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chaoss/grimoirelab-manuscripts | setup.py | files_in_subdir | def files_in_subdir(dir, subdir):
"""Find all files in a directory."""
paths = []
for (path, dirs, files) in os.walk(os.path.join(dir, subdir)):
for file in files:
paths.append(os.path.relpath(os.path.join(path, file), dir))
return paths | python | def files_in_subdir(dir, subdir):
"""Find all files in a directory."""
paths = []
for (path, dirs, files) in os.walk(os.path.join(dir, subdir)):
for file in files:
paths.append(os.path.relpath(os.path.join(path, file), dir))
return paths | [
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chaoss/grimoirelab-manuscripts | manuscripts2/metrics/git.py | overview | def overview(index, start, end):
"""Compute metrics in the overview section for enriched git indexes.
Returns a dictionary. Each key in the dictionary is the name of
a metric, the value is the value of that metric. Value can be
a complex object (eg, a time series).
:param index: index object
:... | python | def overview(index, start, end):
"""Compute metrics in the overview section for enriched git indexes.
Returns a dictionary. Each key in the dictionary is the name of
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chaoss/grimoirelab-manuscripts | manuscripts2/metrics/git.py | project_activity | def project_activity(index, start, end):
"""Compute the metrics for the project activity section of the enriched
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Returns a dictionary containing a "metric" key. This key contains the
metrics for this section.
:param index: index object
:param start: start date to get the data from
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"""Compute the metrics for the project activity section of the enriched
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Returns a dictionary containing a "metric" key. This key contains the
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:param index: index object
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chaoss/grimoirelab-manuscripts | manuscripts2/metrics/git.py | project_community | def project_community(index, start, end):
"""Compute the metrics for the project community section of the enriched
git index.
Returns a dictionary containing "author_metrics", "people_top_metrics"
and "orgs_top_metrics" as the keys and the related Metrics as the values.
:param index: index object
... | python | def project_community(index, start, end):
"""Compute the metrics for the project community section of the enriched
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Returns a dictionary containing "author_metrics", "people_top_metrics"
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chaoss/grimoirelab-manuscripts | manuscripts2/metrics/git.py | Authors.aggregations | def aggregations(self):
"""
Override parent method. Obtain list of the terms and their corresponding
values using "terms" aggregations for the previous time period.
:returns: a data frame containing terms and their corresponding values
"""
prev_month_start = get_prev_mo... | python | def aggregations(self):
"""
Override parent method. Obtain list of the terms and their corresponding
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:returns: a data frame containing terms and their corresponding values
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chaoss/grimoirelab-manuscripts | manuscripts2/metrics/github_issues.py | project_activity | def project_activity(index, start, end):
"""Compute the metrics for the project activity section of the enriched
github issues index.
Returns a dictionary containing a "metric" key. This key contains the
metrics for this section.
:param index: index object
:param start: start date to get the d... | python | def project_activity(index, start, end):
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Returns a dictionary containing a "metric" key. This key contains the
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chaoss/grimoirelab-manuscripts | manuscripts2/metrics/github_issues.py | BMI.aggregations | def aggregations(self):
"""Get the aggregation value for BMI with respect to the previous
time interval."""
prev_month_start = get_prev_month(self.end,
self.closed.query.interval_)
self.closed.query.since(prev_month_start,
... | python | def aggregations(self):
"""Get the aggregation value for BMI with respect to the previous
time interval."""
prev_month_start = get_prev_month(self.end,
self.closed.query.interval_)
self.closed.query.since(prev_month_start,
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openearth/bmi-python | bmi/wrapper.py | c_log | def c_log(level, message):
"""python logger to be called from fortran"""
c_level = level
level = LEVELS_F2PY[c_level]
logger.log(level, message) | python | def c_log(level, message):
"""python logger to be called from fortran"""
c_level = level
level = LEVELS_F2PY[c_level]
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openearth/bmi-python | bmi/wrapper.py | struct2dict | def struct2dict(struct):
"""convert a ctypes structure to a dictionary"""
return {x: getattr(struct, x) for x in dict(struct._fields_).keys()} | python | def struct2dict(struct):
"""convert a ctypes structure to a dictionary"""
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openearth/bmi-python | bmi/wrapper.py | structs2records | def structs2records(structs):
"""convert one or more structs and generate dictionaries"""
try:
n = len(structs)
except TypeError:
# no array
yield struct2dict(structs)
# just 1
return
for i in range(n):
struct = structs[i]
yield struct2dict(struct) | python | def structs2records(structs):
"""convert one or more structs and generate dictionaries"""
try:
n = len(structs)
except TypeError:
# no array
yield struct2dict(structs)
# just 1
return
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openearth/bmi-python | bmi/wrapper.py | structs2pandas | def structs2pandas(structs):
"""convert ctypes structure or structure array to pandas data frame"""
try:
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df = pandas.DataFrame.from_records(records)
# TODO: do this for string columns, for now just for id
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openearth/bmi-python | bmi/wrapper.py | wrap | def wrap(func):
"""Return wrapped function with type conversion and sanity checks.
"""
@functools.wraps(func, assigned=('restype', 'argtypes'))
def wrapped(*args):
if len(args) != len(func.argtypes):
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@functools.wraps(func, assigned=('restype', 'argtypes'))
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper._libname | def _libname(self):
"""Return platform-specific modelf90 shared library name."""
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suffix = '.so'
if platform.system() == 'Darwin':
suffix = '.dylib'
if platform.system() == 'Windows':
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suffix = '.dll'
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"""Return platform-specific modelf90 shared library name."""
prefix = 'lib'
suffix = '.so'
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suffix = '.dylib'
if platform.system() == 'Windows':
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper._library_path | def _library_path(self):
"""Return full path to the shared library.
