partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
train | oauth_token_exchange_cli | Command line function for obtaining the refresh token/code.
For more information visit
:func:`oauth2_token_exchange<ohapi.api.oauth2_token_exchange>`. | ohapi/command_line.py | def oauth_token_exchange_cli(client_id, client_secret, redirect_uri,
base_url=OH_BASE_URL, code=None,
refresh_token=None):
"""
Command line function for obtaining the refresh token/code.
For more information visit
:func:`oauth2_token_exchange<oha... | def oauth_token_exchange_cli(client_id, client_secret, redirect_uri,
base_url=OH_BASE_URL, code=None,
refresh_token=None):
"""
Command line function for obtaining the refresh token/code.
For more information visit
:func:`oauth2_token_exchange<oha... | [
"Command",
"line",
"function",
"for",
"obtaining",
"the",
"refresh",
"token",
"/",
"code",
".",
"For",
"more",
"information",
"visit",
":",
"func",
":",
"oauth2_token_exchange<ohapi",
".",
"api",
".",
"oauth2_token_exchange",
">",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/command_line.py#L427-L436 | [
"def",
"oauth_token_exchange_cli",
"(",
"client_id",
",",
"client_secret",
",",
"redirect_uri",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"code",
"=",
"None",
",",
"refresh_token",
"=",
"None",
")",
":",
"print",
"(",
"oauth2_token_exchange",
"(",
"client_id",
"... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | oauth2_auth_url_cli | Command line function for obtaining the Oauth2 url.
For more information visit
:func:`oauth2_auth_url<ohapi.api.oauth2_auth_url>`. | ohapi/command_line.py | def oauth2_auth_url_cli(redirect_uri=None, client_id=None,
base_url=OH_BASE_URL):
"""
Command line function for obtaining the Oauth2 url.
For more information visit
:func:`oauth2_auth_url<ohapi.api.oauth2_auth_url>`.
"""
result = oauth2_auth_url(redirect_uri, client_id, b... | def oauth2_auth_url_cli(redirect_uri=None, client_id=None,
base_url=OH_BASE_URL):
"""
Command line function for obtaining the Oauth2 url.
For more information visit
:func:`oauth2_auth_url<ohapi.api.oauth2_auth_url>`.
"""
result = oauth2_auth_url(redirect_uri, client_id, b... | [
"Command",
"line",
"function",
"for",
"obtaining",
"the",
"Oauth2",
"url",
".",
"For",
"more",
"information",
"visit",
":",
"func",
":",
"oauth2_auth_url<ohapi",
".",
"api",
".",
"oauth2_auth_url",
">",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/command_line.py#L444-L453 | [
"def",
"oauth2_auth_url_cli",
"(",
"redirect_uri",
"=",
"None",
",",
"client_id",
"=",
"None",
",",
"base_url",
"=",
"OH_BASE_URL",
")",
":",
"result",
"=",
"oauth2_auth_url",
"(",
"redirect_uri",
",",
"client_id",
",",
"base_url",
")",
"print",
"(",
"'The req... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | message_cli | Command line function for sending email to a single user or in bulk.
For more information visit
:func:`message<ohapi.api.message>`. | ohapi/command_line.py | def message_cli(subject, message_body, access_token, all_members=False,
project_member_ids=None, base_url=OH_BASE_URL,
verbose=False, debug=False):
"""
Command line function for sending email to a single user or in bulk.
For more information visit
:func:`message<ohapi.api... | def message_cli(subject, message_body, access_token, all_members=False,
project_member_ids=None, base_url=OH_BASE_URL,
verbose=False, debug=False):
"""
Command line function for sending email to a single user or in bulk.
For more information visit
:func:`message<ohapi.api... | [
"Command",
"line",
"function",
"for",
"sending",
"email",
"to",
"a",
"single",
"user",
"or",
"in",
"bulk",
".",
"For",
"more",
"information",
"visit",
":",
"func",
":",
"message<ohapi",
".",
"api",
".",
"message",
">",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/command_line.py#L468-L480 | [
"def",
"message_cli",
"(",
"subject",
",",
"message_body",
",",
"access_token",
",",
"all_members",
"=",
"False",
",",
"project_member_ids",
"=",
"None",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"verbose",
"=",
"False",
",",
"debug",
"=",
"False",
")",
":",... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | delete_cli | Command line function for deleting files.
For more information visit
:func:`delete_file<ohapi.api.delete_file>`. | ohapi/command_line.py | def delete_cli(access_token, project_member_id, base_url=OH_BASE_URL,
file_basename=None, file_id=None, all_files=False):
"""
Command line function for deleting files.
For more information visit
:func:`delete_file<ohapi.api.delete_file>`.
"""
response = delete_file(access_token, p... | def delete_cli(access_token, project_member_id, base_url=OH_BASE_URL,
file_basename=None, file_id=None, all_files=False):
"""
Command line function for deleting files.
For more information visit
:func:`delete_file<ohapi.api.delete_file>`.
"""
response = delete_file(access_token, p... | [
"Command",
"line",
"function",
"for",
"deleting",
"files",
".",
"For",
"more",
"information",
"visit",
":",
"func",
":",
"delete_file<ohapi",
".",
"api",
".",
"delete_file",
">",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/command_line.py#L491-L503 | [
"def",
"delete_cli",
"(",
"access_token",
",",
"project_member_id",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"file_basename",
"=",
"None",
",",
"file_id",
"=",
"None",
",",
"all_files",
"=",
"False",
")",
":",
"response",
"=",
"delete_file",
"(",
"access_toke... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | public_data_download_cli | Command line tools for downloading public data. | ohapi/command_line.py | def public_data_download_cli(source, username, directory, max_size, quiet,
debug):
"""
Command line tools for downloading public data.
"""
return public_download(source, username, directory, max_size, quiet, debug) | def public_data_download_cli(source, username, directory, max_size, quiet,
debug):
"""
Command line tools for downloading public data.
"""
return public_download(source, username, directory, max_size, quiet, debug) | [
"Command",
"line",
"tools",
"for",
"downloading",
"public",
"data",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/command_line.py#L517-L522 | [
"def",
"public_data_download_cli",
"(",
"source",
",",
"username",
",",
"directory",
",",
"max_size",
",",
"quiet",
",",
"debug",
")",
":",
"return",
"public_download",
"(",
"source",
",",
"username",
",",
"directory",
",",
"max_size",
",",
"quiet",
",",
"de... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | download_url | Download a file.
:param result: This field contains a url from which data will be
downloaded.
:param directory: This field is the target directory to which data will be
downloaded.
:param max_bytes: This field is the maximum file size in bytes. | ohapi/public.py | def download_url(result, directory, max_bytes):
"""
Download a file.
:param result: This field contains a url from which data will be
downloaded.
:param directory: This field is the target directory to which data will be
downloaded.
:param max_bytes: This field is the maximum file s... | def download_url(result, directory, max_bytes):
"""
Download a file.
:param result: This field contains a url from which data will be
downloaded.
:param directory: This field is the target directory to which data will be
downloaded.
:param max_bytes: This field is the maximum file s... | [
"Download",
"a",
"file",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/public.py#L37-L99 | [
"def",
"download_url",
"(",
"result",
",",
"directory",
",",
"max_bytes",
")",
":",
"response",
"=",
"requests",
".",
"get",
"(",
"result",
"[",
"'download_url'",
"]",
",",
"stream",
"=",
"True",
")",
"# TODO: make this more robust by parsing the URL",
"filename",... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | download | Download public data from Open Humans.
:param source: This field is the data source from which to download. It's
default value is None.
:param username: This fiels is username of user. It's default value is
None.
:param directory: This field is the target directory to which data is
... | ohapi/public.py | def download(source=None, username=None, directory='.', max_size='128m',
quiet=None, debug=None):
"""
Download public data from Open Humans.
:param source: This field is the data source from which to download. It's
default value is None.
:param username: This fiels is username of u... | def download(source=None, username=None, directory='.', max_size='128m',
quiet=None, debug=None):
"""
Download public data from Open Humans.
:param source: This field is the data source from which to download. It's
default value is None.
:param username: This fiels is username of u... | [
"Download",
"public",
"data",
"from",
"Open",
"Humans",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/public.py#L102-L172 | [
"def",
"download",
"(",
"source",
"=",
"None",
",",
"username",
"=",
"None",
",",
"directory",
"=",
"'.'",
",",
"max_size",
"=",
"'128m'",
",",
"quiet",
"=",
"None",
",",
"debug",
"=",
"None",
")",
":",
"if",
"debug",
":",
"logging",
".",
"basicConfi... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | get_members_by_source | Function returns which members have joined each activity.
:param base_url: It is URL: `https://www.openhumans.org/api/public-data`. | ohapi/public.py | def get_members_by_source(base_url=BASE_URL_API):
"""
Function returns which members have joined each activity.
:param base_url: It is URL: `https://www.openhumans.org/api/public-data`.
"""
url = '{}members-by-source/'.format(base_url)
response = get_page(url)
return response | def get_members_by_source(base_url=BASE_URL_API):
"""
Function returns which members have joined each activity.
:param base_url: It is URL: `https://www.openhumans.org/api/public-data`.
"""
url = '{}members-by-source/'.format(base_url)
response = get_page(url)
return response | [
"Function",
"returns",
"which",
"members",
"have",
"joined",
"each",
"activity",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/public.py#L175-L183 | [
"def",
"get_members_by_source",
"(",
"base_url",
"=",
"BASE_URL_API",
")",
":",
"url",
"=",
"'{}members-by-source/'",
".",
"format",
"(",
"base_url",
")",
"response",
"=",
"get_page",
"(",
"url",
")",
"return",
"response"
] | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | get_sources_by_member | Function returns which activities each member has joined.
:param base_url: It is URL: `https://www.openhumans.org/api/public-data`.
:param limit: It is the limit of data send by one request. | ohapi/public.py | def get_sources_by_member(base_url=BASE_URL_API, limit=LIMIT_DEFAULT):
"""
Function returns which activities each member has joined.
:param base_url: It is URL: `https://www.openhumans.org/api/public-data`.
:param limit: It is the limit of data send by one request.
"""
url = '{}sources-by-membe... | def get_sources_by_member(base_url=BASE_URL_API, limit=LIMIT_DEFAULT):
"""
Function returns which activities each member has joined.
:param base_url: It is URL: `https://www.openhumans.org/api/public-data`.
:param limit: It is the limit of data send by one request.
"""
url = '{}sources-by-membe... | [
"Function",
"returns",
"which",
"activities",
"each",
"member",
"has",
"joined",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/public.py#L186-L203 | [
"def",
"get_sources_by_member",
"(",
"base_url",
"=",
"BASE_URL_API",
",",
"limit",
"=",
"LIMIT_DEFAULT",
")",
":",
"url",
"=",
"'{}sources-by-member/'",
".",
"format",
"(",
"base_url",
")",
"page",
"=",
"'{}?{}'",
".",
"format",
"(",
"url",
",",
"urlencode",
... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | OHProject._get_member_file_data | Helper function to get file data of member of a project.
:param member_data: This field is data related to member in a project. | ohapi/projects.py | def _get_member_file_data(member_data, id_filename=False):
"""
Helper function to get file data of member of a project.
:param member_data: This field is data related to member in a project.
"""
file_data = {}
for datafile in member_data['data']:
if id_filena... | def _get_member_file_data(member_data, id_filename=False):
"""
Helper function to get file data of member of a project.
:param member_data: This field is data related to member in a project.
"""
file_data = {}
for datafile in member_data['data']:
if id_filena... | [
"Helper",
"function",
"to",
"get",
"file",
"data",
"of",
"member",
"of",
"a",
"project",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/projects.py#L27-L43 | [
"def",
"_get_member_file_data",
"(",
"member_data",
",",
"id_filename",
"=",
"False",
")",
":",
"file_data",
"=",
"{",
"}",
"for",
"datafile",
"in",
"member_data",
"[",
"'data'",
"]",
":",
"if",
"id_filename",
":",
"basename",
"=",
"'{}.{}'",
".",
"format",
... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | OHProject.update_data | Returns data for all users including shared data files. | ohapi/projects.py | def update_data(self):
"""
Returns data for all users including shared data files.
"""
url = ('https://www.openhumans.org/api/direct-sharing/project/'
'members/?access_token={}'.format(self.master_access_token))
results = get_all_results(url)
self.project_d... | def update_data(self):
"""
Returns data for all users including shared data files.
"""
url = ('https://www.openhumans.org/api/direct-sharing/project/'
'members/?access_token={}'.format(self.master_access_token))
results = get_all_results(url)
self.project_d... | [
"Returns",
"data",
"for",
"all",
"users",
"including",
"shared",
"data",
"files",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/projects.py#L45-L63 | [
"def",
"update_data",
"(",
"self",
")",
":",
"url",
"=",
"(",
"'https://www.openhumans.org/api/direct-sharing/project/'",
"'members/?access_token={}'",
".",
"format",
"(",
"self",
".",
"master_access_token",
")",
")",
"results",
"=",
"get_all_results",
"(",
"url",
")"... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | OHProject.download_member_project_data | Download files to sync a local dir to match OH member project data.
:param member_data: This field is data related to member in a project.
:param target_member_dir: This field is the target directory where data
will be downloaded.
:param max_size: This field is the maximum file size... | ohapi/projects.py | def download_member_project_data(cls, member_data, target_member_dir,
max_size=MAX_SIZE_DEFAULT,
id_filename=False):
"""
Download files to sync a local dir to match OH member project data.
:param member_data: This field i... | def download_member_project_data(cls, member_data, target_member_dir,
max_size=MAX_SIZE_DEFAULT,
id_filename=False):
"""
Download files to sync a local dir to match OH member project data.
:param member_data: This field i... | [
"Download",
"files",
"to",
"sync",
"a",
"local",
"dir",
"to",
"match",
"OH",
"member",
"project",
"data",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/projects.py#L66-L91 | [
"def",
"download_member_project_data",
"(",
"cls",
",",
"member_data",
",",
"target_member_dir",
",",
"max_size",
"=",
"MAX_SIZE_DEFAULT",
",",
"id_filename",
"=",
"False",
")",
":",
"logging",
".",
"debug",
"(",
"'Download member project data...'",
")",
"sources_shar... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | OHProject.download_member_shared | Download files to sync a local dir to match OH member shared data.
Files are downloaded to match their "basename" on Open Humans.
If there are multiple files with the same name, the most recent is
downloaded.
:param member_data: This field is data related to member in a project.
... | ohapi/projects.py | def download_member_shared(cls, member_data, target_member_dir, source=None,
max_size=MAX_SIZE_DEFAULT, id_filename=False):
"""
Download files to sync a local dir to match OH member shared data.
Files are downloaded to match their "basename" on Open Humans.
... | def download_member_shared(cls, member_data, target_member_dir, source=None,
max_size=MAX_SIZE_DEFAULT, id_filename=False):
"""
Download files to sync a local dir to match OH member shared data.
Files are downloaded to match their "basename" on Open Humans.
... | [
"Download",
"files",
"to",
"sync",
"a",
"local",
"dir",
"to",
"match",
"OH",
"member",
"shared",
"data",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/projects.py#L94-L137 | [
"def",
"download_member_shared",
"(",
"cls",
",",
"member_data",
",",
"target_member_dir",
",",
"source",
"=",
"None",
",",
"max_size",
"=",
"MAX_SIZE_DEFAULT",
",",
"id_filename",
"=",
"False",
")",
":",
"logging",
".",
"debug",
"(",
"'Download member shared data... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | OHProject.download_all | Download data for all users including shared data files.
:param target_dir: This field is the target directory to download data.
:param source: This field is the data source. It's default value is
None.
:param project_data: This field is data related to particular project.
... | ohapi/projects.py | def download_all(self, target_dir, source=None, project_data=False,
memberlist=None, excludelist=None,
max_size=MAX_SIZE_DEFAULT, id_filename=False):
"""
Download data for all users including shared data files.
