vayne_Jng_Annie(Ratings):
pass
class NA_Vayne_Jng_Ashe(Ratings):
pass
class NA_Vayne_Jng_AurelionSol(Ratings):
pass
class NA_Vayne_Jng_Azir(Ratings):
pass
class NA_Vayne_Jng_Bard(Ratings):
pass
class NA_Vayne_Jng_Blitzcrank(Ratings):
pass
class NA_Vayne_Jng_Brand(Ratings):
pass
class NA_Vayne_Jng_Braum(Ratings):
pass
class NA_Vayne_Jng_Caitlyn(Ratings):
pass
class NA_Vayne_Jng_Camille(Ratings):
pass
class NA_Vayne_Jng_Cassiopeia(Ratings):
pass
class NA_Vayne_Jng_Chogath(Ratings):
pass
class NA_Vayne_Jng_Corki(Ratings):
pass
class NA_Vayne_Jng_Darius(Ratings):
pass
class NA_Vayne_Jng_Diana(Ratings):
pass
class NA_Vayne_Jng_Draven(Ratings):
pass
class NA_Vayne_Jng_DrMundo(Ratings):
pass
class NA_Vayne_Jng_Ekko(Ratings):
pass
class NA_Vayne_Jng_Elise(Ratings):
pass
class NA_Vayne_Jng_Evelynn(Ratings):
pass
class NA_Vayne_Jng_Ezreal(Ratings):
pass
class NA_Vayne_Jng_Fiddlesticks(Ratings):
pass
class NA_Vayne_Jng_Fiora(Ratings):
pass
class NA_Vayne_Jng_Fizz(Ratings):
pass
class NA_Vayne_Jng_Galio(Ratings):
pass
class NA_Vayne_Jng_Gangplank(Ratings):
pass
class NA_Vayne_Jng_Garen(Ratings):
pass
class NA_Vayne_Jng_Gnar(Ratings):
pass
class NA_Vayne_Jng_Gragas(Ratings):
pass
class NA_Vayne_Jng_Graves(Ratings):
pass
class NA_Vayne_Jng_Hecarim(Ratings):
pass
class NA_Vayne_Jng_Heimerdinger(Ratings):
pass
class NA_Vayne_Jng_Illaoi(Ratings):
pass
class NA_Vayne_Jng_Irelia(Ratings):
pass
class NA_Vayne_Jng_Ivern(Ratings):
pass
class NA_Vayne_Jng_Janna(Ratings):
pass
class NA_Vayne_Jng_JarvanIV(Ratings):
pass
class NA_Vayne_Jng_Jax(Ratings):
pass
class NA_Vayne_Jng_Jayce(Ratings):
pass
class NA_Vayne_Jng_Jhin(Ratings):
pass
class NA_Vayne_Jng_Jinx(Ratings):
pass
class NA_Vayne_Jng_Kalista(Ratings):
pass
class NA_Vayne_Jng_Karma(Ratings):
pass
class NA_Vayne_Jng_Karthus(Ratings):
pass
class NA_Vayne_Jng_Kassadin(Ratings):
pass
class NA_Vayne_Jng_Katarina(Ratings):
pass
class NA_Vayne_Jng_Kayle(Ratings):
pass
class NA_Vayne_Jng_Kayn(Ratings):
pass
class NA_Vayne_Jng_Kennen(Ratings):
pass
class NA_Vayne_Jng_Khazix(Ratings):
pass
class NA_Vayne_Jng_Kindred(Ratings):
pass
class NA_Vayne_Jng_Kled(Ratings):
pass
class NA_Vayne_Jng_KogMaw(Ratings):
pass
class NA_Vayne_Jng_Leblanc(Ratings):
pass
class NA_Vayne_Jng_LeeSin(Ratings):
pass
class NA_Vayne_Jng_Leona(Ratings):
pass
class NA_Vayne_Jng_Lissandra(Ratings):
pass
class NA_Vayne_Jng_Lucian(Ratings):
pass
class NA_Vayne_Jng_Lulu(Ratings):
pass
class NA_Vayne_Jng_Lux(Ratings):
pass
class NA_Vayne_Jng_Malphite(Ratings):
pass
class NA_Vayne_Jng_Malzahar(Ratings):
pass
class NA_Vayne_Jng_Maokai(Ratings):
pass
class NA_Vayne_Jng_MasterYi(Ratings):
pass
class NA_Vayne_Jng_MissFortune(Ratings):
pass
class NA_Vayne_Jng_MonkeyKing(Ratings):
pass
class NA_Vayne_Jng_Mordekaiser(Ratings):
pass
class NA_Vayne_Jng_Morgana(Ratings):
pass
class NA_Vayne_Jng_Nami(Ratings):
pass
class NA_Vayne_Jng_Nasus(Ratings):
pass
class NA_Vayne_Jng_Nautilus(Ratings):
pass
class NA_Vayne_Jng_Nidalee(Ratings):
pass
class NA_Vayne_Jng_Nocturne(Ratings):
pass
class NA_Vayne_Jng_Nunu(Ratings):
pass
class NA_Vayne_Jng_Olaf(Ratings):
pass
class NA_Vayne_Jng_Orianna(Ratings):
pass
class NA_Vayne_Jng_Ornn(Ratings):
pass
class NA_Vayne_Jng_Pantheon(Ratings):
pass
class NA_Vayne_Jng_Poppy(Ratings):
pass
class NA_Vayne_Jng_Quinn(Ratings):
pass
class NA_Vayne_Jng_Rakan(Ratings):
pass
class NA_Vayne_Jng_Rammus(Ratings):
pass
class NA_Vayne_Jng_RekSai(Ratings):
pass
class NA_Vayne_Jng_Renekton(Ratings):
pass
class NA_Vayne_Jng_Rengar(Ratings):
pass
class NA_Vayne_Jng_Riven(Ratings):
pass
class NA_Vayne_Jng_Rumble(Ratings):
pass
class NA_Vayne_Jng_Ryze(Ratings):
pass
class NA_Vayne_Jng_Sejuani(Ratings):
pass
class NA_Vayne_Jng_Shaco(Ratings):
pass
class NA_Vayne_Jng_Shen(Ratings):
pass
class NA_Vayne_Jng_Shyvana(Ratings):
pass
class NA_Vayne_Jng_Singed(Ratings):
pass
class NA_Vayne_Jng_Sion(Ratings):
pass
class NA_Vayne_Jng_Sivir(Ratings):
pass
class NA_Vayne_Jng_Skarner(Ratings):
pass
class NA_Vayne_Jng_Sona(Ratings):
pass
class NA_Vayne_Jng_Soraka(Ratings):
pass
class NA_Vayne_Jng_Swain(Ratings):
pass
class NA_Vayne_Jng_Syndra(Ratings):
pass
class NA_Vayne_Jng_TahmKench(Ratings):
pass
class NA_Vayne_Jng_Taliyah(Ratings):
pass
class NA_Vayne_Jng_Talon(Ratings):
pass
class NA_Vayne_Jng_Taric(Ratings):
pass
class NA_Vayne_Jng_Teemo(Ratings):
pass
class NA_Vayne_Jng_Thresh(Ratings):
pass
class NA_Vayne_Jng_Tristana(Ratings):
pass
class NA_Vayne_Jng_Trundle(Ratings):
pass
class NA_Vayne_Jng_Tryndamere(Ratings):
pass
class NA_Vayne_Jng_TwistedFate(Ratings):
pass
class NA_Vayne_Jng_Twitch(Ratings):
pass
class NA_Vayne_Jng_Udyr(Ratings):
pass
class NA_Vayne_Jng_Urgot(Ratings):
pass
class NA_Vayne_Jng_Varus(Ratings):
pass
class NA_Vayne_Jng_Vayne(Ratings):
pass
class NA_Vayne_Jng_Veigar(Ratings):
pass
class NA_Vayne_Jng_Velkoz(Ratings):
pass
class NA_Vayne_Jng_Vi(Ratings):
pass
class NA_Vayne_Jng_Viktor(Ratings):
pass
class NA_Vayne_Jng_Vladimir(Ratings):
pass
class NA_Vayne_Jng_Volibear(Ratings):
pass
class NA_Vayne_Jng_Warwick(Ratings):
pass
class NA_Vayne_Jng_Xayah(Ratings):
pass
class NA_Vayne_Jng_Xerath(Ratings):
pass
class NA_Vayne_Jng_XinZhao(Ratings):
pass
class NA_Vayne_Jng_Yasuo(Ratings):
pass
class NA_Vayne_Jng_Yorick(Ratings):
pass
class NA_Vayne_Jng_Zac(Ratings):
pass
class NA_Vayne_Jng_Zed(Ratings):
pass
class NA_Vayne_Jng_Ziggs(Ratings):
pass
class NA_Vayne_Jng_Zilean(Ratings):
pass
class NA_Vayne_Jng_Zyra(Ratings):
pass
| 15.364508
| 46
| 0.761667
| 972
| 6,407
| 4.59465
| 0.151235
| 0.216301
| 0.370802
| 0.463502
| 0.797582
| 0.797582
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173404
| 6,407
| 416
| 47
| 15.401442
| 0.843278
| 0
| 0
| 0.498195
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.498195
| 0.00361
| 0
| 0.501805
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
7f915715fe66743bb111674c19dd3a0c33310f41
| 163
|
py
|
Python
|
aiofcm/__init__.py
|
cyberbudy/aiofcm
|
30e66b872aa2e1fc43ef4884fb84ba23b91879c5
|
[
"Apache-2.0"
] | 30
|
2017-05-11T08:21:45.000Z
|
2021-11-20T13:52:13.000Z
|
aiofcm/__init__.py
|
cyberbudy/aiofcm
|
30e66b872aa2e1fc43ef4884fb84ba23b91879c5
|
[
"Apache-2.0"
] | 12
|
2017-05-22T16:42:03.000Z
|
2021-08-09T11:11:47.000Z
|
aiofcm/__init__.py
|
cyberbudy/aiofcm
|
30e66b872aa2e1fc43ef4884fb84ba23b91879c5
|
[
"Apache-2.0"
] | 16
|
2017-05-22T11:30:55.000Z
|
2021-11-11T09:48:04.000Z
|
from aiofcm.client import FCM
from aiofcm.common import Message, PRIORITY_NORMAL, PRIORITY_HIGH
__all__ = ['FCM', 'Message', 'PRIORITY_NORMAL', 'PRIORITY_HIGH']
| 27.166667
| 65
| 0.779141
| 21
| 163
| 5.666667
| 0.52381
| 0.168067
| 0.352941
| 0.487395
| 0.554622
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.110429
| 163
| 5
| 66
| 32.6
| 0.82069
| 0
| 0
| 0
| 0
| 0
| 0.233129
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
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| null | 0
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| 1
| 0
| 1
| 0
|
0
| 6
|
7fa6531f44c6da1b189fb62f02e9884de99fadd4
| 223
|
py
|
Python
|
ClassCode/P2/Fibonacci.py
|
tsyet12/ClassCode
|
db1db97f71a6f31769d58739c6687863bc6b88c4
|
[
"MIT"
] | null | null | null |
ClassCode/P2/Fibonacci.py
|
tsyet12/ClassCode
|
db1db97f71a6f31769d58739c6687863bc6b88c4
|
[
"MIT"
] | null | null | null |
ClassCode/P2/Fibonacci.py
|
tsyet12/ClassCode
|
db1db97f71a6f31769d58739c6687863bc6b88c4
|
[
"MIT"
] | null | null | null |
x=[1,1]
for i in range(1000):
x=x+[x[-1]+x[-2]]
#iteration 1
#x=[1,1]+[1+1]
#x=[1,1]+[2]
#x=[1,1,2]
#iteration 2
#x=[1,1,2]+[1+2]
#x=[1,1,2]+[3]
#x=[1,1,2,3]
print(x)
print(x[-1]/x[-2])
| 14.866667
| 21
| 0.394619
| 54
| 223
| 1.62963
| 0.203704
| 0.204545
| 0.238636
| 0.227273
| 0.261364
| 0.136364
| 0
| 0
| 0
| 0
| 0
| 0.208333
| 0.246637
| 223
| 15
| 22
| 14.866667
| 0.315476
| 0.421525
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| 1
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| 0
| 0
| 0
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| 1
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| null | 0
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
f692fd1b43eeb593458fc65f18cac184d7b6b190
| 28
|
py
|
Python
|
ir-exportq/__init__.py
|
culibraries/ir-exportq
|
4c9d10b94a5218d77324aeb30374de0be99aba9b
|
[
"BSD-4-Clause-UC"
] | null | null | null |
ir-exportq/__init__.py
|
culibraries/ir-exportq
|
4c9d10b94a5218d77324aeb30374de0be99aba9b
|
[
"BSD-4-Clause-UC"
] | null | null | null |
ir-exportq/__init__.py
|
culibraries/ir-exportq
|
4c9d10b94a5218d77324aeb30374de0be99aba9b
|
[
"BSD-4-Clause-UC"
] | null | null | null |
from .tasks import __init__
| 14
| 27
| 0.821429
| 4
| 28
| 4.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 28
| 1
| 28
| 28
| 0.791667
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 0
| null | 0
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| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
121cf698dfa749a5ee412ec8949d07af929f5dcf
| 43
|
py
|
Python
|
app/tgbot/handlers/chief/__init__.py
|
AnViSe/cost_confirmation_bot
|
f8eaa39c3df742bef0fc79b8b7ce0231f1b18749
|
[
"MIT"
] | 13
|
2021-12-27T19:46:19.000Z
|
2022-03-19T07:55:25.000Z
|
app/tgbot/handlers/chief/__init__.py
|
AnViSe/cost_confirmation_bot
|
f8eaa39c3df742bef0fc79b8b7ce0231f1b18749
|
[
"MIT"
] | null | null | null |
app/tgbot/handlers/chief/__init__.py
|
AnViSe/cost_confirmation_bot
|
f8eaa39c3df742bef0fc79b8b7ce0231f1b18749
|
[
"MIT"
] | 1
|
2022-02-07T10:48:18.000Z
|
2022-02-07T10:48:18.000Z
|
from .setup import register_chief_handlers
| 21.5
| 42
| 0.883721
| 6
| 43
| 6
| 1
| 0
| 0
| 0
| 0
| 0
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| 0.093023
| 43
| 1
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| 43
| 0.923077
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| true
| 0
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| null | 0
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| null | 0
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
89c06dd9ba2f8ed621e121122736d0a47703f0c1
| 704
|
py
|
Python
|
HW2/tests/q1.1.py
|
ds-modules/EPS-130-SP21
|
783f244145877ad97c0eafde26024310adab55f5
|
[
"BSD-3-Clause"
] | 1
|
2021-01-21T17:00:16.000Z
|
2021-01-21T17:00:16.000Z
|
HW2/tests/q1.1.py
|
ds-modules/EPS-130-SP21
|
783f244145877ad97c0eafde26024310adab55f5
|
[
"BSD-3-Clause"
] | null | null | null |
HW2/tests/q1.1.py
|
ds-modules/EPS-130-SP21
|
783f244145877ad97c0eafde26024310adab55f5
|
[
"BSD-3-Clause"
] | null | null | null |
test = { 'name': 'q1.1',
'points': 1,
'suites': [ { 'cases': [ { 'code': '>>> assert abs(P[0] - 0.003819) < .1*0.003819;\n'
'>>> assert abs(P[1] - 0.016803) < .1*0.016803;\n'
'>>> assert abs(P[2] - 0.180881) < .1*0.180881;\n'
'>>> assert abs(P[3] - 0.631248) < .1*0.631248\n',
'hidden': False,
'locked': False}],
'scored': True,
'setup': '',
'teardown': '',
'type': 'doctest'}]}
| 54.153846
| 97
| 0.27983
| 59
| 704
| 3.338983
| 0.474576
| 0.050761
| 0.203046
| 0.167513
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206154
| 0.538352
| 704
| 12
| 98
| 58.666667
| 0.4
| 0
| 0
| 0
| 0
| 0.333333
| 0.372159
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0
| false
| 0
| 0
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| 0
| 0
| null | 0
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| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
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| 1
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
89f7f546d42d075bc8a286cde7890bbb0007aaf9
| 25
|
py
|
Python
|
core/src/autogluon/core/task/base/__init__.py
|
daobook/autogluon
|
7309118f2ab1c9519f25acf61a283a95af95842b
|
[
"Apache-2.0"
] | 1
|
2022-02-19T13:22:26.000Z
|
2022-02-19T13:22:26.000Z
|
core/src/autogluon/core/task/base/__init__.py
|
daobook/autogluon
|
7309118f2ab1c9519f25acf61a283a95af95842b
|
[
"Apache-2.0"
] | 3
|
2021-12-30T20:28:01.000Z
|
2022-02-09T20:19:21.000Z
|
core/src/autogluon/core/task/base/__init__.py
|
daobook/autogluon
|
7309118f2ab1c9519f25acf61a283a95af95842b
|
[
"Apache-2.0"
] | null | null | null |
from .base_task import *
| 12.5
| 24
| 0.76
| 4
| 25
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16