A couple of regular unix paths like ``/usr/lib/`` is searched by
default. If your library is not in one of those, set a
``LD_LIBRARY_PATH`` environment variable to the directory with your
shared library.
... | python | def _library_path(self):
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper._load_library | def _load_library(self):
"""Return the fortran library, loaded with """
path = self._library_path()
logger.info("Loading library from path {}".format(path))
library_dir = os.path.dirname(path)
if platform.system() == 'Windows':
import win32api
olddir = os.... | python | def _load_library(self):
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path = self._library_path()
logger.info("Loading library from path {}".format(path))
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.finalize | def finalize(self):
"""Shutdown the library and clean up the model.
Note that the Fortran library's cleanup code is not up to snuff yet,
so the cleanup is not perfect. Note also that the working directory is
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"""Shutdown the library and clean up the model.
Note that the Fortran library's cleanup code is not up to snuff yet,
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_var_count | def get_var_count(self):
"""
Return number of variables
"""
n = c_int()
self.library.get_var_count.argtypes = [POINTER(c_int)]
self.library.get_var_count(byref(n))
return n.value | python | def get_var_count(self):
"""
Return number of variables
"""
n = c_int()
self.library.get_var_count.argtypes = [POINTER(c_int)]
self.library.get_var_count(byref(n))
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.inq_compound_field | def inq_compound_field(self, name, index):
"""
Lookup the type,rank and shape of a compound field
"""
typename = create_string_buffer(name)
index = c_int(index + 1)
fieldname = create_string_buffer(MAXSTRLEN)
fieldtype = create_string_buffer(MAXSTRLEN)
ran... | python | def inq_compound_field(self, name, index):
"""
Lookup the type,rank and shape of a compound field
"""
typename = create_string_buffer(name)
index = c_int(index + 1)
fieldname = create_string_buffer(MAXSTRLEN)
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.make_compound_ctype | def make_compound_ctype(self, varname):
"""
Create a ctypes type that corresponds to a compound type in memory.
"""
# look up the type name
compoundname = self.get_var_type(varname)
nfields = self.inq_compound(compoundname)
# for all the fields look up the type, ... | python | def make_compound_ctype(self, varname):
"""
Create a ctypes type that corresponds to a compound type in memory.
"""
# look up the type name
compoundname = self.get_var_type(varname)
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_var_rank | def get_var_rank(self, name):
"""
Return array rank or 0 for scalar.
"""
name = create_string_buffer(name)
rank = c_int()
self.library.get_var_rank.argtypes = [c_char_p, POINTER(c_int)]
self.library.get_var_rank.restype = None
self.library.get_var_rank(nam... | python | def get_var_rank(self, name):
"""
Return array rank or 0 for scalar.
"""
name = create_string_buffer(name)
rank = c_int()
self.library.get_var_rank.argtypes = [c_char_p, POINTER(c_int)]
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_var_shape | def get_var_shape(self, name):
"""
Return shape of the array.
"""
rank = self.get_var_rank(name)
name = create_string_buffer(name)
arraytype = ndpointer(dtype='int32',
ndim=1,
shape=(MAXDIMS, ),
... | python | def get_var_shape(self, name):
"""
Return shape of the array.
"""
rank = self.get_var_rank(name)
name = create_string_buffer(name)
arraytype = ndpointer(dtype='int32',
ndim=1,
shape=(MAXDIMS, ),
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_start_time | def get_start_time(self):
"""
returns start time
"""
start_time = c_double()
self.library.get_start_time.argtypes = [POINTER(c_double)]
self.library.get_start_time.restype = None
self.library.get_start_time(byref(start_time))
return start_time.value | python | def get_start_time(self):
"""
returns start time
"""
start_time = c_double()
self.library.get_start_time.argtypes = [POINTER(c_double)]
self.library.get_start_time.restype = None
self.library.get_start_time(byref(start_time))
return start_time.value | [
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_end_time | def get_end_time(self):
"""
returns end time of simulation
"""
end_time = c_double()
self.library.get_end_time.argtypes = [POINTER(c_double)]
self.library.get_end_time.restype = None
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return end_time.value | python | def get_end_time(self):
"""
returns end time of simulation
"""
end_time = c_double()
self.library.get_end_time.argtypes = [POINTER(c_double)]
self.library.get_end_time.restype = None
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_current_time | def get_current_time(self):
"""
returns current time of simulation
"""
current_time = c_double()
self.library.get_current_time.argtypes = [POINTER(c_double)]
self.library.get_current_time.restype = None
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re... | python | def get_current_time(self):
"""
returns current time of simulation
"""
current_time = c_double()
self.library.get_current_time.argtypes = [POINTER(c_double)]
self.library.get_current_time.restype = None
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_time_step | def get_time_step(self):
"""
returns current time step of simulation
"""
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return time_ste... | python | def get_time_step(self):
"""
returns current time step of simulation
"""
time_step = c_double()
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self.library.get_time_step.restype = None
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.get_var | def get_var(self, name):
"""Return an nd array from model library"""
# How many dimensions.
rank = self.get_var_rank(name)
# The shape array is fixed size
shape = np.empty((MAXDIMS, ), dtype='int32', order='F')
shape = self.get_var_shape(name)
# there should be no... | python | def get_var(self, name):
"""Return an nd array from model library"""
