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4f6cdd0017f8c497e4643df0d01eea199daf5873 | zjuchenll/dataflow-multithreading-on-tia | tools/parameters/interconnect_parameters.py | [
"MIT"
] | Python | from_dictionary | <not_specific> | def from_dictionary(cls, dictionary):
"""
Instantiate an InterconnectParameters wrapper from a dictionary.
:param dictionary: loaded from a configuration file or elsewhere
:return: new InterconnectParameters instance
"""
# Filter the dictionary with only parameters necessary for the initializer.
key_filter_set = {"router_type",
"num_router_sources",
"num_router_destinations",
"num_input_channels",
"num_output_channels",
"router_buffer_depth",
"num_physical_planes"}
filtered_interconnect_dictionary = {key: dictionary[key] for key in key_filter_set}
# Unpack the dictionary into the initializer.
return cls(**filtered_interconnect_dictionary) |
Instantiate an InterconnectParameters wrapper from a dictionary.
:param dictionary: loaded from a configuration file or elsewhere
:return: new InterconnectParameters instance
| Instantiate an InterconnectParameters wrapper from a dictionary. | [
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] | def from_dictionary(cls, dictionary):
key_filter_set = {"router_type",
"num_router_sources",
"num_router_destinations",
"num_input_channels",
"num_output_channels",
"router_buffer_depth",
"num_physical_planes"}
filtered_interconnect_dictionary = {key: dictionary[key] for key in key_filter_set}
return cls(**filtered_interconnect_dictionary) | [
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],
"outlier_params": [],
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} | def from_dictionary(cls, dictionary):
key_filter_set = {"router_type",
"num_router_sources",
"num_router_destinations",
"num_input_channels",
"num_output_channels",
"router_buffer_depth",
"num_physical_planes"}
filtered_interconnect_dictionary = {key: dictionary[key] for key in key_filter_set}
return cls(**filtered_interconnect_dictionary) | 109 | 942 |
2afd93bd348a4c24ebc88321858edb1334f39b73 | formalabstracts/CNL-CIC | 2parser/primitive.py | [
"MIT"
] | Python | line | <not_specific> | def line(etok):
"""String giving the starting line number of Etok."""
raw = etok.raw
if raw:
return f'line={raw[0].lineno}.'
return '' | String giving the starting line number of Etok. | String giving the starting line number of Etok. | [
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raw = etok.raw
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} | def line(etok):
raw = etok.raw
if raw:
return f'line={raw[0].lineno}.'
return '' | 111 | 71 |
033c246f3c0efded7a0f6eb2fcfd6c78a07f462f | SolarSPELL-Main/DLMS | build_automation/content_management/utils.py | [
"MIT"
] | Python | calc_sha256 | <not_specific> | def calc_sha256(input_file):
"""
Calculate the SHA-256 checksum for the given file object.
:param input_file: Input file for which the SHA-256 should be calculated.
"""
sha256_ctxt = hashlib.sha256()
bytes_data = input_file.read(4096)
while bytes_data != b"":
sha256_ctxt.update(bytes_data)
bytes_data = input_file.read(4096)
input_file.seek(0)
return sha256_ctxt.hexdigest() |
Calculate the SHA-256 checksum for the given file object.
:param input_file: Input file for which the SHA-256 should be calculated.
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sha256_ctxt = hashlib.sha256()
bytes_data = input_file.read(4096)
while bytes_data != b"":
sha256_ctxt.update(bytes_data)
bytes_data = input_file.read(4096)
input_file.seek(0)
return sha256_ctxt.hexdigest() | [
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"outlier_params": [],
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def calc_sha256(input_file):
sha256_ctxt = hashlib.sha256()
bytes_data = input_file.read(4096)
while bytes_data != b"":
sha256_ctxt.update(bytes_data)
bytes_data = input_file.read(4096)
input_file.seek(0)
return sha256_ctxt.hexdigest() | 112 | 224 |
42dfe57cceb6f27b443b2c64f85015fa20cf635d | MatteoLacki/rta | rta/preprocessing.py | [
"BSD-2-Clause"
] | Python | split | <not_specific> | def split(L, cond):
"""Split the DataFrame accoring to the count in the condition.
Things with cond > 1 are wrong, == 1 are right.
"""
wrong = L[ L.index.isin(cond[cond > 1].index) ]
good = L[ L.index.isin(cond[cond == 1].index) ]
return good, wrong | Split the DataFrame accoring to the count in the condition.
Things with cond > 1 are wrong, == 1 are right.
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Things with cond > 1 are wrong, == 1 are right. | [
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wrong = L[ L.index.isin(cond[cond > 1].index) ]
good = L[ L.index.isin(cond[cond == 1].index) ]
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} | def split(L, cond):
wrong = L[ L.index.isin(cond[cond > 1].index) ]
good = L[ L.index.isin(cond[cond == 1].index) ]
return good, wrong | 113 | 620 |
a961d896c6e2d71c24a99ad719aecf084c13e02f | Salazar769/Ciclo-1-python | modulo.py | [
"CC0-1.0"
] | Python | modificarHorario | <not_specific> | def modificarHorario(dataFrame, cursoPorCambiar, listaPeriodosNuevos):
"""Esta funcion recibe el dataframe en uso, el nombre del curso a modificar y la lista de periodos va a ocupar ahora el curso.
retorna el dataframe actualizado
"""
indices = dataFrame["Cursos"].to_list()
posicionPorCambiar = indices.index(cursoPorCambiar)
periodosDisponibles = ["","Per1","Per2","Per3","Per4","Per5","Per6","Per7","Per8","Per9","Per10","Per11","Per12","Per13","Per14","Per15","Per16","Per17","Per18","Per19","Per20","Per21","Per22","Per23","Per24","Per25","Per26","Per27","Per28","Per29","Per30","Per31","Per32","Per33","Per34","Per35","Per36","Per37","Per38","Per39","Per40","Per41","Per42","Per43","Per44","Per45","Per46","Per47","Per48","Per49","Per50"]
size = len(dataFrame) #cantidad de cursos actuales
nuevo = [True if i in listaPeriodosNuevos else False for i in periodosDisponibles]
nuevo[0] = cursoPorCambiar
dataFrame.loc[posicionPorCambiar]= nuevo
return dataFrame | Esta funcion recibe el dataframe en uso, el nombre del curso a modificar y la lista de periodos va a ocupar ahora el curso.
retorna el dataframe actualizado
| Esta funcion recibe el dataframe en uso, el nombre del curso a modificar y la lista de periodos va a ocupar ahora el curso.
retorna el dataframe actualizado | [
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indices = dataFrame["Cursos"].to_list()
posicionPorCambiar = indices.index(cursoPorCambiar)
periodosDisponibles = ["","Per1","Per2","Per3","Per4","Per5","Per6","Per7","Per8","Per9","Per10","Per11","Per12","Per13","Per14","Per15","Per16","Per17","Per18","Per19","Per20","Per21","Per22","Per23","Per24","Per25","Per26","Per27","Per28","Per29","Per30","Per31","Per32","Per33","Per34","Per35","Per36","Per37","Per38","Per39","Per40","Per41","Per42","Per43","Per44","Per45","Per46","Per47","Per48","Per49","Per50"]
size = len(dataFrame)
nuevo = [True if i in listaPeriodosNuevos else False for i in periodosDisponibles]
nuevo[0] = cursoPorCambiar
dataFrame.loc[posicionPorCambiar]= nuevo
return dataFrame | [
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indices = dataFrame["Cursos"].to_list()
posicionPorCambiar = indices.index(cursoPorCambiar)
periodosDisponibles = ["","Per1","Per2","Per3","Per4","Per5","Per6","Per7","Per8","Per9","Per10","Per11","Per12","Per13","Per14","Per15","Per16","Per17","Per18","Per19","Per20","Per21","Per22","Per23","Per24","Per25","Per26","Per27","Per28","Per29","Per30","Per31","Per32","Per33","Per34","Per35","Per36","Per37","Per38","Per39","Per40","Per41","Per42","Per43","Per44","Per45","Per46","Per47","Per48","Per49","Per50"]
size = len(dataFrame)
nuevo = [True if i in listaPeriodosNuevos else False for i in periodosDisponibles]
nuevo[0] = cursoPorCambiar
dataFrame.loc[posicionPorCambiar]= nuevo
return dataFrame | 114 | 895 |
f8de74c6b919b82dc36f8903246956eae4e00749 | vincefn/pyvkfft | pyvkfft/scripts/pyvkfft_test.py | [
"MIT"
] | Python | name_next_file | <not_specific> | def name_next_file(pattern="pyvkfft-test%04d.html"):
"""
Find the first unused name for a file, starting at i=1
:param pattern: the pattern for the file name.
:return: the filename
"""
lsdir = os.listdir()
for i in range(1001, 1999):
if pattern % i not in lsdir:
return pattern % i
raise RuntimeError("name_next_file: '%s' files all used from 1001 to 1998. Maybe cleanup ?" % pattern) |
Find the first unused name for a file, starting at i=1
:param pattern: the pattern for the file name.
:return: the filename
| Find the first unused name for a file, starting at i=1 | [
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lsdir = os.listdir()
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if pattern % i not in lsdir:
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} | import os
def name_next_file(pattern="pyvkfft-test%04d.html"):
lsdir = os.listdir()
for i in range(1001, 1999):
if pattern % i not in lsdir:
return pattern % i
raise RuntimeError("name_next_file: '%s' files all used from 1001 to 1998. Maybe cleanup ?" % pattern) | 115 | 322 |
87ca097a645b48edbcefcb038c230c6a4ea137ee | mustafaneguib/spatial-information-programming-analysis-project | assign2_modules.py | [
"BSD-4-Clause-UC"
] | Python | build_html_component_without_title | <not_specific> | def build_html_component_without_title(html_string):
"""
This function builds the html string for a component.
:param html_string: html_string of the component
:param title: Title of the html component
:return: html_string
"""
html = """
<div class="row">
<div class="col-md-12">
<p>
{0}
</p>
</div>
</div>
""".format(html_string)
return html |
This function builds the html string for a component.
:param html_string: html_string of the component
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""".format(html_string)
return html | 116 | 220 |
2b83d531db3363cb8d16823e0c9f3d9d8932e3b2 | diego-hermida/ClimateChangeApp | telegram_bot/main.py | [
"MIT"
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"""
Given an 'str' object, wraps it between ANSI green & bold escape characters.
:param msg: Message to be wrapped.
:return: The same message, which will be displayed as green & bold by the terminal.
"""
return '\u001b[1;32m%s\u001b[0m' % msg |
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a54be27a4d3b2dfecd26b39462bcf25d1e591fc7 | ClimateCompatibleGrowth/scorm_package | src/scorm_package/scorm.py | [
"MIT"
] | Python | retrieve_file_paths | <not_specific> | def retrieve_file_paths(dirName):
"""
Retrieves the filepath for the directory being zipped.
"""
# setup file paths variable
filePaths = []
# Read all directory, subdirectories and file lists
for root, _, files in os.walk(dirName):
for filename in files:
# Create the full filepath by using os module.
filePath = os.path.join(root, filename)
filePaths.append(filePath)
# return all paths
return filePaths |
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return filePaths | 118 | 270 |
6bf0b7f3f63f9cea47b6089d3a52bb5325a16bfa | mernst/cozy | cozy/common.py | [
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"""
Returns a FrameInfo object describing the caller of the function that
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You might care about these properties of the FrameInfo object:
.filename
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.lineno
The `up` parameter can be used to look farther up the call stack. For
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"""
stack = inspect.stack()
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return stack[up+2] | 119 | 503 |
399facab691f0c8d28ecb51ef347628b1d95e281 | cobymc/altimeter | altimeter/core/resource/resource_spec.py | [
"MIT"
] | Python | generate_id | str | def generate_id(
cls: Type["ResourceSpec"], short_resource_id: str, context: Dict[str, Any]
) -> str:
"""Generate a full id for this type given a short_resource_id.
Args:
short_resource_id: short resource id for this resource
context: contains auxiliary information which can be passed through the parse process.
Returns:
full resource id string
"""
return f"{cls.type_name}:{short_resource_id}" | Generate a full id for this type given a short_resource_id.
Args:
short_resource_id: short resource id for this resource
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full resource id string
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eccc77c5d424c27701a538e4bc03a9dba7e2a7f4 | brutalic/pynet_brutal | class6/library/eos_switchport.py | [
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"""Creates a new instance of switchport on the node
"""
name = module.attributes['name']
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c5e6c8821a5dd9fd84b67c0b3853decddb290e9e | balanced/billy | billy/utils/generic.py | [
"MIT"
] | Python | round_down_cent | <not_specific> | def round_down_cent(amount):
"""Round down money value in cent (drop float points), for example, 5.66666
cents will be rounded to 5 cents
:param amount: the money amount in cent to be rounded
:return: the rounded money amount
"""
return int(amount) | Round down money value in cent (drop float points), for example, 5.66666
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15f69d04b5582c34498855c2b7321daab237bb7d | MSLNZ/GTC | GTC/function.py | [
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] | Python | complex_to_seq | <not_specific> | def complex_to_seq(z):
"""Transform a complex number into a 4-element sequence
:arg z: a number
If ``z = x + yj``, then an array of the form ``[[x,-y],[y,x]]``
can be used to represent ``z`` in matrix computations.
**Examples**::
>>> import numpy
>>> z = 1 + 2j
>>> function.complex_to_seq(z)
(1.0, -2.0, 2.0, 1.0)
>>> m = numpy.array( function.complex_to_seq(z) )
>>> m.shape = (2,2)
>>> print( m )
[[ 1. -2.]
[ 2. 1.]]
"""
z = complex(z)
return (z.real,-z.imag,z.imag,z.real) | Transform a complex number into a 4-element sequence
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>>> m.shape = (2,2)
>>> print( m )
[[ 1. -2.]