:param target_dir: This field is the targe... | def download_all(self, target_dir, source=None, project_data=False,
memberlist=None, excludelist=None,
max_size=MAX_SIZE_DEFAULT, id_filename=False):
"""
Download data for all users including shared data files.
:param target_dir: This field is the targe... | [
"Download",
"data",
"for",
"all",
"users",
"including",
"shared",
"data",
"files",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/projects.py#L139-L180 | [
"def",
"download_all",
"(",
"self",
",",
"target_dir",
",",
"source",
"=",
"None",
",",
"project_data",
"=",
"False",
",",
"memberlist",
"=",
"None",
",",
"excludelist",
"=",
"None",
",",
"max_size",
"=",
"MAX_SIZE_DEFAULT",
",",
"id_filename",
"=",
"False",... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | OHProject.upload_member_from_dir | Upload files in target directory to an Open Humans member's account.
The default behavior is to overwrite files with matching filenames on
Open Humans, but not otherwise delete files.
If the 'mode' parameter is 'safe': matching filenames will not be
overwritten.
If the 'mode' ... | ohapi/projects.py | def upload_member_from_dir(member_data, target_member_dir, metadata,
access_token, mode='default',
max_size=MAX_SIZE_DEFAULT):
"""
Upload files in target directory to an Open Humans member's account.
The default behavior is to overwr... | def upload_member_from_dir(member_data, target_member_dir, metadata,
access_token, mode='default',
max_size=MAX_SIZE_DEFAULT):
"""
Upload files in target directory to an Open Humans member's account.
The default behavior is to overwr... | [
"Upload",
"files",
"in",
"target",
"directory",
"to",
"an",
"Open",
"Humans",
"member",
"s",
"account",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/projects.py#L183-L232 | [
"def",
"upload_member_from_dir",
"(",
"member_data",
",",
"target_member_dir",
",",
"metadata",
",",
"access_token",
",",
"mode",
"=",
"'default'",
",",
"max_size",
"=",
"MAX_SIZE_DEFAULT",
")",
":",
"if",
"not",
"validate_metadata",
"(",
"target_member_dir",
",",
... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | oauth2_auth_url | Returns an OAuth2 authorization URL for a project, given Client ID. This
function constructs an authorization URL for a user to follow.
The user will be redirected to Authorize Open Humans data for our external
application. An OAuth2 project on Open Humans is required for this to
properly work. To learn... | ohapi/api.py | def oauth2_auth_url(redirect_uri=None, client_id=None, base_url=OH_BASE_URL):
"""
Returns an OAuth2 authorization URL for a project, given Client ID. This
function constructs an authorization URL for a user to follow.
The user will be redirected to Authorize Open Humans data for our external
applica... | def oauth2_auth_url(redirect_uri=None, client_id=None, base_url=OH_BASE_URL):
"""
Returns an OAuth2 authorization URL for a project, given Client ID. This
function constructs an authorization URL for a user to follow.
The user will be redirected to Authorize Open Humans data for our external
applica... | [
"Returns",
"an",
"OAuth2",
"authorization",
"URL",
"for",
"a",
"project",
"given",
"Client",
"ID",
".",
"This",
"function",
"constructs",
"an",
"authorization",
"URL",
"for",
"a",
"user",
"to",
"follow",
".",
"The",
"user",
"will",
"be",
"redirected",
"to",
... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L27-L60 | [
"def",
"oauth2_auth_url",
"(",
"redirect_uri",
"=",
"None",
",",
"client_id",
"=",
"None",
",",
"base_url",
"=",
"OH_BASE_URL",
")",
":",
"if",
"not",
"client_id",
":",
"client_id",
"=",
"os",
".",
"getenv",
"(",
"'OHAPI_CLIENT_ID'",
")",
"if",
"not",
"cli... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | oauth2_token_exchange | Exchange code or refresh token for a new token and refresh token. For the
first time when a project is created, code is required to generate refresh
token. Once the refresh token is obtained, it can be used later on for
obtaining new access token and refresh token. The user must store the
refresh token ... | ohapi/api.py | def oauth2_token_exchange(client_id, client_secret, redirect_uri,
base_url=OH_BASE_URL, code=None, refresh_token=None):
"""
Exchange code or refresh token for a new token and refresh token. For the
first time when a project is created, code is required to generate refresh
token... | def oauth2_token_exchange(client_id, client_secret, redirect_uri,
base_url=OH_BASE_URL, code=None, refresh_token=None):
"""
Exchange code or refresh token for a new token and refresh token. For the
first time when a project is created, code is required to generate refresh
token... | [
"Exchange",
"code",
"or",
"refresh",
"token",
"for",
"a",
"new",
"token",
"and",
"refresh",
"token",
".",
"For",
"the",
"first",
"time",
"when",
"a",
"project",
"is",
"created",
"code",
"is",
"required",
"to",
"generate",
"refresh",
"token",
".",
"Once",
... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L63-L101 | [
"def",
"oauth2_token_exchange",
"(",
"client_id",
",",
"client_secret",
",",
"redirect_uri",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"code",
"=",
"None",
",",
"refresh_token",
"=",
"None",
")",
":",
"if",
"not",
"(",
"code",
"or",
"refresh_token",
")",
"or... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | get_page | Get a single page of results.
:param url: This field is the url from which data will be requested. | ohapi/api.py | def get_page(url):
"""
Get a single page of results.
:param url: This field is the url from which data will be requested.
"""
response = requests.get(url)
handle_error(response, 200)
data = response.json()
return data | def get_page(url):
"""
Get a single page of results.
:param url: This field is the url from which data will be requested.
"""
response = requests.get(url)
handle_error(response, 200)
data = response.json()
return data | [
"Get",
"a",
"single",
"page",
"of",
"results",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L104-L113 | [
"def",
"get_page",
"(",
"url",
")",
":",
"response",
"=",
"requests",
".",
"get",
"(",
"url",
")",
"handle_error",
"(",
"response",
",",
"200",
")",
"data",
"=",
"response",
".",
"json",
"(",
")",
"return",
"data"
] | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | get_all_results | Given starting API query for Open Humans, iterate to get all results.
:param starting page: This field is the first page, starting from which
results will be obtained. | ohapi/api.py | def get_all_results(starting_page):
"""
Given starting API query for Open Humans, iterate to get all results.
:param starting page: This field is the first page, starting from which
results will be obtained.
"""
logging.info('Retrieving all results for {}'.format(starting_page))
page = ... | def get_all_results(starting_page):
"""
Given starting API query for Open Humans, iterate to get all results.
:param starting page: This field is the first page, starting from which
results will be obtained.
"""
logging.info('Retrieving all results for {}'.format(starting_page))
page = ... | [
"Given",
"starting",
"API",
"query",
"for",
"Open",
"Humans",
"iterate",
"to",
"get",
"all",
"results",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L116-L138 | [
"def",
"get_all_results",
"(",
"starting_page",
")",
":",
"logging",
".",
"info",
"(",
"'Retrieving all results for {}'",
".",
"format",
"(",
"starting_page",
")",
")",
"page",
"=",
"starting_page",
"results",
"=",
"[",
"]",
"while",
"True",
":",
"logging",
".... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | exchange_oauth2_member | Returns data for a specific user, including shared data files.
:param access_token: This field is the user specific access_token.
:param base_url: It is this URL `https://www.openhumans.org`. | ohapi/api.py | def exchange_oauth2_member(access_token, base_url=OH_BASE_URL,
all_files=False):
"""
Returns data for a specific user, including shared data files.
:param access_token: This field is the user specific access_token.
:param base_url: It is this URL `https://www.openhumans.org`.... | def exchange_oauth2_member(access_token, base_url=OH_BASE_URL,
all_files=False):
"""
Returns data for a specific user, including shared data files.
:param access_token: This field is the user specific access_token.
:param base_url: It is this URL `https://www.openhumans.org`.... | [
"Returns",
"data",
"for",
"a",
"specific",
"user",
"including",
"shared",
"data",
"files",
"."
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L141-L164 | [
"def",
"exchange_oauth2_member",
"(",
"access_token",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"all_files",
"=",
"False",
")",
":",
"url",
"=",
"urlparse",
".",
"urljoin",
"(",
"base_url",
",",
"'/api/direct-sharing/project/exchange-member/?{}'",
".",
"format",
"("... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | delete_file | Delete project member files by file_basename, file_id, or all_files. To
learn more about Open Humans OAuth2 projects, go to:
https://www.openhumans.org/direct-sharing/oauth2-features/.
:param access_token: This field is user specific access_token.
:param project_member_id: This field is the pro... | ohapi/api.py | def delete_file(access_token, project_member_id=None, base_url=OH_BASE_URL,
file_basename=None, file_id=None, all_files=False):
"""
Delete project member files by file_basename, file_id, or all_files. To
learn more about Open Humans OAuth2 projects, go to:
https://www.openhumans.... | def delete_file(access_token, project_member_id=None, base_url=OH_BASE_URL,
file_basename=None, file_id=None, all_files=False):
"""
Delete project member files by file_basename, file_id, or all_files. To
learn more about Open Humans OAuth2 projects, go to:
https://www.openhumans.... | [
"Delete",
"project",
"member",
"files",
"by",
"file_basename",
"file_id",
"or",
"all_files",
".",
"To",
"learn",
"more",
"about",
"Open",
"Humans",
"OAuth2",
"projects",
"go",
"to",
":",
"https",
":",
"//",
"www",
".",
"openhumans",
".",
"org",
"/",
"direc... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L166-L203 | [
"def",
"delete_file",
"(",
"access_token",
",",
"project_member_id",
"=",
"None",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"file_basename",
"=",
"None",
",",
"file_id",
"=",
"None",
",",
"all_files",
"=",
"False",
")",
":",
"url",
"=",
"urlparse",
".",
"u... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | message | Send an email to individual users or in bulk. To learn more about Open
Humans OAuth2 projects, go to:
https://www.openhumans.org/direct-sharing/oauth2-features/
:param subject: This field is the subject of the email.
:param message: This field is the body of the email.
:param access_token: This is ... | ohapi/api.py | def message(subject, message, access_token, all_members=False,
project_member_ids=None, base_url=OH_BASE_URL):
"""
Send an email to individual users or in bulk. To learn more about Open
Humans OAuth2 projects, go to:
https://www.openhumans.org/direct-sharing/oauth2-features/
:param subj... | def message(subject, message, access_token, all_members=False,
project_member_ids=None, base_url=OH_BASE_URL):
"""
Send an email to individual users or in bulk. To learn more about Open
Humans OAuth2 projects, go to:
https://www.openhumans.org/direct-sharing/oauth2-features/
:param subj... | [
"Send",
"an",
"email",
"to",
"individual",
"users",
"or",
"in",
"bulk",
".",
"To",
"learn",
"more",
"about",
"Open",
"Humans",
"OAuth2",
"projects",
"go",
"to",
":",
"https",
":",
"//",
"www",
".",
"openhumans",
".",
"org",
"/",
"direct",
"-",
"sharing... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L214-L247 | [
"def",
"message",
"(",
"subject",
",",
"message",
",",
"access_token",
",",
"all_members",
"=",
"False",
",",
"project_member_ids",
"=",
"None",
",",
"base_url",
"=",
"OH_BASE_URL",
")",
":",
"url",
"=",
"urlparse",
".",
"urljoin",
"(",
"base_url",
",",
"'... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | handle_error | Helper function to match reponse of a request to the expected status
code
:param r: This field is the response of request.
:param expected_code: This field is the expected status code for the
function. | ohapi/api.py | def handle_error(r, expected_code):
"""
Helper function to match reponse of a request to the expected status
code
:param r: This field is the response of request.
:param expected_code: This field is the expected status code for the
function.
"""
code = r.status_code
if code != e... | def handle_error(r, expected_code):
"""
Helper function to match reponse of a request to the expected status
code
:param r: This field is the response of request.
:param expected_code: This field is the expected status code for the
function.
"""
code = r.status_code
if code != e... | [
"Helper",
"function",
"to",
"match",
"reponse",
"of",
"a",
"request",
"to",
"the",
"expected",
"status",
"code"
] | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L258-L277 | [
"def",
"handle_error",
"(",
"r",
",",
"expected_code",
")",
":",
"code",
"=",
"r",
".",
"status_code",
"if",
"code",
"!=",
"expected_code",
":",
"info",
"=",
"'API response status code {}'",
".",
"format",
"(",
"code",
")",
"try",
":",
"if",
"'detail'",
"i... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | upload_stream | Upload a file object using the "direct upload" feature, which uploads to
an S3 bucket URL provided by the Open Humans API. To learn more about this
API endpoint see:
* https://www.openhumans.org/direct-sharing/on-site-data-upload/
* https://www.openhumans.org/direct-sharing/oauth2-data-upload/
:par... | ohapi/api.py | def upload_stream(stream, filename, metadata, access_token,
base_url=OH_BASE_URL, remote_file_info=None,
project_member_id=None, max_bytes=MAX_FILE_DEFAULT,
file_identifier=None):
"""
Upload a file object using the "direct upload" feature, which uploads to
... | def upload_stream(stream, filename, metadata, access_token,
base_url=OH_BASE_URL, remote_file_info=None,
project_member_id=None, max_bytes=MAX_FILE_DEFAULT,
file_identifier=None):
"""
Upload a file object using the "direct upload" feature, which uploads to
... | [
"Upload",
"a",
"file",
"object",
"using",
"the",
"direct",
"upload",
"feature",
"which",
"uploads",
"to",
"an",
"S3",
"bucket",
"URL",
"provided",
"by",
"the",
"Open",
"Humans",
"API",
".",
"To",
"learn",
"more",
"about",
"this",
"API",
"endpoint",
"see",
... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L280-L355 | [
"def",
"upload_stream",
"(",
"stream",
",",
"filename",
",",
"metadata",
",",
"access_token",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"remote_file_info",
"=",
"None",
",",
"project_member_id",
"=",
"None",
",",
"max_bytes",
"=",
"MAX_FILE_DEFAULT",
",",
"file_... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | upload_file | Upload a file from a local filepath using the "direct upload" API.
To learn more about this API endpoint see:
* https://www.openhumans.org/direct-sharing/on-site-data-upload/
* https://www.openhumans.org/direct-sharing/oauth2-data-upload/
:param target_filepath: This field is the filepath of the file t... | ohapi/api.py | def upload_file(target_filepath, metadata, access_token, base_url=OH_BASE_URL,
remote_file_info=None, project_member_id=None,
max_bytes=MAX_FILE_DEFAULT):
"""
Upload a file from a local filepath using the "direct upload" API.
To learn more about this API endpoint see:
* h... | def upload_file(target_filepath, metadata, access_token, base_url=OH_BASE_URL,
remote_file_info=None, project_member_id=None,
max_bytes=MAX_FILE_DEFAULT):
"""
Upload a file from a local filepath using the "direct upload" API.
To learn more about this API endpoint see:
* h... | [
"Upload",
"a",
"file",
"from",
"a",
"local",
"filepath",
"using",
"the",
"direct",
"upload",
"API",
".",
"To",
"learn",
"more",
"about",
"this",
"API",
"endpoint",
"see",
":",
"*",
"https",
":",
"//",
"www",
".",
"openhumans",
".",
"org",
"/",
"direct"... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L358-L385 | [
"def",
"upload_file",
"(",
"target_filepath",
",",
"metadata",
",",
"access_token",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"remote_file_info",
"=",
"None",
",",
"project_member_id",
"=",
"None",
",",
"max_bytes",
"=",
"MAX_FILE_DEFAULT",
")",
":",
"with",
"op... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | upload_aws | Upload a file from a local filepath using the "direct upload" API.
Equivalent to upload_file. To learn more about this API endpoint see:
* https://www.openhumans.org/direct-sharing/on-site-data-upload/
* https://www.openhumans.org/direct-sharing/oauth2-data-upload/
:param target_filepath: This field is... | ohapi/api.py | def upload_aws(target_filepath, metadata, access_token, base_url=OH_BASE_URL,
remote_file_info=None, project_member_id=None,
max_bytes=MAX_FILE_DEFAULT):
"""
Upload a file from a local filepath using the "direct upload" API.