| 25
| 1
| 25
| 25
| 0.857143
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| true
| 0
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| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
89fb948813aeedbcd41ba14ca13981e5f427a7da
| 33,046
|
py
|
Python
|
terra_sdk/protobuf/ibc/core/channel/v1/channel_pb2.py
|
sejalsahni/terra.py
|
0fd84969441c58427a21448520697c3ab3ec2d0c
|
[
"MIT"
] | 24
|
2021-05-30T05:48:33.000Z
|
2021-10-07T04:47:15.000Z
|
terra_sdk/protobuf/ibc/core/channel/v1/channel_pb2.py
|
sejalsahni/terra.py
|
0fd84969441c58427a21448520697c3ab3ec2d0c
|
[
"MIT"
] | 18
|
2021-05-30T09:05:26.000Z
|
2021-10-17T07:12:12.000Z
|
terra_sdk/protobuf/ibc/core/channel/v1/channel_pb2.py
|
sejalsahni/terra.py
|
0fd84969441c58427a21448520697c3ab3ec2d0c
|
[
"MIT"
] | 10
|
2021-02-11T00:56:04.000Z
|
2021-05-27T08:37:49.000Z
|
# -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: ibc/core/channel/v1/channel.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import enum_type_wrapper
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from gogoproto import gogo_pb2 as gogoproto_dot_gogo__pb2
from ibc.core.client.v1 import (
client_pb2 as ibc_dot_core_dot_client_dot_v1_dot_client__pb2,
)
DESCRIPTOR = _descriptor.FileDescriptor(
name="ibc/core/channel/v1/channel.proto",
package="ibc.core.channel.v1",
syntax="proto3",
serialized_options=b"Z6github.com/cosmos/ibc-go/modules/core/04-channel/types",
create_key=_descriptor._internal_create_key,
serialized_pb=b'\n!ibc/core/channel/v1/channel.proto\x12\x13ibc.core.channel.v1\x1a\x14gogoproto/gogo.proto\x1a\x1fibc/core/client/v1/client.proto"\xed\x01\n\x07\x43hannel\x12)\n\x05state\x18\x01 \x01(\x0e\x32\x1a.ibc.core.channel.v1.State\x12,\n\x08ordering\x18\x02 \x01(\x0e\x32\x1a.ibc.core.channel.v1.Order\x12=\n\x0c\x63ounterparty\x18\x03 \x01(\x0b\x32!.ibc.core.channel.v1.CounterpartyB\x04\xc8\xde\x1f\x00\x12\x33\n\x0f\x63onnection_hops\x18\x04 \x03(\tB\x1a\xf2\xde\x1f\x16yaml:"connection_hops"\x12\x0f\n\x07version\x18\x05 \x01(\t:\x04\x88\xa0\x1f\x00"\x9c\x02\n\x11IdentifiedChannel\x12)\n\x05state\x18\x01 \x01(\x0e\x32\x1a.ibc.core.channel.v1.State\x12,\n\x08ordering\x18\x02 \x01(\x0e\x32\x1a.ibc.core.channel.v1.Order\x12=\n\x0c\x63ounterparty\x18\x03 \x01(\x0b\x32!.ibc.core.channel.v1.CounterpartyB\x04\xc8\xde\x1f\x00\x12\x33\n\x0f\x63onnection_hops\x18\x04 \x03(\tB\x1a\xf2\xde\x1f\x16yaml:"connection_hops"\x12\x0f\n\x07version\x18\x05 \x01(\t\x12\x0f\n\x07port_id\x18\x06 \x01(\t\x12\x12\n\nchannel_id\x18\x07 \x01(\t:\x04\x88\xa0\x1f\x00"d\n\x0c\x43ounterparty\x12#\n\x07port_id\x18\x01 \x01(\tB\x12\xf2\xde\x1f\x0eyaml:"port_id"\x12)\n\nchannel_id\x18\x02 \x01(\tB\x15\xf2\xde\x1f\x11yaml:"channel_id":\x04\x88\xa0\x1f\x00"\x8e\x03\n\x06Packet\x12\x10\n\x08sequence\x18\x01 \x01(\x04\x12+\n\x0bsource_port\x18\x02 \x01(\tB\x16\xf2\xde\x1f\x12yaml:"source_port"\x12\x31\n\x0esource_channel\x18\x03 \x01(\tB\x19\xf2\xde\x1f\x15yaml:"source_channel"\x12\x35\n\x10\x64\x65stination_port\x18\x04 \x01(\tB\x1b\xf2\xde\x1f\x17yaml:"destination_port"\x12;\n\x13\x64\x65stination_channel\x18\x05 \x01(\tB\x1e\xf2\xde\x1f\x1ayaml:"destination_channel"\x12\x0c\n\x04\x64\x61ta\x18\x06 \x01(\x0c\x12Q\n\x0etimeout_height\x18\x07 \x01(\x0b\x32\x1a.ibc.core.client.v1.HeightB\x1d\xf2\xde\x1f\x15yaml:"timeout_height"\xc8\xde\x1f\x00\x12\x37\n\x11timeout_timestamp\x18\x08 \x01(\x04\x42\x1c\xf2\xde\x1f\x18yaml:"timeout_timestamp":\x04\x88\xa0\x1f\x00"\x83\x01\n\x0bPacketState\x12#\n\x07port_id\x18\x01 \x01(\tB\x12\xf2\xde\x1f\x0eyaml:"port_id"\x12)\n\nchannel_id\x18\x02 \x01(\tB\x15\xf2\xde\x1f\x11yaml:"channel_id"\x12\x10\n\x08sequence\x18\x03 \x01(\x04\x12\x0c\n\x04\x64\x61ta\x18\x04 \x01(\x0c:\x04\x88\xa0\x1f\x00"@\n\x0f\x41\x63knowledgement\x12\x10\n\x06result\x18\x15 \x01(\x0cH\x00\x12\x0f\n\x05\x65rror\x18\x16 \x01(\tH\x00\x42\n\n\x08response*\xb7\x01\n\x05State\x12\x36\n\x1fSTATE_UNINITIALIZED_UNSPECIFIED\x10\x00\x1a\x11\x8a\x9d \rUNINITIALIZED\x12\x18\n\nSTATE_INIT\x10\x01\x1a\x08\x8a\x9d \x04INIT\x12\x1e\n\rSTATE_TRYOPEN\x10\x02\x1a\x0b\x8a\x9d \x07TRYOPEN\x12\x18\n\nSTATE_OPEN\x10\x03\x1a\x08\x8a\x9d \x04OPEN\x12\x1c\n\x0cSTATE_CLOSED\x10\x04\x1a\n\x8a\x9d \x06\x43LOSED\x1a\x04\x88\xa3\x1e\x00*w\n\x05Order\x12$\n\x16ORDER_NONE_UNSPECIFIED\x10\x00\x1a\x08\x8a\x9d \x04NONE\x12"\n\x0fORDER_UNORDERED\x10\x01\x1a\r\x8a\x9d \tUNORDERED\x12\x1e\n\rORDER_ORDERED\x10\x02\x1a\x0b\x8a\x9d \x07ORDERED\x1a\x04\x88\xa3\x1e\x00\x42\x38Z6github.com/cosmos/ibc-go/modules/core/04-channel/typesb\x06proto3',
dependencies=[
gogoproto_dot_gogo__pb2.DESCRIPTOR,
ibc_dot_core_dot_client_dot_v1_dot_client__pb2.DESCRIPTOR,
],
)
_STATE = _descriptor.EnumDescriptor(
name="State",
full_name="ibc.core.channel.v1.State",
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name="STATE_UNINITIALIZED_UNSPECIFIED",
index=0,
number=0,
serialized_options=b"\212\235 \rUNINITIALIZED",
type=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.EnumValueDescriptor(
name="STATE_INIT",
index=1,
number=1,
serialized_options=b"\212\235 \004INIT",
type=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.EnumValueDescriptor(
name="STATE_TRYOPEN",
index=2,
number=2,
serialized_options=b"\212\235 \007TRYOPEN",
type=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.EnumValueDescriptor(
name="STATE_OPEN",
index=3,
number=3,
serialized_options=b"\212\235 \004OPEN",
type=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.EnumValueDescriptor(
name="STATE_CLOSED",
index=4,
number=4,
serialized_options=b"\212\235 \006CLOSED",
type=None,
create_key=_descriptor._internal_create_key,
),
],
containing_type=None,
serialized_options=b"\210\243\036\000",
serialized_start=1344,
serialized_end=1527,
)
_sym_db.RegisterEnumDescriptor(_STATE)
State = enum_type_wrapper.EnumTypeWrapper(_STATE)
_ORDER = _descriptor.EnumDescriptor(
name="Order",
full_name="ibc.core.channel.v1.Order",
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name="ORDER_NONE_UNSPECIFIED",
index=0,
number=0,
serialized_options=b"\212\235 \004NONE",
type=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.EnumValueDescriptor(
name="ORDER_UNORDERED",
index=1,
number=1,
serialized_options=b"\212\235 \tUNORDERED",
type=None,
create_key=_descriptor._internal_create_key,
),
_descriptor.EnumValueDescriptor(
name="ORDER_ORDERED",
index=2,
number=2,
serialized_options=b"\212\235 \007ORDERED",
type=None,
create_key=_descriptor._internal_create_key,
),
],
containing_type=None,
serialized_options=b"\210\243\036\000",
serialized_start=1529,
serialized_end=1648,
)
_sym_db.RegisterEnumDescriptor(_ORDER)
Order = enum_type_wrapper.EnumTypeWrapper(_ORDER)
STATE_UNINITIALIZED_UNSPECIFIED = 0
STATE_INIT = 1
STATE_TRYOPEN = 2
STATE_OPEN = 3
STATE_CLOSED = 4
ORDER_NONE_UNSPECIFIED = 0
ORDER_UNORDERED = 1
ORDER_ORDERED = 2
_CHANNEL = _descriptor.Descriptor(
name="Channel",
full_name="ibc.core.channel.v1.Channel",
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name="state",
full_name="ibc.core.channel.v1.Channel.state",
index=0,
number=1,
type=14,
cpp_type=8,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="ordering",
full_name="ibc.core.channel.v1.Channel.ordering",
index=1,
number=2,
type=14,
cpp_type=8,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="counterparty",
full_name="ibc.core.channel.v1.Channel.counterparty",
index=2,
number=3,
type=11,
cpp_type=10,
label=1,
has_default_value=False,
default_value=None,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b"\310\336\037\000",
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="connection_hops",
full_name="ibc.core.channel.v1.Channel.connection_hops",
index=3,
number=4,
type=9,
cpp_type=9,
label=3,
has_default_value=False,
default_value=[],
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\026yaml:"connection_hops"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="version",
full_name="ibc.core.channel.v1.Channel.version",
index=4,
number=5,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=b"\210\240\037\000",
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=114,
serialized_end=351,
)
_IDENTIFIEDCHANNEL = _descriptor.Descriptor(
name="IdentifiedChannel",
full_name="ibc.core.channel.v1.IdentifiedChannel",
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name="state",
full_name="ibc.core.channel.v1.IdentifiedChannel.state",
index=0,
number=1,
type=14,
cpp_type=8,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="ordering",
full_name="ibc.core.channel.v1.IdentifiedChannel.ordering",
index=1,
number=2,
type=14,
cpp_type=8,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="counterparty",
full_name="ibc.core.channel.v1.IdentifiedChannel.counterparty",
index=2,
number=3,
type=11,
cpp_type=10,
label=1,
has_default_value=False,
default_value=None,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b"\310\336\037\000",
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="connection_hops",
full_name="ibc.core.channel.v1.IdentifiedChannel.connection_hops",
index=3,
number=4,
type=9,
cpp_type=9,
label=3,
has_default_value=False,
default_value=[],
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\026yaml:"connection_hops"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="version",
full_name="ibc.core.channel.v1.IdentifiedChannel.version",
index=4,
number=5,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="port_id",
full_name="ibc.core.channel.v1.IdentifiedChannel.port_id",
index=5,
number=6,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="channel_id",
full_name="ibc.core.channel.v1.IdentifiedChannel.channel_id",
index=6,
number=7,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=b"\210\240\037\000",
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=354,
serialized_end=638,
)
_COUNTERPARTY = _descriptor.Descriptor(
name="Counterparty",
full_name="ibc.core.channel.v1.Counterparty",
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name="port_id",
full_name="ibc.core.channel.v1.Counterparty.port_id",
index=0,
number=1,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\016yaml:"port_id"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="channel_id",
full_name="ibc.core.channel.v1.Counterparty.channel_id",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\021yaml:"channel_id"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=b"\210\240\037\000",
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=640,
serialized_end=740,
)
_PACKET = _descriptor.Descriptor(
name="Packet",
full_name="ibc.core.channel.v1.Packet",
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name="sequence",
full_name="ibc.core.channel.v1.Packet.sequence",
index=0,
number=1,
type=4,
cpp_type=4,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="source_port",
full_name="ibc.core.channel.v1.Packet.source_port",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\022yaml:"source_port"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="source_channel",
full_name="ibc.core.channel.v1.Packet.source_channel",
index=2,
number=3,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\025yaml:"source_channel"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="destination_port",
full_name="ibc.core.channel.v1.Packet.destination_port",
index=3,
number=4,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\027yaml:"destination_port"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="destination_channel",
full_name="ibc.core.channel.v1.Packet.destination_channel",
index=4,
number=5,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\032yaml:"destination_channel"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="data",
full_name="ibc.core.channel.v1.Packet.data",
index=5,
number=6,
type=12,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"",
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="timeout_height",
full_name="ibc.core.channel.v1.Packet.timeout_height",
index=6,
number=7,
type=11,
cpp_type=10,
label=1,
has_default_value=False,
default_value=None,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\025yaml:"timeout_height"\310\336\037\000',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="timeout_timestamp",