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z = complex(z)
return (z.real,-z.imag,z.imag,z.real) | 124 | 247 |
fd1a8736f23ff155b16658aaea6e727940d557a3 | keatonb/astropy | astropy/utils/parsing.py | [
"BSD-3-Clause"
] | Python | _patch_get_caller_module_dict | <not_specific> | def _patch_get_caller_module_dict(module):
"""Temporarily replace the module's get_caller_module_dict.
This is a function inside ``ply.lex`` and ``ply.yacc`` (each has a copy)
that is used to retrieve the caller's local symbols. Here, we patch the
function to instead retrieve the grandparent's local symbols to account
for a wrapper layer.
"""
original = module.get_caller_module_dict
@functools.wraps(original)
def wrapper(levels):
# Add 2, not 1, because the wrapper itself adds another level
return original(levels + 2)
module.get_caller_module_dict = wrapper
yield
module.get_caller_module_dict = original | Temporarily replace the module's get_caller_module_dict.
This is a function inside ``ply.lex`` and ``ply.yacc`` (each has a copy)
that is used to retrieve the caller's local symbols. Here, we patch the
function to instead retrieve the grandparent's local symbols to account
for a wrapper layer.
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original = module.get_caller_module_dict
@functools.wraps(original)
def wrapper(levels):
return original(levels + 2)
module.get_caller_module_dict = wrapper
yield
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def _patch_get_caller_module_dict(module):
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def wrapper(levels):
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module.get_caller_module_dict = original | 125 | 10 |
dad41c3a739529e7e8fe74ae8ee23579c2f82d3f | ankhoudary12/covid19_etl | dags/covid_19_etl.py | [
"MIT"
] | Python | clear_local_raw_covid_data | None | def clear_local_raw_covid_data(path: str) -> None:
"""Clear raw covid csvs from specified path.
Args:
path (str): path to delete files
"""
files = os.listdir(path)
if files:
for file in files:
os.remove(os.path.join(path, file)) | Clear raw covid csvs from specified path.
Args:
path (str): path to delete files
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def clear_local_raw_covid_data(path: str) -> None:
files = os.listdir(path)
if files:
for file in files:
os.remove(os.path.join(path, file)) | 126 | 671 |
079e8d8d31269aeb014b278ab5096adb8d48f46b | slavesocieties/ssda-nlp | ssda_nlp/relationships.py | [
"MIT"
] | Python | build_new_person | <not_specific> | def build_new_person(people_df, next_id, person_type):
'''
appends a row representing a new person to an existing people df
people_df: df containing all entities labeled as people in the entry with unique ids
volume_metadata: metadata for the volume that the entry comes from, built by retrieve_volume_metadata
person_type: type of person being added, e.g. "principal" or "cleric"
returns: updated df with new person added and updated next available id
'''
curr_entry = next_id[next_id.find('-') + 1:next_id.find('P') - 1]
person_name = "Unknown " + person_type
person_number = next_id[next_id.find('P') + 1:]
person_number = int(person_number)
people_df = people_df.append({"entry_no": curr_entry, "pred_entity": person_name, "pred_label": "PER", "unique_id": next_id}, ignore_index=True)
next_id = next_id[:next_id.find('P') + 1] + str(person_number + 1)
return people_df, next_id |
appends a row representing a new person to an existing people df
people_df: df containing all entities labeled as people in the entry with unique ids
volume_metadata: metadata for the volume that the entry comes from, built by retrieve_volume_metadata
person_type: type of person being added, e.g. "principal" or "cleric"
returns: updated df with new person added and updated next available id
| appends a row representing a new person to an existing people df
people_df: df containing all entities labeled as people in the entry with unique ids
volume_metadata: metadata for the volume that the entry comes from, built by retrieve_volume_metadata
person_type: type of person being added, e.g. "principal" or "cleric"
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person_name = "Unknown " + person_type
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person_number = int(person_number)
people_df = people_df.append({"entry_no": curr_entry, "pred_entity": person_name, "pred_label": "PER", "unique_id": next_id}, ignore_index=True)
next_id = next_id[:next_id.find('P') + 1] + str(person_number + 1)
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person_name = "Unknown " + person_type
person_number = next_id[next_id.find('P') + 1:]
person_number = int(person_number)
people_df = people_df.append({"entry_no": curr_entry, "pred_entity": person_name, "pred_label": "PER", "unique_id": next_id}, ignore_index=True)
next_id = next_id[:next_id.find('P') + 1] + str(person_number + 1)
return people_df, next_id | 127 | 111 |
26dd55b6a0f612234e711d2e9da51f482146a66d | ian-bartholomew/machine-learning | classification/decision_tree/decision_tree_binary.py | [
"MIT"
] | Python | error_reduction | <not_specific> | def error_reduction(error_before_split, error_after_split):
"""
Purpose: Compute the difference between error before and after split
Input : Error before split and error after split
Output : Difference between error before and after split
"""
return (error_before_split - error_after_split) |
Purpose: Compute the difference between error before and after split
Input : Error before split and error after split
Output : Difference between error before and after split
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c5a885594689cfda35e49a7fad738e21e2d73d02 | aweandreverence/django-htk | utils/data_structures/general.py | [
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] | Python | filter_dict | <not_specific> | def filter_dict(d, keys):
"""Returns a subset of dictionary `d` with keys from `keys`
"""
filtered = {}
for key in keys:
filtered[key] = d.get(key)
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return filtered | 129 | 47 |
8fa90889cd9fae41026d28fea6f8322c68e01fb2 | PhilippJunk/homelette | homelette/routines.py | [
"MIT"
] | Python | _remove_files | None | def _remove_files(*args: str) -> None:
'''
Remove files given after modelling procedure.
Called by Children classes after model generation in order to clean up
temporary files or unneccessary output files.
Uses glob.glob internally and can therefore handle wildcards.
Parameters
----------
*args : str
Filenames or queries for filenames that will be deleted.
Returns
-------
None
'''
for query in args:
for file in glob.glob(query):
os.remove(file) |
Remove files given after modelling procedure.
Called by Children classes after model generation in order to clean up
temporary files or unneccessary output files.
Uses glob.glob internally and can therefore handle wildcards.
Parameters
----------
*args : str
Filenames or queries for filenames that will be deleted.
Returns
-------
None
| Remove files given after modelling procedure.
Called by Children classes after model generation in order to clean up
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Uses glob.glob internally and can therefore handle wildcards.
Parameters
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Filenames or queries for filenames that will be deleted.
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3707dc49c15865574597d3e7688934cb1492836f | mrbot-ai/deep_qa | deep_qa/data/instances/text_classification/tuple_instance.py | [
"Apache-2.0"
] | Python | read_from_line | <not_specific> | def read_from_line(cls, line: str):
"""
Reads a TupleInstances from a line. The format has one of four options:
(1) [subject]###[predicate]###[object1]...
(2) [sentence index][tab][subject]###[predicate]###[object1]...
(3) [subject]###[predicate]###[object1]...[tab][label]
(4) [sentence index][tab][subject]###[predicate]###[object1]...[tab][label]
Objects are optional, and can vary in number. This makes the acceptable number of slots per
tuple, 2 or more.
"""
fields = line.split("\t")
if len(fields) == 1:
# Case 1
tuple_string = fields[0]
index = None
label = None
elif len(fields) == 2:
if fields[0].isdigit():
# Case 2
index = int(fields[0])
tuple_string = fields[1]
label = None
else:
# Case 3
tuple_string = fields[0]
index = None
label = fields[2].strip() == "1"
else:
# Case 4
index = int(fields[0])
tuple_string = fields[1]
label = fields[2].strip() == "1"
tuple_fields = tuple_string.split('###')
if len(tuple_fields) < 2:
raise RuntimeError("Unexpected number of fields in tuple: " + tuple_string)
return cls(tuple_fields, label=label, index=index) |
Reads a TupleInstances from a line. The format has one of four options:
(1) [subject]###[predicate]###[object1]...
(2) [sentence index][tab][subject]###[predicate]###[object1]...
(3) [subject]###[predicate]###[object1]...[tab][label]
(4) [sentence index][tab][subject]###[predicate]###[object1]...[tab][label]
Objects are optional, and can vary in number. This makes the acceptable number of slots per
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| Reads a TupleInstances from a line.
Objects are optional, and can vary in number. This makes the acceptable number of slots per
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index = None
label = None
elif len(fields) == 2:
if fields[0].isdigit():
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tuple_fields = tuple_string.split('###')
if len(tuple_fields) < 2:
raise RuntimeError("Unexpected number of fields in tuple: " + tuple_string)
return cls(tuple_fields, label=label, index=index) | [
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fields = line.split("\t")
if len(fields) == 1:
tuple_string = fields[0]
index = None
label = None
elif len(fields) == 2:
if fields[0].isdigit():
index = int(fields[0])
tuple_string = fields[1]
label = None
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tuple_string = fields[0]
index = None
label = fields[2].strip() == "1"
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index = int(fields[0])
tuple_string = fields[1]
label = fields[2].strip() == "1"
tuple_fields = tuple_string.split('###')
if len(tuple_fields) < 2:
raise RuntimeError("Unexpected number of fields in tuple: " + tuple_string)
return cls(tuple_fields, label=label, index=index) | 131 | 756 |
a50c6a0056a6b4fd3f66568c6d36a3bbd51b0dd9 | bce-toolkit/BCE | bce/logic/balancer/model.py | [
"BSD-3-Clause"
] | Python | _convert_unknown_id_to_symbol | <not_specific> | def _convert_unknown_id_to_symbol(unknown_id):
"""Get the symbol of an unknown.
:type unknown_id: int
:param unknown_id: The ID of the unknown.
:rtype : str
:return: The symbol.
"""
# If the |unknown_id| is zero, just returns |PROTECT_HEADER|a.
if unknown_id == 0:
return "a"
# Initialize alphabet table.
ch_table = "abcdefghijklmnopqrstuvwxyz"
ch_table_len = len(ch_table)
# Convert decimal to 26 ary.
cur_id = unknown_id
r = ""
while cur_id != 0:
r = ch_table[cur_id % ch_table_len] + r
cur_id = int(cur_id / ch_table_len)
return r | Get the symbol of an unknown.
:type unknown_id: int
:param unknown_id: The ID of the unknown.
:rtype : str
:return: The symbol.
| Get the symbol of an unknown. | [
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if unknown_id == 0:
return "a"
ch_table = "abcdefghijklmnopqrstuvwxyz"
ch_table_len = len(ch_table)
cur_id = unknown_id
r = ""
while cur_id != 0:
r = ch_table[cur_id % ch_table_len] + r
cur_id = int(cur_id / ch_table_len)
return r | [
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],
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if unknown_id == 0:
return "a"
ch_table = "abcdefghijklmnopqrstuvwxyz"
ch_table_len = len(ch_table)
cur_id = unknown_id
r = ""
while cur_id != 0:
r = ch_table[cur_id % ch_table_len] + r
cur_id = int(cur_id / ch_table_len)
return r | 132 | 700 |
1fe799da6cddb25113e43e0da619a723468d1013 | logr4y/tgscrape | tgscrape.py | [
"MIT"
] | Python | guess_if_last | <not_specific> | def guess_if_last(lmsg):
"""Guesses if message is the last one in a group"""
msg_day = lmsg['datetime'].split('T')[0]
msg_day = datetime.datetime.strptime(msg_day, '%Y-%m-%d')
check_day = datetime.datetime.today() - datetime.timedelta(days=1)
if msg_day >= check_day:
return True
return False | Guesses if message is the last one in a group | Guesses if message is the last one in a group | [
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msg_day = lmsg['datetime'].split('T')[0]
msg_day = datetime.datetime.strptime(msg_day, '%Y-%m-%d')
check_day = datetime.datetime.today() - datetime.timedelta(days=1)
if msg_day >= check_day:
return True
return False | [
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def guess_if_last(lmsg):
msg_day = lmsg['datetime'].split('T')[0]
msg_day = datetime.datetime.strptime(msg_day, '%Y-%m-%d')
check_day = datetime.datetime.today() - datetime.timedelta(days=1)
if msg_day >= check_day:
return True
return False | 133 | 205 |
3107f63b7aef96fe1421e4ac30a8e7b0303215c7 | ByRellex/sinstruments | sinstruments/simulators/icepap.py | [
"MIT"
] | Python | _cmd_result | <not_specific> | def _cmd_result(cmd_match):
"""retrieve the command error message prefix from the command line"""
groups = cmd_match.groupdict()
# replace None values with ''
groups_str = dict([(k, ("" if v is None else v)) for k, v in groups.items()])
groups_str["instr"] = groups_str["instr"].upper()
cmd_err = "{addr}{broadcast}{is_query}{instr}".format(**groups_str)
return cmd_err | retrieve the command error message prefix from the command line | retrieve the command error message prefix from the command line | [
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groups = cmd_match.groupdict()
groups_str = dict([(k, ("" if v is None else v)) for k, v in groups.items()])
groups_str["instr"] = groups_str["instr"].upper()
cmd_err = "{addr}{broadcast}{is_query}{instr}".format(**groups_str)
return cmd_err | [
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groups_str["instr"] = groups_str["instr"].upper()
cmd_err = "{addr}{broadcast}{is_query}{instr}".format(**groups_str)
return cmd_err | 134 | 934 |
5acf79fa3353bf8da526d4e500f619b0a8ab92e9 | RhuaYuri/radio | projeto_pesquisa/Lib/site-packages/flyingcircus/base.py | [
"MIT"
] | Python | median | <not_specific> | def median(
seq,
force_sort=True):
"""
Compute the median of a numeric sequence.
