repository_name stringlengths 7 55 | func_path_in_repository stringlengths 4 223 | func_name stringlengths 1 134 | whole_func_string stringlengths 75 104k | language stringclasses 1
value | func_code_string stringlengths 75 104k | func_code_tokens listlengths 19 28.4k | func_documentation_string stringlengths 1 46.9k | func_documentation_tokens listlengths 1 1.97k | split_name stringclasses 1
value | func_code_url stringlengths 87 315 |
|---|---|---|---|---|---|---|---|---|---|---|
googledatalab/pydatalab | google/datalab/bigquery/commands/_bigquery.py | _extract_cell | def _extract_cell(args, cell_body):
"""Implements the BigQuery extract magic used to extract query or table data to GCS.
The supported syntax is:
%bq extract <args>
Args:
args: the arguments following '%bigquery extract'.
"""
env = google.datalab.utils.commands.notebook_environment()
config = g... | python | def _extract_cell(args, cell_body):
"""Implements the BigQuery extract magic used to extract query or table data to GCS.
The supported syntax is:
%bq extract <args>
Args:
args: the arguments following '%bigquery extract'.
"""
env = google.datalab.utils.commands.notebook_environment()
config = g... | [
"def",
"_extract_cell",
"(",
"args",
",",
"cell_body",
")",
":",
"env",
"=",
"google",
".",
"datalab",
".",
"utils",
".",
"commands",
".",
"notebook_environment",
"(",
")",
"config",
"=",
"google",
".",
"datalab",
".",
"utils",
".",
"commands",
".",
"par... | Implements the BigQuery extract magic used to extract query or table data to GCS.
The supported syntax is:
%bq extract <args>
Args:
args: the arguments following '%bigquery extract'. | [
"Implements",
"the",
"BigQuery",
"extract",
"magic",
"used",
"to",
"extract",
"query",
"or",
"table",
"data",
"to",
"GCS",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/bigquery/commands/_bigquery.py#L757-L802 |
googledatalab/pydatalab | google/datalab/bigquery/commands/_bigquery.py | _load_cell | def _load_cell(args, cell_body):
"""Implements the BigQuery load magic used to load data from GCS to a table.
The supported syntax is:
%bq load <optional args>
Args:
args: the arguments following '%bq load'.
cell_body: optional contents of the cell interpreted as YAML or JSON.
Returns:
A ... | python | def _load_cell(args, cell_body):
"""Implements the BigQuery load magic used to load data from GCS to a table.
The supported syntax is:
%bq load <optional args>
Args:
args: the arguments following '%bq load'.
cell_body: optional contents of the cell interpreted as YAML or JSON.
Returns:
A ... | [
"def",
"_load_cell",
"(",
"args",
",",
"cell_body",
")",
":",
"env",
"=",
"google",
".",
"datalab",
".",
"utils",
".",
"commands",
".",
"notebook_environment",
"(",
")",
"config",
"=",
"google",
".",
"datalab",
".",
"utils",
".",
"commands",
".",
"parse_... | Implements the BigQuery load magic used to load data from GCS to a table.
The supported syntax is:
%bq load <optional args>
Args:
args: the arguments following '%bq load'.
cell_body: optional contents of the cell interpreted as YAML or JSON.
Returns:
A message about whether the load succeed... | [
"Implements",
"the",
"BigQuery",
"load",
"magic",
"used",
"to",
"load",
"data",
"from",
"GCS",
"to",
"a",
"table",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/bigquery/commands/_bigquery.py#L805-L855 |
googledatalab/pydatalab | google/datalab/bigquery/commands/_bigquery.py | _pipeline_cell | def _pipeline_cell(args, cell_body):
"""Implements the pipeline subcommand in the %%bq magic.
Args:
args: the arguments following '%%bq pipeline'.
cell_body: Cell contents.
"""
name = args.get('name')
if name is None:
raise Exception('Pipeline name was not specified.')
impor... | python | def _pipeline_cell(args, cell_body):
"""Implements the pipeline subcommand in the %%bq magic.
Args:
args: the arguments following '%%bq pipeline'.
cell_body: Cell contents.
"""
name = args.get('name')
if name is None:
raise Exception('Pipeline name was not specified.')
impor... | [
"def",
"_pipeline_cell",
"(",
"args",
",",
"cell_body",
")",
":",
"name",
"=",
"args",
".",
"get",
"(",
"'name'",
")",
"if",
"name",
"is",
"None",
":",
"raise",
"Exception",
"(",
"'Pipeline name was not specified.'",
")",
"import",
"google",
".",
"datalab",
... | Implements the pipeline subcommand in the %%bq magic.
Args:
args: the arguments following '%%bq pipeline'.
cell_body: Cell contents. | [
"Implements",
"the",
"pipeline",
"subcommand",
"in",
"the",
"%%bq",
"magic",
".",
"Args",
":",
"args",
":",
"the",
"arguments",
"following",
"%%bq",
"pipeline",
".",
"cell_body",
":",
"Cell",
"contents",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/bigquery/commands/_bigquery.py#L913-L962 |
googledatalab/pydatalab | google/datalab/bigquery/commands/_bigquery.py | _create_bigquery_parser | def _create_bigquery_parser():
""" Create the parser for the %bq magics.
Note that because we use the func default handler dispatch mechanism of argparse,
our handlers can take only one argument which is the parsed args. So we must create closures
for the handlers that bind the cell contents and thus must recr... | python | def _create_bigquery_parser():
""" Create the parser for the %bq magics.
Note that because we use the func default handler dispatch mechanism of argparse,
our handlers can take only one argument which is the parsed args. So we must create closures
for the handlers that bind the cell contents and thus must recr... | [
"def",
"_create_bigquery_parser",
"(",
")",
":",
"parser",
"=",
"google",
".",
"datalab",
".",
"utils",
".",
"commands",
".",
"CommandParser",
"(",
"prog",
"=",
"'%bq'",
",",
"description",
"=",
"\"\"\"\nExecute various BigQuery-related operations. Use \"%bq <command> -... | Create the parser for the %bq magics.
Note that because we use the func default handler dispatch mechanism of argparse,
our handlers can take only one argument which is the parsed args. So we must create closures
for the handlers that bind the cell contents and thus must recreate this parser for each
cell upon... | [
"Create",
"the",
"parser",
"for",
"the",
"%bq",
"magics",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/bigquery/commands/_bigquery.py#L972-L1021 |
googledatalab/pydatalab | google/datalab/bigquery/commands/_bigquery.py | bq | def bq(line, cell=None):
"""Implements the bq cell magic for ipython notebooks.
The supported syntax is:
%%bq <command> [<args>]
<cell>
or:
%bq <command> [<args>]
Use %bq --help for a list of commands, or %bq <command> --help for help
on a specific command.
"""
return google.datalab.utils... | python | def bq(line, cell=None):
"""Implements the bq cell magic for ipython notebooks.
The supported syntax is:
%%bq <command> [<args>]
<cell>
or:
%bq <command> [<args>]
Use %bq --help for a list of commands, or %bq <command> --help for help
on a specific command.
"""
return google.datalab.utils... | [
"def",
"bq",
"(",
"line",
",",
"cell",
"=",
"None",
")",
":",
"return",
"google",
".",
"datalab",
".",
"utils",
".",
"commands",
".",
"handle_magic_line",
"(",
"line",
",",
"cell",
",",
"_bigquery_parser",
")"
] | Implements the bq cell magic for ipython notebooks.
The supported syntax is:
%%bq <command> [<args>]
<cell>
or:
%bq <command> [<args>]
Use %bq --help for a list of commands, or %bq <command> --help for help
on a specific command. | [
"Implements",
"the",
"bq",
"cell",
"magic",
"for",
"ipython",
"notebooks",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/bigquery/commands/_bigquery.py#L1028-L1043 |
googledatalab/pydatalab | google/datalab/bigquery/commands/_bigquery.py | _table_viewer | def _table_viewer(table, rows_per_page=25, fields=None):
""" Return a table viewer.
This includes a static rendering of the first page of the table, that gets replaced
by the charting code in environments where Javascript is executable and BQ is available.
Args:
table: the table to view.
rows_per... | python | def _table_viewer(table, rows_per_page=25, fields=None):
""" Return a table viewer.
This includes a static rendering of the first page of the table, that gets replaced
by the charting code in environments where Javascript is executable and BQ is available.
Args:
table: the table to view.
rows_per... | [
"def",
"_table_viewer",
"(",
"table",
",",
"rows_per_page",
"=",
"25",
",",
"fields",
"=",
"None",
")",
":",
"# TODO(gram): rework this to use google.datalab.utils.commands.chart_html",
"if",
"not",
"table",
".",
"exists",
"(",
")",
":",
"raise",
"Exception",
"(",
... | Return a table viewer.
This includes a static rendering of the first page of the table, that gets replaced
by the charting code in environments where Javascript is executable and BQ is available.
Args:
table: the table to view.
rows_per_page: how many rows to display at one time.
fields: an arra... | [
"Return",
"a",
"table",
"viewer",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/bigquery/commands/_bigquery.py#L1074-L1186 |
googledatalab/pydatalab | datalab/bigquery/_udf.py | UDF._build_js | def _build_js(inputs, outputs, name, implementation, support_code):
"""Creates a BigQuery SQL UDF javascript object.
Args:
inputs: a list of (name, type) tuples representing the schema of input.
outputs: a list of (name, type) tuples representing the schema of the output.
name: the name of th... | python | def _build_js(inputs, outputs, name, implementation, support_code):
"""Creates a BigQuery SQL UDF javascript object.
Args:
inputs: a list of (name, type) tuples representing the schema of input.
outputs: a list of (name, type) tuples representing the schema of the output.
name: the name of th... | [
"def",
"_build_js",
"(",
"inputs",
",",
"outputs",
",",
"name",
",",
"implementation",
",",
"support_code",
")",
":",
"# Construct a comma-separated list of input field names",
"# For example, field1,field2,...",
"input_fields",
"=",
"json",
".",
"dumps",
"(",
"[",
"f",... | Creates a BigQuery SQL UDF javascript object.
Args:
inputs: a list of (name, type) tuples representing the schema of input.
outputs: a list of (name, type) tuples representing the schema of the output.
name: the name of the function
implementation: a javascript function defining the UDF log... | [
"Creates",
"a",
"BigQuery",
"SQL",
"UDF",
"javascript",
"object",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/datalab/bigquery/_udf.py#L59-L84 |
googledatalab/pydatalab | datalab/bigquery/_sampling.py | Sampling.sampling_query | def sampling_query(sql, fields=None, count=5, sampling=None):
"""Returns a sampling query for the SQL object.
Args:
sql: the SQL object to sample
fields: an optional list of field names to retrieve.
count: an optional count of rows to retrieve which is used if a specific
sampling is... | python | def sampling_query(sql, fields=None, count=5, sampling=None):
"""Returns a sampling query for the SQL object.
Args:
sql: the SQL object to sample
fields: an optional list of field names to retrieve.
count: an optional count of rows to retrieve which is used if a specific
sampling is... | [
"def",
"sampling_query",
"(",
"sql",
",",
"fields",
"=",
"None",
",",
"count",
"=",
"5",
",",
"sampling",
"=",
"None",
")",
":",
"if",
"sampling",
"is",
"None",
":",
"sampling",
"=",
"Sampling",
".",
"default",
"(",
"count",
"=",
"count",
",",
"field... | Returns a sampling query for the SQL object.
Args:
sql: the SQL object to sample
fields: an optional list of field names to retrieve.
count: an optional count of rows to retrieve which is used if a specific
sampling is not specified.
sampling: an optional sampling strategy to appl... | [
"Returns",
"a",
"sampling",
"query",
"for",
"the",
"SQL",
"object",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/datalab/bigquery/_sampling.py#L74-L88 |
googledatalab/pydatalab | google/datalab/ml/_fasets.py | FacetsOverview._remove_nonascii | def _remove_nonascii(self, df):
"""Make copy and remove non-ascii characters from it."""
df_copy = df.copy(deep=True)
for col in df_copy.columns:
if (df_copy[col].dtype == np.dtype('O')):
df_copy[col] = df[col].apply(
lambda x: re.sub(r'[^\x00-\x7f]', r'', x) if isinstance(x, six.st... | python | def _remove_nonascii(self, df):
"""Make copy and remove non-ascii characters from it."""
df_copy = df.copy(deep=True)
for col in df_copy.columns:
if (df_copy[col].dtype == np.dtype('O')):
df_copy[col] = df[col].apply(
lambda x: re.sub(r'[^\x00-\x7f]', r'', x) if isinstance(x, six.st... | [
"def",
"_remove_nonascii",
"(",
"self",
",",
"df",
")",
":",
"df_copy",
"=",
"df",
".",
"copy",
"(",
"deep",
"=",
"True",
")",
"for",
"col",
"in",
"df_copy",
".",
"columns",
":",
"if",
"(",
"df_copy",
"[",
"col",
"]",
".",
"dtype",
"==",
"np",
".... | Make copy and remove non-ascii characters from it. | [
"Make",
"copy",
"and",
"remove",
"non",
"-",
"ascii",
"characters",
"from",
"it",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/ml/_fasets.py#L27-L36 |
googledatalab/pydatalab | google/datalab/ml/_fasets.py | FacetsOverview.plot | def plot(self, data):
""" Plots an overview in a list of dataframes
Args:
data: a dictionary with key the name, and value the dataframe.