# How many dimensions.
rank = self.get_var_rank(name)
# The shape array is fixed size
shape = np.empty((MAXDIMS, ), dtype='int32', order='F')
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.set_logger | def set_logger(self, logger):
"""subscribe to fortran log messages"""
# we don't expect anything back
try:
self.library.set_logger.restype = None
except AttributeError:
logger.warn("Tried to set logger but method is not implemented in %s", self.engine)
... | python | def set_logger(self, logger):
"""subscribe to fortran log messages"""
# we don't expect anything back
try:
self.library.set_logger.restype = None
except AttributeError:
logger.warn("Tried to set logger but method is not implemented in %s", self.engine)
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openearth/bmi-python | bmi/wrapper.py | BMIWrapper.set_current_time | def set_current_time(self, current_time):
"""
sets current time of simulation
"""
current_time = c_double(current_time)
try:
self.library.set_current_time.argtypes = [POINTER(c_double)]
self.library.set_current_time.restype = None
self.library.... | python | def set_current_time(self, current_time):
"""
sets current time of simulation
"""
current_time = c_double(current_time)
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insomnia-lab/libreant | libreantdb/api.py | DB.setup_db | def setup_db(self, wait_for_ready=True):
''' Create and configure index
If `wait_for_ready` is True, this function will block until
status for `self.index_name` will be `yellow`
'''
if self.es.indices.exists(self.index_name):
try:
self.update... | python | def setup_db(self, wait_for_ready=True):
''' Create and configure index
If `wait_for_ready` is True, this function will block until
status for `self.index_name` will be `yellow`
'''
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insomnia-lab/libreant | libreantdb/api.py | DB.create_index | def create_index(self, indexname=None, index_conf=None):
''' Create the index
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''' Create the index
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insomnia-lab/libreant | libreantdb/api.py | DB.clone_index | def clone_index(self, new_indexname, index_conf=None):
'''Clone current index
All entries of the current index will be copied into the newly
created one named `new_indexname`
:param index_conf: Configuration to be used in the new index creation.
T... | python | def clone_index(self, new_indexname, index_conf=None):
'''Clone current index
All entries of the current index will be copied into the newly
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:param index_conf: Configuration to be used in the new index creation.
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insomnia-lab/libreant | libreantdb/api.py | DB.reindex | def reindex(self, new_index=None, index_conf=None):
'''Rebuilt the current index
This function could be useful in the case you want to change some index settings/mappings
and you don't want to loose all the entries belonging to that index.
This function is built in such a way ... | python | def reindex(self, new_index=None, index_conf=None):
'''Rebuilt the current index
This function could be useful in the case you want to change some index settings/mappings
and you don't want to loose all the entries belonging to that index.
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insomnia-lab/libreant | libreantdb/api.py | DB.mlt | def mlt(self, _id):
'''
High-level method to do "more like this".
Its exact implementation can vary.
'''
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'min_doc_freq'... | python | def mlt(self, _id):
'''
High-level method to do "more like this".
Its exact implementation can vary.
'''
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insomnia-lab/libreant | libreantdb/api.py | DB.file_is_attached | def file_is_attached(self, url):
'''return true if at least one book has
file with the given url as attachment
'''
body = self._get_search_field('_attachments.url', url)
return self.es.count(index=self.index_name, body=body)['count'] > 0 | python | def file_is_attached(self, url):
'''return true if at least one book has
file with the given url as attachment
'''
body = self._get_search_field('_attachments.url', url)
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insomnia-lab/libreant | libreantdb/api.py | DB.delete_all | def delete_all(self):
'''Delete all books from the index'''
def delete_action_gen():
scanner = scan(self.es,
index=self.index_name,
query={'query': {'match_all':{}}})
for v in scanner:
yield { '_op_type': 'dele... | python | def delete_all(self):
'''Delete all books from the index'''
def delete_action_gen():
scanner = scan(self.es,
index=self.index_name,
query={'query': {'match_all':{}}})
for v in scanner:
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insomnia-lab/libreant | libreantdb/api.py | DB.update_book | def update_book(self, id, body, doc_type='book'):
''' Update a book
The "body" is merged with the current one.
Yes, it is NOT overwritten.
In case of concurrency conflict
this function could raise `elasticsearch.ConflictError`
'''
# note that we ... | python | def update_book(self, id, body, doc_type='book'):
''' Update a book
The "body" is merged with the current one.
Yes, it is NOT overwritten.
In case of concurrency conflict
this function could raise `elasticsearch.ConflictError`
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insomnia-lab/libreant | libreantdb/api.py | DB.modify_book | def modify_book(self, id, body, doc_type='book', version=None):
''' replace the entire book body
Instead of `update_book` this function
will overwrite the book content with param body
If param `version` is given, it will be checked that the
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insomnia-lab/libreant | libreantdb/api.py | DB.increment_download_count | def increment_download_count(self, id, attachmentID, doc_type='book'):
'''
Increment the download counter of a specific file
'''
body = self.es.get(index=self.index_name, id=id, doc_type='book', _source_include='_attachments')['_source']
for attachment in body['_attachments']:
... | python | def increment_download_count(self, id, attachmentID, doc_type='book'):
'''
Increment the download counter of a specific file
'''
body = self.es.get(index=self.index_name, id=id, doc_type='book', _source_include='_attachments')['_source']
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chaoss/grimoirelab-manuscripts | manuscripts/config.py | Config.__add_types | def __add_types(self, raw_conf):
""" Convert to int, boolean, list, None types config items """
typed_conf = {}
for s in raw_conf.keys():
typed_conf[s] = {}
for option in raw_conf[s]:
val = raw_conf[s][option]
if len(val) > 1 and (val[0] ... | python | def __add_types(self, raw_conf):
""" Convert to int, boolean, list, None types config items """
typed_conf = {}
for s in raw_conf.keys():
typed_conf[s] = {}
for option in raw_conf[s]:
val = raw_conf[s][option]
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insomnia-lab/libreant | utils/es.py | Elasticsearch | def Elasticsearch(*args, **kwargs):
"""Elasticsearch wrapper function
Wrapper function around the official Elasticsearch class that adds
a simple version check upon initialization.