For iterative computation see:
- `flyingcircus.next_median()`
- `flyingcircus.next_medoid_and_median()`
- `flyingcircus.i_median()`
- `flyingcircus.i_medoid_and_median()`
- `flyingcircus.i_median_and_median_abs_dev()`
This is roughly comparable to `statistics.median()`.
If more than one among median, medoid, quantile, quantiloid is needed,
it is more efficient to sort the items prior to calling and then
perform the multiple required calle with `force_sort` set to False.
Args:
seq (Sequence[Number]): The input items.
force_sort (bool): Force sorting of the input items.
If the items are already sorted, this can be safely set to False.
Otherwise, it should be set to True.
Returns:
result (Number): The median of the items.
Examples:
>>> items = range(0, 52, 2)
>>> median(items)
25.0
>>> statistics.median(items) == median(items)
True
See Also:
- flyingcircus.median_and_median_abs_dev()
- flyingcircus.next_median()
- flyingcircus.next_medoid_and_median()
- flyingcircus.i_median()
- flyingcircus.i_medoid_and_median()
- flyingcircus.i_median_and_median_abs_dev()
- flyingcircus.medoid()
- flyingcircus.quantile()
- flyingcircus.interquantilic_range()
- flyingcircus.sym_interquantilic_range()
- flyingcircus.median_abs_dev()
"""
n = len(seq)
i = n // 2
sorted_items = sorted(seq) if force_sort else seq
if not (n % 2) and sorted_items[i - 1] != sorted_items[i]:
median_ = (sorted_items[i - 1] + sorted_items[i]) / 2
else:
median_ = sorted_items[i]
return median_ |
Compute the median of a numeric sequence.
For iterative computation see:
- `flyingcircus.next_median()`
- `flyingcircus.next_medoid_and_median()`
- `flyingcircus.i_median()`
- `flyingcircus.i_medoid_and_median()`
- `flyingcircus.i_median_and_median_abs_dev()`
This is roughly comparable to `statistics.median()`.
If more than one among median, medoid, quantile, quantiloid is needed,
it is more efficient to sort the items prior to calling and then
perform the multiple required calle with `force_sort` set to False.
Args:
seq (Sequence[Number]): The input items.
force_sort (bool): Force sorting of the input items.
If the items are already sorted, this can be safely set to False.
Otherwise, it should be set to True.
Returns:
result (Number): The median of the items.
Examples:
>>> items = range(0, 52, 2)
>>> median(items)
25.0
>>> statistics.median(items) == median(items)
True
See Also:
- flyingcircus.median_and_median_abs_dev()
- flyingcircus.next_median()
- flyingcircus.next_medoid_and_median()
- flyingcircus.i_median()
- flyingcircus.i_medoid_and_median()
- flyingcircus.i_median_and_median_abs_dev()
- flyingcircus.medoid()
- flyingcircus.quantile()
- flyingcircus.interquantilic_range()
- flyingcircus.sym_interquantilic_range()
- flyingcircus.median_abs_dev()
| Compute the median of a numeric sequence.
This is roughly comparable to `statistics.median()`.
If more than one among median, medoid, quantile, quantiloid is needed,
it is more efficient to sort the items prior to calling and then
perform the multiple required calle with `force_sort` set to False. | [
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if not (n % 2) and sorted_items[i - 1] != sorted_items[i]:
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"\"\"\"\n Compute the median of a numeric sequence.\n\n For iterative computation see:\n - `flyingcircus.next_median()`\n - `flyingcircus.next_medoid_and_median()`\n - `flyingcircus.i_median()`\n - `flyingcircus.i_medoid_and_median()`\n - `flyingcircus.i_median_and_median_abs_dev()`\n\n This is roughly comparable to `statistics.median()`.\n\n If more than one among median, medoid, quantile, quantiloid is needed,\n it is more efficient to sort the items prior to calling and then\n perform the multiple required calle with `force_sort` set to False.\n\n Args:\n seq (Sequence[Number]): The input items.\n force_sort (bool): Force sorting of the input items.\n If the items are already sorted, this can be safely set to False.\n Otherwise, it should be set to True.\n\n Returns:\n result (Number): The median of the items.\n\n Examples:\n >>> items = range(0, 52, 2)\n >>> median(items)\n 25.0\n >>> statistics.median(items) == median(items)\n True\n\n See Also:\n - flyingcircus.median_and_median_abs_dev()\n - flyingcircus.next_median()\n - flyingcircus.next_medoid_and_median()\n - flyingcircus.i_median()\n - flyingcircus.i_medoid_and_median()\n - flyingcircus.i_median_and_median_abs_dev()\n - flyingcircus.medoid()\n - flyingcircus.quantile()\n - flyingcircus.interquantilic_range()\n - flyingcircus.sym_interquantilic_range()\n - flyingcircus.median_abs_dev()\n \"\"\""
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}
] | {
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"identifier": "seq",
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},
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"is_optional": false
}
],
"outlier_params": [],
"others": [
{
"identifier": "examples",
"docstring": null,
"docstring_tokens": [
"None"
]
}
]
} | def median(
seq,
force_sort=True):
n = len(seq)
i = n // 2
sorted_items = sorted(seq) if force_sort else seq
if not (n % 2) and sorted_items[i - 1] != sorted_items[i]:
median_ = (sorted_items[i - 1] + sorted_items[i]) / 2
else:
median_ = sorted_items[i]
return median_ | 135 | 131 |
a5b9563a7eb8e6b70fd19da335fda92520e4aadd | MPI-MAPSS/MAPSS | mapss/static/packages/arches/arches/app/utils/flatten_dict.py | [
"CC0-1.0"
] | Python | flatten_dict | <not_specific> | def flatten_dict(nested_dict, separator="_"):
"""
Flatten dict object with nested keys into a single level.
Args:
nested_dict: A nested dict object.
separator: a string used to denote hierarchical
Returns:
The flattened dict object if successful, None otherwise.
"""
out = {}
def flatten(x, name=""):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + separator)
elif type(x) is list:
i = 0
for a in x:
flatten(a, name + str(i) + separator)
i += 1
else:
out[name[:-1]] = x
flatten(nested_dict)
return out |
Flatten dict object with nested keys into a single level.
Args:
nested_dict: A nested dict object.
separator: a string used to denote hierarchical
Returns:
The flattened dict object if successful, None otherwise.
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] | def flatten_dict(nested_dict, separator="_"):
out = {}
def flatten(x, name=""):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + separator)
elif type(x) is list:
i = 0
for a in x:
flatten(a, name + str(i) + separator)
i += 1
else:
out[name[:-1]] = x
flatten(nested_dict)
return out | [
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],
"default": null,
"is_optional": null
}
],
"outlier_params": [],
"others": []
} | def flatten_dict(nested_dict, separator="_"):
out = {}
def flatten(x, name=""):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + separator)
elif type(x) is list:
i = 0
for a in x:
flatten(a, name + str(i) + separator)
i += 1
else:
out[name[:-1]] = x
flatten(nested_dict)
return out | 136 | 92 |
6deb97b7f83a3c2505dff29dbe9b8f02a411e7f2 | ftnext/python-as-pyconjp-staff | timetable_maker/main.py | [
"MIT"
] | Python | handle_existing_worksheet | <not_specific> | def handle_existing_worksheet(spreadsheet, worksheet_name, do_overwrite):
"""Return worksheet when overwrite, otherwise stash and return None"""
worksheet = spreadsheet.worksheet(worksheet_name)
if do_overwrite:
worksheet.clear()
return worksheet
new_title = f"{worksheet_name}_stash_{datetime.now():%Y%m%d_%H%M%S}"
worksheet.update_title(new_title)
return None | Return worksheet when overwrite, otherwise stash and return None | Return worksheet when overwrite, otherwise stash and return None | [
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] | def handle_existing_worksheet(spreadsheet, worksheet_name, do_overwrite):
worksheet = spreadsheet.worksheet(worksheet_name)
if do_overwrite:
worksheet.clear()
return worksheet
new_title = f"{worksheet_name}_stash_{datetime.now():%Y%m%d_%H%M%S}"
worksheet.update_title(new_title)
return None | [
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}
],
"outlier_params": [],
"others": []
} | import datetime
def handle_existing_worksheet(spreadsheet, worksheet_name, do_overwrite):
worksheet = spreadsheet.worksheet(worksheet_name)
if do_overwrite:
worksheet.clear()
return worksheet
new_title = f"{worksheet_name}_stash_{datetime.now():%Y%m%d_%H%M%S}"
worksheet.update_title(new_title)
return None | 139 | 926 |
2ba5cb3b10e94082f14c51c17f6d4f9cc693c19b | buffbob/titanic | src/titanic/go1_utils.py | [
"MIT"
] | Python | process_digit_data | <not_specific> | def process_digit_data(df):
"""
df(a DataFrame) is num x 784
scale and convert to num x 28 x 28
return an array
"""
df = df/255
vals = df.values.reshape(-1,28,28,1)
return vals |
df(a DataFrame) is num x 784
scale and convert to num x 28 x 28
return an array
| df(a DataFrame) is num x 784
scale and convert to num x 28 x 28
return an array | [
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df = df/255
vals = df.values.reshape(-1,28,28,1)
return vals | [
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],
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} | def process_digit_data(df):
df = df/255
vals = df.values.reshape(-1,28,28,1)
return vals | 140 | 247 |
2dc10fa28137004d12712d67664389ed355f338e | Jeffro80/Convert_Expenses | convertExpenses.py | [
"CC-BY-3.0"
] | Python | weekly_to_annual | <not_specific> | def weekly_to_annual(weekly):
"""Convert weekly amount to annual cost.
Args:
weekly (float): Weekly cost.
Returns:
(float): Annual cost.
"""
return weekly * 52 | Convert weekly amount to annual cost.
Args:
weekly (float): Weekly cost.
Returns:
(float): Annual cost.
| Convert weekly amount to annual cost. | [
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] | def weekly_to_annual(weekly):
return weekly * 52 | [
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] | [
"\"\"\"Convert weekly amount to annual cost.\n \n Args:\n weekly (float): Weekly cost.\n \n Returns:\n (float): Annual cost.\n \"\"\""
] | [
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}
] | {
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}
],
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"default": null,
"is_optional": false
}
],
"outlier_params": [],
"others": []
} | def weekly_to_annual(weekly):
return weekly * 52 | 141 | 529 |
d24b56bd00d99dc1d7abe4594e5cfb75ce250077 | arccode/factory | py/test/fixture/arduino.py | [
"BSD-3-Clause"
] | Python | _Blink | null | def _Blink(arduino, times=1, interval_secs=0.1):
"""Blinks LED light in Arduino board.
This is an example of how to use ArduinoController object.
"""
for nth in range(times):
if nth:
time.sleep(interval_secs)
if not arduino.SendExpectReceive('H', 'H', retry=2):
raise Exception('Failed to send command "H"')
time.sleep(interval_secs)
if not arduino.SendExpectReceive('L', 'L', retry=2):
raise Exception('Failed to send command "L"') | Blinks LED light in Arduino board.
This is an example of how to use ArduinoController object.
| Blinks LED light in Arduino board.
This is an example of how to use ArduinoController object. | [
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for nth in range(times):
if nth:
time.sleep(interval_secs)
if not arduino.SendExpectReceive('H', 'H', retry=2):
raise Exception('Failed to send command "H"')
time.sleep(interval_secs)
if not arduino.SendExpectReceive('L', 'L', retry=2):
raise Exception('Failed to send command "L"') | [
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] | {
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{
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"docstring": null,
"docstring_tokens": [],
"default": null,
"is_optional": null
}
],
"outlier_params": [],
"others": []
} | import time
def _Blink(arduino, times=1, interval_secs=0.1):
for nth in range(times):
if nth:
time.sleep(interval_secs)
if not arduino.SendExpectReceive('H', 'H', retry=2):
raise Exception('Failed to send command "H"')
time.sleep(interval_secs)
if not arduino.SendExpectReceive('L', 'L', retry=2):
raise Exception('Failed to send command "L"') | 142 | 233 |
4bc5ce9a85413586a08c49651984f0ab6f940317 | kevlar1818/mipster | mipster.py | [
"MIT"
] | Python | parse_cmd | <not_specific> | def parse_cmd(line):
'''takes a string and breaks it into a command name and its arguments'''
line = re.sub('^\w+:', '', line)
line = re.sub('#.*', '', line) # handle in-line comments
line = re.sub('[,\(\)]', ' ', line) # handle commas and parens
return re.split('\s+', line.strip()) | takes a string and breaks it into a command name and its arguments | takes a string and breaks it into a command name and its arguments | [
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] | def parse_cmd(line):
line = re.sub('^\w+:', '', line)
line = re.sub('#.*', '', line)
line = re.sub('[,\(\)]', ' ', line)
return re.split('\s+', line.strip()) | [
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"docstring": null,
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}
],
"outlier_params": [],
"others": []
} | import re
def parse_cmd(line):
line = re.sub('^\w+:', '', line)
line = re.sub('#.*', '', line)
line = re.sub('[,\(\)]', ' ', line)
return re.split('\s+', line.strip()) | 143 | 589 |
b41a05c1ac470df22125490ae349e0dec66bd31c | NervanaSystems/ngraph-python | examples/deepspeech/deepspeech.py | [
"Apache-2.0"
] | Python | decode_outputs | <not_specific> | def decode_outputs(probs, inds, decoder):
"""
Decode from network probabilities and compute CER
Arguments:
probs: Tensor of character probabilities
inds: List of character indices for ground truth
decoder: instance of a Decoder
Returns:
Tuple of (ground truth transcript, decoded transcript, CER)
"""
ground_truth = decoder.process_string(decoder.convert_to_string(inds),
remove_repetitions=False)
decoded_string = decoder.decode(probs)
cer = decoder.cer(ground_truth, decoded_string) / float(len(ground_truth))
return ground_truth, decoded_string, cer |
Decode from network probabilities and compute CER
Arguments:
probs: Tensor of character probabilities
inds: List of character indices for ground truth
decoder: instance of a Decoder
Returns:
Tuple of (ground truth transcript, decoded transcript, CER)
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ground_truth = decoder.process_string(decoder.convert_to_string(inds),
remove_repetitions=False)
decoded_string = decoder.decode(probs)
cer = decoder.cer(ground_truth, decoded_string) / float(len(ground_truth))
return ground_truth, decoded_string, cer | [
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"default": null,
"is_optional": null
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"default": null,
"is_optional": null
}
],
"outlier_params": [],
"others": []
} | def decode_outputs(probs, inds, decoder):
ground_truth = decoder.process_string(decoder.convert_to_string(inds),
remove_repetitions=False)
decoded_string = decoder.decode(probs)
cer = decoder.cer(ground_truth, decoded_string) / float(len(ground_truth))
return ground_truth, decoded_string, cer | 144 | 257 |
f7e07e8a5c6379c2f966fd23d5e9c11c4e99552b | bwhmather/python-jpake | jpake/__init__.py | [
"BSD-3-Clause"
] | Python | pascal | <not_specific> | def pascal(s):
"""
Encode a byte string as a pascal string with a big-endian header
"""
if len(s) >= 2**16:
raise ValueError("cannot encode value greater than (2^8)^(2^16)")
return len(s).to_bytes(2, 'big') + s |
Encode a byte string as a pascal string with a big-endian header
| Encode a byte string as a pascal string with a big-endian header | [
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if len(s) >= 2**16:
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if len(s) >= 2**16:
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return len(s).to_bytes(2, 'big') + s | 145 | 874 |
bc1c7538ee455539c4f5c750aebdb98ef2a3d10a | Robpol86/general | convert_music.py | [
"MIT"
] | Python | error | null | def error(message, code=1):
"""Prints an error message to stderr and exits with a status of 1 by default."""