"""
import IPython
if not isinstance(data, dict) or not all(isinstance(v, pd.DataFrame) for v in data.values()):
raise ValueError('Expect a dictiona... | python | def plot(self, data):
""" Plots an overview in a list of dataframes
Args:
data: a dictionary with key the name, and value the dataframe.
"""
import IPython
if not isinstance(data, dict) or not all(isinstance(v, pd.DataFrame) for v in data.values()):
raise ValueError('Expect a dictiona... | [
"def",
"plot",
"(",
"self",
",",
"data",
")",
":",
"import",
"IPython",
"if",
"not",
"isinstance",
"(",
"data",
",",
"dict",
")",
"or",
"not",
"all",
"(",
"isinstance",
"(",
"v",
",",
"pd",
".",
"DataFrame",
")",
"for",
"v",
"in",
"data",
".",
"v... | Plots an overview in a list of dataframes
Args:
data: a dictionary with key the name, and value the dataframe. | [
"Plots",
"an",
"overview",
"in",
"a",
"list",
"of",
"dataframes"
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/ml/_fasets.py#L38-L62 |
googledatalab/pydatalab | google/datalab/ml/_fasets.py | FacetsDiveview.plot | def plot(self, data, height=1000, render_large_data=False):
""" Plots a detail view of data.
Args:
data: a Pandas dataframe.
height: the height of the output.
"""
import IPython
if not isinstance(data, pd.DataFrame):
raise ValueError('Expect a DataFrame.')
if (len(data) > 1... | python | def plot(self, data, height=1000, render_large_data=False):
""" Plots a detail view of data.
Args:
data: a Pandas dataframe.
height: the height of the output.
"""
import IPython
if not isinstance(data, pd.DataFrame):
raise ValueError('Expect a DataFrame.')
if (len(data) > 1... | [
"def",
"plot",
"(",
"self",
",",
"data",
",",
"height",
"=",
"1000",
",",
"render_large_data",
"=",
"False",
")",
":",
"import",
"IPython",
"if",
"not",
"isinstance",
"(",
"data",
",",
"pd",
".",
"DataFrame",
")",
":",
"raise",
"ValueError",
"(",
"'Exp... | Plots a detail view of data.
Args:
data: a Pandas dataframe.
height: the height of the output. | [
"Plots",
"a",
"detail",
"view",
"of",
"data",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/ml/_fasets.py#L68-L95 |
googledatalab/pydatalab | google/datalab/utils/facets/base_generic_feature_statistics_generator.py | BaseGenericFeatureStatisticsGenerator.ProtoFromDataFrames | def ProtoFromDataFrames(self, dataframes):
"""Creates a feature statistics proto from a set of pandas dataframes.
Args:
dataframes: A list of dicts describing tables for each dataset for the
proto. Each entry contains a 'table' field of the dataframe of the
data
and a 'name... | python | def ProtoFromDataFrames(self, dataframes):
"""Creates a feature statistics proto from a set of pandas dataframes.
Args:
dataframes: A list of dicts describing tables for each dataset for the
proto. Each entry contains a 'table' field of the dataframe of the
data
and a 'name... | [
"def",
"ProtoFromDataFrames",
"(",
"self",
",",
"dataframes",
")",
":",
"datasets",
"=",
"[",
"]",
"for",
"dataframe",
"in",
"dataframes",
":",
"table",
"=",
"dataframe",
"[",
"'table'",
"]",
"table_entries",
"=",
"{",
"}",
"for",
"col",
"in",
"table",
"... | Creates a feature statistics proto from a set of pandas dataframes.
Args:
dataframes: A list of dicts describing tables for each dataset for the
proto. Each entry contains a 'table' field of the dataframe of the
data
and a 'name' field to identify the dataset in the proto.
... | [
"Creates",
"a",
"feature",
"statistics",
"proto",
"from",
"a",
"set",
"of",
"pandas",
"dataframes",
".",
"Args",
":",
"dataframes",
":",
"A",
"list",
"of",
"dicts",
"describing",
"tables",
"for",
"each",
"dataset",
"for",
"the",
"proto",
".",
"Each",
"entr... | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/utils/facets/base_generic_feature_statistics_generator.py#L35-L56 |
googledatalab/pydatalab | google/datalab/utils/facets/base_generic_feature_statistics_generator.py | BaseGenericFeatureStatisticsGenerator.DtypeToType | def DtypeToType(self, dtype):
"""Converts a Numpy dtype to the FeatureNameStatistics.Type proto enum."""
if dtype.char in np.typecodes['AllFloat']:
return self.fs_proto.FLOAT
elif (dtype.char in np.typecodes['AllInteger'] or dtype == np.bool or
np.issubdtype(dtype, np.datetime64) or
... | python | def DtypeToType(self, dtype):
"""Converts a Numpy dtype to the FeatureNameStatistics.Type proto enum."""
if dtype.char in np.typecodes['AllFloat']:
return self.fs_proto.FLOAT
elif (dtype.char in np.typecodes['AllInteger'] or dtype == np.bool or
np.issubdtype(dtype, np.datetime64) or
... | [
"def",
"DtypeToType",
"(",
"self",
",",
"dtype",
")",
":",
"if",
"dtype",
".",
"char",
"in",
"np",
".",
"typecodes",
"[",
"'AllFloat'",
"]",
":",
"return",
"self",
".",
"fs_proto",
".",
"FLOAT",
"elif",
"(",
"dtype",
".",
"char",
"in",
"np",
".",
"... | Converts a Numpy dtype to the FeatureNameStatistics.Type proto enum. | [
"Converts",
"a",
"Numpy",
"dtype",
"to",
"the",
"FeatureNameStatistics",
".",
"Type",
"proto",
"enum",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/utils/facets/base_generic_feature_statistics_generator.py#L58-L67 |
googledatalab/pydatalab | google/datalab/utils/facets/base_generic_feature_statistics_generator.py | BaseGenericFeatureStatisticsGenerator.DtypeToNumberConverter | def DtypeToNumberConverter(self, dtype):
"""Converts a Numpy dtype to a converter method if applicable.
The converter method takes in a numpy array of objects of the provided
dtype
and returns a numpy array of the numbers backing that object for
statistical
analysis. Returns None if no... | python | def DtypeToNumberConverter(self, dtype):
"""Converts a Numpy dtype to a converter method if applicable.
The converter method takes in a numpy array of objects of the provided
dtype
and returns a numpy array of the numbers backing that object for
statistical
analysis. Returns None if no... | [
"def",
"DtypeToNumberConverter",
"(",
"self",
",",
"dtype",
")",
":",
"if",
"np",
".",
"issubdtype",
"(",
"dtype",
",",
"np",
".",
"datetime64",
")",
":",
"def",
"DatetimesToNumbers",
"(",
"dt_list",
")",
":",
"return",
"np",
".",
"array",
"(",
"[",
"p... | Converts a Numpy dtype to a converter method if applicable.
The converter method takes in a numpy array of objects of the provided
dtype
and returns a numpy array of the numbers backing that object for
statistical
analysis. Returns None if no converter is necessary.
Args:
dtype: ... | [
"Converts",
"a",
"Numpy",
"dtype",
"to",
"a",
"converter",
"method",
"if",
"applicable",
".",
"The",
"converter",
"method",
"takes",
"in",
"a",
"numpy",
"array",
"of",
"objects",
"of",
"the",
"provided",
"dtype",
"and",
"returns",
"a",
"numpy",
"array",
"o... | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/utils/facets/base_generic_feature_statistics_generator.py#L69-L94 |
googledatalab/pydatalab | google/datalab/utils/facets/base_generic_feature_statistics_generator.py | BaseGenericFeatureStatisticsGenerator.NdarrayToEntry | def NdarrayToEntry(self, x):
"""Converts an ndarray to the Entry format."""
row_counts = []
for row in x:
try:
rc = np.count_nonzero(~np.isnan(row))
if rc != 0:
row_counts.append(rc)
except TypeError:
try:
row_counts.append(row.size)
except Att... | python | def NdarrayToEntry(self, x):
"""Converts an ndarray to the Entry format."""
row_counts = []
for row in x:
try:
rc = np.count_nonzero(~np.isnan(row))
if rc != 0:
row_counts.append(rc)
except TypeError:
try:
row_counts.append(row.size)
except Att... | [
"def",
"NdarrayToEntry",
"(",
"self",
",",
"x",
")",
":",
"row_counts",
"=",
"[",
"]",
"for",
"row",
"in",
"x",
":",
"try",
":",
"rc",
"=",
"np",
".",
"count_nonzero",
"(",
"~",
"np",
".",
"isnan",
"(",
"row",
")",
")",
"if",
"rc",
"!=",
"0",
... | Converts an ndarray to the Entry format. | [
"Converts",
"an",
"ndarray",
"to",
"the",
"Entry",
"format",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/utils/facets/base_generic_feature_statistics_generator.py#L96-L137 |
googledatalab/pydatalab | google/datalab/utils/facets/base_generic_feature_statistics_generator.py | BaseGenericFeatureStatisticsGenerator.GetDatasetsProto | def GetDatasetsProto(self, datasets, features=None):
"""Generates the feature stats proto from dictionaries of feature values.
Args:
datasets: An array of dictionaries, one per dataset, each one containing:
- 'entries': The dictionary of features in the dataset from the parsed
exampl... | python | def GetDatasetsProto(self, datasets, features=None):
"""Generates the feature stats proto from dictionaries of feature values.
Args:
datasets: An array of dictionaries, one per dataset, each one containing:
- 'entries': The dictionary of features in the dataset from the parsed
exampl... | [
"def",
"GetDatasetsProto",
"(",
"self",
",",
"datasets",
",",
"features",
"=",
"None",
")",
":",
"features_seen",
"=",
"set",
"(",
")",
"whitelist_features",
"=",
"set",
"(",
"features",
")",
"if",
"features",
"else",
"None",
"all_datasets",
"=",
"self",
"... | Generates the feature stats proto from dictionaries of feature values.
Args:
datasets: An array of dictionaries, one per dataset, each one containing:
- 'entries': The dictionary of features in the dataset from the parsed
examples.
- 'size': The number of examples parsed for th... | [
"Generates",
"the",
"feature",
"stats",
"proto",
"from",
"dictionaries",
"of",
"feature",
"values",
".",
"Args",
":",
"datasets",
":",
"An",
"array",
"of",
"dictionaries",
"one",
"per",
"dataset",
"each",
"one",
"containing",
":",
"-",
"entries",
":",
"The",... | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/utils/facets/base_generic_feature_statistics_generator.py#L139-L286 |
googledatalab/pydatalab | google/datalab/utils/facets/base_generic_feature_statistics_generator.py | BaseGenericFeatureStatisticsGenerator._PopulateQuantilesHistogram | def _PopulateQuantilesHistogram(self, hist, nums):
"""Fills in the histogram with quantile information from the provided array.
Args:
hist: A Histogram proto message to fill in.
nums: A list of numbers to create a quantiles histogram from.
"""
if not nums:
return
num_quantile_bucke... | python | def _PopulateQuantilesHistogram(self, hist, nums):
"""Fills in the histogram with quantile information from the provided array.
Args:
hist: A Histogram proto message to fill in.
nums: A list of numbers to create a quantiles histogram from.
"""
if not nums:
return
num_quantile_bucke... | [
"def",
"_PopulateQuantilesHistogram",
"(",
"self",
",",
"hist",
",",
"nums",
")",
":",
"if",
"not",
"nums",
":",
"return",
"num_quantile_buckets",
"=",
"10",
"quantiles_to_get",
"=",
"[",
"x",
"*",
"100",
"/",
"num_quantile_buckets",
"for",
"x",
"in",
"range... | Fills in the histogram with quantile information from the provided array.
