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7540540e177a568c94169af73b1747f4da9025d7
akersten/cute-kitchen
src/router/annotations.py
[ "MIT" ]
Python
route_login_required
<not_specific>
def route_login_required(): """ Decorates a function to indicate the requirement for a logged-in session. :return: The decorated function. """ def decorator(fn): fn.route_login_required = True return fn return decorator
Decorates a function to indicate the requirement for a logged-in session. :return: The decorated function.
Decorates a function to indicate the requirement for a logged-in session.
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def route_login_required(): def decorator(fn): fn.route_login_required = True return fn return decorator
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Decorates a function to indicate the requirement for a logged-in session.
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[ "\"\"\"\n Decorates a function to indicate the requirement for a logged-in session.\n :return: The decorated function.\n \"\"\"" ]
[]
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def route_login_required(): def decorator(fn): fn.route_login_required = True return fn return decorator
0
56
c5b891ac420cbeffb65019d562bc382e7bf6367b
MacFarlaneBro/compose-mode
compose_mode/generate.py
[ "MIT" ]
Python
fix_restart
<not_specific>
def fix_restart(restart_config): """ Fix output of docker-compose. docker-compose's "show config" mechanism--the internals of which we use to merge configs--doesn't actually return valid configurations for the "restart" property as they convert it to an internal representation which they then forget to convert back to the yaml format. We do that by hand here. """ try: mrc = restart_config['MaximumRetryCount'] except TypeError: name = restart_config else: name = restart_config['Name'] if name in ['always', 'unless-stopped', 'no']: return name else: return '{}:{}'.format(name, mrc)
Fix output of docker-compose. docker-compose's "show config" mechanism--the internals of which we use to merge configs--doesn't actually return valid configurations for the "restart" property as they convert it to an internal representation which they then forget to convert back to the yaml format. We do that by hand here.
Fix output of docker-compose.
[ "Fix", "output", "of", "docker", "-", "compose", "." ]
def fix_restart(restart_config): try: mrc = restart_config['MaximumRetryCount'] except TypeError: name = restart_config else: name = restart_config['Name'] if name in ['always', 'unless-stopped', 'no']: return name else: return '{}:{}'.format(name, mrc)
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Fix output of docker-compose.
[ "Fix", "output", "of", "docker", "-", "compose", "." ]
[ "\"\"\" Fix output of docker-compose.\n\n docker-compose's \"show config\" mechanism--the internals of which we use to\n merge configs--doesn't actually return valid configurations for the\n \"restart\" property as they convert it to an internal representation which\n they then forget to convert back to the yaml format. We do that by hand\n here.\n \"\"\"" ]
[ { "param": "restart_config", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "restart_config", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def fix_restart(restart_config): try: mrc = restart_config['MaximumRetryCount'] except TypeError: name = restart_config else: name = restart_config['Name'] if name in ['always', 'unless-stopped', 'no']: return name else: return '{}:{}'.format(name, mrc)
1
921
65ef5aa7f6bb80020bfccdca5945fcdda9118ad3
netceteragroup/da4e
assembler.py
[ "MIT" ]
Python
_read_file_and_join_lines
<not_specific>
def _read_file_and_join_lines(file_name): ''' Reads all contents of a file and appends each line into one ',' separated string. Leading and trailing whitespace is removed. Lines having a '#' character as first non- whitespace character are considered as comment and are therefore ignored in the output. @param fileName: the file to read ''' def _normalizeString(line): return line.replace('\n', '').strip() def _isComment(line): return not line.startswith("#") def _isEmptyLine(line): return line != "" with open(file_name, 'r') as file: return ','.join(filter(_isEmptyLine, filter(_isComment, map(_normalizeString, file.readlines()))))
Reads all contents of a file and appends each line into one ',' separated string. Leading and trailing whitespace is removed. Lines having a '#' character as first non- whitespace character are considered as comment and are therefore ignored in the output. @param fileName: the file to read
Reads all contents of a file and appends each line into one ',' separated string. Leading and trailing whitespace is removed. Lines having a '#' character as first non whitespace character are considered as comment and are therefore ignored in the output.
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def _read_file_and_join_lines(file_name): def _normalizeString(line): return line.replace('\n', '').strip() def _isComment(line): return not line.startswith("#") def _isEmptyLine(line): return line != "" with open(file_name, 'r') as file: return ','.join(filter(_isEmptyLine, filter(_isComment, map(_normalizeString, file.readlines()))))
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Reads all contents of a file and appends each line into one ',' separated string.
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[ "'''\n Reads all contents of a file and appends each line into one ',' separated string. \n Leading and trailing whitespace is removed. Lines having a '#' character as first non-\n whitespace character are considered as comment and are therefore ignored in the output. \n @param fileName: the file to read\n '''" ]
[ { "param": "file_name", "type": null } ]
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def _read_file_and_join_lines(file_name): def _normalizeString(line): return line.replace('\n', '').strip() def _isComment(line): return not line.startswith("#") def _isEmptyLine(line): return line != "" with open(file_name, 'r') as file: return ','.join(filter(_isEmptyLine, filter(_isComment, map(_normalizeString, file.readlines()))))
2
312
4ba9d06164e542a8b6d024e64d49a8773a1ff650
WolfgangFahl/pyOnlineSpreadSheetEditing
onlinespreadsheet/tablequery.py
[ "Apache-2.0" ]
Python
match
<not_specific>
def match(pattern:str,string:str): ''' re match search for the given pattern with ignore case ''' return re.search(pattern=pattern, string=string, flags=re.IGNORECASE)
re match search for the given pattern with ignore case
re match search for the given pattern with ignore case
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def match(pattern:str,string:str): return re.search(pattern=pattern, string=string, flags=re.IGNORECASE)
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re match search for the given pattern with ignore case
[ "re", "match", "search", "for", "the", "given", "pattern", "with", "ignore", "case" ]
[ "'''\n re match search for the given pattern with ignore case\n '''" ]
[ { "param": "pattern", "type": "str" }, { "param": "string", "type": "str" } ]
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import re def match(pattern:str,string:str): return re.search(pattern=pattern, string=string, flags=re.IGNORECASE)
3
994
ed05c8d76b4e4beff6fca1cee61e2aadf3732abe
tomerten/PyElegantSDDS
pyelegantsdds/elegantrun.py
[ "MIT" ]
Python
write_parallel_run_script
null
def write_parallel_run_script(sif): """ Method to generate parallel elegant run script. Parameters: ----------- sif: str path to singularity container """ bashstrlist = [ "#!/bin/bash", "pele={}".format(sif), 'cmd="bash temp_run_pelegant.sh"', "", "$pele $cmd $1", ] bashstr = "\n".join(bashstrlist) # write to file with open("run_pelegant.sh", "w") as f: f.write(bashstr)
Method to generate parallel elegant run script. Parameters: ----------- sif: str path to singularity container
Method to generate parallel elegant run script. str path to singularity container
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def write_parallel_run_script(sif): bashstrlist = [ "#!/bin/bash", "pele={}".format(sif), 'cmd="bash temp_run_pelegant.sh"', "", "$pele $cmd $1", ] bashstr = "\n".join(bashstrlist) with open("run_pelegant.sh", "w") as f: f.write(bashstr)
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Method to generate parallel elegant run script.
[ "Method", "to", "generate", "parallel", "elegant", "run", "script", "." ]
[ "\"\"\"\n Method to generate parallel elegant run\n script.\n\n Parameters:\n -----------\n sif: str\n path to singularity container\n\n \"\"\"", "# write to file" ]
[ { "param": "sif", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "sif", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def write_parallel_run_script(sif): bashstrlist = [ "#!/bin/bash", "pele={}".format(sif), 'cmd="bash temp_run_pelegant.sh"', "", "$pele $cmd $1", ] bashstr = "\n".join(bashstrlist) with open("run_pelegant.sh", "w") as f: f.write(bashstr)
5
673
bf09424b7fd16830410dec98a364876163fae903
erikagardini/InferringMusicAndVisualArtStyleEvolution
python/utilities.py
[ "MIT" ]
Python
find_min_max_indexes
<not_specific>
def find_min_max_indexes(dates): """ Get the index of the min value and the max value (centroids are not considered) Args: [ndarray int] dates: dates matrix Returns: [float] index_min: index of the min value [int] index_max: index of the max value """ min = dates[0] index_min = 0 max = dates[0] index_max = 0 for i in range(0, dates.shape[0]): if dates[i] < min and dates[i] != -1: min = dates[i] index_min = i if dates[i] > max and dates[i] != -1: max = dates[i] index_max = i return index_min, index_max
Get the index of the min value and the max value (centroids are not considered) Args: [ndarray int] dates: dates matrix Returns: [float] index_min: index of the min value [int] index_max: index of the max value
Get the index of the min value and the max value (centroids are not considered)
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def find_min_max_indexes(dates): min = dates[0] index_min = 0 max = dates[0] index_max = 0 for i in range(0, dates.shape[0]): if dates[i] < min and dates[i] != -1: min = dates[i] index_min = i if dates[i] > max and dates[i] != -1: max = dates[i] index_max = i return index_min, index_max
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Get the index of the min value and the max value (centroids are not considered)
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[ "\"\"\"\n Get the index of the min value and the max value (centroids are not considered)\n Args:\n [ndarray int] dates: dates matrix\n\n Returns:\n [float] index_min: index of the min value\n [int] index_max: index of the max value\n \"\"\"" ]
[ { "param": "dates", "type": null } ]
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def find_min_max_indexes(dates): min = dates[0] index_min = 0 max = dates[0] index_max = 0 for i in range(0, dates.shape[0]): if dates[i] < min and dates[i] != -1: min = dates[i] index_min = i if dates[i] > max and dates[i] != -1: max = dates[i] index_max = i return index_min, index_max
6
721
8eae126dbf8a8baeab1e2e976d363b1bcf02863a
muvr/muvr-ml
sensorcnn/dataset/utils.py
[ "BSD-3-Clause" ]
Python
csv_file_iterator
null
def csv_file_iterator(root_directory): """Returns a generator (iterator) of absolute file paths for CSV files in a given directory""" for root_path, _, files in os.walk(root_directory, followlinks=True): for f in files: if f.endswith("csv"): yield os.path.join(root_path, f)
Returns a generator (iterator) of absolute file paths for CSV files in a given directory
Returns a generator (iterator) of absolute file paths for CSV files in a given directory
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def csv_file_iterator(root_directory): for root_path, _, files in os.walk(root_directory, followlinks=True): for f in files: if f.endswith("csv"): yield os.path.join(root_path, f)
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Returns a generator (iterator) of absolute file paths for CSV files in a given directory
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[ "\"\"\"Returns a generator (iterator) of absolute file paths for CSV files in a given directory\"\"\"" ]
[ { "param": "root_directory", "type": null } ]
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import os def csv_file_iterator(root_directory): for root_path, _, files in os.walk(root_directory, followlinks=True): for f in files: if f.endswith("csv"): yield os.path.join(root_path, f)
7
671
4c8f7cefbccbd3770a96057fbf07a756c0ce334d
intrlocutr/nightcoreify
nightcorei.py
[ "0BSD" ]
Python
create_tags
list
def create_tags(tags: list) -> list: """Prepares tags for a new upload. Keeps as many old tags as possible while adding a "nightcore" tag.""" to_add = 'nightcore' # The total number of characters in YouTube video tags can't exceed 400. # We're adding the "nightcore" tag, so we'll only keep this many characters of the original tags. target_len = 400 - len(to_add) new_tags = [] length = 0 # Keep tags up until they can no longer fit within our target. for tag in tags: length += len(tag) if length < target_len: new_tags.append(tag) else: break new_tags.append(to_add) return new_tags
Prepares tags for a new upload. Keeps as many old tags as possible while adding a "nightcore" tag.
Prepares tags for a new upload. Keeps as many old tags as possible while adding a "nightcore" tag.
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def create_tags(tags: list) -> list: to_add = 'nightcore' target_len = 400 - len(to_add) new_tags = [] length = 0 for tag in tags: length += len(tag) if length < target_len: new_tags.append(tag) else: break new_tags.append(to_add) return new_tags
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Prepares tags for a new upload.
[ "Prepares", "tags", "for", "a", "new", "upload", "." ]
[ "\"\"\"Prepares tags for a new upload. Keeps as many old tags as possible while adding a \"nightcore\" tag.\"\"\"", "# The total number of characters in YouTube video tags can't exceed 400.", "# We're adding the \"nightcore\" tag, so we'll only keep this many characters of the original tags.", "# Keep tags up until they can no longer fit within our target." ]
[ { "param": "tags", "type": "list" } ]
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def create_tags(tags: list) -> list: to_add = 'nightcore' target_len = 400 - len(to_add) new_tags = [] length = 0 for tag in tags: length += len(tag) if length < target_len: new_tags.append(tag) else: break new_tags.append(to_add) return new_tags
8
208
903fc63fede8ca3f8a8dc0b5f4ca496131e1a105
JustKowalski/sound_separation
datasets/fuss/reverberate_and_mix.py
[ "Apache-2.0" ]
Python
write_item_dict
null
def write_item_dict(item_dict, item_file, separate=False): """Write tab separated source/rir lists in files for train/validate/eval.""" if not separate: with open(item_file, 'w') as f: for subfolder in item_dict: for example in item_dict[subfolder]: line = '\t'.join([example] + item_dict[subfolder][example]) f.write(line + '\n') else: for subfolder in item_dict: item_base, item_ext = item_file.split('.') item_file_sub = item_base + '_' + subfolder + '.' + item_ext with open(item_file_sub, 'w') as f: for example in item_dict[subfolder]: line = '\t'.join([example] + item_dict[subfolder][example]) f.write(line + '\n')
Write tab separated source/rir lists in files for train/validate/eval.
Write tab separated source/rir lists in files for train/validate/eval.
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def write_item_dict(item_dict, item_file, separate=False): if not separate: with open(item_file, 'w') as f: for subfolder in item_dict: for example in item_dict[subfolder]: line = '\t'.join([example] + item_dict[subfolder][example]) f.write(line + '\n') else: for subfolder in item_dict: item_base, item_ext = item_file.split('.') item_file_sub = item_base + '_' + subfolder + '.' + item_ext with open(item_file_sub, 'w') as f: for example in item_dict[subfolder]: line = '\t'.join([example] + item_dict[subfolder][example]) f.write(line + '\n')
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Write tab separated source/rir lists in files for train/validate/eval.
[ "Write", "tab", "separated", "source", "/", "rir", "lists", "in", "files", "for", "train", "/", "validate", "/", "eval", "." ]
[ "\"\"\"Write tab separated source/rir lists in files for train/validate/eval.\"\"\"" ]
[ { "param": "item_dict", "type": null }, { "param": "item_file", "type": null }, { "param": "separate", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "item_dict", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "item_file", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "separate", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def write_item_dict(item_dict, item_file, separate=False): if not separate: with open(item_file, 'w') as f: for subfolder in item_dict: for example in item_dict[subfolder]: line = '\t'.join([example] + item_dict[subfolder][example]) f.write(line + '\n') else: for subfolder in item_dict: item_base, item_ext = item_file.split('.') item_file_sub = item_base + '_' + subfolder + '.' + item_ext with open(item_file_sub, 'w') as f: for example in item_dict[subfolder]: line = '\t'.join([example] + item_dict[subfolder][example]) f.write(line + '\n')
9
677
8f34f83cd4a60a8d8e72e31e4fde3b9e819b893f
BAMWelDX/weldx
weldx/tests/test_time.py
[ "BSD-3-Clause" ]
Python
_transform_array
<not_specific>
def _transform_array(data, is_array, is_scalar): """Transform an array into a scalar, single value array or return in unmodified.""" if not is_array: return data[0] if is_scalar: return [data[0]] return data
Transform an array into a scalar, single value array or return in unmodified.
Transform an array into a scalar, single value array or return in unmodified.
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def _transform_array(data, is_array, is_scalar): if not is_array: return data[0] if is_scalar: return [data[0]] return data
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Transform an array into a scalar, single value array or return in unmodified.
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[ "\"\"\"Transform an array into a scalar, single value array or return in unmodified.\"\"\"" ]
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{ "returns": [], "raises": [], "params": [ { "identifier": "data", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "is_array", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "is_scalar", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def _transform_array(data, is_array, is_scalar): if not is_array: return data[0] if is_scalar: return [data[0]] return data
10
524
cc94e3893f2982011fc08d2790d839d5a009c4f5
EmersonAires/Introducao_a_ciencia_da_computacao_com_Python
Exercicios_Resolvidos/Parte 2/Semana 1/exercicio_12_1.py
[ "MIT" ]
Python
extrair_coluna
<not_specific>
def extrair_coluna(b_mat, col): '''retorna uma lista com os elementos da coluna indicada''' coluna_b_mat = [] for linha in b_mat: elemento = linha[col] coluna_b_mat.append(elemento) return coluna_b_mat
retorna uma lista com os elementos da coluna indicada
retorna uma lista com os elementos da coluna indicada
[ "retorna", "uma", "lista", "com", "os", "elementos", "da", "coluna", "indicada" ]
def extrair_coluna(b_mat, col): coluna_b_mat = [] for linha in b_mat: elemento = linha[col] coluna_b_mat.append(elemento) return coluna_b_mat
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retorna uma lista com os elementos da coluna indicada
[ "retorna", "uma", "lista", "com", "os", "elementos", "da", "coluna", "indicada" ]
[ "'''retorna uma lista com os elementos da coluna indicada'''" ]
[ { "param": "b_mat", "type": null }, { "param": "col", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "b_mat", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "col", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def extrair_coluna(b_mat, col): coluna_b_mat = [] for linha in b_mat: elemento = linha[col] coluna_b_mat.append(elemento) return coluna_b_mat
11
667
5bb08e1a378e746bf276fdb1704d41f5409d7d65
trisongz/file_io
fileio/core/py_utils.py
[ "MIT" ]
Python
temporary_assignment
null
def temporary_assignment(obj, attr, value): """Temporarily assign obj.attr to value.""" original = getattr(obj, attr) setattr(obj, attr, value) try: yield finally: setattr(obj, attr, original)
Temporarily assign obj.attr to value.
Temporarily assign obj.attr to value.
[ "Temporarily", "assign", "obj", ".", "attr", "to", "value", "." ]
def temporary_assignment(obj, attr, value): original = getattr(obj, attr) setattr(obj, attr, value) try: yield finally: setattr(obj, attr, original)
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Temporarily assign obj.attr to value.
[ "Temporarily", "assign", "obj", ".", "attr", "to", "value", "." ]
[ "\"\"\"Temporarily assign obj.attr to value.\"\"\"" ]
[ { "param": "obj", "type": null }, { "param": "attr", "type": null }, { "param": "value", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "obj", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "attr", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "value", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def temporary_assignment(obj, attr, value): original = getattr(obj, attr) setattr(obj, attr, value) try: yield finally: setattr(obj, attr, original)
12
748
63484325eaa962f8f517d4993495bc314d2325ed
alchem0x2A/vasp-interactive-test
examples/ex11_k8s_minimal.py
[ "MIT" ]
Python
_thread_calculate
<not_specific>
def _thread_calculate(atoms, energy): """A threaded version of atoms.get_potential_energy. Energy is a one-member list ideas taken from https://wiki.fysik.dtu.dk/ase/_modules/ase/neb.html#NEB """ energy[0] = atoms.get_potential_energy() return
A threaded version of atoms.get_potential_energy. Energy is a one-member list ideas taken from https://wiki.fysik.dtu.dk/ase/_modules/ase/neb.html#NEB
A threaded version of atoms.get_potential_energy.
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def _thread_calculate(atoms, energy): energy[0] = atoms.get_potential_energy() return
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A threaded version of atoms.get_potential_energy.
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[ "\"\"\"A threaded version of atoms.get_potential_energy. Energy is a one-member list\n ideas taken from https://wiki.fysik.dtu.dk/ase/_modules/ase/neb.html#NEB\n \"\"\"" ]
[ { "param": "atoms", "type": null }, { "param": "energy", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "atoms", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "energy", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def _thread_calculate(atoms, energy): energy[0] = atoms.get_potential_energy() return
13
315
e71a7da7f51510edc97fee6d78a7582b46d166d7
seung-lab/mapbuffer
mapbuffer/mapbuffer.py
[ "BSD-3-Clause" ]
Python
eytzinger_sort
<not_specific>
def eytzinger_sort(inpt, output, i = 0, k = 1): """ Takes an ascendingly sorted input and an equal sized output buffer into which to rewrite the input in eytzinger order. Modified from: https://algorithmica.org/en/eytzinger """ if k <= len(inpt): i = eytzinger_sort(inpt, output, i, 2 * k) output[k - 1] = inpt[i] i += 1 i = eytzinger_sort(inpt, output,i, 2 * k + 1) return i
Takes an ascendingly sorted input and an equal sized output buffer into which to rewrite the input in eytzinger order. Modified from: https://algorithmica.org/en/eytzinger
Takes an ascendingly sorted input and an equal sized output buffer into which to rewrite the input in eytzinger order.
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def eytzinger_sort(inpt, output, i = 0, k = 1): if k <= len(inpt): i = eytzinger_sort(inpt, output, i, 2 * k) output[k - 1] = inpt[i] i += 1 i = eytzinger_sort(inpt, output,i, 2 * k + 1) return i
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Takes an ascendingly sorted input and an equal sized output buffer into which to rewrite the input in eytzinger order.
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[ "\"\"\"\n Takes an ascendingly sorted input and \n an equal sized output buffer into which to \n rewrite the input in eytzinger order.\n\n Modified from:\n https://algorithmica.org/en/eytzinger\n \"\"\"" ]
[ { "param": "inpt", "type": null }, { "param": "output", "type": null }, { "param": "i", "type": null }, { "param": "k", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "inpt", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "output", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "i", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "k", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def eytzinger_sort(inpt, output, i = 0, k = 1): if k <= len(inpt): i = eytzinger_sort(inpt, output, i, 2 * k) output[k - 1] = inpt[i] i += 1 i = eytzinger_sort(inpt, output,i, 2 * k + 1) return i
14
993
b2984037c6a8ed370b786cafaa04ec91d894c19a
GHzytp/PyLorentz
GUI/PyLorentz_GUI.py
[ "BSD-3-Clause" ]
Python
change_visibility
None
def change_visibility(window: sg.Window, elem_val_list: List[Tuple[sg.Element, Any]]) -> None: """ Take a list of element keys and change visibility of the element. Args: window : The element representing the main GUI window. elem_val_list : The list of elements with values whose state is to be changed. Returns: None """ for elem_key, val in elem_val_list: window[elem_key].Update(visible=val)
Take a list of element keys and change visibility of the element. Args: window : The element representing the main GUI window. elem_val_list : The list of elements with values whose state is to be changed. Returns: None
Take a list of element keys and change visibility of the element.
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def change_visibility(window: sg.Window, elem_val_list: List[Tuple[sg.Element, Any]]) -> None: for elem_key, val in elem_val_list: window[elem_key].Update(visible=val)
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Take a list of element keys and change visibility of the element.
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[ "\"\"\" Take a list of element keys and change\n visibility of the element.\n\n Args:\n window : The element representing the main GUI window.\n elem_val_list : The list of elements with values whose\n state is to be changed.\n\n Returns:\n None\n \"\"\"" ]
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def change_visibility(window: sg.Window, elem_val_list: List[Tuple[sg.Element, Any]]) -> None: for elem_key, val in elem_val_list: window[elem_key].Update(visible=val)
15
239
61d3a295b3c1cedde8c1eab628b02734cf1c0cd5
BensonGathu/neighborhood
virtual/lib/python3.8/site-packages/PIL/ImageChops.py
[ "Unlicense" ]
Python
multiply
<not_specific>
def multiply(image1, image2): """ Superimposes two images on top of each other. If you multiply an image with a solid black image, the result is black. If you multiply with a solid white image, the image is unaffected. .. code-block:: python out = image1 * image2 / MAX :rtype: :py:class:`~PIL.Image.Image` """ image1.load() image2.load() return image1._new(image1.im.chop_multiply(image2.im))
Superimposes two images on top of each other. If you multiply an image with a solid black image, the result is black. If you multiply with a solid white image, the image is unaffected. .. code-block:: python out = image1 * image2 / MAX :rtype: :py:class:`~PIL.Image.Image`
Superimposes two images on top of each other. If you multiply an image with a solid black image, the result is black. If you multiply with a solid white image, the image is unaffected. code-block:: python out = image1 * image2 / MAX
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def multiply(image1, image2): image1.load() image2.load() return image1._new(image1.im.chop_multiply(image2.im))
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Superimposes two images on top of each other.