if message:
print('ERROR: {}'.format(message), file=sys.stderr)
else:
print(file=sys.stderr)
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if message:
print('ERROR: {}'.format(message), file=sys.stderr)
else:
print(file=sys.stderr)
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"outlier_params": [],
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} | import sys
def error(message, code=1):
if message:
print('ERROR: {}'.format(message), file=sys.stderr)
else:
print(file=sys.stderr)
sys.exit(code) | 146 | 317 |
53de0bddc21359194be6ccbf61eecf40d0263deb | Omritk/warriorframework | warhorn/source/utils.py | [
"Apache-2.0"
] | Python | words | null | def words(import_actions):
""" This function gives out the words by splitting the lines
:Arguments:
1. import_actions (list) = list of the lines starting from 'import'
:Returns:
list = list of words in the line
"""
line_stream = iter(import_actions)
for line in line_stream:
for word in line.split():
yield word | This function gives out the words by splitting the lines
:Arguments:
1. import_actions (list) = list of the lines starting from 'import'
:Returns:
list = list of words in the line
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line_stream = iter(import_actions)
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yield word | 147 | 122 |
417b92b4da60e1680d5399326786ea34d3efffd1 | MTrajK/python-projects | SureDone API/suredone_upload.py | [
"MIT"
] | Python | construct_input_file_path | <not_specific> | def construct_input_file_path(args, logger):
"""Gets the input file value from the command line and construct the path.
Parameters:
args: Object with command line arguments (input file path)
logger: Function used for logging
Returns:
Input file path.
"""
if args.input_file == None:
raise Exception('Missing input file path.')
# absolute path
if os.path.isabs(args.input_file):
return args.input_file
# relative path
if sys.platform == 'linux' or sys.platform == 'linux2':
# Linux
input_file = ['~']
elif sys.platform == 'win32':
# Windows
input_file = ['~', 'Downloads']
input_file.append(args.input_file)
return os.path.expanduser(os.sep.join(input_file)) | Gets the input file value from the command line and construct the path.
Parameters:
args: Object with command line arguments (input file path)
logger: Function used for logging
Returns:
Input file path.
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if sys.platform == 'linux' or sys.platform == 'linux2':
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import os
def construct_input_file_path(args, logger):
if args.input_file == None:
raise Exception('Missing input file path.')
if os.path.isabs(args.input_file):
return args.input_file
if sys.platform == 'linux' or sys.platform == 'linux2':
input_file = ['~']
elif sys.platform == 'win32':
input_file = ['~', 'Downloads']
input_file.append(args.input_file)
return os.path.expanduser(os.sep.join(input_file)) | 148 | 493 |
c813809667d8d1c8a2280e6941692d300ff47a94 | moorea1/DS595CS525-RL-Projects | Project1/mdp_dp.py | [
"MIT"
] | Python | render_single | <not_specific> | def render_single(env, policy, render = False, n_episodes=100):
"""
Given a game envrionemnt of gym package, play multiple episodes of the game.
An episode is over when the returned value for "done" = True.
At each step, pick an action and collect the reward and new state from the game.
Parameters:
----------
env: gym.core.Environment
Environment to play on. Must have nS, nA, and P as attributes.
policy: np.array of shape [env.nS, env.nA]
The action to take at a given state
render: whether or not to render the game(it's slower to render the game)
n_episodes: the number of episodes to play in the game.
Returns:
------
total_rewards: the total number of rewards achieved in the game.
"""
total_rewards = 0
for _ in range(n_episodes):
ob = env.reset() # initialize the episode
done = False
while not done:
if render:
env.render() # render the game
############################
# YOUR IMPLEMENTATION HERE #
return total_rewards |
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An episode is over when the returned value for "done" = True.
At each step, pick an action and collect the reward and new state from the game.
Parameters:
----------
env: gym.core.Environment
Environment to play on. Must have nS, nA, and P as attributes.
policy: np.array of shape [env.nS, env.nA]
The action to take at a given state
render: whether or not to render the game(it's slower to render the game)
n_episodes: the number of episodes to play in the game.
Returns:
------
total_rewards: the total number of rewards achieved in the game.
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Environment to play on. Must have nS, nA, and P as attributes.
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The action to take at a given state
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n_episodes: the number of episodes to play in the game.
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for _ in range(n_episodes):
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done = False
while not done:
if render:
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return total_rewards | 149 | 458 |
cf64bc9f88234a57121765ad15e762b30128bc19 | meraki/meraki-python-sdk | meraki_sdk/models/update_network_cellular_gateway_settings_dhcp_model.py | [
"MIT"
] | Python | from_dictionary | <not_specific> | def from_dictionary(cls,
dictionary):
"""Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
Returns:
object: An instance of this structure class.
"""
if dictionary is None:
return None
# Extract variables from the dictionary
dhcp_lease_time = dictionary.get('dhcpLeaseTime')
dns_nameservers = dictionary.get('dnsNameservers')
dns_custom_nameservers = dictionary.get('dnsCustomNameservers')
# Return an object of this model
return cls(dhcp_lease_time,
dns_nameservers,
dns_custom_nameservers) | Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
Returns:
object: An instance of this structure class.
| Creates an instance of this model from a dictionary
Args:
dictionary (dictionary): A dictionary representation of the object as
obtained from the deserialization of the server's response. The keys
MUST match property names in the API description.
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return None
dhcp_lease_time = dictionary.get('dhcpLeaseTime')
dns_nameservers = dictionary.get('dnsNameservers')
dns_custom_nameservers = dictionary.get('dnsCustomNameservers')
return cls(dhcp_lease_time,
dns_nameservers,
dns_custom_nameservers) | [
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],
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dictionary):
if dictionary is None:
return None
dhcp_lease_time = dictionary.get('dhcpLeaseTime')
dns_nameservers = dictionary.get('dnsNameservers')
dns_custom_nameservers = dictionary.get('dnsCustomNameservers')
return cls(dhcp_lease_time,
dns_nameservers,
dns_custom_nameservers) | 150 | 171 |
8f4a1203b463b44bc7984646f24dc9de34450f34 | anshulahuja98/python3-crdt | py3crdt/orset.py | [
"MIT"
] | Python | add | <not_specific> | def add(payload, elem, unique_tag):
"""
The function to add an element with it's unique tag to ORSet object's payload.
Args:
payload (list): Payload in which element has to be added.
elem (any_type): The element to be added.
unique_tag (any_type): Tag to identify element.
Returns:
payload (list): Payload in which element is added.
"""
# Bool value to check if element already in payload
found = False
for item in payload:
# If element already in payload, add unique_tag to it's tag_list
if elem == item["elem"]:
item["tags"].append(unique_tag)
found = True
break
# If element not in payload, add element with unique tag
if not found:
payload.append({"elem": elem, "tags": [unique_tag]})
# Sort the payload
payload.sort(key=lambda i: i['elem'])
return payload |
The function to add an element with it's unique tag to ORSet object's payload.
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payload (list): Payload in which element has to be added.
elem (any_type): The element to be added.
unique_tag (any_type): Tag to identify element.
Returns:
payload (list): Payload in which element is added.
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item["tags"].append(unique_tag)
found = True
break
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payload.append({"elem": elem, "tags": [unique_tag]})
payload.sort(key=lambda i: i['elem'])
return payload | 151 | 547 |
9e417a39aedeffec349c6214ef92ac204904d9ee | jankukacka/happy | src/happy/io.py | [
"MIT"
] | Python | save_pickle | <not_specific> | def save_pickle(filename, data):
'''
Save pickle file by its filename.
'''
## Pickle files
import pickle
with open(filename, 'wb') as file:
return pickle.dump(data, file, protocol=4) |
Save pickle file by its filename.
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import pickle
with open(filename, 'wb') as file:
return pickle.dump(data, file, protocol=4) | [
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def save_pickle(filename, data):
import pickle
with open(filename, 'wb') as file:
return pickle.dump(data, file, protocol=4) | 152 | 515 |
f3ea671bf79aa3e0db549f06061fa9343b09ed70 | JonasSinjan/hrt_pipeline | src/utils.py | [
"MIT"
] | Python | check_filenames | <not_specific> | def check_filenames(data_f):
"""
checks if the science scans have the same DID - this would cause an issue for naming the output demod files
"""
scan_name_list = [str(scan.split('.fits')[0][-10:]) for scan in data_f]
seen = set()
uniq_scan_DIDs = [x for x in scan_name_list if x in seen or seen.add(x)] #creates list of unique DIDs from the list
#print(uniq_scan_DIDs)
#print(scan_name_list)S
if uniq_scan_DIDs == []:
print("The scans' DIDs are all unique")
else:
for x in uniq_scan_DIDs:
number = scan_name_list.count(x)
if number > 1: #if more than one
print(f"The DID: {x} is repeated {number} times")
i = 1
for index, name in enumerate(scan_name_list):
if name == x:
scan_name_list[index] = name + f"_{i}" #add _1, _2, etc to the file name, so that when written to output file not overwriting
i += 1
print("The New DID list is: ", scan_name_list)
return scan_name_list |
checks if the science scans have the same DID - this would cause an issue for naming the output demod files
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scan_name_list = [str(scan.split('.fits')[0][-10:]) for scan in data_f]
seen = set()
uniq_scan_DIDs = [x for x in scan_name_list if x in seen or seen.add(x)]
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scan_name_list = [str(scan.split('.fits')[0][-10:]) for scan in data_f]
seen = set()
uniq_scan_DIDs = [x for x in scan_name_list if x in seen or seen.add(x)]
if uniq_scan_DIDs == []:
print("The scans' DIDs are all unique")
else:
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print(f"The DID: {x} is repeated {number} times")
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if name == x:
scan_name_list[index] = name + f"_{i}"
i += 1
print("The New DID list is: ", scan_name_list)
return scan_name_list | 153 | 272 |
6e56dfb612ec509d88e968bec66f7b9e38bcf149 | withinnoitatpmet/mxnetsource | python/mxnet/visualization.py | [
"Apache-2.0"
] | Python | looks_like_weight | <not_specific> | def looks_like_weight(name):
"""Internal helper to figure out if node should be hidden with `hide_weights`.
"""
if name.endswith("_weight"):
return True
if name.endswith("_bias"):
return True
return False | Internal helper to figure out if node should be hidden with `hide_weights`.
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aac221e5e318801560f96c29048ef19c9c31ed24 | jerryhgoss/atmospy | atmospy/stats.py | [
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] | Python | days_avg_gt_std | <not_specific> | def days_avg_gt_std(data, std):
"""
Find the number of days where the maximum hourly measurement is
above the 1-hour standard used by the EPA
Inputs
------
:param data: dataframe or Series with timestamp index and pollution data column.
should already be resampled to appropriate timebase
:type data: pd.DataFrame or pd.Series
:param std: standard value used by EPA
:type std: float
Returns
-------
count: the number of days where the average value surpassed the standard
"""
daily_avg = data.groupby(data.index.floor('d')).mean()
count = daily_avg[daily_avg > std].count()
return count |
Find the number of days where the maximum hourly measurement is
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Inputs
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:param data: dataframe or Series with timestamp index and pollution data column.
should already be resampled to appropriate timebase
:type data: pd.DataFrame or pd.Series
:param std: standard value used by EPA
:type std: float
Returns
-------
count: the number of days where the average value surpassed the standard
| Find the number of days where the maximum hourly measurement is
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:param data: dataframe or Series with timestamp index and pollution data column.
Returns
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daily_avg = data.groupby(data.index.floor('d')).mean()
count = daily_avg[daily_avg > std].count()
return count | 156 | 635 |
c9b820b2531cc2cc587d88a8b4a7a50f67502d0a | zjsteyn/Eyra | Backend/scripts/processMIMTokens.py | [
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] | Python | containsCapsAbbrev | <not_specific> | def containsCapsAbbrev(x):
'''
Test if list x contains e.g. OECD, DNA, RNA which are abbreviations but
not filtered out with punctuation.