Args:
hist: A Histogram proto message to fill in.
nums: A list of numbers to create a quantiles histogram from. | [
"Fills",
"in",
"the",
"histogram",
"with",
"quantile",
"information",
"from",
"the",
"provided",
"array",
".",
"Args",
":",
"hist",
":",
"A",
"Histogram",
"proto",
"message",
"to",
"fill",
"in",
".",
"nums",
":",
"A",
"list",
"of",
"numbers",
"to",
"crea... | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/google/datalab/utils/facets/base_generic_feature_statistics_generator.py#L288-L305 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | serving_from_csv_input | def serving_from_csv_input(train_config, args, keep_target):
"""Read the input features from a placeholder csv string tensor."""
examples = tf.placeholder(
dtype=tf.string,
shape=(None,),
name='csv_input_string')
features = parse_example_tensor(examples=examples,
... | python | def serving_from_csv_input(train_config, args, keep_target):
"""Read the input features from a placeholder csv string tensor."""
examples = tf.placeholder(
dtype=tf.string,
shape=(None,),
name='csv_input_string')
features = parse_example_tensor(examples=examples,
... | [
"def",
"serving_from_csv_input",
"(",
"train_config",
",",
"args",
",",
"keep_target",
")",
":",
"examples",
"=",
"tf",
".",
"placeholder",
"(",
"dtype",
"=",
"tf",
".",
"string",
",",
"shape",
"=",
"(",
"None",
",",
")",
",",
"name",
"=",
"'csv_input_st... | Read the input features from a placeholder csv string tensor. | [
"Read",
"the",
"input",
"features",
"from",
"a",
"placeholder",
"csv",
"string",
"tensor",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L90-L115 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | parse_example_tensor | def parse_example_tensor(examples, train_config, keep_target):
"""Read the csv files.
Args:
examples: string tensor
train_config: training config
keep_target: if true, the target column is expected to exist and it is
returned in the features dict.
Returns:
Dict of feature_name to tensor.... | python | def parse_example_tensor(examples, train_config, keep_target):
"""Read the csv files.
Args:
examples: string tensor
train_config: training config
keep_target: if true, the target column is expected to exist and it is
returned in the features dict.
Returns:
Dict of feature_name to tensor.... | [
"def",
"parse_example_tensor",
"(",
"examples",
",",
"train_config",
",",
"keep_target",
")",
":",
"csv_header",
"=",
"[",
"]",
"if",
"keep_target",
":",
"csv_header",
"=",
"train_config",
"[",
"'csv_header'",
"]",
"else",
":",
"csv_header",
"=",
"[",
"name",
... | Read the csv files.
Args:
examples: string tensor
train_config: training config
keep_target: if true, the target column is expected to exist and it is
returned in the features dict.
Returns:
Dict of feature_name to tensor. Target feature is in the dict. | [
"Read",
"the",
"csv",
"files",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L281-L312 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | read_examples | def read_examples(input_files, batch_size, shuffle, num_epochs=None):
"""Creates readers and queues for reading example protos."""
files = []
for e in input_files:
for path in e.split(','):
files.extend(file_io.get_matching_files(path))
thread_count = multiprocessing.cpu_count()
# The minimum numbe... | python | def read_examples(input_files, batch_size, shuffle, num_epochs=None):
"""Creates readers and queues for reading example protos."""
files = []
for e in input_files:
for path in e.split(','):
files.extend(file_io.get_matching_files(path))
thread_count = multiprocessing.cpu_count()
# The minimum numbe... | [
"def",
"read_examples",
"(",
"input_files",
",",
"batch_size",
",",
"shuffle",
",",
"num_epochs",
"=",
"None",
")",
":",
"files",
"=",
"[",
"]",
"for",
"e",
"in",
"input_files",
":",
"for",
"path",
"in",
"e",
".",
"split",
"(",
"','",
")",
":",
"file... | Creates readers and queues for reading example protos. | [
"Creates",
"readers",
"and",
"queues",
"for",
"reading",
"example",
"protos",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L315-L359 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | get_estimator | def get_estimator(output_dir, train_config, args):
"""Returns a tf learn estimator.
We only support {DNN, Linear}Regressor and {DNN, Linear}Classifier. This is
controlled by the values of model_type in the args.
Args:
output_dir: Modes are saved into outputdir/train
train_config: our training config
... | python | def get_estimator(output_dir, train_config, args):
"""Returns a tf learn estimator.
We only support {DNN, Linear}Regressor and {DNN, Linear}Classifier. This is
controlled by the values of model_type in the args.
Args:
output_dir: Modes are saved into outputdir/train
train_config: our training config
... | [
"def",
"get_estimator",
"(",
"output_dir",
",",
"train_config",
",",
"args",
")",
":",
"# Check the requested mode fits the preprocessed data.",
"target_name",
"=",
"train_config",
"[",
"'target_column'",
"]",
"if",
"is_classification_model",
"(",
"args",
".",
"model_type... | Returns a tf learn estimator.
We only support {DNN, Linear}Regressor and {DNN, Linear}Classifier. This is
controlled by the values of model_type in the args.
Args:
output_dir: Modes are saved into outputdir/train
train_config: our training config
args: command line parameters
Returns:
TF lean... | [
"Returns",
"a",
"tf",
"learn",
"estimator",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L367-L445 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | preprocess_input | def preprocess_input(features, target, train_config, preprocess_output_dir,
model_type):
"""Perform some transformations after reading in the input tensors.
Args:
features: dict of feature_name to tensor
target: tensor
train_config: our training config object
preprocess_output_... | python | def preprocess_input(features, target, train_config, preprocess_output_dir,
model_type):
"""Perform some transformations after reading in the input tensors.
Args:
features: dict of feature_name to tensor
target: tensor
train_config: our training config object
preprocess_output_... | [
"def",
"preprocess_input",
"(",
"features",
",",
"target",
",",
"train_config",
",",
"preprocess_output_dir",
",",
"model_type",
")",
":",
"target_name",
"=",
"train_config",
"[",
"'target_column'",
"]",
"key_name",
"=",
"train_config",
"[",
"'key_column'",
"]",
"... | Perform some transformations after reading in the input tensors.
Args:
features: dict of feature_name to tensor
target: tensor
train_config: our training config object
preprocess_output_dir: folder should contain the vocab files.
model_type: the tf model type.
Raises:
ValueError: if wrong ... | [
"Perform",
"some",
"transformations",
"after",
"reading",
"in",
"the",
"input",
"tensors",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L448-L542 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | _scale_tensor | def _scale_tensor(tensor, range_min, range_max, scale_min, scale_max):
"""Scale a tensor to scale_min to scale_max.
Args:
tensor: input tensor. Should be a numerical tensor.
range_min: min expected value for this feature/tensor.
range_max: max expected Value.
scale_min: new expected min value.
... | python | def _scale_tensor(tensor, range_min, range_max, scale_min, scale_max):
"""Scale a tensor to scale_min to scale_max.
Args:
tensor: input tensor. Should be a numerical tensor.
range_min: min expected value for this feature/tensor.
range_max: max expected Value.
scale_min: new expected min value.
... | [
"def",
"_scale_tensor",
"(",
"tensor",
",",
"range_min",
",",
"range_max",
",",
"scale_min",
",",
"scale_max",
")",
":",
"if",
"range_min",
"==",
"range_max",
":",
"return",
"tensor",
"float_tensor",
"=",
"tf",
".",
"to_float",
"(",
"tensor",
")",
"scaled_te... | Scale a tensor to scale_min to scale_max.
Args:
tensor: input tensor. Should be a numerical tensor.
range_min: min expected value for this feature/tensor.
range_max: max expected Value.
scale_min: new expected min value.
scale_max: new expected max value.
Returns:
scaled tensor. | [
"Scale",
"a",
"tensor",
"to",
"scale_min",
"to",
"scale_max",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L545-L567 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | _tflearn_features | def _tflearn_features(train_config, args):
"""Builds the tf.learn feature list.
All numerical features are just given real_valued_column because all the
preprocessing transformations are done in preprocess_input. Categoriacl
features are processed here depending if the vocab map (from string to int)
was appl... | python | def _tflearn_features(train_config, args):
"""Builds the tf.learn feature list.
All numerical features are just given real_valued_column because all the
preprocessing transformations are done in preprocess_input. Categoriacl
features are processed here depending if the vocab map (from string to int)
was appl... | [
"def",
"_tflearn_features",
"(",
"train_config",
",",
"args",
")",
":",
"feature_columns",
"=",
"[",
"]",
"target_name",
"=",
"train_config",
"[",
"'target_column'",
"]",
"key_name",
"=",
"train_config",
"[",
"'key_column'",
"]",
"for",
"name",
"in",
"train_conf... | Builds the tf.learn feature list.
All numerical features are just given real_valued_column because all the
preprocessing transformations are done in preprocess_input. Categoriacl
features are processed here depending if the vocab map (from string to int)
was applied in preprocess_input.
Args:
train_conf... | [
"Builds",
"the",
"tf",
".",
"learn",
"feature",
"list",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L570-L647 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | get_vocabulary | def get_vocabulary(preprocess_output_dir, name):
"""Loads the vocabulary file as a list of strings.
Args:
preprocess_output_dir: Should contain the file CATEGORICAL_ANALYSIS % name.
name: name of the csv column.
Returns:
List of strings.
Raises:
ValueError: if file is missing.
"""
vocab_f... | python | def get_vocabulary(preprocess_output_dir, name):
"""Loads the vocabulary file as a list of strings.
Args:
preprocess_output_dir: Should contain the file CATEGORICAL_ANALYSIS % name.
name: name of the csv column.
Returns:
List of strings.
Raises:
ValueError: if file is missing.
"""
vocab_f... | [
"def",
"get_vocabulary",
"(",
"preprocess_output_dir",
",",
"name",
")",
":",
"vocab_file",
"=",
"os",
".",
"path",
".",
"join",
"(",
"preprocess_output_dir",
",",
"CATEGORICAL_ANALYSIS",
"%",
"name",
")",
"if",
"not",
"file_io",
".",
"file_exists",
"(",
"voca... | Loads the vocabulary file as a list of strings.
Args:
preprocess_output_dir: Should contain the file CATEGORICAL_ANALYSIS % name.
name: name of the csv column.
Returns:
List of strings.
Raises:
ValueError: if file is missing. | [
"Loads",
"the",
"vocabulary",
"file",
"as",
"a",
"list",
"of",
"strings",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L655-L677 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | merge_metadata | def merge_metadata(preprocess_output_dir, transforms_file):
"""Merge schema, analysis, and transforms files into one python object.
Args:
preprocess_output_dir: the output folder of preprocessing. Should contain
the schema, and the numerical and categorical
analysis files.
transforms_file: ... | python | def merge_metadata(preprocess_output_dir, transforms_file):
"""Merge schema, analysis, and transforms files into one python object.
Args:
preprocess_output_dir: the output folder of preprocessing. Should contain
the schema, and the numerical and categorical
analysis files.
transforms_file: ... | [
"def",
"merge_metadata",
"(",
"preprocess_output_dir",
",",
"transforms_file",
")",
":",
"numerical_anlysis_file",
"=",
"os",
".",
"path",
".",
"join",
"(",
"preprocess_output_dir",
",",
"NUMERICAL_ANALYSIS",
")",
"schema_file",
"=",
"os",
".",
"path",
".",
"join"... | Merge schema, analysis, and transforms files into one python object.
Args:
preprocess_output_dir: the output folder of preprocessing. Should contain
the schema, and the numerical and categorical
analysis files.
transforms_file: the training transforms file.
Returns:
A dict in the form
... | [
"Merge",
"schema",
"analysis",
"and",
"transforms",
"files",
"into",
"one",
"python",
"object",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L680-L808 |
googledatalab/pydatalab | solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py | validate_metadata | def validate_metadata(train_config):
"""Perform some checks that the trainig config is correct.
Args:
train_config: train config as produced by merge_metadata()
Raises:
ValueError: if columns look wrong.
"""
# Make sure we have a default for every column
if len(train_config['csv_header']) != len(... | python | def validate_metadata(train_config):
"""Perform some checks that the trainig config is correct.
Args:
train_config: train config as produced by merge_metadata()
Raises:
ValueError: if columns look wrong.
"""
# Make sure we have a default for every column
if len(train_config['csv_header']) != len(... | [
"def",
"validate_metadata",
"(",
"train_config",
")",
":",
"# Make sure we have a default for every column",
"if",
"len",
"(",
"train_config",
"[",
"'csv_header'",
"]",
")",
"!=",
"len",
"(",
"train_config",
"[",
"'csv_defaults'",
"]",
")",
":",
"raise",
"ValueError... | Perform some checks that the trainig config is correct.
Args:
train_config: train config as produced by merge_metadata()
Raises:
ValueError: if columns look wrong. | [
"Perform",
"some",
"checks",
"that",
"the",
"trainig",
"config",
"is",
"correct",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/solutionbox/structured_data/mltoolbox/_structured_data/trainer/util.py#L811-L838 |
googledatalab/pydatalab | datalab/context/_project.py | Projects.get_default_id | def get_default_id(credentials=None):
""" Get default project id.
Returns: the default project id if there is one, or None.
"""
project_id = _utils.get_project_id()
if project_id is None:
projects, _ = Projects(credentials)._retrieve_projects(None, 2)
if len(projects) == 1:
proj... | python | def get_default_id(credentials=None):
""" Get default project id.