full_name="ibc.core.channel.v1.Packet.timeout_timestamp",
index=7,
number=8,
type=4,
cpp_type=4,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\030yaml:"timeout_timestamp"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=b"\210\240\037\000",
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=743,
serialized_end=1141,
)
_PACKETSTATE = _descriptor.Descriptor(
name="PacketState",
full_name="ibc.core.channel.v1.PacketState",
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name="port_id",
full_name="ibc.core.channel.v1.PacketState.port_id",
index=0,
number=1,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\016yaml:"port_id"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="channel_id",
full_name="ibc.core.channel.v1.PacketState.channel_id",
index=1,
number=2,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=b'\362\336\037\021yaml:"channel_id"',
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="sequence",
full_name="ibc.core.channel.v1.PacketState.sequence",
index=2,
number=3,
type=4,
cpp_type=4,
label=1,
has_default_value=False,
default_value=0,
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="data",
full_name="ibc.core.channel.v1.PacketState.data",
index=3,
number=4,
type=12,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"",
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=b"\210\240\037\000",
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[],
serialized_start=1144,
serialized_end=1275,
)
_ACKNOWLEDGEMENT = _descriptor.Descriptor(
name="Acknowledgement",
full_name="ibc.core.channel.v1.Acknowledgement",
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name="result",
full_name="ibc.core.channel.v1.Acknowledgement.result",
index=0,
number=21,
type=12,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"",
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
_descriptor.FieldDescriptor(
name="error",
full_name="ibc.core.channel.v1.Acknowledgement.error",
index=1,
number=22,
type=9,
cpp_type=9,
label=1,
has_default_value=False,
default_value=b"".decode("utf-8"),
message_type=None,
enum_type=None,
containing_type=None,
is_extension=False,
extension_scope=None,
serialized_options=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
),
],
extensions=[],
nested_types=[],
enum_types=[],
serialized_options=None,
is_extendable=False,
syntax="proto3",
extension_ranges=[],
oneofs=[
_descriptor.OneofDescriptor(
name="response",
full_name="ibc.core.channel.v1.Acknowledgement.response",
index=0,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[],
),
],
serialized_start=1277,
serialized_end=1341,
)
_CHANNEL.fields_by_name["state"].enum_type = _STATE
_CHANNEL.fields_by_name["ordering"].enum_type = _ORDER
_CHANNEL.fields_by_name["counterparty"].message_type = _COUNTERPARTY
_IDENTIFIEDCHANNEL.fields_by_name["state"].enum_type = _STATE
_IDENTIFIEDCHANNEL.fields_by_name["ordering"].enum_type = _ORDER
_IDENTIFIEDCHANNEL.fields_by_name["counterparty"].message_type = _COUNTERPARTY
_PACKET.fields_by_name[
"timeout_height"
].message_type = ibc_dot_core_dot_client_dot_v1_dot_client__pb2._HEIGHT
_ACKNOWLEDGEMENT.oneofs_by_name["response"].fields.append(
_ACKNOWLEDGEMENT.fields_by_name["result"]
)
_ACKNOWLEDGEMENT.fields_by_name[
"result"
].containing_oneof = _ACKNOWLEDGEMENT.oneofs_by_name["response"]
_ACKNOWLEDGEMENT.oneofs_by_name["response"].fields.append(
_ACKNOWLEDGEMENT.fields_by_name["error"]
)
_ACKNOWLEDGEMENT.fields_by_name[
"error"
].containing_oneof = _ACKNOWLEDGEMENT.oneofs_by_name["response"]
DESCRIPTOR.message_types_by_name["Channel"] = _CHANNEL
DESCRIPTOR.message_types_by_name["IdentifiedChannel"] = _IDENTIFIEDCHANNEL
DESCRIPTOR.message_types_by_name["Counterparty"] = _COUNTERPARTY
DESCRIPTOR.message_types_by_name["Packet"] = _PACKET
DESCRIPTOR.message_types_by_name["PacketState"] = _PACKETSTATE
DESCRIPTOR.message_types_by_name["Acknowledgement"] = _ACKNOWLEDGEMENT
DESCRIPTOR.enum_types_by_name["State"] = _STATE
DESCRIPTOR.enum_types_by_name["Order"] = _ORDER
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
Channel = _reflection.GeneratedProtocolMessageType(
"Channel",
(_message.Message,),
{
"DESCRIPTOR": _CHANNEL,
"__module__": "ibc.core.channel.v1.channel_pb2"
# @@protoc_insertion_point(class_scope:ibc.core.channel.v1.Channel)
},
)
_sym_db.RegisterMessage(Channel)
IdentifiedChannel = _reflection.GeneratedProtocolMessageType(
"IdentifiedChannel",
(_message.Message,),
{
"DESCRIPTOR": _IDENTIFIEDCHANNEL,
"__module__": "ibc.core.channel.v1.channel_pb2"
# @@protoc_insertion_point(class_scope:ibc.core.channel.v1.IdentifiedChannel)
},
)
_sym_db.RegisterMessage(IdentifiedChannel)
Counterparty = _reflection.GeneratedProtocolMessageType(
"Counterparty",
(_message.Message,),
{
"DESCRIPTOR": _COUNTERPARTY,
"__module__": "ibc.core.channel.v1.channel_pb2"
# @@protoc_insertion_point(class_scope:ibc.core.channel.v1.Counterparty)
},
)
_sym_db.RegisterMessage(Counterparty)
Packet = _reflection.GeneratedProtocolMessageType(
"Packet",
(_message.Message,),
{
"DESCRIPTOR": _PACKET,
"__module__": "ibc.core.channel.v1.channel_pb2"
# @@protoc_insertion_point(class_scope:ibc.core.channel.v1.Packet)
},
)
_sym_db.RegisterMessage(Packet)
PacketState = _reflection.GeneratedProtocolMessageType(
"PacketState",
(_message.Message,),
{
"DESCRIPTOR": _PACKETSTATE,
"__module__": "ibc.core.channel.v1.channel_pb2"
# @@protoc_insertion_point(class_scope:ibc.core.channel.v1.PacketState)
},
)
_sym_db.RegisterMessage(PacketState)
Acknowledgement = _reflection.GeneratedProtocolMessageType(
"Acknowledgement",
(_message.Message,),
{
"DESCRIPTOR": _ACKNOWLEDGEMENT,
"__module__": "ibc.core.channel.v1.channel_pb2"
# @@protoc_insertion_point(class_scope:ibc.core.channel.v1.Acknowledgement)
},
)
_sym_db.RegisterMessage(Acknowledgement)
DESCRIPTOR._options = None
_STATE._options = None
_STATE.values_by_name["STATE_UNINITIALIZED_UNSPECIFIED"]._options = None
_STATE.values_by_name["STATE_INIT"]._options = None
_STATE.values_by_name["STATE_TRYOPEN"]._options = None
_STATE.values_by_name["STATE_OPEN"]._options = None
_STATE.values_by_name["STATE_CLOSED"]._options = None
_ORDER._options = None
_ORDER.values_by_name["ORDER_NONE_UNSPECIFIED"]._options = None
_ORDER.values_by_name["ORDER_UNORDERED"]._options = None
_ORDER.values_by_name["ORDER_ORDERED"]._options = None
_CHANNEL.fields_by_name["counterparty"]._options = None
_CHANNEL.fields_by_name["connection_hops"]._options = None
_CHANNEL._options = None
_IDENTIFIEDCHANNEL.fields_by_name["counterparty"]._options = None
_IDENTIFIEDCHANNEL.fields_by_name["connection_hops"]._options = None
_IDENTIFIEDCHANNEL._options = None
_COUNTERPARTY.fields_by_name["port_id"]._options = None
_COUNTERPARTY.fields_by_name["channel_id"]._options = None
_COUNTERPARTY._options = None
_PACKET.fields_by_name["source_port"]._options = None
_PACKET.fields_by_name["source_channel"]._options = None
_PACKET.fields_by_name["destination_port"]._options = None
_PACKET.fields_by_name["destination_channel"]._options = None
_PACKET.fields_by_name["timeout_height"]._options = None
_PACKET.fields_by_name["timeout_timestamp"]._options = None
_PACKET._options = None
_PACKETSTATE.fields_by_name["port_id"]._options = None
_PACKETSTATE.fields_by_name["channel_id"]._options = None
_PACKETSTATE._options = None
# @@protoc_insertion_point(module_scope)
| 35.11796
| 3,033
| 0.618713
| 3,659
| 33,046
| 5.278491
| 0.082263
| 0.041835
| 0.072797
| 0.048876
| 0.777622
| 0.743088
| 0.719012
| 0.637931
| 0.610956
| 0.603293
| 0
| 0.055745
| 0.272045
| 33,046
| 940
| 3,034
| 35.155319
| 0.747132
| 0.019609
| 0
| 0.730812
| 1
| 0.001112
| 0.209067
| 0.161942
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.007786
| 0
| 0.007786
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
d653eab941fc274e3def185109a52209d3a7d6f5
| 107
|
py
|
Python
|
pyramda/relation/min.py
|
sergiors/pyramda
|
5bf200888809b1bc946e813e29460f204bccd13e
|
[
"MIT"
] | 124
|
2015-07-30T21:34:25.000Z
|
2022-02-19T08:45:50.000Z
|
pyramda/relation/min.py
|
sergiors/pyramda
|
5bf200888809b1bc946e813e29460f204bccd13e
|
[
"MIT"
] | 37
|
2015-08-31T23:02:20.000Z
|
2022-02-04T04:45:28.000Z
|
pyramda/relation/min.py
|
sergiors/pyramda
|
5bf200888809b1bc946e813e29460f204bccd13e
|
[
"MIT"
] | 20
|
2015-08-04T18:59:09.000Z
|
2021-12-13T08:08:59.000Z
|
from pyramda.function.curry import curry
import builtins
@curry
def min(xs):
return builtins.min(xs)
| 13.375
| 40
| 0.757009
| 16
| 107
| 5.0625
| 0.625
| 0.271605
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.158879
| 107
| 7
| 41
| 15.285714
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.4
| 0.2
| 0.8
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
c38d4ba88dec3a6cf1435946f4281d6d8b305e6b
| 925
|
py
|
Python
|
preprocessing/signal1D/filter_RLC.py
|
erickfmm/ML-experiments
|
b1e81b8eea976efeda6e4dc70af747628a6eb43a
|
[
"MIT"
] | null | null | null |
preprocessing/signal1D/filter_RLC.py
|
erickfmm/ML-experiments
|
b1e81b8eea976efeda6e4dc70af747628a6eb43a
|
[
"MIT"
] | null | null | null |
preprocessing/signal1D/filter_RLC.py
|
erickfmm/ML-experiments
|
b1e81b8eea976efeda6e4dc70af747628a6eb43a
|
[
"MIT"
] | null | null | null |
import math
def LC_lowpass(input: list, sample_rate: int, frequency: float, Q: float):
O : float = float(2.0 * math.pi * frequency) / float(sample_rate)
C : float = Q / O
L : float = 1.0 / Q / O
V : float = 0.0
I : float = 0.0
T : float = 0.0
output : list = list()
for element in input:
T = float(I-V) / float(C)
I += float(element * O - V) / L
V += T
output.append(float(V)/float(O))
return output
def LC_highpass(input: list, sample_rate: int, frequency: float, Q: float):
O : float = float(2.0 * math.pi * frequency) / float(sample_rate)
C : float = Q / O
L : float = 1.0 / Q / O
V : float = 0.0
I : float = 0.0
T : float = 0.0
output : list = list()
for element in input:
T = float(element * O) - V
V += float(I + T) / C
I += T / L
output.append(- float(V)/float(O))
return output
| 28.030303
| 75
| 0.527568
| 149
| 925
| 3.234899
| 0.201342
| 0.074689
| 0.087137
| 0.078838
| 0.829876
| 0.829876
| 0.829876
| 0.829876
| 0.680498
| 0.680498
| 0
| 0.032206
| 0.328649
| 925
| 32
| 76
| 28.90625
| 0.743961
| 0
| 0
| 0.62069
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.068966
| false
| 0.068966
| 0.034483
| 0
| 0.172414
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
c3b9332311c0ae038ebceaccc8a261b9c02073a1
| 130
|
py
|
Python
|
exp1/__init__.py
|
HeroPD/exp1
|
b8b2064e16fa48520231463955d212c09ca6f22d
|
[
"MIT"
] | null | null | null |
exp1/__init__.py
|
HeroPD/exp1
|
b8b2064e16fa48520231463955d212c09ca6f22d
|
[
"MIT"
] | null | null | null |
exp1/__init__.py
|
HeroPD/exp1
|
b8b2064e16fa48520231463955d212c09ca6f22d
|
[
"MIT"
] | null | null | null |
import core
def core_test():
print(core.add(101, 210))
def test():
print("test called")
def test1():
print("test called")
| 13
| 27
| 0.653846
| 20
| 130
| 4.2
| 0.5
| 0.214286
| 0.357143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064815
| 0.169231
| 130
| 10
| 28
| 13
| 0.712963
| 0
| 0
| 0.285714
| 0
| 0
| 0.167939
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| true
| 0
| 0.142857
| 0
| 0.571429
| 0.428571
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
c3dfcf142fc3090494b516ecda9d11e3572e9b12
| 11,608
|
py
|
Python
|
tests/core/arithmetic_test.py
|
mlund/scipp
|
26648fdcda49b21a7aacdafd58625fab7ee3403b
|
[
"BSD-3-Clause"
] | null | null | null |
tests/core/arithmetic_test.py
|
mlund/scipp
|
26648fdcda49b21a7aacdafd58625fab7ee3403b
|
[
"BSD-3-Clause"
] | null | null | null |
tests/core/arithmetic_test.py
|
mlund/scipp
|
26648fdcda49b21a7aacdafd58625fab7ee3403b
|
[
"BSD-3-Clause"
] | null | null | null |
# SPDX-License-Identifier: BSD-3-Clause
# Copyright (c) 2022 Scipp contributors (https://github.com/scipp)
# @author Jan-Lukas Wynen
import numpy as np
import scipp as sc
def make_variables():
data = np.arange(1, 4, dtype=float)
a = sc.Variable(dims=['x'], values=data)
b = sc.Variable(dims=['x'], values=data)
a_slice = a['x', :]
b_slice = b['x', :]