'''
for word in x:
upperCase = 0
for c in word:
if c.isupper():
upperCase += 1
if upperCase >= 2:
return True
return False |
Test if list x contains e.g. OECD, DNA, RNA which are abbreviations but
not filtered out with punctuation.
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18af1df768de33fc7185d8e4fe853759d1703842 | moddent/NTHU-COM-526000-DL-HW | HW01/function.py | [
"MIT"
] | Python | lr_scheduler | <not_specific> | def lr_scheduler(epoch, lr):
"""
Decay the learning rate every 50 epoch.
"""
drop = 0.5
epochs_drop = 25
lr = lr * math.pow(drop, math.floor((1 + epoch) / epochs_drop))
return lr |
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drop = 0.5
epochs_drop = 25
lr = lr * math.pow(drop, math.floor((1 + epoch) / epochs_drop))
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],
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} | import math
def lr_scheduler(epoch, lr):
drop = 0.5
epochs_drop = 25
lr = lr * math.pow(drop, math.floor((1 + epoch) / epochs_drop))
return lr | 158 | 227 |
bc70c80ae5907a0d3c782634e8e936ff43468a55 | davidwtbuxton/lotus-notes-export | notesexport.py | [
"MIT"
] | Python | notes_headers | <not_specific> | def notes_headers(msg):
"""Returns a dictionary of some interesting notes headers."""
d = {
'Subject': None,
'PostedDate': None,
'From': None,
'SentTo': None,
}
for line in msg.splitlines():
if None not in d.values():
return d
for k in d:
if d[k] is None:
if line.startswith(k + ': '):
d[k] = line[len(k + ': '):]
else:
return d | Returns a dictionary of some interesting notes headers. | Returns a dictionary of some interesting notes headers. | [
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d = {
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'SentTo': None,
}
for line in msg.splitlines():
if None not in d.values():
return d
for k in d:
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d[k] = line[len(k + ': '):]
else:
return d | 159 | 613 |
a58ed2f9ff977888b86bef17454ca86ab8aeeef8 | dcsparkes/adventofcode | lifegame/lifegame.py | [
"Unlicense"
] | Python | sideBySide | <not_specific> | def sideBySide(seatA, seatB, separation=5):
"""
Turn two LifeGames into a single string separated by 'separation' spaces.
Relatively easy to rewrite with *args for more than 2
:param seatA:
:param seatB:
:param separation:
:return:
"""
delimiter = " " * separation
rowsA = str(seatA).split('\n')
rowsB = str(seatB).split('\n')
rows = [delimiter.join(components) for components in zip(rowsA, rowsB)]
return '\n'.join(rows) |
Turn two LifeGames into a single string separated by 'separation' spaces.
Relatively easy to rewrite with *args for more than 2
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:param seatB:
:param separation:
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| Turn two LifeGames into a single string separated by 'separation' spaces.
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rowsA = str(seatA).split('\n')
rowsB = str(seatB).split('\n')
rows = [delimiter.join(components) for components in zip(rowsA, rowsB)]
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} | def sideBySide(seatA, seatB, separation=5):
delimiter = " " * separation
rowsA = str(seatA).split('\n')
rowsB = str(seatB).split('\n')
rows = [delimiter.join(components) for components in zip(rowsA, rowsB)]
return '\n'.join(rows) | 160 | 507 |
3be80331c354459f34c9fe0c26eaf4e3713cd032 | meramsey/python-scripts-collection | scripts/human_filesize.py | [
"MIT"
] | Python | human_size | <not_specific> | def human_size(bytes, units=None):
""" Returns a human readable string representation of bytes """
if units is None:
units = [' bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB']
return str(bytes) + units[0] if bytes < 1024 else human_size(bytes >> 10, units[1:]) | Returns a human readable string representation of bytes | Returns a human readable string representation of bytes | [
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b648699bb61ce3c7b8511e991d7508d05d72967b | pimoroni/plasma | library/tests/conftest.py | [
"MIT"
] | Python | cleanup_plasma | null | def cleanup_plasma():
"""This fixture removes all plasma modules from sys.modules.
This ensures that each module is fully re-imported, along with
the fixtures for serial, etc, for each test function.
"""
yield None
to_delete = []
for module in sys.modules:
if module.startswith('plasma'):
to_delete.append(module)
for module in to_delete:
del sys.modules[module] | This fixture removes all plasma modules from sys.modules.
This ensures that each module is fully re-imported, along with
the fixtures for serial, etc, for each test function.
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"returns": [],
"raises": [],
"params": [],
"outlier_params": [],
"others": []
} | import sys
def cleanup_plasma():
yield None
to_delete = []
for module in sys.modules:
if module.startswith('plasma'):
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for module in to_delete:
del sys.modules[module] | 164 | 690 |
6bcba49c66cf183836a392f7b1da6e731785571a | Anrufliste/voice-skill-sdk | skill_sdk/l10n.py | [
"MIT"
] | Python | nl_decapitalize | <not_specific> | def nl_decapitalize(string: str):
"""
Decapitalize first character (the rest is untouched)
:param string:
:return:
"""
return string[:1].lower() + string[1:] |
Decapitalize first character (the rest is untouched)
:param string:
:return:
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return string[:1].lower() + string[1:] | 165 | 992 |
9f67126b284c449f9f058bc48c7945a75e089554 | sxie22/uf3 | uf3/regression/least_squares.py | [
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] | Python | validate_regularizer | null | def validate_regularizer(regularizer: np.ndarray, n_feats: int):
"""
Check for consistency between regularizer matrix and number of features.
Args:
regularizer (np.ndarray): regularizer matrix.
n_feats (int): number of features.
"""
n_row, n_col = regularizer.shape
if n_col != n_feats:
shape_comparison = "N x {0}. Provided: {1} x {2}".format(n_feats,
n_row,
n_col)
raise ValueError(
"Expected regularizer shape: " + shape_comparison) |
Check for consistency between regularizer matrix and number of features.
Args:
regularizer (np.ndarray): regularizer matrix.
n_feats (int): number of features.
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shape_comparison = "N x {0}. Provided: {1} x {2}".format(n_feats,
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shape_comparison = "N x {0}. Provided: {1} x {2}".format(n_feats,
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raise ValueError(
"Expected regularizer shape: " + shape_comparison) | 167 | 241 |
09ded4cbd5c7ddb58c41a6ad303da10ce845bb04 | maytrue/webrtc | modules/audio_processing/test/py_quality_assessment/quality_assessment/evaluation.py | [
"DOC",
"BSD-3-Clause"
] | Python | Run | <not_specific> | def Run(cls, evaluation_score_workers, apm_input_metadata,
apm_output_filepath, reference_input_filepath, output_path):
"""Runs the evaluation.
Iterates over the given evaluation score workers.
Args:
evaluation_score_workers: list of EvaluationScore instances.
apm_input_metadata: dictionary with metadata of the APM input.
apm_output_filepath: path to the audio track file with the APM output.
reference_input_filepath: path to the reference audio track file.
output_path: output path.
Returns:
A dict of evaluation score name and score pairs.
"""
# Init.
scores = {}
for evaluation_score_worker in evaluation_score_workers:
logging.info(' computing <%s> score', evaluation_score_worker.NAME)
evaluation_score_worker.SetInputSignalMetadata(apm_input_metadata)
evaluation_score_worker.SetReferenceSignalFilepath(
reference_input_filepath)
evaluation_score_worker.SetTestedSignalFilepath(
apm_output_filepath)
evaluation_score_worker.Run(output_path)
scores[evaluation_score_worker.NAME] = evaluation_score_worker.score
return scores | Runs the evaluation.
Iterates over the given evaluation score workers.
Args:
evaluation_score_workers: list of EvaluationScore instances.
apm_input_metadata: dictionary with metadata of the APM input.
apm_output_filepath: path to the audio track file with the APM output.
reference_input_filepath: path to the reference audio track file.
output_path: output path.
Returns:
A dict of evaluation score name and score pairs.
| Runs the evaluation.
Iterates over the given evaluation score workers. | [
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apm_output_filepath, reference_input_filepath, output_path):
scores = {}
for evaluation_score_worker in evaluation_score_workers:
logging.info(' computing <%s> score', evaluation_score_worker.NAME)
evaluation_score_worker.SetInputSignalMetadata(apm_input_metadata)
evaluation_score_worker.SetReferenceSignalFilepath(
reference_input_filepath)
evaluation_score_worker.SetTestedSignalFilepath(
apm_output_filepath)
evaluation_score_worker.Run(output_path)
scores[evaluation_score_worker.NAME] = evaluation_score_worker.score
return scores | [
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"docstring": null,
"docstring_tokens": [
"None"
],
"default": null,
"is_optional": null
}
],
"outlier_params": [],
"others": []
} | import logging
def Run(cls, evaluation_score_workers, apm_input_metadata,
apm_output_filepath, reference_input_filepath, output_path):
scores = {}
for evaluation_score_worker in evaluation_score_workers:
logging.info(' computing <%s> score', evaluation_score_worker.NAME)
evaluation_score_worker.SetInputSignalMetadata(apm_input_metadata)
evaluation_score_worker.SetReferenceSignalFilepath(
reference_input_filepath)
evaluation_score_worker.SetTestedSignalFilepath(
apm_output_filepath)
evaluation_score_worker.Run(output_path)
scores[evaluation_score_worker.NAME] = evaluation_score_worker.score
return scores | 168 | 110 |
c6460d3b38eb380df5b9c790ad806ad14ec836a9 | BIONF/taXaminer | prepare_and_check.py | [
"MIT"
] | Python | check_dir_slash | <not_specific> | def check_dir_slash(path):
"""Appends trailing slash to path if necessary.
Args:
path(str): path to be checked for slash
Returns:
(str) path with slash at the end
"""
if path.endswith('/'):
return path
else:
return path+'/' | Appends trailing slash to path if necessary.
Args:
path(str): path to be checked for slash
Returns:
(str) path with slash at the end
| Appends trailing slash to path if necessary. | [
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if path.endswith('/'):
return path
else:
return path+'/' | 169 | 71 |
18d6baaf0359b10f5388a1c72403426339b872c7 | ezramorris/smrt-importer | smrt_importer/processor.py | [
"MIT"
] | Python | move_file | null | def move_file(path: Path, dest: Path):
"""Move a file, adding a suffix if necessary.
path: file path
dest: destination directory
"""
newpath = dest / path.name
i=1
while newpath.exists():
newpath = dest / f'{path.stem}_{i}{path.suffix}'
i+=1
path.rename(newpath) | Move a file, adding a suffix if necessary.
path: file path
dest: destination directory
| Move a file, adding a suffix if necessary.
path: file path
dest: destination directory | [
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] | def move_file(path: Path, dest: Path):
newpath = dest / path.name
i=1
while newpath.exists():
newpath = dest / f'{path.stem}_{i}{path.suffix}'
i+=1
path.rename(newpath) | [
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newpath = dest / path.name
i=1
while newpath.exists():
newpath = dest / f'{path.stem}_{i}{path.suffix}'
i+=1
path.rename(newpath) | 170 | 606 |
0c17379a655101f895d7eba780521973b03a73ef | ypsun-umd/MiniDAQ-DCB-Panels | utils/dim_browser.py | [
"BSD-2-Clause"
] | Python | print_all_clients_connected_to_server | null | def print_all_clients_connected_to_server(dbr):
"""
dbr.getServerClients("TimeService-server") returns the number of clients
connected to the server
dbr.getNextServerClient() can be called after this call
"""
# getNextServerClient() is a generator that generates a tuple or None if no
# Clients are found this is another way to use the getNext*** functions
for client_tuple in dbr.getNextServerClient():
if client_tuple is not None:
print(
"Client name = {0}, node name = {1}".format(
client_tuple[0], client_tuple[1]
))
print("") |
dbr.getServerClients("TimeService-server") returns the number of clients
connected to the server
dbr.getNextServerClient() can be called after this call
| dbr.getServerClients("TimeService-server") returns the number of clients
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print(
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client_tuple[0], client_tuple[1]
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print("") | [
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if client_tuple is not None:
print(
"Client name = {0}, node name = {1}".format(
client_tuple[0], client_tuple[1]
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print("") | 171 | 19 |
3914697415b7fe9af8bd8f9a02dcfab6149d0435 | ParkvilleData/MetaGenePipe | scripts/inputArgMaker.v.1.0.1.py | [
"Apache-2.0"
] | Python | printDictionary | null | def printDictionary(dictionary):
""" print Dictionary
Prints contents of dictionary for debug purposes
Args:
param1 (Dictionary): Dictionary of questionable content
Returns:
NA: print out dictionary contents
"""
print("\nDictionary contents below")
pp = pprint.PrettyPrinter(indent=4)
pp.pprint(dictionary)
print(len(dictionary)) | print Dictionary
Prints contents of dictionary for debug purposes
Args:
param1 (Dictionary): Dictionary of questionable content
Returns:
NA: print out dictionary contents
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print("\nDictionary contents below")
pp = pprint.PrettyPrinter(indent=4)
pp.pprint(dictionary)
print(len(dictionary)) | [
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def printDictionary(dictionary):
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pp = pprint.PrettyPrinter(indent=4)
pp.pprint(dictionary)
print(len(dictionary)) | 172 | 345 |
4151806476243e46058cd970a601534f21ba9447 | adelolmo/snapraid-runner | deb/opt/snapraid-runner/snapraid-runner.py | [
"Apache-2.0"
] | Python | tee_log | <not_specific> | def tee_log(infile, out_lines, log_level):
"""
Create a thread thot saves all the output on infile to out_lines and
logs every line with log_level
"""
def tee_thread():
for line in iter(infile.readline, ""):
line = line.strip()
# Do not log the progress display
if "\r" in line:
line = line.split("\r")[-1]
logging.log(log_level, line.strip())
out_lines.append(line)
infile.close()
t = threading.Thread(target=tee_thread)
t.daemon = True
t.start()
return t |
Create a thread thot saves all the output on infile to out_lines and
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| Create a thread thot saves all the output on infile to out_lines and
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def tee_thread():
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line = line.strip()
if "\r" in line:
line = line.split("\r")[-1]
logging.log(log_level, line.strip())
out_lines.append(line)
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t.daemon = True
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import threading
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def tee_thread():
for line in iter(infile.readline, ""):
line = line.strip()
if "\r" in line:
line = line.split("\r")[-1]
logging.log(log_level, line.strip())
out_lines.append(line)
infile.close()
t = threading.Thread(target=tee_thread)
t.daemon = True
t.start()
return t | 173 | 417 |
926daa19f7aa4411ffca1cb5deb12c9e73205581 | PabRod/snakePi | scripts/process.py | [
"Apache-2.0"
] | Python | writer | null | def writer(val, file):
""" Writes a value to a file """
val_str = f'{val:.8f}' # Keep decimals enough
with open(file, 'w') as f:
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} | def writer(val, file):
val_str = f'{val:.8f}'
with open(file, 'w') as f:
f.write(val_str) | 174 | 483 |
a997c809edca66b028d3be6bea5b6d08753edb22 | corenel/flambeau | flambeau/network/lr_scheduler.py | [
"MIT"
] | Python | linear_anneal | <not_specific> | def linear_anneal(base_lr, global_step, warmup_steps, min_lr):
"""
Linearly annealed learning rate from 0 in the first warming up epochs.