Returns: the default project id if there is one, or None.
"""
project_id = _utils.get_project_id()
if project_id is None:
projects, _ = Projects(credentials)._retrieve_projects(None, 2)
if len(projects) == 1:
proj... | [
"def",
"get_default_id",
"(",
"credentials",
"=",
"None",
")",
":",
"project_id",
"=",
"_utils",
".",
"get_project_id",
"(",
")",
"if",
"project_id",
"is",
"None",
":",
"projects",
",",
"_",
"=",
"Projects",
"(",
"credentials",
")",
".",
"_retrieve_projects"... | Get default project id.
Returns: the default project id if there is one, or None. | [
"Get",
"default",
"project",
"id",
"."
] | train | https://github.com/googledatalab/pydatalab/blob/d9031901d5bca22fe0d5925d204e6698df9852e1/datalab/context/_project.py#L97-L107 |
jpvanhal/flask-split | flask_split/core.py | init_app | def init_app(state):
"""
Prepare the Flask application for Flask-Split.
:param state: :class:`BlueprintSetupState` instance
"""
app = state.app
app.config.setdefault('SPLIT_ALLOW_MULTIPLE_EXPERIMENTS', False)
app.config.setdefault('SPLIT_DB_FAILOVER', False)
app.config.setdefault('SPLI... | python | def init_app(state):
"""
Prepare the Flask application for Flask-Split.
:param state: :class:`BlueprintSetupState` instance
"""
app = state.app
app.config.setdefault('SPLIT_ALLOW_MULTIPLE_EXPERIMENTS', False)
app.config.setdefault('SPLIT_DB_FAILOVER', False)
app.config.setdefault('SPLI... | [
"def",
"init_app",
"(",
"state",
")",
":",
"app",
"=",
"state",
".",
"app",
"app",
".",
"config",
".",
"setdefault",
"(",
"'SPLIT_ALLOW_MULTIPLE_EXPERIMENTS'",
",",
"False",
")",
"app",
".",
"config",
".",
"setdefault",
"(",
"'SPLIT_DB_FAILOVER'",
",",
"Fals... | Prepare the Flask application for Flask-Split.
:param state: :class:`BlueprintSetupState` instance | [
"Prepare",
"the",
"Flask",
"application",
"for",
"Flask",
"-",
"Split",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/core.py#L23-L61 |
jpvanhal/flask-split | flask_split/core.py | finished | def finished(experiment_name, reset=True):
"""
Track a conversion.
:param experiment_name: Name of the experiment.
:param reset: If set to `True` current user's session is reset so that they
may start the test again in the future. If set to `False` the user
will always see the alternat... | python | def finished(experiment_name, reset=True):
"""
Track a conversion.
:param experiment_name: Name of the experiment.
:param reset: If set to `True` current user's session is reset so that they
may start the test again in the future. If set to `False` the user
will always see the alternat... | [
"def",
"finished",
"(",
"experiment_name",
",",
"reset",
"=",
"True",
")",
":",
"if",
"_exclude_visitor",
"(",
")",
":",
"return",
"redis",
"=",
"_get_redis_connection",
"(",
")",
"try",
":",
"experiment",
"=",
"Experiment",
".",
"find",
"(",
"redis",
",",... | Track a conversion.
:param experiment_name: Name of the experiment.
:param reset: If set to `True` current user's session is reset so that they
may start the test again in the future. If set to `False` the user
will always see the alternative they started with. Defaults to `True`. | [
"Track",
"a",
"conversion",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/core.py#L108-L142 |
jpvanhal/flask-split | flask_split/core.py | _is_robot | def _is_robot():
"""
Return `True` if the current visitor is a robot or spider, or
`False` otherwise.
This function works by comparing the request's user agent with a regular
expression. The regular expression can be configured with the
``SPLIT_ROBOT_REGEX`` setting.
"""
robot_regex = ... | python | def _is_robot():
"""
Return `True` if the current visitor is a robot or spider, or
`False` otherwise.
This function works by comparing the request's user agent with a regular
expression. The regular expression can be configured with the
``SPLIT_ROBOT_REGEX`` setting.
"""
robot_regex = ... | [
"def",
"_is_robot",
"(",
")",
":",
"robot_regex",
"=",
"current_app",
".",
"config",
"[",
"'SPLIT_ROBOT_REGEX'",
"]",
"user_agent",
"=",
"request",
".",
"headers",
".",
"get",
"(",
"'User-Agent'",
",",
"''",
")",
"return",
"re",
".",
"search",
"(",
"robot_... | Return `True` if the current visitor is a robot or spider, or
`False` otherwise.
This function works by comparing the request's user agent with a regular
expression. The regular expression can be configured with the
``SPLIT_ROBOT_REGEX`` setting. | [
"Return",
"True",
"if",
"the",
"current",
"visitor",
"is",
"a",
"robot",
"or",
"spider",
"or",
"False",
"otherwise",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/core.py#L206-L217 |
jpvanhal/flask-split | flask_split/models.py | Experiment.start_time | def start_time(self):
"""The start time of this experiment."""
t = self.redis.hget('experiment_start_times', self.name)
if t:
return datetime.strptime(t, '%Y-%m-%dT%H:%M:%S') | python | def start_time(self):
"""The start time of this experiment."""
t = self.redis.hget('experiment_start_times', self.name)
if t:
return datetime.strptime(t, '%Y-%m-%dT%H:%M:%S') | [
"def",
"start_time",
"(",
"self",
")",
":",
"t",
"=",
"self",
".",
"redis",
".",
"hget",
"(",
"'experiment_start_times'",
",",
"self",
".",
"name",
")",
"if",
"t",
":",
"return",
"datetime",
".",
"strptime",
"(",
"t",
",",
"'%Y-%m-%dT%H:%M:%S'",
")"
] | The start time of this experiment. | [
"The",
"start",
"time",
"of",
"this",
"experiment",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/models.py#L163-L167 |
jpvanhal/flask-split | flask_split/models.py | Experiment.reset | def reset(self):
"""Delete all data for this experiment."""
for alternative in self.alternatives:
alternative.reset()
self.reset_winner()
self.increment_version() | python | def reset(self):
"""Delete all data for this experiment."""
for alternative in self.alternatives:
alternative.reset()
self.reset_winner()
self.increment_version() | [
"def",
"reset",
"(",
"self",
")",
":",
"for",
"alternative",
"in",
"self",
".",
"alternatives",
":",
"alternative",
".",
"reset",
"(",
")",
"self",
".",
"reset_winner",
"(",
")",
"self",
".",
"increment_version",
"(",
")"
] | Delete all data for this experiment. | [
"Delete",
"all",
"data",
"for",
"this",
"experiment",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/models.py#L211-L216 |
jpvanhal/flask-split | flask_split/models.py | Experiment.delete | def delete(self):
"""Delete this experiment and all its data."""
for alternative in self.alternatives:
alternative.delete()
self.reset_winner()
self.redis.srem('experiments', self.name)
self.redis.delete(self.name)
self.increment_version() | python | def delete(self):
"""Delete this experiment and all its data."""
for alternative in self.alternatives:
alternative.delete()
self.reset_winner()
self.redis.srem('experiments', self.name)
self.redis.delete(self.name)
self.increment_version() | [
"def",
"delete",
"(",
"self",
")",
":",
"for",
"alternative",
"in",
"self",
".",
"alternatives",
":",
"alternative",
".",
"delete",
"(",
")",
"self",
".",
"reset_winner",
"(",
")",
"self",
".",
"redis",
".",
"srem",
"(",
"'experiments'",
",",
"self",
"... | Delete this experiment and all its data. | [
"Delete",
"this",
"experiment",
"and",
"all",
"its",
"data",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/models.py#L218-L225 |
jpvanhal/flask-split | flask_split/utils.py | _get_redis_connection | def _get_redis_connection():
"""
Return a Redis connection based on the Flask application's configuration.
The connection parameters are retrieved from `REDIS_URL` configuration
variable.
:return: an instance of :class:`redis.Connection`
"""
url = current_app.config.get('REDIS_URL', 'redis... | python | def _get_redis_connection():
"""
Return a Redis connection based on the Flask application's configuration.
The connection parameters are retrieved from `REDIS_URL` configuration
variable.
:return: an instance of :class:`redis.Connection`
"""
url = current_app.config.get('REDIS_URL', 'redis... | [
"def",
"_get_redis_connection",
"(",
")",
":",
"url",
"=",
"current_app",
".",
"config",
".",
"get",
"(",
"'REDIS_URL'",
",",
"'redis://localhost:6379'",
")",
"return",
"redis",
".",
"from_url",
"(",
"url",
",",
"decode_responses",
"=",
"True",
")"
] | Return a Redis connection based on the Flask application's configuration.
The connection parameters are retrieved from `REDIS_URL` configuration
variable.
:return: an instance of :class:`redis.Connection` | [
"Return",
"a",
"Redis",
"connection",
"based",
"on",
"the",
"Flask",
"application",
"s",
"configuration",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/utils.py#L24-L34 |
jpvanhal/flask-split | flask_split/views.py | set_experiment_winner | def set_experiment_winner(experiment):
"""Mark an alternative as the winner of the experiment."""
redis = _get_redis_connection()
experiment = Experiment.find(redis, experiment)
if experiment:
alternative_name = request.form.get('alternative')
alternative = Alternative(redis, alternative... | python | def set_experiment_winner(experiment):
"""Mark an alternative as the winner of the experiment."""
redis = _get_redis_connection()
experiment = Experiment.find(redis, experiment)
if experiment:
alternative_name = request.form.get('alternative')
alternative = Alternative(redis, alternative... | [
"def",
"set_experiment_winner",
"(",
"experiment",
")",
":",
"redis",
"=",
"_get_redis_connection",
"(",
")",
"experiment",
"=",
"Experiment",
".",
"find",
"(",
"redis",
",",
"experiment",
")",
"if",
"experiment",
":",
"alternative_name",
"=",
"request",
".",
... | Mark an alternative as the winner of the experiment. | [
"Mark",
"an",
"alternative",
"as",
"the",
"winner",
"of",
"the",
"experiment",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/views.py#L44-L53 |
jpvanhal/flask-split | flask_split/views.py | reset_experiment | def reset_experiment(experiment):
"""Delete all data for an experiment."""
redis = _get_redis_connection()
experiment = Experiment.find(redis, experiment)
if experiment:
experiment.reset()
return redirect(url_for('.index')) | python | def reset_experiment(experiment):
"""Delete all data for an experiment."""
redis = _get_redis_connection()
experiment = Experiment.find(redis, experiment)
if experiment:
experiment.reset()
return redirect(url_for('.index')) | [
"def",
"reset_experiment",
"(",
"experiment",
")",
":",
"redis",
"=",
"_get_redis_connection",
"(",
")",
"experiment",
"=",
"Experiment",
".",
"find",
"(",
"redis",
",",
"experiment",
")",
"if",
"experiment",
":",
"experiment",
".",
"reset",
"(",
")",
"retur... | Delete all data for an experiment. | [
"Delete",
"all",
"data",
"for",
"an",
"experiment",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/views.py#L57-L63 |
jpvanhal/flask-split | flask_split/views.py | delete_experiment | def delete_experiment(experiment):
"""Delete an experiment and all its data."""
redis = _get_redis_connection()
experiment = Experiment.find(redis, experiment)
if experiment:
experiment.delete()
return redirect(url_for('.index')) | python | def delete_experiment(experiment):
"""Delete an experiment and all its data."""
redis = _get_redis_connection()
experiment = Experiment.find(redis, experiment)
if experiment:
experiment.delete()
return redirect(url_for('.index')) | [
"def",
"delete_experiment",
"(",
"experiment",
")",
":",
"redis",
"=",
"_get_redis_connection",
"(",
")",
"experiment",
"=",
"Experiment",
".",
"find",
"(",
"redis",
",",
"experiment",
")",
"if",
"experiment",
":",
"experiment",
".",
"delete",
"(",
")",
"ret... | Delete an experiment and all its data. | [
"Delete",
"an",
"experiment",
"and",
"all",
"its",
"data",
"."