return a, b, a_slice, b_slice, data
# This check is important: It can happen that an implementation of,
# e.g., __iadd__ does an in-place modification, updating `b`, but then the
# return value is assigned to `a`, which could break the connection unless
# the correct Python object is returned.
def test_iadd_returns_original_object():
a = sc.scalar(1.2)
b = a
a += 1.0
assert sc.identical(a, b)
def test_isub_returns_original_object():
a = sc.scalar(1.2)
b = a
a -= 1.0
assert sc.identical(a, b)
def test_imul_returns_original_object():
a = sc.scalar(1.2)
b = a
a *= 1.0
assert sc.identical(a, b)
def test_itruediv_returns_original_object():
a = sc.scalar(1.2)
b = a
a /= 1.0
assert sc.identical(a, b)
def test_add_variable():
a, b, a_slice, b_slice, data = make_variables()
c = a + b
assert np.array_equal(c.values, data + data)
c = a + 2.0
assert np.array_equal(c.values, data + 2.0)
c = a + b_slice
assert np.array_equal(c.values, data + data)
c += b
assert np.array_equal(c.values, data + data + data)
c += b_slice
assert np.array_equal(c.values, data + data + data + data)
c = 3.5 + c
assert np.array_equal(c.values, data + data + data + data + 3.5)
def test_sub_variable():
a, b, a_slice, b_slice, data = make_variables()
c = a - b
assert np.array_equal(c.values, data - data)
c = a - 2.0
assert np.array_equal(c.values, data - 2.0)
c = a - b_slice
assert np.array_equal(c.values, data - data)
c -= b
assert np.array_equal(c.values, data - data - data)
c -= b_slice
assert np.array_equal(c.values, data - data - data - data)
c = 3.5 - c
assert np.array_equal(c.values, 3.5 - data + data + data + data)
def test_mul_variable():
a, b, a_slice, b_slice, data = make_variables()
c = a * b
assert np.array_equal(c.values, data * data)
c = a * 2.0
assert np.array_equal(c.values, data * 2.0)
c = a * b_slice
assert np.array_equal(c.values, data * data)
c *= b
assert np.array_equal(c.values, data * data * data)
c *= b_slice
assert np.array_equal(c.values, data * data * data * data)
c = 3.5 * c
assert np.array_equal(c.values, data * data * data * data * 3.5)
def test_truediv_variable():
a, b, a_slice, b_slice, data = make_variables()
c = a / b
assert np.array_equal(c.values, data / data)
c = a / 2.0
assert np.array_equal(c.values, data / 2.0)
c = a / b_slice
assert np.array_equal(c.values, data / data)
c /= b
assert np.array_equal(c.values, data / data / data)
c /= b_slice
assert np.array_equal(c.values, data / data / data / data)
c = 2.0 / a
assert np.array_equal(c.values, 2.0 / data)
def test_pow_variable():
a, b, a_slice, b_slice, data = make_variables()
c = a**b
assert np.array_equal(c.values, data**data)
c **= b
assert np.array_equal(c.values, (data**data)**data)
c = a**3
assert np.array_equal(c.values, data**3)
c **= 3
assert np.array_equal(c.values, (data**3)**3)
c = a**3.0
assert np.array_equal(c.values, data**3.0)
c **= 3.0
assert np.array_equal(c.values, (data**3.0)**3.0)
c = a**b_slice
assert np.array_equal(c.values, data**data)
c **= b_slice
assert np.array_equal(c.values, (data**data)**data)
c = 2**b
assert np.array_equal(c.values, 2**data)
c = 2.0**b
assert np.array_equal(c.values, 2.0**data)
def test_iadd_variable_with_scalar():
v = sc.Variable(dims=['x'], values=[10.0])
expected = sc.Variable(dims=['x'], values=[12.0])
v += 2
assert sc.identical(v, expected)
def test_isub_variable_with_scalar():
v = sc.Variable(dims=['x'], values=[10.0])
expected = sc.Variable(dims=['x'], values=[9.0])
v -= 1
assert sc.identical(v, expected)
def test_imul_variable_with_scalar():
v = sc.Variable(dims=['x'], values=[10.0])
expected = sc.Variable(dims=['x'], values=[30.0])
v *= 3
assert sc.identical(v, expected)
def test_itruediv_variable_with_scalar():
v = sc.Variable(dims=['x'], values=[10.0])
expected = sc.Variable(dims=['x'], values=[5.0])
v /= 2
assert sc.identical(v, expected)
def test_add_dataarray_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 2.0, 20.0, 2.0)
assert sc.identical(da + da, expected)
def test_sub_dataarray_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
assert sc.identical(da - da, expected)
def test_mul_dataarray_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 1.0, 10.0)**2
assert sc.identical(da * da, expected)
def test_truediv_dataarray_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.ones_like(da)
assert sc.identical(da / da, expected)
def test_add_dataarray_with_variable():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 2.0, 20.0, 2.0)
assert sc.identical(da + da.data, expected)
assert sc.identical(da.data + da, expected)
def test_sub_dataarray_with_variable():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
assert sc.identical(da - da.data, expected)
assert sc.identical(da.data - da, expected)
def test_mul_dataarray_with_variable():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 1.0, 10.0)**2
assert sc.identical(da * da.data, expected)
assert sc.identical(da.data * da, expected)
def test_truediv_dataarray_with_variable():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.ones_like(da)
assert sc.identical(da / da.data, expected)
assert sc.identical(da.data / da, expected)
def test_add_dataarray_with_scalar():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 3.0, 12.0)
assert sc.identical(da + 2.0, expected)
assert sc.identical(2.0 + da, expected)
def test_sub_dataarray_with_scalar():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 1.0, 10.0) - 2.0
assert sc.identical(da - 2.0, expected)
expected.data = 2.0 - sc.arange('x', 1.0, 10.0)
assert sc.identical(2.0 - da, expected)
def test_mul_dataarray_with_scalar():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 2.0, 20.0, 2.0)
assert sc.identical(da * 2.0, expected)
assert sc.identical(2.0 * da, expected)
def test_truediv_dataarray_with_scalar():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = sc.zeros_like(da)
expected.data = sc.arange('x', 1.0, 10.0) / 2.0
assert sc.identical(da / 2.0, expected)
expected.data = 2.0 / sc.arange('x', 1.0, 10.0)
assert sc.identical(2.0 / da, expected)
def test_iadd_dataset_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
ds = sc.Dataset({'data': da.copy()})
expected = sc.Dataset({'data': da + da})
ds += da
assert sc.identical(ds, expected)
def test_isub_dataset_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
ds = sc.Dataset({'data': da.copy()})
expected = sc.Dataset({'data': da - da})
ds -= da
assert sc.identical(ds, expected)
def test_imul_dataset_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
ds = sc.Dataset({'data': da.copy()})
expected = sc.Dataset({'data': da * da})
ds *= da
assert sc.identical(ds, expected)
def test_itruediv_dataset_with_dataarray():
da = sc.DataArray(sc.arange('x', 1.0, 10.0),
coords={'x': sc.arange('x', 10.0, 20.0)})
ds = sc.Dataset({'data': da.copy()})
expected = sc.Dataset({'data': da / da})
ds /= da
assert sc.identical(ds, expected)
def test_iadd_dataset_with_scalar():
ds = sc.Dataset(data={'data': sc.arange('x', 10.0)},
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = ds.copy()
expected['data'] = ds['data'] + 2.0
ds += 2.0
assert sc.identical(ds, expected)
def test_isub_dataset_with_scalar():
ds = sc.Dataset(data={'data': sc.arange('x', 10.0)},
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = ds.copy()
expected['data'] = ds['data'] - 3.0
ds -= 3.0
assert sc.identical(ds, expected)
def test_imul_dataset_with_scalar():
ds = sc.Dataset(data={'data': sc.arange('x', 10.0)},
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = ds.copy()
expected['data'] = ds['data'] * 1.5
ds *= 1.5
assert sc.identical(ds, expected)
def test_itruediv_dataset_with_scalar():
ds = sc.Dataset(data={'data': sc.arange('x', 10.0)},
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = ds.copy()
expected['data'] = ds['data'] / 0.5
ds /= 0.5
assert sc.identical(ds, expected)
def test_isub_dataset_with_dataset_broadcast():
ds = sc.Dataset(data={'data': sc.arange('x', 10.0)},
coords={'x': sc.arange('x', 10.0, 20.0)})
expected = ds - ds['x', 0]
ds -= ds['x', 0]
assert sc.identical(ds, expected)
def test_add_function():
assert sc.identical(sc.add(sc.scalar(3), sc.scalar(2)), sc.scalar(5))
def test_divide_function():
assert sc.identical(sc.divide(sc.scalar(6), sc.scalar(2)), sc.scalar(3.0))
def test_floor_divide_function():
assert sc.identical(sc.floor_divide(sc.scalar(6), sc.scalar(2.5)), sc.scalar(2.0))
def test_mod_function():
assert sc.identical(sc.mod(sc.scalar(3), sc.scalar(2)), sc.scalar(1))
def test_multipy_function():
assert sc.identical(sc.multiply(sc.scalar(3), sc.scalar(2)), sc.scalar(6))
def test_subtract_function():
assert sc.identical(sc.subtract(sc.scalar(3), sc.scalar(2)), sc.scalar(1))
def test_negative_function():
assert sc.identical(sc.negative(sc.scalar(3)), sc.scalar(-3))
| 30.708995
| 86
| 0.60062
| 1,908
| 11,608
| 3.537212
| 0.062893
| 0.023115
| 0.069344
| 0.09068
| 0.901171
| 0.877019
| 0.858201
| 0.831975
| 0.809898
| 0.800711
| 0
| 0.049473
| 0.22338
| 11,608
| 377
| 87
| 30.790451
| 0.699168
| 0.032478
| 0
| 0.402135
| 0
| 0
| 0.015237
| 0
| 0
| 0
| 0
| 0
| 0.27758
| 1
| 0.149466
| false
| 0
| 0.007117
| 0
| 0.160142
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
7f16ab6d5c3936e91e279552b4925bd7bbdc47f5
| 22
|
py
|
Python
|
src/comments/models/__init__.py
|
samrika25/TRAVIS_HEROKU_GIT
|
bcae6d0422d9a0369810944a91dd03db7df0d058
|
[
"MIT"
] | null | null | null |
src/comments/models/__init__.py
|
samrika25/TRAVIS_HEROKU_GIT
|
bcae6d0422d9a0369810944a91dd03db7df0d058
|
[
"MIT"
] | 4
|
2021-03-30T12:35:36.000Z
|
2021-06-10T18:11:24.000Z
|
src/comments/models/__init__.py
|
samrika25/TRAVIS_HEROKU_GIT
|
bcae6d0422d9a0369810944a91dd03db7df0d058
|
[
"MIT"
] | 2
|
2021-02-07T16:16:36.000Z
|
2021-07-13T05:26:51.000Z
|
from .Comment import *
| 22
| 22
| 0.772727
| 3
| 22
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 22
| 1
| 22
| 22
| 0.894737
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
6135350b5c95ecc33f092de02f7e8c2506bc700f
| 1,553
|
py
|
Python
|
Simulator/init_simulation.py
|
nicoladainese96/CoopVM
|
91064e8495e2bb4c6dfd27fd52801f1ba871fb44
|
[
"MIT"
] | null | null | null |
Simulator/init_simulation.py
|
nicoladainese96/CoopVM
|
91064e8495e2bb4c6dfd27fd52801f1ba871fb44
|
[
"MIT"
] | null | null | null |
Simulator/init_simulation.py
|
nicoladainese96/CoopVM
|
91064e8495e2bb4c6dfd27fd52801f1ba871fb44
|
[
"MIT"
] | 1
|
2018-10-08T11:52:59.000Z
|
2018-10-08T11:52:59.000Z
|
def init_simulation(N):
import math
from random import randint
from copy import deepcopy
S = int(math.sqrt(N))
#print("S = {}".format(S))
nu = 0
v = [ randint(0, S-1) for x in range (0,N)]
n = []
Smax = max(v)
for i in range (0,Smax+1):
c = v.count(i)
n.append(c)
from one_step_bi import one_step_mono
t_conv = 0
i = 0
while t_conv == 0:
i = i + 1
(v,n) = one_step_mono(N, nu, v, n, i)
n1 = deepcopy(n)
S = len(n1) - n1.count(0)
if S == 1:
print("Convergenza raggiunta allo step {}.".format(i))
t_conv = i
return t_conv
def init_simulation2(N, S, dir_name, name):