:param base_lr: base learning rate
:type base_lr: float
:param global_step: global training steps
:type global_step: int
:param warmup_steps: number of steps for warming up
:type warmup_steps: int
:param min_lr: minimum learning rate
:type min_lr: float
:return: scheduled learning rate
:rtype: float
"""
lr = max(min_lr + (base_lr - min_lr) * (1.0 - global_step / warmup_steps),
min_lr)
return lr |
Linearly annealed learning rate from 0 in the first warming up epochs.
:param base_lr: base learning rate
:type base_lr: float
:param global_step: global training steps
:type global_step: int
:param warmup_steps: number of steps for warming up
:type warmup_steps: int
:param min_lr: minimum learning rate
:type min_lr: float
:return: scheduled learning rate
:rtype: float
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lr = max(min_lr + (base_lr - min_lr) * (1.0 - global_step / warmup_steps),
min_lr)
return lr | [
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],
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} | def linear_anneal(base_lr, global_step, warmup_steps, min_lr):
lr = max(min_lr + (base_lr - min_lr) * (1.0 - global_step / warmup_steps),
min_lr)
return lr | 175 | 554 |
39f1cc2e03f1e8d4a4cbcea5957c96172ced046a | moyamo/polygon2square | geometry.py | [
"MIT"
] | Python | line_intersects_segment | <not_specific> | def line_intersects_segment(line, line_segment):
"""Returns the intersection the Line and LineSegment or None if they do
not intersect.
This function is useful for splitting polygons by a straight line.
"""
linesegform = line_segment.to_line()
if line.is_parallel_to(linesegform):
return None
else:
p = line.intersection(linesegform)
# Is the intersection on the line_segment?
if line_segment.between(p):
return p
else:
return None | Returns the intersection the Line and LineSegment or None if they do
not intersect.
This function is useful for splitting polygons by a straight line.
| Returns the intersection the Line and LineSegment or None if they do
not intersect.
This function is useful for splitting polygons by a straight line. | [
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linesegform = line_segment.to_line()
if line.is_parallel_to(linesegform):
return None
else:
p = line.intersection(linesegform)
if line_segment.between(p):
return p
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return None
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p = line.intersection(linesegform)
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return p
else:
return None | 176 | 208 |
f1427a0b1563fd72c10e3b46ea035ae51710b217 | bmorledge-hampton19/benbiohelpers | python/benbiohelpers/CountThisInThat/OutputDataStratifiers.py | [
"MIT"
] | Python | sortPositionIDs | <not_specific> | def sortPositionIDs(positionIDs: Union[List[str], List[Tuple]]):
"""
Sorts the position IDs derived from the Encompassed Data and Encompassing Data ODS's.
Can handle input as a list of strings or tuples, and with a single position or both a start and end position.
However, it is assumed that all members of the list are formatted the same with respect to the above variations.
"""
# Sorting for list of strings:
if isinstance(positionIDs[0], str):
# If both start and end positions are given (Represented by a '-' between positions, before the strand designation), sort on end position first
if '-' in positionIDs[0].split('(')[0]:
positionIDs.sort(key = lambda positionID: float(positionID.split('(')[0].split('-')[1]))
# Next, sort on the first (potentially only) given position.
positionIDs.sort(key = lambda positionID: float(positionID.split('(')[0].split(':')[1].split('-')[0]))
# Finally, sort on the chromosome identifier.
positionIDs.sort(key = lambda positionID: positionID.split(':')[0])
return positionIDs # Do this as a formality, even though this sorts in place (I think).
# Otherwise, assume we have some iterable.
else:
# If the iterable has 4 items, sort on item 3 first, which represents the end position
if len(positionIDs[0]) == 4: positionIDs.sort(key = lambda positionID: positionID[2])
# Next, sort by the start position and then the chromosome
positionIDs.sort(key = lambda positionID: positionID[1])
positionIDs.sort(key = lambda positionID: positionID[0]) |
Sorts the position IDs derived from the Encompassed Data and Encompassing Data ODS's.
Can handle input as a list of strings or tuples, and with a single position or both a start and end position.
However, it is assumed that all members of the list are formatted the same with respect to the above variations.
| Sorts the position IDs derived from the Encompassed Data and Encompassing Data ODS's.
Can handle input as a list of strings or tuples, and with a single position or both a start and end position.
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positionIDs.sort(key = lambda positionID: positionID.split(':')[0])
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if len(positionIDs[0]) == 4: positionIDs.sort(key = lambda positionID: positionID[2])
positionIDs.sort(key = lambda positionID: positionID[1])
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} | def sortPositionIDs(positionIDs: Union[List[str], List[Tuple]]):
if isinstance(positionIDs[0], str):
if '-' in positionIDs[0].split('(')[0]:
positionIDs.sort(key = lambda positionID: float(positionID.split('(')[0].split('-')[1]))
positionIDs.sort(key = lambda positionID: float(positionID.split('(')[0].split(':')[1].split('-')[0]))
positionIDs.sort(key = lambda positionID: positionID.split(':')[0])
return positionIDs
else:
if len(positionIDs[0]) == 4: positionIDs.sort(key = lambda positionID: positionID[2])
positionIDs.sort(key = lambda positionID: positionID[1])
positionIDs.sort(key = lambda positionID: positionID[0]) | 177 | 340 |
6a5460420e8e6297daab6e39711c4336ce592144 | 2019-fall-csc-226/t03-boustrophedon-turtles-meadors-frank-t03 | t03_stub.py | [
"MIT"
] | Python | squiggle_right | null | def squiggle_right(meadors):
"""
Uses turtle to fill a line left to right
"""
for cross_space in range(12):
for first_arc in range(2):
meadors.forward(20)
meadors.right(90)
for second_arc in range(2):
meadors.forward(20)
meadors.left(90) |
Uses turtle to fill a line left to right
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for cross_space in range(12):
for first_arc in range(2):
meadors.forward(20)
meadors.right(90)
for second_arc in range(2):
meadors.forward(20)
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} | def squiggle_right(meadors):
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for first_arc in range(2):
meadors.forward(20)
meadors.right(90)
for second_arc in range(2):
meadors.forward(20)
meadors.left(90) | 178 | 208 |
a4bad79a38087b87cf65767ccd679f09a571f15f | ssh0/growing-string | triangular_lattice/correlation.py | [
"MIT"
] | Python | choose_indexes | <not_specific> | def choose_indexes(_list, num, L):
"""Choose the index pairs whose width is fixed. """
N = len(_list)
if N - L < num:
raise StopIteration('list index is smaller than expected (%d), '
% (num + L)
+ 'given (%d).' % N
)
return sorted(random.sample(_list[:N - L], num)) | Choose the index pairs whose width is fixed. | Choose the index pairs whose width is fixed. | [
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raise StopIteration('list index is smaller than expected (%d), '
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def choose_indexes(_list, num, L):
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if N - L < num:
raise StopIteration('list index is smaller than expected (%d), '
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return sorted(random.sample(_list[:N - L], num)) | 179 | 291 |
e4fc25dd2f9033f2277ba4757222048350167d65 | InbarRose/irtools | irtools/_libs/file_utils.py | [
"MIT"
] | Python | write_to_tmp_file | <not_specific> | def write_to_tmp_file(content):
"""
writes the content to a temporary file
:param content: the content to write (string)
:return: returns the file_path
"""
with tempfile.NamedTemporaryFile(delete=False) as f:
f.write(content)
return f.name |
writes the content to a temporary file
:param content: the content to write (string)
:return: returns the file_path
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with tempfile.NamedTemporaryFile(delete=False) as f:
f.write(content)
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} | import tempfile
def write_to_tmp_file(content):
with tempfile.NamedTemporaryFile(delete=False) as f:
f.write(content)
return f.name | 180 | 483 |
d642856c24c7129dee1af95b499bd6a18318e6d6 | mathigatti/silence-removal | silenceRemoval.py | [
"MIT"
] | Python | detect_leading_silence | <not_specific> | def detect_leading_silence(sound, silence_threshold=-50.0, chunk_size=10):
'''
sound is a pydub.AudioSegment
silence_threshold in dB
chunk_size in ms
iterate over chunks until you find the first one with sound
'''
trim_ms = 0 # ms
while sound[trim_ms:trim_ms+chunk_size].dBFS < silence_threshold:
trim_ms += chunk_size
return trim_ms |
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silence_threshold in dB
chunk_size in ms
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chunk_size in ms
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trim_ms = 0
while sound[trim_ms:trim_ms+chunk_size].dBFS < silence_threshold:
trim_ms += chunk_size
return trim_ms | 181 | 554 |
6aaf7c2737a002697abb08c82d6222d1e68020c3 | ohsu-comp-bio/neoepiscope | neoepiscope/transcript_expression.py | [
"MIT"
] | Python | feature_to_tpm_dict | <not_specific> | def feature_to_tpm_dict(feature_to_read_count, feature_to_feature_length):
"""Calculate TPM values for feature
feature_to_read_count: dictionary linking features to read counts (float)
feature_to_feature_length: dictionary linking features to feature lengths (float)
Return value: dictionary linking feature ID to TPM value
"""
total_rpk = 0.0
feature_to_rpk = {}
feature_to_tpm = {}
# Get read per kilobase counts for each feature
for feature in feature_to_read_count:
try:
rpk = feature_to_read_count[feature] / feature_to_feature_length[feature]
except KeyError:
continue
feature_to_rpk[feature] = rpk
total_rpk += rpk
# Calculate scaling factor
scaling = total_rpk / 1000000.0
# Calculate TPM values
for feature in feature_to_rpk:
tpm = feature_to_rpk[feature] / scaling
feature_to_tpm[feature] = tpm
return feature_to_tpm | Calculate TPM values for feature
feature_to_read_count: dictionary linking features to read counts (float)
feature_to_feature_length: dictionary linking features to feature lengths (float)
Return value: dictionary linking feature ID to TPM value
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feature_to_feature_length: dictionary linking features to feature lengths (float)
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total_rpk = 0.0
feature_to_rpk = {}
feature_to_tpm = {}
for feature in feature_to_read_count:
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rpk = feature_to_read_count[feature] / feature_to_feature_length[feature]
except KeyError:
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feature_to_rpk[feature] = rpk
total_rpk += rpk
scaling = total_rpk / 1000000.0
for feature in feature_to_rpk:
tpm = feature_to_rpk[feature] / scaling
feature_to_tpm[feature] = tpm
return feature_to_tpm | 182 | 96 |
807d3c6a43078e1a316a558c13e5e3d375e846db | tangzhiyi11/Paddle | python/paddle/fluid/contrib/quantize/quantize_transpiler.py | [
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] | Python | _quantized_scale_name | <not_specific> | def _quantized_scale_name(var_name):
"""
Return quantized variable name for the input `var_name`.
"""
return "%s.scale" % (var_name) |
Return quantized variable name for the input `var_name`.