] | train | https://github.com/jpvanhal/flask-split/blob/52bc9df49b5ce8b0ec436ba09b361a4b0b1793ba/flask_split/views.py#L67-L73 |
tobami/littlechef | littlechef/chef.py | save_config | def save_config(node, force=False):
"""Saves node configuration
if no nodes/hostname.json exists, or force=True, it creates one
it also saves to tmp_node.json
"""
filepath = os.path.join("nodes", env.host_string + ".json")
tmp_filename = 'tmp_{0}.json'.format(env.host_string)
files_to_creat... | python | def save_config(node, force=False):
"""Saves node configuration
if no nodes/hostname.json exists, or force=True, it creates one
it also saves to tmp_node.json
"""
filepath = os.path.join("nodes", env.host_string + ".json")
tmp_filename = 'tmp_{0}.json'.format(env.host_string)
files_to_creat... | [
"def",
"save_config",
"(",
"node",
",",
"force",
"=",
"False",
")",
":",
"filepath",
"=",
"os",
".",
"path",
".",
"join",
"(",
"\"nodes\"",
",",
"env",
".",
"host_string",
"+",
"\".json\"",
")",
"tmp_filename",
"=",
"'tmp_{0}.json'",
".",
"format",
"(",
... | Saves node configuration
if no nodes/hostname.json exists, or force=True, it creates one
it also saves to tmp_node.json | [
"Saves",
"node",
"configuration",
"if",
"no",
"nodes",
"/",
"hostname",
".",
"json",
"exists",
"or",
"force",
"=",
"True",
"it",
"creates",
"one",
"it",
"also",
"saves",
"to",
"tmp_node",
".",
"json"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L36-L52 |
tobami/littlechef | littlechef/chef.py | _get_ipaddress | def _get_ipaddress(node):
"""Adds the ipaddress attribute to the given node object if not already
present and it is correctly given by ohai
Returns True if ipaddress is added, False otherwise
"""
if "ipaddress" not in node:
with settings(hide('stdout'), warn_only=True):
output =... | python | def _get_ipaddress(node):
"""Adds the ipaddress attribute to the given node object if not already
present and it is correctly given by ohai
Returns True if ipaddress is added, False otherwise
"""
if "ipaddress" not in node:
with settings(hide('stdout'), warn_only=True):
output =... | [
"def",
"_get_ipaddress",
"(",
"node",
")",
":",
"if",
"\"ipaddress\"",
"not",
"in",
"node",
":",
"with",
"settings",
"(",
"hide",
"(",
"'stdout'",
")",
",",
"warn_only",
"=",
"True",
")",
":",
"output",
"=",
"sudo",
"(",
"'ohai -l warn ipaddress'",
")",
... | Adds the ipaddress attribute to the given node object if not already
present and it is correctly given by ohai
Returns True if ipaddress is added, False otherwise | [
"Adds",
"the",
"ipaddress",
"attribute",
"to",
"the",
"given",
"node",
"object",
"if",
"not",
"already",
"present",
"and",
"it",
"is",
"correctly",
"given",
"by",
"ohai",
"Returns",
"True",
"if",
"ipaddress",
"is",
"added",
"False",
"otherwise"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L55-L71 |
tobami/littlechef | littlechef/chef.py | sync_node | def sync_node(node):
"""Builds, synchronizes and configures a node.
It also injects the ipaddress to the node's config file if not already
existent.
"""
if node.get('dummy') or 'dummy' in node.get('tags', []):
lib.print_header("Skipping dummy: {0}".format(env.host))
return False
... | python | def sync_node(node):
"""Builds, synchronizes and configures a node.
It also injects the ipaddress to the node's config file if not already
existent.
"""
if node.get('dummy') or 'dummy' in node.get('tags', []):
lib.print_header("Skipping dummy: {0}".format(env.host))
return False
... | [
"def",
"sync_node",
"(",
"node",
")",
":",
"if",
"node",
".",
"get",
"(",
"'dummy'",
")",
"or",
"'dummy'",
"in",
"node",
".",
"get",
"(",
"'tags'",
",",
"[",
"]",
")",
":",
"lib",
".",
"print_header",
"(",
"\"Skipping dummy: {0}\"",
".",
"format",
"(... | Builds, synchronizes and configures a node.
It also injects the ipaddress to the node's config file if not already
existent. | [
"Builds",
"synchronizes",
"and",
"configures",
"a",
"node",
".",
"It",
"also",
"injects",
"the",
"ipaddress",
"to",
"the",
"node",
"s",
"config",
"file",
"if",
"not",
"already",
"existent",
"."
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L86-L110 |
tobami/littlechef | littlechef/chef.py | _synchronize_node | def _synchronize_node(configfile, node):
"""Performs the Synchronize step of a Chef run:
Uploads all cookbooks, all roles and all databags to a node and add the
patch for data bags
Returns the node object of the node which is about to be configured,
or None if this node object cannot be found.
... | python | def _synchronize_node(configfile, node):
"""Performs the Synchronize step of a Chef run:
Uploads all cookbooks, all roles and all databags to a node and add the
patch for data bags
Returns the node object of the node which is about to be configured,
or None if this node object cannot be found.
... | [
"def",
"_synchronize_node",
"(",
"configfile",
",",
"node",
")",
":",
"msg",
"=",
"\"Synchronizing nodes, environments, roles, cookbooks and data bags...\"",
"if",
"env",
".",
"parallel",
":",
"msg",
"=",
"\"[{0}]: {1}\"",
".",
"format",
"(",
"env",
".",
"host_string"... | Performs the Synchronize step of a Chef run:
Uploads all cookbooks, all roles and all databags to a node and add the
patch for data bags
Returns the node object of the node which is about to be configured,
or None if this node object cannot be found. | [
"Performs",
"the",
"Synchronize",
"step",
"of",
"a",
"Chef",
"run",
":",
"Uploads",
"all",
"cookbooks",
"all",
"roles",
"and",
"all",
"databags",
"to",
"a",
"node",
"and",
"add",
"the",
"patch",
"for",
"data",
"bags"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L113-L189 |
tobami/littlechef | littlechef/chef.py | build_dct | def build_dct(dic, keys, value):
"""Builds a dictionary with arbitrary depth out of a key list"""
key = keys.pop(0)
if len(keys):
dic.setdefault(key, {})
build_dct(dic[key], keys, value)
else:
# Transform cookbook default attribute strings into proper booleans
if value ==... | python | def build_dct(dic, keys, value):
"""Builds a dictionary with arbitrary depth out of a key list"""
key = keys.pop(0)
if len(keys):
dic.setdefault(key, {})
build_dct(dic[key], keys, value)
else:
# Transform cookbook default attribute strings into proper booleans
if value ==... | [
"def",
"build_dct",
"(",
"dic",
",",
"keys",
",",
"value",
")",
":",
"key",
"=",
"keys",
".",
"pop",
"(",
"0",
")",
"if",
"len",
"(",
"keys",
")",
":",
"dic",
".",
"setdefault",
"(",
"key",
",",
"{",
"}",
")",
"build_dct",
"(",
"dic",
"[",
"k... | Builds a dictionary with arbitrary depth out of a key list | [
"Builds",
"a",
"dictionary",
"with",
"arbitrary",
"depth",
"out",
"of",
"a",
"key",
"list"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L192-L205 |
tobami/littlechef | littlechef/chef.py | update_dct | def update_dct(dic1, dic2):
"""Merges two dictionaries recursively
dic2 will have preference over dic1
"""
for key, val in dic2.items():
if isinstance(val, dict):
dic1.setdefault(key, {})
update_dct(dic1[key], val)
else:
dic1[key] = val | python | def update_dct(dic1, dic2):
"""Merges two dictionaries recursively
dic2 will have preference over dic1
"""
for key, val in dic2.items():
if isinstance(val, dict):
dic1.setdefault(key, {})
update_dct(dic1[key], val)
else:
dic1[key] = val | [
"def",
"update_dct",
"(",
"dic1",
",",
"dic2",
")",
":",
"for",
"key",
",",
"val",
"in",
"dic2",
".",
"items",
"(",
")",
":",
"if",
"isinstance",
"(",
"val",
",",
"dict",
")",
":",
"dic1",
".",
"setdefault",
"(",
"key",
",",
"{",
"}",
")",
"upd... | Merges two dictionaries recursively
dic2 will have preference over dic1 | [
"Merges",
"two",
"dictionaries",
"recursively",
"dic2",
"will",
"have",
"preference",
"over",
"dic1"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L208-L218 |
tobami/littlechef | littlechef/chef.py | _add_automatic_attributes | def _add_automatic_attributes(node):
"""Adds some of Chef's automatic attributes:
http://wiki.opscode.com/display/chef/Recipes#Recipes
-CommonAutomaticAttributes
"""
node['fqdn'] = node['name']
node['hostname'] = node['fqdn'].split('.')[0]
node['domain'] = ".".join(node['fqdn'].spli... | python | def _add_automatic_attributes(node):
"""Adds some of Chef's automatic attributes:
http://wiki.opscode.com/display/chef/Recipes#Recipes
-CommonAutomaticAttributes
"""
node['fqdn'] = node['name']
node['hostname'] = node['fqdn'].split('.')[0]
node['domain'] = ".".join(node['fqdn'].spli... | [
"def",
"_add_automatic_attributes",
"(",
"node",
")",
":",
"node",
"[",
"'fqdn'",
"]",
"=",
"node",
"[",
"'name'",
"]",
"node",
"[",
"'hostname'",
"]",
"=",
"node",
"[",
"'fqdn'",
"]",
".",
"split",
"(",
"'.'",
")",
"[",
"0",
"]",
"node",
"[",
"'do... | Adds some of Chef's automatic attributes:
http://wiki.opscode.com/display/chef/Recipes#Recipes
-CommonAutomaticAttributes | [
"Adds",
"some",
"of",
"Chef",
"s",
"automatic",
"attributes",
":",
"http",
":",
"//",
"wiki",
".",
"opscode",
".",
"com",
"/",
"display",
"/",
"chef",
"/",
"Recipes#Recipes",
"-",
"CommonAutomaticAttributes"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L221-L229 |
tobami/littlechef | littlechef/chef.py | _add_merged_attributes | def _add_merged_attributes(node, all_recipes, all_roles):
"""Merges attributes from cookbooks, node and roles
Chef Attribute precedence:
http://docs.opscode.com/essentials_cookbook_attribute_files.html#attribute-precedence
LittleChef implements, in precedence order:
- Cookbook default
-... | python | def _add_merged_attributes(node, all_recipes, all_roles):
"""Merges attributes from cookbooks, node and roles
Chef Attribute precedence:
http://docs.opscode.com/essentials_cookbook_attribute_files.html#attribute-precedence
LittleChef implements, in precedence order:
- Cookbook default
-... | [
"def",
"_add_merged_attributes",
"(",
"node",
",",
"all_recipes",
",",
"all_roles",
")",
":",
"# Get cookbooks from extended recipes",
"attributes",
"=",
"{",
"}",
"for",
"recipe",
"in",
"node",
"[",
"'recipes'",
"]",
":",
"# Find this recipe",
"found",
"=",
"Fals... | Merges attributes from cookbooks, node and roles
Chef Attribute precedence:
http://docs.opscode.com/essentials_cookbook_attribute_files.html#attribute-precedence
LittleChef implements, in precedence order:
- Cookbook default
- Environment default
- Role default
- Node normal... | [
"Merges",
"attributes",
"from",
"cookbooks",
"node",
"and",
"roles"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L232-L300 |
tobami/littlechef | littlechef/chef.py | build_node_data_bag | def build_node_data_bag():
"""Builds one 'node' data bag item per file found in the 'nodes' directory
Automatic attributes for a node item:
'id': It adds data bag 'id', same as filename but with underscores
'name': same as the filename
'fqdn': same as the filename (LittleChef filenames ... | python | def build_node_data_bag():
"""Builds one 'node' data bag item per file found in the 'nodes' directory
Automatic attributes for a node item:
'id': It adds data bag 'id', same as filename but with underscores
'name': same as the filename
'fqdn': same as the filename (LittleChef filenames ... | [
"def",
"build_node_data_bag",
"(",
")",
":",
"nodes",
"=",
"lib",
".",
"get_nodes",
"(",
")",
"node_data_bag_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"'data_bags'",
",",
"'node'",
")",
"# In case there are leftovers",
"remove_local_node_data_bag",
"(",
"... | Builds one 'node' data bag item per file found in the 'nodes' directory
Automatic attributes for a node item:
'id': It adds data bag 'id', same as filename but with underscores
'name': same as the filename
'fqdn': same as the filename (LittleChef filenames should be fqdns)
'hostname... | [
"Builds",
"one",
"node",
"data",
"bag",
"item",
"per",
"file",
"found",
"in",
"the",
"nodes",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L303-L352 |
tobami/littlechef | littlechef/chef.py | remove_local_node_data_bag | def remove_local_node_data_bag():
"""Removes generated 'node' data_bag locally"""
node_data_bag_path = os.path.join('data_bags', 'node')
if os.path.exists(node_data_bag_path):
shutil.rmtree(node_data_bag_path) | python | def remove_local_node_data_bag():
"""Removes generated 'node' data_bag locally"""
node_data_bag_path = os.path.join('data_bags', 'node')
if os.path.exists(node_data_bag_path):
shutil.rmtree(node_data_bag_path) | [
"def",
"remove_local_node_data_bag",
"(",
")",
":",
"node_data_bag_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"'data_bags'",
",",
"'node'",
")",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"node_data_bag_path",
")",
":",
"shutil",
".",
"rmtree",
"("... | Removes generated 'node' data_bag locally | [
"Removes",
"generated",
"node",
"data_bag",
"locally"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L355-L359 |
tobami/littlechef | littlechef/chef.py | ensure_berksfile_cookbooks_are_installed | def ensure_berksfile_cookbooks_are_installed():
"""Run 'berks vendor' to berksfile cookbooks directory"""
msg = "Vendoring cookbooks from Berksfile {0} to directory {1}..."