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[ "\"\"\"\n Superimposes two images on top of each other.\n\n If you multiply an image with a solid black image, the result is black. If\n you multiply with a solid white image, the image is unaffected.\n\n .. code-block:: python\n\n out = image1 * image2 / MAX\n\n :rtype: :py:class:`~PIL.Image.Image`\n \"\"\"" ]
[ { "param": "image1", "type": null }, { "param": "image2", "type": null } ]
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def multiply(image1, image2): image1.load() image2.load() return image1._new(image1.im.chop_multiply(image2.im))
16
804
2d8da20bf2fb315a41e314223d05cc62ea9dcae5
DeepanshS/mrsimulator-ui
app/sims/method/__init__.py
[ "BSD-3-Clause" ]
Python
generate_sidepanel
<not_specific>
def generate_sidepanel(method, index): """Generate scrollable side panel listing for methods""" title = html.B(f"Method {index}", className="") # method name name = html.Div(method["name"], className="") # method channel(s) channels = ", ".join(method["channels"]) channels = html.Div(f"Channel: {channels}") # n dimensions n_dim = len(method["spectral_dimensions"]) n_dim = html.Div(f"Dimensions: {n_dim}") a_tag = html.A([title, name, channels, n_dim]) # The H6(index) only shows for smaller screen sizes. return html.Li( [html.H6(index), html.Div(a_tag)], # draggable="true", className="list-group-item", # id={"type": "select-method-index", "index": index}, )
Generate scrollable side panel listing for methods
Generate scrollable side panel listing for methods
[ "Generate", "scrollable", "side", "panel", "listing", "for", "methods" ]
def generate_sidepanel(method, index): title = html.B(f"Method {index}", className="") name = html.Div(method["name"], className="") channels = ", ".join(method["channels"]) channels = html.Div(f"Channel: {channels}") n_dim = len(method["spectral_dimensions"]) n_dim = html.Div(f"Dimensions: {n_dim}") a_tag = html.A([title, name, channels, n_dim]) return html.Li( [html.H6(index), html.Div(a_tag)], className="list-group-item", )
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Generate scrollable side panel listing for methods
[ "Generate", "scrollable", "side", "panel", "listing", "for", "methods" ]
[ "\"\"\"Generate scrollable side panel listing for methods\"\"\"", "# method name", "# method channel(s)", "# n dimensions", "# The H6(index) only shows for smaller screen sizes.", "# draggable=\"true\",", "# id={\"type\": \"select-method-index\", \"index\": index}," ]
[ { "param": "method", "type": null }, { "param": "index", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "method", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "index", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import html def generate_sidepanel(method, index): title = html.B(f"Method {index}", className="") name = html.Div(method["name"], className="") channels = ", ".join(method["channels"]) channels = html.Div(f"Channel: {channels}") n_dim = len(method["spectral_dimensions"]) n_dim = html.Div(f"Dimensions: {n_dim}") a_tag = html.A([title, name, channels, n_dim]) return html.Li( [html.H6(index), html.Div(a_tag)], className="list-group-item", )
18
196
6b1bbc653af085e7c5303ff686cc116c3b15f540
QuantumJack/GNN
lib/net_gen.py
[ "Apache-2.0" ]
Python
__generate_nets
<not_specific>
def __generate_nets(gnw_path, main_netfile_path, net_size, num_nets_per_size, outdir_path): """ Generate random network modules extracted from main_net_filename Args: gnw_path: path to GeneNetWeaver ".jar" file. main_netfile_path: filepath for the main network used for module extraction. net_size: size of the extracted modules. num_nets_per_size: number of modules to be extracted for each size. outdir_path: directory to store extracted network modules. """ if not os.path.exists(outdir_path): os.mkdir(outdir_path) command = ("java -jar {!s} --extract -c data/settings.txt --input-net {!s}" " --input-net-format=0 --random-seed --greedy-selection --subnet-size={!s}" " --num-subnets={!s} --output-net-format=0 --output-path={!s}" ).format(gnw_path, main_netfile_path, net_size, num_nets_per_size, outdir_path) subprocess.run([command], shell=True) file_prefix = os.path.basename(main_netfile_path)[:-4] generated_files = glob.glob("{!s}/{!s}*.tsv".format(outdir_path, file_prefix)) return generated_files
Generate random network modules extracted from main_net_filename Args: gnw_path: path to GeneNetWeaver ".jar" file. main_netfile_path: filepath for the main network used for module extraction. net_size: size of the extracted modules. num_nets_per_size: number of modules to be extracted for each size. outdir_path: directory to store extracted network modules.
Generate random network modules extracted from main_net_filename
[ "Generate", "random", "network", "modules", "extracted", "from", "main_net_filename" ]
def __generate_nets(gnw_path, main_netfile_path, net_size, num_nets_per_size, outdir_path): if not os.path.exists(outdir_path): os.mkdir(outdir_path) command = ("java -jar {!s} --extract -c data/settings.txt --input-net {!s}" " --input-net-format=0 --random-seed --greedy-selection --subnet-size={!s}" " --num-subnets={!s} --output-net-format=0 --output-path={!s}" ).format(gnw_path, main_netfile_path, net_size, num_nets_per_size, outdir_path) subprocess.run([command], shell=True) file_prefix = os.path.basename(main_netfile_path)[:-4] generated_files = glob.glob("{!s}/{!s}*.tsv".format(outdir_path, file_prefix)) return generated_files
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Generate random network modules extracted from main_net_filename
[ "Generate", "random", "network", "modules", "extracted", "from", "main_net_filename" ]
[ "\"\"\" Generate random network modules extracted from main_net_filename\n Args:\n gnw_path: path to GeneNetWeaver \".jar\" file.\n main_netfile_path: filepath for the main network used for module extraction.\n net_size: size of the extracted modules.\n num_nets_per_size: number of modules to be extracted for each size.\n outdir_path: directory to store extracted network modules.\n \"\"\"" ]
[ { "param": "gnw_path", "type": null }, { "param": "main_netfile_path", "type": null }, { "param": "net_size", "type": null }, { "param": "num_nets_per_size", "type": null }, { "param": "outdir_path", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "gnw_path", "type": null, "docstring": "path to GeneNetWeaver \".jar\" file.", "docstring_tokens": [ "path", "to", "GeneNetWeaver", "\"", ".", "jar", "\"", "file", "." ], "default": null, "is_optional": null }, { "identifier": "main_netfile_path", "type": null, "docstring": "filepath for the main network used for module extraction.", "docstring_tokens": [ "filepath", "for", "the", "main", "network", "used", "for", "module", "extraction", "." ], "default": null, "is_optional": null }, { "identifier": "net_size", "type": null, "docstring": "size of the extracted modules.", "docstring_tokens": [ "size", "of", "the", "extracted", "modules", "." ], "default": null, "is_optional": null }, { "identifier": "num_nets_per_size", "type": null, "docstring": "number of modules to be extracted for each size.", "docstring_tokens": [ "number", "of", "modules", "to", "be", "extracted", "for", "each", "size", "." ], "default": null, "is_optional": null }, { "identifier": "outdir_path", "type": null, "docstring": "directory to store extracted network modules.", "docstring_tokens": [ "directory", "to", "store", "extracted", "network", "modules", "." ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import subprocess import os import glob def __generate_nets(gnw_path, main_netfile_path, net_size, num_nets_per_size, outdir_path): if not os.path.exists(outdir_path): os.mkdir(outdir_path) command = ("java -jar {!s} --extract -c data/settings.txt --input-net {!s}" " --input-net-format=0 --random-seed --greedy-selection --subnet-size={!s}" " --num-subnets={!s} --output-net-format=0 --output-path={!s}" ).format(gnw_path, main_netfile_path, net_size, num_nets_per_size, outdir_path) subprocess.run([command], shell=True) file_prefix = os.path.basename(main_netfile_path)[:-4] generated_files = glob.glob("{!s}/{!s}*.tsv".format(outdir_path, file_prefix)) return generated_files
20
539
5258c905652f8e689e7f69238996a5b2f5d95f0d
clbarnes/pyboolnet
boolnet/misc.py
[ "MIT" ]
Python
prod
<not_specific>
def prod(numbers): """ Find the product of a sequence :param numbers: Sequence of numbers :return: Their product """ ret = 1 for number in numbers: ret *= number return ret
Find the product of a sequence :param numbers: Sequence of numbers :return: Their product
Find the product of a sequence
[ "Find", "the", "product", "of", "a", "sequence" ]
def prod(numbers): ret = 1 for number in numbers: ret *= number return ret
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Find the product of a sequence
[ "Find", "the", "product", "of", "a", "sequence" ]
[ "\"\"\"\n Find the product of a sequence\n\n :param numbers: Sequence of numbers\n :return: Their product\n \"\"\"" ]
[ { "param": "numbers", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "numbers", "type": null, "docstring": "Sequence of numbers", "docstring_tokens": [ "Sequence", "of", "numbers" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def prod(numbers): ret = 1 for number in numbers: ret *= number return ret
23
413
664e3c76f043a3063bee9e66192f6daf1dad61e8
sullivanmj/pywemo
pywemo/ouimeaux_device/api/rules_db.py
[ "MIT" ]
Python
_unpack_db
<not_specific>
def _unpack_db(content, db_file): """Unpack the sqlite database from a .zip file content.""" zip_contents = io.BytesIO(content) with zipfile.ZipFile(zip_contents) as zip_file: inner_file_name = zip_file.namelist()[0] with zip_file.open(inner_file_name) as zipped_db_file: db_file.write(zipped_db_file.read()) db_file.flush() return inner_file_name raise RuntimeError("Could not find database within zip file")
Unpack the sqlite database from a .zip file content.
Unpack the sqlite database from a .zip file content.
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def _unpack_db(content, db_file): zip_contents = io.BytesIO(content) with zipfile.ZipFile(zip_contents) as zip_file: inner_file_name = zip_file.namelist()[0] with zip_file.open(inner_file_name) as zipped_db_file: db_file.write(zipped_db_file.read()) db_file.flush() return inner_file_name raise RuntimeError("Could not find database within zip file")
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Unpack the sqlite database from a .zip file content.
[ "Unpack", "the", "sqlite", "database", "from", "a", ".", "zip", "file", "content", "." ]
[ "\"\"\"Unpack the sqlite database from a .zip file content.\"\"\"" ]
[ { "param": "content", "type": null }, { "param": "db_file", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "content", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "db_file", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import zipfile import io def _unpack_db(content, db_file): zip_contents = io.BytesIO(content) with zipfile.ZipFile(zip_contents) as zip_file: inner_file_name = zip_file.namelist()[0] with zip_file.open(inner_file_name) as zipped_db_file: db_file.write(zipped_db_file.read()) db_file.flush() return inner_file_name raise RuntimeError("Could not find database within zip file")
24
619
ae5462bd222a5c5bd4c72139814f3a36c73c6486
4con/hello-gn
build/android/apksize.py
[ "BSD-3-Clause-No-Nuclear-License-2014", "BSD-3-Clause" ]
Python
print_human_readable_size_info
null
def print_human_readable_size_info(apk): """Prints size information in human readable format. Args: apk: ApkSizeInfo object """ files = apk.processed_files logging.critical('Stats for files as they exist within the apk:') for ext in files: logging.critical(' %-8s %s bytes in %s files', ext, files[ext]['compressed_bytes'], files[ext]['number']) logging.critical('--------------------------------------') logging.critical( 'All Files: %s bytes in %s files', apk.compressed_size, apk.total_files) logging.critical('APK Size: %s', apk.apk_size) logging.critical('APK overhead: %s', apk.apk_size - apk.compressed_size) logging.critical('--------------------------------------') logging.critical('Stats for files when extracted from the apk:') for ext in files: logging.critical(' %-8s %s bytes in %s files', ext, files[ext]['uncompressed_bytes'], files[ext]['number']) logging.critical('--------------------------------------') logging.critical( 'All Files: %s bytes in %s files', apk.uncompressed_size, apk.total_files)
Prints size information in human readable format. Args: apk: ApkSizeInfo object
Prints size information in human readable format.
[ "Prints", "size", "information", "in", "human", "readable", "format", "." ]
def print_human_readable_size_info(apk): files = apk.processed_files logging.critical('Stats for files as they exist within the apk:') for ext in files: logging.critical(' %-8s %s bytes in %s files', ext, files[ext]['compressed_bytes'], files[ext]['number']) logging.critical('--------------------------------------') logging.critical( 'All Files: %s bytes in %s files', apk.compressed_size, apk.total_files) logging.critical('APK Size: %s', apk.apk_size) logging.critical('APK overhead: %s', apk.apk_size - apk.compressed_size) logging.critical('--------------------------------------') logging.critical('Stats for files when extracted from the apk:') for ext in files: logging.critical(' %-8s %s bytes in %s files', ext, files[ext]['uncompressed_bytes'], files[ext]['number']) logging.critical('--------------------------------------') logging.critical( 'All Files: %s bytes in %s files', apk.uncompressed_size, apk.total_files)
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Prints size information in human readable format.
[ "Prints", "size", "information", "in", "human", "readable", "format", "." ]
[ "\"\"\"Prints size information in human readable format.\n\n Args:\n apk: ApkSizeInfo object\n \"\"\"" ]
[ { "param": "apk", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "apk", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import logging def print_human_readable_size_info(apk): files = apk.processed_files logging.critical('Stats for files as they exist within the apk:') for ext in files: logging.critical(' %-8s %s bytes in %s files', ext, files[ext]['compressed_bytes'], files[ext]['number']) logging.critical('--------------------------------------') logging.critical( 'All Files: %s bytes in %s files', apk.compressed_size, apk.total_files) logging.critical('APK Size: %s', apk.apk_size) logging.critical('APK overhead: %s', apk.apk_size - apk.compressed_size) logging.critical('--------------------------------------') logging.critical('Stats for files when extracted from the apk:') for ext in files: logging.critical(' %-8s %s bytes in %s files', ext, files[ext]['uncompressed_bytes'], files[ext]['number']) logging.critical('--------------------------------------') logging.critical( 'All Files: %s bytes in %s files', apk.uncompressed_size, apk.total_files)
25
803
cfb9c7e09aba8ed937f808b341f34b7eee06405b
finex-dev/finex
finex/ratios.py
[ "BSD-3-Clause" ]
Python
roce
<not_specific>
def roce(net_income, preferred_dividends, average_common_equity): """Computes return on common equity. Parameters ---------- net_income : int or float Net income preferred_dividends : int or float Preferred dividends average_common_equity : int or float Average common equity Returns ------- out : int or float Return on common equity """ return (net_income - preferred_dividends) / average_common_equity
Computes return on common equity. Parameters ---------- net_income : int or float Net income preferred_dividends : int or float Preferred dividends average_common_equity : int or float Average common equity Returns ------- out : int or float Return on common equity
Computes return on common equity. Parameters net_income : int or float Net income preferred_dividends : int or float Preferred dividends average_common_equity : int or float Average common equity Returns out : int or float Return on common equity
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def roce(net_income, preferred_dividends, average_common_equity): return (net_income - preferred_dividends) / average_common_equity
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Computes return on common equity.
[ "Computes", "return", "on", "common", "equity", "." ]
[ "\"\"\"Computes return on common equity.\n\n Parameters\n ----------\n net_income : int or float\n Net income\n preferred_dividends : int or float\n Preferred dividends\n average_common_equity : int or float\n Average common equity\n\n Returns\n -------\n out : int or float\n Return on common equity\n \"\"\"" ]
[ { "param": "net_income", "type": null }, { "param": "preferred_dividends", "type": null }, { "param": "average_common_equity", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "net_income", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "preferred_dividends", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "average_common_equity", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def roce(net_income, preferred_dividends, average_common_equity): return (net_income - preferred_dividends) / average_common_equity
26
306
177f8f7c5c114b75e46eb141489e8ed3694972a9
guesswhohaha/learntools
learntools/core/asserts.py
[ "Apache-2.0" ]
Python
assert_has_columns
null
def assert_has_columns(df, cols, name="dataframe", strict=False): """Assert that the given dataframe contains columns with the given names. If strict is True, then assert it has *only* those columns. """ for col in cols: assert col in df.columns, "Expected {} to have column `{}`".format( name, col ) if strict: for col in df.columns: msg = "Unexpected column in {}: `{}`".format(name, col) assert col in cols, msg
Assert that the given dataframe contains columns with the given names. If strict is True, then assert it has *only* those columns.
Assert that the given dataframe contains columns with the given names. If strict is True, then assert it has *only* those columns.
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def assert_has_columns(df, cols, name="dataframe", strict=False): for col in cols: assert col in df.columns, "Expected {} to have column `{}`".format( name, col ) if strict: for col in df.columns: msg = "Unexpected column in {}: `{}`".format(name, col) assert col in cols, msg
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Assert that the given dataframe contains columns with the given names.
[ "Assert", "that", "the", "given", "dataframe", "contains", "columns", "with", "the", "given", "names", "." ]
[ "\"\"\"Assert that the given dataframe contains columns with the given names.\n If strict is True, then assert it has *only* those columns.\n \"\"\"" ]
[ { "param": "df", "type": null }, { "param": "cols", "type": null }, { "param": "name", "type": null }, { "param": "strict", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "df", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "cols", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "name", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "strict", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def assert_has_columns(df, cols, name="dataframe", strict=False): for col in cols: assert col in df.columns, "Expected {} to have column `{}`".format( name, col ) if strict: for col in df.columns: msg = "Unexpected column in {}: `{}`".format(name, col) assert col in cols, msg
27
419
bb9bc874cfb0cf7a29aef5ba2b188b6dea437065
maurogaravello/Pirati
plot.py
[ "MIT" ]
Python
check_negative
<not_specific>
def check_negative(value): """ check if a value is negative""" ivalue = int(value) if ivalue <= 0: raise argparse.ArgumentTypeError("%s is an invalid entry" % value) return ivalue
check if a value is negative
check if a value is negative
[ "check", "if", "a", "value", "is", "negative" ]
def check_negative(value): ivalue = int(value) if ivalue <= 0: raise argparse.ArgumentTypeError("%s is an invalid entry" % value) return ivalue
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check if a value is negative
[ "check", "if", "a", "value", "is", "negative" ]
[ "\"\"\" check if a value is negative\"\"\"" ]
[ { "param": "value", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "value", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import argparse def check_negative(value): ivalue = int(value) if ivalue <= 0: raise argparse.ArgumentTypeError("%s is an invalid entry" % value) return ivalue
28
856
642f0f99428865d2e704e0a3535fd3e4cd3f9e98
larsOhne/pvdn
pvdn/detection/train.py
[ "CC0-1.0" ]
Python
print_end_summary
null
def print_end_summary(epochs: int, output_dir: str, best_epochs: dict, best_metrics: dict): """ Outputs the final summary to the terminal. :param epochs: number of epochs the model has been trained :type epochs: int :param output_dir: directory where the results are written to :type output_dir: str :param best_epochs: dictionary with metrics as keys, and epoch number of the model that has the best performance in it as value :type best_epochs: dict :param best_metrics: dictionary storing the best result for each metric :type best_metrics: dict """ print(f"\nTraining completed successfully for {epochs} epochs.\n" f"Logs written to {output_dir}.") best_str = [f"{k}: {v:4f} (epoch {best_epochs[k]})" for k, v in best_metrics.items()] print(f"-------------- Best --------------") for s in best_str: print(s)
Outputs the final summary to the terminal. :param epochs: number of epochs the model has been trained :type epochs: int :param output_dir: directory where the results are written to :type output_dir: str :param best_epochs: dictionary with metrics as keys, and epoch number of the model that has the best performance in it as value :type best_epochs: dict :param best_metrics: dictionary storing the best result for each metric :type best_metrics: dict
Outputs the final summary to the terminal.
[ "Outputs", "the", "final", "summary", "to", "the", "terminal", "." ]
def print_end_summary(epochs: int, output_dir: str, best_epochs: dict, best_metrics: dict): print(f"\nTraining completed successfully for {epochs} epochs.\n" f"Logs written to {output_dir}.") best_str = [f"{k}: {v:4f} (epoch {best_epochs[k]})" for k, v in best_metrics.items()] print(f"-------------- Best --------------") for s in best_str: print(s)
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Outputs the final summary to the terminal.
[ "Outputs", "the", "final", "summary", "to", "the", "terminal", "." ]
[ "\"\"\"\n Outputs the final summary to the terminal.\n :param epochs: number of epochs the model has been trained\n :type epochs: int\n :param output_dir: directory where the results are written to\n :type output_dir: str\n :param best_epochs: dictionary with metrics as keys, and epoch number of\n the model that has the best performance in it as value\n :type best_epochs: dict\n :param best_metrics: dictionary storing the best result for each metric\n :type best_metrics: dict\n \"\"\"" ]
[ { "param": "epochs", "type": "int" }, { "param": "output_dir", "type": "str" }, { "param": "best_epochs", "type": "dict" }, { "param": "best_metrics", "type": "dict" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "epochs", "type": "int", "docstring": "number of epochs the model has been trained", "docstring_tokens": [ "number", "of", "epochs", "the", "model", "has", "been", "trained" ], "default": null, "is_optional": null }, { "identifier": "output_dir", "type": "str", "docstring": "directory where the results are written to", "docstring_tokens": [ "directory", "where", "the", "results", "are", "written", "to" ], "default": null, "is_optional": null }, { "identifier": "best_epochs", "type": "dict", "docstring": "dictionary with metrics as keys, and epoch number of\nthe model that has the best performance in it as value", "docstring_tokens": [ "dictionary", "with", "metrics", "as", "keys", "and", "epoch", "number", "of", "the", "model", "that", "has", "the", "best", "performance", "in", "it", "as", "value" ], "default": null, "is_optional": null }, { "identifier": "best_metrics", "type": "dict", "docstring": "dictionary storing the best result for each metric", "docstring_tokens": [ "dictionary", "storing", "the", "best", "result", "for", "each", "metric" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def print_end_summary(epochs: int, output_dir: str, best_epochs: dict, best_metrics: dict): print(f"\nTraining completed successfully for {epochs} epochs.\n" f"Logs written to {output_dir}.") best_str = [f"{k}: {v:4f} (epoch {best_epochs[k]})" for k, v in best_metrics.items()] print(f"-------------- Best --------------") for s in best_str: print(s)
29
22
8a51d4283261aa0674abb481617734ad2aaf10f1
j19sch/pytest-logfest
pytest_logfest/plugin.py
[ "MIT" ]
Python
fxt_function_logger
null
def fxt_function_logger(request, module_logger, session_filememoryhandler): """ Yields a logger, child of the module logger and named the name of the function. Adds records for test started, setup error, test fail, and test ended. """ logger = module_logger.getChild(request.node.name) logger.info("TEST STARTED") yield logger try: if request.node.rep_setup.failed: logger.warning("SETUP ERROR") except AttributeError: pass try: if request.node.rep_call.failed: logger.warning("TEST FAIL") except AttributeError: pass logger.info("TEST ENDED\n") session_filememoryhandler.flush_with_filter_on_info()
Yields a logger, child of the module logger and named the name of the function. Adds records for test started, setup error, test fail, and test ended.
Yields a logger, child of the module logger and named the name of the function. Adds records for test started, setup error, test fail, and test ended.
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def fxt_function_logger(request, module_logger, session_filememoryhandler): logger = module_logger.getChild(request.node.name) logger.info("TEST STARTED") yield logger try: if request.node.rep_setup.failed: logger.warning("SETUP ERROR") except AttributeError: pass try: if request.node.rep_call.failed: logger.warning("TEST FAIL") except AttributeError: pass logger.info("TEST ENDED\n") session_filememoryhandler.flush_with_filter_on_info()
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Yields a logger, child of the module logger and named the name of the function.
[ "Yields", "a", "logger", "child", "of", "the", "module", "logger", "and", "named", "the", "name", "of", "the", "function", "." ]
[ "\"\"\"\n Yields a logger, child of the module logger and named the name of the function.\n Adds records for test started, setup error, test fail, and test ended.\n\n \"\"\"" ]
[ { "param": "request", "type": null }, { "param": "module_logger", "type": null }, { "param": "session_filememoryhandler", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "request", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "module_logger", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "session_filememoryhandler", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def fxt_function_logger(request, module_logger, session_filememoryhandler): logger = module_logger.getChild(request.node.name) logger.info("TEST STARTED") yield logger try: if request.node.rep_setup.failed: logger.warning("SETUP ERROR") except AttributeError: pass try: if request.node.rep_call.failed: logger.warning("TEST FAIL") except AttributeError: pass logger.info("TEST ENDED\n") session_filememoryhandler.flush_with_filter_on_info()
30
301
4d978bbc81c4e00039d1224dd4790f6483e5af9b
abugler/SMLFinalProject
runners/utils.py
[ "MIT" ]
Python
disp_script
null
def disp_script(spec): """ Displays the arguments for a script in a readable fashion in logging. Args: spec (dict): Dictionary containing script parameters. """ logging.info( f"\n" f" Running {spec['script']} with args:\n" f" config: {spec['config']}\n" f" run_in: {spec['run_in']}\n" f" num_gpus: {spec['num_gpus']}\n" f" blocking: {spec['blocking']}\n" )
Displays the arguments for a script in a readable fashion in logging. Args: spec (dict): Dictionary containing script parameters.
Displays the arguments for a script in a readable fashion in logging.