In particular it checks if the major version of the library in use
match the one of the cluster that we are tring to i... | python | def Elasticsearch(*args, **kwargs):
"""Elasticsearch wrapper function
Wrapper function around the official Elasticsearch class that adds
a simple version check upon initialization.
In particular it checks if the major version of the library in use
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insomnia-lab/libreant | conf/config_utils.py | from_envvars | def from_envvars(prefix=None, environ=None, envvars=None, as_json=True):
"""Load environment variables in a dictionary
Values are parsed as JSON. If parsing fails with a ValueError,
values are instead used as verbatim strings.
:param prefix: If ``None`` is passed as envvars, all variables from
... | python | def from_envvars(prefix=None, environ=None, envvars=None, as_json=True):
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Values are parsed as JSON. If parsing fails with a ValueError,
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | calculate_bmi | def calculate_bmi(closed, submitted):
"""
BMI is the ratio of the number of closed items to the number of total items
submitted in a particular period of analysis. The items can be issues, pull
requests and such
:param closed: dataframe returned from get_timeseries() containing closed items
:pa... | python | def calculate_bmi(closed, submitted):
"""
BMI is the ratio of the number of closed items to the number of total items
submitted in a particular period of analysis. The items can be issues, pull
requests and such
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.add_query | def add_query(self, key_val={}):
"""
Add an es_dsl query object to the es_dsl Search object
:param key_val: a key-value pair(dict) containing the query to be added to the search object
:returns: self, which allows the method to be chainable with the other methods
"""
q ... | python | def add_query(self, key_val={}):
"""
Add an es_dsl query object to the es_dsl Search object
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:returns: self, which allows the method to be chainable with the other methods
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.add_inverse_query | def add_inverse_query(self, key_val={}):
"""
Add an es_dsl inverse query object to the es_dsl Search object
:param key_val: a key-value pair(dict) containing the query to be added to the search object
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"""
Add an es_dsl inverse query object to the es_dsl Search object
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_sum | def get_sum(self, field=None):
"""
Create a sum aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:returns: self, which allows the method to be chainable with the other methods
"""
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... | python | def get_sum(self, field=None):
"""
Create a sum aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_average | def get_average(self, field=None):
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Create an avg aggregation object and add it to the aggregation dict
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:returns: self, which allows the method to be chainable with the other methods
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Create an avg aggregation object and add it to the aggregation dict
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_percentiles | def get_percentiles(self, field=None, percents=None):
"""
Create a percentile aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:param percents: the specific percentiles to be calculated
d... | python | def get_percentiles(self, field=None, percents=None):
"""
Create a percentile aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:param percents: the specific percentiles to be calculated
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_terms | def get_terms(self, field=None):
"""
Create a terms aggregation object and add it to the aggregation dict
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:returns: self, which allows the method to be chainable with the other methods
"""
if not fiel... | python | def get_terms(self, field=None):
"""
Create a terms aggregation object and add it to the aggregation dict
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_min | def get_min(self, field=None):
"""
Create a min aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:returns: self, which allows the method to be chainable with the other methods
"""
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"""
Create a min aggregation object and add it to the aggregation dict
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_max | def get_max(self, field=None):
"""
Create a max aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:returns: self, which allows the method to be chainable with the other methods
"""
if not field:
... | python | def get_max(self, field=None):
"""
Create a max aggregation object and add it to the aggregation dict
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:returns: self, which allows the method to be chainable with the other methods
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_cardinality | def get_cardinality(self, field=None):
"""
Create a cardinality aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:returns: self, which allows the method to be chainable with the other methods
"""
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"""
Create a cardinality aggregation object and add it to the aggregation dict
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:returns: self, which allows the method to be chainable with the other methods
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_extended_stats | def get_extended_stats(self, field=None):
"""
Create an extended_stats aggregation object and add it to the aggregation dict
:param field: the field present in the index that is to be aggregated
:returns: self, which allows the method to be chainable with the other methods
"""
... | python | def get_extended_stats(self, field=None):
"""
Create an extended_stats aggregation object and add it to the aggregation dict
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:returns: self, which allows the method to be chainable with the other methods
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.add_custom_aggregation | def add_custom_aggregation(self, agg, name=None):
"""
Takes in an es_dsl Aggregation object and adds it to the aggregation dict.
Can be used to add custom aggregations such as moving averages
:param agg: aggregation to be added to the es_dsl search object
:param name: name of th... | python | def add_custom_aggregation(self, agg, name=None):
"""
Takes in an es_dsl Aggregation object and adds it to the aggregation dict.