print(msg.format(env.berksfile, env.berksfile_cookbooks_directory))
run_vendor = True
cookbooks_dir = env.berksfile_cookbooks_... | python | def ensure_berksfile_cookbooks_are_installed():
"""Run 'berks vendor' to berksfile cookbooks directory"""
msg = "Vendoring cookbooks from Berksfile {0} to directory {1}..."
print(msg.format(env.berksfile, env.berksfile_cookbooks_directory))
run_vendor = True
cookbooks_dir = env.berksfile_cookbooks_... | [
"def",
"ensure_berksfile_cookbooks_are_installed",
"(",
")",
":",
"msg",
"=",
"\"Vendoring cookbooks from Berksfile {0} to directory {1}...\"",
"print",
"(",
"msg",
".",
"format",
"(",
"env",
".",
"berksfile",
",",
"env",
".",
"berksfile_cookbooks_directory",
")",
")",
... | Run 'berks vendor' to berksfile cookbooks directory | [
"Run",
"berks",
"vendor",
"to",
"berksfile",
"cookbooks",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L362-L388 |
tobami/littlechef | littlechef/chef.py | _remove_remote_node_data_bag | def _remove_remote_node_data_bag():
"""Removes generated 'node' data_bag from the remote node"""
node_data_bag_path = os.path.join(env.node_work_path, 'data_bags', 'node')
if exists(node_data_bag_path):
sudo("rm -rf {0}".format(node_data_bag_path)) | python | def _remove_remote_node_data_bag():
"""Removes generated 'node' data_bag from the remote node"""
node_data_bag_path = os.path.join(env.node_work_path, 'data_bags', 'node')
if exists(node_data_bag_path):
sudo("rm -rf {0}".format(node_data_bag_path)) | [
"def",
"_remove_remote_node_data_bag",
"(",
")",
":",
"node_data_bag_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"env",
".",
"node_work_path",
",",
"'data_bags'",
",",
"'node'",
")",
"if",
"exists",
"(",
"node_data_bag_path",
")",
":",
"sudo",
"(",
"\"r... | Removes generated 'node' data_bag from the remote node | [
"Removes",
"generated",
"node",
"data_bag",
"from",
"the",
"remote",
"node"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L391-L395 |
tobami/littlechef | littlechef/chef.py | _remove_remote_data_bags | def _remove_remote_data_bags():
"""Remove remote data bags, so it won't leak any sensitive information"""
data_bags_path = os.path.join(env.node_work_path, 'data_bags')
if exists(data_bags_path):
sudo("rm -rf {0}".format(data_bags_path)) | python | def _remove_remote_data_bags():
"""Remove remote data bags, so it won't leak any sensitive information"""
data_bags_path = os.path.join(env.node_work_path, 'data_bags')
if exists(data_bags_path):
sudo("rm -rf {0}".format(data_bags_path)) | [
"def",
"_remove_remote_data_bags",
"(",
")",
":",
"data_bags_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"env",
".",
"node_work_path",
",",
"'data_bags'",
")",
"if",
"exists",
"(",
"data_bags_path",
")",
":",
"sudo",
"(",
"\"rm -rf {0}\"",
".",
"format"... | Remove remote data bags, so it won't leak any sensitive information | [
"Remove",
"remote",
"data",
"bags",
"so",
"it",
"won",
"t",
"leak",
"any",
"sensitive",
"information"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L397-L401 |
tobami/littlechef | littlechef/chef.py | _add_environment_lib | def _add_environment_lib():
"""Adds the chef_solo_envs cookbook, which provides a library that adds
environment attribute compatibility for chef-solo v10
NOTE: Chef 10 only
"""
# Create extra cookbook dir
lib_path = os.path.join(env.node_work_path, cookbook_paths[0],
... | python | def _add_environment_lib():
"""Adds the chef_solo_envs cookbook, which provides a library that adds
environment attribute compatibility for chef-solo v10
NOTE: Chef 10 only
"""
# Create extra cookbook dir
lib_path = os.path.join(env.node_work_path, cookbook_paths[0],
... | [
"def",
"_add_environment_lib",
"(",
")",
":",
"# Create extra cookbook dir",
"lib_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"env",
".",
"node_work_path",
",",
"cookbook_paths",
"[",
"0",
"]",
",",
"'chef_solo_envs'",
",",
"'libraries'",
")",
"with",
"hi... | Adds the chef_solo_envs cookbook, which provides a library that adds
environment attribute compatibility for chef-solo v10
NOTE: Chef 10 only | [
"Adds",
"the",
"chef_solo_envs",
"cookbook",
"which",
"provides",
"a",
"library",
"that",
"adds",
"environment",
"attribute",
"compatibility",
"for",
"chef",
"-",
"solo",
"v10",
"NOTE",
":",
"Chef",
"10",
"only"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L415-L428 |
tobami/littlechef | littlechef/chef.py | _configure_node | def _configure_node():
"""Exectutes chef-solo to apply roles and recipes to a node"""
print("")
msg = "Cooking..."
if env.parallel:
msg = "[{0}]: {1}".format(env.host_string, msg)
print(msg)
# Backup last report
with settings(hide('stdout', 'warnings', 'running'), warn_only=True):
... | python | def _configure_node():
"""Exectutes chef-solo to apply roles and recipes to a node"""
print("")
msg = "Cooking..."
if env.parallel:
msg = "[{0}]: {1}".format(env.host_string, msg)
print(msg)
# Backup last report
with settings(hide('stdout', 'warnings', 'running'), warn_only=True):
... | [
"def",
"_configure_node",
"(",
")",
":",
"print",
"(",
"\"\"",
")",
"msg",
"=",
"\"Cooking...\"",
"if",
"env",
".",
"parallel",
":",
"msg",
"=",
"\"[{0}]: {1}\"",
".",
"format",
"(",
"env",
".",
"host_string",
",",
"msg",
")",
"print",
"(",
"msg",
")",... | Exectutes chef-solo to apply roles and recipes to a node | [
"Exectutes",
"chef",
"-",
"solo",
"to",
"apply",
"roles",
"and",
"recipes",
"to",
"a",
"node"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/chef.py#L431-L474 |
tobami/littlechef | littlechef/lib.py | _resolve_hostname | def _resolve_hostname(name):
"""Returns resolved hostname using the ssh config"""
if env.ssh_config is None:
return name
elif not os.path.exists(os.path.join("nodes", name + ".json")):
resolved_name = env.ssh_config.lookup(name)['hostname']
if os.path.exists(os.path.join("nodes", res... | python | def _resolve_hostname(name):
"""Returns resolved hostname using the ssh config"""
if env.ssh_config is None:
return name
elif not os.path.exists(os.path.join("nodes", name + ".json")):
resolved_name = env.ssh_config.lookup(name)['hostname']
if os.path.exists(os.path.join("nodes", res... | [
"def",
"_resolve_hostname",
"(",
"name",
")",
":",
"if",
"env",
".",
"ssh_config",
"is",
"None",
":",
"return",
"name",
"elif",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"os",
".",
"path",
".",
"join",
"(",
"\"nodes\"",
",",
"name",
"+",
"\".json... | Returns resolved hostname using the ssh config | [
"Returns",
"resolved",
"hostname",
"using",
"the",
"ssh",
"config"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L31-L39 |
tobami/littlechef | littlechef/lib.py | get_environment | def get_environment(name):
"""Returns a JSON environment file as a dictionary"""
if name == "_default":
return env_from_template(name)
filename = os.path.join("environments", name + ".json")
try:
with open(filename) as f:
try:
return json.loads(f.read())
... | python | def get_environment(name):
"""Returns a JSON environment file as a dictionary"""
if name == "_default":
return env_from_template(name)
filename = os.path.join("environments", name + ".json")
try:
with open(filename) as f:
try:
return json.loads(f.read())
... | [
"def",
"get_environment",
"(",
"name",
")",
":",
"if",
"name",
"==",
"\"_default\"",
":",
"return",
"env_from_template",
"(",
"name",
")",
"filename",
"=",
"os",
".",
"path",
".",
"join",
"(",
"\"environments\"",
",",
"name",
"+",
"\".json\"",
")",
"try",
... | Returns a JSON environment file as a dictionary | [
"Returns",
"a",
"JSON",
"environment",
"file",
"as",
"a",
"dictionary"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L62-L76 |
tobami/littlechef | littlechef/lib.py | get_environments | def get_environments():
"""Gets all environments found in the 'environments' directory"""
envs = []
for root, subfolders, files in os.walk('environments'):
for filename in files:
if filename.endswith(".json"):
path = os.path.join(
root[len('environment... | python | def get_environments():
"""Gets all environments found in the 'environments' directory"""
envs = []
for root, subfolders, files in os.walk('environments'):
for filename in files:
if filename.endswith(".json"):
path = os.path.join(
root[len('environment... | [
"def",
"get_environments",
"(",
")",
":",
"envs",
"=",
"[",
"]",
"for",
"root",
",",
"subfolders",
",",
"files",
"in",
"os",
".",
"walk",
"(",
"'environments'",
")",
":",
"for",
"filename",
"in",
"files",
":",
"if",
"filename",
".",
"endswith",
"(",
... | Gets all environments found in the 'environments' directory | [
"Gets",
"all",
"environments",
"found",
"in",
"the",
"environments",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L79-L88 |
tobami/littlechef | littlechef/lib.py | get_node | def get_node(name, merged=False):
"""Returns a JSON node file as a dictionary"""
if merged:
node_path = os.path.join("data_bags", "node", name.replace('.', '_') + ".json")
else:
node_path = os.path.join("nodes", name + ".json")
if os.path.exists(node_path):
# Read node.json
... | python | def get_node(name, merged=False):
"""Returns a JSON node file as a dictionary"""
if merged:
node_path = os.path.join("data_bags", "node", name.replace('.', '_') + ".json")
else:
node_path = os.path.join("nodes", name + ".json")
if os.path.exists(node_path):
# Read node.json
... | [
"def",
"get_node",
"(",
"name",
",",
"merged",
"=",
"False",
")",
":",
"if",
"merged",
":",
"node_path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"\"data_bags\"",
",",
"\"node\"",
",",
"name",
".",
"replace",
"(",
"'.'",
",",
"'_'",
")",
"+",
"\".... | Returns a JSON node file as a dictionary | [
"Returns",
"a",
"JSON",
"node",
"file",
"as",
"a",
"dictionary"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L91-L113 |
tobami/littlechef | littlechef/lib.py | get_nodes | def get_nodes(environment=None):
"""Gets all nodes found in the nodes/ directory"""
if not os.path.exists('nodes'):
return []
nodes = []
for filename in sorted(
[f for f in os.listdir('nodes')
if (not os.path.isdir(f)
and f.endswith(".json") and not f.st... | python | def get_nodes(environment=None):