[ "Displays", "the", "arguments", "for", "a", "script", "in", "a", "readable", "fashion", "in", "logging", "." ]
def disp_script(spec): logging.info( f"\n" f" Running {spec['script']} with args:\n" f" config: {spec['config']}\n" f" run_in: {spec['run_in']}\n" f" num_gpus: {spec['num_gpus']}\n" f" blocking: {spec['blocking']}\n" )
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Displays the arguments for a script in a readable fashion in logging.
[ "Displays", "the", "arguments", "for", "a", "script", "in", "a", "readable", "fashion", "in", "logging", "." ]
[ "\"\"\"\n Displays the arguments for a script in a readable fashion in\n logging.\n \n Args:\n spec (dict): Dictionary containing script parameters.\n \"\"\"" ]
[ { "param": "spec", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "spec", "type": null, "docstring": "Dictionary containing script parameters.", "docstring_tokens": [ "Dictionary", "containing", "script", "parameters", "." ], "default": null, "is_optional": false } ], "outlier_params": [], "others": [] }
import logging def disp_script(spec): logging.info( f"\n" f" Running {spec['script']} with args:\n" f" config: {spec['config']}\n" f" run_in: {spec['run_in']}\n" f" num_gpus: {spec['num_gpus']}\n" f" blocking: {spec['blocking']}\n" )
31
1,017
bcc04efb1ef7d3258b74f184ec0c0258e4e8c5fa
elyase/altair
altair/expr/core.py
[ "BSD-3-Clause" ]
Python
_js_repr
<not_specific>
def _js_repr(val): """Return a javascript-safe string representation of val""" if val is True: return 'true' elif val is False: return 'false' elif val is None: return 'null' else: return repr(val)
Return a javascript-safe string representation of val
Return a javascript-safe string representation of val
[ "Return", "a", "javascript", "-", "safe", "string", "representation", "of", "val" ]
def _js_repr(val): if val is True: return 'true' elif val is False: return 'false' elif val is None: return 'null' else: return repr(val)
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Return a javascript-safe string representation of val
[ "Return", "a", "javascript", "-", "safe", "string", "representation", "of", "val" ]
[ "\"\"\"Return a javascript-safe string representation of val\"\"\"" ]
[ { "param": "val", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "val", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def _js_repr(val): if val is True: return 'true' elif val is False: return 'false' elif val is None: return 'null' else: return repr(val)
32
126
892fd63e452f2cae6fe22559ccb6584141ee4b92
Bielorusse/Erdorbit_random
script.py
[ "MIT" ]
Python
multiplyArrayByScalar
<not_specific>
def multiplyArrayByScalar(inputArray, scalar): ''' Multiplying each component of a 2D array by a scalar - Inputs: inputArray input array scal input scalar - Outputs: outputArray output array ''' outputArray = [] for j in range(len(inputArray)): outputArray.append(inputArray[j]) for k in range(len(inputArray[j])): outputArray[j][k] = inputArray[j][k] * scalar return outputArray
Multiplying each component of a 2D array by a scalar - Inputs: inputArray input array scal input scalar - Outputs: outputArray output array
Multiplying each component of a 2D array by a scalar Inputs: inputArray input array scal input scalar Outputs: outputArray output array
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def multiplyArrayByScalar(inputArray, scalar): outputArray = [] for j in range(len(inputArray)): outputArray.append(inputArray[j]) for k in range(len(inputArray[j])): outputArray[j][k] = inputArray[j][k] * scalar return outputArray
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Multiplying each component of a 2D array by a scalar Inputs: inputArray input array scal input scalar Outputs: outputArray output array
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[ "'''\n\tMultiplying each component of a 2D array by a scalar\n \t- Inputs:\n inputArray input array\n scal input scalar\n \t- Outputs:\n \t\t outputArray output array\n '''" ]
[ { "param": "inputArray", "type": null }, { "param": "scalar", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "inputArray", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "scalar", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def multiplyArrayByScalar(inputArray, scalar): outputArray = [] for j in range(len(inputArray)): outputArray.append(inputArray[j]) for k in range(len(inputArray[j])): outputArray[j][k] = inputArray[j][k] * scalar return outputArray
33
1,004
950f789d70c9ff60ddf38726d7b8992d103f289c
google-research/pyreach
pyreach/common/base/debug.py
[ "Apache-2.0" ]
Python
debug
None
def debug(msg: str) -> None: """Write debug message to stderr. Debug message consists file name, line number and function name of the calling routine. Args: msg: a custom message. """ parent_frame = inspect.stack()[1] file = parent_frame[1] line = parent_frame[2] func = parent_frame[3] sys.stderr.write("{}:{}-{}: {}\n".format(file, line, func, msg)) sys.stderr.flush()
Write debug message to stderr. Debug message consists file name, line number and function name of the calling routine. Args: msg: a custom message.
Write debug message to stderr. Debug message consists file name, line number and function name of the calling routine.
[ "Write", "debug", "message", "to", "stderr", ".", "Debug", "message", "consists", "file", "name", "line", "number", "and", "function", "name", "of", "the", "calling", "routine", "." ]
def debug(msg: str) -> None: parent_frame = inspect.stack()[1] file = parent_frame[1] line = parent_frame[2] func = parent_frame[3] sys.stderr.write("{}:{}-{}: {}\n".format(file, line, func, msg)) sys.stderr.flush()
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Write debug message to stderr.
[ "Write", "debug", "message", "to", "stderr", "." ]
[ "\"\"\"Write debug message to stderr.\n\n Debug message consists file name, line number and function name\n of the calling routine.\n\n Args:\n msg: a custom message.\n \"\"\"" ]
[ { "param": "msg", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "msg", "type": "str", "docstring": "a custom message.", "docstring_tokens": [ "a", "custom", "message", "." ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import inspect import sys def debug(msg: str) -> None: parent_frame = inspect.stack()[1] file = parent_frame[1] line = parent_frame[2] func = parent_frame[3] sys.stderr.write("{}:{}-{}: {}\n".format(file, line, func, msg)) sys.stderr.flush()
34
504
9a6a097e06c1ab31ad5a3c4d60545ff85a3c54d4
cookbrite/ebs-deploy
ebs_deploy/__init__.py
[ "MIT" ]
Python
override_scaling
<not_specific>
def override_scaling(option_settings, min_size, max_size): """ takes the merged option_settings and injects custom min/max autoscaling sizes """ match_namespace = "aws:autoscaling:asg" match_keys = {"MinSize": min_size, "MaxSize": max_size} copied_option_settings = [] for (namespace, key, value) in option_settings: new_option = (namespace, key, value) if match_namespace == namespace and key in match_keys: new_option = (namespace, key, match_keys[key]) copied_option_settings.append(new_option) return copied_option_settings
takes the merged option_settings and injects custom min/max autoscaling sizes
takes the merged option_settings and injects custom min/max autoscaling sizes
[ "takes", "the", "merged", "option_settings", "and", "injects", "custom", "min", "/", "max", "autoscaling", "sizes" ]
def override_scaling(option_settings, min_size, max_size): match_namespace = "aws:autoscaling:asg" match_keys = {"MinSize": min_size, "MaxSize": max_size} copied_option_settings = [] for (namespace, key, value) in option_settings: new_option = (namespace, key, value) if match_namespace == namespace and key in match_keys: new_option = (namespace, key, match_keys[key]) copied_option_settings.append(new_option) return copied_option_settings
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takes the merged option_settings and injects custom min/max autoscaling sizes
[ "takes", "the", "merged", "option_settings", "and", "injects", "custom", "min", "/", "max", "autoscaling", "sizes" ]
[ "\"\"\" takes the merged option_settings and injects custom min/max autoscaling sizes \"\"\"" ]
[ { "param": "option_settings", "type": null }, { "param": "min_size", "type": null }, { "param": "max_size", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "option_settings", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "min_size", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "max_size", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def override_scaling(option_settings, min_size, max_size): match_namespace = "aws:autoscaling:asg" match_keys = {"MinSize": min_size, "MaxSize": max_size} copied_option_settings = [] for (namespace, key, value) in option_settings: new_option = (namespace, key, value) if match_namespace == namespace and key in match_keys: new_option = (namespace, key, match_keys[key]) copied_option_settings.append(new_option) return copied_option_settings
35
744
440b71cde91480a4acc2ad27be6b5c2c2c2604ee
iamholger/professor
pyext/professor2/ipol.py
[ "MIT" ]
Python
mk_ipolinputs
<not_specific>
def mk_ipolinputs(params): """ Make sorted run name and parameter name & value lists, suitable for passing to prof.Ipol params is a dict (actually, prefer OrderedDict) of run_names -> param_vals, as returned from read_rundata """ runs = sorted(params.keys()) if not runs: return runs, [], [[]] paramnames = params[runs[0]].keys() paramslist = [[params[run][pn] for pn in paramnames] for run in runs] return runs, paramnames, paramslist
Make sorted run name and parameter name & value lists, suitable for passing to prof.Ipol params is a dict (actually, prefer OrderedDict) of run_names -> param_vals, as returned from read_rundata
Make sorted run name and parameter name & value lists, suitable for passing to prof.Ipol params is a dict (actually, prefer OrderedDict) of run_names -> param_vals, as returned from read_rundata
[ "Make", "sorted", "run", "name", "and", "parameter", "name", "&", "value", "lists", "suitable", "for", "passing", "to", "prof", ".", "Ipol", "params", "is", "a", "dict", "(", "actually", "prefer", "OrderedDict", ")", "of", "run_names", "-", ">", "param_vals", "as", "returned", "from", "read_rundata" ]
def mk_ipolinputs(params): runs = sorted(params.keys()) if not runs: return runs, [], [[]] paramnames = params[runs[0]].keys() paramslist = [[params[run][pn] for pn in paramnames] for run in runs] return runs, paramnames, paramslist
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Make sorted run name and parameter name & value lists, suitable for passing to prof.Ipol params is a dict (actually, prefer OrderedDict) of run_names -> param_vals, as returned from read_rundata
[ "Make", "sorted", "run", "name", "and", "parameter", "name", "&", "value", "lists", "suitable", "for", "passing", "to", "prof", ".", "Ipol", "params", "is", "a", "dict", "(", "actually", "prefer", "OrderedDict", ")", "of", "run_names", "-", ">", "param_vals", "as", "returned", "from", "read_rundata" ]
[ "\"\"\"\n Make sorted run name and parameter name & value lists, suitable for passing to prof.Ipol\n\n params is a dict (actually, prefer OrderedDict) of run_names -> param_vals,\n as returned from read_rundata\n \"\"\"" ]
[ { "param": "params", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "params", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def mk_ipolinputs(params): runs = sorted(params.keys()) if not runs: return runs, [], [[]] paramnames = params[runs[0]].keys() paramslist = [[params[run][pn] for pn in paramnames] for run in runs] return runs, paramnames, paramslist
36
703
6ba8475b25a768b98f6094c5b04ba522fbead45a
Hyperparticle/lct-master
charles-university/statistical-nlp/assignment-3/tag.py
[ "MIT" ]
Python
open_text
<not_specific>
def open_text(filename): """Reads a text line by line, applies light preprocessing, and returns an array of words and tags""" with open(filename, encoding='iso-8859-2') as f: content = f.readlines() preprocess = lambda word: tuple(word.strip().rsplit('/', 1)) return [preprocess(word) for word in content]
Reads a text line by line, applies light preprocessing, and returns an array of words and tags
Reads a text line by line, applies light preprocessing, and returns an array of words and tags
[ "Reads", "a", "text", "line", "by", "line", "applies", "light", "preprocessing", "and", "returns", "an", "array", "of", "words", "and", "tags" ]
def open_text(filename): with open(filename, encoding='iso-8859-2') as f: content = f.readlines() preprocess = lambda word: tuple(word.strip().rsplit('/', 1)) return [preprocess(word) for word in content]
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Reads a text line by line, applies light preprocessing, and returns an array of words and tags
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[ "\"\"\"Reads a text line by line, applies light preprocessing, and returns an array of words and tags\"\"\"" ]
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def open_text(filename): with open(filename, encoding='iso-8859-2') as f: content = f.readlines() preprocess = lambda word: tuple(word.strip().rsplit('/', 1)) return [preprocess(word) for word in content]
37
628
9b15eca2a02be787e6c3a05fff838aba8bbda7f9
jschmidtnj/CS115
hw5.py
[ "MIT" ]
Python
fast_lucas
<not_specific>
def fast_lucas(n): '''Returns the nth Lucas number using the memoization technique shown in class and lab. The Lucas numbers are as follows: [2, 1, 3, 4, 7, 11, ...]''' def lucasMemo(n, memo): if n in memo: return memo[n] if n == 0: result = 2 elif n == 1: result = 1 else: result = lucasMemo(n-1, memo) + lucasMemo(n-2, memo) memo[n] = result return result return lucasMemo(n, {})
Returns the nth Lucas number using the memoization technique shown in class and lab. The Lucas numbers are as follows: [2, 1, 3, 4, 7, 11, ...]
Returns the nth Lucas number using the memoization technique shown in class and lab.
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def fast_lucas(n): def lucasMemo(n, memo): if n in memo: return memo[n] if n == 0: result = 2 elif n == 1: result = 1 else: result = lucasMemo(n-1, memo) + lucasMemo(n-2, memo) memo[n] = result return result return lucasMemo(n, {})
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Returns the nth Lucas number using the memoization technique shown in class and lab.
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def fast_lucas(n): def lucasMemo(n, memo): if n in memo: return memo[n] if n == 0: result = 2 elif n == 1: result = 1 else: result = lucasMemo(n-1, memo) + lucasMemo(n-2, memo) memo[n] = result return result return lucasMemo(n, {})
38
371
4b509323441ad1cfa76f24e0b712b509f5f23a01
fangohr/oommf-python
vision/oommf/mifgen.py
[ "BSD-2-Clause" ]
Python
_save_mif
<not_specific>
def _save_mif(sim_object, target): """ save_mif(sim_object) Function takes a simulation instance and then saves the mif to file in order to run a simulation, and also += 1 to the N_mifs in order to keep track of multiple simulation steps, ie if a parameter will change. Parameters ---------- sim_object : instance A simulation instance. Returns ------- string The path to the mif file """ path = sim_object.name + "_" + str(sim_object.t) + "_" + str(target) + ".mif" f = open(path, 'w') f.write(sim_object.mif) return path
save_mif(sim_object) Function takes a simulation instance and then saves the mif to file in order to run a simulation, and also += 1 to the N_mifs in order to keep track of multiple simulation steps, ie if a parameter will change. Parameters ---------- sim_object : instance A simulation instance. Returns ------- string The path to the mif file
save_mif(sim_object) Function takes a simulation instance and then saves the mif to file in order to run a simulation, and also += 1 to the N_mifs in order to keep track of multiple simulation steps, ie if a parameter will change. Parameters sim_object : instance A simulation instance. Returns string The path to the mif file
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def _save_mif(sim_object, target): path = sim_object.name + "_" + str(sim_object.t) + "_" + str(target) + ".mif" f = open(path, 'w') f.write(sim_object.mif) return path
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save_mif(sim_object) Function takes a simulation instance and then saves the mif to file in order to run a simulation, and also += 1 to the N_mifs in order to keep track of multiple simulation steps, ie if a parameter will change.
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[ "\"\"\"\n save_mif(sim_object)\n\n Function takes a simulation instance and then saves the mif to file in\n order to run a simulation, and also += 1 to the N_mifs in order to keep\n track of multiple simulation steps, ie if a parameter will change.\n \n Parameters\n ----------\n sim_object : instance\n A simulation instance.\n \n Returns\n -------\n string\n The path to the mif file\n \"\"\"" ]
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def _save_mif(sim_object, target): path = sim_object.name + "_" + str(sim_object.t) + "_" + str(target) + ".mif" f = open(path, 'w') f.write(sim_object.mif) return path
39
157
fdbaead8c186a6baca4ad86b5dbf22f4c5e3e1b2
masenf/metaforward
src/metaforward.py
[ "BSD-2-Clause" ]
Python
shadowed_attributes_from_bases
<not_specific>
def shadowed_attributes_from_bases(mcs, bases, dct=None): """ Collect attributes from a base class and the dct of a class under construction. :param bases: sequence of types :param dct: optional dict of attributes for a class under construction :return: set of attributes which should not be proxied """ shadowed_attributes = set() if dct is not None: shadowed_attributes.update(dct.keys()) for base in bases: shadowed_attributes.update(dir(base)) return shadowed_attributes
Collect attributes from a base class and the dct of a class under construction. :param bases: sequence of types :param dct: optional dict of attributes for a class under construction :return: set of attributes which should not be proxied
Collect attributes from a base class and the dct of a class under construction.
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def shadowed_attributes_from_bases(mcs, bases, dct=None): shadowed_attributes = set() if dct is not None: shadowed_attributes.update(dct.keys()) for base in bases: shadowed_attributes.update(dir(base)) return shadowed_attributes
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Collect attributes from a base class and the dct of a class under construction.
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def shadowed_attributes_from_bases(mcs, bases, dct=None): shadowed_attributes = set() if dct is not None: shadowed_attributes.update(dct.keys()) for base in bases: shadowed_attributes.update(dir(base)) return shadowed_attributes
40
867
efb7d56381ffb678d115f43d13a2057ef73b85d9
nuxy/bittrex_autotrader
bittrex_autotrader/__main__.py
[ "MIT" ]
Python
_list_of_dict_filter_by
<not_specific>
def _list_of_dict_filter_by(data, key, value): """ Returns list of dictionary items filtered by key/value. Args: data (dict): Data to filter. key (str): Dictionary key search. value (str): Dictionary key value match. Returns: list """ return [ item for i, item in enumerate(data) if data[i].get(key) == value ]
Returns list of dictionary items filtered by key/value. Args: data (dict): Data to filter. key (str): Dictionary key search. value (str): Dictionary key value match. Returns: list
Returns list of dictionary items filtered by key/value.
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def _list_of_dict_filter_by(data, key, value): return [ item for i, item in enumerate(data) if data[i].get(key) == value ]
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Returns list of dictionary items filtered by key/value.
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def _list_of_dict_filter_by(data, key, value): return [ item for i, item in enumerate(data) if data[i].get(key) == value ]
41
411
95e101001497dcd38c9653f10ac6de81199769ab
d-chambers/OpenSarToolkit
ost/helpers/scihub.py
[ "MIT" ]
Python
connect
<not_specific>
def connect(uname=None, pword=None, base_url="https://apihub.copernicus.eu/apihub"): """Generates an opener for the Copernicus apihub/dhus :param uname: username of Copernicus' scihub :type uname: str :param pword: password of Copernicus' scihub :type pword: str :param base_url: :return: an urllib opener instance for Copernicus' scihub :rtype: opener object """ if not uname: print( " If you do not have a Copernicus Scihub user" " account go to: https://scihub.copernicus.eu" ) uname = input(" Your Copernicus Scihub Username:") if not pword: pword = getpass.getpass(" Your Copernicus Scihub Password:") # create opener manager = urllib.request.HTTPPasswordMgrWithDefaultRealm() manager.add_password(None, base_url, uname, pword) handler = urllib.request.HTTPBasicAuthHandler(manager) opener = urllib.request.build_opener(handler) return opener
Generates an opener for the Copernicus apihub/dhus :param uname: username of Copernicus' scihub :type uname: str :param pword: password of Copernicus' scihub :type pword: str :param base_url: :return: an urllib opener instance for Copernicus' scihub :rtype: opener object
Generates an opener for the Copernicus apihub/dhus
[ "Generates", "an", "opener", "for", "the", "Copernicus", "apihub", "/", "dhus" ]
def connect(uname=None, pword=None, base_url="https://apihub.copernicus.eu/apihub"): if not uname: print( " If you do not have a Copernicus Scihub user" " account go to: https://scihub.copernicus.eu" ) uname = input(" Your Copernicus Scihub Username:") if not pword: pword = getpass.getpass(" Your Copernicus Scihub Password:") manager = urllib.request.HTTPPasswordMgrWithDefaultRealm() manager.add_password(None, base_url, uname, pword) handler = urllib.request.HTTPBasicAuthHandler(manager) opener = urllib.request.build_opener(handler) return opener
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Generates an opener for the Copernicus apihub/dhus
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[ "\"\"\"Generates an opener for the Copernicus apihub/dhus\n\n\n :param uname: username of Copernicus' scihub\n :type uname: str\n :param pword: password of Copernicus' scihub\n :type pword: str\n :param base_url:\n :return: an urllib opener instance for Copernicus' scihub\n :rtype: opener object\n \"\"\"", "# create opener" ]
[ { "param": "uname", "type": null }, { "param": "pword", "type": null }, { "param": "base_url", "type": null } ]
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import getpass import urllib def connect(uname=None, pword=None, base_url="https://apihub.copernicus.eu/apihub"): if not uname: print( " If you do not have a Copernicus Scihub user" " account go to: https://scihub.copernicus.eu" ) uname = input(" Your Copernicus Scihub Username:") if not pword: pword = getpass.getpass(" Your Copernicus Scihub Password:") manager = urllib.request.HTTPPasswordMgrWithDefaultRealm() manager.add_password(None, base_url, uname, pword) handler = urllib.request.HTTPBasicAuthHandler(manager) opener = urllib.request.build_opener(handler) return opener
43
125
32e3f226d9e450744b37a06b1b5e8904828a3571
beli302/Pitches
virtual/lib/python3.6/site-packages/flask_uploads.py
[ "MIT" ]
Python
patch_request_class
<not_specific>
def patch_request_class(app, size=64 * 1024 * 1024): """ By default, Flask will accept uploads to an arbitrary size. While Werkzeug switches uploads from memory to a temporary file when they hit 500 KiB, it's still possible for someone to overload your disk space with a gigantic file. This patches the app's request class's `~werkzeug.BaseRequest.max_content_length` attribute so that any upload larger than the given size is rejected with an HTTP error. .. note:: In Flask 0.6, you can do this by setting the `MAX_CONTENT_LENGTH` setting, without patching the request class. To emulate this behavior, you can pass `None` as the size (you must pass it explicitly). That is the best way to call this function, as it won't break the Flask 0.6 functionality if it exists. .. versionchanged:: 0.1.1 :param app: The app to patch the request class of. :param size: The maximum size to accept, in bytes. The default is 64 MiB. If it is `None`, the app's `MAX_CONTENT_LENGTH` configuration setting will be used to patch. """ if size is None: if isinstance(app.request_class.__dict__['max_content_length'], property): return size = app.config.get('MAX_CONTENT_LENGTH') reqclass = app.request_class patched = type(reqclass.__name__, (reqclass,), {'max_content_length': size}) app.request_class = patched
By default, Flask will accept uploads to an arbitrary size. While Werkzeug switches uploads from memory to a temporary file when they hit 500 KiB, it's still possible for someone to overload your disk space with a gigantic file. This patches the app's request class's `~werkzeug.BaseRequest.max_content_length` attribute so that any upload larger than the given size is rejected with an HTTP error. .. note:: In Flask 0.6, you can do this by setting the `MAX_CONTENT_LENGTH` setting, without patching the request class. To emulate this behavior, you can pass `None` as the size (you must pass it explicitly). That is the best way to call this function, as it won't break the Flask 0.6 functionality if it exists. .. versionchanged:: 0.1.1 :param app: The app to patch the request class of. :param size: The maximum size to accept, in bytes. The default is 64 MiB. If it is `None`, the app's `MAX_CONTENT_LENGTH` configuration setting will be used to patch.
By default, Flask will accept uploads to an arbitrary size. While Werkzeug switches uploads from memory to a temporary file when they hit 500 KiB, it's still possible for someone to overload your disk space with a gigantic file. This patches the app's request class's `~werkzeug.BaseRequest.max_content_length` attribute so that any upload larger than the given size is rejected with an HTTP error. In Flask 0.6, you can do this by setting the `MAX_CONTENT_LENGTH` setting, without patching the request class. To emulate this behavior, you can pass `None` as the size (you must pass it explicitly). That is the best way to call this function, as it won't break the Flask 0.6 functionality if it exists.
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def patch_request_class(app, size=64 * 1024 * 1024): if size is None: if isinstance(app.request_class.__dict__['max_content_length'], property): return size = app.config.get('MAX_CONTENT_LENGTH') reqclass = app.request_class patched = type(reqclass.__name__, (reqclass,), {'max_content_length': size}) app.request_class = patched
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By default, Flask will accept uploads to an arbitrary size.