#import math
from random import randint
from copy import deepcopy
import my_print as my
#S = int(math.sqrt(N))
#print("S = {}".format(S))
nu = 0
v = [ randint(0, S-1) for x in range (0,N)]
n = []
Smax = max(v)
for i in range (0,Smax+1):
c = v.count(i)
n.append(c)
from one_step_bi import one_step_mono
t_conv = 0
i = 0
while t_conv == 0:
i = i + 1
for j in range(N):
(v,n) = one_step_mono(N, nu, v, n, i)
n1 = deepcopy(n)
my.print_tuple(n, 'n_'+name, dir_name, d = len(n))
S = len(n1) - n1.count(0)
if S == 1:
print("Convergenza raggiunta a tau {}.".format(i))
t_conv = i
v_n = my.tab_reader2('n_'+name, dir_name)
info = {}
my.mono_plot(v_n, name, dir_name, info)
| 25.459016
| 66
| 0.5132
| 259
| 1,553
| 2.949807
| 0.223938
| 0.045812
| 0.041885
| 0.036649
| 0.79712
| 0.721204
| 0.721204
| 0.721204
| 0.721204
| 0.721204
| 0
| 0.031558
| 0.34707
| 1,553
| 61
| 67
| 25.459016
| 0.721893
| 0.052801
| 0
| 0.745098
| 0
| 0
| 0.047684
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.039216
| false
| 0
| 0.156863
| 0
| 0.215686
| 0.078431
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
61431bcf1c23cc083e1fabbe1293fa4b0bf26854
| 118
|
py
|
Python
|
train_script/train_mnist_to_binary.py
|
jack-Dong/one_hot_to_binary_code
|
3107a6d49d5cd4b7236c0368949a12c21c966368
|
[
"MIT"
] | null | null | null |
train_script/train_mnist_to_binary.py
|
jack-Dong/one_hot_to_binary_code
|
3107a6d49d5cd4b7236c0368949a12c21c966368
|
[
"MIT"
] | null | null | null |
train_script/train_mnist_to_binary.py
|
jack-Dong/one_hot_to_binary_code
|
3107a6d49d5cd4b7236c0368949a12c21c966368
|
[
"MIT"
] | null | null | null |
import importlib
from train_eval import train_eval
cfg = importlib.import_module('config.mnist')
train_eval(cfg)
| 11.8
| 45
| 0.79661
| 17
| 118
| 5.294118
| 0.529412
| 0.3
| 0.266667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.127119
| 118
| 9
| 46
| 13.111111
| 0.873786
| 0
| 0
| 0
| 0
| 0
| 0.104348
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f615b96e0584a63309e38dc6c4abc3801800d1f7
| 46
|
py
|
Python
|
PyCharm/Primer_3.py
|
tamaranesterenko/Python.LR_13
|
c96456a036605d4fd0cf163bb93fb0865ddbd45d
|
[
"MIT"
] | null | null | null |
PyCharm/Primer_3.py
|
tamaranesterenko/Python.LR_13
|
c96456a036605d4fd0cf163bb93fb0865ddbd45d
|
[
"MIT"
] | null | null | null |
PyCharm/Primer_3.py
|
tamaranesterenko/Python.LR_13
|
c96456a036605d4fd0cf163bb93fb0865ddbd45d
|
[
"MIT"
] | null | null | null |
a = [1, 2, 3]
b = [*a, 4, 5, 6]
print(b)
| 9.2
| 18
| 0.326087
| 11
| 46
| 1.363636
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206897
| 0.369565
| 46
| 4
| 19
| 11.5
| 0.310345
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
f61ba426c6871c5a4906f62ac88e6626999aba73
| 12,181
|
py
|
Python
|
tests/test_observable/test_debounce.py
|
mmpio/RxPY
|
4ed60bb5c04aa85de5210e5537a6adfe1b667d50
|
[
"MIT"
] | 4,342
|
2015-01-06T09:00:23.000Z
|
2022-03-28T15:05:50.000Z
|
tests/test_observable/test_debounce.py
|
mmpio/RxPY
|
4ed60bb5c04aa85de5210e5537a6adfe1b667d50
|
[
"MIT"
] | 613
|
2015-01-07T20:44:56.000Z
|
2022-03-20T06:14:20.000Z
|
tests/test_observable/test_debounce.py
|
mmpio/RxPY
|
4ed60bb5c04aa85de5210e5537a6adfe1b667d50
|
[
"MIT"
] | 420
|
2015-01-07T14:30:30.000Z
|
2022-03-11T22:47:46.000Z
|
import unittest
from rx import empty, never, throw, operators as _
from rx.testing import TestScheduler, ReactiveTest
on_next = ReactiveTest.on_next
on_completed = ReactiveTest.on_completed
on_error = ReactiveTest.on_error
subscribe = ReactiveTest.subscribe
subscribed = ReactiveTest.subscribed
disposed = ReactiveTest.disposed
created = ReactiveTest.created
class RxException(Exception):
pass
# Helper function for raising exceptions within lambdas
def _raise(ex):
raise RxException(ex)
class TestDebounce(unittest.TestCase):
def test_debounce_timespan_allpass(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(200, 2), on_next(250, 3), on_next(
300, 4), on_next(350, 5), on_next(400, 6), on_next(450, 7), on_next(500, 8), on_completed(550))
def create():
return xs.pipe(_.debounce(40))
results = scheduler.start(create)
assert results.messages == [on_next(290, 3), on_next(340, 4), on_next(
390, 5), on_next(440, 6), on_next(490, 7), on_next(540, 8), on_completed(550)]
def test_debounce_timespan_allpass_error_end(self):
ex = 'ex'
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(200, 2), on_next(250, 3), on_next(
300, 4), on_next(350, 5), on_next(400, 6), on_next(450, 7), on_next(500, 8), on_error(550, ex))
def create():
return xs.pipe(_.debounce(40))
results = scheduler.start(create)
assert results.messages == [on_next(290, 3), on_next(340, 4), on_next(
390, 5), on_next(440, 6), on_next(490, 7), on_next(540, 8), on_error(550, ex)]
def test_debounce_timespan_alldrop(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(200, 2), on_next(250, 3), on_next(
300, 4), on_next(350, 5), on_next(400, 6), on_next(450, 7), on_next(500, 8), on_completed(550))
def create():
return xs.pipe(_.debounce(60))
results = scheduler.start(create)
assert results.messages == [on_next(550, 8), on_completed(550)]
def test_debounce_timespan_alldrop_error_end(self):
ex = 'ex'
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(200, 2), on_next(250, 3), on_next(
300, 4), on_next(350, 5), on_next(400, 6), on_next(450, 7), on_next(500, 8), on_error(550, ex))
def create():
return xs.pipe(_.debounce(60))
results = scheduler.start(create)
assert results.messages == [on_error(550, ex)]
def test_debounce_timespan_some_drop(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(250, 2), on_next(350, 3), on_next(
370, 4), on_next(421, 5), on_next(480, 6), on_next(490, 7), on_next(500, 8), on_completed(600))
def create():
return xs.pipe(_.debounce(50))
results = scheduler.start(create)
assert results.messages == [on_next(300, 2), on_next(
420, 4), on_next(471, 5), on_next(550, 8), on_completed(600)]
def test_debounce_empty(self):
scheduler = TestScheduler()
def create():
return empty().pipe(_.debounce(10))
results = scheduler.start(create)
assert results.messages == [on_completed(200)]
def test_debounce_error(self):
ex = 'ex'
scheduler = TestScheduler()
def create():
return throw(ex).pipe(_.debounce(10))
results = scheduler.start(create)
assert results.messages == [on_error(200, ex)]
def test_debounce_never(self):
scheduler = TestScheduler()
def create():
return never().pipe(_.debounce(10))
results = scheduler.start(create)
assert results.messages == []
def test_debounce_duration_delay_behavior(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(
on_next(150, -1),
on_next(250, 0),
on_next(280, 1),
on_next(310, 2),
on_next(350, 3),
on_next(400, 4),
on_completed(550))
ys = [scheduler.create_cold_observable(on_next(20, 42), on_next(25, 99)), scheduler.create_cold_observable(on_next(20, 42), on_next(25, 99)), scheduler.create_cold_observable(
on_next(20, 42), on_next(25, 99)), scheduler.create_cold_observable(on_next(20, 42), on_next(25, 99)), scheduler.create_cold_observable(on_next(20, 42), on_next(25, 99))]
def create():
def mapper(x):
return ys[x]
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 20, 0), on_next(280 + 20, 1), on_next(310 + 20, 2),
on_next(350 + 20, 3), on_next(400 + 20, 4), on_completed(550)]
assert xs.subscriptions == [subscribe(200, 550)]
assert ys[0].subscriptions == [subscribe(250, 250 + 20)]
assert ys[1].subscriptions == [subscribe(280, 280 + 20)]
assert ys[2].subscriptions == [subscribe(310, 310 + 20)]
assert ys[3].subscriptions == [subscribe(350, 350 + 20)]
assert ys[4].subscriptions == [subscribe(400, 400 + 20)]
def test_debounce_duration_throttle_behavior(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, -1), on_next(250, 0), on_next(280, 1),
on_next(310, 2), on_next(350, 3), on_next(400, 4), on_completed(550))
ys = [scheduler.create_cold_observable(on_next(20, 42), on_next(25, 99)), scheduler.create_cold_observable(on_next(40, 42), on_next(45, 99)), scheduler.create_cold_observable(
on_next(20, 42), on_next(25, 99)), scheduler.create_cold_observable(on_next(60, 42), on_next(65, 99)), scheduler.create_cold_observable(on_next(20, 42), on_next(25, 99))]
def create():
def mapper(x):
return ys[x]
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 20, 0), on_next(310 + 20, 2), on_next(400 + 20, 4), on_completed(550)]
assert xs.subscriptions == [subscribe(200, 550)]
assert ys[0].subscriptions == [subscribe(250, 250 + 20)]
assert ys[1].subscriptions == [subscribe(280, 310)]
assert ys[2].subscriptions == [subscribe(310, 310 + 20)]
assert ys[3].subscriptions == [subscribe(350, 400)]
assert ys[4].subscriptions == [subscribe(400, 400 + 20)]
def test_debounce_duration_early_completion(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(
on_next(150, -1),
on_next(250, 0),
on_next(280, 1),
on_next(310, 2),
on_next(350, 3),
on_next(400, 4),
on_completed(410))
ys = [
scheduler.create_cold_observable(
on_next(20, 42),
on_next(25, 99)),
scheduler.create_cold_observable(
on_next(40, 42),
on_next(45, 99)),
scheduler.create_cold_observable(
on_next(20, 42),
on_next(25, 99)),
scheduler.create_cold_observable(
on_next(60, 42),
on_next(65, 99)),
scheduler.create_cold_observable(
on_next(20, 42),
on_next(25, 99))
]
def create():
def mapper(x):
return ys[x]
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 20, 0), on_next(310 + 20, 2), on_next(410, 4), on_completed(410)]
assert xs.subscriptions == [subscribe(200, 410)]
assert ys[0].subscriptions == [subscribe(250, 250 + 20)]
assert ys[1].subscriptions == [subscribe(280, 310)]
assert ys[2].subscriptions == [subscribe(310, 310 + 20)]
assert ys[3].subscriptions == [subscribe(350, 400)]
assert ys[4].subscriptions == [subscribe(400, 410)]
def test_debounce_duration_inner_error(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(
250, 2), on_next(350, 3), on_next(450, 4), on_completed(550))
ex = 'ex'
def create():
def mapper(x):
if x < 4:
return scheduler.create_cold_observable(on_next(x * 10, "Ignore"), on_next(x * 10 + 5, "Aargh!"))
else:
return scheduler.create_cold_observable(on_error(x * 10, ex))
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 2 * 10, 2), on_next(350 + 3 * 10, 3), on_error(450 + 4 * 10, ex)]
assert xs.subscriptions == [subscribe(200, 490)]
def test_debounce_duration_outer_error(self):
ex = 'ex'
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(
250, 2), on_next(350, 3), on_next(450, 4), on_error(460, ex))
def create():
def mapper(x):
return scheduler.create_cold_observable(on_next(x * 10, "Ignore"), on_next(x * 10 + 5, "Aargh!"))
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 2 * 10, 2), on_next(350 + 3 * 10, 3), on_error(460, ex)]
assert xs.subscriptions == [subscribe(200, 460)]
def test_debounce_duration_mapper_throws(self):
ex = 'ex'
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(
250, 2), on_next(350, 3), on_next(450, 4), on_completed(550))
def create():
def mapper(x):
if x < 4:
return scheduler.create_cold_observable(on_next(x * 10, "Ignore"), on_next(x * 10 + 5, "Aargh!"))