Equivalent to upload_file. To learn more about this A... | def upload_aws(target_filepath, metadata, access_token, base_url=OH_BASE_URL,
remote_file_info=None, project_member_id=None,
max_bytes=MAX_FILE_DEFAULT):
"""
Upload a file from a local filepath using the "direct upload" API.
Equivalent to upload_file. To learn more about this A... | [
"Upload",
"a",
"file",
"from",
"a",
"local",
"filepath",
"using",
"the",
"direct",
"upload",
"API",
".",
"Equivalent",
"to",
"upload_file",
".",
"To",
"learn",
"more",
"about",
"this",
"API",
"endpoint",
"see",
":",
"*",
"https",
":",
"//",
"www",
".",
... | OpenHumans/open-humans-api | python | https://github.com/OpenHumans/open-humans-api/blob/ca2a28cf5d55cfdae13dd222ba58c25565bdb86e/ohapi/api.py#L388-L411 | [
"def",
"upload_aws",
"(",
"target_filepath",
",",
"metadata",
",",
"access_token",
",",
"base_url",
"=",
"OH_BASE_URL",
",",
"remote_file_info",
"=",
"None",
",",
"project_member_id",
"=",
"None",
",",
"max_bytes",
"=",
"MAX_FILE_DEFAULT",
")",
":",
"return",
"u... | ca2a28cf5d55cfdae13dd222ba58c25565bdb86e |
train | pack_list | Return the wire packed version of `from_`. `pack_type` should be some
subclass of `xcffib.Struct`, or a string that can be passed to
`struct.pack`. You must pass `size` if `pack_type` is a struct.pack string. | module/__init__.py | def pack_list(from_, pack_type):
""" Return the wire packed version of `from_`. `pack_type` should be some
subclass of `xcffib.Struct`, or a string that can be passed to
`struct.pack`. You must pass `size` if `pack_type` is a struct.pack string.
"""
# We need from_ to not be empty
if len(from_) ... | def pack_list(from_, pack_type):
""" Return the wire packed version of `from_`. `pack_type` should be some
subclass of `xcffib.Struct`, or a string that can be passed to
`struct.pack`. You must pass `size` if `pack_type` is a struct.pack string.
"""
# We need from_ to not be empty
if len(from_) ... | [
"Return",
"the",
"wire",
"packed",
"version",
"of",
"from_",
".",
"pack_type",
"should",
"be",
"some",
"subclass",
"of",
"xcffib",
".",
"Struct",
"or",
"a",
"string",
"that",
"can",
"be",
"passed",
"to",
"struct",
".",
"pack",
".",
"You",
"must",
"pass",... | tych0/xcffib | python | https://github.com/tych0/xcffib/blob/c9c50c3ce513b130821f430be78c4c733626c707/module/__init__.py#L751-L793 | [
"def",
"pack_list",
"(",
"from_",
",",
"pack_type",
")",
":",
"# We need from_ to not be empty",
"if",
"len",
"(",
"from_",
")",
"==",
"0",
":",
"return",
"bytes",
"(",
")",
"if",
"pack_type",
"==",
"'c'",
":",
"if",
"isinstance",
"(",
"from_",
",",
"byt... | c9c50c3ce513b130821f430be78c4c733626c707 |
train | Connection.ensure_connected | Check that the connection is valid both before and
after the function is invoked. | module/__init__.py | def ensure_connected(f):
"""
Check that the connection is valid both before and
after the function is invoked.
"""
@functools.wraps(f)
def wrapper(*args):
self = args[0]
self.invalid()
try:
return f(*args)
fi... | def ensure_connected(f):
"""
Check that the connection is valid both before and
after the function is invoked.
"""
@functools.wraps(f)
def wrapper(*args):
self = args[0]
self.invalid()
try:
return f(*args)
fi... | [
"Check",
"that",
"the",
"connection",
"is",
"valid",
"both",
"before",
"and",
"after",
"the",
"function",
"is",
"invoked",
"."
] | tych0/xcffib | python | https://github.com/tych0/xcffib/blob/c9c50c3ce513b130821f430be78c4c733626c707/module/__init__.py#L560-L573 | [
"def",
"ensure_connected",
"(",
"f",
")",
":",
"@",
"functools",
".",
"wraps",
"(",
"f",
")",
"def",
"wrapper",
"(",
"*",
"args",
")",
":",
"self",
"=",
"args",
"[",
"0",
"]",
"self",
".",
"invalid",
"(",
")",
"try",
":",
"return",
"f",
"(",
"*... | c9c50c3ce513b130821f430be78c4c733626c707 |
train | Connection.get_screen_pointers | Returns the xcb_screen_t for every screen
useful for other bindings | module/__init__.py | def get_screen_pointers(self):
"""
Returns the xcb_screen_t for every screen
useful for other bindings
"""
root_iter = lib.xcb_setup_roots_iterator(self._setup)
screens = [root_iter.data]
for i in range(self._setup.roots_len - 1):
lib.xcb_screen_next(... | def get_screen_pointers(self):
"""
Returns the xcb_screen_t for every screen
useful for other bindings
"""
root_iter = lib.xcb_setup_roots_iterator(self._setup)
screens = [root_iter.data]
for i in range(self._setup.roots_len - 1):
lib.xcb_screen_next(... | [
"Returns",
"the",
"xcb_screen_t",
"for",
"every",
"screen",
"useful",
"for",
"other",
"bindings"
] | tych0/xcffib | python | https://github.com/tych0/xcffib/blob/c9c50c3ce513b130821f430be78c4c733626c707/module/__init__.py#L586-L597 | [
"def",
"get_screen_pointers",
"(",
"self",
")",
":",
"root_iter",
"=",
"lib",
".",
"xcb_setup_roots_iterator",
"(",
"self",
".",
"_setup",
")",
"screens",
"=",
"[",
"root_iter",
".",
"data",
"]",
"for",
"i",
"in",
"range",
"(",
"self",
".",
"_setup",
"."... | c9c50c3ce513b130821f430be78c4c733626c707 |
train | Connection.hoist_event | Hoist an xcb_generic_event_t to the right xcffib structure. | module/__init__.py | def hoist_event(self, e):
""" Hoist an xcb_generic_event_t to the right xcffib structure. """
if e.response_type == 0:
return self._process_error(ffi.cast("xcb_generic_error_t *", e))
# We mask off the high bit here because events sent with SendEvent have
# this bit set. We ... | def hoist_event(self, e):
""" Hoist an xcb_generic_event_t to the right xcffib structure. """
if e.response_type == 0:
return self._process_error(ffi.cast("xcb_generic_error_t *", e))
# We mask off the high bit here because events sent with SendEvent have
# this bit set. We ... | [
"Hoist",
"an",
"xcb_generic_event_t",
"to",
"the",
"right",
"xcffib",
"structure",
"."
] | tych0/xcffib | python | https://github.com/tych0/xcffib/blob/c9c50c3ce513b130821f430be78c4c733626c707/module/__init__.py#L681-L693 | [
"def",
"hoist_event",
"(",
"self",
",",
"e",
")",
":",
"if",
"e",
".",
"response_type",
"==",
"0",
":",
"return",
"self",
".",
"_process_error",
"(",
"ffi",
".",
"cast",
"(",
"\"xcb_generic_error_t *\"",
",",
"e",
")",
")",
"# We mask off the high bit here b... | c9c50c3ce513b130821f430be78c4c733626c707 |
train | ColumnList.serialize | Greedy serialization requires the value to either be a column
or convertible to a column, whereas non-greedy serialization
will pass through any string as-is and will only serialize
Column objects.
Non-greedy serialization is useful when preparing queries with
custom filters or ... | googleanalytics/columns.py | def serialize(self, value, greedy=True):
"""
Greedy serialization requires the value to either be a column
or convertible to a column, whereas non-greedy serialization
will pass through any string as-is and will only serialize
Column objects.
Non-greedy serialization is ... | def serialize(self, value, greedy=True):
"""
Greedy serialization requires the value to either be a column
or convertible to a column, whereas non-greedy serialization
will pass through any string as-is and will only serialize
Column objects.
Non-greedy serialization is ... | [
"Greedy",
"serialization",
"requires",
"the",
"value",
"to",
"either",
"be",
"a",
"column",
"or",
"convertible",
"to",
"a",
"column",
"whereas",
"non",
"-",
"greedy",
"serialization",
"will",
"pass",
"through",
"any",
"string",
"as",
"-",
"is",
"and",
"will"... | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/columns.py#L237-L254 | [
"def",
"serialize",
"(",
"self",
",",
"value",
",",
"greedy",
"=",
"True",
")",
":",
"if",
"greedy",
"and",
"not",
"isinstance",
"(",
"value",
",",
"Column",
")",
":",
"value",
"=",
"self",
".",
"normalize",
"(",
"value",
")",
"if",
"isinstance",
"("... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | describe | Generate a query by describing it as a series of actions
and parameters to those actions. These map directly
to Query methods and arguments to those methods.
This is an alternative to the chaining interface.
Mostly useful if you'd like to put your queries
in a file, rather than in Python code. | googleanalytics/query.py | def describe(profile, description):
"""
Generate a query by describing it as a series of actions
and parameters to those actions. These map directly
to Query methods and arguments to those methods.
This is an alternative to the chaining interface.
Mostly useful if you'd like to put your queries... | def describe(profile, description):
"""
Generate a query by describing it as a series of actions
and parameters to those actions. These map directly
to Query methods and arguments to those methods.
This is an alternative to the chaining interface.
Mostly useful if you'd like to put your queries... | [
"Generate",
"a",
"query",
"by",
"describing",
"it",
"as",
"a",
"series",
"of",
"actions",
"and",
"parameters",
"to",
"those",
"actions",
".",
"These",
"map",
"directly",
"to",
"Query",
"methods",
"and",
"arguments",
"to",
"those",
"methods",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L1093-L1105 | [
"def",
"describe",
"(",
"profile",
",",
"description",
")",
":",
"api_type",
"=",
"description",
".",
"pop",
"(",
"'type'",
",",
"'core'",
")",
"api",
"=",
"getattr",
"(",
"profile",
",",
"api_type",
")",
"return",
"refine",
"(",
"api",
".",
"query",
"... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | refine | Refine a query from a dictionary of parameters that describes it.
See `describe` for more information. | googleanalytics/query.py | def refine(query, description):
"""
Refine a query from a dictionary of parameters that describes it.
See `describe` for more information.
"""
for attribute, arguments in description.items():
if hasattr(query, attribute):
attribute = getattr(query, attribute)
else:
... | def refine(query, description):
"""
Refine a query from a dictionary of parameters that describes it.
See `describe` for more information.
"""
for attribute, arguments in description.items():
if hasattr(query, attribute):
attribute = getattr(query, attribute)
else:
... | [
"Refine",
"a",
"query",
"from",
"a",
"dictionary",
"of",
"parameters",
"that",
"describes",
"it",
".",
"See",
"describe",
"for",
"more",
"information",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L1107-L1135 | [
"def",
"refine",
"(",
"query",
",",
"description",
")",
":",
"for",
"attribute",
",",
"arguments",
"in",
"description",
".",
"items",
"(",
")",
":",
"if",
"hasattr",
"(",
"query",
",",
"attribute",
")",
":",
"attribute",
"=",
"getattr",
"(",
"query",
"... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Query.set | `set` is a way to add raw properties to the request,
for features that this module does not
support or supports incompletely. For convenience's
sake, it will serialize Column objects but will
leave any other kind of value alone. | googleanalytics/query.py | def set(self, key=None, value=None, **kwargs):
"""
`set` is a way to add raw properties to the request,
for features that this module does not
support or supports incompletely. For convenience's
sake, it will serialize Column objects but will
leave any other kind of value... | def set(self, key=None, value=None, **kwargs):
"""
`set` is a way to add raw properties to the request,
for features that this module does not
support or supports incompletely. For convenience's
sake, it will serialize Column objects but will
leave any other kind of value... | [
"set",
"is",
"a",
"way",
"to",
"add",
"raw",
"properties",
"to",
"the",
"request",
"for",
"features",
"that",
"this",
"module",
"does",
"not",
"support",
"or",
"supports",
"incompletely",
".",
"For",
"convenience",
"s",
"sake",
"it",
"will",
"serialize",
"... | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L430-L451 | [
"def",
"set",
"(",
"self",
",",
"key",
"=",
"None",
",",
"value",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"serialize",
"=",
"partial",
"(",
"self",
".",
"api",
".",
"columns",
".",
"serialize",
",",
"greedy",
"=",
"False",
")",
"if",
"key... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Query.description | A list of the metrics this query will ask for. | googleanalytics/query.py | def description(self):
"""
A list of the metrics this query will ask for.
"""
if 'metrics' in self.raw:
metrics = self.raw['metrics']
head = metrics[0:-1] or metrics[0:1]
text = ", ".join(head)
if len(metrics) > 1:
tail = m... | def description(self):
"""
A list of the metrics this query will ask for.
"""
if 'metrics' in self.raw:
metrics = self.raw['metrics']
head = metrics[0:-1] or metrics[0:1]
text = ", ".join(head)
if len(metrics) > 1:
tail = m... | [
"A",
"list",
"of",
"the",
"metrics",
"this",
"query",
"will",
"ask",
"for",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L469-L484 | [
"def",
"description",
"(",
"self",
")",
":",
"if",
"'metrics'",
"in",
"self",
".",
"raw",
":",
"metrics",
"=",
"self",
".",
"raw",
"[",
"'metrics'",
"]",
"head",
"=",
"metrics",
"[",
"0",
":",
"-",
"1",
"]",
"or",
"metrics",
"[",
"0",
":",
"1",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Query.sort | Return a new query which will produce results sorted by
one or more metrics or dimensions. You may use plain
strings for the columns, or actual `Column`, `Metric`
and `Dimension` objects.
Add a minus in front of the metric (either the string or
the object) to sort in descending ... | googleanalytics/query.py | def sort(self, *columns, **options):
"""
Return a new query which will produce results sorted by
one or more metrics or dimensions. You may use plain
strings for the columns, or actual `Column`, `Metric`
and `Dimension` objects.
Add a minus in front of the metric (either... | def sort(self, *columns, **options):
"""
Return a new query which will produce results sorted by
one or more metrics or dimensions. You may use plain
strings for the columns, or actual `Column`, `Metric`
and `Dimension` objects.