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[ "\"\"\"\n By default, Flask will accept uploads to an arbitrary size. While Werkzeug\n switches uploads from memory to a temporary file when they hit 500 KiB,\n it's still possible for someone to overload your disk space with a\n gigantic file.\n\n This patches the app's request class's\n `~werkzeug.BaseRequest.max_content_length` attribute so that any upload\n larger than the given size is rejected with an HTTP error.\n\n .. note::\n\n In Flask 0.6, you can do this by setting the `MAX_CONTENT_LENGTH`\n setting, without patching the request class. To emulate this behavior,\n you can pass `None` as the size (you must pass it explicitly). That is\n the best way to call this function, as it won't break the Flask 0.6\n functionality if it exists.\n\n .. versionchanged:: 0.1.1\n\n :param app: The app to patch the request class of.\n :param size: The maximum size to accept, in bytes. The default is 64 MiB.\n If it is `None`, the app's `MAX_CONTENT_LENGTH` configuration\n setting will be used to patch.\n \"\"\"" ]
[ { "param": "app", "type": null }, { "param": "size", "type": null } ]
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def patch_request_class(app, size=64 * 1024 * 1024): if size is None: if isinstance(app.request_class.__dict__['max_content_length'], property): return size = app.config.get('MAX_CONTENT_LENGTH') reqclass = app.request_class patched = type(reqclass.__name__, (reqclass,), {'max_content_length': size}) app.request_class = patched
44
142
303426d5ee7004b9dd1a7767a2408579d6fb2033
neptune-ml/sacred
sacred/commandline_options.py
[ "MIT" ]
Python
apply
null
def apply(cls, args, run): """Add priority info for this run.""" try: priority = float(args) except ValueError: raise ValueError( "The PRIORITY argument must be a number! " "(but was '{}')".format(args) ) run.meta_info["priority"] = priority
Add priority info for this run.
Add priority info for this run.
[ "Add", "priority", "info", "for", "this", "run", "." ]
def apply(cls, args, run): try: priority = float(args) except ValueError: raise ValueError( "The PRIORITY argument must be a number! " "(but was '{}')".format(args) ) run.meta_info["priority"] = priority
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Add priority info for this run.
[ "Add", "priority", "info", "for", "this", "run", "." ]
[ "\"\"\"Add priority info for this run.\"\"\"" ]
[ { "param": "cls", "type": null }, { "param": "args", "type": null }, { "param": "run", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "cls", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "args", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "run", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def apply(cls, args, run): try: priority = float(args) except ValueError: raise ValueError( "The PRIORITY argument must be a number! " "(but was '{}')".format(args) ) run.meta_info["priority"] = priority
45
194
866a30195e6c69b24064d40dcd0432c7464bdea9
tvhahn/Tool-Wear-Files
load_data.py
[ "MIT" ]
Python
tool_no_apply
<not_specific>
def tool_no_apply(cols): """Gets the tool number from the PMC signal Explanation =========== Same explanation as in the cut_signal_apply function """ pmc = cols[0] if (pmc - 64) > 0: return int(pmc - 64) else: return int(pmc)
Gets the tool number from the PMC signal Explanation =========== Same explanation as in the cut_signal_apply function
Gets the tool number from the PMC signal Explanation Same explanation as in the cut_signal_apply function
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def tool_no_apply(cols): pmc = cols[0] if (pmc - 64) > 0: return int(pmc - 64) else: return int(pmc)
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Gets the tool number from the PMC signal Explanation
[ "Gets", "the", "tool", "number", "from", "the", "PMC", "signal", "Explanation" ]
[ "\"\"\"Gets the tool number from the PMC signal\n \n Explanation\n ===========\n Same explanation as in the cut_signal_apply function\n\n \"\"\"" ]
[ { "param": "cols", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "cols", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def tool_no_apply(cols): pmc = cols[0] if (pmc - 64) > 0: return int(pmc - 64) else: return int(pmc)
46
531
323c8a621d742c6892970c147bed4e6c27b1d7f0
pypyjs/pypy
pypy/module/cpyext/import_.py
[ "Apache-2.0", "OpenSSL" ]
Python
PyImport_Import
<not_specific>
def PyImport_Import(space, w_name): """ This is a higher-level interface that calls the current "import hook function". It invokes the __import__() function from the __builtins__ of the current globals. This means that the import is done using whatever import hooks are installed in the current environment, e.g. by rexec or ihooks. Always uses absolute imports.""" caller = space.getexecutioncontext().gettopframe_nohidden() # Get the builtins from current globals if caller is not None: w_globals = caller.w_globals w_builtin = space.getitem(w_globals, space.wrap('__builtins__')) else: # No globals -- use standard builtins, and fake globals w_builtin = space.getbuiltinmodule('__builtin__') w_globals = space.newdict() space.setitem(w_globals, space.wrap("__builtins__"), w_builtin) # Get the __import__ function from the builtins if space.isinstance_w(w_builtin, space.w_dict): w_import = space.getitem(w_builtin, space.wrap("__import__")) else: w_import = space.getattr(w_builtin, space.wrap("__import__")) # Call the __import__ function with the proper argument list # Always use absolute import here. return space.call_function(w_import, w_name, w_globals, w_globals, space.newlist([space.wrap("__doc__")]))
This is a higher-level interface that calls the current "import hook function". It invokes the __import__() function from the __builtins__ of the current globals. This means that the import is done using whatever import hooks are installed in the current environment, e.g. by rexec or ihooks. Always uses absolute imports.
This is a higher-level interface that calls the current "import hook function". It invokes the __import__() function from the __builtins__ of the current globals. This means that the import is done using whatever import hooks are installed in the current environment, e.g. by rexec or ihooks. Always uses absolute imports.
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def PyImport_Import(space, w_name): caller = space.getexecutioncontext().gettopframe_nohidden() if caller is not None: w_globals = caller.w_globals w_builtin = space.getitem(w_globals, space.wrap('__builtins__')) else: w_builtin = space.getbuiltinmodule('__builtin__') w_globals = space.newdict() space.setitem(w_globals, space.wrap("__builtins__"), w_builtin) if space.isinstance_w(w_builtin, space.w_dict): w_import = space.getitem(w_builtin, space.wrap("__import__")) else: w_import = space.getattr(w_builtin, space.wrap("__import__")) return space.call_function(w_import, w_name, w_globals, w_globals, space.newlist([space.wrap("__doc__")]))
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This is a higher-level interface that calls the current "import hook function".
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[ "\"\"\"\n This is a higher-level interface that calls the current \"import hook function\".\n It invokes the __import__() function from the __builtins__ of the\n current globals. This means that the import is done using whatever import hooks\n are installed in the current environment, e.g. by rexec or ihooks.\n\n Always uses absolute imports.\"\"\"", "# Get the builtins from current globals", "# No globals -- use standard builtins, and fake globals", "# Get the __import__ function from the builtins", "# Call the __import__ function with the proper argument list", "# Always use absolute import here." ]
[ { "param": "space", "type": null }, { "param": "w_name", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "space", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "w_name", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def PyImport_Import(space, w_name): caller = space.getexecutioncontext().gettopframe_nohidden() if caller is not None: w_globals = caller.w_globals w_builtin = space.getitem(w_globals, space.wrap('__builtins__')) else: w_builtin = space.getbuiltinmodule('__builtin__') w_globals = space.newdict() space.setitem(w_globals, space.wrap("__builtins__"), w_builtin) if space.isinstance_w(w_builtin, space.w_dict): w_import = space.getitem(w_builtin, space.wrap("__import__")) else: w_import = space.getattr(w_builtin, space.wrap("__import__")) return space.call_function(w_import, w_name, w_globals, w_globals, space.newlist([space.wrap("__doc__")]))
47
54
f134b7410f030c009eefe67e740f832d9cbaa2f8
MirkoLedda/polyoligo
src/polyoligo/lib_utils.py
[ "BSD-2-Clause" ]
Python
seconds_to_hms
<not_specific>
def seconds_to_hms(t): """Formats a datetime.timedelta object to a HH:MM:SS string.""" hours, remainder = divmod(t.total_seconds(), 3600) minutes, seconds = divmod(remainder, 60) hours, minutes, seconds = int(hours), int(minutes), int(seconds) if hours < 10: hours = "0%s" % int(hours) if minutes < 10: minutes = "0%s" % minutes if seconds < 10: seconds = "0%s" % seconds return "%s:%s:%s" % (hours, minutes, seconds)
Formats a datetime.timedelta object to a HH:MM:SS string.
Formats a datetime.timedelta object to a HH:MM:SS string.
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def seconds_to_hms(t): hours, remainder = divmod(t.total_seconds(), 3600) minutes, seconds = divmod(remainder, 60) hours, minutes, seconds = int(hours), int(minutes), int(seconds) if hours < 10: hours = "0%s" % int(hours) if minutes < 10: minutes = "0%s" % minutes if seconds < 10: seconds = "0%s" % seconds return "%s:%s:%s" % (hours, minutes, seconds)
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Formats a datetime.timedelta object to a HH:MM:SS string.
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[ "\"\"\"Formats a datetime.timedelta object to a HH:MM:SS string.\"\"\"" ]
[ { "param": "t", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "t", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def seconds_to_hms(t): hours, remainder = divmod(t.total_seconds(), 3600) minutes, seconds = divmod(remainder, 60) hours, minutes, seconds = int(hours), int(minutes), int(seconds) if hours < 10: hours = "0%s" % int(hours) if minutes < 10: minutes = "0%s" % minutes if seconds < 10: seconds = "0%s" % seconds return "%s:%s:%s" % (hours, minutes, seconds)
48
814
d37711957c262fbe690050937109571e502cf3e6
Pandaaaa906/scrapy-playwright
scrapy_playwright/headers.py
[ "BSD-3-Clause" ]
Python
use_playwright_headers
dict
async def use_playwright_headers( browser_type: str, playwright_request: PlaywrightRequest, scrapy_headers: Headers, ) -> dict: """Return headers from the Playwright request, unaltered""" return playwright_request.headers
Return headers from the Playwright request, unaltered
Return headers from the Playwright request, unaltered
[ "Return", "headers", "from", "the", "Playwright", "request", "unaltered" ]
async def use_playwright_headers( browser_type: str, playwright_request: PlaywrightRequest, scrapy_headers: Headers, ) -> dict: return playwright_request.headers
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Return headers from the Playwright request, unaltered
[ "Return", "headers", "from", "the", "Playwright", "request", "unaltered" ]
[ "\"\"\"Return headers from the Playwright request, unaltered\"\"\"" ]
[ { "param": "browser_type", "type": "str" }, { "param": "playwright_request", "type": "PlaywrightRequest" }, { "param": "scrapy_headers", "type": "Headers" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "browser_type", "type": "str", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "playwright_request", "type": "PlaywrightRequest", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "scrapy_headers", "type": "Headers", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
async def use_playwright_headers( browser_type: str, playwright_request: PlaywrightRequest, scrapy_headers: Headers, ) -> dict: return playwright_request.headers
49
759
35a98f36b10113ace2ee5dac283ea5b6e9f91f5e
threefoldtech/jumpscaleX_core
install/threesdk/shell.py
[ "Apache-2.0" ]
Python
eval_code
<not_specific>
def eval_code(stmts, locals_=None, globals_=None): """ a helper function to ignore incomplete syntax erros when evaluating code while typing incomplete lines, e.g.: j.clien... """ if not stmts: return try: code = compile(stmts, filename=__name__, mode="eval") except SyntaxError: return try: return eval(code, globals_, locals_) except: return
a helper function to ignore incomplete syntax erros when evaluating code while typing incomplete lines, e.g.: j.clien...
a helper function to ignore incomplete syntax erros when evaluating code while typing incomplete lines, e.g.: j.clien
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def eval_code(stmts, locals_=None, globals_=None): if not stmts: return try: code = compile(stmts, filename=__name__, mode="eval") except SyntaxError: return try: return eval(code, globals_, locals_) except: return
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a helper function to ignore incomplete syntax erros when evaluating code while typing incomplete lines, e.g.
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[ "\"\"\"\n a helper function to ignore incomplete syntax erros when evaluating code\n while typing incomplete lines, e.g.: j.clien...\n \"\"\"" ]
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def eval_code(stmts, locals_=None, globals_=None): if not stmts: return try: code = compile(stmts, filename=__name__, mode="eval") except SyntaxError: return try: return eval(code, globals_, locals_) except: return
51
545
3d22d48525dfc4451cbff275e76eaf0f861d2502
Allthemighty/SataniaBot
src/modules/misc/misc_util.py
[ "MIT" ]
Python
simple_check
<not_specific>
def simple_check(author, channel): """ A predicate used in the wait_for() function, to ensure the user input can only come from the user who activated the command, and in the same channel. :param author: Author object :param channel: Channel object :return: Check function """ def check(message): return message.author == author and message.channel == channel return check
A predicate used in the wait_for() function, to ensure the user input can only come from the user who activated the command, and in the same channel. :param author: Author object :param channel: Channel object :return: Check function
A predicate used in the wait_for() function, to ensure the user input can only come from the user who activated the command, and in the same channel.
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def simple_check(author, channel): def check(message): return message.author == author and message.channel == channel return check
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A predicate used in the wait_for() function, to ensure the user input can only come from the user who activated the command, and in the same channel.
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[ "\"\"\"\n A predicate used in the wait_for() function, to ensure the user input can only come\n from the user who activated the command, and in the same channel.\n :param author: Author object\n :param channel: Channel object\n :return: Check function\n \"\"\"" ]
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def simple_check(author, channel): def check(message): return message.author == author and message.channel == channel return check
52
443
ecd832b296a9381f4398c16dcef906a078177dd4
cmu-sei/usersim
tasks/frequency.py
[ "BSL-1.0" ]
Python
parameters
<not_specific>
def parameters(cls): """ Returns a dictionary with human-readable descriptions of required arguments for the Frequency task. Returns: dict of dicts: Configuration dictionary with the keys 'required' and 'optional', where values are dicts containing the required and optional parameters and their descriptions for the Frequency task, respectively. """ params = {'required': {'task': 'task| the configuration of another task', 'frequency': 'number| positive decimal number - avg number of triggers per hour', 'repetitions': 'int| non-negative integer - 0 for unlimited'}, 'optional': {}} return params
Returns a dictionary with human-readable descriptions of required arguments for the Frequency task. Returns: dict of dicts: Configuration dictionary with the keys 'required' and 'optional', where values are dicts containing the required and optional parameters and their descriptions for the Frequency task, respectively.
Returns a dictionary with human-readable descriptions of required arguments for the Frequency task.
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def parameters(cls): params = {'required': {'task': 'task| the configuration of another task', 'frequency': 'number| positive decimal number - avg number of triggers per hour', 'repetitions': 'int| non-negative integer - 0 for unlimited'}, 'optional': {}} return params
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Returns a dictionary with human-readable descriptions of required arguments for the Frequency task.
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[ "\"\"\" Returns a dictionary with human-readable descriptions of required arguments for the Frequency task.\n\n Returns:\n dict of dicts: Configuration dictionary with the keys 'required' and 'optional', where values are dicts\n containing the required and optional parameters and their descriptions for the Frequency task,\n respectively.\n \"\"\"" ]
[ { "param": "cls", "type": null } ]
{ "returns": [ { "docstring": "dict of dicts: Configuration dictionary with the keys 'required' and 'optional', where values are dicts\ncontaining the required and optional parameters and their descriptions for the Frequency task,\nrespectively.", "docstring_tokens": [ "dict", "of", "dicts", ":", "Configuration", "dictionary", "with", "the", "keys", "'", "required", "'", "and", "'", "optional", "'", "where", "values", "are", "dicts", "containing", "the", "required", "and", "optional", "parameters", "and", "their", "descriptions", "for", "the", "Frequency", "task", "respectively", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "cls", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def parameters(cls): params = {'required': {'task': 'task| the configuration of another task', 'frequency': 'number| positive decimal number - avg number of triggers per hour', 'repetitions': 'int| non-negative integer - 0 for unlimited'}, 'optional': {}} return params
53
85
3a0d16ef8d51a02e0c9568006f90794aa64c9e5c
russhughes/TurtlePlotBot
lib/oledui.py
[ "MIT" ]
Python
_screen_shot
null
def _screen_shot(uio, *_): """ _screen_shot Append a text screen shot of the OLED display in the screenshot.txt file. This can be triggered by a call to the routine or by long pressing a button on the Pin 0 any time the UI is waiting for a button press. Each screen shot starts with a line consisting of the word "BEGIN". Each row of the display is represented as a line of '.' and 'X' characters where a dark pixel is represented by a '.' and each light pixel is represented by a 'X'. The screenshot ends with a line consisting of the word "END". The screenshot.txt file can contain multiple screenshots. """ print("Writing screenshot... ") with open('screenshots.txt', 'a') as output: print('BEGIN', file=output) for row in range(uio.display.height): for col in range(uio.display.width): if uio.display.pixel(col, row): print('X', sep="", end="", file=output) else: print(".", sep="", end="", file=output) print("", file=output) print("END", file=output) print("done.")
_screen_shot Append a text screen shot of the OLED display in the screenshot.txt file. This can be triggered by a call to the routine or by long pressing a button on the Pin 0 any time the UI is waiting for a button press. Each screen shot starts with a line consisting of the word "BEGIN". Each row of the display is represented as a line of '.' and 'X' characters where a dark pixel is represented by a '.' and each light pixel is represented by a 'X'. The screenshot ends with a line consisting of the word "END". The screenshot.txt file can contain multiple screenshots.
_screen_shot Append a text screen shot of the OLED display in the screenshot.txt file. This can be triggered by a call to the routine or by long pressing a button on the Pin 0 any time the UI is waiting for a button press. Each screen shot starts with a line consisting of the word "BEGIN".
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def _screen_shot(uio, *_): print("Writing screenshot... ") with open('screenshots.txt', 'a') as output: print('BEGIN', file=output) for row in range(uio.display.height): for col in range(uio.display.width): if uio.display.pixel(col, row): print('X', sep="", end="", file=output) else: print(".", sep="", end="", file=output) print("", file=output) print("END", file=output) print("done.")
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_screen_shot Append a text screen shot of the OLED display in the screenshot.txt file.
[ "_screen_shot", "Append", "a", "text", "screen", "shot", "of", "the", "OLED", "display", "in", "the", "screenshot", ".", "txt", "file", "." ]
[ "\"\"\"\n _screen_shot\n\n Append a text screen shot of the OLED display in the screenshot.txt\n file. This can be triggered by a call to the routine or by long\n pressing a button on the Pin 0 any time the UI is waiting for a\n button press.\n\n Each screen shot starts with a line consisting of the word \"BEGIN\".\n Each row of the display is represented as a line of '.' and 'X'\n characters where a dark pixel is represented by a '.' and each light\n pixel is represented by a 'X'. The screenshot ends with a line\n consisting of the word \"END\". The screenshot.txt file can contain\n multiple screenshots.\n \"\"\"" ]
[ { "param": "uio", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "uio", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def _screen_shot(uio, *_): print("Writing screenshot... ") with open('screenshots.txt', 'a') as output: print('BEGIN', file=output) for row in range(uio.display.height): for col in range(uio.display.width): if uio.display.pixel(col, row): print('X', sep="", end="", file=output) else: print(".", sep="", end="", file=output) print("", file=output) print("END", file=output) print("done.")
54
918
2e79e2b725ac9e7e5c08e4e2dcbc552df0a4a442
ooici/coi-services
ion/agents/platform/test/helper.py
[ "BSD-2-Clause" ]
Python
using_actual_rsn_oms_endpoint
<not_specific>
def using_actual_rsn_oms_endpoint(cls): """ Determines whether we are testing against the actual RSN OMS endpoint. This is based on looking up the "USING_ACTUAL_RSN_OMS_ENDPOINT" environment variable, which normally will only be defined as convenient while doing local tests. See OOIION-1352. """ return "yes" == os.getenv('USING_ACTUAL_RSN_OMS_ENDPOINT')
Determines whether we are testing against the actual RSN OMS endpoint. This is based on looking up the "USING_ACTUAL_RSN_OMS_ENDPOINT" environment variable, which normally will only be defined as convenient while doing local tests. See OOIION-1352.
Determines whether we are testing against the actual RSN OMS endpoint. This is based on looking up the "USING_ACTUAL_RSN_OMS_ENDPOINT" environment variable, which normally will only be defined as convenient while doing local tests.
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def using_actual_rsn_oms_endpoint(cls): return "yes" == os.getenv('USING_ACTUAL_RSN_OMS_ENDPOINT')
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Determines whether we are testing against the actual RSN OMS endpoint.
[ "Determines", "whether", "we", "are", "testing", "against", "the", "actual", "RSN", "OMS", "endpoint", "." ]
[ "\"\"\"\n Determines whether we are testing against the actual RSN OMS endpoint.\n This is based on looking up the \"USING_ACTUAL_RSN_OMS_ENDPOINT\"\n environment variable, which normally will only be defined as\n convenient while doing local tests. See OOIION-1352.\n \"\"\"" ]
[ { "param": "cls", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "cls", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import os def using_actual_rsn_oms_endpoint(cls): return "yes" == os.getenv('USING_ACTUAL_RSN_OMS_ENDPOINT')
55
657
cc179d17e4e35730d499aba1ba8c9c604fca0dad
crahal/lit_reviewer
src/pubmed_functions.py
[ "MIT" ]
Python
return_pag
<not_specific>
def return_pag(paper): """ Return the pagination from the paper nest""" try: return paper['MedlineCitation']['Article']['Pagination']['MedlinePgn'] except KeyError: return None
Return the pagination from the paper nest
Return the pagination from the paper nest
[ "Return", "the", "pagination", "from", "the", "paper", "nest" ]
def return_pag(paper): try: return paper['MedlineCitation']['Article']['Pagination']['MedlinePgn'] except KeyError: return None
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Return the pagination from the paper nest
[ "Return", "the", "pagination", "from", "the", "paper", "nest" ]
[ "\"\"\" Return the pagination from the paper nest\"\"\"" ]
[ { "param": "paper", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "paper", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def return_pag(paper): try: return paper['MedlineCitation']['Article']['Pagination']['MedlinePgn'] except KeyError: return None
56
359
2e17d39b74ad622e3ac0ae25d5f59143463bfa85
rafaelcn/cryptography
aes/src/aes/common.py
[ "MIT" ]
Python
add_round_key
null
def add_round_key(state, key): """ Add the given key to the state using XOR. """ for i in range(4): for j in range(4): state[i][j] ^= key[i][j]
Add the given key to the state using XOR.
Add the given key to the state using XOR.
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def add_round_key(state, key): for i in range(4): for j in range(4): state[i][j] ^= key[i][j]
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Add the given key to the state using XOR.
[ "Add", "the", "given", "key", "to", "the", "state", "using", "XOR", "." ]
[ "\"\"\"\n Add the given key to the state using XOR.\n \"\"\"" ]
[ { "param": "state", "type": null }, { "param": "key", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "state", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "key", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def add_round_key(state, key): for i in range(4): for j in range(4): state[i][j] ^= key[i][j]
57
727
e18bd85473e5921ae439f6af3476d616402d6ba0
waikato-datamining/video-frame-processor
src/vfp/_processor.py
[ "MIT" ]
Python
decode_fourcc
<not_specific>
def decode_fourcc(cc): """ Turns the float into a four letter codec string. Taken from here: https://stackoverflow.com/a/49138893/4698227 :param cc: the codec as float :type cc: float :return: the codec string :rtype: str """ return "".join([chr((int(cc) >> 8 * i) & 0xFF) for i in range(4)])
Turns the float into a four letter codec string. Taken from here: https://stackoverflow.com/a/49138893/4698227 :param cc: the codec as float :type cc: float :return: the codec string :rtype: str
Turns the float into a four letter codec string.
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def decode_fourcc(cc): return "".join([chr((int(cc) >> 8 * i) & 0xFF) for i in range(4)])
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Turns the float into a four letter codec string.
[ "Turns", "the", "float", "into", "a", "four", "letter", "codec", "string", "." ]
[ "\"\"\"\n Turns the float into a four letter codec string.\n Taken from here:\n https://stackoverflow.com/a/49138893/4698227\n :param cc: the codec as float\n :type cc: float\n :return: the codec string\n :rtype: str\n \"\"\"" ]
[ { "param": "cc", "type": null } ]
{ "returns": [ { "docstring": "the codec string", "docstring_tokens": [ "the", "codec", "string" ], "type": "str" } ], "raises": [], "params": [ { "identifier": "cc", "type": null, "docstring": "the codec as float", "docstring_tokens": [ "the", "codec", "as", "float" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def decode_fourcc(cc): return "".join([chr((int(cc) >> 8 * i) & 0xFF) for i in range(4)])
58
316
3378601f401cc65b610da88dac290768b028faa7
mwhit74/sau
sau/sau.py
[ "MIT" ]
Python
ac1_mx
<not_specific>
def ac1_mx(w, l, x): """Moment at x - Beam simply supported - Uniformly dist. loads Calculates the moment in the beam at any location, x, along the beam due to a uniformly distributed load. m = w*x/2*(l-x) Args: w (float): uniformly distributed load l (float): length of beam between supports E (float): modulus of elasticity I (float): section modulus x (float): distance along beam from left support Returns: m (tuple(float, str)): maximum positive moment at midspan Notes: 1. Consistent units are the responsibility of the user. 3. For maximum positive moment use x = L/2. """ m = w*x/2.*(l-x) text = (f'm = w*x/2*(l-x) \n' + f'm = {w:.2f}*{x:.2f}/2*({l:.2f}-{x:.2f}) \n' + f'm = {m:.2f}') return m, text
Moment at x - Beam simply supported - Uniformly dist. loads Calculates the moment in the beam at any location, x, along the beam due to a uniformly distributed load. m = w*x/2*(l-x) Args: w (float): uniformly distributed load l (float): length of beam between supports E (float): modulus of elasticity I (float): section modulus x (float): distance along beam from left support Returns: m (tuple(float, str)): maximum positive moment at midspan Notes: 1. Consistent units are the responsibility of the user. 3. For maximum positive moment use x = L/2.