"""Gets all nodes found in the nodes/ directory"""
if not os.path.exists('nodes'):
return []
nodes = []
for filename in sorted(
[f for f in os.listdir('nodes')
if (not os.path.isdir(f)
and f.endswith(".json") and not f.st... | [
"def",
"get_nodes",
"(",
"environment",
"=",
"None",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"'nodes'",
")",
":",
"return",
"[",
"]",
"nodes",
"=",
"[",
"]",
"for",
"filename",
"in",
"sorted",
"(",
"[",
"f",
"for",
"f",
"in"... | Gets all nodes found in the nodes/ directory | [
"Gets",
"all",
"nodes",
"found",
"in",
"the",
"nodes",
"/",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L116-L129 |
tobami/littlechef | littlechef/lib.py | get_nodes_with_role | def get_nodes_with_role(role_name, environment=None):
"""Get all nodes which include a given role,
prefix-searches are also supported
"""
prefix_search = role_name.endswith("*")
if prefix_search:
role_name = role_name.rstrip("*")
for n in get_nodes(environment):
roles = get_role... | python | def get_nodes_with_role(role_name, environment=None):
"""Get all nodes which include a given role,
prefix-searches are also supported
"""
prefix_search = role_name.endswith("*")
if prefix_search:
role_name = role_name.rstrip("*")
for n in get_nodes(environment):
roles = get_role... | [
"def",
"get_nodes_with_role",
"(",
"role_name",
",",
"environment",
"=",
"None",
")",
":",
"prefix_search",
"=",
"role_name",
".",
"endswith",
"(",
"\"*\"",
")",
"if",
"prefix_search",
":",
"role_name",
"=",
"role_name",
".",
"rstrip",
"(",
"\"*\"",
")",
"fo... | Get all nodes which include a given role,
prefix-searches are also supported | [
"Get",
"all",
"nodes",
"which",
"include",
"a",
"given",
"role",
"prefix",
"-",
"searches",
"are",
"also",
"supported"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L132-L147 |
tobami/littlechef | littlechef/lib.py | get_nodes_with_tag | def get_nodes_with_tag(tag, environment=None, include_guests=False):
"""Get all nodes which include a given tag"""
nodes = get_nodes(environment)
nodes_mapping = dict((n['name'], n) for n in nodes)
for n in nodes:
if tag in n.get('tags', []):
# Remove from node mapping so it doesn't ... | python | def get_nodes_with_tag(tag, environment=None, include_guests=False):
"""Get all nodes which include a given tag"""
nodes = get_nodes(environment)
nodes_mapping = dict((n['name'], n) for n in nodes)
for n in nodes:
if tag in n.get('tags', []):
# Remove from node mapping so it doesn't ... | [
"def",
"get_nodes_with_tag",
"(",
"tag",
",",
"environment",
"=",
"None",
",",
"include_guests",
"=",
"False",
")",
":",
"nodes",
"=",
"get_nodes",
"(",
"environment",
")",
"nodes_mapping",
"=",
"dict",
"(",
"(",
"n",
"[",
"'name'",
"]",
",",
"n",
")",
... | Get all nodes which include a given tag | [
"Get",
"all",
"nodes",
"which",
"include",
"a",
"given",
"tag"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L150-L171 |
tobami/littlechef | littlechef/lib.py | get_nodes_with_recipe | def get_nodes_with_recipe(recipe_name, environment=None):
"""Get all nodes which include a given recipe,
prefix-searches are also supported
"""
prefix_search = recipe_name.endswith("*")
if prefix_search:
recipe_name = recipe_name.rstrip("*")
for n in get_nodes(environment):
reci... | python | def get_nodes_with_recipe(recipe_name, environment=None):
"""Get all nodes which include a given recipe,
prefix-searches are also supported
"""
prefix_search = recipe_name.endswith("*")
if prefix_search:
recipe_name = recipe_name.rstrip("*")
for n in get_nodes(environment):
reci... | [
"def",
"get_nodes_with_recipe",
"(",
"recipe_name",
",",
"environment",
"=",
"None",
")",
":",
"prefix_search",
"=",
"recipe_name",
".",
"endswith",
"(",
"\"*\"",
")",
"if",
"prefix_search",
":",
"recipe_name",
"=",
"recipe_name",
".",
"rstrip",
"(",
"\"*\"",
... | Get all nodes which include a given recipe,
prefix-searches are also supported | [
"Get",
"all",
"nodes",
"which",
"include",
"a",
"given",
"recipe",
"prefix",
"-",
"searches",
"are",
"also",
"supported"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L174-L191 |
tobami/littlechef | littlechef/lib.py | print_node | def print_node(node, detailed=False):
"""Pretty prints the given node"""
nodename = node['name']
print(colors.yellow("\n" + nodename))
# Roles
if detailed:
for role in get_roles_in_node(node):
print_role(_get_role(role), detailed=False)
else:
print(' Roles: {0}'.form... | python | def print_node(node, detailed=False):
"""Pretty prints the given node"""
nodename = node['name']
print(colors.yellow("\n" + nodename))
# Roles
if detailed:
for role in get_roles_in_node(node):
print_role(_get_role(role), detailed=False)
else:
print(' Roles: {0}'.form... | [
"def",
"print_node",
"(",
"node",
",",
"detailed",
"=",
"False",
")",
":",
"nodename",
"=",
"node",
"[",
"'name'",
"]",
"print",
"(",
"colors",
".",
"yellow",
"(",
"\"\\n\"",
"+",
"nodename",
")",
")",
"# Roles",
"if",
"detailed",
":",
"for",
"role",
... | Pretty prints the given node | [
"Pretty",
"prints",
"the",
"given",
"node"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L194-L216 |
tobami/littlechef | littlechef/lib.py | print_nodes | def print_nodes(nodes, detailed=False):
"""Prints all the given nodes"""
found = 0
for node in nodes:
found += 1
print_node(node, detailed=detailed)
print("\nFound {0} node{1}".format(found, "s" if found != 1 else "")) | python | def print_nodes(nodes, detailed=False):
"""Prints all the given nodes"""
found = 0
for node in nodes:
found += 1
print_node(node, detailed=detailed)
print("\nFound {0} node{1}".format(found, "s" if found != 1 else "")) | [
"def",
"print_nodes",
"(",
"nodes",
",",
"detailed",
"=",
"False",
")",
":",
"found",
"=",
"0",
"for",
"node",
"in",
"nodes",
":",
"found",
"+=",
"1",
"print_node",
"(",
"node",
",",
"detailed",
"=",
"detailed",
")",
"print",
"(",
"\"\\nFound {0} node{1}... | Prints all the given nodes | [
"Prints",
"all",
"the",
"given",
"nodes"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L219-L225 |
tobami/littlechef | littlechef/lib.py | _generate_metadata | def _generate_metadata(path, cookbook_path, name):
"""Checks whether metadata.rb has changed and regenerate metadata.json"""
global knife_installed
if not knife_installed:
return
metadata_path_rb = os.path.join(path, 'metadata.rb')
metadata_path_json = os.path.join(path, 'metadata.json')
... | python | def _generate_metadata(path, cookbook_path, name):
"""Checks whether metadata.rb has changed and regenerate metadata.json"""
global knife_installed
if not knife_installed:
return
metadata_path_rb = os.path.join(path, 'metadata.rb')
metadata_path_json = os.path.join(path, 'metadata.json')
... | [
"def",
"_generate_metadata",
"(",
"path",
",",
"cookbook_path",
",",
"name",
")",
":",
"global",
"knife_installed",
"if",
"not",
"knife_installed",
":",
"return",
"metadata_path_rb",
"=",
"os",
".",
"path",
".",
"join",
"(",
"path",
",",
"'metadata.rb'",
")",
... | Checks whether metadata.rb has changed and regenerate metadata.json | [
"Checks",
"whether",
"metadata",
".",
"rb",
"has",
"changed",
"and",
"regenerate",
"metadata",
".",
"json"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L228-L268 |
tobami/littlechef | littlechef/lib.py | get_recipes_in_cookbook | def get_recipes_in_cookbook(name):
"""Gets the name of all recipes present in a cookbook
Returns a list of dictionaries
"""
recipes = {}
path = None
cookbook_exists = False
metadata_exists = False
for cookbook_path in cookbook_paths:
path = os.path.join(cookbook_path, name)
... | python | def get_recipes_in_cookbook(name):
"""Gets the name of all recipes present in a cookbook
Returns a list of dictionaries
"""
recipes = {}
path = None
cookbook_exists = False
metadata_exists = False
for cookbook_path in cookbook_paths:
path = os.path.join(cookbook_path, name)
... | [
"def",
"get_recipes_in_cookbook",
"(",
"name",
")",
":",
"recipes",
"=",
"{",
"}",
"path",
"=",
"None",
"cookbook_exists",
"=",
"False",
"metadata_exists",
"=",
"False",
"for",
"cookbook_path",
"in",
"cookbook_paths",
":",
"path",
"=",
"os",
".",
"path",
"."... | Gets the name of all recipes present in a cookbook
Returns a list of dictionaries | [
"Gets",
"the",
"name",
"of",
"all",
"recipes",
"present",
"in",
"a",
"cookbook",
"Returns",
"a",
"list",
"of",
"dictionaries"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L271-L348 |
tobami/littlechef | littlechef/lib.py | get_recipes_in_node | def get_recipes_in_node(node):
"""Gets the name of all recipes present in the run_list of a node"""
recipes = []
for elem in node.get('run_list', []):
if elem.startswith("recipe"):
recipe = elem.split('[')[1].split(']')[0]
recipes.append(recipe)
return recipes | python | def get_recipes_in_node(node):
"""Gets the name of all recipes present in the run_list of a node"""
recipes = []
for elem in node.get('run_list', []):
if elem.startswith("recipe"):
recipe = elem.split('[')[1].split(']')[0]
recipes.append(recipe)
return recipes | [
"def",
"get_recipes_in_node",
"(",
"node",
")",
":",
"recipes",
"=",
"[",
"]",
"for",
"elem",
"in",
"node",
".",
"get",
"(",
"'run_list'",
",",
"[",
"]",
")",
":",
"if",
"elem",
".",
"startswith",
"(",
"\"recipe\"",
")",
":",
"recipe",
"=",
"elem",
... | Gets the name of all recipes present in the run_list of a node | [
"Gets",
"the",
"name",
"of",
"all",
"recipes",
"present",
"in",
"the",
"run_list",
"of",
"a",
"node"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L357-L364 |
tobami/littlechef | littlechef/lib.py | get_recipes | def get_recipes():
"""Gets all recipes found in the cookbook directories"""
dirnames = set()
for path in cookbook_paths:
dirnames.update([d for d in os.listdir(path) if os.path.isdir(
os.path.join(path, d)) and not d.startswith('.')])
recipes = []
for dirname in d... | python | def get_recipes():
"""Gets all recipes found in the cookbook directories"""
dirnames = set()
for path in cookbook_paths:
dirnames.update([d for d in os.listdir(path) if os.path.isdir(
os.path.join(path, d)) and not d.startswith('.')])