Add a minus in front of the metric (either... | [
"Return",
"a",
"new",
"query",
"which",
"will",
"produce",
"results",
"sorted",
"by",
"one",
"or",
"more",
"metrics",
"or",
"dimensions",
".",
"You",
"may",
"use",
"plain",
"strings",
"for",
"the",
"columns",
"or",
"actual",
"Column",
"Metric",
"and",
"Dim... | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L515-L556 | [
"def",
"sort",
"(",
"self",
",",
"*",
"columns",
",",
"*",
"*",
"options",
")",
":",
"sorts",
"=",
"self",
".",
"meta",
".",
"setdefault",
"(",
"'sort'",
",",
"[",
"]",
")",
"for",
"column",
"in",
"columns",
":",
"if",
"isinstance",
"(",
"column",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Query.filter | Most of the actual functionality lives on the Column
object and the `all` and `any` functions. | googleanalytics/query.py | def filter(self, value=None, exclude=False, **selection):
""" Most of the actual functionality lives on the Column
object and the `all` and `any` functions. """
filters = self.meta.setdefault('filters', [])
if value and len(selection):
raise ValueError("Cannot specify a filt... | def filter(self, value=None, exclude=False, **selection):
""" Most of the actual functionality lives on the Column
object and the `all` and `any` functions. """
filters = self.meta.setdefault('filters', [])
if value and len(selection):
raise ValueError("Cannot specify a filt... | [
"Most",
"of",
"the",
"actual",
"functionality",
"lives",
"on",
"the",
"Column",
"object",
"and",
"the",
"all",
"and",
"any",
"functions",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L559-L573 | [
"def",
"filter",
"(",
"self",
",",
"value",
"=",
"None",
",",
"exclude",
"=",
"False",
",",
"*",
"*",
"selection",
")",
":",
"filters",
"=",
"self",
".",
"meta",
".",
"setdefault",
"(",
"'filters'",
",",
"[",
"]",
")",
"if",
"value",
"and",
"len",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.precision | For queries that should run faster, you may specify a lower precision,
and for those that need to be more precise, a higher precision:
```python
# faster queries
query.range('2014-01-01', '2014-01-31', precision=0)
query.range('2014-01-01', '2014-01-31', precision='FASTER')
... | googleanalytics/query.py | def precision(self, precision):
"""
For queries that should run faster, you may specify a lower precision,
and for those that need to be more precise, a higher precision:
```python
# faster queries
query.range('2014-01-01', '2014-01-31', precision=0)
query.range(... | def precision(self, precision):
"""
For queries that should run faster, you may specify a lower precision,
and for those that need to be more precise, a higher precision:
```python
# faster queries
query.range('2014-01-01', '2014-01-31', precision=0)
query.range(... | [
"For",
"queries",
"that",
"should",
"run",
"faster",
"you",
"may",
"specify",
"a",
"lower",
"precision",
"and",
"for",
"those",
"that",
"need",
"to",
"be",
"more",
"precise",
"a",
"higher",
"precision",
":"
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L702-L731 | [
"def",
"precision",
"(",
"self",
",",
"precision",
")",
":",
"if",
"isinstance",
"(",
"precision",
",",
"int",
")",
":",
"precision",
"=",
"self",
".",
"PRECISION_LEVELS",
"[",
"precision",
"]",
"if",
"precision",
"not",
"in",
"self",
".",
"PRECISION_LEVEL... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.interval | Note that if you don't specify a granularity (either through the `interval`
method or through the `hourly`, `daily`, `weekly`, `monthly` or `yearly`
shortcut methods) you will get only a single result, encompassing the
entire date range, per metric. | googleanalytics/query.py | def interval(self, granularity):
"""
Note that if you don't specify a granularity (either through the `interval`
method or through the `hourly`, `daily`, `weekly`, `monthly` or `yearly`
shortcut methods) you will get only a single result, encompassing the
entire date range, per m... | def interval(self, granularity):
"""
Note that if you don't specify a granularity (either through the `interval`
method or through the `hourly`, `daily`, `weekly`, `monthly` or `yearly`
shortcut methods) you will get only a single result, encompassing the
entire date range, per m... | [
"Note",
"that",
"if",
"you",
"don",
"t",
"specify",
"a",
"granularity",
"(",
"either",
"through",
"the",
"interval",
"method",
"or",
"through",
"the",
"hourly",
"daily",
"weekly",
"monthly",
"or",
"yearly",
"shortcut",
"methods",
")",
"you",
"will",
"get",
... | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L734-L755 | [
"def",
"interval",
"(",
"self",
",",
"granularity",
")",
":",
"if",
"granularity",
"==",
"'total'",
":",
"return",
"self",
"if",
"not",
"isinstance",
"(",
"granularity",
",",
"int",
")",
":",
"if",
"granularity",
"in",
"self",
".",
"GRANULARITY_LEVELS",
":... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.range | Return a new query that fetches metrics within a certain date range.
```python
query.range('2014-01-01', '2014-06-30')
```
If you don't specify a `stop` argument, the date range will end today. If instead
you meant to fetch just a single day's results, try:
```python
... | googleanalytics/query.py | def range(self, start=None, stop=None, months=0, days=0):
"""
Return a new query that fetches metrics within a certain date range.
```python
query.range('2014-01-01', '2014-06-30')
```
If you don't specify a `stop` argument, the date range will end today. If instead
... | def range(self, start=None, stop=None, months=0, days=0):
"""
Return a new query that fetches metrics within a certain date range.
```python
query.range('2014-01-01', '2014-06-30')
```
If you don't specify a `stop` argument, the date range will end today. If instead
... | [
"Return",
"a",
"new",
"query",
"that",
"fetches",
"metrics",
"within",
"a",
"certain",
"date",
"range",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L758-L798 | [
"def",
"range",
"(",
"self",
",",
"start",
"=",
"None",
",",
"stop",
"=",
"None",
",",
"months",
"=",
"0",
",",
"days",
"=",
"0",
")",
":",
"start",
",",
"stop",
"=",
"utils",
".",
"date",
".",
"range",
"(",
"start",
",",
"stop",
",",
"months",... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.limit | Return a new query, limited to a certain number of results.
```python
# first 100
query.limit(100)
# 50 to 60
query.limit(50, 10)
```
Please note carefully that Google Analytics uses
1-indexing on its rows. | googleanalytics/query.py | def limit(self, *_range):
"""
Return a new query, limited to a certain number of results.
```python
# first 100
query.limit(100)
# 50 to 60
query.limit(50, 10)
```
Please note carefully that Google Analytics uses
1-indexing on its rows.
... | def limit(self, *_range):
"""
Return a new query, limited to a certain number of results.
```python
# first 100
query.limit(100)
# 50 to 60
query.limit(50, 10)
```
Please note carefully that Google Analytics uses
1-indexing on its rows.
... | [
"Return",
"a",
"new",
"query",
"limited",
"to",
"a",
"certain",
"number",
"of",
"results",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L866-L895 | [
"def",
"limit",
"(",
"self",
",",
"*",
"_range",
")",
":",
"# uses the same argument order as",
"# LIMIT in a SQL database",
"if",
"len",
"(",
"_range",
")",
"==",
"2",
":",
"start",
",",
"maximum",
"=",
"_range",
"else",
":",
"start",
"=",
"1",
"maximum",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.segment | Return a new query, limited to a segment of all users or sessions.
Accepts segment objects, filtered segment objects and segment names:
```python
query.segment(account.segments['browser'])
query.segment('browser')
query.segment(account.segments['browser'].any('Chrome', 'Firefox... | googleanalytics/query.py | def segment(self, value=None, scope=None, metric_scope=None, **selection):
"""
Return a new query, limited to a segment of all users or sessions.
Accepts segment objects, filtered segment objects and segment names:
```python
query.segment(account.segments['browser'])
qu... | def segment(self, value=None, scope=None, metric_scope=None, **selection):
"""
Return a new query, limited to a segment of all users or sessions.
Accepts segment objects, filtered segment objects and segment names:
```python
query.segment(account.segments['browser'])
qu... | [
"Return",
"a",
"new",
"query",
"limited",
"to",
"a",
"segment",
"of",
"all",
"users",
"or",
"sessions",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L909-L1003 | [
"def",
"segment",
"(",
"self",
",",
"value",
"=",
"None",
",",
"scope",
"=",
"None",
",",
"metric_scope",
"=",
"None",
",",
"*",
"*",
"selection",
")",
":",
"\"\"\"\n Technical note to self about segments:\n\n * users or sessions\n * sequence or condi... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.next | Return a new query with a modified `start_index`.
Mainly used internally to paginate through results. | googleanalytics/query.py | def next(self):
"""
Return a new query with a modified `start_index`.
Mainly used internally to paginate through results.
"""
step = self.raw.get('max_results', 1000)
start = self.raw.get('start_index', 1) + step
self.raw['start_index'] = start
return self | def next(self):
"""
Return a new query with a modified `start_index`.
Mainly used internally to paginate through results.
"""
step = self.raw.get('max_results', 1000)
start = self.raw.get('start_index', 1) + step
self.raw['start_index'] = start
return self | [
"Return",
"a",
"new",
"query",
"with",
"a",
"modified",
"start_index",
".",
"Mainly",
"used",
"internally",
"to",
"paginate",
"through",
"results",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L1012-L1020 | [
"def",
"next",
"(",
"self",
")",
":",
"step",
"=",
"self",
".",
"raw",
".",
"get",
"(",
"'max_results'",
",",
"1000",
")",
"start",
"=",
"self",
".",
"raw",
".",
"get",
"(",
"'start_index'",
",",
"1",
")",
"+",
"step",
"self",
".",
"raw",
"[",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | CoreQuery.get | Run the query and return a `Report`.
This method transparently handles paginated results, so even for results that
are larger than the maximum amount of rows the Google Analytics API will
return in a single request, or larger than the amount of rows as specified
through `CoreQuery#step`... | googleanalytics/query.py | def get(self):
"""
Run the query and return a `Report`.
This method transparently handles paginated results, so even for results that
are larger than the maximum amount of rows the Google Analytics API will
return in a single request, or larger than the amount of rows as specifi... | def get(self):
"""
Run the query and return a `Report`.
This method transparently handles paginated results, so even for results that
are larger than the maximum amount of rows the Google Analytics API will
return in a single request, or larger than the amount of rows as specifi... | [
"Run",
"the",
"query",
"and",
"return",
"a",
"Report",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L1022-L1050 | [
"def",
"get",
"(",
"self",
")",
":",
"cursor",
"=",
"self",
"report",
"=",
"None",
"is_complete",
"=",
"False",
"is_enough",
"=",
"False",
"while",
"not",
"(",
"is_enough",
"or",
"is_complete",
")",
":",
"chunk",
"=",
"cursor",
".",
"execute",
"(",
")"... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | RealTimeQuery.limit | Return a new query, limited to a certain number of results.
Unlike core reporting queries, you cannot specify a starting
point for live queries, just the maximum results returned.
```python
# first 50
query.limit(50)
``` | googleanalytics/query.py | def limit(self, maximum):
"""
Return a new query, limited to a certain number of results.
Unlike core reporting queries, you cannot specify a starting
point for live queries, just the maximum results returned.
```python
# first 50
query.limit(50)
```
... | def limit(self, maximum):
"""
Return a new query, limited to a certain number of results.
Unlike core reporting queries, you cannot specify a starting
point for live queries, just the maximum results returned.
```python
# first 50
query.limit(50)
```
... | [
"Return",
"a",
"new",
"query",
"limited",
"to",
"a",
"certain",
"number",
"of",
"results",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/query.py#L1068-L1085 | [
"def",
"limit",
"(",
"self",
",",
"maximum",
")",
":",
"self",
".",
"meta",
"[",
"'limit'",
"]",
"=",
"maximum",
"self",
".",
"raw",
".",
"update",
"(",
"{",
"'max_results'",
":",
"maximum",
",",
"}",
")",
"return",
"self"
] | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Credentials.valid | Valid credentials are not necessarily correct, but
they contain all necessary information for an
authentication attempt. | googleanalytics/auth/credentials.py | def valid(self):
""" Valid credentials are not necessarily correct, but
they contain all necessary information for an
authentication attempt. """
two_legged = self.client_email and self.private_key
three_legged = self.client_id and self.client_secret
return two_legged or ... | def valid(self):
""" Valid credentials are not necessarily correct, but
they contain all necessary information for an
authentication attempt. """
two_legged = self.client_email and self.private_key
three_legged = self.client_id and self.client_secret
return two_legged or ... | [
"Valid",
"credentials",
"are",
"not",
"necessarily",
"correct",
"but",
"they",
"contain",
"all",
"necessary",
"information",
"for",
"an",
"authentication",
"attempt",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/auth/credentials.py#L136-L142 | [
"def",
"valid",
"(",
"self",
")",
":",
"two_legged",
"=",
"self",
".",
"client_email",
"and",
"self",
".",
"private_key",
"three_legged",
"=",
"self",
".",
"client_id",
"and",
"self",
".",
"client_secret",
"return",
"two_legged",
"or",
"three_legged",
"or",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Credentials.complete | Complete credentials are valid and are either two-legged or include a token. | googleanalytics/auth/credentials.py | def complete(self):
""" Complete credentials are valid and are either two-legged or include a token. """
return self.valid and (self.access_token or self.refresh_token or self.type == 2) | def complete(self):
""" Complete credentials are valid and are either two-legged or include a token. """
return self.valid and (self.access_token or self.refresh_token or self.type == 2) | [
"Complete",
"credentials",
"are",
"valid",
"and",
"are",
"either",
"two",
"-",
"legged",
"or",
"include",
"a",
"token",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/auth/credentials.py#L149-L151 | [
"def",
"complete",
"(",
"self",
")",
":",
"return",
"self",
".",
"valid",
"and",
"(",
"self",
".",
"access_token",
"or",
"self",
".",
"refresh_token",
"or",
"self",
".",
"type",
"==",
"2",
")"
] | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | authenticate | The `authenticate` function will authenticate the user with the Google Analytics API,
using a variety of strategies: keyword arguments provided to this function, credentials
stored in in environment variables, credentials stored in the keychain and, finally, by
asking for missing information interactively i... | googleanalytics/auth/__init__.py | def authenticate(
client_id=None, client_secret=None,
client_email=None, private_key=None,
access_token=None, refresh_token=None,
account=None, webproperty=None, profile=None,
identity=None, prefix=None, suffix=None,
interactive=False, save=False):
"""
The `authen... | def authenticate(
client_id=None, client_secret=None,
client_email=None, private_key=None,
access_token=None, refresh_token=None,
account=None, webproperty=None, profile=None,
identity=None, prefix=None, suffix=None,
interactive=False, save=False):
"""
The `authen... | [
"The",
"authenticate",
"function",
"will",
"authenticate",
"the",
"user",
"with",
"the",
"Google",
"Analytics",
"API",
"using",
"a",
"variety",
"of",
"strategies",
":",
"keyword",
"arguments",
"provided",
"to",
"this",
"function",
"credentials",
"stored",
"in",
... | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/auth/__init__.py#L43-L97 | [
"def",
"authenticate",
"(",
"client_id",
"=",
"None",
",",
"client_secret",
"=",
"None",
",",
"client_email",
"=",
"None",
",",
"private_key",
"=",
"None",
",",
"access_token",
"=",
"None",
",",
"refresh_token",
"=",
"None",
",",
"account",
"=",
"None",
",... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | revoke | Given a client id, client secret and either an access token or a refresh token,
revoke OAuth access to the Google Analytics data and remove any stored credentials
that use these tokens. | googleanalytics/auth/__init__.py | def revoke(client_id, client_secret,
client_email=None, private_key=None,
access_token=None, refresh_token=None,
identity=None, prefix=None, suffix=None):
"""
Given a client id, client secret and either an access token or a refresh token,
revoke OAuth access to the Google Analytics ... | def revoke(client_id, client_secret,
client_email=None, private_key=None,
access_token=None, refresh_token=None,
identity=None, prefix=None, suffix=None):
"""
Given a client id, client secret and either an access token or a refresh token,
revoke OAuth access to the Google Analytics ... | [
"Given",
"a",
"client",
"id",
"client",
"secret",
"and",
"either",
"an",
"access",
"token",
"or",
"a",
"refresh",
"token",
"revoke",
"OAuth",
"access",
"to",
"the",
"Google",
"Analytics",
"data",
"and",
"remove",
"any",
"stored",
"credentials",
"that",
"use"... | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/auth/__init__.py#L123-L151 | [
"def",
"revoke",
"(",
"client_id",
",",
"client_secret",
",",
"client_email",
"=",
"None",
",",
"private_key",
"=",
"None",
",",
"access_token",
"=",
"None",
",",
"refresh_token",
"=",
"None",
",",
"identity",
"=",
"None",
",",
"prefix",
"=",
"None",
",",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | query | e.g.
googleanalytics --identity debrouwere --account debrouwere --webproperty http://debrouwere.org \
query pageviews \
--start yesterday --limit -10 --sort -pageviews \
--dimensions pagepath \
--debug | googleanalytics/commands/query.py | def query(scope, blueprint, debug, output, with_metadata, realtime, **description):
"""
e.g.
googleanalytics --identity debrouwere --account debrouwere --webproperty http://debrouwere.org \
query pageviews \
--start yesterday --limit -10 --sort -pageviews \
--dimensi... | def query(scope, blueprint, debug, output, with_metadata, realtime, **description):
"""
e.g.
googleanalytics --identity debrouwere --account debrouwere --webproperty http://debrouwere.org \
query pageviews \
--start yesterday --limit -10 --sort -pageviews \
--dimensi... | [
"e",
".",
"g",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/commands/query.py#L102-L130 | [
"def",
"query",
"(",
"scope",
",",
"blueprint",
",",
"debug",
",",
"output",
",",
"with_metadata",
",",
"realtime",
",",
"*",
"*",
"description",
")",
":",
"if",
"realtime",
":",
"description",
"[",
"'type'",
"]",
"=",
"'realtime'",
"if",
"blueprint",
":... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | vectorize | Allows a method to accept one or more values,
but internally deal only with a single item,
and returning a list or a single item depending
on what is desired. | googleanalytics/utils/functional.py | def vectorize(fn):
"""
Allows a method to accept one or more values,
but internally deal only with a single item,
and returning a list or a single item depending
on what is desired.