Moment at x - Beam simply supported - Uniformly dist. loads Calculates the moment in the beam at any location, x, along the beam due to a uniformly distributed load.
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def ac1_mx(w, l, x): m = w*x/2.*(l-x) text = (f'm = w*x/2*(l-x) \n' + f'm = {w:.2f}*{x:.2f}/2*({l:.2f}-{x:.2f}) \n' + f'm = {m:.2f}') return m, text
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Moment at x - Beam simply supported - Uniformly dist.
[ "Moment", "at", "x", "-", "Beam", "simply", "supported", "-", "Uniformly", "dist", "." ]
[ "\"\"\"Moment at x - Beam simply supported - Uniformly dist. loads\n \n Calculates the moment in the beam at any location, x, along the\n beam due to a uniformly distributed load.\n \n m = w*x/2*(l-x)\n \n Args:\n w (float): uniformly distributed load\n \n l (float): length of beam between supports\n \n E (float): modulus of elasticity\n \n I (float): section modulus\n \n x (float): distance along beam from left support\n \n Returns:\n m (tuple(float, str)): maximum positive moment at midspan\n \n Notes:\n 1. Consistent units are the responsibility of the user.\n 3. For maximum positive moment use x = L/2.\n \"\"\"" ]
[ { "param": "w", "type": null }, { "param": "l", "type": null }, { "param": "x", "type": null } ]
{ "returns": [ { "docstring": "m (tuple(float, str)): maximum positive moment at midspan", "docstring_tokens": [ "m", "(", "tuple", "(", "float", "str", "))", ":", "maximum", "positive", "moment", "at", "midspan" ], "type": null } ], "raises": [], "params": [ { "identifier": "w", "type": null, "docstring": "uniformly distributed load", "docstring_tokens": [ "uniformly", "distributed", "load" ], "default": null, "is_optional": false }, { "identifier": "l", "type": null, "docstring": "length of beam between supports", "docstring_tokens": [ "length", "of", "beam", "between", "supports" ], "default": null, "is_optional": false }, { "identifier": "x", "type": null, "docstring": "distance along beam from left support", "docstring_tokens": [ "distance", "along", "beam", "from", "left", "support" ], "default": null, "is_optional": false } ], "outlier_params": [ { "identifier": "E", "type": null, "docstring": "modulus of elasticity", "docstring_tokens": [ "modulus", "of", "elasticity" ], "default": null, "is_optional": false }, { "identifier": "I", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": false } ], "others": [] }
def ac1_mx(w, l, x): m = w*x/2.*(l-x) text = (f'm = w*x/2*(l-x) \n' + f'm = {w:.2f}*{x:.2f}/2*({l:.2f}-{x:.2f}) \n' + f'm = {m:.2f}') return m, text
59
185
85c81e489f3398ee5c56508f8cd0e49341a902fc
amole-arup/eng_utilities
eng_utilities/section_utilities.py
[ "MIT" ]
Python
deck_props
<not_specific>
def deck_props(DD, DR, B, TT, TB): """Properties of a trapezoidal deck when given deck depth (DD), rib depth (DR) rib spacing (B), rib width at top (TT), rib width at bottom (TB) - P is the length of the deck on the underside (topside is ignored) - A is the cross-sectional area of concrete per rib - D_AVE is the average depth of concrete NB At the moment no flexural properties are calculated""" A = DD * B + 0.5 * (TT + TB) * DR P = B - TT + TB + ((TT - TB)**2 + 4 * DR**2)**0.5 return {'P': P, 'A': A, 'D_AVE': A / B}
Properties of a trapezoidal deck when given deck depth (DD), rib depth (DR) rib spacing (B), rib width at top (TT), rib width at bottom (TB) - P is the length of the deck on the underside (topside is ignored) - A is the cross-sectional area of concrete per rib - D_AVE is the average depth of concrete NB At the moment no flexural properties are calculated
Properties of a trapezoidal deck when given deck depth (DD), rib depth (DR) rib spacing (B), rib width at top (TT), rib width at bottom (TB) P is the length of the deck on the underside (topside is ignored) A is the cross-sectional area of concrete per rib D_AVE is the average depth of concrete NB At the moment no flexural properties are calculated
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def deck_props(DD, DR, B, TT, TB): A = DD * B + 0.5 * (TT + TB) * DR P = B - TT + TB + ((TT - TB)**2 + 4 * DR**2)**0.5 return {'P': P, 'A': A, 'D_AVE': A / B}
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Properties of a trapezoidal deck when given deck depth (DD), rib depth (DR) rib spacing (B), rib width at top (TT), rib width at bottom (TB) P is the length of the deck on the underside (topside is ignored) A is the cross-sectional area of concrete per rib D_AVE is the average depth of concrete
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[ "\"\"\"Properties of a trapezoidal deck when given deck depth (DD), rib depth (DR)\n rib spacing (B), rib width at top (TT), rib width at bottom (TB)\n - P is the length of the deck on the underside (topside is ignored)\n - A is the cross-sectional area of concrete per rib\n - D_AVE is the average depth of concrete\n \n NB At the moment no flexural properties are calculated\"\"\"" ]
[ { "param": "DD", "type": null }, { "param": "DR", "type": null }, { "param": "B", "type": null }, { "param": "TT", "type": null }, { "param": "TB", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "DD", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "DR", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "B", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "TT", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "TB", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def deck_props(DD, DR, B, TT, TB): A = DD * B + 0.5 * (TT + TB) * DR P = B - TT + TB + ((TT - TB)**2 + 4 * DR**2)**0.5 return {'P': P, 'A': A, 'D_AVE': A / B}
60
30
4158684ebdf6a0f7e38126105f4c44de5ba48d04
turnoutnow/game-analytics-pipeline
source/demo/publish_data.py
[ "MIT-0" ]
Python
send_record_batch
null
def send_record_batch(kinesis_client, stream_name, raw_records): """Send a batch of records to Amazon Kinesis.""" # Translate input records into the format needed by the boto3 SDK formatted_records = [] for rec in raw_records: formatted_records.append({'PartitionKey': rec['event']['event_id'], 'Data': json.dumps(rec)}) kinesis_client.put_records(StreamName=stream_name, Records=formatted_records) print('Sent %d records to stream %s.' % (len(formatted_records), stream_name))
Send a batch of records to Amazon Kinesis.
Send a batch of records to Amazon Kinesis.
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def send_record_batch(kinesis_client, stream_name, raw_records): formatted_records = [] for rec in raw_records: formatted_records.append({'PartitionKey': rec['event']['event_id'], 'Data': json.dumps(rec)}) kinesis_client.put_records(StreamName=stream_name, Records=formatted_records) print('Sent %d records to stream %s.' % (len(formatted_records), stream_name))
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Send a batch of records to Amazon Kinesis.
[ "Send", "a", "batch", "of", "records", "to", "Amazon", "Kinesis", "." ]
[ "\"\"\"Send a batch of records to Amazon Kinesis.\"\"\"", "# Translate input records into the format needed by the boto3 SDK" ]
[ { "param": "kinesis_client", "type": null }, { "param": "stream_name", "type": null }, { "param": "raw_records", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "kinesis_client", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "stream_name", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "raw_records", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import json def send_record_batch(kinesis_client, stream_name, raw_records): formatted_records = [] for rec in raw_records: formatted_records.append({'PartitionKey': rec['event']['event_id'], 'Data': json.dumps(rec)}) kinesis_client.put_records(StreamName=stream_name, Records=formatted_records) print('Sent %d records to stream %s.' % (len(formatted_records), stream_name))
61
111
21cda7ead5143cd6dba8fbe256ccb44e0a991113
baajur/Anakin
tools/external_converter_v2/parser/tensorflow/run_pb.py
[ "Apache-2.0" ]
Python
convert_name_tf2ak
<not_specific>
def convert_name_tf2ak(tf_name, perfix='record_'): ''' conver tf name to ak name :param tf_name: :param perfix: :return: ''' ak_name = tf_name[:] for index, x in enumerate(tf_name): if x == '/': ak_name = ak_name[:index] + '_' + ak_name[index + 1:] return perfix + ak_name
conver tf name to ak name :param tf_name: :param perfix: :return:
conver tf name to ak name
[ "conver", "tf", "name", "to", "ak", "name" ]
def convert_name_tf2ak(tf_name, perfix='record_'): ak_name = tf_name[:] for index, x in enumerate(tf_name): if x == '/': ak_name = ak_name[:index] + '_' + ak_name[index + 1:] return perfix + ak_name
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conver tf name to ak name
[ "conver", "tf", "name", "to", "ak", "name" ]
[ "'''\n conver tf name to ak name\n :param tf_name:\n :param perfix:\n :return:\n '''" ]
[ { "param": "tf_name", "type": null }, { "param": "perfix", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "tf_name", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null }, { "identifier": "perfix", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def convert_name_tf2ak(tf_name, perfix='record_'): ak_name = tf_name[:] for index, x in enumerate(tf_name): if x == '/': ak_name = ak_name[:index] + '_' + ak_name[index + 1:] return perfix + ak_name
62
80
fde94ebd28e106560e867cbb11453ca9930c778e
philosofool/phi_baseball
stats.py
[ "MIT" ]
Python
from_rate
<not_specific>
def from_rate(rate, denominator, to_int=False): ''' Returns a counting-type stat from a rate and a denominator. Note: this is essentially the product of the two arguments. You might be wondering: so, why? You certainly don't have to! It's mostly for coherence and the idea that this is "all you need for your baseball maths" in a single place. Note that get_rate (the complement of this function) allows us to decide whether to allow infitie values instead of handling a division by zero error. When coupled with pandas, this gives us a good way impute stats via df.replace(inf,df['ERA'].mean()) for example. ''' out = rate * denominator if to_int: out = int(round(out)) return out
Returns a counting-type stat from a rate and a denominator. Note: this is essentially the product of the two arguments. You might be wondering: so, why? You certainly don't have to! It's mostly for coherence and the idea that this is "all you need for your baseball maths" in a single place. Note that get_rate (the complement of this function) allows us to decide whether to allow infitie values instead of handling a division by zero error. When coupled with pandas, this gives us a good way impute stats via df.replace(inf,df['ERA'].mean()) for example.
Returns a counting-type stat from a rate and a denominator. Note: this is essentially the product of the two arguments. You might be wondering: so, why. You certainly don't have to. It's mostly for coherence and the idea that this is "all you need for your baseball maths" in a single place. Note that get_rate (the complement of this function) allows us to decide whether to allow infitie values instead of handling a division by zero error. When coupled with pandas, this gives us a good way impute stats via df.replace(inf,df['ERA'].mean()) for example.
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def from_rate(rate, denominator, to_int=False): out = rate * denominator if to_int: out = int(round(out)) return out
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Returns a counting-type stat from a rate and a denominator.
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[ "'''\n Returns a counting-type stat from a rate and a denominator.\n \n Note: this is essentially the product of the two arguments.\n\n You might be wondering: so, why? You certainly don't have to! It's mostly for coherence\n and the idea that this is \"all you need for your baseball maths\" in a single\n place. Note that get_rate (the complement of this function) allows us to decide whether to \n allow infitie values instead of handling a division by zero error. When coupled with pandas,\n this gives us a good way impute stats via df.replace(inf,df['ERA'].mean()) for example.\n '''" ]
[ { "param": "rate", "type": null }, { "param": "denominator", "type": null }, { "param": "to_int", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "rate", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "denominator", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "to_int", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def from_rate(rate, denominator, to_int=False): out = rate * denominator if to_int: out = int(round(out)) return out
63
716
1ffae5cebb1ccc9bb42ff4492d22793eeb7fe105
lbouma/Cyclopath
doc/landonb/geometry_useful.py
[ "Apache-2.0" ]
Python
geoPointInsideBox
<not_specific>
def geoPointInsideBox(p, edges): """ returns True only if p lies inside or on the sides of box """ y,x = p (y0,x0),(y1,x1) = edges if y0>y1: y0,y1 = y1,y0 if x0>x1: x0,x1 = x1,x0 return x0<=x<=x1 and y0<=y<=y1
returns True only if p lies inside or on the sides of box
returns True only if p lies inside or on the sides of box
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def geoPointInsideBox(p, edges): y,x = p (y0,x0),(y1,x1) = edges if y0>y1: y0,y1 = y1,y0 if x0>x1: x0,x1 = x1,x0 return x0<=x<=x1 and y0<=y<=y1
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returns True only if p lies inside or on the sides of box
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[ "\"\"\"\n returns True only if p lies inside or on the sides of box\n \"\"\"" ]
[ { "param": "p", "type": null }, { "param": "edges", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "p", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "edges", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def geoPointInsideBox(p, edges): y,x = p (y0,x0),(y1,x1) = edges if y0>y1: y0,y1 = y1,y0 if x0>x1: x0,x1 = x1,x0 return x0<=x<=x1 and y0<=y<=y1
64
149
bb3705c4383f3156e1e20fb980b44c1bcf644701
cbrew/chartparse
python/chart/chart.py
[ "Apache-2.0" ]
Python
edge_summary
<not_specific>
def edge_summary(v): """ Summarize the contents of the chart. >>> v = parse(["the","pigeons","suffer"],return_chart=True) ['the', 'pigeons', 'suffer'] Parse 1: S Np det the Nn n pigeons Vp v suffer 1 parses >>> edge_summary(v) {'partials': 31, 'completes': 12} """ ps = set().union(*v.partials) cs = set().union(*v.completes) ps_no_pred = {p for p in ps if p not in v.prev} cs_no_pred = {p for p in cs if p not in v.prev} assert len(cs_no_pred) == 0 assert len(ps_no_pred) == 0 return dict(partials= len(ps),completes=len(cs))
Summarize the contents of the chart. >>> v = parse(["the","pigeons","suffer"],return_chart=True) ['the', 'pigeons', 'suffer'] Parse 1: S Np det the Nn n pigeons Vp v suffer 1 parses >>> edge_summary(v) {'partials': 31, 'completes': 12}
Summarize the contents of the chart.
[ "Summarize", "the", "contents", "of", "the", "chart", "." ]
def edge_summary(v): ps = set().union(*v.partials) cs = set().union(*v.completes) ps_no_pred = {p for p in ps if p not in v.prev} cs_no_pred = {p for p in cs if p not in v.prev} assert len(cs_no_pred) == 0 assert len(ps_no_pred) == 0 return dict(partials= len(ps),completes=len(cs))
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Summarize the contents of the chart.
[ "Summarize", "the", "contents", "of", "the", "chart", "." ]
[ "\"\"\"\n Summarize the contents of the chart. \n >>> v = parse([\"the\",\"pigeons\",\"suffer\"],return_chart=True)\n ['the', 'pigeons', 'suffer']\n Parse 1:\n S\n Np\n det the\n Nn\n n pigeons\n Vp\n v suffer\n 1 parses\n >>> edge_summary(v)\n {'partials': 31, 'completes': 12}\n \"\"\"" ]
[ { "param": "v", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "v", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def edge_summary(v): ps = set().union(*v.partials) cs = set().union(*v.completes) ps_no_pred = {p for p in ps if p not in v.prev} cs_no_pred = {p for p in cs if p not in v.prev} assert len(cs_no_pred) == 0 assert len(ps_no_pred) == 0 return dict(partials= len(ps),completes=len(cs))
65
520
6777462f81774b840637af9418604b1c28b0243d
xavipor/myAdversarial
game_agent.py
[ "MIT" ]
Python
custom_score_3
<not_specific>
def custom_score_3(game, player): """Calculate the heuristic value of a game state from the point of view of the given player. Note: this function should be called from within a Player instance as `self.score()` -- you should not need to call this function directly. Parameters ---------- game : `isolation.Board` An instance of `isolation.Board` encoding the current state of the game (e.g., player locations and blocked cells). player : object A player instance in the current game (i.e., an object corresponding to one of the player objects `game.__player_1__` or `game.__player_2__`.) Returns ------- float The heuristic value of the current game state to the specified player. """ # TODO: finish this function! if game.is_loser(player): return float("-inf") if game.is_winner(player): return float("inf") # Try to disturb opponent tunning_1=4 nmovements=2 tunning_2=4 center=[float(game.height/2),float(game.width/2)] movements=game.move_count loc=game.get_player_location(player) total=float(game.height*game.width) percentage=100*(total-float(len(game.get_blank_spaces())))/total my_moves = len(game.get_legal_moves(player)) enemy_moves = len(game.get_legal_moves(game.get_opponent(player))) distance=float(abs(loc[0]-center[0])+abs(loc[1]-center[1])) overlap = set(game.get_legal_moves(player)) & set(game.get_legal_moves(game.get_opponent(player))) if movements <=nmovements : if distance==0.0: distance=1 return 100.0/ distance else: return float(my_moves - tunning_1 * enemy_moves) + 50*len(overlap)
Calculate the heuristic value of a game state from the point of view of the given player. Note: this function should be called from within a Player instance as `self.score()` -- you should not need to call this function directly. Parameters ---------- game : `isolation.Board` An instance of `isolation.Board` encoding the current state of the game (e.g., player locations and blocked cells). player : object A player instance in the current game (i.e., an object corresponding to one of the player objects `game.__player_1__` or `game.__player_2__`.) Returns ------- float The heuristic value of the current game state to the specified player.
Calculate the heuristic value of a game state from the point of view of the given player. this function should be called from within a Player instance as `self.score()` -- you should not need to call this function directly. Parameters game : `isolation.Board` An instance of `isolation.Board` encoding the current state of the game . player : object A player instance in the current game Returns float The heuristic value of the current game state to the specified player.
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def custom_score_3(game, player): if game.is_loser(player): return float("-inf") if game.is_winner(player): return float("inf") tunning_1=4 nmovements=2 tunning_2=4 center=[float(game.height/2),float(game.width/2)] movements=game.move_count loc=game.get_player_location(player) total=float(game.height*game.width) percentage=100*(total-float(len(game.get_blank_spaces())))/total my_moves = len(game.get_legal_moves(player)) enemy_moves = len(game.get_legal_moves(game.get_opponent(player))) distance=float(abs(loc[0]-center[0])+abs(loc[1]-center[1])) overlap = set(game.get_legal_moves(player)) & set(game.get_legal_moves(game.get_opponent(player))) if movements <=nmovements : if distance==0.0: distance=1 return 100.0/ distance else: return float(my_moves - tunning_1 * enemy_moves) + 50*len(overlap)
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Calculate the heuristic value of a game state from the point of view of the given player.
[ "Calculate", "the", "heuristic", "value", "of", "a", "game", "state", "from", "the", "point", "of", "view", "of", "the", "given", "player", "." ]
[ "\"\"\"Calculate the heuristic value of a game state from the point of view\n of the given player.\n\n Note: this function should be called from within a Player instance as\n `self.score()` -- you should not need to call this function directly.\n\n Parameters\n ----------\n game : `isolation.Board`\n An instance of `isolation.Board` encoding the current state of the\n game (e.g., player locations and blocked cells).\n\n player : object\n A player instance in the current game (i.e., an object corresponding to\n one of the player objects `game.__player_1__` or `game.__player_2__`.)\n\n Returns\n -------\n float\n The heuristic value of the current game state to the specified player.\n \"\"\"", "# TODO: finish this function!", "# Try to disturb opponent" ]
[ { "param": "game", "type": null }, { "param": "player", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "game", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "player", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def custom_score_3(game, player): if game.is_loser(player): return float("-inf") if game.is_winner(player): return float("inf") tunning_1=4 nmovements=2 tunning_2=4 center=[float(game.height/2),float(game.width/2)] movements=game.move_count loc=game.get_player_location(player) total=float(game.height*game.width) percentage=100*(total-float(len(game.get_blank_spaces())))/total my_moves = len(game.get_legal_moves(player)) enemy_moves = len(game.get_legal_moves(game.get_opponent(player))) distance=float(abs(loc[0]-center[0])+abs(loc[1]-center[1])) overlap = set(game.get_legal_moves(player)) & set(game.get_legal_moves(game.get_opponent(player))) if movements <=nmovements : if distance==0.0: distance=1 return 100.0/ distance else: return float(my_moves - tunning_1 * enemy_moves) + 50*len(overlap)
66
447
ad5656be7921fe524c0908b6a9aaf3c8f0bab780
Laufire/laufire
dev/laufire/filesys.py
[ "MIT" ]
Python
iterateContent
null
def iterateContent(filePath, width=4096): r"""Reads the given file as small chunks. This could be used to read large files without buffer overruns. """ with open(filePath, 'rb') as file: for chunk in iter(lambda: file.read(width), b''): yield chunk
r"""Reads the given file as small chunks. This could be used to read large files without buffer overruns.
r"""Reads the given file as small chunks. This could be used to read large files without buffer overruns.
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def iterateContent(filePath, width=4096): with open(filePath, 'rb') as file: for chunk in iter(lambda: file.read(width), b''): yield chunk
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r"""Reads the given file as small chunks.
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[ "r\"\"\"Reads the given file as small chunks. This could be used to read large files without buffer overruns.\n\t\"\"\"" ]
[ { "param": "filePath", "type": null }, { "param": "width", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "filePath", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "width", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def iterateContent(filePath, width=4096): with open(filePath, 'rb') as file: for chunk in iter(lambda: file.read(width), b''): yield chunk
67
522
c7213c53d170ac541cda11324c75c2eeb51403fb
admariner/ecommercetools
ecommercetools/utilities/metrics.py
[ "MIT" ]
Python
revenue_per_unit
<not_specific>
def revenue_per_unit(total_revenue, total_units): """Return the total revenue per unit for the period. Args: total_revenue (float): Total revenue generated during the period. total_units (int): Total units sold during the period. Returns: Total revenue per unit during the period. """ return total_revenue / total_units
Return the total revenue per unit for the period. Args: total_revenue (float): Total revenue generated during the period. total_units (int): Total units sold during the period. Returns: Total revenue per unit during the period.
Return the total revenue per unit for the period.
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def revenue_per_unit(total_revenue, total_units): return total_revenue / total_units
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Return the total revenue per unit for the period.
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[ "\"\"\"Return the total revenue per unit for the period.\n\n Args:\n total_revenue (float): Total revenue generated during the period.\n total_units (int): Total units sold during the period.\n\n Returns:\n Total revenue per unit during the period.\n \"\"\"" ]
[ { "param": "total_revenue", "type": null }, { "param": "total_units", "type": null } ]
{ "returns": [ { "docstring": "Total revenue per unit during the period.", "docstring_tokens": [ "Total", "revenue", "per", "unit", "during", "the", "period", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "total_revenue", "type": null, "docstring": "Total revenue generated during the period.", "docstring_tokens": [ "Total", "revenue", "generated", "during", "the", "period", "." ], "default": null, "is_optional": false }, { "identifier": "total_units", "type": null, "docstring": "Total units sold during the period.", "docstring_tokens": [ "Total", "units", "sold", "during", "the", "period", "." ], "default": null, "is_optional": false } ], "outlier_params": [], "others": [] }
def revenue_per_unit(total_revenue, total_units): return total_revenue / total_units
68
306
37516c09b27b0ff3e34b22cbd2e2a1eb1e282a19
aws-samples/research-pacs-on-aws
python/de-identifier/research_pacs/de_identifier/dicom_tag_path_pattern.py
[ "MIT-0" ]
Python
_get_elem_tag_hexa
<not_specific>
def _get_elem_tag_hexa(elem): """ Returns a 8-hexadecimal digit corresponding to the data element tag. Args: elem: pydicom Data Element """ return hex(elem.tag.group)[2:].upper().zfill(4) + hex(elem.tag.elem)[2:].upper().zfill(4)
Returns a 8-hexadecimal digit corresponding to the data element tag. Args: elem: pydicom Data Element
Returns a 8-hexadecimal digit corresponding to the data element tag.
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def _get_elem_tag_hexa(elem): return hex(elem.tag.group)[2:].upper().zfill(4) + hex(elem.tag.elem)[2:].upper().zfill(4)
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Returns a 8-hexadecimal digit corresponding to the data element tag.