else:
_raise(ex)
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 2 * 10, 2), on_next(350 + 3 * 10, 3), on_error(450, ex)]
assert xs.subscriptions == [subscribe(200, 450)]
def test_debounce_duration_inner_done_delay_behavior(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(on_next(150, 1), on_next(
250, 2), on_next(350, 3), on_next(450, 4), on_completed(550))
def create():
def mapper(x):
return scheduler.create_cold_observable(on_completed(x * 10))
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [
on_next(250 + 2 * 10, 2),
on_next(350 + 3 * 10, 3),
on_next(450 + 4 * 10, 4),
on_completed(550)]
assert xs.subscriptions == [subscribe(200, 550)]
def test_debounce_duration_inner_done_throttle_behavior(self):
scheduler = TestScheduler()
xs = scheduler.create_hot_observable(
on_next(150, 1),
on_next(250, 2),
on_next(280, 3),
on_next(300, 4),
on_next(400, 5),
on_next(410, 6),
on_completed(550))
def create():
def mapper(x):
return scheduler.create_cold_observable(on_completed(x * 10))
return xs.pipe(_.throttle_with_mapper(mapper))
results = scheduler.start(create)
assert results.messages == [on_next(250 + 2 * 10, 2), on_next(300 + 4 * 10, 4),
on_next(410 + 6 * 10, 6), on_completed(550)]
assert xs.subscriptions == [subscribe(200, 550)]
| 39.80719
| 183
| 0.595107
| 1,598
| 12,181
| 4.312265
| 0.075094
| 0.137571
| 0.071978
| 0.088376
| 0.882746
| 0.861849
| 0.805979
| 0.796256
| 0.77681
| 0.759687
| 0
| 0.108142
| 0.275018
| 12,181
| 305
| 184
| 39.937705
| 0.672178
| 0.004351
| 0
| 0.618644
| 0
| 0
| 0.003958
| 0
| 0
| 0
| 0
| 0
| 0.165254
| 1
| 0.173729
| false
| 0.012712
| 0.012712
| 0.059322
| 0.300847
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
f678a57030a711370b691e9f6a755ebb9cb9e32e
| 31,072
|
py
|
Python
|
Wigle/python-client/swagger_client/api/v3_alpha_api.py
|
BillReyor/SSIDprobeCollector
|
437989fd1e9d8d200ca28f88a692ecc17530db73
|
[
"MIT"
] | 1
|
2022-01-30T16:34:05.000Z
|
2022-01-30T16:34:05.000Z
|
Wigle/python-client/swagger_client/api/v3_alpha_api.py
|
BillReyor/SSIDprobeCollector
|
437989fd1e9d8d200ca28f88a692ecc17530db73
|
[
"MIT"
] | null | null | null |
Wigle/python-client/swagger_client/api/v3_alpha_api.py
|
BillReyor/SSIDprobeCollector
|
437989fd1e9d8d200ca28f88a692ecc17530db73
|
[
"MIT"
] | null | null | null |
# coding: utf-8
"""
WiGLE API
Search, upload, and integrate statistics from WiGLE. Use API Name+Token from https://wigle.net/account # noqa: E501
OpenAPI spec version: 3.1
Contact: WiGLE-admin@wigle.net
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import re # noqa: F401
# python 2 and python 3 compatibility library
import six
from swagger_client.api_client import ApiClient
class V3ALPHAApi(object):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
Ref: https://github.com/swagger-api/swagger-codegen
"""
def __init__(self, api_client=None):
if api_client is None:
api_client = ApiClient()
self.api_client = api_client
def bt(self, bt_network_id, **kwargs): # noqa: E501
"""Request detail for a bluetooth network # noqa: E501
Location and detail properties for bluetooth networks. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.bt(bt_network_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str bt_network_id: Network ID. (required)
:return: BtDetail
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.bt_with_http_info(bt_network_id, **kwargs) # noqa: E501
else:
(data) = self.bt_with_http_info(bt_network_id, **kwargs) # noqa: E501
return data
def bt_with_http_info(self, bt_network_id, **kwargs): # noqa: E501
"""Request detail for a bluetooth network # noqa: E501
Location and detail properties for bluetooth networks. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.bt_with_http_info(bt_network_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str bt_network_id: Network ID. (required)
:return: BtDetail
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['bt_network_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method bt" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'bt_network_id' is set
if self.api_client.client_side_validation and ('bt_network_id' not in params or
params['bt_network_id'] is None): # noqa: E501
raise ValueError("Missing the required parameter `bt_network_id` when calling `bt`") # noqa: E501
if self.api_client.client_side_validation and ('bt_network_id' in params and not re.search(r'^([0-9a-fA-F]{2}:){5}[0-9a-fA-F]{2}$', params['bt_network_id'])): # noqa: E501
raise ValueError("Invalid value for parameter `bt_network_id` when calling `bt`, must conform to the pattern `/^([0-9a-fA-F]{2}:){5}[0-9a-fA-F]{2}$/`") # noqa: E501
collection_formats = {}
path_params = {}
if 'bt_network_id' in params:
path_params['btNetworkId'] = params['bt_network_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['user'] # noqa: E501
return self.api_client.call_api(
'/api/v3/detail/bt/{btNetworkId}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='BtDetail', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cdma_cell(self, sid, nid, bsid, **kwargs): # noqa: E501
"""Request detail for a CDMA network # noqa: E501
Location and detail properties for CDMA networks. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cdma_cell(sid, nid, bsid, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str sid: CDMA System ID. (required)
:param str nid: CDMA Network ID. (required)
:param str bsid: CDMA Base Station ID. (required)
:return: CellDetail
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cdma_cell_with_http_info(sid, nid, bsid, **kwargs) # noqa: E501
else:
(data) = self.cdma_cell_with_http_info(sid, nid, bsid, **kwargs) # noqa: E501
return data
def cdma_cell_with_http_info(self, sid, nid, bsid, **kwargs): # noqa: E501
"""Request detail for a CDMA network # noqa: E501
Location and detail properties for CDMA networks. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cdma_cell_with_http_info(sid, nid, bsid, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str sid: CDMA System ID. (required)
:param str nid: CDMA Network ID. (required)
:param str bsid: CDMA Base Station ID. (required)
:return: CellDetail
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['sid', 'nid', 'bsid'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cdma_cell" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'sid' is set
if self.api_client.client_side_validation and ('sid' not in params or
params['sid'] is None): # noqa: E501
raise ValueError("Missing the required parameter `sid` when calling `cdma_cell`") # noqa: E501
# verify the required parameter 'nid' is set
if self.api_client.client_side_validation and ('nid' not in params or
params['nid'] is None): # noqa: E501
raise ValueError("Missing the required parameter `nid` when calling `cdma_cell`") # noqa: E501
# verify the required parameter 'bsid' is set
if self.api_client.client_side_validation and ('bsid' not in params or
params['bsid'] is None): # noqa: E501
raise ValueError("Missing the required parameter `bsid` when calling `cdma_cell`") # noqa: E501
if self.api_client.client_side_validation and ('sid' in params and not re.search(r'^[0-9]{1,5}$', params['sid'])): # noqa: E501
raise ValueError("Invalid value for parameter `sid` when calling `cdma_cell`, must conform to the pattern `/^[0-9]{1,5}$/`") # noqa: E501
if self.api_client.client_side_validation and ('nid' in params and not re.search(r'^[0-9]{1,5}$', params['nid'])): # noqa: E501
raise ValueError("Invalid value for parameter `nid` when calling `cdma_cell`, must conform to the pattern `/^[0-9]{1,5}$/`") # noqa: E501
if self.api_client.client_side_validation and ('bsid' in params and not re.search(r'^[0-9]{1,9}$', params['bsid'])): # noqa: E501
raise ValueError("Invalid value for parameter `bsid` when calling `cdma_cell`, must conform to the pattern `/^[0-9]{1,9}$/`") # noqa: E501
collection_formats = {}
path_params = {}
if 'sid' in params:
path_params['sid'] = params['sid'] # noqa: E501
if 'nid' in params:
path_params['nid'] = params['nid'] # noqa: E501
if 'bsid' in params:
path_params['bsid'] = params['bsid'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['user'] # noqa: E501
return self.api_client.call_api(
'/api/v3/detail/cell/CDMA/{sid}/{nid}/{bsid}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='CellDetail', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cell(self, operator, lac, cid, type, **kwargs): # noqa: E501
"""Request detail for a GSM, LTE, or WCDMA network # noqa: E501
Location and detail properties for non-CDMA cell types. Note that the type parameter is sensitive to current type in the WiGLE database - this means that LTE and WCDMA networks may have been reported as GSM in some packages, a fallback query to GSM is recommended if the LTE/WCDMA network appears to be absent. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cell(operator, lac, cid, type, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str operator: GSM/LTE/WCDMA Operator ID (required)
:param str lac: GSM/LTE/WCDMA Location Area Code (required)
:param str cid: GSM/LTE/WCDMA Cell ID (required)
:param str type: Network Type: GSM/LTE/WCDMA (required)
:return: BtDetail
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cell_with_http_info(operator, lac, cid, type, **kwargs) # noqa: E501
else:
(data) = self.cell_with_http_info(operator, lac, cid, type, **kwargs) # noqa: E501
return data
def cell_with_http_info(self, operator, lac, cid, type, **kwargs): # noqa: E501
"""Request detail for a GSM, LTE, or WCDMA network # noqa: E501
Location and detail properties for non-CDMA cell types. Note that the type parameter is sensitive to current type in the WiGLE database - this means that LTE and WCDMA networks may have been reported as GSM in some packages, a fallback query to GSM is recommended if the LTE/WCDMA network appears to be absent. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cell_with_http_info(operator, lac, cid, type, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str operator: GSM/LTE/WCDMA Operator ID (required)
:param str lac: GSM/LTE/WCDMA Location Area Code (required)
:param str cid: GSM/LTE/WCDMA Cell ID (required)
:param str type: Network Type: GSM/LTE/WCDMA (required)
:return: BtDetail
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['operator', 'lac', 'cid', 'type'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cell" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'operator' is set
if self.api_client.client_side_validation and ('operator' not in params or
params['operator'] is None): # noqa: E501
raise ValueError("Missing the required parameter `operator` when calling `cell`") # noqa: E501
# verify the required parameter 'lac' is set
if self.api_client.client_side_validation and ('lac' not in params or
params['lac'] is None): # noqa: E501
raise ValueError("Missing the required parameter `lac` when calling `cell`") # noqa: E501
# verify the required parameter 'cid' is set
if self.api_client.client_side_validation and ('cid' not in params or
params['cid'] is None): # noqa: E501
raise ValueError("Missing the required parameter `cid` when calling `cell`") # noqa: E501
# verify the required parameter 'type' is set
if self.api_client.client_side_validation and ('type' not in params or
params['type'] is None): # noqa: E501
raise ValueError("Missing the required parameter `type` when calling `cell`") # noqa: E501
if self.api_client.client_side_validation and ('operator' in params and not re.search(r'^[0-9]{1,6}$', params['operator'])): # noqa: E501
raise ValueError("Invalid value for parameter `operator` when calling `cell`, must conform to the pattern `/^[0-9]{1,6}$/`") # noqa: E501
if self.api_client.client_side_validation and ('lac' in params and not re.search(r'^[0-9]{1,5}$', params['lac'])): # noqa: E501
raise ValueError("Invalid value for parameter `lac` when calling `cell`, must conform to the pattern `/^[0-9]{1,5}$/`") # noqa: E501
if self.api_client.client_side_validation and ('cid' in params and not re.search(r'^[0-9]{1,9}$', params['cid'])): # noqa: E501
raise ValueError("Invalid value for parameter `cid` when calling `cell`, must conform to the pattern `/^[0-9]{1,9}$/`") # noqa: E501
if self.api_client.client_side_validation and ('type' in params and not re.search(r'^(GSM|LTE|WCDMA)$', params['type'])): # noqa: E501
raise ValueError("Invalid value for parameter `type` when calling `cell`, must conform to the pattern `/^(GSM|LTE|WCDMA)$/`") # noqa: E501
collection_formats = {}
path_params = {}
if 'operator' in params:
path_params['operator'] = params['operator'] # noqa: E501
if 'lac' in params:
path_params['lac'] = params['lac'] # noqa: E501
if 'cid' in params:
path_params['cid'] = params['cid'] # noqa: E501
if 'type' in params:
path_params['type'] = params['type'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['user'] # noqa: E501
return self.api_client.call_api(
'/api/v3/detail/cell/{type}/{operator}/{lac}/{cid}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='BtDetail', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def cell_channel(self, type, latitude1, latitude2, longitude1, longitude2, **kwargs): # noqa: E501
"""Request list of channels for GSM, LTE, or WCDMA transmitters in specified region # noqa: E501
List of known channels and QoS values for any of the non-CDMA cell types in a bounding box. Note that the type parameter is sensitive to current type in the WiGLE database - this means that LTE and WCDMA networks may have been reported as GSM in some packages, a fallback query to GSM is recommended if the LTE/WCDMA network appears to be absent. Channel endpoints are NOT included in COMMAPI subscriptions at this time. Region cannot be large than 99 square miles (~256 sq km). Daily query limit subject to user DETAIL limit. Designed to support cell-site simulator detection. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cell_channel(type, latitude1, latitude2, longitude1, longitude2, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str type: Network Type: GSM/LTE/WCDMA (required)
:param float latitude1: First bounding latitude (required)
:param float latitude2: Second bounding latitude (required)
:param float longitude1: First bounding longitude (required)
:param float longitude2: Second bounding longitude (required)
:return: ChannelDetailResponse
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.cell_channel_with_http_info(type, latitude1, latitude2, longitude1, longitude2, **kwargs) # noqa: E501
else:
(data) = self.cell_channel_with_http_info(type, latitude1, latitude2, longitude1, longitude2, **kwargs) # noqa: E501
return data
def cell_channel_with_http_info(self, type, latitude1, latitude2, longitude1, longitude2, **kwargs): # noqa: E501
"""Request list of channels for GSM, LTE, or WCDMA transmitters in specified region # noqa: E501
List of known channels and QoS values for any of the non-CDMA cell types in a bounding box. Note that the type parameter is sensitive to current type in the WiGLE database - this means that LTE and WCDMA networks may have been reported as GSM in some packages, a fallback query to GSM is recommended if the LTE/WCDMA network appears to be absent. Channel endpoints are NOT included in COMMAPI subscriptions at this time. Region cannot be large than 99 square miles (~256 sq km). Daily query limit subject to user DETAIL limit. Designed to support cell-site simulator detection. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.cell_channel_with_http_info(type, latitude1, latitude2, longitude1, longitude2, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str type: Network Type: GSM/LTE/WCDMA (required)
:param float latitude1: First bounding latitude (required)
:param float latitude2: Second bounding latitude (required)
:param float longitude1: First bounding longitude (required)
:param float longitude2: Second bounding longitude (required)
:return: ChannelDetailResponse
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['type', 'latitude1', 'latitude2', 'longitude1', 'longitude2'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method cell_channel" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'type' is set
if self.api_client.client_side_validation and ('type' not in params or
params['type'] is None): # noqa: E501
raise ValueError("Missing the required parameter `type` when calling `cell_channel`") # noqa: E501
# verify the required parameter 'latitude1' is set
if self.api_client.client_side_validation and ('latitude1' not in params or
params['latitude1'] is None): # noqa: E501
raise ValueError("Missing the required parameter `latitude1` when calling `cell_channel`") # noqa: E501
# verify the required parameter 'latitude2' is set
if self.api_client.client_side_validation and ('latitude2' not in params or
params['latitude2'] is None): # noqa: E501
raise ValueError("Missing the required parameter `latitude2` when calling `cell_channel`") # noqa: E501
# verify the required parameter 'longitude1' is set
if self.api_client.client_side_validation and ('longitude1' not in params or
params['longitude1'] is None): # noqa: E501
raise ValueError("Missing the required parameter `longitude1` when calling `cell_channel`") # noqa: E501
# verify the required parameter 'longitude2' is set
if self.api_client.client_side_validation and ('longitude2' not in params or
params['longitude2'] is None): # noqa: E501
raise ValueError("Missing the required parameter `longitude2` when calling `cell_channel`") # noqa: E501
if self.api_client.client_side_validation and ('type' in params and not re.search(r'^(GSM|LTE|WCDMA)$', params['type'])): # noqa: E501
raise ValueError("Invalid value for parameter `type` when calling `cell_channel`, must conform to the pattern `/^(GSM|LTE|WCDMA)$/`") # noqa: E501
collection_formats = {}
path_params = {}
if 'type' in params:
path_params['type'] = params['type'] # noqa: E501
query_params = []
if 'latitude1' in params:
query_params.append(('latitude1', params['latitude1'])) # noqa: E501
if 'latitude2' in params:
query_params.append(('latitude2', params['latitude2'])) # noqa: E501
if 'longitude1' in params:
query_params.append(('longitude1', params['longitude1'])) # noqa: E501
if 'longitude2' in params:
query_params.append(('longitude2', params['longitude2'])) # noqa: E501
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['user'] # noqa: E501
return self.api_client.call_api(
'/api/v3/cellChannel/{type}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='ChannelDetailResponse', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
def wifi(self, wifi_network_id, **kwargs): # noqa: E501
"""Request detail for a WiFi network # noqa: E501
Location and detail properties for WiFi networks. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.wifi(wifi_network_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str wifi_network_id: Network ID. (required)
:return: WiFiDetail
If the method is called asynchronously,
returns the request thread.