"""
@functools.wraps(fn)
def vectorized_method(self, values, *vargs, **kwargs):
wrap = not isinst... | def vectorize(fn):
"""
Allows a method to accept one or more values,
but internally deal only with a single item,
and returning a list or a single item depending
on what is desired.
"""
@functools.wraps(fn)
def vectorized_method(self, values, *vargs, **kwargs):
wrap = not isinst... | [
"Allows",
"a",
"method",
"to",
"accept",
"one",
"or",
"more",
"values",
"but",
"internally",
"deal",
"only",
"with",
"a",
"single",
"item",
"and",
"returning",
"a",
"list",
"or",
"a",
"single",
"item",
"depending",
"on",
"what",
"is",
"desired",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/utils/functional.py#L20-L45 | [
"def",
"vectorize",
"(",
"fn",
")",
":",
"@",
"functools",
".",
"wraps",
"(",
"fn",
")",
"def",
"vectorized_method",
"(",
"self",
",",
"values",
",",
"*",
"vargs",
",",
"*",
"*",
"kwargs",
")",
":",
"wrap",
"=",
"not",
"isinstance",
"(",
"values",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | Account.webproperties | A list of all web properties on this account. You may
select a specific web property using its name, its id
or an index.
```python
account.webproperties[0]
account.webproperties['UA-9234823-5']
account.webproperties['debrouwere.org']
``` | googleanalytics/account.py | def webproperties(self):
"""
A list of all web properties on this account. You may
select a specific web property using its name, its id
or an index.
```python
account.webproperties[0]
account.webproperties['UA-9234823-5']
account.webproperties['debrouwer... | def webproperties(self):
"""
A list of all web properties on this account. You may
select a specific web property using its name, its id
or an index.
```python
account.webproperties[0]
account.webproperties['UA-9234823-5']
account.webproperties['debrouwer... | [
"A",
"list",
"of",
"all",
"web",
"properties",
"on",
"this",
"account",
".",
"You",
"may",
"select",
"a",
"specific",
"web",
"property",
"using",
"its",
"name",
"its",
"id",
"or",
"an",
"index",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/account.py#L47-L63 | [
"def",
"webproperties",
"(",
"self",
")",
":",
"raw_properties",
"=",
"self",
".",
"service",
".",
"management",
"(",
")",
".",
"webproperties",
"(",
")",
".",
"list",
"(",
"accountId",
"=",
"self",
".",
"id",
")",
".",
"execute",
"(",
")",
"[",
"'it... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | WebProperty.profiles | A list of all profiles on this web property. You may
select a specific profile using its name, its id
or an index.
```python
property.profiles[0]
property.profiles['9234823']
property.profiles['marketing profile']
``` | googleanalytics/account.py | def profiles(self):
"""
A list of all profiles on this web property. You may
select a specific profile using its name, its id
or an index.
```python
property.profiles[0]
property.profiles['9234823']
property.profiles['marketing profile']
```
... | def profiles(self):
"""
A list of all profiles on this web property. You may
select a specific profile using its name, its id
or an index.
```python
property.profiles[0]
property.profiles['9234823']
property.profiles['marketing profile']
```
... | [
"A",
"list",
"of",
"all",
"profiles",
"on",
"this",
"web",
"property",
".",
"You",
"may",
"select",
"a",
"specific",
"profile",
"using",
"its",
"name",
"its",
"id",
"or",
"an",
"index",
"."
] | debrouwere/google-analytics | python | https://github.com/debrouwere/google-analytics/blob/7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c/googleanalytics/account.py#L98-L114 | [
"def",
"profiles",
"(",
"self",
")",
":",
"raw_profiles",
"=",
"self",
".",
"account",
".",
"service",
".",
"management",
"(",
")",
".",
"profiles",
"(",
")",
".",
"list",
"(",
"accountId",
"=",
"self",
".",
"account",
".",
"id",
",",
"webPropertyId",
... | 7d585c2f6f5ca191e975e6e3eaf7d5e2424fa11c |
train | check_output_input | Run command with arguments and return its output as a byte string.
If the exit code was non-zero it raises a CalledProcessError. The
CalledProcessError object will have the return code in the returncode
attribute and output in the output attribute.
The arguments are the same as for the Popen construc... | texcla/libs/fastTextWikiTokenizer/subprocess_fix.py | def check_output_input(*popenargs, **kwargs):
"""Run command with arguments and return its output as a byte string.
If the exit code was non-zero it raises a CalledProcessError. The
CalledProcessError object will have the return code in the returncode
attribute and output in the output attribute.
... | def check_output_input(*popenargs, **kwargs):
"""Run command with arguments and return its output as a byte string.
If the exit code was non-zero it raises a CalledProcessError. The
CalledProcessError object will have the return code in the returncode
attribute and output in the output attribute.
... | [
"Run",
"command",
"with",
"arguments",
"and",
"return",
"its",
"output",
"as",
"a",
"byte",
"string",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/libs/fastTextWikiTokenizer/subprocess_fix.py#L7-L63 | [
"def",
"check_output_input",
"(",
"*",
"popenargs",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"'stdout'",
"in",
"kwargs",
":",
"raise",
"ValueError",
"(",
"'stdout argument not allowed, it will be overridden.'",
")",
"if",
"'input'",
"in",
"kwargs",
":",
"if",
"'... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.create_token_indices | If `apply_encoding_options` is inadequate, one can retrieve tokens from `self.token_counts`, filter with
a desired strategy and regenerate `token_index` using this method. The token index is subsequently used
when `encode_texts` or `decode_texts` methods are called. | texcla/preprocessing/tokenizer.py | def create_token_indices(self, tokens):
"""If `apply_encoding_options` is inadequate, one can retrieve tokens from `self.token_counts`, filter with
a desired strategy and regenerate `token_index` using this method. The token index is subsequently used
when `encode_texts` or `decode_texts` method... | def create_token_indices(self, tokens):
"""If `apply_encoding_options` is inadequate, one can retrieve tokens from `self.token_counts`, filter with
a desired strategy and regenerate `token_index` using this method. The token index is subsequently used
when `encode_texts` or `decode_texts` method... | [
"If",
"apply_encoding_options",
"is",
"inadequate",
"one",
"can",
"retrieve",
"tokens",
"from",
"self",
".",
"token_counts",
"filter",
"with",
"a",
"desired",
"strategy",
"and",
"regenerate",
"token_index",
"using",
"this",
"method",
".",
"The",
"token",
"index",
... | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L70-L80 | [
"def",
"create_token_indices",
"(",
"self",
",",
"tokens",
")",
":",
"start_index",
"=",
"len",
"(",
"self",
".",
"special_token",
")",
"indices",
"=",
"list",
"(",
"range",
"(",
"len",
"(",
"tokens",
")",
"+",
"start_index",
")",
")",
"# prepend because t... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.apply_encoding_options | Applies the given settings for subsequent calls to `encode_texts` and `decode_texts`. This allows you to
play with different settings without having to re-run tokenization on the entire corpus.
Args:
min_token_count: The minimum token count (frequency) in order to include during encoding. A... | texcla/preprocessing/tokenizer.py | def apply_encoding_options(self, min_token_count=1, limit_top_tokens=None):
"""Applies the given settings for subsequent calls to `encode_texts` and `decode_texts`. This allows you to
play with different settings without having to re-run tokenization on the entire corpus.
Args:
min_... | def apply_encoding_options(self, min_token_count=1, limit_top_tokens=None):
"""Applies the given settings for subsequent calls to `encode_texts` and `decode_texts`. This allows you to
play with different settings without having to re-run tokenization on the entire corpus.
Args:
min_... | [
"Applies",
"the",
"given",
"settings",
"for",
"subsequent",
"calls",
"to",
"encode_texts",
"and",
"decode_texts",
".",
"This",
"allows",
"you",
"to",
"play",
"with",
"different",
"settings",
"without",
"having",
"to",
"re",
"-",
"run",
"tokenization",
"on",
"t... | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L82-L111 | [
"def",
"apply_encoding_options",
"(",
"self",
",",
"min_token_count",
"=",
"1",
",",
"limit_top_tokens",
"=",
"None",
")",
":",
"if",
"not",
"self",
".",
"has_vocab",
":",
"raise",
"ValueError",
"(",
"\"You need to build the vocabulary using `build_vocab` \"",
"\"befo... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.encode_texts | Encodes the given texts using internal vocabulary with optionally applied encoding options. See
``apply_encoding_options` to set various options.
Args:
texts: The list of text items to encode.
unknown_token: The token to replace words that out of vocabulary. If none, those words... | texcla/preprocessing/tokenizer.py | def encode_texts(self, texts, unknown_token="<UNK>", verbose=1, **kwargs):
"""Encodes the given texts using internal vocabulary with optionally applied encoding options. See
``apply_encoding_options` to set various options.
Args:
texts: The list of text items to encode.
... | def encode_texts(self, texts, unknown_token="<UNK>", verbose=1, **kwargs):
"""Encodes the given texts using internal vocabulary with optionally applied encoding options. See
``apply_encoding_options` to set various options.
Args:
texts: The list of text items to encode.
... | [
"Encodes",
"the",
"given",
"texts",
"using",
"internal",
"vocabulary",
"with",
"optionally",
"applied",
"encoding",
"options",
".",
"See",
"apply_encoding_options",
"to",
"set",
"various",
"options",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L113-L151 | [
"def",
"encode_texts",
"(",
"self",
",",
"texts",
",",
"unknown_token",
"=",
"\"<UNK>\"",
",",
"verbose",
"=",
"1",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"not",
"self",
".",
"has_vocab",
":",
"raise",
"ValueError",
"(",
"\"You need to build the vocabulary... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.decode_texts | Decodes the texts using internal vocabulary. The list structure is maintained.
Args:
encoded_texts: The list of texts to decode.
unknown_token: The placeholder value for unknown token. (Default value: "<UNK>")
inplace: True to make changes inplace. (Default value: True)
... | texcla/preprocessing/tokenizer.py | def decode_texts(self, encoded_texts, unknown_token="<UNK>", inplace=True):
"""Decodes the texts using internal vocabulary. The list structure is maintained.
Args:
encoded_texts: The list of texts to decode.
unknown_token: The placeholder value for unknown token. (Default value:... | def decode_texts(self, encoded_texts, unknown_token="<UNK>", inplace=True):
"""Decodes the texts using internal vocabulary. The list structure is maintained.
Args:
encoded_texts: The list of texts to decode.
unknown_token: The placeholder value for unknown token. (Default value:... | [
"Decodes",
"the",
"texts",
"using",
"internal",
"vocabulary",
".",
"The",
"list",
"structure",
"is",
"maintained",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L153-L176 | [
"def",
"decode_texts",
"(",
"self",
",",
"encoded_texts",
",",
"unknown_token",
"=",
"\"<UNK>\"",
",",
"inplace",
"=",
"True",
")",
":",
"if",
"len",
"(",
"self",
".",
"_token2idx",
")",
"==",
"0",
":",
"raise",
"ValueError",
"(",
"\"You need to build vocabu... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.build_vocab | Builds the internal vocabulary and computes various statistics.
Args:
texts: The list of text items to encode.
verbose: The verbosity level for progress. Can be 0, 1, 2. (Default value = 1)
**kwargs: The kwargs for `token_generator`. | texcla/preprocessing/tokenizer.py | def build_vocab(self, texts, verbose=1, **kwargs):
"""Builds the internal vocabulary and computes various statistics.
Args:
texts: The list of text items to encode.
verbose: The verbosity level for progress. Can be 0, 1, 2. (Default value = 1)
**kwargs: The kwargs fo... | def build_vocab(self, texts, verbose=1, **kwargs):
"""Builds the internal vocabulary and computes various statistics.
Args:
texts: The list of text items to encode.
verbose: The verbosity level for progress. Can be 0, 1, 2. (Default value = 1)
**kwargs: The kwargs fo... | [
"Builds",
"the",
"internal",
"vocabulary",
"and",
"computes",
"various",
"statistics",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L207-L239 | [
"def",
"build_vocab",
"(",
"self",
",",
"texts",
",",
"verbose",
"=",
"1",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"self",
".",
"has_vocab",
":",
"logger",
".",
"warn",
"(",
"\"Tokenizer already has existing vocabulary. Overriding and building new vocabulary.\"",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.pad_sequences | Pads each sequence to the same fixed length (length of the longest sequence or provided override).
Args:
sequences: list of list (samples, words) or list of list of list (samples, sentences, words)
fixed_sentences_seq_length: The fix sentence sequence length to use. If None, largest sen... | texcla/preprocessing/tokenizer.py | def pad_sequences(self, sequences, fixed_sentences_seq_length=None, fixed_token_seq_length=None,
padding='pre', truncating='post', padding_token="<PAD>"):
"""Pads each sequence to the same fixed length (length of the longest sequence or provided override).
Args:
sequen... | def pad_sequences(self, sequences, fixed_sentences_seq_length=None, fixed_token_seq_length=None,
padding='pre', truncating='post', padding_token="<PAD>"):
"""Pads each sequence to the same fixed length (length of the longest sequence or provided override).
Args:
sequen... | [
"Pads",
"each",
"sequence",
"to",
"the",
"same",
"fixed",
"length",
"(",
"length",
"of",
"the",
"longest",
"sequence",
"or",
"provided",
"override",
")",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L241-L271 | [
"def",
"pad_sequences",
"(",
"self",
",",
"sequences",
",",
"fixed_sentences_seq_length",
"=",
"None",
",",
"fixed_token_seq_length",
"=",
"None",
",",
"padding",
"=",
"'pre'",
",",
"truncating",
"=",
"'post'",
",",
"padding_token",
"=",
"\"<PAD>\"",
")",
":",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Tokenizer.get_stats | Gets the standard statistics for aux_index `i`. For example, if `token_generator` generates
`(text_idx, sentence_idx, word)`, then `get_stats(0)` will return various statistics about sentence lengths
across texts. Similarly, `get_counts(1)` will return statistics of token lengths across sentences.