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[ "\"\"\"\n Returns a 8-hexadecimal digit corresponding to the data element tag.\n \n Args:\n elem: pydicom Data Element\n \n \"\"\"" ]
[ { "param": "elem", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "elem", "type": null, "docstring": "pydicom Data Element", "docstring_tokens": [ "pydicom", "Data", "Element" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def _get_elem_tag_hexa(elem): return hex(elem.tag.group)[2:].upper().zfill(4) + hex(elem.tag.elem)[2:].upper().zfill(4)
69
799
ccb28a6c89695e1895b09241f2c913633c3636f4
ngageoint/voxel-globe
voxel_globe/visualsfm/tools.py
[ "MIT" ]
Python
writeGcpFile
null
def writeGcpFile(inputs, outputGps): ''' inputs - List of objcets, with .filename and .xyz fields, in degree/meters outputGps - output gps filename ''' with open(outputGps, 'w') as fid: for input in inputs: fid.write(input['filename'] + (' %0.12g'*3) % (input['xyz'][0], input['xyz'][1], input['xyz'][2]) +'\n')
inputs - List of objcets, with .filename and .xyz fields, in degree/meters outputGps - output gps filename
List of objcets, with .filename and .xyz fields, in degree/meters outputGps - output gps filename
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def writeGcpFile(inputs, outputGps): with open(outputGps, 'w') as fid: for input in inputs: fid.write(input['filename'] + (' %0.12g'*3) % (input['xyz'][0], input['xyz'][1], input['xyz'][2]) +'\n')
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inputs - List of objcets, with .filename and .xyz fields, in degree/meters outputGps - output gps filename
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[ "''' inputs - List of objcets, with .filename and .xyz fields, in degree/meters\n outputGps - output gps filename '''" ]
[ { "param": "inputs", "type": null }, { "param": "outputGps", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "inputs", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "outputGps", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def writeGcpFile(inputs, outputGps): with open(outputGps, 'w') as fid: for input in inputs: fid.write(input['filename'] + (' %0.12g'*3) % (input['xyz'][0], input['xyz'][1], input['xyz'][2]) +'\n')
70
724
b24801507e94d1354b33c33a0e640be2eeb06113
swipswaps/juriscraper
juriscraper/pacer/utils.py
[ "BSD-2-Clause" ]
Python
reverse_goDLS_function
<not_specific>
def reverse_goDLS_function(s): """Extract the arguments from the goDLS JavaScript function. In: goDLS('/doc1/01712427473','56121','69','','','1','','');return(false); Out: { 'form_post_url': '/doc1/01712427473', 'caseid': '56121', 'de_seq_num': '69', 'got_receipt': '', 'pdf_header': '', 'pdf_toggle_possible': '1', 'magic_num': '', 'hdr': '', } The key names correspond to the form field names in the JavaScript on PACER, but we don't actually know what each of these values does. Our best speculation is: - form_post_url: Where the form is posted to. The HTML 'action' attribute. - caseid: The internal PACER ID for the case. - de_seq_num: Unclear. This seems to be the internal ID for the document, but this field can be omitted without any known issues. - got_receipt: If set to '1', this will bypass the receipt page and immediately direct you to the page where the PDF is embedded in an iframe. - pdf_header: Can be either 1 or 2. 1: Show the header. 2: No header. - pdf_toggle_possible: This seems to always be 1. Could be that some courts do not allow the header to be turned off, but we haven't discoered that yet. - magic_num: This is used for the "One free look" downloads. - hdr: Unclear what HDR stands for but on items that have attachments, passing this parameter bypasses the download attachment screen and takes you directly to the PDF that you're trying to download. For an example, see document 108 from 1:12-cv-00102 in tnmd, which is a free opinion that has an attachment. Note that the eighth parameter was added some time after 2010. Dockets older than that date only have seven responses. """ args = re.findall("\'(.*?)\'", s) parts = { 'form_post_url': args[0], 'caseid': args[1], 'de_seq_num': args[2], 'got_receipt': args[3], 'pdf_header': args[4], 'pdf_toggle_possible': args[5], 'magic_num': args[6], } try: parts['hdr'] = args[7] except IndexError: # At some point dockets added this eighth parameter. Older ones lack it parts['hdr'] = None return parts
Extract the arguments from the goDLS JavaScript function. In: goDLS('/doc1/01712427473','56121','69','','','1','','');return(false); Out: { 'form_post_url': '/doc1/01712427473', 'caseid': '56121', 'de_seq_num': '69', 'got_receipt': '', 'pdf_header': '', 'pdf_toggle_possible': '1', 'magic_num': '', 'hdr': '', } The key names correspond to the form field names in the JavaScript on PACER, but we don't actually know what each of these values does. Our best speculation is: - form_post_url: Where the form is posted to. The HTML 'action' attribute. - caseid: The internal PACER ID for the case. - de_seq_num: Unclear. This seems to be the internal ID for the document, but this field can be omitted without any known issues. - got_receipt: If set to '1', this will bypass the receipt page and immediately direct you to the page where the PDF is embedded in an iframe. - pdf_header: Can be either 1 or 2. 1: Show the header. 2: No header. - pdf_toggle_possible: This seems to always be 1. Could be that some courts do not allow the header to be turned off, but we haven't discoered that yet. - magic_num: This is used for the "One free look" downloads. - hdr: Unclear what HDR stands for but on items that have attachments, passing this parameter bypasses the download attachment screen and takes you directly to the PDF that you're trying to download. For an example, see document 108 from 1:12-cv-00102 in tnmd, which is a free opinion that has an attachment. Note that the eighth parameter was added some time after 2010. Dockets older than that date only have seven responses.
Extract the arguments from the goDLS JavaScript function. The key names correspond to the form field names in the JavaScript on PACER, but we don't actually know what each of these values does. Our best speculation is.
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def reverse_goDLS_function(s): args = re.findall("\'(.*?)\'", s) parts = { 'form_post_url': args[0], 'caseid': args[1], 'de_seq_num': args[2], 'got_receipt': args[3], 'pdf_header': args[4], 'pdf_toggle_possible': args[5], 'magic_num': args[6], } try: parts['hdr'] = args[7] except IndexError: parts['hdr'] = None return parts
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Extract the arguments from the goDLS JavaScript function.
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[ "\"\"\"Extract the arguments from the goDLS JavaScript function.\n\n In: goDLS('/doc1/01712427473','56121','69','','','1','','');return(false);\n Out: {\n 'form_post_url': '/doc1/01712427473',\n 'caseid': '56121',\n 'de_seq_num': '69',\n 'got_receipt': '',\n 'pdf_header': '',\n 'pdf_toggle_possible': '1',\n 'magic_num': '',\n 'hdr': '',\n }\n\n The key names correspond to the form field names in the JavaScript on PACER,\n but we don't actually know what each of these values does. Our best\n speculation is:\n\n - form_post_url: Where the form is posted to. The HTML 'action' attribute.\n - caseid: The internal PACER ID for the case.\n - de_seq_num: Unclear. This seems to be the internal ID for the document,\n but this field can be omitted without any known issues.\n - got_receipt: If set to '1', this will bypass the receipt page and\n immediately direct you to the page where the PDF is embedded in an\n iframe.\n - pdf_header: Can be either 1 or 2. 1: Show the header. 2: No header.\n - pdf_toggle_possible: This seems to always be 1. Could be that some courts\n do not allow the header to be turned off, but we haven't discoered that\n yet.\n - magic_num: This is used for the \"One free look\" downloads.\n - hdr: Unclear what HDR stands for but on items that have attachments,\n passing this parameter bypasses the download attachment screen and takes\n you directly to the PDF that you're trying to download. For an example,\n see document 108 from 1:12-cv-00102 in tnmd, which is a free opinion that\n has an attachment. Note that the eighth parameter was added some time\n after 2010. Dockets older than that date only have seven responses.\n \"\"\"", "# At some point dockets added this eighth parameter. Older ones lack it" ]
[ { "param": "s", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "s", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import re def reverse_goDLS_function(s): args = re.findall("\'(.*?)\'", s) parts = { 'form_post_url': args[0], 'caseid': args[1], 'de_seq_num': args[2], 'got_receipt': args[3], 'pdf_header': args[4], 'pdf_toggle_possible': args[5], 'magic_num': args[6], } try: parts['hdr'] = args[7] except IndexError: parts['hdr'] = None return parts
71
732
d0eed2c52c6a7966d44ce7fc7758b0cb58fba734
mod9-asr/python-sdk
mod9/es/client.py
[ "BSD-2-Clause" ]
Python
index_lines
null
def index_lines(json_lines_by_speaker, es, index, title): """Index speaker-separated reply messages passed in as JSON-formatted lines.""" tracks = [] for speaker, json_lines in json_lines_by_speaker.items(): concats = [] for json_line in json_lines: engine_reply = json.loads(json_line) if engine_reply.get('final'): concats += engine_reply.get('phrases', '') if len(concats) > 0: tracks.append({'asr': json.dumps(concats), 'speaker': speaker}) if len(tracks) > 0: document = {'title': title, 'tracks': tracks} index_id = str(uuid.uuid4()) es.index(index, index_id, document) logging.info("Indexed audio in index %s with ID %s.", index, index_id) else: logging.info('Not indexing; no "phrases" fields found.')
Index speaker-separated reply messages passed in as JSON-formatted lines.
Index speaker-separated reply messages passed in as JSON-formatted lines.
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def index_lines(json_lines_by_speaker, es, index, title): tracks = [] for speaker, json_lines in json_lines_by_speaker.items(): concats = [] for json_line in json_lines: engine_reply = json.loads(json_line) if engine_reply.get('final'): concats += engine_reply.get('phrases', '') if len(concats) > 0: tracks.append({'asr': json.dumps(concats), 'speaker': speaker}) if len(tracks) > 0: document = {'title': title, 'tracks': tracks} index_id = str(uuid.uuid4()) es.index(index, index_id, document) logging.info("Indexed audio in index %s with ID %s.", index, index_id) else: logging.info('Not indexing; no "phrases" fields found.')
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Index speaker-separated reply messages passed in as JSON-formatted lines.
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[ "\"\"\"Index speaker-separated reply messages passed in as JSON-formatted lines.\"\"\"" ]
[ { "param": "json_lines_by_speaker", "type": null }, { "param": "es", "type": null }, { "param": "index", "type": null }, { "param": "title", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "json_lines_by_speaker", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "es", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "index", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "title", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import logging import uuid import json def index_lines(json_lines_by_speaker, es, index, title): tracks = [] for speaker, json_lines in json_lines_by_speaker.items(): concats = [] for json_line in json_lines: engine_reply = json.loads(json_line) if engine_reply.get('final'): concats += engine_reply.get('phrases', '') if len(concats) > 0: tracks.append({'asr': json.dumps(concats), 'speaker': speaker}) if len(tracks) > 0: document = {'title': title, 'tracks': tracks} index_id = str(uuid.uuid4()) es.index(index, index_id, document) logging.info("Indexed audio in index %s with ID %s.", index, index_id) else: logging.info('Not indexing; no "phrases" fields found.')
72
508
ea1c7d1974b1bf929f94f1dd2e097291279992db
topliceanu/learn
cci-book/ed6/linked_lists.py
[ "MIT" ]
Python
delete_middle
null
def delete_middle(middle): """ 2.3 Delete Middle Node: Implement an algorithm to delete a node in the middle (i.e., any node but the first and last node, not necessarily the exact middle) of a singly linked list, given only access to that node. EXAMPLE Input: the node c from the linked list a->b->c->d->e->f Result: nothing is returned, but the new linked list looks like a->b->d->e->f """ middle.value = middle.next.value middle.next = middle.next.next
2.3 Delete Middle Node: Implement an algorithm to delete a node in the middle (i.e., any node but the first and last node, not necessarily the exact middle) of a singly linked list, given only access to that node. EXAMPLE Input: the node c from the linked list a->b->c->d->e->f Result: nothing is returned, but the new linked list looks like a->b->d->e->f
2.3 Delete Middle Node: Implement an algorithm to delete a node in the middle of a singly linked list, given only access to that node.
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def delete_middle(middle): middle.value = middle.next.value middle.next = middle.next.next
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2.3 Delete Middle Node: Implement an algorithm to delete a node in the middle (i.e., any node but the first and last node, not necessarily the exact middle) of a singly linked list, given only access to that node.
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[ "\"\"\" 2.3 Delete Middle Node: Implement an algorithm to delete a node in the\n middle (i.e., any node but the first and last node, not necessarily the exact\n middle) of a singly linked list, given only access to that node.\n EXAMPLE\n Input: the node c from the linked list a->b->c->d->e->f\n Result: nothing is returned, but the new linked list looks like a->b->d->e->f\n \"\"\"" ]
[ { "param": "middle", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "middle", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def delete_middle(middle): middle.value = middle.next.value middle.next = middle.next.next
73
120
a7ecc0642cc7dddb24b80b7ae5e01c9c6672b47b
nageshlop/cligj
cligj/features.py
[ "BSD-3-Clause" ]
Python
coords_from_query
<not_specific>
def coords_from_query(query): """Transform a query line into a (lng, lat) pair of coordinates.""" try: coords = json.loads(query) except ValueError: query = query.replace(',', ' ') vals = query.split() coords = [float(v) for v in vals] return tuple(coords[:2])
Transform a query line into a (lng, lat) pair of coordinates.
Transform a query line into a (lng, lat) pair of coordinates.
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def coords_from_query(query): try: coords = json.loads(query) except ValueError: query = query.replace(',', ' ') vals = query.split() coords = [float(v) for v in vals] return tuple(coords[:2])
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Transform a query line into a (lng, lat) pair of coordinates.
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[ "\"\"\"Transform a query line into a (lng, lat) pair of coordinates.\"\"\"" ]
[ { "param": "query", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "query", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import json def coords_from_query(query): try: coords = json.loads(query) except ValueError: query = query.replace(',', ' ') vals = query.split() coords = [float(v) for v in vals] return tuple(coords[:2])
74
678
de247152d7a7ab4beefa2476dfebbb053561bdbd
hugadams/scikit-spectra
skspec/nptools/haiss.py
[ "BSD-3-Clause" ]
Python
_haiss_m1
<not_specific>
def _haiss_m1(lambda_spr): ''' Return diameter from wavelength at spr maximum of absorbance curve. Parameters: ----------- lambda_spr: the wavelength at spr absorbance maximum. Notes: ----------- this method is not accurate for particles with diameter less than 25nm. ''' lambda_0=512 L1=6.53 L2=0.0216 d=(math.log((lambda_spr-lambda_0)/L1))/L2 return d
Return diameter from wavelength at spr maximum of absorbance curve. Parameters: ----------- lambda_spr: the wavelength at spr absorbance maximum. Notes: ----------- this method is not accurate for particles with diameter less than 25nm.
Return diameter from wavelength at spr maximum of absorbance curve. Parameters. the wavelength at spr absorbance maximum. this method is not accurate for particles with diameter less than 25nm.
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def _haiss_m1(lambda_spr): lambda_0=512 L1=6.53 L2=0.0216 d=(math.log((lambda_spr-lambda_0)/L1))/L2 return d
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Return diameter from wavelength at spr maximum of absorbance curve.
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[ "''' Return diameter from wavelength at spr maximum of absorbance curve.\n\n Parameters:\n -----------\n lambda_spr: the wavelength at spr absorbance maximum.\n\n Notes:\n -----------\n this method is not accurate for particles with diameter less than 25nm.\n\n '''" ]
[ { "param": "lambda_spr", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lambda_spr", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import math def _haiss_m1(lambda_spr): lambda_0=512 L1=6.53 L2=0.0216 d=(math.log((lambda_spr-lambda_0)/L1))/L2 return d
75
30
94cd0211858390df4d0f2154cb32db76c59352c6
Tasignotas/topographica_mirror
topo/tests/reference/topo_or_defs.py
[ "BSD-3-Clause" ]
Python
half_odd_array
<not_specific>
def half_odd_array(r): """Return r that ends in .5""" int_width = int(2*r) # force odd width if int_width%2==0: int_width+=1 new_r = int_width/2.0 assert new_r-0.5==int(new_r) return new_r
Return r that ends in .5
Return r that ends in .5
[ "Return", "r", "that", "ends", "in", ".", "5" ]
def half_odd_array(r): int_width = int(2*r) if int_width%2==0: int_width+=1 new_r = int_width/2.0 assert new_r-0.5==int(new_r) return new_r
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Return r that ends in .5
[ "Return", "r", "that", "ends", "in", ".", "5" ]
[ "\"\"\"Return r that ends in .5\"\"\"", "# force odd width" ]
[ { "param": "r", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "r", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def half_odd_array(r): int_width = int(2*r) if int_width%2==0: int_width+=1 new_r = int_width/2.0 assert new_r-0.5==int(new_r) return new_r
76
267
075536ccf1ce622f39db77fd8e219f4b9b0d8e67
trsvchn/captum
captum/attr/_utils/lrp_rules.py
[ "BSD-3-Clause" ]
Python
backward_hook_activation
<not_specific>
def backward_hook_activation(module, grad_input, grad_output): """Backward hook to propagate relevance over non-linear activations.""" if ( isinstance(grad_input, tuple) and isinstance(grad_output, tuple) and len(grad_input) > len(grad_output) ): # Adds any additional elements of grad_input if applicable # This occurs when registering a backward hook on nn.Dropout # modules, which has an additional element of None in # grad_input return grad_output + grad_input[len(grad_output) :] return grad_output
Backward hook to propagate relevance over non-linear activations.
Backward hook to propagate relevance over non-linear activations.
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def backward_hook_activation(module, grad_input, grad_output): if ( isinstance(grad_input, tuple) and isinstance(grad_output, tuple) and len(grad_input) > len(grad_output) ): return grad_output + grad_input[len(grad_output) :] return grad_output
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Backward hook to propagate relevance over non-linear activations.
[ "Backward", "hook", "to", "propagate", "relevance", "over", "non", "-", "linear", "activations", "." ]
[ "\"\"\"Backward hook to propagate relevance over non-linear activations.\"\"\"", "# Adds any additional elements of grad_input if applicable", "# This occurs when registering a backward hook on nn.Dropout", "# modules, which has an additional element of None in", "# grad_input" ]
[ { "param": "module", "type": null }, { "param": "grad_input", "type": null }, { "param": "grad_output", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "module", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "grad_input", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "grad_output", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def backward_hook_activation(module, grad_input, grad_output): if ( isinstance(grad_input, tuple) and isinstance(grad_output, tuple) and len(grad_input) > len(grad_output) ): return grad_output + grad_input[len(grad_output) :] return grad_output
77
546
0cd2c8c8242dd34c4b2d40629282346a342b4d29
jwcarr/eyek
eyekit/measure.py
[ "MIT" ]
Python
number_of_regressions_in
<not_specific>
def number_of_regressions_in(interest_area, fixation_sequence): """ Given an interest area and fixation sequence, return the number of regressions back to that interest area after the interest area was read for the first time. In other words, find the first fixation to exit the interest area and then count how many times the reader returns to the interest area from the right (or from the left in the case of right-to-left text). """ entered_interest_area = False first_exit_index = None for fixation in fixation_sequence.iter_without_discards(): if fixation in interest_area: entered_interest_area = True elif entered_interest_area: first_exit_index = fixation.index break if first_exit_index is None: return 0 # IA was never exited, so there can't be any regressions back to it count = 0 for prev_fix, curr_fix in fixation_sequence.iter_pairs(include_discards=False): if prev_fix.index < first_exit_index: continue if prev_fix not in interest_area and curr_fix in interest_area: if interest_area.right_to_left: if curr_fix.x > prev_fix.x: count += 1 else: if curr_fix.x < prev_fix.x: count += 1 return count
Given an interest area and fixation sequence, return the number of regressions back to that interest area after the interest area was read for the first time. In other words, find the first fixation to exit the interest area and then count how many times the reader returns to the interest area from the right (or from the left in the case of right-to-left text).
Given an interest area and fixation sequence, return the number of regressions back to that interest area after the interest area was read for the first time. In other words, find the first fixation to exit the interest area and then count how many times the reader returns to the interest area from the right (or from the left in the case of right-to-left text).
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def number_of_regressions_in(interest_area, fixation_sequence): entered_interest_area = False first_exit_index = None for fixation in fixation_sequence.iter_without_discards(): if fixation in interest_area: entered_interest_area = True elif entered_interest_area: first_exit_index = fixation.index break if first_exit_index is None: return 0 count = 0 for prev_fix, curr_fix in fixation_sequence.iter_pairs(include_discards=False): if prev_fix.index < first_exit_index: continue if prev_fix not in interest_area and curr_fix in interest_area: if interest_area.right_to_left: if curr_fix.x > prev_fix.x: count += 1 else: if curr_fix.x < prev_fix.x: count += 1 return count
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Given an interest area and fixation sequence, return the number of regressions back to that interest area after the interest area was read for the first time.
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[ "\"\"\"\n Given an interest area and fixation sequence, return the number of\n regressions back to that interest area after the interest area was read\n for the first time. In other words, find the first fixation to exit the\n interest area and then count how many times the reader returns to the\n interest area from the right (or from the left in the case of\n right-to-left text).\n \"\"\"", "# IA was never exited, so there can't be any regressions back to it" ]
[ { "param": "interest_area", "type": null }, { "param": "fixation_sequence", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "interest_area", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "fixation_sequence", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def number_of_regressions_in(interest_area, fixation_sequence): entered_interest_area = False first_exit_index = None for fixation in fixation_sequence.iter_without_discards(): if fixation in interest_area: entered_interest_area = True elif entered_interest_area: first_exit_index = fixation.index break if first_exit_index is None: return 0 count = 0 for prev_fix, curr_fix in fixation_sequence.iter_pairs(include_discards=False): if prev_fix.index < first_exit_index: continue if prev_fix not in interest_area and curr_fix in interest_area: if interest_area.right_to_left: if curr_fix.x > prev_fix.x: count += 1 else: if curr_fix.x < prev_fix.x: count += 1 return count
78
272
2025358bc8a3b62cb83c283914ff2a1bf457c1c0
lietu/connquality
connquality/graph.py
[ "BSD-3-Clause" ]
Python
parse_options
<not_specific>
def parse_options(args): """ Parse commandline arguments into options for Graph :param args: :return: """ parser = argparse.ArgumentParser() parser.add_argument("--logfile", default="connection.log", help="Where is the connection quality data stored") parser.add_argument("--outfile", default="graph.png", help="Where to store the generated graph") parser.add_argument("--dpi", default=100.0, help="Target DPI for graph") parser.add_argument("--datapoints", default=None, help="Limit number of datapoints to show") parser.add_argument("--start", default=None, help="Only include entries starting from this datetime") parser.add_argument("--end", default=None, help="Only include entries until this datetime") return parser.parse_args(args)
Parse commandline arguments into options for Graph :param args: :return:
Parse commandline arguments into options for Graph
[ "Parse", "commandline", "arguments", "into", "options", "for", "Graph" ]
def parse_options(args): parser = argparse.ArgumentParser() parser.add_argument("--logfile", default="connection.log", help="Where is the connection quality data stored") parser.add_argument("--outfile", default="graph.png", help="Where to store the generated graph") parser.add_argument("--dpi", default=100.0, help="Target DPI for graph") parser.add_argument("--datapoints", default=None, help="Limit number of datapoints to show") parser.add_argument("--start", default=None, help="Only include entries starting from this datetime") parser.add_argument("--end", default=None, help="Only include entries until this datetime") return parser.parse_args(args)
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Parse commandline arguments into options for Graph
[ "Parse", "commandline", "arguments", "into", "options", "for", "Graph" ]
[ "\"\"\"\n Parse commandline arguments into options for Graph\n :param args:\n :return:\n \"\"\"" ]
[ { "param": "args", "type": null } ]
{ "returns": [ { "docstring": null, "docstring_tokens": [ "None" ], "type": null } ], "raises": [], "params": [ { "identifier": "args", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import argparse def parse_options(args): parser = argparse.ArgumentParser() parser.add_argument("--logfile", default="connection.log", help="Where is the connection quality data stored") parser.add_argument("--outfile", default="graph.png", help="Where to store the generated graph") parser.add_argument("--dpi", default=100.0, help="Target DPI for graph") parser.add_argument("--datapoints", default=None, help="Limit number of datapoints to show") parser.add_argument("--start", default=None, help="Only include entries starting from this datetime") parser.add_argument("--end", default=None, help="Only include entries until this datetime") return parser.parse_args(args)
79
849
b2ac457c81aad66f249904c1bf51af4a546e4401
azadoks/aiida-core
tests/manage/test_caching_config.py
[ "MIT", "BSD-3-Clause" ]
Python
configure_caching
<not_specific>
def configure_caching(config_with_profile_factory): """ Fixture to set the caching configuration in the test profile to a specific dictionary. This is done by creating a temporary caching configuration file. """ config = config_with_profile_factory() @contextlib.contextmanager def inner(config_dict): for key, value in config_dict.items(): config.set_option(f'caching.{key}', value) yield # reset the configuration for key in config_dict.keys(): config.unset_option(f'caching.{key}') return inner
Fixture to set the caching configuration in the test profile to a specific dictionary. This is done by creating a temporary caching configuration file.
Fixture to set the caching configuration in the test profile to a specific dictionary. This is done by creating a temporary caching configuration file.
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def configure_caching(config_with_profile_factory): config = config_with_profile_factory() @contextlib.contextmanager def inner(config_dict): for key, value in config_dict.items(): config.set_option(f'caching.{key}', value) yield for key in config_dict.keys(): config.unset_option(f'caching.{key}') return inner
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Fixture to set the caching configuration in the test profile to a specific dictionary.