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.since | def since(self, start, field=None):
"""
Add the start date to query data starting from that date
sets the default start date for each query
:param start: date to start looking at the fields (from date)
:param field: specific field for the start date in range filter
... | python | def since(self, start, field=None):
"""
Add the start date to query data starting from that date
sets the default start date for each query
:param start: date to start looking at the fields (from date)
:param field: specific field for the start date in range filter
... | [
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.until | def until(self, end, field=None):
"""
Add the end date to query data upto that date
sets the default end date for each query
:param end: date to stop looking at the fields (to date)
:param field: specific field for the end date in range filter
for the Searc... | python | def until(self, end, field=None):
"""
Add the end date to query data upto that date
sets the default end date for each query
:param end: date to stop looking at the fields (to date)
:param field: specific field for the end date in range filter
for the Searc... | [
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.by_organizations | def by_organizations(self, field=None):
"""
Used to seggregate the data acording to organizations. This method
pops the latest aggregation from the self.aggregations dict and
adds it as a nested aggregation under itself
:param field: the field to create the parent agg (optional)... | python | def by_organizations(self, field=None):
"""
Used to seggregate the data acording to organizations. This method
pops the latest aggregation from the self.aggregations dict and
adds it as a nested aggregation under itself
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.by_period | def by_period(self, field=None, period=None, timezone=None, start=None, end=None):
"""
Create a date histogram aggregation using the last added aggregation for the
current object. Add this date_histogram aggregation into self.aggregations
:param field: the index field to create the hist... | python | def by_period(self, field=None, period=None, timezone=None, start=None, end=None):
"""
Create a date histogram aggregation using the last added aggregation for the
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_bounds | def get_bounds(self, start=None, end=None):
"""
Get bounds for the date_histogram method
:param start: start date to set the extended_bounds min field
:param end: end date to set the extended_bounds max field
:returns bounds: a dictionary containing the min and max fields
... | python | def get_bounds(self, start=None, end=None):
"""
Get bounds for the date_histogram method
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.reset_aggregations | def reset_aggregations(self):
"""
Remove all aggregations added to the search object
"""
temp_search = self.search.to_dict()
if 'aggs' in temp_search.keys():
del temp_search['aggs']
self.search.from_dict(temp_search)
self.parent_agg_counter = 0
... | python | def reset_aggregations(self):
"""
Remove all aggregations added to the search object
"""
temp_search = self.search.to_dict()
if 'aggs' in temp_search.keys():
del temp_search['aggs']
self.search.from_dict(temp_search)
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.fetch_aggregation_results | def fetch_aggregation_results(self):
"""
Loops though the self.aggregations dict and adds them to the Search object
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:returns: a dictionary containing the response from elasticsea... | python | def fetch_aggregation_results(self):
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.fetch_results_from_source | def fetch_results_from_source(self, *fields, dataframe=False):
"""
Get values for specific fields in the elasticsearch index, from source
:param fields: a list of fields that have to be retrieved from the index
:param dataframe: if true, will return the data in the form of a pandas.Data... | python | def fetch_results_from_source(self, *fields, dataframe=False):
"""
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_timeseries | def get_timeseries(self, child_agg_count=0, dataframe=False):
"""
Get time series data for the specified fields and period of analysis
:param child_agg_count: the child aggregation count to be used
default = 0
:param dataframe: if dataframe=True, return a... | python | def get_timeseries(self, child_agg_count=0, dataframe=False):
"""
Get time series data for the specified fields and period of analysis
:param child_agg_count: the child aggregation count to be used
default = 0
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_aggs | def get_aggs(self):
"""
Compute the values for single valued aggregations
:returns: the single aggregation value
"""
res = self.fetch_aggregation_results()
if 'aggregations' in res and 'values' in res['aggregations'][str(self.parent_agg_counter - 1)]:
try:
... | python | def get_aggs(self):
"""
Compute the values for single valued aggregations
:returns: the single aggregation value
"""
res = self.fetch_aggregation_results()
if 'aggregations' in res and 'values' in res['aggregations'][str(self.parent_agg_counter - 1)]:
try:
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chaoss/grimoirelab-manuscripts | manuscripts2/elasticsearch.py | Query.get_list | def get_list(self, dataframe=False):
"""
Compute the value for multi-valued aggregations
:returns: a dict containing 'keys' and their corresponding 'values'
"""
res = self.fetch_aggregation_results()
keys = []
values = []
for bucket in res['aggregations'... | python | def get_list(self, dataframe=False):
"""
Compute the value for multi-valued aggregations
:returns: a dict containing 'keys' and their corresponding 'values'
"""
res = self.fetch_aggregation_results()
keys = []
values = []
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insomnia-lab/libreant | cli/libreant_db.py | upgrade | def upgrade(check_only, yes):
'''
Upgrade libreant database.
This command can be used after an update of libreant
in order to upgrade the database and make it aligned with the new version.
'''
from utils.es import Elasticsearch
from libreantdb import DB, migration
from libreantdb.except... | python | def upgrade(check_only, yes):
'''
Upgrade libreant database.
This command can be used after an update of libreant
in order to upgrade the database and make it aligned with the new version.
'''
from utils.es import Elasticsearch
from libreantdb import DB, migration
from libreantdb.except... | [
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insomnia-lab/libreant | cli/libreant_db.py | insert_volume | def insert_volume(language, filepath, notes, metadata):
'''
Add a new volume to libreant.
The metadata of the volume are taken from a json file whose path must be
passed as argument. Passing "-" as argument will read the file from stdin.
language is an exception, because it must be set using --lang... | python | def insert_volume(language, filepath, notes, metadata):
'''
Add a new volume to libreant.
The metadata of the volume are taken from a json file whose path must be
passed as argument. Passing "-" as argument will read the file from stdin.