"""
kwargs['_return_http_data_only'] = True
if kwargs.get('async_req'):
return self.wifi_with_http_info(wifi_network_id, **kwargs) # noqa: E501
else:
(data) = self.wifi_with_http_info(wifi_network_id, **kwargs) # noqa: E501
return data
def wifi_with_http_info(self, wifi_network_id, **kwargs): # noqa: E501
"""Request detail for a WiFi network # noqa: E501
Location and detail properties for WiFi networks. Detail endpoints are NOT included in COMMAPI subscriptions at this time. Daily query limit subject to user DETAIL limit. # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.wifi_with_http_info(wifi_network_id, async_req=True)
>>> result = thread.get()
:param async_req bool
:param str wifi_network_id: Network ID. (required)
:return: WiFiDetail
If the method is called asynchronously,
returns the request thread.
"""
all_params = ['wifi_network_id'] # noqa: E501
all_params.append('async_req')
all_params.append('_return_http_data_only')
all_params.append('_preload_content')
all_params.append('_request_timeout')
params = locals()
for key, val in six.iteritems(params['kwargs']):
if key not in all_params:
raise TypeError(
"Got an unexpected keyword argument '%s'"
" to method wifi" % key
)
params[key] = val
del params['kwargs']
# verify the required parameter 'wifi_network_id' is set
if self.api_client.client_side_validation and ('wifi_network_id' not in params or
params['wifi_network_id'] is None): # noqa: E501
raise ValueError("Missing the required parameter `wifi_network_id` when calling `wifi`") # noqa: E501
if self.api_client.client_side_validation and ('wifi_network_id' in params and not re.search(r'^([0-9a-fA-F]{2}:){5}[0-9a-fA-F]{2}$', params['wifi_network_id'])): # noqa: E501
raise ValueError("Invalid value for parameter `wifi_network_id` when calling `wifi`, must conform to the pattern `/^([0-9a-fA-F]{2}:){5}[0-9a-fA-F]{2}$/`") # noqa: E501
collection_formats = {}
path_params = {}
if 'wifi_network_id' in params:
path_params['wifiNetworkId'] = params['wifi_network_id'] # noqa: E501
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
['application/json']) # noqa: E501
# Authentication setting
auth_settings = ['user'] # noqa: E501
return self.api_client.call_api(
'/api/v3/detail/wifi/{wifiNetworkId}', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
response_type='WiFiDetail', # noqa: E501
auth_settings=auth_settings,
async_req=params.get('async_req'),
_return_http_data_only=params.get('_return_http_data_only'),
_preload_content=params.get('_preload_content', True),
_request_timeout=params.get('_request_timeout'),
collection_formats=collection_formats)
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| false
| 0
| 0.011976
| 0
| 0.092814
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| null | 0
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| 0
| 0
| 0
| 0
|
0
| 6
|
9c9256a90e94e3386d0c84dec521c23e98628f18
| 2,840
|
py
|
Python
|
fbpcp/decorator/metrics.py
|
corbantek/fbpcp
|
ed94bde5db40e4713f26dd7e0697c010a5d87e52
|
[
"MIT"
] | 24
|
2021-08-24T09:30:18.000Z
|
2022-03-28T20:51:01.000Z
|
fbpcp/decorator/metrics.py
|
corbantek/fbpcp
|
ed94bde5db40e4713f26dd7e0697c010a5d87e52
|
[
"MIT"
] | 142
|
2021-08-16T23:49:27.000Z
|
2022-03-31T21:05:04.000Z
|
fbpcp/decorator/metrics.py
|
corbantek/fbpcp
|
ed94bde5db40e4713f26dd7e0697c010a5d87e52
|
[
"MIT"
] | 23
|
2021-09-10T22:55:04.000Z
|
2022-03-25T18:11:25.000Z
|
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""Metrics Decorators
The decorators in this file are designed to deocrate classes that implement MetricsGetter.
"""
import asyncio
import functools
import time
from typing import Callable
from fbpcp.metrics.getter import MetricsGetter
def request_counter(metrics_name: str) -> Callable:
def wrap(f: Callable):
@functools.wraps(f)
def wrapper_sync(self: MetricsGetter, *args, **kwargs):
if self.has_metrics():
self.get_metrics().count(metrics_name, 1)
return f(self, *args, **kwargs)
@functools.wraps(f)
async def wrapper_async(self: MetricsGetter, *args, **kwargs):
if self.has_metrics():
self.get_metrics().count(metrics_name, 1)
return await f(self, *args, **kwargs)
return wrapper_async if asyncio.iscoroutinefunction(f) else wrapper_sync
return wrap
def error_counter(metrics_name: str) -> Callable:
def wrap(f: Callable):
@functools.wraps(f)
def wrapper_sync(self: MetricsGetter, *args, **kwargs):
try:
return f(self, *args, **kwargs)
except Exception as err:
if self.has_metrics():
self.get_metrics().count(metrics_name, 1)
raise err
@functools.wraps(f)
async def wrapper_async(self: MetricsGetter, *args, **kwargs):
try:
return await f(self, *args, **kwargs)
except Exception as err:
if self.has_metrics():
self.get_metrics().count(metrics_name, 1)
raise err
return wrapper_async if asyncio.iscoroutinefunction(f) else wrapper_sync
return wrap
def duration_time(metrics_name: str) -> Callable:
def wrap(f: Callable):
@functools.wraps(f)
def wrapper_sync(self: MetricsGetter, *args, **kwargs):
start = time.perf_counter_ns()
res = f(self, *args, **kwargs)
end = time.perf_counter_ns()
if self.has_metrics():
self.get_metrics().gauge(metrics_name, int((end - start) / 1e6))
return res
@functools.wraps(f)
async def wrapper_async(self: MetricsGetter, *args, **kwargs):
start = time.perf_counter_ns()
res = await f(self, *args, **kwargs)
end = time.perf_counter_ns()
if self.has_metrics():
self.get_metrics().gauge(metrics_name, int((end - start) / 1e6))
return res
return wrapper_async if asyncio.iscoroutinefunction(f) else wrapper_sync
return wrap
| 31.208791
| 90
| 0.609507
| 339
| 2,840
| 4.976401
| 0.250737
| 0.071132
| 0.053349
| 0.096028
| 0.777119
| 0.765264
| 0.739775
| 0.739775
| 0.739775
| 0.739775
| 0
| 0.004469
| 0.290845
| 2,840
| 90
| 91
| 31.555556
| 0.833168
| 0.10669
| 0
| 0.830508
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.152542
| false
| 0
| 0.084746
| 0
| 0.440678
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| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
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| 0
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| 0
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| 0
| 0
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| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
140f5321c126afb7b5f8f3fde665774d9a15a997
| 42
|
py
|
Python
|
src/cloudfront_short_url/__init__.py
|
bluemoonforms/cloudfront-short-url
|
d291e05b9692e4c674376076c92220b784e79536
|
[
"MIT"
] | null | null | null |
src/cloudfront_short_url/__init__.py
|
bluemoonforms/cloudfront-short-url
|
d291e05b9692e4c674376076c92220b784e79536
|
[
"MIT"
] | null | null | null |
src/cloudfront_short_url/__init__.py
|
bluemoonforms/cloudfront-short-url
|
d291e05b9692e4c674376076c92220b784e79536
|
[
"MIT"
] | null | null | null |
from .generator import Settings, ShortUrl
| 21
| 41
| 0.833333
| 5
| 42
| 7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.119048
| 42
| 1
| 42
| 42
| 0.945946
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1426c749552f0f13c158d0dc7f2b9002f41fc2e1
| 6,945
|
py
|
Python
|
tests/components/google_travel_time/test_config_flow.py
|
MrDelik/core
|
93a66cc357b226389967668441000498a10453bb
|
[
"Apache-2.0"
] | 30,023
|
2016-04-13T10:17:53.000Z
|
2020-03-02T12:56:31.000Z
|
tests/components/google_travel_time/test_config_flow.py
|
MrDelik/core
|
93a66cc357b226389967668441000498a10453bb
|
[
"Apache-2.0"
] | 24,710
|
2016-04-13T08:27:26.000Z
|
2020-03-02T12:59:13.000Z
|
tests/components/google_travel_time/test_config_flow.py
|
MrDelik/core
|
93a66cc357b226389967668441000498a10453bb
|
[
"Apache-2.0"
] | 11,956
|
2016-04-13T18:42:31.000Z
|
2020-03-02T09:32:12.000Z
|
"""Test the Google Maps Travel Time config flow."""
import pytest
from homeassistant import config_entries, data_entry_flow
from homeassistant.components.google_travel_time.const import (
ARRIVAL_TIME,
CONF_ARRIVAL_TIME,
CONF_AVOID,
CONF_DEPARTURE_TIME,
CONF_DESTINATION,
CONF_LANGUAGE,
CONF_ORIGIN,
CONF_TIME,
CONF_TIME_TYPE,
CONF_TRAFFIC_MODEL,
CONF_TRANSIT_MODE,
CONF_TRANSIT_ROUTING_PREFERENCE,
CONF_UNITS,
DEFAULT_NAME,
DEPARTURE_TIME,
DOMAIN,
)
from homeassistant.const import (
CONF_API_KEY,
CONF_MODE,
CONF_NAME,
CONF_UNIT_SYSTEM_IMPERIAL,
)
from tests.components.google_travel_time.const import MOCK_CONFIG
@pytest.mark.usefixtures("validate_config_entry", "bypass_setup")
async def test_minimum_fields(hass):
"""Test we get the form."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["errors"] == {}
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
MOCK_CONFIG,
)
assert result2["type"] == data_entry_flow.RESULT_TYPE_CREATE_ENTRY
assert result2["title"] == DEFAULT_NAME
assert result2["data"] == {
CONF_NAME: DEFAULT_NAME,
CONF_API_KEY: "api_key",
CONF_ORIGIN: "location1",
CONF_DESTINATION: "location2",
}
@pytest.mark.usefixtures("invalidate_config_entry")
async def test_invalid_config_entry(hass):
"""Test we get the form."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["errors"] == {}
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
MOCK_CONFIG,
)
assert result2["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result2["errors"] == {"base": "cannot_connect"}
@pytest.mark.parametrize(
"data,options",
[
(
MOCK_CONFIG,
{
CONF_MODE: "driving",
CONF_ARRIVAL_TIME: "test",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
},
)
],
)
@pytest.mark.usefixtures("validate_config_entry")
async def test_options_flow(hass, mock_config):
"""Test options flow."""
result = await hass.config_entries.options.async_init(
mock_config.entry_id, data=None
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["step_id"] == "init"
result = await hass.config_entries.options.async_configure(
result["flow_id"],
user_input={
CONF_MODE: "driving",
CONF_LANGUAGE: "en",
CONF_AVOID: "tolls",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
CONF_TIME_TYPE: ARRIVAL_TIME,
CONF_TIME: "test",
CONF_TRAFFIC_MODEL: "best_guess",
CONF_TRANSIT_MODE: "train",
CONF_TRANSIT_ROUTING_PREFERENCE: "less_walking",
},
)
assert result["type"] == data_entry_flow.RESULT_TYPE_CREATE_ENTRY
assert result["title"] == ""
assert result["data"] == {
CONF_MODE: "driving",
CONF_LANGUAGE: "en",
CONF_AVOID: "tolls",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
CONF_ARRIVAL_TIME: "test",
CONF_TRAFFIC_MODEL: "best_guess",
CONF_TRANSIT_MODE: "train",
CONF_TRANSIT_ROUTING_PREFERENCE: "less_walking",
}
assert mock_config.options == {
CONF_MODE: "driving",
CONF_LANGUAGE: "en",
CONF_AVOID: "tolls",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
CONF_ARRIVAL_TIME: "test",
CONF_TRAFFIC_MODEL: "best_guess",
CONF_TRANSIT_MODE: "train",
CONF_TRANSIT_ROUTING_PREFERENCE: "less_walking",
}
@pytest.mark.parametrize(
"data,options",
[(MOCK_CONFIG, {})],
)
@pytest.mark.usefixtures("validate_config_entry")
async def test_options_flow_departure_time(hass, mock_config):
"""Test options flow with departure time."""
result = await hass.config_entries.options.async_init(
mock_config.entry_id, data=None
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["step_id"] == "init"
result = await hass.config_entries.options.async_configure(
result["flow_id"],
user_input={
CONF_MODE: "driving",
CONF_LANGUAGE: "en",
CONF_AVOID: "tolls",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
CONF_TIME_TYPE: DEPARTURE_TIME,
CONF_TIME: "test",
CONF_TRAFFIC_MODEL: "best_guess",
CONF_TRANSIT_MODE: "train",
CONF_TRANSIT_ROUTING_PREFERENCE: "less_walking",
},
)
assert result["type"] == data_entry_flow.RESULT_TYPE_CREATE_ENTRY
assert result["title"] == ""
assert result["data"] == {
CONF_MODE: "driving",
CONF_LANGUAGE: "en",
CONF_AVOID: "tolls",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
CONF_DEPARTURE_TIME: "test",
CONF_TRAFFIC_MODEL: "best_guess",
CONF_TRANSIT_MODE: "train",
CONF_TRANSIT_ROUTING_PREFERENCE: "less_walking",
}
assert mock_config.options == {
CONF_MODE: "driving",
CONF_LANGUAGE: "en",
CONF_AVOID: "tolls",
CONF_UNITS: CONF_UNIT_SYSTEM_IMPERIAL,
CONF_DEPARTURE_TIME: "test",
CONF_TRAFFIC_MODEL: "best_guess",
CONF_TRANSIT_MODE: "train",
CONF_TRANSIT_ROUTING_PREFERENCE: "less_walking",
}
@pytest.mark.usefixtures("validate_config_entry", "bypass_setup")
async def test_dupe(hass):
"""Test setting up the same entry data twice is OK."""