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[ "\"\"\"\n Fixture to set the caching configuration in the test profile to\n a specific dictionary. This is done by creating a temporary\n caching configuration file.\n \"\"\"", "# reset the configuration" ]
[ { "param": "config_with_profile_factory", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "config_with_profile_factory", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import contextlib def configure_caching(config_with_profile_factory): config = config_with_profile_factory() @contextlib.contextmanager def inner(config_dict): for key, value in config_dict.items(): config.set_option(f'caching.{key}', value) yield for key in config_dict.keys(): config.unset_option(f'caching.{key}') return inner
80
407
462585d4e0f04e68e994e80943e1282299537ded
jon-athon/content
Packs/MISP/Integrations/MISPV3/MISPV3.py
[ "MIT" ]
Python
build_tag_output
null
def build_tag_output(given_object): """given_object is attribute or event, depends on the called function""" if given_object.get('Tag'): given_object['Tag'] = [ {'Name': tag.get('name'), 'is_galaxy': tag.get('is_galaxy') } for tag in given_object.get('Tag') ]
given_object is attribute or event, depends on the called function
given_object is attribute or event, depends on the called function
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def build_tag_output(given_object): if given_object.get('Tag'): given_object['Tag'] = [ {'Name': tag.get('name'), 'is_galaxy': tag.get('is_galaxy') } for tag in given_object.get('Tag') ]
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given_object is attribute or event, depends on the called function
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[ "\"\"\"given_object is attribute or event, depends on the called function\"\"\"" ]
[ { "param": "given_object", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "given_object", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def build_tag_output(given_object): if given_object.get('Tag'): given_object['Tag'] = [ {'Name': tag.get('name'), 'is_galaxy': tag.get('is_galaxy') } for tag in given_object.get('Tag') ]
81
867
477d3cf9b9e459f83b232fa785d8088adc781aa9
Phlya/pysradb
pysradb/filter_attrs.py
[ "BSD-3-Clause" ]
Python
guess_tissue_type
<not_specific>
def guess_tissue_type(sample_attribute): """Guess tissue type from sample_attribute data. Parameters ---------- sample_attribute: string sample_attribute string as in the metadata column Returns ------- tissue_type: string Possible cell type of sample. Returns None if no match found. """ sample_attribute = str(sample_attribute) tissue_type = None if "tissue: " in sample_attribute: x = re.search(r"tissue: \w+", sample_attribute) tissue_type = re.sub(r"\s+", " ", x.group(0).lstrip("tissue:").lower().strip()) else: warnings.warn( "Couldn't parse {} for tissue".format(sample_attribute), UserWarning ) return tissue_type
Guess tissue type from sample_attribute data. Parameters ---------- sample_attribute: string sample_attribute string as in the metadata column Returns ------- tissue_type: string Possible cell type of sample. Returns None if no match found.
Guess tissue type from sample_attribute data. Parameters string sample_attribute string as in the metadata column Returns string Possible cell type of sample. Returns None if no match found.
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def guess_tissue_type(sample_attribute): sample_attribute = str(sample_attribute) tissue_type = None if "tissue: " in sample_attribute: x = re.search(r"tissue: \w+", sample_attribute) tissue_type = re.sub(r"\s+", " ", x.group(0).lstrip("tissue:").lower().strip()) else: warnings.warn( "Couldn't parse {} for tissue".format(sample_attribute), UserWarning ) return tissue_type
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Guess tissue type from sample_attribute data.
[ "Guess", "tissue", "type", "from", "sample_attribute", "data", "." ]
[ "\"\"\"Guess tissue type from sample_attribute data.\n\n Parameters\n ----------\n sample_attribute: string\n sample_attribute string as in the metadata column\n\n Returns\n -------\n tissue_type: string\n Possible cell type of sample.\n Returns None if no match found.\n \"\"\"" ]
[ { "param": "sample_attribute", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "sample_attribute", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import warnings import re def guess_tissue_type(sample_attribute): sample_attribute = str(sample_attribute) tissue_type = None if "tissue: " in sample_attribute: x = re.search(r"tissue: \w+", sample_attribute) tissue_type = re.sub(r"\s+", " ", x.group(0).lstrip("tissue:").lower().strip()) else: warnings.warn( "Couldn't parse {} for tissue".format(sample_attribute), UserWarning ) return tissue_type
82
186
eb550db30fae881fd7dc4ae147163ec908b5cae7
lsbloo/GeradorHorariosUfpb
algortimoGA/virtualenv/lib/python3.8/site-packages/jaraco/functools.py
[ "MIT" ]
Python
assign_params
<not_specific>
def assign_params(func, namespace): """ Assign parameters from namespace where func solicits. >>> def func(x, y=3): ... print(x, y) >>> assigned = assign_params(func, dict(x=2, z=4)) >>> assigned() 2 3 The usual errors are raised if a function doesn't receive its required parameters: >>> assigned = assign_params(func, dict(y=3, z=4)) >>> assigned() Traceback (most recent call last): TypeError: func() ...argument... It even works on methods: >>> class Handler: ... def meth(self, arg): ... print(arg) >>> assign_params(Handler().meth, dict(arg='crystal', foo='clear'))() crystal """ sig = inspect.signature(func) params = sig.parameters.keys() call_ns = {k: namespace[k] for k in params if k in namespace} return functools.partial(func, **call_ns)
Assign parameters from namespace where func solicits. >>> def func(x, y=3): ... print(x, y) >>> assigned = assign_params(func, dict(x=2, z=4)) >>> assigned() 2 3 The usual errors are raised if a function doesn't receive its required parameters: >>> assigned = assign_params(func, dict(y=3, z=4)) >>> assigned() Traceback (most recent call last): TypeError: func() ...argument... It even works on methods: >>> class Handler: ... def meth(self, arg): ... print(arg) >>> assign_params(Handler().meth, dict(arg='crystal', foo='clear'))() crystal
Assign parameters from namespace where func solicits. The usual errors are raised if a function doesn't receive its required parameters. It even works on methods.
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def assign_params(func, namespace): sig = inspect.signature(func) params = sig.parameters.keys() call_ns = {k: namespace[k] for k in params if k in namespace} return functools.partial(func, **call_ns)
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Assign parameters from namespace where func solicits.
[ "Assign", "parameters", "from", "namespace", "where", "func", "solicits", "." ]
[ "\"\"\"\n Assign parameters from namespace where func solicits.\n\n >>> def func(x, y=3):\n ... print(x, y)\n >>> assigned = assign_params(func, dict(x=2, z=4))\n >>> assigned()\n 2 3\n\n The usual errors are raised if a function doesn't receive\n its required parameters:\n\n >>> assigned = assign_params(func, dict(y=3, z=4))\n >>> assigned()\n Traceback (most recent call last):\n TypeError: func() ...argument...\n\n It even works on methods:\n\n >>> class Handler:\n ... def meth(self, arg):\n ... print(arg)\n >>> assign_params(Handler().meth, dict(arg='crystal', foo='clear'))()\n crystal\n \"\"\"" ]
[ { "param": "func", "type": null }, { "param": "namespace", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "func", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "namespace", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import inspect import functools def assign_params(func, namespace): sig = inspect.signature(func) params = sig.parameters.keys() call_ns = {k: namespace[k] for k in params if k in namespace} return functools.partial(func, **call_ns)
83
504
7cf20fd0161c0d248819f73cd81dba7e24ab50e0
prizm1/bartsummarizer
fairseq/tasks/sentence_pair_classification_task.py
[ "BSD-3-Clause" ]
Python
add_args
null
def add_args(parser): """Add task-specific arguments to the parser.""" parser.add_argument('data', help='path to data directory') parser.add_argument('--raw-text', default=False, action='store_true', help='load raw text dataset') parser.add_argument('--num-labels', type=int, default=3, help='number of labels') parser.add_argument('--concat-sentences-mode', default='none', help='concat sentences in the dataset. none = dont concat, eos = eos concat, unk = unk concat') parser.add_argument('--use-bos', default=False, action='store_true', help='if true, uses a separate bos tokens to indicate beginning of string')
Add task-specific arguments to the parser.
Add task-specific arguments to the parser.
[ "Add", "task", "-", "specific", "arguments", "to", "the", "parser", "." ]
def add_args(parser): parser.add_argument('data', help='path to data directory') parser.add_argument('--raw-text', default=False, action='store_true', help='load raw text dataset') parser.add_argument('--num-labels', type=int, default=3, help='number of labels') parser.add_argument('--concat-sentences-mode', default='none', help='concat sentences in the dataset. none = dont concat, eos = eos concat, unk = unk concat') parser.add_argument('--use-bos', default=False, action='store_true', help='if true, uses a separate bos tokens to indicate beginning of string')
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Add task-specific arguments to the parser.
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[ "\"\"\"Add task-specific arguments to the parser.\"\"\"" ]
[ { "param": "parser", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "parser", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def add_args(parser): parser.add_argument('data', help='path to data directory') parser.add_argument('--raw-text', default=False, action='store_true', help='load raw text dataset') parser.add_argument('--num-labels', type=int, default=3, help='number of labels') parser.add_argument('--concat-sentences-mode', default='none', help='concat sentences in the dataset. none = dont concat, eos = eos concat, unk = unk concat') parser.add_argument('--use-bos', default=False, action='store_true', help='if true, uses a separate bos tokens to indicate beginning of string')
84
849
adb638de9aa86bd0333d454f873d42a7e0db5a9c
izikeros/sequence_to_sequence_translation
preporcessing.py
[ "MIT" ]
Python
create_mapping
<not_specific>
def create_mapping(vocab): """Creating an array of words from the vocabulary set, use this array as index-to-word dictionary """ idx_to_word = [word[0] for word in vocab] # Adding the word "ZERO" to the beginning of the array idx_to_word.insert(0, 'ZERO') # Adding the word 'UNK' to the end of the array (stands for UNKNOWN words) idx_to_word.append('UNK') # Creating the word-to-index dictionary from the array created above word_to_idx = {word: idx for idx, word in enumerate(idx_to_word)} return word_to_idx, idx_to_word
Creating an array of words from the vocabulary set, use this array as index-to-word dictionary
Creating an array of words from the vocabulary set, use this array as index-to-word dictionary
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def create_mapping(vocab): idx_to_word = [word[0] for word in vocab] idx_to_word.insert(0, 'ZERO') idx_to_word.append('UNK') word_to_idx = {word: idx for idx, word in enumerate(idx_to_word)} return word_to_idx, idx_to_word
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Creating an array of words from the vocabulary set, use this array as index-to-word dictionary
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[ "\"\"\"Creating an array of words from the vocabulary set,\r\n\r\n use this array as index-to-word dictionary\r\n \"\"\"", "# Adding the word \"ZERO\" to the beginning of the array\r", "# Adding the word 'UNK' to the end of the array (stands for UNKNOWN words)\r", "# Creating the word-to-index dictionary from the array created above\r" ]
[ { "param": "vocab", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "vocab", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def create_mapping(vocab): idx_to_word = [word[0] for word in vocab] idx_to_word.insert(0, 'ZERO') idx_to_word.append('UNK') word_to_idx = {word: idx for idx, word in enumerate(idx_to_word)} return word_to_idx, idx_to_word
85
961
f501502e7424fef95f2c2b66c1aa33b1a59481ea
WarwickRSE/SOUP
004_Recursion/list_combination.py
[ "BSD-3-Clause" ]
Python
combine_lists
<not_specific>
def combine_lists(list_of_lists): """Produce all combinations of one word from each list in input list of lists The key principle is to think only about combining this list with all previous ones, assuming those have already been dealt with. I.e. an inductive solution. """ list_size = len(list_of_lists) tmp = [] output = list_of_lists[0] total= len(output) for i in range(1, list_size): list=list_of_lists[i] total*=len(list) for element in list: for i in range(len(output)): tmp.append(output[i]+ element) output = tmp tmp = [] return output
Produce all combinations of one word from each list in input list of lists The key principle is to think only about combining this list with all previous ones, assuming those have already been dealt with. I.e. an inductive solution.
Produce all combinations of one word from each list in input list of lists The key principle is to think only about combining this list with all previous ones, assuming those have already been dealt with.
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def combine_lists(list_of_lists): list_size = len(list_of_lists) tmp = [] output = list_of_lists[0] total= len(output) for i in range(1, list_size): list=list_of_lists[i] total*=len(list) for element in list: for i in range(len(output)): tmp.append(output[i]+ element) output = tmp tmp = [] return output
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Produce all combinations of one word from each list in input list of lists The key principle is to think only about combining this list with all previous ones, assuming those have already been dealt with.
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[ "\"\"\"Produce all combinations of one word from each list in input list of lists\n The key principle is to think only about combining this list with all previous ones,\n assuming those have already been dealt with. I.e. an inductive solution.\n\n \"\"\"" ]
[ { "param": "list_of_lists", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "list_of_lists", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def combine_lists(list_of_lists): list_size = len(list_of_lists) tmp = [] output = list_of_lists[0] total= len(output) for i in range(1, list_size): list=list_of_lists[i] total*=len(list) for element in list: for i in range(len(output)): tmp.append(output[i]+ element) output = tmp tmp = [] return output
86
98
fe9544d5782ec48c533757f0ef15c32050542ed7
MikeOMa/DriftMLP
driftmlp/drifter_indexing/driftiter/__init__.py
[ "MIT" ]
Python
drifter_meta
<not_specific>
def drifter_meta(drifter_id_group, variables): """ Simple function to grab metadata from the h5py group. Input: drifter_id_group: The group corresponding to one id from the h5py file. Output: dict_out: with variables as the keys. """ dict_out = {key: drifter_id_group.attrs[key][:] for key in variables} return dict_out
Simple function to grab metadata from the h5py group. Input: drifter_id_group: The group corresponding to one id from the h5py file. Output: dict_out: with variables as the keys.
Simple function to grab metadata from the h5py group. Input: drifter_id_group: The group corresponding to one id from the h5py file. Output: dict_out: with variables as the keys.
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def drifter_meta(drifter_id_group, variables): dict_out = {key: drifter_id_group.attrs[key][:] for key in variables} return dict_out
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Simple function to grab metadata from the h5py group.
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[ "\"\"\"\n Simple function to grab metadata from the h5py group.\n Input:\n drifter_id_group: The group corresponding to one id from the h5py file.\n Output:\n dict_out: with variables as the keys.\n \"\"\"" ]
[ { "param": "drifter_id_group", "type": null }, { "param": "variables", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "drifter_id_group", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "variables", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def drifter_meta(drifter_id_group, variables): dict_out = {key: drifter_id_group.attrs[key][:] for key in variables} return dict_out
87
592
449492c6887e5d02f66a26e88e759e39fd8995e1
Ranga123/test1
build/run_tests.py
[ "Apache-2.0" ]
Python
_get_term_width
<not_specific>
def _get_term_width(): 'Attempt to discern the width of the terminal' # This may not work on all platforms, in which case the default of 80 # characters is used. Improvements welcomed. def ioctl_GWINSZ(fd): try: import fcntl, termios, struct, os cr = struct.unpack('hh', fcntl.ioctl(fd, termios.TIOCGWINSZ, '1234')) except: return None return cr cr = None if not cr: try: cr = (os.environ['SVN_MAKE_CHECK_LINES'], os.environ['SVN_MAKE_CHECK_COLUMNS']) except: cr = None if not cr: cr = ioctl_GWINSZ(0) or ioctl_GWINSZ(1) or ioctl_GWINSZ(2) if not cr: try: fd = os.open(os.ctermid(), os.O_RDONLY) cr = ioctl_GWINSZ(fd) os.close(fd) except: pass if not cr: try: cr = (os.environ['LINES'], os.environ['COLUMNS']) except: cr = None if not cr: # Default if sys.platform == 'win32': cr = (25, 79) else: cr = (25, 80) return int(cr[1])
Attempt to discern the width of the terminal
Attempt to discern the width of the terminal
[ "Attempt", "to", "discern", "the", "width", "of", "the", "terminal" ]
def _get_term_width(): def ioctl_GWINSZ(fd): try: import fcntl, termios, struct, os cr = struct.unpack('hh', fcntl.ioctl(fd, termios.TIOCGWINSZ, '1234')) except: return None return cr cr = None if not cr: try: cr = (os.environ['SVN_MAKE_CHECK_LINES'], os.environ['SVN_MAKE_CHECK_COLUMNS']) except: cr = None if not cr: cr = ioctl_GWINSZ(0) or ioctl_GWINSZ(1) or ioctl_GWINSZ(2) if not cr: try: fd = os.open(os.ctermid(), os.O_RDONLY) cr = ioctl_GWINSZ(fd) os.close(fd) except: pass if not cr: try: cr = (os.environ['LINES'], os.environ['COLUMNS']) except: cr = None if not cr: if sys.platform == 'win32': cr = (25, 79) else: cr = (25, 80) return int(cr[1])
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Attempt to discern the width of the terminal
[ "Attempt", "to", "discern", "the", "width", "of", "the", "terminal" ]
[ "'Attempt to discern the width of the terminal'", "# This may not work on all platforms, in which case the default of 80", "# characters is used. Improvements welcomed.", "# Default" ]
[]
{ "returns": [], "raises": [], "params": [], "outlier_params": [], "others": [] }
import fcntl import sys import struct import os import termios def _get_term_width(): def ioctl_GWINSZ(fd): try: import fcntl, termios, struct, os cr = struct.unpack('hh', fcntl.ioctl(fd, termios.TIOCGWINSZ, '1234')) except: return None return cr cr = None if not cr: try: cr = (os.environ['SVN_MAKE_CHECK_LINES'], os.environ['SVN_MAKE_CHECK_COLUMNS']) except: cr = None if not cr: cr = ioctl_GWINSZ(0) or ioctl_GWINSZ(1) or ioctl_GWINSZ(2) if not cr: try: fd = os.open(os.ctermid(), os.O_RDONLY) cr = ioctl_GWINSZ(fd) os.close(fd) except: pass if not cr: try: cr = (os.environ['LINES'], os.environ['COLUMNS']) except: cr = None if not cr: if sys.platform == 'win32': cr = (25, 79) else: cr = (25, 80) return int(cr[1])
88
31
3a04cc0858ea1984ea4e383ce4809c47e34ed64d
jkrukoff/Exercism
python/pangram/pangram.py
[ "MIT" ]
Python
is_pangram
bool
def is_pangram(sentence: str) -> bool: """ Determine if a given string contains all the characters from a to z. sentence -- Any string. returns -- true/false for if string contains all letters from a to z. """ letters = set(string.ascii_lowercase) return letters.issubset(sentence.lower())
Determine if a given string contains all the characters from a to z. sentence -- Any string. returns -- true/false for if string contains all letters from a to z.
Determine if a given string contains all the characters from a to z. sentence -- Any string. returns -- true/false for if string contains all letters from a to z.
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def is_pangram(sentence: str) -> bool: letters = set(string.ascii_lowercase) return letters.issubset(sentence.lower())
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Determine if a given string contains all the characters from a to z. sentence -- Any string.
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[ "\"\"\"\n Determine if a given string contains all the characters from a to z.\n\n sentence -- Any string.\n returns -- true/false for if string contains all letters from a to z.\n \"\"\"" ]
[ { "param": "sentence", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "sentence", "type": "str", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import string def is_pangram(sentence: str) -> bool: letters = set(string.ascii_lowercase) return letters.issubset(sentence.lower())
89
646
cfec1b5ed01d104807ec2c5af1d813be7e96110d
CSeq/manticore
manticore/core/cpu/x86.py
[ "Apache-2.0" ]
Python
TEST
null
def TEST(cpu, src1, src2): ''' Logical compare. Computes the bit-wise logical AND of first operand (source 1 operand) and the second operand (source 2 operand) and sets the SF, ZF, and PF status flags according to the result. The result is then discarded:: TEMP = SRC1 AND SRC2; SF = MSB(TEMP); IF TEMP = 0 THEN ZF = 1; ELSE ZF = 0; FI: PF = BitwiseXNOR(TEMP[0:7]); CF = 0; OF = 0; (*AF is Undefined*) :param cpu: current CPU. :param src1: first operand. :param src2: second operand. ''' #Defined Flags: szp temp = src1.read() & src2.read(); cpu.SF = (temp & (1 << (src1.size-1))) != 0 cpu.ZF = temp == 0 cpu.PF = cpu._calculate_parity_flag(temp) cpu.CF = False cpu.OF = False
Logical compare. Computes the bit-wise logical AND of first operand (source 1 operand) and the second operand (source 2 operand) and sets the SF, ZF, and PF status flags according to the result. The result is then discarded:: TEMP = SRC1 AND SRC2; SF = MSB(TEMP); IF TEMP = 0 THEN ZF = 1; ELSE ZF = 0; FI: PF = BitwiseXNOR(TEMP[0:7]); CF = 0; OF = 0; (*AF is Undefined*) :param cpu: current CPU. :param src1: first operand. :param src2: second operand.
Logical compare. Computes the bit-wise logical AND of first operand (source 1 operand) and the second operand (source 2 operand) and sets the SF, ZF, and PF status flags according to the result. The result is then discarded:.
[ "Logical", "compare", ".", "Computes", "the", "bit", "-", "wise", "logical", "AND", "of", "first", "operand", "(", "source", "1", "operand", ")", "and", "the", "second", "operand", "(", "source", "2", "operand", ")", "and", "sets", "the", "SF", "ZF", "and", "PF", "status", "flags", "according", "to", "the", "result", ".", "The", "result", "is", "then", "discarded", ":", "." ]
def TEST(cpu, src1, src2): temp = src1.read() & src2.read(); cpu.SF = (temp & (1 << (src1.size-1))) != 0 cpu.ZF = temp == 0 cpu.PF = cpu._calculate_parity_flag(temp) cpu.CF = False cpu.OF = False
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Logical compare.
[ "Logical", "compare", "." ]
[ "'''\n Logical compare. \n \n Computes the bit-wise logical AND of first operand (source 1 operand) \n and the second operand (source 2 operand) and sets the SF, ZF, and PF \n status flags according to the result. The result is then discarded::\n\n TEMP = SRC1 AND SRC2;\n SF = MSB(TEMP);\n IF TEMP = 0\n THEN ZF = 1;\n ELSE ZF = 0;\n FI:\n PF = BitwiseXNOR(TEMP[0:7]);\n CF = 0;\n OF = 0;\n (*AF is Undefined*)\n \n :param cpu: current CPU. \n :param src1: first operand.\n :param src2: second operand.\n '''", "#Defined Flags: szp" ]
[ { "param": "cpu", "type": null }, { "param": "src1", "type": null }, { "param": "src2", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "cpu", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null }, { "identifier": "src1", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null }, { "identifier": "src2", "type": null, "docstring": null, "docstring_tokens": [ "None" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def TEST(cpu, src1, src2): temp = src1.read() & src2.read(); cpu.SF = (temp & (1 << (src1.size-1))) != 0 cpu.ZF = temp == 0 cpu.PF = cpu._calculate_parity_flag(temp) cpu.CF = False cpu.OF = False
90
237
cceb367304af50013cb611d35ef35ece567c7c9d
jennyfong/pythonbits
file_groups.py
[ "MIT" ]
Python
numRange
<not_specific>
def numRange(numList): """ Get the first and last number in the list """ start = numList[0] end = numList[-1] if start != end: return "{}-{}".format(start, end) else: return "{}".format(start)
Get the first and last number in the list
Get the first and last number in the list
[ "Get", "the", "first", "and", "last", "number", "in", "the", "list" ]
def numRange(numList): start = numList[0] end = numList[-1] if start != end: return "{}-{}".format(start, end) else: return "{}".format(start)
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Get the first and last number in the list
[ "Get", "the", "first", "and", "last", "number", "in", "the", "list" ]
[ "\"\"\"\n Get the first and last number in the list\n \"\"\"" ]
[ { "param": "numList", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "numList", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def numRange(numList): start = numList[0] end = numList[-1] if start != end: return "{}-{}".format(start, end) else: return "{}".format(start)
91
603
a3c8d79203071fbd0a3231ff242144dce321cc3a
akapila011/Text-to-Image
text_to_image/utilities.py
[ "MIT" ]
Python
convert_char_to_int
<not_specific>
def convert_char_to_int(char, limit=256): """ Take a character and return an integer value while ensuring the values returned do not go above the limit. :param str char: A single character. :param int limit: An integer representing the largest value which will start requiring reducing char value. (default=256). :return int: A number between 1 (0=NULL) and the limit that represents the int value of the char. """ value = ord(char) % limit value = 1 if value == 0 else value return value
Take a character and return an integer value while ensuring the values returned do not go above the limit. :param str char: A single character. :param int limit: An integer representing the largest value which will start requiring reducing char value. (default=256). :return int: A number between 1 (0=NULL) and the limit that represents the int value of the char.
Take a character and return an integer value while ensuring the values returned do not go above the limit.
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def convert_char_to_int(char, limit=256): value = ord(char) % limit value = 1 if value == 0 else value return value
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Take a character and return an integer value while ensuring the values returned do not go above the limit.