... | texcla/preprocessing/tokenizer.py | def get_stats(self, i):
"""Gets the standard statistics for aux_index `i`. For example, if `token_generator` generates
`(text_idx, sentence_idx, word)`, then `get_stats(0)` will return various statistics about sentence lengths
across texts. Similarly, `get_counts(1)` will return statistics of to... | def get_stats(self, i):
"""Gets the standard statistics for aux_index `i`. For example, if `token_generator` generates
`(text_idx, sentence_idx, word)`, then `get_stats(0)` will return various statistics about sentence lengths
across texts. Similarly, `get_counts(1)` will return statistics of to... | [
"Gets",
"the",
"standard",
"statistics",
"for",
"aux_index",
"i",
".",
"For",
"example",
"if",
"token_generator",
"generates",
"(",
"text_idx",
"sentence_idx",
"word",
")",
"then",
"get_stats",
"(",
"0",
")",
"will",
"return",
"various",
"statistics",
"about",
... | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/tokenizer.py#L286-L299 | [
"def",
"get_stats",
"(",
"self",
",",
"i",
")",
":",
"# OrderedDict to always show same order if printed.",
"result",
"=",
"OrderedDict",
"(",
")",
"result",
"[",
"'min'",
"]",
"=",
"np",
".",
"min",
"(",
"self",
".",
"_counts",
"[",
"i",
"]",
")",
"result... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | build_embedding_weights | Builds an embedding matrix for all words in vocab using embeddings_index | texcla/embeddings.py | def build_embedding_weights(word_index, embeddings_index):
"""Builds an embedding matrix for all words in vocab using embeddings_index
"""
logger.info('Loading embeddings for all words in the corpus')
embedding_dim = list(embeddings_index.values())[0].shape[-1]
# setting special tokens such as UNK ... | def build_embedding_weights(word_index, embeddings_index):
"""Builds an embedding matrix for all words in vocab using embeddings_index
"""
logger.info('Loading embeddings for all words in the corpus')
embedding_dim = list(embeddings_index.values())[0].shape[-1]
# setting special tokens such as UNK ... | [
"Builds",
"an",
"embedding",
"matrix",
"for",
"all",
"words",
"in",
"vocab",
"using",
"embeddings_index"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/embeddings.py#L146-L161 | [
"def",
"build_embedding_weights",
"(",
"word_index",
",",
"embeddings_index",
")",
":",
"logger",
".",
"info",
"(",
"'Loading embeddings for all words in the corpus'",
")",
"embedding_dim",
"=",
"list",
"(",
"embeddings_index",
".",
"values",
"(",
")",
")",
"[",
"0"... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | build_fasttext_wiki_embedding_obj | FastText pre-trained word vectors for 294 languages, with 300 dimensions, trained on Wikipedia. It's recommended to use the same tokenizer for your data that was used to construct the embeddings. It's implemented as 'FasttextWikiTokenizer'. More information: https://fasttext.cc/docs/en/pretrained-vectors.html.
Arg... | texcla/embeddings.py | def build_fasttext_wiki_embedding_obj(embedding_type):
"""FastText pre-trained word vectors for 294 languages, with 300 dimensions, trained on Wikipedia. It's recommended to use the same tokenizer for your data that was used to construct the embeddings. It's implemented as 'FasttextWikiTokenizer'. More information:... | def build_fasttext_wiki_embedding_obj(embedding_type):
"""FastText pre-trained word vectors for 294 languages, with 300 dimensions, trained on Wikipedia. It's recommended to use the same tokenizer for your data that was used to construct the embeddings. It's implemented as 'FasttextWikiTokenizer'. More information:... | [
"FastText",
"pre",
"-",
"trained",
"word",
"vectors",
"for",
"294",
"languages",
"with",
"300",
"dimensions",
"trained",
"on",
"Wikipedia",
".",
"It",
"s",
"recommended",
"to",
"use",
"the",
"same",
"tokenizer",
"for",
"your",
"data",
"that",
"was",
"used",
... | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/embeddings.py#L164-L177 | [
"def",
"build_fasttext_wiki_embedding_obj",
"(",
"embedding_type",
")",
":",
"lang",
"=",
"embedding_type",
".",
"split",
"(",
"'.'",
")",
"[",
"2",
"]",
"return",
"{",
"'file'",
":",
"'wiki.{}.vec'",
".",
"format",
"(",
"lang",
")",
",",
"'url'",
":",
"'h... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | build_fasttext_cc_embedding_obj | FastText pre-trained word vectors for 157 languages, with 300 dimensions, trained on Common Crawl and Wikipedia. Released in 2018, it succeesed the 2017 FastText Wikipedia embeddings. It's recommended to use the same tokenizer for your data that was used to construct the embeddings. This information and more can be fin... | texcla/embeddings.py | def build_fasttext_cc_embedding_obj(embedding_type):
"""FastText pre-trained word vectors for 157 languages, with 300 dimensions, trained on Common Crawl and Wikipedia. Released in 2018, it succeesed the 2017 FastText Wikipedia embeddings. It's recommended to use the same tokenizer for your data that was used to co... | def build_fasttext_cc_embedding_obj(embedding_type):
"""FastText pre-trained word vectors for 157 languages, with 300 dimensions, trained on Common Crawl and Wikipedia. Released in 2018, it succeesed the 2017 FastText Wikipedia embeddings. It's recommended to use the same tokenizer for your data that was used to co... | [
"FastText",
"pre",
"-",
"trained",
"word",
"vectors",
"for",
"157",
"languages",
"with",
"300",
"dimensions",
"trained",
"on",
"Common",
"Crawl",
"and",
"Wikipedia",
".",
"Released",
"in",
"2018",
"it",
"succeesed",
"the",
"2017",
"FastText",
"Wikipedia",
"emb... | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/embeddings.py#L180-L193 | [
"def",
"build_fasttext_cc_embedding_obj",
"(",
"embedding_type",
")",
":",
"lang",
"=",
"embedding_type",
".",
"split",
"(",
"'.'",
")",
"[",
"2",
"]",
"return",
"{",
"'file'",
":",
"'cc.{}.300.vec.gz'",
".",
"format",
"(",
"lang",
")",
",",
"'url'",
":",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | get_embeddings_index | Retrieves embeddings index from embedding name or path. Will automatically download and cache as needed.
Args:
embedding_type: The embedding type to load.
embedding_path: Path to a local embedding to use instead of the embedding type. Ignores `embedding_type` if specified.
Returns:
The... | texcla/embeddings.py | def get_embeddings_index(embedding_type='glove.42B.300d', embedding_dims=None, embedding_path=None, cache=True):
"""Retrieves embeddings index from embedding name or path. Will automatically download and cache as needed.
Args:
embedding_type: The embedding type to load.
embedding_path: Path to ... | def get_embeddings_index(embedding_type='glove.42B.300d', embedding_dims=None, embedding_path=None, cache=True):
"""Retrieves embeddings index from embedding name or path. Will automatically download and cache as needed.
Args:
embedding_type: The embedding type to load.
embedding_path: Path to ... | [
"Retrieves",
"embeddings",
"index",
"from",
"embedding",
"name",
"or",
"path",
".",
"Will",
"automatically",
"download",
"and",
"cache",
"as",
"needed",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/embeddings.py#L211-L257 | [
"def",
"get_embeddings_index",
"(",
"embedding_type",
"=",
"'glove.42B.300d'",
",",
"embedding_dims",
"=",
"None",
",",
"embedding_path",
"=",
"None",
",",
"cache",
"=",
"True",
")",
":",
"if",
"embedding_path",
"is",
"not",
"None",
":",
"embedding_type",
"=",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | CharTokenizer.token_generator | Yields tokens from texts as `(text_idx, character)` | texcla/preprocessing/char_tokenizer.py | def token_generator(self, texts, **kwargs):
"""Yields tokens from texts as `(text_idx, character)`
"""
for text_idx, text in enumerate(texts):
if self.lower:
text = text.lower()
for char in text:
yield text_idx, char | def token_generator(self, texts, **kwargs):
"""Yields tokens from texts as `(text_idx, character)`
"""
for text_idx, text in enumerate(texts):
if self.lower:
text = text.lower()
for char in text:
yield text_idx, char | [
"Yields",
"tokens",
"from",
"texts",
"as",
"(",
"text_idx",
"character",
")"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/char_tokenizer.py#L27-L34 | [
"def",
"token_generator",
"(",
"self",
",",
"texts",
",",
"*",
"*",
"kwargs",
")",
":",
"for",
"text_idx",
",",
"text",
"in",
"enumerate",
"(",
"texts",
")",
":",
"if",
"self",
".",
"lower",
":",
"text",
"=",
"text",
".",
"lower",
"(",
")",
"for",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | SentenceCharTokenizer.token_generator | Yields tokens from texts as `(text_idx, sent_idx, character)`
Args:
texts: The list of texts.
**kwargs: Supported args include:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_size: The number of texts to accumulate in... | texcla/preprocessing/char_tokenizer.py | def token_generator(self, texts, **kwargs):
"""Yields tokens from texts as `(text_idx, sent_idx, character)`
Args:
texts: The list of texts.
**kwargs: Supported args include:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
... | def token_generator(self, texts, **kwargs):
"""Yields tokens from texts as `(text_idx, sent_idx, character)`
Args:
texts: The list of texts.
**kwargs: Supported args include:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
... | [
"Yields",
"tokens",
"from",
"texts",
"as",
"(",
"text_idx",
"sent_idx",
"character",
")"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/char_tokenizer.py#L53-L80 | [
"def",
"token_generator",
"(",
"self",
",",
"texts",
",",
"*",
"*",
"kwargs",
")",
":",
"# Perf optimization. Only process what is necessary.",
"n_threads",
",",
"batch_size",
"=",
"utils",
".",
"_parse_spacy_kwargs",
"(",
"*",
"*",
"kwargs",
")",
"nlp",
"=",
"s... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | equal_distribution_folds | Creates `folds` number of indices that has roughly balanced multi-label distribution.
Args:
y: The multi-label outputs.
folds: The number of folds to create.
Returns:
`folds` number of indices that have roughly equal multi-label distributions. | texcla/utils/sampling.py | def equal_distribution_folds(y, folds=2):
"""Creates `folds` number of indices that has roughly balanced multi-label distribution.
Args:
y: The multi-label outputs.
folds: The number of folds to create.
Returns:
`folds` number of indices that have roughly equal multi-label distribu... | def equal_distribution_folds(y, folds=2):
"""Creates `folds` number of indices that has roughly balanced multi-label distribution.
Args:
y: The multi-label outputs.
folds: The number of folds to create.
Returns:
`folds` number of indices that have roughly equal multi-label distribu... | [
"Creates",
"folds",
"number",
"of",
"indices",
"that",
"has",
"roughly",
"balanced",
"multi",
"-",
"label",
"distribution",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/utils/sampling.py#L11-L44 | [
"def",
"equal_distribution_folds",
"(",
"y",
",",
"folds",
"=",
"2",
")",
":",
"n",
",",
"classes",
"=",
"y",
".",
"shape",
"# Compute sample distribution over classes",
"dist",
"=",
"y",
".",
"sum",
"(",
"axis",
"=",
"0",
")",
".",
"astype",
"(",
"'floa... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | SentenceModelFactory.build_model | Builds a model that first encodes all words within sentences using `token_encoder_model`, followed by
`sentence_encoder_model`.
Args:
token_encoder_model: An instance of `SequenceEncoderBase` for encoding tokens within sentences. This model
will be applied across all sentenc... | texcla/models/sentence_model.py | def build_model(self, token_encoder_model, sentence_encoder_model,
trainable_embeddings=True, output_activation='softmax'):
"""Builds a model that first encodes all words within sentences using `token_encoder_model`, followed by
`sentence_encoder_model`.
Args:
to... | def build_model(self, token_encoder_model, sentence_encoder_model,
trainable_embeddings=True, output_activation='softmax'):
"""Builds a model that first encodes all words within sentences using `token_encoder_model`, followed by
`sentence_encoder_model`.
Args:
to... | [
"Builds",
"a",
"model",
"that",
"first",
"encodes",
"all",
"words",
"within",
"sentences",
"using",
"token_encoder_model",
"followed",
"by",
"sentence_encoder_model",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/models/sentence_model.py#L45-L104 | [
"def",
"build_model",
"(",
"self",
",",
"token_encoder_model",
",",
"sentence_encoder_model",
",",
"trainable_embeddings",
"=",
"True",
",",
"output_activation",
"=",
"'softmax'",
")",
":",
"if",
"not",
"isinstance",
"(",
"token_encoder_model",
",",
"SequenceEncoderBa... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | process_save | Process text and save as Dataset | texcla/experiment.py | def process_save(X, y, tokenizer, proc_data_path, max_len=400, train=False, ngrams=None, limit_top_tokens=None):
"""Process text and save as Dataset
"""
if train and limit_top_tokens is not None:
tokenizer.apply_encoding_options(limit_top_tokens=limit_top_tokens)
X_encoded = tokenizer.encode_te... | def process_save(X, y, tokenizer, proc_data_path, max_len=400, train=False, ngrams=None, limit_top_tokens=None):
"""Process text and save as Dataset
"""
if train and limit_top_tokens is not None:
tokenizer.apply_encoding_options(limit_top_tokens=limit_top_tokens)
X_encoded = tokenizer.encode_te... | [
"Process",
"text",
"and",
"save",
"as",
"Dataset"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/experiment.py#L106-L126 | [
"def",
"process_save",
"(",
"X",
",",
"y",
",",
"tokenizer",
",",
"proc_data_path",
",",
"max_len",
"=",
"400",
",",
"train",
"=",
"False",
",",
"ngrams",
"=",
"None",
",",
"limit_top_tokens",
"=",
"None",
")",
":",
"if",
"train",
"and",
"limit_top_token... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | setup_data | Setup data
Args:
X: text data,
y: data labels,
tokenizer: A Tokenizer instance
proc_data_path: Path for the processed data | texcla/experiment.py | def setup_data(X, y, tokenizer, proc_data_path, **kwargs):
"""Setup data
Args:
X: text data,
y: data labels,
tokenizer: A Tokenizer instance
proc_data_path: Path for the processed data
"""
# only build vocabulary once (e.g. training data)
train = ... | def setup_data(X, y, tokenizer, proc_data_path, **kwargs):
"""Setup data
Args:
X: text data,
y: data labels,
tokenizer: A Tokenizer instance
proc_data_path: Path for the processed data
"""
# only build vocabulary once (e.g. training data)
train = ... | [
"Setup",
"data"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/experiment.py#L129-L145 | [
"def",
"setup_data",
"(",
"X",
",",
"y",
",",
"tokenizer",
",",
"proc_data_path",
",",
"*",
"*",
"kwargs",
")",
":",
"# only build vocabulary once (e.g. training data)",
"train",
"=",
"not",
"tokenizer",
".",
"has_vocab",
"if",
"train",
":",
"tokenizer",
".",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | split_data | Splits data into a training, validation, and test set.
Args:
X: text data
y: data labels
ratio: the ratio for splitting. Default: (0.8, 0.1, 0.1)
Returns:
split data: X_train, X_val, X_test, y_train, y_val, y_test | texcla/experiment.py | def split_data(X, y, ratio=(0.8, 0.1, 0.1)):
"""Splits data into a training, validation, and test set.
Args:
X: text data
y: data labels
ratio: the ratio for splitting. Default: (0.8, 0.1, 0.1)
Returns:
split data: X_train, X_val, X_test, y_train, y_... | def split_data(X, y, ratio=(0.8, 0.1, 0.1)):
"""Splits data into a training, validation, and test set.
Args:
X: text data
y: data labels
ratio: the ratio for splitting. Default: (0.8, 0.1, 0.1)
Returns:
split data: X_train, X_val, X_test, y_train, y_... | [
"Splits",
"data",
"into",
"a",
"training",
"validation",
"and",
"test",
"set",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/experiment.py#L148-L164 | [
"def",
"split_data",
"(",
"X",
",",
"y",
",",
"ratio",
"=",
"(",
"0.8",
",",
"0.1",
",",
"0.1",
")",
")",
":",
"assert",
"(",
"sum",
"(",
"ratio",
")",
"==",
"1",
"and",
"len",
"(",
"ratio",
")",
"==",
"3",
")",
"X_train",
",",
"X_rest",
",",... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | setup_data_split | Setup data while splitting into a training, validation, and test set.
Args:
X: text data,
y: data labels,
tokenizer: A Tokenizer instance
proc_data_dir: Directory for the split and processed data | texcla/experiment.py | def setup_data_split(X, y, tokenizer, proc_data_dir, **kwargs):
"""Setup data while splitting into a training, validation, and test set.
Args:
X: text data,
y: data labels,
tokenizer: A Tokenizer instance
proc_data_dir: Directory for the split and processed d... | def setup_data_split(X, y, tokenizer, proc_data_dir, **kwargs):
"""Setup data while splitting into a training, validation, and test set.