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["errors"] == {}
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
{
CONF_API_KEY: "test",
CONF_ORIGIN: "location1",
CONF_DESTINATION: "location2",
},
)
assert result2["type"] == data_entry_flow.RESULT_TYPE_CREATE_ENTRY
result = await hass.config_entries.flow.async_init(
DOMAIN, context={"source": config_entries.SOURCE_USER}
)
assert result["type"] == data_entry_flow.RESULT_TYPE_FORM
assert result["errors"] == {}
result2 = await hass.config_entries.flow.async_configure(
result["flow_id"],
{
CONF_API_KEY: "test",
CONF_ORIGIN: "location1",
CONF_DESTINATION: "location2",
},
)
await hass.async_block_till_done()
assert result2["type"] == data_entry_flow.RESULT_TYPE_CREATE_ENTRY
| 30.594714
| 70
| 0.6491
| 799
| 6,945
| 5.257822
| 0.123905
| 0.047608
| 0.040229
| 0.062842
| 0.831469
| 0.821471
| 0.772435
| 0.757201
| 0.75006
| 0.748631
| 0
| 0.003228
| 0.241613
| 6,945
| 226
| 71
| 30.730089
| 0.79438
| 0.006479
| 0
| 0.61658
| 0
| 0
| 0.106579
| 0.015927
| 0
| 0
| 0
| 0
| 0.139896
| 1
| 0
| false
| 0.010363
| 0.025907
| 0
| 0.025907
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
14872a3f3b6054b8feb377463481bbece8687441
| 110
|
py
|
Python
|
mainsite/views.py
|
Nodir2001/portfolio_business_card-
|
8b0648a48cdbd430de7b02ed6e13c409b58eadbe
|
[
"MIT"
] | null | null | null |
mainsite/views.py
|
Nodir2001/portfolio_business_card-
|
8b0648a48cdbd430de7b02ed6e13c409b58eadbe
|
[
"MIT"
] | 1
|
2021-04-22T00:17:44.000Z
|
2021-04-22T00:17:44.000Z
|
mainsite/views.py
|
Nodir2001/portfolio_business_card-
|
8b0648a48cdbd430de7b02ed6e13c409b58eadbe
|
[
"MIT"
] | 1
|
2021-04-22T00:14:37.000Z
|
2021-04-22T00:14:37.000Z
|
from django.shortcuts import render
def home_page(request):
return render(request, 'mainsite/base.html')
| 22
| 48
| 0.772727
| 15
| 110
| 5.6
| 0.866667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.127273
| 110
| 5
| 48
| 22
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0.162162
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
14a3773884e1f7e48b779f436a61c80a60e86387
| 611
|
py
|
Python
|
academicstoday/shared_foundation/models/__init__.py
|
MikaSoftware/academicstoday-paas-django
|
cf58cf216d377ea97a2676cd594f96fb9d602a46
|
[
"BSD-3-Clause"
] | null | null | null |
academicstoday/shared_foundation/models/__init__.py
|
MikaSoftware/academicstoday-paas-django
|
cf58cf216d377ea97a2676cd594f96fb9d602a46
|
[
"BSD-3-Clause"
] | 6
|
2020-06-05T17:54:00.000Z
|
2022-03-11T23:18:41.000Z
|
academicstoday/shared_foundation/models/__init__.py
|
MikaSoftware/academicstoday-paas-django
|
cf58cf216d377ea97a2676cd594f96fb9d602a46
|
[
"BSD-3-Clause"
] | 2
|
2020-05-01T12:50:38.000Z
|
2021-07-17T09:51:12.000Z
|
from shared_foundation.models.user import SharedUser
from shared_foundation.models.abstract_thing import AbstractSharedThing
from shared_foundation.models.abstract_contact_point import AbstractSharedContactPoint
from shared_foundation.models.abstract_postal_address import AbstractSharedPostalAddress
from shared_foundation.models.abstract_geo_coorindate import AbstractSharedGeoCoordinate
from shared_foundation.models.opening_hours_specification import SharedOpeningHoursSpecification
from shared_foundation.models.academy import SharedAcademy
from shared_foundation.models.academy import SharedAcademyDomain
| 67.888889
| 96
| 0.92144
| 65
| 611
| 8.4
| 0.4
| 0.14652
| 0.29304
| 0.380952
| 0.391941
| 0.142857
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052373
| 611
| 8
| 97
| 76.375
| 0.943005
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
14a68e70ad27bf356da0147f51f73048d16f128a
| 320
|
py
|
Python
|
tests/conftest.py
|
vsevdrob/nft-brownie-ipfs-pinata-hashlips
|
32080aa0eca2ee3143e1845adf0a246bbe148192
|
[
"MIT"
] | 2
|
2022-03-06T21:14:58.000Z
|
2022-03-16T00:22:22.000Z
|
tests/conftest.py
|
webdriedesign/nft-brownie-ipfs-pinata-hashlips
|
32080aa0eca2ee3143e1845adf0a246bbe148192
|
[
"MIT"
] | 2
|
2022-03-17T00:53:53.000Z
|
2022-03-17T00:59:20.000Z
|
tests/conftest.py
|
webdriedesign/nft-brownie-ipfs-pinata-hashlips
|
32080aa0eca2ee3143e1845adf0a246bbe148192
|
[
"MIT"
] | 1
|
2022-03-06T21:08:22.000Z
|
2022-03-06T21:08:22.000Z
|
import pytest
from scripts.collectible.config import COLLECTIBLE
from web3 import Web3
@pytest.fixture
def get_sale_price():
return Web3.toWei(32.11, "ether") # assumming in MATIC token.
@pytest.fixture
def get_royalty_amount():
return (Web3.toWei(32.11, "ether") * COLLECTIBLE["royalty_fraction"]) / 10000
| 22.857143
| 81
| 0.75
| 44
| 320
| 5.340909
| 0.568182
| 0.110638
| 0.13617
| 0.161702
| 0.204255
| 0.204255
| 0
| 0
| 0
| 0
| 0
| 0.061594
| 0.1375
| 320
| 13
| 82
| 24.615385
| 0.789855
| 0.078125
| 0
| 0.222222
| 0
| 0
| 0.088737
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| true
| 0
| 0.333333
| 0.222222
| 0.777778
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
210cc141dabde7ac36832eff5db65315a0d5ccaa
| 69
|
py
|
Python
|
src/github/models/issue_comment.py
|
isabella232/SGTM
|
3793d78e99f89e5f73bac5c44f9d8a18cac75fbf
|
[
"MIT"
] | 8
|
2020-12-05T00:13:03.000Z
|
2022-01-11T11:35:51.000Z
|
src/github/models/issue_comment.py
|
Asana/SGTM
|
0e9e236980ed68e80e021470da6374945bbac501
|
[
"MIT"
] | 12
|
2020-12-14T18:21:21.000Z
|
2022-03-29T17:06:20.000Z
|
src/github/models/issue_comment.py
|
isabella232/SGTM
|
3793d78e99f89e5f73bac5c44f9d8a18cac75fbf
|
[
"MIT"
] | 2
|
2021-06-27T09:32:55.000Z
|
2022-02-27T23:17:36.000Z
|
from .comment import Comment
class IssueComment(Comment):
pass
| 11.5
| 28
| 0.753623
| 8
| 69
| 6.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.188406
| 69
| 5
| 29
| 13.8
| 0.928571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
214bb33e46466b7720a734bf7b0760780deac507
| 6,127
|
py
|
Python
|
backend/tests/test_k8s_app.py
|
bakdata/streams-explorer
|
4d84fc70067bb9ec27d1a26e3ca93c142417db0e
|
[
"MIT"
] | 24
|
2021-02-17T16:29:07.000Z
|
2022-01-03T05:13:31.000Z
|
backend/tests/test_k8s_app.py
|
bakdata/streams-explorer
|
4d84fc70067bb9ec27d1a26e3ca93c142417db0e
|
[
"MIT"
] | 116
|
2021-02-03T08:44:27.000Z
|
2022-03-22T09:50:03.000Z
|
backend/tests/test_k8s_app.py
|
bakdata/streams-explorer
|
4d84fc70067bb9ec27d1a26e3ca93c142417db0e
|
[
"MIT"
] | 2
|
2021-04-06T15:34:37.000Z
|
2021-05-14T16:52:44.000Z
|
from streams_explorer.core.k8s_app import K8sApp, K8sAppDeployment, K8sAppStatefulSet
from streams_explorer.core.k8s_config_parser import StreamsBootstrapArgsParser
from tests.utils import (
ConfigType,
get_streaming_app_deployment,
get_streaming_app_stateful_set,
)
class TestK8sApp:
def test_parse_env(self):
k8s_objects = [
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
),
get_streaming_app_stateful_set(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
),
]
k8s_apps = [K8sApp.factory(k8s_object) for k8s_object in k8s_objects]
for k8s_app in k8s_apps:
assert k8s_app.name == "test-app"
assert k8s_app.error_topic == "error-topic"
assert k8s_app.output_topic == "output-topic"
assert k8s_app.input_topics == ["input-topic"]
assert isinstance(k8s_apps[0], K8sAppDeployment)
assert isinstance(k8s_apps[1], K8sAppStatefulSet)
assert k8s_apps[1].get_service_name() == "test-service"
def test_parse_args(self, monkeypatch):
monkeypatch.setattr(
"streams_explorer.core.k8s_app.config_parser", StreamsBootstrapArgsParser
)
k8s_objects = [
get_streaming_app_deployment(
config_type=ConfigType.ARGS,
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
),
get_streaming_app_stateful_set(
config_type=ConfigType.ARGS,
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
),
]
k8s_apps = [K8sApp.factory(k8s_object) for k8s_object in k8s_objects]
for k8s_app in k8s_apps:
assert k8s_app.name == "test-app"
assert k8s_app.error_topic == "error-topic"
assert k8s_app.output_topic == "output-topic"
assert k8s_app.input_topics == ["input-topic"]
assert isinstance(k8s_apps[0], K8sAppDeployment)
assert isinstance(k8s_apps[1], K8sAppStatefulSet)
assert k8s_apps[1].get_service_name() == "test-service"
def test_is_streams_bootstrap_app(self):
streams_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic=None,
)
)
assert streams_app.is_streams_bootstrap_app()
non_streams_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics=None,
output_topic=None,
error_topic=None,
)
)
assert not non_streams_app.is_streams_bootstrap_app()
def test_error_topic_undefined(self):
k8s_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic=None,
)
)
assert k8s_app.name == "test-app"
assert k8s_app.error_topic is None
assert k8s_app.output_topic == "output-topic"
assert k8s_app.input_topics == ["input-topic"]
def test_multiple_inputs(self):
k8s_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic1,input-topics2",
output_topic="output-topic",
error_topic="error-topic",
)
)
assert k8s_app.input_topics == ["input-topic1", "input-topics2"]
def test_env_prefix_support(self):
k8s_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
env_prefix="TEST_",
)
)
assert k8s_app.name == "test-app"
assert k8s_app.error_topic == "error-topic"
assert k8s_app.output_topic == "output-topic"
assert k8s_app.input_topics == ["input-topic"]
def test_extra_input_topics(self):
k8s_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
multiple_inputs="0=test1,1=test2",
env_prefix="TEST_",
)
)
assert k8s_app.extra_input_topics == ["test1", "test2"]
def test_extra_output_topics(self):
k8s_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
multiple_outputs="0=test1,1=test2",
env_prefix="TEST_",
)
)
assert k8s_app.extra_output_topics == ["test1", "test2"]
def test_attributes(self):
k8s_app = K8sAppDeployment(
get_streaming_app_deployment(
name="test-app",
input_topics="input-topic",
output_topic="output-topic",
error_topic="error-topic",
multiple_outputs="0=test1,1=test2",
env_prefix="TEST_",
pipeline="pipeline1",
)
)
assert k8s_app.attributes["pipeline"] == "pipeline1"
assert len(k8s_app.attributes) == 1
| 35.416185
| 85
| 0.567325
| 631
| 6,127
| 5.183835
| 0.10935
| 0.056863
| 0.122287
| 0.092938
| 0.83797
| 0.791501
| 0.754815
| 0.735249
| 0.722409
| 0.722409
| 0
| 0.023874
| 0.33687
| 6,127
| 172
| 86
| 35.622093
| 0.781196
| 0
| 0
| 0.658065
| 0
| 0
| 0.134323
| 0.011262
| 0
| 0
| 0
| 0
| 0.187097
| 1
| 0.058065
| false
| 0
| 0.019355
| 0
| 0.083871
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
216200890822db2ce4ae440cdf1cd862b5a822ad
| 213
|
py
|
Python
|
starlette/database/__init__.py
|
rajeev/starlette
|
7e1bfa8c01a697f95291b27cbe59fee5e3d35944
|
[
"BSD-3-Clause"
] | 2
|
2019-03-15T02:44:45.000Z
|
2019-04-29T04:25:17.000Z
|
starlette/database/__init__.py
|
cfhamlet/starlette
|
7e1bfa8c01a697f95291b27cbe59fee5e3d35944
|
[
"BSD-3-Clause"
] | null | null | null |
starlette/database/__init__.py
|
cfhamlet/starlette
|
7e1bfa8c01a697f95291b27cbe59fee5e3d35944
|
[
"BSD-3-Clause"
] | null | null | null |
from starlette.database.core import (
transaction,
DatabaseBackend,
DatabaseSession,
DatabaseTransaction,
)
__all__ = ["transaction", "DatabaseBackend", "DatabaseSession", "DatabaseTransaction"]
| 21.3
| 86
| 0.741784
| 14
| 213
| 11
| 0.714286
| 0.337662
| 0.532468
| 0.779221
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15493
| 213
| 9
| 87
| 23.666667
| 0.855556
| 0
| 0
| 0
| 0
| 0
| 0.28169
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 0
| 0.142857
| 0
| 1
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dce0e2b8cb162f450785e41f2bc6b7baee3b8b74
| 25
|
py
|
Python
|
scripts/tools/run/__init__.py
|
yixinliao/pytorch_connectomics
|
0f6de546e6da1e0f3258b2c84f7e16b3a993c70c
|
[
"MIT"
] | 1
|
2020-07-22T12:56:09.000Z
|
2020-07-22T12:56:09.000Z
|
scripts/tools/run/__init__.py
|
yixinliao/pytorch_connectomics
|
0f6de546e6da1e0f3258b2c84f7e16b3a993c70c
|
[
"MIT"
] | null | null | null |
scripts/tools/run/__init__.py
|
yixinliao/pytorch_connectomics
|
0f6de546e6da1e0f3258b2c84f7e16b3a993c70c
|
[
"MIT"
] | null | null | null |
from .run_slurm import *
| 12.5
| 24
| 0.76
| 4
| 25
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16
| 25
| 1
| 25
| 25
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
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