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2e48be5cdfa6fd39291f2a3ae37f9fd92ba35a27 | itongs/Historic_Work | FIT2004-All-Assns/assignment1.py | [
"MIT"
] | Python | convert_to_numbers | <not_specific> | def convert_to_numbers(string_list):
"""
Converts each string to a number as if it were a base 27 number
@param string_list The list of strings to convert
@return num_list The numbers corresponding to each string
@complexity O(NM) where N is the length of the list and M the maximum number of letters in a string
"""
num_list = [0] * len(string_list)
for i in range(len(string_list)): # Loop for each string
word = string_list[i]
num = 0
for j in range(len(word)): # For each character in each string
mult = ord(word[-1-j]) % 32
num = (26**j)*mult + num
num_list[i] = num
return num_list |
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@param string_list The list of strings to convert
@return num_list The numbers corresponding to each string
@complexity O(NM) where N is the length of the list and M the maximum number of letters in a string
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num_list = [0] * len(string_list)
for i in range(len(string_list)):
word = string_list[i]
num = 0
for j in range(len(word)):
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num_list[i] = num
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num = 0
for j in range(len(word)):
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num_list[i] = num
return num_list | 184 | 187 |
f14cde8e28d29ae671614c8a7783e5e7015c9e9f | eifinger/hass-here-weather | custom_components/here_weather/utils.py | [
"MIT"
] | Python | convert_asterisk_to_none | str | None | def convert_asterisk_to_none(state: str) -> str | None:
"""Convert HERE API representation of None."""
if state == "*":
return None
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61ab8f2051d78497acb3a700b5a4918a05a6819e | Grrmo/Domino-console-game | dominoes.py | [
"MIT"
] | Python | assign | <not_specific> | def assign(domino_set):
"""Assigns 7 domino pieces to each player and returns each players set of tiles and the list of remaining tiles"""
player_hand = []
computer_hand = []
for _ in range(7):
player_hand += [domino_set.pop()]
computer_hand += [domino_set.pop()]
return player_hand, computer_hand, domino_set | Assigns 7 domino pieces to each player and returns each players set of tiles and the list of remaining tiles | Assigns 7 domino pieces to each player and returns each players set of tiles and the list of remaining tiles | [
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5ed113ded28667bad8971c9f226aa933fb254623 | password520/macro_pack | src/common/utils.py | [
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r"""Returns if a top-level module with :attr:`name` exists *without**
importing it. This is generally safer than try-catch block around a
`import X`. It avoids third party libraries breaking assumptions of some of
our tests, e.g., setting multiprocessing start method when imported
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"""
spec = importlib.util.find_spec(name)
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def checkModuleExist(name):
spec = importlib.util.find_spec(name)
return spec is not None | 187 | 914 |
8331cdba8be31b794a2c219b4c04c3cf5553dd87 | Sandia-OpenSHMEM/sandia-shmem | scripts/generate_manpages.py | [
"BSD-3-Clause-Open-MPI"
] | Python | funcReplacements | <not_specific> | def funcReplacements(tex):
"""
Convert every FUNC macro with the bolded argument string
(.B <argument>).
-- Special consideration to any periods after the macro, since a
period at the beginning of a line denotes a comment and the
entire line will not appear.
(.BR <argument> .)
"""
keyString = "\FUNC{"
while (tex.find(keyString) != -1):
index = tex.find(keyString)
startBrace = tex.find("{", index)
endBrace = tex.find("}", startBrace)
innerText = tex[startBrace+1:endBrace]
if(endBrace + 1 < len(tex) and
(tex[endBrace + 1] == "." or tex[endBrace + 1] == ",")
or tex[endBrace + 1] == ";"):
tex = tex[:index] + "\n" + \
".BR \"" + innerText + \
"\" " + tex[endBrace + 1] + "\n" + tex[endBrace+2:]
else:
tex = tex[:index] + "\n" + \
".B " + innerText + \
"\n" + tex[endBrace+1:]
return tex |
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"outlier_params": [],
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} | def funcReplacements(tex):
keyString = "\FUNC{"
while (tex.find(keyString) != -1):
index = tex.find(keyString)
startBrace = tex.find("{", index)
endBrace = tex.find("}", startBrace)
innerText = tex[startBrace+1:endBrace]
if(endBrace + 1 < len(tex) and
(tex[endBrace + 1] == "." or tex[endBrace + 1] == ",")
or tex[endBrace + 1] == ";"):
tex = tex[:index] + "\n" + \
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else:
tex = tex[:index] + "\n" + \
".B " + innerText + \
"\n" + tex[endBrace+1:]
return tex | 188 | 1,005 |
8d011bf1ee203ac028187f1f23461d026dcbdeff | bpsinc-native/src_third_party_chromite | cbuildbot/lkgm_manager.py | [
"BSD-3-Clause"
] | Python | VersionCompare | <not_specific> | def VersionCompare(cls, version_string):
"""Useful method to return a comparable version of a LKGM string."""
lkgm = cls(version_string)
return map(int, [lkgm.build_number, lkgm.branch_build_number,
lkgm.patch_number, lkgm.revision_number]) | Useful method to return a comparable version of a LKGM string. | Useful method to return a comparable version of a LKGM string. | [
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lkgm = cls(version_string)
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401f0cfdd4d07937015de2f31a029649edea8015 | Lovely-XPP/tkzgeom | src/ConnectSignal/Lambda.py | [
"MIT"
] | Python | connect_lineedit_abstract | null | def connect_lineedit_abstract(scene, properties_list, dict_key, lineedit):
"""Be an abstract lineEdit callback function."""
ids = scene.list_focus_ids
if not lineedit.hasFocus():
for id_ in ids:
final_property = scene.project_data.items[id_].item
for prop in properties_list:
final_property = final_property[prop]
final_property[dict_key] = lineedit.text()
scene.edit.add_undo_item(scene)
else:
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if not lineedit.hasFocus():
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final_property = scene.project_data.items[id_].item
for prop in properties_list:
final_property = final_property[prop]
final_property[dict_key] = lineedit.text()
scene.edit.add_undo_item(scene)
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if not lineedit.hasFocus():
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final_property = scene.project_data.items[id_].item
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final_property = final_property[prop]
final_property[dict_key] = lineedit.text()
scene.edit.add_undo_item(scene)
else:
scene.ui.listWidget.setFocus(True) | 191 | 417 |
8dc9f4a1bcd36a48d92389f10a73fbb5256a500a | nhasbun/ds3231_test_tool | time_sync.py | [
"MIT"
] | Python | _sync_time | null | def _sync_time(_serial):
"""
Activates programming mode on arduino and sync time between machine and
ds3231 rtc.
"""
current_date = datetime.now()
year = current_date.year % 100 # extract 2 last digits
month = current_date.month
day = current_date.day
hour = current_date.hour
minute = current_date.minute
second = current_date.second
_serial.write(b'p') # Enabling programming mode
# Formatting data
data = f"{year},{month},{day},{hour},{minute},{second}"
data_b = data.encode('ascii')
_serial.write(data_b) |
Activates programming mode on arduino and sync time between machine and
ds3231 rtc.
| Activates programming mode on arduino and sync time between machine and
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] | def _sync_time(_serial):
current_date = datetime.now()
year = current_date.year % 100
month = current_date.month
day = current_date.day
hour = current_date.hour
minute = current_date.minute
second = current_date.second
_serial.write(b'p')
data = f"{year},{month},{day},{hour},{minute},{second}"
data_b = data.encode('ascii')
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def _sync_time(_serial):
current_date = datetime.now()
year = current_date.year % 100
month = current_date.month
day = current_date.day
hour = current_date.hour
minute = current_date.minute
second = current_date.second
_serial.write(b'p')
data = f"{year},{month},{day},{hour},{minute},{second}"
data_b = data.encode('ascii')
_serial.write(data_b) | 192 | 809 |
9f20e621b3d55a1272e24858daf2018cf38bc79b | bendichter/brainrender | brainrender/atlases/custom_atlases/insects_brains_db.py | [
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] | Python | add_descendants_to_tree | <not_specific> | def add_descendants_to_tree(tree, structure, parent_id=None):
"""
Recursively goes through all the the descendants of a region and adds them to the tree
"""
if parent_id is not None:
tree.create_node(
tag=structure["name"],
identifier=structure["id"],
parent=parent_id,
)
else:
tree.create_node(
tag=structure["name"], identifier=structure["id"],
)
if "children" not in structure.keys():
return
if structure["children"]:
for child in structure["children"]:
add_descendants_to_tree(tree, child, structure["id"]) |
Recursively goes through all the the descendants of a region and adds them to the tree
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identifier=structure["id"],
parent=parent_id,
)
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} | def add_descendants_to_tree(tree, structure, parent_id=None):
if parent_id is not None:
tree.create_node(
tag=structure["name"],
identifier=structure["id"],
parent=parent_id,
)
else:
tree.create_node(
tag=structure["name"], identifier=structure["id"],
)
if "children" not in structure.keys():
return
if structure["children"]:
for child in structure["children"]:
add_descendants_to_tree(tree, child, structure["id"]) | 194 | 517 |
a3532fa0fceeb8c1d1988dcc10ce38982fc43414 | aiventures/phpbb_scraper | soup_converter.py | [
"MIT"
] | Python | convert_datetime | <not_specific> | def convert_datetime(date_string, date_format='%A %d. %B %Y, %H:%M'):
"""converts date string of format WEEKDAY DD. MONTH YYYY, HH:MM into date format"""
try:
# Convert Dates of sort Sonntag 9. Juni 2019, 09:00 as date format
date_obj = datetime.strptime(date_string.strip(), date_format)
except:
date_obj = datetime(1900, 1, 1)
print(traceback.format_exc())
return date_obj | converts date string of format WEEKDAY DD. MONTH YYYY, HH:MM into date format | converts date string of format WEEKDAY DD. MONTH YYYY, HH:MM into date format | [
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try:
date_obj = datetime.strptime(date_string.strip(), date_format)
except:
date_obj = datetime(1900, 1, 1)
print(traceback.format_exc())
return date_obj | [
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} | import traceback
import datetime
def convert_datetime(date_string, date_format='%A %d. %B %Y, %H:%M'):
try:
date_obj = datetime.strptime(date_string.strip(), date_format)
except:
date_obj = datetime(1900, 1, 1)
print(traceback.format_exc())
return date_obj | 195 | 205 |
16217ec741e174fa5a05bb07cc2d4a68998b183d | clamsproject/clams-sdk-python | clams/restify/__init__.py | [
"Apache-2.0"
] | Python | bool_param | <not_specific> | def bool_param(value):
"""
Helper function to convert string values to bool type.
"""
return False if value in (False, 0, 'False', 'false', '0') else True |
Helper function to convert string values to bool type.
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return False if value in (False, 0, 'False', 'false', '0') else True | [
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return False if value in (False, 0, 'False', 'false', '0') else True | 196 | 1,006 |
752df89308491fcefb2c471834f66aebfdb1aa75 | Nithinraot/pythontox | stringz/__init__.py | [
"MIT"
] | Python | count_characters | <not_specific> | def count_characters(string):
"""Return the amount of characters in the string."""
if type(string) is not str:
raise ValueError("This is not a string")
return len(string) | Return the amount of characters in the string. | Return the amount of characters in the string. | [
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if type(string) is not str:
raise ValueError("This is not a string")
return len(string) | 197 | 137 |
0ca358a0d1aeb186b33f989fdcce523ec2a72ae3 | damogranlabs/dlpt | dlpt/json.py | [
"MIT"
] | Python | write | null | def write(data: Dict[str, Any],
fPath: str,
indent: int = 2,
sortKeys: bool = True,
*args):
""" Write given data to a file in a JSON format.
Args:
data: serializable object to store to a file in JSON format.
fPath: destination file path.
indent: number of spaces to use while building file line indentation.
sortKeys: if True, data keys are sorted alphabetically, else
left unchanged.
*args: `json.dump()` additional arguments.
"""
with open(fPath, 'w+') as fHandler:
json.dump(data, fHandler, sort_keys=sortKeys, indent=indent) | Write given data to a file in a JSON format.
Args:
data: serializable object to store to a file in JSON format.
fPath: destination file path.
indent: number of spaces to use while building file line indentation.
sortKeys: if True, data keys are sorted alphabetically, else
left unchanged.
*args: `json.dump()` additional arguments.
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fPath: str,
indent: int = 2,
sortKeys: bool = True,
*args):
with open(fPath, 'w+') as fHandler:
json.dump(data, fHandler, sort_keys=sortKeys, indent=indent) | [
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def write(data: Dict[str, Any],
fPath: str,
indent: int = 2,
sortKeys: bool = True,
*args):
with open(fPath, 'w+') as fHandler:
json.dump(data, fHandler, sort_keys=sortKeys, indent=indent) | 198 | 357 |
a3b9a1b0f3ac451151395b039d12173cc6c0bbd1 | rootasjey/oc-py-p4 | views/tournament/add_player.py | [
"MIT"
] | Python | show_single_player | null | def show_single_player(player):
"""Format & display a single player to the console."""
print("------")
print(
f"• First name: {player.first_name}\n• Last name: {player.last_name}\n• Elo: {player.elo}\n• Sex: {player.sex}\n• Birth date: {player.birth_date}"
)
print("------")
print("") | Format & display a single player to the console. | Format & display a single player to the console. | [
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print(
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print("------")
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)
print("------")
print("") | 199 | 307 |
728d8a694d4b21c4c1082be2cfaa19ea53ea9f5d | Redmar-van-den-Berg/HiFi-assembly | scripts/pyBlast.py | [
"MIT"
] | Python | _minmax | <not_specific> | def _minmax(*args):
""" Return the min and max of the input arguments """
min_ = min(*args)
max_ = max(*args)
return(min_, max_) | Return the min and max of the input arguments | Return the min and max of the input arguments | [
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max_ = max(*args)
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return(min_, max_) | 200 | 836 |
d97d793f7717c0cc65c00e8e10e88d008b072e96 | tjmoran/Formation | hoverset/util/execution.py | [
"MIT"
] | Python | as_thread | <not_specific> | def as_thread(func):
"""
Run the function in a separate thread
:param func: the function to be executed in a separate thread
:return: wrapped function
"""
@functools.wraps(func)
def wrap(*args, **kwargs):
threading.Thread(target=func, args=args, kwargs=kwargs).start()
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import threading
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def wrap(*args, **kwargs):
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return wrap | 201 | 183 |
b11278a9c7dfa20e279b3cf0b8f08bfee67dbab2 | agdsn/sipa | sipa/mail.py | [
"MIT"
] | Python | compose_body | <not_specific> | def compose_body(message: str, header: Optional[Dict[str, Any]] = None):
"""Prepend additional information to a message.
:param message:
:param header: Dict of the additional "key: value"
entries to be prepended to the mail.
:returns: The composed body
"""
if not header:
return message
serialized_header = "\n".join(f"{k}: {v}" for k, v in header.items())
return f"{serialized_header}\n\n{message}" | Prepend additional information to a message.