Args:
X: text data,
y: data labels,
tokenizer: A Tokenizer instance
proc_data_dir: Directory for the split and processed d... | [
"Setup",
"data",
"while",
"splitting",
"into",
"a",
"training",
"validation",
"and",
"test",
"set",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/experiment.py#L167-L186 | [
"def",
"setup_data_split",
"(",
"X",
",",
"y",
",",
"tokenizer",
",",
"proc_data_dir",
",",
"*",
"*",
"kwargs",
")",
":",
"X_train",
",",
"X_val",
",",
"X_test",
",",
"y_train",
",",
"y_val",
",",
"y_test",
"=",
"split_data",
"(",
"X",
",",
"y",
")",... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | load_data_split | Loads a split dataset
Args:
proc_data_dir: Directory with the split and processed data
Returns:
(Training Data, Validation Data, Test Data) | texcla/experiment.py | def load_data_split(proc_data_dir):
"""Loads a split dataset
Args:
proc_data_dir: Directory with the split and processed data
Returns:
(Training Data, Validation Data, Test Data)
"""
ds_train = Dataset.load(path.join(proc_data_dir, 'train.bin'))
ds_val = Dataset... | def load_data_split(proc_data_dir):
"""Loads a split dataset
Args:
proc_data_dir: Directory with the split and processed data
Returns:
(Training Data, Validation Data, Test Data)
"""
ds_train = Dataset.load(path.join(proc_data_dir, 'train.bin'))
ds_val = Dataset... | [
"Loads",
"a",
"split",
"dataset"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/experiment.py#L189-L201 | [
"def",
"load_data_split",
"(",
"proc_data_dir",
")",
":",
"ds_train",
"=",
"Dataset",
".",
"load",
"(",
"path",
".",
"join",
"(",
"proc_data_dir",
",",
"'train.bin'",
")",
")",
"ds_val",
"=",
"Dataset",
".",
"load",
"(",
"path",
".",
"join",
"(",
"proc_d... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | TokenModelFactory.build_model | Builds a model using the given `text_model`
Args:
token_encoder_model: An instance of `SequenceEncoderBase` for encoding all the tokens within a document.
This encoding is then fed into a final `Dense` layer for classification.
trainable_embeddings: Whether or not to fin... | texcla/models/token_model.py | def build_model(self, token_encoder_model, trainable_embeddings=True, output_activation='softmax'):
"""Builds a model using the given `text_model`
Args:
token_encoder_model: An instance of `SequenceEncoderBase` for encoding all the tokens within a document.
This encoding is ... | def build_model(self, token_encoder_model, trainable_embeddings=True, output_activation='softmax'):
"""Builds a model using the given `text_model`
Args:
token_encoder_model: An instance of `SequenceEncoderBase` for encoding all the tokens within a document.
This encoding is ... | [
"Builds",
"a",
"model",
"using",
"the",
"given",
"text_model"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/models/token_model.py#L39-L83 | [
"def",
"build_model",
"(",
"self",
",",
"token_encoder_model",
",",
"trainable_embeddings",
"=",
"True",
",",
"output_activation",
"=",
"'softmax'",
")",
":",
"if",
"not",
"isinstance",
"(",
"token_encoder_model",
",",
"SequenceEncoderBase",
")",
":",
"raise",
"Va... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | _softmax | Computes softmax along a specified dim. Keras currently lacks this feature. | texcla/models/layers.py | def _softmax(x, dim):
"""Computes softmax along a specified dim. Keras currently lacks this feature.
"""
if K.backend() == 'tensorflow':
import tensorflow as tf
return tf.nn.softmax(x, dim)
elif K.backend() is 'cntk':
import cntk
return cntk.softmax(x, dim)
elif K.ba... | def _softmax(x, dim):
"""Computes softmax along a specified dim. Keras currently lacks this feature.
"""
if K.backend() == 'tensorflow':
import tensorflow as tf
return tf.nn.softmax(x, dim)
elif K.backend() is 'cntk':
import cntk
return cntk.softmax(x, dim)
elif K.ba... | [
"Computes",
"softmax",
"along",
"a",
"specified",
"dim",
".",
"Keras",
"currently",
"lacks",
"this",
"feature",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/models/layers.py#L10-L33 | [
"def",
"_softmax",
"(",
"x",
",",
"dim",
")",
":",
"if",
"K",
".",
"backend",
"(",
")",
"==",
"'tensorflow'",
":",
"import",
"tensorflow",
"as",
"tf",
"return",
"tf",
".",
"nn",
".",
"softmax",
"(",
"x",
",",
"dim",
")",
"elif",
"K",
".",
"backen... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | SpacyTokenizer._apply_options | Applies various filtering and processing options on token.
Returns:
The processed token. None if filtered. | texcla/preprocessing/word_tokenizer.py | def _apply_options(self, token):
"""Applies various filtering and processing options on token.
Returns:
The processed token. None if filtered.
"""
# Apply work token filtering.
if token.is_punct and self.remove_punct:
return None
if token.is_stop ... | def _apply_options(self, token):
"""Applies various filtering and processing options on token.
Returns:
The processed token. None if filtered.
"""
# Apply work token filtering.
if token.is_punct and self.remove_punct:
return None
if token.is_stop ... | [
"Applies",
"various",
"filtering",
"and",
"processing",
"options",
"on",
"token",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/word_tokenizer.py#L52-L77 | [
"def",
"_apply_options",
"(",
"self",
",",
"token",
")",
":",
"# Apply work token filtering.",
"if",
"token",
".",
"is_punct",
"and",
"self",
".",
"remove_punct",
":",
"return",
"None",
"if",
"token",
".",
"is_stop",
"and",
"self",
".",
"remove_stop_words",
":... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | SpacyTokenizer.token_generator | Yields tokens from texts as `(text_idx, word)`
Args:
texts: The list of texts.
**kwargs: Supported args include:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_size: The number of texts to accumulate into a common wor... | texcla/preprocessing/word_tokenizer.py | def token_generator(self, texts, **kwargs):
"""Yields tokens from texts as `(text_idx, word)`
Args:
texts: The list of texts.
**kwargs: Supported args include:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_si... | def token_generator(self, texts, **kwargs):
"""Yields tokens from texts as `(text_idx, word)`
Args:
texts: The list of texts.
**kwargs: Supported args include:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_si... | [
"Yields",
"tokens",
"from",
"texts",
"as",
"(",
"text_idx",
"word",
")"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/word_tokenizer.py#L79-L107 | [
"def",
"token_generator",
"(",
"self",
",",
"texts",
",",
"*",
"*",
"kwargs",
")",
":",
"# Perf optimization. Only process what is necessary.",
"n_threads",
",",
"batch_size",
"=",
"utils",
".",
"_parse_spacy_kwargs",
"(",
"*",
"*",
"kwargs",
")",
"nlp",
"=",
"s... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | _append | Adds `value` to `lst` list indexed by `indices`. Will create sub lists as required. | texcla/preprocessing/utils.py | def _append(lst, indices, value):
"""Adds `value` to `lst` list indexed by `indices`. Will create sub lists as required.
"""
for i, idx in enumerate(indices):
# We need to loop because sometimes indices can increment by more than 1 due to missing tokens.
# Example: Sentence with no words aft... | def _append(lst, indices, value):
"""Adds `value` to `lst` list indexed by `indices`. Will create sub lists as required.
"""
for i, idx in enumerate(indices):
# We need to loop because sometimes indices can increment by more than 1 due to missing tokens.
# Example: Sentence with no words aft... | [
"Adds",
"value",
"to",
"lst",
"list",
"indexed",
"by",
"indices",
".",
"Will",
"create",
"sub",
"lists",
"as",
"required",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/utils.py#L82-L95 | [
"def",
"_append",
"(",
"lst",
",",
"indices",
",",
"value",
")",
":",
"for",
"i",
",",
"idx",
"in",
"enumerate",
"(",
"indices",
")",
":",
"# We need to loop because sometimes indices can increment by more than 1 due to missing tokens.",
"# Example: Sentence with no words a... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | _parse_spacy_kwargs | Supported args include:
Args:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_size: The number of texts to accumulate into a common working set before processing.
(Default value: 1000) | texcla/preprocessing/utils.py | def _parse_spacy_kwargs(**kwargs):
"""Supported args include:
Args:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_size: The number of texts to accumulate into a common working set before processing.
(Default value: 1000)
"""
n_threads =... | def _parse_spacy_kwargs(**kwargs):
"""Supported args include:
Args:
n_threads/num_threads: Number of threads to use. Uses num_cpus - 1 by default.
batch_size: The number of texts to accumulate into a common working set before processing.
(Default value: 1000)
"""
n_threads =... | [
"Supported",
"args",
"include",
":"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/utils.py#L113-L128 | [
"def",
"_parse_spacy_kwargs",
"(",
"*",
"*",
"kwargs",
")",
":",
"n_threads",
"=",
"kwargs",
".",
"get",
"(",
"'n_threads'",
")",
"or",
"kwargs",
".",
"get",
"(",
"'num_threads'",
")",
"batch_size",
"=",
"kwargs",
".",
"get",
"(",
"'batch_size'",
")",
"i... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | _CountTracker.update | Updates counts based on indices. The algorithm tracks the index change at i and
update global counts for all indices beyond i with local counts tracked so far. | texcla/preprocessing/utils.py | def update(self, indices):
"""Updates counts based on indices. The algorithm tracks the index change at i and
update global counts for all indices beyond i with local counts tracked so far.
"""
# Initialize various lists for the first time based on length of indices.
if self._pre... | def update(self, indices):
"""Updates counts based on indices. The algorithm tracks the index change at i and
update global counts for all indices beyond i with local counts tracked so far.
"""
# Initialize various lists for the first time based on length of indices.
if self._pre... | [
"Updates",
"counts",
"based",
"on",
"indices",
".",
"The",
"algorithm",
"tracks",
"the",
"index",
"change",
"at",
"i",
"and",
"update",
"global",
"counts",
"for",
"all",
"indices",
"beyond",
"i",
"with",
"local",
"counts",
"tracked",
"so",
"far",
"."
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/utils.py#L34-L62 | [
"def",
"update",
"(",
"self",
",",
"indices",
")",
":",
"# Initialize various lists for the first time based on length of indices.",
"if",
"self",
".",
"_prev_indices",
"is",
"None",
":",
"self",
".",
"_prev_indices",
"=",
"indices",
"# +1 to track token counts in the last ... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | _CountTracker.finalize | This will add the very last document to counts. We also get rid of counts[0] since that
represents document level which doesnt come under anything else. We also convert all count
values to numpy arrays so that stats can be computed easily. | texcla/preprocessing/utils.py | def finalize(self):
"""This will add the very last document to counts. We also get rid of counts[0] since that
represents document level which doesnt come under anything else. We also convert all count
values to numpy arrays so that stats can be computed easily.
"""
for i in rang... | def finalize(self):
"""This will add the very last document to counts. We also get rid of counts[0] since that
represents document level which doesnt come under anything else. We also convert all count
values to numpy arrays so that stats can be computed easily.
"""
for i in rang... | [
"This",
"will",
"add",
"the",
"very",
"last",
"document",
"to",
"counts",
".",
"We",
"also",
"get",
"rid",
"of",
"counts",
"[",
"0",
"]",
"since",
"that",
"represents",
"document",
"level",
"which",
"doesnt",
"come",
"under",
"anything",
"else",
".",
"We... | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/preprocessing/utils.py#L64-L74 | [
"def",
"finalize",
"(",
"self",
")",
":",
"for",
"i",
"in",
"range",
"(",
"1",
",",
"len",
"(",
"self",
".",
"_local_counts",
")",
")",
":",
"self",
".",
"counts",
"[",
"i",
"]",
".",
"append",
"(",
"self",
".",
"_local_counts",
"[",
"i",
"]",
... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | read_folder | read text files in directory and returns them as array
Args:
directory: where the text files are
Returns:
Array of text | texcla/corpus.py | def read_folder(directory):
"""read text files in directory and returns them as array
Args:
directory: where the text files are
Returns:
Array of text
"""
res = []
for filename in os.listdir(directory):
with io.open(os.path.join(directory, filename), encoding="utf-8") a... | def read_folder(directory):
"""read text files in directory and returns them as array
Args:
directory: where the text files are
Returns:
Array of text
"""
res = []
for filename in os.listdir(directory):
with io.open(os.path.join(directory, filename), encoding="utf-8") a... | [
"read",
"text",
"files",
"in",
"directory",
"and",
"returns",
"them",
"as",
"array"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/corpus.py#L8-L22 | [
"def",
"read_folder",
"(",
"directory",
")",
":",
"res",
"=",
"[",
"]",
"for",
"filename",
"in",
"os",
".",
"listdir",
"(",
"directory",
")",
":",
"with",
"io",
".",
"open",
"(",
"os",
".",
"path",
".",
"join",
"(",
"directory",
",",
"filename",
")... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | read_pos_neg_data | returns array with positive and negative examples | texcla/corpus.py | def read_pos_neg_data(path, folder, limit):
"""returns array with positive and negative examples"""
training_pos_path = os.path.join(path, folder, 'pos')
training_neg_path = os.path.join(path, folder, 'neg')
X_pos = read_folder(training_pos_path)
X_neg = read_folder(training_neg_path)
if limit... | def read_pos_neg_data(path, folder, limit):
"""returns array with positive and negative examples"""
training_pos_path = os.path.join(path, folder, 'pos')
training_neg_path = os.path.join(path, folder, 'neg')
X_pos = read_folder(training_pos_path)
X_neg = read_folder(training_neg_path)
if limit... | [
"returns",
"array",
"with",
"positive",
"and",
"negative",
"examples"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/corpus.py#L25-L40 | [
"def",
"read_pos_neg_data",
"(",
"path",
",",
"folder",
",",
"limit",
")",
":",
"training_pos_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"path",
",",
"folder",
",",
"'pos'",
")",
"training_neg_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"pat... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | imdb | Downloads (and caches) IMDB Moview Reviews. 25k training data, 25k test data
Args:
limit: get only first N items for each class
Returns:
[X_train, y_train, X_test, y_test] | texcla/corpus.py | def imdb(limit=None, shuffle=True):
"""Downloads (and caches) IMDB Moview Reviews. 25k training data, 25k test data
Args:
limit: get only first N items for each class
Returns:
[X_train, y_train, X_test, y_test]
"""
movie_review_url = 'http://ai.stanford.edu/~amaas/data/sentiment/a... | def imdb(limit=None, shuffle=True):
"""Downloads (and caches) IMDB Moview Reviews. 25k training data, 25k test data
Args:
limit: get only first N items for each class
Returns:
[X_train, y_train, X_test, y_test]
"""
movie_review_url = 'http://ai.stanford.edu/~amaas/data/sentiment/a... | [
"Downloads",
"(",
"and",
"caches",
")",
"IMDB",
"Moview",
"Reviews",
".",
"25k",
"training",
"data",
"25k",
"test",
"data"
] | jfilter/text-classification-keras | python | https://github.com/jfilter/text-classification-keras/blob/a59c652805da41d18937c7fdad0d9fd943cf8578/texcla/corpus.py#L43-L66 | [
"def",
"imdb",
"(",
"limit",
"=",
"None",
",",
"shuffle",
"=",
"True",
")",
":",
"movie_review_url",
"=",
"'http://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz'",
"# download and extract, thus remove the suffix '.tar.gz'",
"path",
"=",
"keras",
".",
"utils",
".",... | a59c652805da41d18937c7fdad0d9fd943cf8578 |
train | Dial.to_absolute | Converts coordinates provided with reference to the center \
of the canvas (0, 0) to absolute coordinates which are used \
by the canvas object in which (0, 0) is located in the top \
left of the object.
:param x: x value in pixels
:param y: x value in pixels
:return: No... | tk_tools/canvas.py | def to_absolute(self, x, y):
"""
Converts coordinates provided with reference to the center \
of the canvas (0, 0) to absolute coordinates which are used \
by the canvas object in which (0, 0) is located in the top \
left of the object.
:param x: x value in pixels
... | def to_absolute(self, x, y):
"""
Converts coordinates provided with reference to the center \
of the canvas (0, 0) to absolute coordinates which are used \
by the canvas object in which (0, 0) is located in the top \
left of the object.