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insomnia-lab/libreant | cli/libreant_db.py | attach_list | def attach_list(filepaths, notes):
'''
all the arguments are lists
returns a list of dictionaries; each dictionary "represent" an attachment
'''
assert type(filepaths) in (list, tuple)
assert type(notes) in (list, tuple)
# this if clause means "if those lists are not of the same length"
... | python | def attach_list(filepaths, notes):
'''
all the arguments are lists
returns a list of dictionaries; each dictionary "represent" an attachment
'''
assert type(filepaths) in (list, tuple)
assert type(notes) in (list, tuple)
# this if clause means "if those lists are not of the same length"
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pricingassistant/mongokat | mongokat/collection.py | _param_fields | def _param_fields(kwargs, fields):
"""
Normalize the "fields" argument to most find methods
"""
if fields is None:
return
if type(fields) in [list, set, frozenset, tuple]:
fields = {x: True for x in fields}
if type(fields) == dict:
fields.setdefault("_id", False)
kwargs["projection"] = field... | python | def _param_fields(kwargs, fields):
"""
Normalize the "fields" argument to most find methods
"""
if fields is None:
return
if type(fields) in [list, set, frozenset, tuple]:
fields = {x: True for x in fields}
if type(fields) == dict:
fields.setdefault("_id", False)
kwargs["projection"] = field... | [
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pricingassistant/mongokat | mongokat/collection.py | patch_cursor | def patch_cursor(cursor, batch_size=None, limit=None, skip=None, sort=None, **kwargs):
"""
Adds batch_size, limit, sort parameters to a DB cursor
"""
if type(batch_size) == int:
cursor.batch_size(batch_size)
if limit is not None:
cursor.limit(limit)
if sort is not None:
cursor.sort(sort)
... | python | def patch_cursor(cursor, batch_size=None, limit=None, skip=None, sort=None, **kwargs):
"""
Adds batch_size, limit, sort parameters to a DB cursor
"""
if type(batch_size) == int:
cursor.batch_size(batch_size)
if limit is not None:
cursor.limit(limit)
if sort is not None:
cursor.sort(sort)
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pricingassistant/mongokat | mongokat/collection.py | Collection.exists | def exists(self, query, **args):
"""
Returns True if the search matches at least one document
"""
return bool(self.find(query, **args).limit(1).count()) | python | def exists(self, query, **args):
"""
Returns True if the search matches at least one document
"""
return bool(self.find(query, **args).limit(1).count()) | [
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pricingassistant/mongokat | mongokat/collection.py | Collection._collection_with_options | def _collection_with_options(self, kwargs):
""" Returns a copy of the pymongo collection with various options set up """
# class DocumentClassWithFields(self.document_class):
# _fetched_fields = kwargs.get("projection")
# mongokat_collection = self
read_preference = kwa... | python | def _collection_with_options(self, kwargs):
""" Returns a copy of the pymongo collection with various options set up """
# class DocumentClassWithFields(self.document_class):
# _fetched_fields = kwargs.get("projection")
# mongokat_collection = self
read_preference = kwa... | [
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pricingassistant/mongokat | mongokat/collection.py | Collection.find_by_b64id | def find_by_b64id(self, _id, **kwargs):
"""
Pass me a base64-encoded ObjectId
"""
return self.find_one({"_id": ObjectId(base64.b64decode(_id))}, **kwargs) | python | def find_by_b64id(self, _id, **kwargs):
"""
Pass me a base64-encoded ObjectId
"""
return self.find_one({"_id": ObjectId(base64.b64decode(_id))}, **kwargs) | [
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pricingassistant/mongokat | mongokat/collection.py | Collection.find_by_b64ids | def find_by_b64ids(self, _ids, **kwargs):
"""
Pass me a list of base64-encoded ObjectId
"""
return self.find_by_ids([ObjectId(base64.b64decode(_id)) for _id in _ids], **kwargs) | python | def find_by_b64ids(self, _ids, **kwargs):
"""
Pass me a list of base64-encoded ObjectId
"""
return self.find_by_ids([ObjectId(base64.b64decode(_id)) for _id in _ids], **kwargs) | [
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pricingassistant/mongokat | mongokat/collection.py | Collection.iter_column | def iter_column(self, query=None, field="_id", **kwargs):
"""
Return one field as an iterator.
Beware that if your query returns records where the field is not set, it will raise a KeyError.
"""
find_kwargs = {
"projection": {"_id": False}
}
fi... | python | def iter_column(self, query=None, field="_id", **kwargs):
"""
Return one field as an iterator.
Beware that if your query returns records where the field is not set, it will raise a KeyError.
"""
find_kwargs = {
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pricingassistant/mongokat | mongokat/collection.py | Collection.find_random | def find_random(self, **kwargs):
"""
return one random document from the collection
"""
import random
max = self.count(**kwargs)
if max:
num = random.randint(0, max - 1)
return next(self.find(**kwargs).skip(num)) | python | def find_random(self, **kwargs):
"""
return one random document from the collection
"""
import random
max = self.count(**kwargs)
if max:
num = random.randint(0, max - 1)
return next(self.find(**kwargs).skip(num)) | [
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pricingassistant/mongokat | mongokat/collection.py | Collection.insert | def insert(self, data, return_object=False):
""" Inserts the data as a new document. """
obj = self(data) # pylint: disable=E1102
obj.save()
if return_object:
return obj
else:
return obj["_id"] | python | def insert(self, data, return_object=False):
""" Inserts the data as a new document. """
obj = self(data) # pylint: disable=E1102
obj.save()
if return_object:
return obj
else:
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pricingassistant/mongokat | mongokat/collection.py | Collection.trigger | def trigger(self, event, filter=None, update=None, documents=None, ids=None, replacements=None):
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""" Trigger the after_save hook on documents, if present. """
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insomnia-lab/libreant | msgfmt.py | usage | def usage(ecode, msg=''):
"""
Print usage and msg and exit with given code.
"""
print >> sys.stderr, __doc__
if msg:
print >> sys.stderr, msg
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"""
Print usage and msg and exit with given code.
"""
print >> sys.stderr, __doc__
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insomnia-lab/libreant | msgfmt.py | add | def add(msgid, transtr, fuzzy):
"""
Add a non-fuzzy translation to the dictionary.
"""
global MESSAGES
if not fuzzy and transtr and not transtr.startswith('\0'):
MESSAGES[msgid] = transtr | python | def add(msgid, transtr, fuzzy):
"""
Add a non-fuzzy translation to the dictionary.
"""
global MESSAGES
if not fuzzy and transtr and not transtr.startswith('\0'):
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insomnia-lab/libreant | msgfmt.py | generate | def generate():
"""
Return the generated output.
"""
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keys = MESSAGES.keys()
# the keys are sorted in the .mo file
keys.sort()
offsets = []
ids = strs = ''
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# For each string, we need size and file offset. Each string is NUL
# termi... | python | def generate():
"""
Return the generated output.