:param message:
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return message
serialized_header = "\n".join(f"{k}: {v}" for k, v in header.items())
return f"{serialized_header}\n\n{message}" | [
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return f"{serialized_header}\n\n{message}" | 202 | 307 |
f98828ae4464d7a478c76136008a0318867c8888 | jdswalker/Advent-of-Code-2015 | advent_of_code/solvers/day_16.py | [
"MIT"
] | Python | _get_aunts_with_detail_gt | <not_specific> | def _get_aunts_with_detail_gt(aunts, detail, target):
"""Get aunts without the detail or with a value greater than the target
Args:
aunts (dict): Stores remembered details about each Aunt Sue
detail (str): Check aunts based on this remembered detail
target (int): Lower limit for the detail value of the correct Aunt
Returns:
dict: Aunts without the detail or with a detail value > target
"""
return {
aunt: memory for aunt, memory in aunts.items()
if detail not in memory or memory[detail] > target
} | Get aunts without the detail or with a value greater than the target
Args:
aunts (dict): Stores remembered details about each Aunt Sue
detail (str): Check aunts based on this remembered detail
target (int): Lower limit for the detail value of the correct Aunt
Returns:
dict: Aunts without the detail or with a detail value > target
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} | def _get_aunts_with_detail_gt(aunts, detail, target):
return {
aunt: memory for aunt, memory in aunts.items()
if detail not in memory or memory[detail] > target
} | 203 | 793 |
b02e42e8ee7aecd0a6eb07e3eadb33d854800223 | markkvdb/pyscihub | pyscihub/cli.py | [
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"""CLI to download PDFs from Sci-Hub."""
ctx.ensure_object(dict)
ctx.obj["OUTPUT"] = output
ctx.obj["VERBOSE"] = verbose | CLI to download PDFs from Sci-Hub. | CLI to download PDFs from Sci-Hub. | [
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ad282837bde39ae6a8e7a4a227789f7d4566e59a | qkrguswn2401/dstc8-meta-dialog | mldc/preprocessing/featurizer.py | [
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"""
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"""
return False
return not sys.stdout.isatty() |
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7f20e655ce92a0699469b8c404222188dbd6490c | Mati86/sonic-mgmt | tests/common/ixia/qos_fixtures.py | [
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"""
This fixture reads the QOS parameters from SONiC DUT, and creates
priority Vs. DSCP priority port map
Args:
duthosts (pytest fixture) : list of DUTs
rand_one_dut_hostname (pytest fixture): DUT hostname
Returns:
Priority vs. DSCP map (dictionary, key = priority).
Example: {0: [0], 1: [1], 2: [2], 3: [3], 4: [4] ....}
"""
duthost = duthosts[rand_one_dut_hostname]
config_facts = duthost.config_facts(host=duthost.hostname,
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if "DSCP_TO_TC_MAP" not in config_facts.keys():
return None
dscp_to_tc_map_lists = config_facts["DSCP_TO_TC_MAP"]
if len(dscp_to_tc_map_lists) != 1:
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profile = dscp_to_tc_map_lists.keys()[0]
dscp_to_tc_map = dscp_to_tc_map_lists[profile]
result = {}
for dscp in dscp_to_tc_map:
tc = int(dscp_to_tc_map[dscp])
result.setdefault(tc, []).append(int(dscp))
return result |
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Args:
duthosts (pytest fixture) : list of DUTs
rand_one_dut_hostname (pytest fixture): DUT hostname
Returns:
Priority vs. DSCP map (dictionary, key = priority).
Example: {0: [0], 1: [1], 2: [2], 3: [3], 4: [4] ....}
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result = {}
for dscp in dscp_to_tc_map:
tc = int(dscp_to_tc_map[dscp])
result.setdefault(tc, []).append(int(dscp))
return result | 206 | 146 |
79ba399c117d1cd7eb919d3bb5e3b5eb610b01c5 | coldrye-collaboration/feincms3 | feincms3/regions.py | [
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Create and return a regions instance using the bare minimum of a
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"""
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f0df8daa55461bc2328c0fd49de5f1b3f5ee909f | sbabashahi/backend | utilities/utilities.py | [
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"""
Use this in generating and checking JWT token,
and when logout jwt_secret will change so previous JWT token wil be invalidate
:param user:
:return:
"""
return user.profile.jwt_secret |
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4107dc73b7b61e25b8519db94cb6f686dec4fa50 | JustNao/DofusHelper | modules/hdvMissingItems.py | [
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] | Python | printProgressBar | null | def printProgressBar (iteration, total, prefix = '', suffix = '', decimals = 1, length = 100, fill = '█', printEnd = "\r"):
global requestCount
"""
Call in a loop to create terminal progress bar
@params:
iteration - Required : current iteration (Int)
total - Required : total iterations (Int)
prefix - Optional : prefix string (Str)
suffix - Optional : suffix string (Str)
decimals - Optional : positive number of decimals in percent complete (Int)
length - Optional : character length of bar (Int)
fill - Optional : bar fill character (Str)
printEnd - Optional : end character (e.g. "\r", "\r\n") (Str)
"""
requestCount += 1
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
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bar = fill * filledLength + '-' * (length - filledLength)
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# Print New Line on Complete
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global requestCount
requestCount += 1
percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
filledLength = int(length * iteration // total)
bar = fill * filledLength + '-' * (length - filledLength)
print(f'\r{prefix} |{bar}| {percent}% {suffix}', end = printEnd)
if iteration == total:
print() | 209 | 634 |
afa3172084270b8bfaa80d5d1a82df4c00dc739d | datalogics-cgreen/server_core | classifier.py | [
"Apache-2.0"
] | Python | and_up | <not_specific> | def and_up(cls, young, keyword):
"""Encapsulates the logic of what "[x] and up" actually means.
Given the lower end of an age range, tries to determine the
upper end of the range.
"""
if young is None:
return None
if not any(
[keyword.endswith(x) for x in
("and up", "and up.", "+", "+.")
]
):
return None
if young >= 18:
old = young
elif young >= 12:
# "12 and up", "14 and up", etc. are
# generally intended to cover the entire
# YA span.
old = 17
elif young >= 8:
# "8 and up" means something like "8-12"
old = young + 4
else:
# Whereas "3 and up" really means more
# like "3 to 5".
old = young + 2
return old | Encapsulates the logic of what "[x] and up" actually means.
Given the lower end of an age range, tries to determine the
upper end of the range.
| Encapsulates the logic of what "[x] and up" actually means.
Given the lower end of an age range, tries to determine the
upper end of the range. | [
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]
):
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if young >= 18:
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old = young + 4
else:
old = young + 2
return old | 210 | 613 |
762afb689c07f82cb9b864c2768c5ec49c037b18 | neighthan/singleshotpose | singleshotpose/multi_obj_pose_estimation/train_multi.py | [
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] | Python | adjust_learning_rate | <not_specific> | def adjust_learning_rate(optimizer, batch, learning_rate, steps, scales, batch_size):
"""
Modifies `optimizer`'s learning rate(s) directly and returns the new lr.
"""
lr = learning_rate
for i in range(len(steps)):
scale = scales[i] if i < len(scales) else 1
if batch >= steps[i]:
lr = lr * scale
if batch == steps[i]:
break
else:
break
for param_group in optimizer.param_groups:
param_group["lr"] = lr / batch_size
return lr |
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lr = lr * scale
if batch == steps[i]:
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for param_group in optimizer.param_groups:
param_group["lr"] = lr / batch_size
return lr | 211 | 975 |
54d0950e030699802baf5af83854b68fbe485b67 | bunjiboys/lemur | lemur/plugins/lemur_digicert/plugin.py | [
"Apache-2.0"
] | Python | handle_cis_response | <not_specific> | def handle_cis_response(response):
"""
Handle the DigiCert CIS API response and any errors it might have experienced.
:param response:
:return:
"""
if response.status_code > 399:
raise Exception(response.json()['errors'][0]['message'])
return response.json() |
Handle the DigiCert CIS API response and any errors it might have experienced.
:param response:
:return:
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return response.json() | 212 | 819 |
dfb36503f6f0f1f93cb072de3b6a16d109ae3f95 | idkidknow/repeater_analyzer | repeater_analyzer.py | [
"MIT"
] | Python | message_filter | <not_specific> | def message_filter(msg):
"""Return True if the message cannot be considered as a repeat."""
if msg == '' or '--' in msg or 'List:\n' in msg:
return True
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return False | 213 | 137 |
ce30168d742cc09b3ea1ca5e1da4cba007236a5c | reiniervlinschoten/castoredc_api | castoredc_api/importer/helpers.py | [
"MIT"
] | Python | castorize_num_column | <not_specific> | def castorize_num_column(data: list, target_field: "CastorField"):
"""Castorizes a numeric column and replaces errors with 'Error'."""
new_list = []
for datapoint in data:
if datapoint is None:
new_list.append(None)
else:
try:
# Test if data point is convertible to float
numeric_datapoint = float(datapoint)
# Test if between bounds
if target_field.field_max > numeric_datapoint > target_field.field_min:
new_list.append(datapoint)
else:
new_list.append("Error: number out of bounds")
except ValueError:
new_list.append("Error: not a number")
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new_list = []
for datapoint in data:
if datapoint is None:
new_list.append(None)
else:
try:
numeric_datapoint = float(datapoint)
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return new_list | 214 | 528 |
97a7547e2dd8fc08efea8b582df958660254c8ec | NAELIC/dribbler | mbedignore.py | [
"MIT"
] | Python | _is_ignored | <not_specific> | def _is_ignored(path):
"""
Checks whether the specified path is ignored within the Mbed compilation.
In details, takes the .mbedignore file in the path and checks whether it
contains a line with string '*'.
"""
mbedignore_path = os.path.join(path, '.mbedignore')
if not os.path.isfile(mbedignore_path):
return False
with open(mbedignore_path) as f:
lines = f.read().splitlines()
return '*' in lines |
Checks whether the specified path is ignored within the Mbed compilation.
In details, takes the .mbedignore file in the path and checks whether it
contains a line with string '*'.
| Checks whether the specified path is ignored within the Mbed compilation.
In details, takes the .mbedignore file in the path and checks whether it
contains a line with string '*'. | [
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mbedignore_path = os.path.join(path, '.mbedignore')
if not os.path.isfile(mbedignore_path):
return False
with open(mbedignore_path) as f:
lines = f.read().splitlines()
return '*' in lines | [
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} | import os
def _is_ignored(path):
mbedignore_path = os.path.join(path, '.mbedignore')
if not os.path.isfile(mbedignore_path):
return False
with open(mbedignore_path) as f:
lines = f.read().splitlines()
return '*' in lines | 215 | 822 |
c4631afab38dc24e12eb9597fd364eefa032343f | gpooja3/pyvcloud | pyvcloud/vcd/utils.py | [
"Apache-2.0"
] | Python | extract_id | <not_specific> | def extract_id(urn):
"""Extract id from an urn.
'urn:vcloud:catalog:39867ab4-04e0-4b13-b468-08abcc1de810' will produce
'39867ab4-04e0-4b13-b468-08abcc1de810'
:param str urn: a vcloud resource urn.
:return: the extracted id
:rtype: str
"""
if urn is None:
return None
if ':' in urn:
return urn.split(':')[-1]
else:
return urn | Extract id from an urn.
'urn:vcloud:catalog:39867ab4-04e0-4b13-b468-08abcc1de810' will produce
'39867ab4-04e0-4b13-b468-08abcc1de810'
:param str urn: a vcloud resource urn.
:return: the extracted id
:rtype: str
| Extract id from an urn. | [
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if urn is None:
return None
if ':' in urn:
return urn.split(':')[-1]
else:
return urn | [
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],
"outlier_params": [],
"others": []
} | def extract_id(urn):
if urn is None:
return None
if ':' in urn:
return urn.split(':')[-1]
else:
return urn | 216 | 395 |
c46c36f2ee4e1c5ba74d20d8000a24520a0967c8 | ilinastoilkovska/syncTA | helper.py | [
"Apache-2.0"
] | Python | sum_counters_le | <not_specific> | def sum_counters_le(sum_cnt, num):
"""
Returns an SMT inequality assertion given a list of counters and a threshold
"""
return "(<= (+ " + sum_cnt + ") " + str(num) + ")\n" |
Returns an SMT inequality assertion given a list of counters and a threshold
| Returns an SMT inequality assertion given a list of counters and a threshold | [
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} | def sum_counters_le(sum_cnt, num):
return "(<= (+ " + sum_cnt + ") " + str(num) + ")\n" | 217 | 213 |
01923d51812dd3fc50794952473c11d121fbc45d | zzyyrr/fuzzbench | analysis/data_utils.py | [
"Apache-2.0"
] | Python | benchmark_rank_by_median | <not_specific> | def benchmark_rank_by_median(benchmark_snapshot_df):
"""Returns ranking of fuzzers based on median coverage."""
assert benchmark_snapshot_df.time.nunique() == 1, 'Not a snapshot!'
medians = benchmark_snapshot_df.groupby('fuzzer')['edges_covered'].median()
medians.rename('median cov', inplace=True)
return medians.sort_values(ascending=False) | Returns ranking of fuzzers based on median coverage. | Returns ranking of fuzzers based on median coverage. | [
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assert benchmark_snapshot_df.time.nunique() == 1, 'Not a snapshot!'
medians = benchmark_snapshot_df.groupby('fuzzer')['edges_covered'].median()
medians.rename('median cov', inplace=True)
return medians.sort_values(ascending=False) | [
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} | def benchmark_rank_by_median(benchmark_snapshot_df):
assert benchmark_snapshot_df.time.nunique() == 1, 'Not a snapshot!'
medians = benchmark_snapshot_df.groupby('fuzzer')['edges_covered'].median()
medians.rename('median cov', inplace=True)
return medians.sort_values(ascending=False) | 219 | 635 |