:param x: x value in pixels
... | [
"Converts",
"coordinates",
"provided",
"with",
"reference",
"to",
"the",
"center",
"\\",
"of",
"the",
"canvas",
"(",
"0",
"0",
")",
"to",
"absolute",
"coordinates",
"which",
"are",
"used",
"\\",
"by",
"the",
"canvas",
"object",
"in",
"which",
"(",
"0",
"... | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L43-L54 | [
"def",
"to_absolute",
"(",
"self",
",",
"x",
",",
"y",
")",
":",
"return",
"x",
"+",
"self",
".",
"size",
"/",
"2",
",",
"y",
"+",
"self",
".",
"size",
"/",
"2"
] | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | RotaryScale.set_value | Sets the value of the graphic
:param number: the number (must be between 0 and \
'max_range' or the scale will peg the limits
:return: None | tk_tools/canvas.py | def set_value(self, number: (float, int)):
"""
Sets the value of the graphic
:param number: the number (must be between 0 and \
'max_range' or the scale will peg the limits
:return: None
"""
self.canvas.delete('all')
self.canvas.create_image(0, 0, image=s... | def set_value(self, number: (float, int)):
"""
Sets the value of the graphic
:param number: the number (must be between 0 and \
'max_range' or the scale will peg the limits
:return: None
"""
self.canvas.delete('all')
self.canvas.create_image(0, 0, image=s... | [
"Sets",
"the",
"value",
"of",
"the",
"graphic"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L112-L145 | [
"def",
"set_value",
"(",
"self",
",",
"number",
":",
"(",
"float",
",",
"int",
")",
")",
":",
"self",
".",
"canvas",
".",
"delete",
"(",
"'all'",
")",
"self",
".",
"canvas",
".",
"create_image",
"(",
"0",
",",
"0",
",",
"image",
"=",
"self",
".",... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | RotaryScale._draw_background | Draws the background of the dial
:param divisions: the number of divisions
between 'ticks' shown on the dial
:return: None | tk_tools/canvas.py | def _draw_background(self, divisions=10):
"""
Draws the background of the dial
:param divisions: the number of divisions
between 'ticks' shown on the dial
:return: None
"""
self.canvas.create_arc(2, 2, self.size-2, self.size-2,
styl... | def _draw_background(self, divisions=10):
"""
Draws the background of the dial
:param divisions: the number of divisions
between 'ticks' shown on the dial
:return: None
"""
self.canvas.create_arc(2, 2, self.size-2, self.size-2,
styl... | [
"Draws",
"the",
"background",
"of",
"the",
"dial"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L147-L179 | [
"def",
"_draw_background",
"(",
"self",
",",
"divisions",
"=",
"10",
")",
":",
"self",
".",
"canvas",
".",
"create_arc",
"(",
"2",
",",
"2",
",",
"self",
".",
"size",
"-",
"2",
",",
"self",
".",
"size",
"-",
"2",
",",
"style",
"=",
"tk",
".",
"... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Graph.draw_axes | Removes all existing series and re-draws the axes.
:return: None | tk_tools/canvas.py | def draw_axes(self):
"""
Removes all existing series and re-draws the axes.
:return: None
"""
self.canvas.delete('all')
rect = 50, 50, self.w - 50, self.h - 50
self.canvas.create_rectangle(rect, outline="black")
for x in self.frange(0, self.x_max - self... | def draw_axes(self):
"""
Removes all existing series and re-draws the axes.
:return: None
"""
self.canvas.delete('all')
rect = 50, 50, self.w - 50, self.h - 50
self.canvas.create_rectangle(rect, outline="black")
for x in self.frange(0, self.x_max - self... | [
"Removes",
"all",
"existing",
"series",
"and",
"re",
"-",
"draws",
"the",
"axes",
"."
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L391-L423 | [
"def",
"draw_axes",
"(",
"self",
")",
":",
"self",
".",
"canvas",
".",
"delete",
"(",
"'all'",
")",
"rect",
"=",
"50",
",",
"50",
",",
"self",
".",
"w",
"-",
"50",
",",
"self",
".",
"h",
"-",
"50",
"self",
".",
"canvas",
".",
"create_rectangle",
... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Graph.plot_point | Places a single point on the grid
:param x: the x coordinate
:param y: the y coordinate
:param visible: True if the individual point should be visible
:param color: the color of the point
:param size: the point size in pixels
:return: The absolute coordinates as a tuple | tk_tools/canvas.py | def plot_point(self, x, y, visible=True, color='black', size=5):
"""
Places a single point on the grid
:param x: the x coordinate
:param y: the y coordinate
:param visible: True if the individual point should be visible
:param color: the color of the point
:param... | def plot_point(self, x, y, visible=True, color='black', size=5):
"""
Places a single point on the grid
:param x: the x coordinate
:param y: the y coordinate
:param visible: True if the individual point should be visible
:param color: the color of the point
:param... | [
"Places",
"a",
"single",
"point",
"on",
"the",
"grid"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L425-L451 | [
"def",
"plot_point",
"(",
"self",
",",
"x",
",",
"y",
",",
"visible",
"=",
"True",
",",
"color",
"=",
"'black'",
",",
"size",
"=",
"5",
")",
":",
"xp",
"=",
"(",
"self",
".",
"px_x",
"*",
"(",
"x",
"-",
"self",
".",
"x_min",
")",
")",
"/",
... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Graph.plot_line | Plot a line of points
:param points: a list of tuples, each tuple containing an (x, y) point
:param color: the color of the line
:param point_visibility: True if the points \
should be individually visible
:return: None | tk_tools/canvas.py | def plot_line(self, points: list, color='black', point_visibility=False):
"""
Plot a line of points
:param points: a list of tuples, each tuple containing an (x, y) point
:param color: the color of the line
:param point_visibility: True if the points \
should be individu... | def plot_line(self, points: list, color='black', point_visibility=False):
"""
Plot a line of points
:param points: a list of tuples, each tuple containing an (x, y) point
:param color: the color of the line
:param point_visibility: True if the points \
should be individu... | [
"Plot",
"a",
"line",
"of",
"points"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L453-L470 | [
"def",
"plot_line",
"(",
"self",
",",
"points",
":",
"list",
",",
"color",
"=",
"'black'",
",",
"point_visibility",
"=",
"False",
")",
":",
"last_point",
"=",
"(",
")",
"for",
"point",
"in",
"points",
":",
"this_point",
"=",
"self",
".",
"plot_point",
... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Graph.frange | Works like range for doubles
:param start: starting value
:param stop: ending value
:param step: the increment_value
:param digits_to_round: the digits to which to round \
(makes floating-point numbers much easier to work with)
:return: generator | tk_tools/canvas.py | def frange(start, stop, step, digits_to_round=3):
"""
Works like range for doubles
:param start: starting value
:param stop: ending value
:param step: the increment_value
:param digits_to_round: the digits to which to round \
(makes floating-point numbers much ea... | def frange(start, stop, step, digits_to_round=3):
"""
Works like range for doubles
:param start: starting value
:param stop: ending value
:param step: the increment_value
:param digits_to_round: the digits to which to round \
(makes floating-point numbers much ea... | [
"Works",
"like",
"range",
"for",
"doubles"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L474-L487 | [
"def",
"frange",
"(",
"start",
",",
"stop",
",",
"step",
",",
"digits_to_round",
"=",
"3",
")",
":",
"while",
"start",
"<",
"stop",
":",
"yield",
"round",
"(",
"start",
",",
"digits_to_round",
")",
"start",
"+=",
"step"
] | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Led._load_new | Load a new image.
:param img_data: the image data as a base64 string
:return: None | tk_tools/canvas.py | def _load_new(self, img_data: str):
"""
Load a new image.
:param img_data: the image data as a base64 string
:return: None
"""
self._image = tk.PhotoImage(data=img_data)
self._image = self._image.subsample(int(200 / self._size),
... | def _load_new(self, img_data: str):
"""
Load a new image.
:param img_data: the image data as a base64 string
:return: None
"""
self._image = tk.PhotoImage(data=img_data)
self._image = self._image.subsample(int(200 / self._size),
... | [
"Load",
"a",
"new",
"image",
"."
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L534-L548 | [
"def",
"_load_new",
"(",
"self",
",",
"img_data",
":",
"str",
")",
":",
"self",
".",
"_image",
"=",
"tk",
".",
"PhotoImage",
"(",
"data",
"=",
"img_data",
")",
"self",
".",
"_image",
"=",
"self",
".",
"_image",
".",
"subsample",
"(",
"int",
"(",
"2... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Led.to_grey | Change the LED to grey.
:param on: Unused, here for API consistency with the other states
:return: None | tk_tools/canvas.py | def to_grey(self, on: bool=False):
"""
Change the LED to grey.
:param on: Unused, here for API consistency with the other states
:return: None
"""
self._on = False
self._load_new(led_grey) | def to_grey(self, on: bool=False):
"""
Change the LED to grey.
:param on: Unused, here for API consistency with the other states
:return: None
"""
self._on = False
self._load_new(led_grey) | [
"Change",
"the",
"LED",
"to",
"grey",
"."
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L550-L558 | [
"def",
"to_grey",
"(",
"self",
",",
"on",
":",
"bool",
"=",
"False",
")",
":",
"self",
".",
"_on",
"=",
"False",
"self",
".",
"_load_new",
"(",
"led_grey",
")"
] | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Led.to_green | Change the LED to green (on or off).
:param on: True or False
:return: None | tk_tools/canvas.py | def to_green(self, on: bool=False):
"""
Change the LED to green (on or off).
:param on: True or False
:return: None
"""
self._on = on
if on:
self._load_new(led_green_on)
if self._toggle_on_click:
self._canvas.bind('<Button... | def to_green(self, on: bool=False):
"""
Change the LED to green (on or off).
:param on: True or False
:return: None
"""
self._on = on
if on:
self._load_new(led_green_on)
if self._toggle_on_click:
self._canvas.bind('<Button... | [
"Change",
"the",
"LED",
"to",
"green",
"(",
"on",
"or",
"off",
")",
"."
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L560-L577 | [
"def",
"to_green",
"(",
"self",
",",
"on",
":",
"bool",
"=",
"False",
")",
":",
"self",
".",
"_on",
"=",
"on",
"if",
"on",
":",
"self",
".",
"_load_new",
"(",
"led_green_on",
")",
"if",
"self",
".",
"_toggle_on_click",
":",
"self",
".",
"_canvas",
... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Led.to_red | Change the LED to red (on or off)
:param on: True or False
:return: None | tk_tools/canvas.py | def to_red(self, on: bool=False):
"""
Change the LED to red (on or off)
:param on: True or False
:return: None
"""
self._on = on
if on:
self._load_new(led_red_on)
if self._toggle_on_click:
self._canvas.bind('<Button-1>', la... | def to_red(self, on: bool=False):
"""
Change the LED to red (on or off)
:param on: True or False
:return: None
"""
self._on = on
if on:
self._load_new(led_red_on)
if self._toggle_on_click:
self._canvas.bind('<Button-1>', la... | [
"Change",
"the",
"LED",
"to",
"red",
"(",
"on",
"or",
"off",
")",
":",
"param",
"on",
":",
"True",
"or",
"False",
":",
"return",
":",
"None"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L579-L595 | [
"def",
"to_red",
"(",
"self",
",",
"on",
":",
"bool",
"=",
"False",
")",
":",
"self",
".",
"_on",
"=",
"on",
"if",
"on",
":",
"self",
".",
"_load_new",
"(",
"led_red_on",
")",
"if",
"self",
".",
"_toggle_on_click",
":",
"self",
".",
"_canvas",
".",... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | Led.to_yellow | Change the LED to yellow (on or off)
:param on: True or False
:return: None | tk_tools/canvas.py | def to_yellow(self, on: bool=False):
"""
Change the LED to yellow (on or off)
:param on: True or False
:return: None
"""
self._on = on
if on:
self._load_new(led_yellow_on)
if self._toggle_on_click:
self._canvas.bind('<Butto... | def to_yellow(self, on: bool=False):
"""
Change the LED to yellow (on or off)
:param on: True or False
:return: None
"""
self._on = on
if on:
self._load_new(led_yellow_on)
if self._toggle_on_click:
self._canvas.bind('<Butto... | [
"Change",
"the",
"LED",
"to",
"yellow",
"(",
"on",
"or",
"off",
")",
":",
"param",
"on",
":",
"True",
"or",
"False",
":",
"return",
":",
"None"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/canvas.py#L597-L615 | [
"def",
"to_yellow",
"(",
"self",
",",
"on",
":",
"bool",
"=",
"False",
")",
":",
"self",
".",
"_on",
"=",
"on",
"if",
"on",
":",
"self",
".",
"_load_new",
"(",
"led_yellow_on",
")",
"if",
"self",
".",
"_toggle_on_click",
":",
"self",
".",
"_canvas",
... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | _Grid._redraw | Forgets the current layout and redraws with the most recent information
:return: None | tk_tools/groups.py | def _redraw(self):
"""
Forgets the current layout and redraws with the most recent information
:return: None
"""
for row in self._rows:
for widget in row:
widget.grid_forget()
offset = 0 if not self.headers else 1
for i, row in enumer... | def _redraw(self):
"""
Forgets the current layout and redraws with the most recent information
:return: None
"""
for row in self._rows:
for widget in row:
widget.grid_forget()
offset = 0 if not self.headers else 1
for i, row in enumer... | [
"Forgets",
"the",
"current",
"layout",
"and",
"redraws",
"with",
"the",
"most",
"recent",
"information"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/groups.py#L56-L69 | [
"def",
"_redraw",
"(",
"self",
")",
":",
"for",
"row",
"in",
"self",
".",
"_rows",
":",
"for",
"widget",
"in",
"row",
":",
"widget",
".",
"grid_forget",
"(",
")",
"offset",
"=",
"0",
"if",
"not",
"self",
".",
"headers",
"else",
"1",
"for",
"i",
"... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | _Grid.remove_row | Removes a specified row of data
:param row_number: the row to remove (defaults to the last row)
:return: None | tk_tools/groups.py | def remove_row(self, row_number: int=-1):
"""
Removes a specified row of data
:param row_number: the row to remove (defaults to the last row)
:return: None
"""
if len(self._rows) == 0:
return
row = self._rows.pop(row_number)
for widget in row... | def remove_row(self, row_number: int=-1):
"""
Removes a specified row of data
:param row_number: the row to remove (defaults to the last row)
:return: None
"""
if len(self._rows) == 0:
return
row = self._rows.pop(row_number)
for widget in row... | [
"Removes",
"a",
"specified",
"row",
"of",
"data"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/groups.py#L71-L83 | [
"def",
"remove_row",
"(",
"self",
",",
"row_number",
":",
"int",
"=",
"-",
"1",
")",
":",
"if",
"len",
"(",
"self",
".",
"_rows",
")",
"==",
"0",
":",
"return",
"row",
"=",
"self",
".",
"_rows",
".",
"pop",
"(",
"row_number",
")",
"for",
"widget"... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
train | LabelGrid.add_row | Add a row of data to the current widget
:param data: a row of data
:return: None | tk_tools/groups.py | def add_row(self, data: list):
"""
Add a row of data to the current widget
:param data: a row of data
:return: None
"""
# validation
if self.headers:
if len(self.headers) != len(data):
raise ValueError
if len(data) != self.num... | def add_row(self, data: list):
"""
Add a row of data to the current widget
:param data: a row of data
:return: None
"""
# validation
if self.headers:
if len(self.headers) != len(data):
raise ValueError
if len(data) != self.num... | [
"Add",
"a",
"row",
"of",
"data",
"to",
"the",
"current",
"widget"
] | slightlynybbled/tk_tools | python | https://github.com/slightlynybbled/tk_tools/blob/7c1792cad42890251a34f0617ce9b4b3e7abcf50/tk_tools/groups.py#L109-L132 | [
"def",
"add_row",
"(",
"self",
",",
"data",
":",
"list",
")",
":",
"# validation",
"if",
"self",
".",
"headers",
":",
"if",
"len",
"(",
"self",
".",
"headers",
")",
"!=",
"len",
"(",
"data",
")",
":",
"raise",
"ValueError",
"if",
"len",
"(",
"data"... | 7c1792cad42890251a34f0617ce9b4b3e7abcf50 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.