"""
global MESSAGES
keys = MESSAGES.keys()
# the keys are sorted in the .mo file
keys.sort()
offsets = []
ids = strs = ''
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insomnia-lab/libreant | setup.py | get_es_requirements | def get_es_requirements(es_version):
'''Get the requirements string for elasticsearch-py library
Returns a suitable requirements string for the elsaticsearch-py library
according to the elasticsearch version to be supported (es_version)'''
# accepts version range in the form `2.x`
es_version = es_... | python | def get_es_requirements(es_version):
'''Get the requirements string for elasticsearch-py library
Returns a suitable requirements string for the elsaticsearch-py library
according to the elasticsearch version to be supported (es_version)'''
# accepts version range in the form `2.x`
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insomnia-lab/libreant | setup.py | compile_translations.run | def run(self):
"""
Compile all message catalogs .po files into .mo files.
Skips not changed file based on source mtime.
"""
# thanks to deluge guys ;)
po_dir = os.path.join(os.path.dirname(__file__), 'webant', 'translations')
print('Compiling po files from "... | python | def run(self):
"""
Compile all message catalogs .po files into .mo files.
Skips not changed file based on source mtime.
"""
# thanks to deluge guys ;)
po_dir = os.path.join(os.path.dirname(__file__), 'webant', 'translations')
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argaen/python-google-distance-matrix | google_distance_matrix/core.py | DM.__get_response_element_data | def __get_response_element_data(self, key1, key2):
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For each origin an elements object is created in the ouput.
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For each origin an elements object is created in the ouput.
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argaen/python-google-distance-matrix | google_distance_matrix/core.py | DM.get_closest_points | def get_closest_points(self, max_distance=None, origin_index=0, origin_raw=None):
"""
Get closest points to a given origin. Returns a list of 2 element tuples where first element is the destination and the second is the distance.
"""
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... | python | def get_closest_points(self, max_distance=None, origin_index=0, origin_raw=None):
"""
Get closest points to a given origin. Returns a list of 2 element tuples where first element is the destination and the second is the distance.
"""
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snowblink14/smatch | amr.py | AMR.rename_node | def rename_node(self, prefix):
"""
Rename AMR graph nodes to prefix + node_index to avoid nodes with the same name in two different AMRs.
"""
node_map_dict = {}
# map each node to its new name (e.g. "a1")
for i in range(0, len(self.nodes)):
node_map_dict[self... | python | def rename_node(self, prefix):
"""
Rename AMR graph nodes to prefix + node_index to avoid nodes with the same name in two different AMRs.
"""
node_map_dict = {}
# map each node to its new name (e.g. "a1")
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chaoss/grimoirelab-manuscripts | manuscripts/report.py | Report.bar3_chart | def bar3_chart(self, title, labels, data1, file_name, data2, data3, legend=["", ""]):
"""
Generate a bar plot with three columns in each x position and save it to file_name
:param title: title to be used in the chart
:param labels: list of labels for the x axis
:param data1: val... | python | def bar3_chart(self, title, labels, data1, file_name, data2, data3, legend=["", ""]):
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Generate a bar plot with three columns in each x position and save it to file_name
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chaoss/grimoirelab-manuscripts | manuscripts/report.py | Report.sections | def sections(self):
"""
Get the sections of the report and howto build them.
:return: a dict with the method to be called to fill each section of the report
"""
secs = OrderedDict()
secs['Overview'] = self.sec_overview
secs['Communication Channels'] = self.sec_co... | python | def sections(self):
"""
Get the sections of the report and howto build them.
:return: a dict with the method to be called to fill each section of the report
"""
secs = OrderedDict()
secs['Overview'] = self.sec_overview
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chaoss/grimoirelab-manuscripts | manuscripts/report.py | Report.replace_text | def replace_text(filepath, to_replace, replacement):
"""
Replaces a string in a given file with another string
:param file: the file in which the string has to be replaced
:param to_replace: the string to be replaced in the file
:param replacement: the string which replaces 'to_... | python | def replace_text(filepath, to_replace, replacement):
"""
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chaoss/grimoirelab-manuscripts | manuscripts/report.py | Report.replace_text_dir | def replace_text_dir(self, directory, to_replace, replacement, file_type=None):
"""
Replaces a string with its replacement in all the files in the directory
:param directory: the directory in which the files have to be modified
:param to_replace: the string to be replaced in the files
... | python | def replace_text_dir(self, directory, to_replace, replacement, file_type=None):
"""
Replaces a string with its replacement in all the files in the directory
:param directory: the directory in which the files have to be modified
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snowblink14/smatch | smatch-table.py | pprint_table | def pprint_table(table):
"""
Print a table in pretty format
"""
col_paddings = []
for i in range(len(table[0])):
col_paddings.append(get_max_width(table,i))
for row in table:
print(row[0].ljust(col_paddings[0] + 1), end="")
for i in range(1, len(row)):
col = ... | python | def pprint_table(table):
"""
Print a table in pretty format
"""
col_paddings = []
for i in range(len(table[0])):
col_paddings.append(get_max_width(table,i))
for row in table:
print(row[0].ljust(col_paddings[0] + 1), end="")
for i in range(1, len(row)):
col = ... | [
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snowblink14/smatch | smatch-table.py | cb | def cb(option, value, parser):
"""
Callback function to handle variable number of arguments in optparse
"""
arguments = [value]
for arg in parser.rargs:
if arg[0] != "-":
arguments.append(arg)
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break
if g... | python | def cb(option, value, parser):
"""
Callback function to handle variable number of arguments in optparse
"""
arguments = [value]
for arg in parser.rargs:
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break
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snowblink14/smatch | smatch-table.py | check_args | def check_args(args):
"""
Parse arguments and check if the arguments are valid
"""
if not os.path.exists(args.fd):
print("Not a valid path", args.fd, file=ERROR_LOG)
return [], [], False
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# we already ensure the file can be opened and opened the file
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"""
Parse arguments and check if the arguments are valid
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if not os.path.exists(args.fd):
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return [], [], False
if args.fl is not None:
# we already ensure the file can be opened and opened the file
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chaoss/grimoirelab-manuscripts | manuscripts2/report.py | create_csv | def create_csv(filename, csv_data, mode="w"):
"""
Create a CSV file with the given data and store it in the
file with the given name.