[ "Take", "a", "character", "and", "return", "an", "integer", "value", "while", "ensuring", "the", "values", "returned", "do", "not", "go", "above", "the", "limit", "." ]
[ "\"\"\"\n Take a character and return an integer value while ensuring the values returned do not go above the limit.\n :param str char: A single character.\n :param int limit: An integer representing the largest value which will start requiring reducing char value.\n (default=256).\n :return int: A number between 1 (0=NULL) and the limit that represents the int value of the char.\n \"\"\"" ]
[ { "param": "char", "type": null }, { "param": "limit", "type": null } ]
{ "returns": [ { "docstring": "A number between 1 (0=NULL) and the limit that represents the int value of the char.", "docstring_tokens": [ "A", "number", "between", "1", "(", "0", "=", "NULL", ")", "and", "the", "limit", "that", "represents", "the", "int", "value", "of", "the", "char", "." ], "type": "int" } ], "raises": [], "params": [ { "identifier": "char", "type": null, "docstring": "A single character.", "docstring_tokens": [ "A", "single", "character", "." ], "default": null, "is_optional": false }, { "identifier": "limit", "type": null, "docstring": "An integer representing the largest value which will start requiring reducing char value.", "docstring_tokens": [ "An", "integer", "representing", "the", "largest", "value", "which", "will", "start", "requiring", "reducing", "char", "value", "." ], "default": null, "is_optional": false } ], "outlier_params": [], "others": [] }
def convert_char_to_int(char, limit=256): value = ord(char) % limit value = 1 if value == 0 else value return value
92
384
d73c866df2d6c0c82eec69683313d6c98803488a
mtholder/peyotl
peyotl/__init__.py
[ "BSD-2-Clause" ]
Python
iter_tree
null
def iter_tree(nex_obj): """Generator over each tree object in the NexSON object.""" for tb in nex_obj.get('trees', []): for tree in tb.get('tree', []): yield tree
Generator over each tree object in the NexSON object.
Generator over each tree object in the NexSON object.
[ "Generator", "over", "each", "tree", "object", "in", "the", "NexSON", "object", "." ]
def iter_tree(nex_obj): for tb in nex_obj.get('trees', []): for tree in tb.get('tree', []): yield tree
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Generator over each tree object in the NexSON object.
[ "Generator", "over", "each", "tree", "object", "in", "the", "NexSON", "object", "." ]
[ "\"\"\"Generator over each tree object in the NexSON object.\"\"\"" ]
[ { "param": "nex_obj", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "nex_obj", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def iter_tree(nex_obj): for tb in nex_obj.get('trees', []): for tree in tb.get('tree', []): yield tree
93
706
5cc205938fb7dd2eef8c9924bb92b3d1fb712255
erwanp/pyspeckit
pyspeckit/spectrum/plotters.py
[ "MIT", "BSD-3-Clause" ]
Python
parse_norm
<not_specific>
def parse_norm(norm): """ Expected format: norm = 10E15 """ try: base, exp = norm.split('E') except ValueError: base, exp = norm.split('e') if float(base) == 1.0: norm = '10' else: norm = base norm += '^{%s}' % exp return norm
Expected format: norm = 10E15
Expected format: norm = 10E15
[ "Expected", "format", ":", "norm", "=", "10E15" ]
def parse_norm(norm): try: base, exp = norm.split('E') except ValueError: base, exp = norm.split('e') if float(base) == 1.0: norm = '10' else: norm = base norm += '^{%s}' % exp return norm
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Expected format: norm = 10E15
[ "Expected", "format", ":", "norm", "=", "10E15" ]
[ "\"\"\"\n Expected format: norm = 10E15\n \"\"\"" ]
[ { "param": "norm", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "norm", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def parse_norm(norm): try: base, exp = norm.split('E') except ValueError: base, exp = norm.split('e') if float(base) == 1.0: norm = '10' else: norm = base norm += '^{%s}' % exp return norm
94
609
e9db6a6856a6ea3fe010f6fed54a060e5f1f996e
dialoguemd/pypred
pypred/util.py
[ "BSD-3-Clause" ]
Python
harmonic_mean
<not_specific>
def harmonic_mean(lst): "Returns the harmonic mean. Will crash if any value is zero." n = len(lst) inv_sum = sum((1.0 / x) for x in lst) return (1.0 / ((1.0 / n) * inv_sum))
Returns the harmonic mean. Will crash if any value is zero.
Returns the harmonic mean. Will crash if any value is zero.
[ "Returns", "the", "harmonic", "mean", ".", "Will", "crash", "if", "any", "value", "is", "zero", "." ]
def harmonic_mean(lst): n = len(lst) inv_sum = sum((1.0 / x) for x in lst) return (1.0 / ((1.0 / n) * inv_sum))
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Returns the harmonic mean.
[ "Returns", "the", "harmonic", "mean", "." ]
[ "\"Returns the harmonic mean. Will crash if any value is zero.\"" ]
[ { "param": "lst", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "lst", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def harmonic_mean(lst): n = len(lst) inv_sum = sum((1.0 / x) for x in lst) return (1.0 / ((1.0 / n) * inv_sum))
96
845
2d122810280dbaf3cd0bf286636fcd56a6b6a47a
scivision/asyncio-subprocess-examples
src/asyncio_subprocess_examples/__init__.py
[ "MIT" ]
Python
fortran_compiler_ok_sync
typing.Tuple[str, bool]
def fortran_compiler_ok_sync(compiler: str, name: str, src: str) -> typing.Tuple[str, bool]: """check that Fortran compiler is able to compile a basic program""" with tempfile.NamedTemporaryFile("w", suffix=".f90", delete=False) as f: f.write(src) logging.debug(f"testing {compiler} with source: {src}") cmd = [compiler, f.name] ret = subprocess.run(cmd, stderr=subprocess.DEVNULL) # this and delete=False is necessary due to Windows no double-open file limitation os.unlink(f.name) return name, ret.returncode == 0
check that Fortran compiler is able to compile a basic program
check that Fortran compiler is able to compile a basic program
[ "check", "that", "Fortran", "compiler", "is", "able", "to", "compile", "a", "basic", "program" ]
def fortran_compiler_ok_sync(compiler: str, name: str, src: str) -> typing.Tuple[str, bool]: with tempfile.NamedTemporaryFile("w", suffix=".f90", delete=False) as f: f.write(src) logging.debug(f"testing {compiler} with source: {src}") cmd = [compiler, f.name] ret = subprocess.run(cmd, stderr=subprocess.DEVNULL) os.unlink(f.name) return name, ret.returncode == 0
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check that Fortran compiler is able to compile a basic program
[ "check", "that", "Fortran", "compiler", "is", "able", "to", "compile", "a", "basic", "program" ]
[ "\"\"\"check that Fortran compiler is able to compile a basic program\"\"\"", "# this and delete=False is necessary due to Windows no double-open file limitation" ]
[ { "param": "compiler", "type": "str" }, { "param": "name", "type": "str" }, { "param": "src", "type": "str" } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "compiler", "type": "str", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "name", "type": "str", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "src", "type": "str", "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import subprocess import tempfile import logging import os import typing def fortran_compiler_ok_sync(compiler: str, name: str, src: str) -> typing.Tuple[str, bool]: with tempfile.NamedTemporaryFile("w", suffix=".f90", delete=False) as f: f.write(src) logging.debug(f"testing {compiler} with source: {src}") cmd = [compiler, f.name] ret = subprocess.run(cmd, stderr=subprocess.DEVNULL) os.unlink(f.name) return name, ret.returncode == 0
97
926
7a4b77500026829e09347d9b3969e9a4c978a15e
liam-i/firebase-ios-sdk
Firestore/Protos/build_protos.py
[ "Apache-2.0" ]
Python
cpp_rename_in
<not_specific>
def cpp_rename_in(lines): """Renames an IN symbol to IN_. If a proto uses a enum member named 'IN', protobuf happily uses that in the message definition. This conflicts with the IN parameter annotation macro in windows.h. Args: lines: The lines to fix. Returns: The lines, fixed. """ in_macro = re.compile(r'\bIN\b') return [in_macro.sub('IN_', line) for line in lines]
Renames an IN symbol to IN_. If a proto uses a enum member named 'IN', protobuf happily uses that in the message definition. This conflicts with the IN parameter annotation macro in windows.h. Args: lines: The lines to fix. Returns: The lines, fixed.
Renames an IN symbol to IN_. If a proto uses a enum member named 'IN', protobuf happily uses that in the message definition. This conflicts with the IN parameter annotation macro in windows.h.
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def cpp_rename_in(lines): in_macro = re.compile(r'\bIN\b') return [in_macro.sub('IN_', line) for line in lines]
[ "def", "cpp_rename_in", "(", "lines", ")", ":", "in_macro", "=", "re", ".", "compile", "(", "r'\\bIN\\b'", ")", "return", "[", "in_macro", ".", "sub", "(", "'IN_'", ",", "line", ")", "for", "line", "in", "lines", "]" ]
Renames an IN symbol to IN_.
[ "Renames", "an", "IN", "symbol", "to", "IN_", "." ]
[ "\"\"\"Renames an IN symbol to IN_.\n\n If a proto uses a enum member named 'IN', protobuf happily uses that in the\n message definition. This conflicts with the IN parameter annotation macro in\n windows.h.\n\n Args:\n lines: The lines to fix.\n\n Returns:\n The lines, fixed.\n \"\"\"" ]
[ { "param": "lines", "type": null } ]
{ "returns": [ { "docstring": "The lines, fixed.", "docstring_tokens": [ "The", "lines", "fixed", "." ], "type": null } ], "raises": [], "params": [ { "identifier": "lines", "type": null, "docstring": "The lines to fix.", "docstring_tokens": [ "The", "lines", "to", "fix", "." ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import re def cpp_rename_in(lines): in_macro = re.compile(r'\bIN\b') return [in_macro.sub('IN_', line) for line in lines]
98
618
9e4e5a5a2028afec1fb905195a7b2b3b874ff7ca
EsoNes0/dork
dork/types.py
[ "MIT" ]
Python
use
<not_specific>
def use(target, name): """Useless use method This method is called by filler items to be used Concrete unusable item class use method Args: target (Player): passes Player as target to be used on name (str): passed as name of item used returns: blurb (str): returns "You find no use of this item" """ return "You find no use of this item"
Useless use method This method is called by filler items to be used Concrete unusable item class use method Args: target (Player): passes Player as target to be used on name (str): passed as name of item used returns: blurb (str): returns "You find no use of this item"
Useless use method This method is called by filler items to be used Concrete unusable item class use method
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def use(target, name): return "You find no use of this item"
[ "def", "use", "(", "target", ",", "name", ")", ":", "return", "\"You find no use of this item\"" ]
Useless use method This method is called by filler items to be used
[ "Useless", "use", "method", "This", "method", "is", "called", "by", "filler", "items", "to", "be", "used" ]
[ "\"\"\"Useless use method\n\n This method is called by filler items to be used\n\n Concrete unusable item class use method\n\n Args:\n target (Player): passes Player as target to be used on\n name (str): passed as name of item used\n\n returns:\n blurb (str): returns \"You find no use of this item\"\n\n \"\"\"" ]
[ { "param": "target", "type": null }, { "param": "name", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "target", "type": null, "docstring": "passes Player as target to be used on", "docstring_tokens": [ "passes", "Player", "as", "target", "to", "be", "used", "on" ], "default": null, "is_optional": false }, { "identifier": "name", "type": null, "docstring": "passed as name of item used", "docstring_tokens": [ "passed", "as", "name", "of", "item", "used" ], "default": null, "is_optional": false } ], "outlier_params": [], "others": [] }
def use(target, name): return "You find no use of this item"
99
1,006
74b245113943f48daaed839f4beea4a217a7a9fe
c3e/gridpy
gridpy.py
[ "MIT" ]
Python
split_in_2bytes
<not_specific>
def split_in_2bytes(value): """ Returns a tuple with 2 integers (upper,lower) matching the according bytes The AMG88 usually uses 2 byte to store 12bit values. """ upper = value >> 9 lower = 0b011111111 & value return (upper, lower)
Returns a tuple with 2 integers (upper,lower) matching the according bytes The AMG88 usually uses 2 byte to store 12bit values.
Returns a tuple with 2 integers (upper,lower) matching the according bytes The AMG88 usually uses 2 byte to store 12bit values.
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def split_in_2bytes(value): upper = value >> 9 lower = 0b011111111 & value return (upper, lower)
[ "def", "split_in_2bytes", "(", "value", ")", ":", "upper", "=", "value", ">>", "9", "lower", "=", "0b011111111", "&", "value", "return", "(", "upper", ",", "lower", ")" ]
Returns a tuple with 2 integers (upper,lower) matching the according bytes The AMG88 usually uses 2 byte to store 12bit values.
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[ "\"\"\"\n Returns a tuple with 2 integers (upper,lower) matching the according bytes\n The AMG88 usually uses 2 byte to store 12bit values.\n \"\"\"" ]
[ { "param": "value", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "value", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def split_in_2bytes(value): upper = value >> 9 lower = 0b011111111 & value return (upper, lower)
100
20
2e09acbff09afa7a8f17170f3121237522f9568d
aidan-lane/GMFinalProject
server/main.py
[ "MIT" ]
Python
cardinal_direction
<not_specific>
def cardinal_direction(b): """ Calculate the cardinal direction for a given bearing. Ex: 0 is 'North Args: b: bearing (in degrees) Returns: A string representing cardinal direction """ dirs = ["North", "North-East", "East", "South-East", "South", "South-West", "West", "North-West"] degree = 337.5 for dir in dirs: if b >= degree and b < degree + 45: return dir if degree + 45 >= 360: degree = 22.5 else: degree += 45 return None
Calculate the cardinal direction for a given bearing. Ex: 0 is 'North Args: b: bearing (in degrees) Returns: A string representing cardinal direction
Calculate the cardinal direction for a given bearing. Ex: 0 is 'North
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def cardinal_direction(b): dirs = ["North", "North-East", "East", "South-East", "South", "South-West", "West", "North-West"] degree = 337.5 for dir in dirs: if b >= degree and b < degree + 45: return dir if degree + 45 >= 360: degree = 22.5 else: degree += 45 return None
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Calculate the cardinal direction for a given bearing.
[ "Calculate", "the", "cardinal", "direction", "for", "a", "given", "bearing", "." ]
[ "\"\"\" Calculate the cardinal direction for a given bearing.\n\n Ex: 0 is 'North\n\n Args:\n b: bearing (in degrees)\n\n Returns:\n A string representing cardinal direction\n \"\"\"" ]
[ { "param": "b", "type": null } ]
{ "returns": [ { "docstring": "A string representing cardinal direction", "docstring_tokens": [ "A", "string", "representing", "cardinal", "direction" ], "type": null } ], "raises": [], "params": [ { "identifier": "b", "type": null, "docstring": "bearing (in degrees)", "docstring_tokens": [ "bearing", "(", "in", "degrees", ")" ], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def cardinal_direction(b): dirs = ["North", "North-East", "East", "South-East", "South", "South-West", "West", "North-West"] degree = 337.5 for dir in dirs: if b >= degree and b < degree + 45: return dir if degree + 45 >= 360: degree = 22.5 else: degree += 45 return None
101
29
8c8ef114651c3d6d6990d715e2a9605ca646ee43
avcopan/elstruct-interface
elstruct/writer/storage/__init__.py
[ "Apache-2.0" ]
Python
single_val_writer
<not_specific>
def single_val_writer(file_name, output_string): """ Writes a single float value to the file. """ with open(file_name, 'w') as info_file: info_file.write( ) return None
Writes a single float value to the file.
Writes a single float value to the file.
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def single_val_writer(file_name, output_string): with open(file_name, 'w') as info_file: info_file.write( ) return None
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Writes a single float value to the file.
[ "Writes", "a", "single", "float", "value", "to", "the", "file", "." ]
[ "\"\"\" Writes a single float value to the file.\n \"\"\"" ]
[ { "param": "file_name", "type": null }, { "param": "output_string", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "file_name", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "output_string", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def single_val_writer(file_name, output_string): with open(file_name, 'w') as info_file: info_file.write( ) return None
102
389
de2877a0a841293fa84498df50935e88f30a931d
wbazant/kneaddata
kneaddata/read_count_table_concat_pairs.py
[ "MIT" ]
Python
parse_arguments
<not_specific>
def parse_arguments(args): """ Parse the arguments from the user""" parser=argparse.ArgumentParser( description="Count paired/orphan reads from kneaddata run on a set of paired end reads concatenated into a single file.") parser.add_argument("--input", help="The folder of kneaddata output files for all samples", required=True) parser.add_argument("--output", help="The output file of reads to write.", required=True) return parser.parse_args()
Parse the arguments from the user
Parse the arguments from the user
[ "Parse", "the", "arguments", "from", "the", "user" ]
def parse_arguments(args): parser=argparse.ArgumentParser( description="Count paired/orphan reads from kneaddata run on a set of paired end reads concatenated into a single file.") parser.add_argument("--input", help="The folder of kneaddata output files for all samples", required=True) parser.add_argument("--output", help="The output file of reads to write.", required=True) return parser.parse_args()
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Parse the arguments from the user
[ "Parse", "the", "arguments", "from", "the", "user" ]
[ "\"\"\" Parse the arguments from the user\"\"\"" ]
[ { "param": "args", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "args", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import argparse def parse_arguments(args): parser=argparse.ArgumentParser( description="Count paired/orphan reads from kneaddata run on a set of paired end reads concatenated into a single file.") parser.add_argument("--input", help="The folder of kneaddata output files for all samples", required=True) parser.add_argument("--output", help="The output file of reads to write.", required=True) return parser.parse_args()
103
116
6693540ea470157df5566140677a3ebb2745f363
delvor64/practices-of-the-python-pro
ch03/ex_01_greeter.py
[ "MIT" ]
Python
part_of_day
<not_specific>
def part_of_day(): ''' Determine which part of the day to greet the customer with. ''' hour = datetime.datetime.now().hour if hour < 12: part = 'Morning' elif hour < 17: part = 'Afternoon' else: part = 'Evening' return part
Determine which part of the day to greet the customer with.
Determine which part of the day to greet the customer with.
[ "Determine", "which", "part", "of", "the", "day", "to", "greet", "the", "customer", "with", "." ]
def part_of_day(): hour = datetime.datetime.now().hour if hour < 12: part = 'Morning' elif hour < 17: part = 'Afternoon' else: part = 'Evening' return part
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Determine which part of the day to greet the customer with.
[ "Determine", "which", "part", "of", "the", "day", "to", "greet", "the", "customer", "with", "." ]
[ "'''\n Determine which part of the day to greet the customer with.\n '''" ]
[]
{ "returns": [], "raises": [], "params": [], "outlier_params": [], "others": [] }
import datetime def part_of_day(): hour = datetime.datetime.now().hour if hour < 12: part = 'Morning' elif hour < 17: part = 'Afternoon' else: part = 'Evening' return part
104
126
3155603a10a0d361d6a7ad339ad45f7b79ae0247
bernhardreiter/OpenSlides
server/openslides/core/migrations/0002_misc_features.py
[ "MIT" ]
Python
remove_old_countdowns_messages
null
def remove_old_countdowns_messages(apps, schema_editor): """ Remove old countdowns and messages created by 2.0 from projector elements which are unusable in 2.1. """ Projector = apps.get_model("core", "Projector") projector = Projector.objects.get(pk=1) projector_config = projector.config for key, value in list(projector.config.items()): if value.get("name") in ("core/countdown", "core/message"): del projector_config[key] projector.config = projector_config projector.save(skip_autoupdate=True)
Remove old countdowns and messages created by 2.0 from projector elements which are unusable in 2.1.
Remove old countdowns and messages created by 2.0 from projector elements which are unusable in 2.1.
[ "Remove", "old", "countdowns", "and", "messages", "created", "by", "2", ".", "0", "from", "projector", "elements", "which", "are", "unusable", "in", "2", ".", "1", "." ]
def remove_old_countdowns_messages(apps, schema_editor): Projector = apps.get_model("core", "Projector") projector = Projector.objects.get(pk=1) projector_config = projector.config for key, value in list(projector.config.items()): if value.get("name") in ("core/countdown", "core/message"): del projector_config[key] projector.config = projector_config projector.save(skip_autoupdate=True)
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Remove old countdowns and messages created by 2.0 from projector elements which are unusable in 2.1.
[ "Remove", "old", "countdowns", "and", "messages", "created", "by", "2", ".", "0", "from", "projector", "elements", "which", "are", "unusable", "in", "2", ".", "1", "." ]
[ "\"\"\"\n Remove old countdowns and messages created by 2.0 from projector elements which are unusable in 2.1.\n \"\"\"" ]
[ { "param": "apps", "type": null }, { "param": "schema_editor", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "apps", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "schema_editor", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def remove_old_countdowns_messages(apps, schema_editor): Projector = apps.get_model("core", "Projector") projector = Projector.objects.get(pk=1) projector_config = projector.config for key, value in list(projector.config.items()): if value.get("name") in ("core/countdown", "core/message"): del projector_config[key] projector.config = projector_config projector.save(skip_autoupdate=True)
105
453
a7230b83935edfcbd4f7b042fd3841ef68ade640
flothesof/rois-maudits-carte-interactive
make_map.py
[ "BSD-3-Clause" ]
Python
make_snippet
<not_specific>
def make_snippet(snippets, location): """Makes a colored html snippet.""" output = "<br>".join(sentence.replace( location, f'<i style="background-color: yellow;">{location}</i>') for sentence in snippets) return output
Makes a colored html snippet.
Makes a colored html snippet.
[ "Makes", "a", "colored", "html", "snippet", "." ]
def make_snippet(snippets, location): output = "<br>".join(sentence.replace( location, f'<i style="background-color: yellow;">{location}</i>') for sentence in snippets) return output
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Makes a colored html snippet.
[ "Makes", "a", "colored", "html", "snippet", "." ]
[ "\"\"\"Makes a colored html snippet.\"\"\"" ]
[ { "param": "snippets", "type": null }, { "param": "location", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "snippets", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "location", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
def make_snippet(snippets, location): output = "<br>".join(sentence.replace( location, f'<i style="background-color: yellow;">{location}</i>') for sentence in snippets) return output
106
731
2602983113e7dc0d48af4bf30da65e854db2b336
lboyd93/arcgis-runtime-samples-dotnet
tools/metadata_tools/process_metadata.py
[ "Apache-2.0" ]
Python
write_samples_toc
null
def write_samples_toc(platform_dir, relative_path_to_samples, samples_in_categories): ''' sample_in_categories is a dictionary of categories, each key is a list of sample_metadata platform_dir is where the readme.md file should be written ''' readme_text = "# Table of contents\n\n" for category in samples_in_categories.keys(): readme_text += f"## {category}\n\n" for sample in samples_in_categories[category]: entry_url = f"{relative_path_to_samples}/{sample.category}/{sample.formal_name}/readme.md" entry_url = urllib.parse.quote(entry_url) readme_text += f"* [{sample.friendly_name}]({entry_url}) - {sample.description}\n" readme_text += "\n" readme_path = os.path.join(platform_dir, "../..", "readme.md") with open(readme_path, 'w+') as file: file.write(readme_text)
sample_in_categories is a dictionary of categories, each key is a list of sample_metadata platform_dir is where the readme.md file should be written
sample_in_categories is a dictionary of categories, each key is a list of sample_metadata platform_dir is where the readme.md file should be written
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def write_samples_toc(platform_dir, relative_path_to_samples, samples_in_categories): readme_text = "# Table of contents\n\n" for category in samples_in_categories.keys(): readme_text += f"## {category}\n\n" for sample in samples_in_categories[category]: entry_url = f"{relative_path_to_samples}/{sample.category}/{sample.formal_name}/readme.md" entry_url = urllib.parse.quote(entry_url) readme_text += f"* [{sample.friendly_name}]({entry_url}) - {sample.description}\n" readme_text += "\n" readme_path = os.path.join(platform_dir, "../..", "readme.md") with open(readme_path, 'w+') as file: file.write(readme_text)
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sample_in_categories is a dictionary of categories, each key is a list of sample_metadata platform_dir is where the readme.md file should be written
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[ "'''\n sample_in_categories is a dictionary of categories, each key is a list of sample_metadata\n platform_dir is where the readme.md file should be written\n '''" ]
[ { "param": "platform_dir", "type": null }, { "param": "relative_path_to_samples", "type": null }, { "param": "samples_in_categories", "type": null } ]
{ "returns": [], "raises": [], "params": [ { "identifier": "platform_dir", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "relative_path_to_samples", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null }, { "identifier": "samples_in_categories", "type": null, "docstring": null, "docstring_tokens": [], "default": null, "is_optional": null } ], "outlier_params": [], "others": [] }
import urllib import os def write_samples_toc(platform_dir, relative_path_to_samples, samples_in_categories): readme_text = "# Table of contents\n\n" for category in samples_in_categories.keys(): readme_text += f"## {category}\n\n" for sample in samples_in_categories[category]: entry_url = f"{relative_path_to_samples}/{sample.category}/{sample.formal_name}/readme.md" entry_url = urllib.parse.quote(entry_url) readme_text += f"* [{sample.friendly_name}]({entry_url}) - {sample.description}\n" readme_text += "\n" readme_path = os.path.join(platform_dir, "../..", "readme.md") with open(readme_path, 'w+') as file: file.write(readme_text)
108
548