:param filename: name of the file to store the data in
:pram csv_data: the data to be stored in the file
:param mode: the mode in which we have to open the file.... | python | def create_csv(filename, csv_data, mode="w"):
"""
Create a CSV file with the given data and store it in the
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chaoss/grimoirelab-manuscripts | manuscripts2/report.py | Report.get_metric_index | def get_metric_index(self, data_source):
"""
This function will return the elasticsearch index for a corresponding
data source. It chooses in between the default and the user inputed
es indices and returns the user inputed one if it is available.
:param data_source: the data sou... | python | def get_metric_index(self, data_source):
"""
This function will return the elasticsearch index for a corresponding
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chaoss/grimoirelab-manuscripts | manuscripts2/report.py | Report.get_sec_overview | def get_sec_overview(self):
"""
Generate the "overview" section of the report.
"""
logger.debug("Calculating Overview metrics.")
data_path = os.path.join(self.data_dir, "overview")
if not os.path.exists(data_path):
os.makedirs(data_path)
overview_co... | python | def get_sec_overview(self):
"""
Generate the "overview" section of the report.
"""
logger.debug("Calculating Overview metrics.")
data_path = os.path.join(self.data_dir, "overview")
if not os.path.exists(data_path):
os.makedirs(data_path)
overview_co... | [
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] | 94a3ad4f11bfbcd6c5190e01cb5d3e47a5187cd9 | https://github.com/chaoss/grimoirelab-manuscripts/blob/94a3ad4f11bfbcd6c5190e01cb5d3e47a5187cd9/manuscripts2/report.py#L150-L239 | train | 64,594 |
chaoss/grimoirelab-manuscripts | manuscripts2/report.py | Report.get_sec_project_activity | def get_sec_project_activity(self):
"""
Generate the "project activity" section of the report.
"""
logger.debug("Calculating Project Activity metrics.")
data_path = os.path.join(self.data_dir, "activity")
if not os.path.exists(data_path):
os.makedirs(data_pa... | python | def get_sec_project_activity(self):
"""
Generate the "project activity" section of the report.
"""
logger.debug("Calculating Project Activity metrics.")
data_path = os.path.join(self.data_dir, "activity")
if not os.path.exists(data_path):
os.makedirs(data_pa... | [
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chaoss/grimoirelab-manuscripts | manuscripts2/report.py | Report.get_sec_project_community | def get_sec_project_community(self):
"""
Generate the "project community" section of the report.
"""
logger.debug("Calculating Project Community metrics.")
data_path = os.path.join(self.data_dir, "community")
if not os.path.exists(data_path):
os.makedirs(dat... | python | def get_sec_project_community(self):
"""
Generate the "project community" section of the report.
"""
logger.debug("Calculating Project Community metrics.")
data_path = os.path.join(self.data_dir, "community")
if not os.path.exists(data_path):
os.makedirs(dat... | [
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] | 94a3ad4f11bfbcd6c5190e01cb5d3e47a5187cd9 | https://github.com/chaoss/grimoirelab-manuscripts/blob/94a3ad4f11bfbcd6c5190e01cb5d3e47a5187cd9/manuscripts2/report.py#L273-L324 | train | 64,596 |
chaoss/grimoirelab-manuscripts | manuscripts2/report.py | Report.create_csv_fig_from_df | def create_csv_fig_from_df(self, data_frames=[], filename=None, headers=[], index_label=None,
fig_type=None, title=None, xlabel=None, ylabel=None, xfont=10,
yfont=10, titlefont=15, fig_size=(8, 10), image_type="eps"):
"""
Joins all the datafa... | python | def create_csv_fig_from_df(self, data_frames=[], filename=None, headers=[], index_label=None,
fig_type=None, title=None, xlabel=None, ylabel=None, xfont=10,
yfont=10, titlefont=15, fig_size=(8, 10), image_type="eps"):
"""
Joins all the datafa... | [
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insomnia-lab/libreant | users/__init__.py | create_tables | def create_tables(database):
'''Create all tables in the given database'''
logging.getLogger(__name__).debug("Creating missing database tables")
database.connect()
database.create_tables([User,
Group,
UserToGroup,
GroupT... | python | def create_tables(database):
'''Create all tables in the given database'''
logging.getLogger(__name__).debug("Creating missing database tables")
database.connect()
database.create_tables([User,
Group,
UserToGroup,
GroupT... | [
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] | 55d529435baf4c05a86b8341899e9f5e14e50245 | https://github.com/insomnia-lab/libreant/blob/55d529435baf4c05a86b8341899e9f5e14e50245/users/__init__.py#L72-L80 | train | 64,598 |
insomnia-lab/libreant | users/__init__.py | populate_with_defaults | def populate_with_defaults():
'''Create user admin and grant him all permission
If the admin user already exists the function will simply return
'''
logging.getLogger(__name__).debug("Populating with default users")
if not User.select().where(User.name == 'admin').exists():
admin = User.cre... | python | def populate_with_defaults():
'''Create user admin and grant him all permission
If the admin user already exists the function will simply return
'''
logging.getLogger(__name__).debug("Populating with default users")
if not User.select().where(User.name == 'admin').exists():
admin = User.cre... | [
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