recipes = []
for dirname in d... | [
"def",
"get_recipes",
"(",
")",
":",
"dirnames",
"=",
"set",
"(",
")",
"for",
"path",
"in",
"cookbook_paths",
":",
"dirnames",
".",
"update",
"(",
"[",
"d",
"for",
"d",
"in",
"os",
".",
"listdir",
"(",
"path",
")",
"if",
"os",
".",
"path",
".",
"... | Gets all recipes found in the cookbook directories | [
"Gets",
"all",
"recipes",
"found",
"in",
"the",
"cookbook",
"directories"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L367-L376 |
tobami/littlechef | littlechef/lib.py | print_recipe | def print_recipe(recipe):
"""Pretty prints the given recipe"""
print(colors.yellow("\n{0}".format(recipe['name'])))
print " description: {0}".format(recipe['description'])
print " version: {0}".format(recipe['version'])
print " dependencies: {0}".format(", ".join(recipe['dependencies']))
... | python | def print_recipe(recipe):
"""Pretty prints the given recipe"""
print(colors.yellow("\n{0}".format(recipe['name'])))
print " description: {0}".format(recipe['description'])
print " version: {0}".format(recipe['version'])
print " dependencies: {0}".format(", ".join(recipe['dependencies']))
... | [
"def",
"print_recipe",
"(",
"recipe",
")",
":",
"print",
"(",
"colors",
".",
"yellow",
"(",
"\"\\n{0}\"",
".",
"format",
"(",
"recipe",
"[",
"'name'",
"]",
")",
")",
")",
"print",
"\" description: {0}\"",
".",
"format",
"(",
"recipe",
"[",
"'description'... | Pretty prints the given recipe | [
"Pretty",
"prints",
"the",
"given",
"recipe"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L379-L385 |
tobami/littlechef | littlechef/lib.py | get_roles_in_node | def get_roles_in_node(node, recursive=False, depth=0):
"""Returns a list of roles found in the run_list of a node
* recursive: True feches roles recursively
* depth: Keeps track of recursion depth
"""
LIMIT = 5
roles = []
for elem in node.get('run_list', []):
if elem.startswith("rol... | python | def get_roles_in_node(node, recursive=False, depth=0):
"""Returns a list of roles found in the run_list of a node
* recursive: True feches roles recursively
* depth: Keeps track of recursion depth
"""
LIMIT = 5
roles = []
for elem in node.get('run_list', []):
if elem.startswith("rol... | [
"def",
"get_roles_in_node",
"(",
"node",
",",
"recursive",
"=",
"False",
",",
"depth",
"=",
"0",
")",
":",
"LIMIT",
"=",
"5",
"roles",
"=",
"[",
"]",
"for",
"elem",
"in",
"node",
".",
"get",
"(",
"'run_list'",
",",
"[",
"]",
")",
":",
"if",
"elem... | Returns a list of roles found in the run_list of a node
* recursive: True feches roles recursively
* depth: Keeps track of recursion depth | [
"Returns",
"a",
"list",
"of",
"roles",
"found",
"in",
"the",
"run_list",
"of",
"a",
"node",
"*",
"recursive",
":",
"True",
"feches",
"roles",
"recursively",
"*",
"depth",
":",
"Keeps",
"track",
"of",
"recursion",
"depth"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L393-L410 |
tobami/littlechef | littlechef/lib.py | _get_role | def _get_role(rolename):
"""Reads and parses a file containing a role"""
path = os.path.join('roles', rolename + '.json')
if not os.path.exists(path):
abort("Couldn't read role file {0}".format(path))
with open(path, 'r') as f:
try:
role = json.loads(f.read())
except ... | python | def _get_role(rolename):
"""Reads and parses a file containing a role"""
path = os.path.join('roles', rolename + '.json')
if not os.path.exists(path):
abort("Couldn't read role file {0}".format(path))
with open(path, 'r') as f:
try:
role = json.loads(f.read())
except ... | [
"def",
"_get_role",
"(",
"rolename",
")",
":",
"path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"'roles'",
",",
"rolename",
"+",
"'.json'",
")",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"path",
")",
":",
"abort",
"(",
"\"Couldn't read rol... | Reads and parses a file containing a role | [
"Reads",
"and",
"parses",
"a",
"file",
"containing",
"a",
"role"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L413-L426 |
tobami/littlechef | littlechef/lib.py | get_roles | def get_roles():
"""Gets all roles found in the 'roles' directory"""
roles = []
for root, subfolders, files in os.walk('roles'):
for filename in files:
if filename.endswith(".json"):
path = os.path.join(
root[len('roles'):], filename[:-len('.json')])
... | python | def get_roles():
"""Gets all roles found in the 'roles' directory"""
roles = []
for root, subfolders, files in os.walk('roles'):
for filename in files:
if filename.endswith(".json"):
path = os.path.join(
root[len('roles'):], filename[:-len('.json')])
... | [
"def",
"get_roles",
"(",
")",
":",
"roles",
"=",
"[",
"]",
"for",
"root",
",",
"subfolders",
",",
"files",
"in",
"os",
".",
"walk",
"(",
"'roles'",
")",
":",
"for",
"filename",
"in",
"files",
":",
"if",
"filename",
".",
"endswith",
"(",
"\".json\"",
... | Gets all roles found in the 'roles' directory | [
"Gets",
"all",
"roles",
"found",
"in",
"the",
"roles",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L429-L438 |
tobami/littlechef | littlechef/lib.py | print_role | def print_role(role, detailed=True):
"""Pretty prints the given role"""
if detailed:
print(colors.yellow(role.get('fullname')))
else:
print(" Role: {0}".format(role.get('fullname')))
if detailed:
print(" description: {0}".format(role.get('description')))
if 'default_attri... | python | def print_role(role, detailed=True):
"""Pretty prints the given role"""
if detailed:
print(colors.yellow(role.get('fullname')))
else:
print(" Role: {0}".format(role.get('fullname')))
if detailed:
print(" description: {0}".format(role.get('description')))
if 'default_attri... | [
"def",
"print_role",
"(",
"role",
",",
"detailed",
"=",
"True",
")",
":",
"if",
"detailed",
":",
"print",
"(",
"colors",
".",
"yellow",
"(",
"role",
".",
"get",
"(",
"'fullname'",
")",
")",
")",
"else",
":",
"print",
"(",
"\" Role: {0}\"",
".",
"for... | Pretty prints the given role | [
"Pretty",
"prints",
"the",
"given",
"role"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L441-L457 |
tobami/littlechef | littlechef/lib.py | get_plugins | def get_plugins():
"""Gets available plugins by looking into the plugins/ directory"""
if os.path.exists('plugins'):
for filename in sorted([f for f in os.listdir('plugins')
if not os.path.isdir(f) and f.endswith(".py")]):
plugin_name = filename[:-3]
try:
... | python | def get_plugins():
"""Gets available plugins by looking into the plugins/ directory"""
if os.path.exists('plugins'):
for filename in sorted([f for f in os.listdir('plugins')
if not os.path.isdir(f) and f.endswith(".py")]):
plugin_name = filename[:-3]
try:
... | [
"def",
"get_plugins",
"(",
")",
":",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"'plugins'",
")",
":",
"for",
"filename",
"in",
"sorted",
"(",
"[",
"f",
"for",
"f",
"in",
"os",
".",
"listdir",
"(",
"'plugins'",
")",
"if",
"not",
"os",
".",
"pat... | Gets available plugins by looking into the plugins/ directory | [
"Gets",
"available",
"plugins",
"by",
"looking",
"into",
"the",
"plugins",
"/",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L467-L479 |
tobami/littlechef | littlechef/lib.py | import_plugin | def import_plugin(name):
"""Imports plugin python module"""
path = os.path.join("plugins", name + ".py")
try:
with open(path, 'rb') as f:
try:
plugin = imp.load_module(
"p_" + name, f, name + '.py',
('.py', 'rb', imp.PY_SOURCE)
... | python | def import_plugin(name):
"""Imports plugin python module"""
path = os.path.join("plugins", name + ".py")
try:
with open(path, 'rb') as f:
try:
plugin = imp.load_module(
"p_" + name, f, name + '.py',
('.py', 'rb', imp.PY_SOURCE)
... | [
"def",
"import_plugin",
"(",
"name",
")",
":",
"path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"\"plugins\"",
",",
"name",
"+",
"\".py\"",
")",
"try",
":",
"with",
"open",
"(",
"path",
",",
"'rb'",
")",
"as",
"f",
":",
"try",
":",
"plugin",
"="... | Imports plugin python module | [
"Imports",
"plugin",
"python",
"module"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L482-L499 |
tobami/littlechef | littlechef/lib.py | get_cookbook_path | def get_cookbook_path(cookbook_name):
"""Returns path to the cookbook for the given cookbook name"""
for cookbook_path in cookbook_paths:
path = os.path.join(cookbook_path, cookbook_name)
if os.path.exists(path):
return path
raise IOError('Can\'t find cookbook with name "{0}"'.fo... | python | def get_cookbook_path(cookbook_name):
"""Returns path to the cookbook for the given cookbook name"""
for cookbook_path in cookbook_paths:
path = os.path.join(cookbook_path, cookbook_name)
if os.path.exists(path):
return path
raise IOError('Can\'t find cookbook with name "{0}"'.fo... | [
"def",
"get_cookbook_path",
"(",
"cookbook_name",
")",
":",
"for",
"cookbook_path",
"in",
"cookbook_paths",
":",
"path",
"=",
"os",
".",
"path",
".",
"join",
"(",
"cookbook_path",
",",
"cookbook_name",
")",
"if",
"os",
".",
"path",
".",
"exists",
"(",
"pat... | Returns path to the cookbook for the given cookbook name | [
"Returns",
"path",
"to",
"the",
"cookbook",
"for",
"the",
"given",
"cookbook",
"name"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L502-L508 |
tobami/littlechef | littlechef/lib.py | global_confirm | def global_confirm(question, default=True):
"""Shows a confirmation that applies to all hosts
by temporarily disabling parallel execution in Fabric
"""
if env.abort_on_prompts:
return True
original_parallel = env.parallel
env.parallel = False
result = confirm(question, default)
e... | python | def global_confirm(question, default=True):
"""Shows a confirmation that applies to all hosts
by temporarily disabling parallel execution in Fabric
"""
if env.abort_on_prompts:
return True
original_parallel = env.parallel
env.parallel = False
result = confirm(question, default)
e... | [
"def",
"global_confirm",
"(",
"question",
",",
"default",
"=",
"True",
")",
":",
"if",
"env",
".",
"abort_on_prompts",
":",
"return",
"True",
"original_parallel",
"=",
"env",
".",
"parallel",
"env",
".",
"parallel",
"=",
"False",
"result",
"=",
"confirm",
... | Shows a confirmation that applies to all hosts
by temporarily disabling parallel execution in Fabric | [
"Shows",
"a",
"confirmation",
"that",
"applies",
"to",
"all",
"hosts",
"by",
"temporarily",
"disabling",
"parallel",
"execution",
"in",
"Fabric"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L511-L521 |
tobami/littlechef | littlechef/lib.py | _pprint | def _pprint(dic):
"""Prints a dictionary with one indentation level"""
for key, value in dic.items():
print(" {0}: {1}".format(key, value)) | python | def _pprint(dic):
"""Prints a dictionary with one indentation level"""
for key, value in dic.items():
print(" {0}: {1}".format(key, value)) | [
"def",
"_pprint",
"(",
"dic",
")",
":",
"for",
"key",
",",
"value",
"in",
"dic",
".",
"items",
"(",
")",
":",
"print",
"(",
"\" {0}: {1}\"",
".",
"format",
"(",
"key",
",",
"value",
")",
")"
] | Prints a dictionary with one indentation level | [
"Prints",
"a",
"dictionary",
"with",
"one",
"indentation",
"level"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L524-L527 |
tobami/littlechef | littlechef/lib.py | get_margin | def get_margin(length):
"""Add enough tabs to align in two columns"""
if length > 23:
margin_left = "\t"
chars = 1
elif length > 15:
margin_left = "\t\t"
chars = 2
elif length > 7:
margin_left = "\t\t\t"
chars = 3
else:
margin_left = "\t\t\t\t"... | python | def get_margin(length):
"""Add enough tabs to align in two columns"""
if length > 23:
margin_left = "\t"
chars = 1
elif length > 15:
margin_left = "\t\t"
chars = 2
elif length > 7:
margin_left = "\t\t\t"
chars = 3
else:
margin_left = "\t\t\t\t"... | [
"def",
"get_margin",
"(",
"length",
")",
":",
"if",
"length",
">",
"23",
":",
"margin_left",
"=",
"\"\\t\"",
"chars",
"=",
"1",
"elif",
"length",
">",
"15",
":",
"margin_left",
"=",
"\"\\t\\t\"",
"chars",
"=",
"2",
"elif",
"length",
">",
"7",
":",
"m... | Add enough tabs to align in two columns | [
"Add",
"enough",
"tabs",
"to",
"align",
"in",
"two",
"columns"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/lib.py#L535-L549 |
tobami/littlechef | littlechef/solo.py | install | def install(version):
"""Install Chef using the omnibus installer"""
url = "https://www.chef.io/chef/install.sh"
with hide('stdout', 'running'):
local("""python -c "import urllib; print urllib.urlopen('{0}').read()"'
' > /tmp/install.sh""".format(url))
put('/tmp/install.sh', '/... | python | def install(version):
"""Install Chef using the omnibus installer"""
url = "https://www.chef.io/chef/install.sh"
with hide('stdout', 'running'):
local("""python -c "import urllib; print urllib.urlopen('{0}').read()"'
' > /tmp/install.sh""".format(url))
put('/tmp/install.sh', '/... | [
"def",
"install",
"(",
"version",
")",
":",
"url",
"=",
"\"https://www.chef.io/chef/install.sh\"",
"with",
"hide",
"(",
"'stdout'",
",",
"'running'",
")",
":",
"local",
"(",
"\"\"\"python -c \"import urllib; print urllib.urlopen('{0}').read()\"'\n ' > /tmp/install.... | Install Chef using the omnibus installer | [
"Install",
"Chef",
"using",
"the",
"omnibus",
"installer"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/solo.py#L29-L39 |
tobami/littlechef | littlechef/solo.py | configure | def configure(current_node=None):
"""Deploy chef-solo specific files"""
current_node = current_node or {}
# Ensure that the /tmp/chef-solo/cache directory exist
cache_dir = "{0}/cache".format(env.node_work_path)
# First remote call, could go wrong
try:
cache_exists = exists(cache_dir)
... | python | def configure(current_node=None):
"""Deploy chef-solo specific files"""
current_node = current_node or {}
# Ensure that the /tmp/chef-solo/cache directory exist
cache_dir = "{0}/cache".format(env.node_work_path)
# First remote call, could go wrong
try:
cache_exists = exists(cache_dir)
... | [
"def",
"configure",
"(",
"current_node",
"=",
"None",
")",
":",
"current_node",
"=",
"current_node",
"or",
"{",
"}",
"# Ensure that the /tmp/chef-solo/cache directory exist",
"cache_dir",
"=",
"\"{0}/cache\"",
".",
"format",
"(",
"env",
".",
"node_work_path",
")",
"... | Deploy chef-solo specific files | [
"Deploy",
"chef",
"-",
"solo",
"specific",
"files"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/solo.py#L42-L99 |
tobami/littlechef | plugins/save_ip.py | parse_ip | def parse_ip(text):
"""Extract an IPv4 IP from a text string
Uses an IP Address Regex: http://www.regular-expressions.info/examples.html
"""
ip_matches = re.findall(r'\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b', text)
ip = ip_matches[0] if ip_matches else None
return ip | python | def parse_ip(text):
"""Extract an IPv4 IP from a text string
Uses an IP Address Regex: http://www.regular-expressions.info/examples.html
"""
ip_matches = re.findall(r'\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b', text)
ip = ip_matches[0] if ip_matches else None
return ip | [
"def",
"parse_ip",
"(",
"text",
")",
":",
"ip_matches",
"=",
"re",
".",
"findall",
"(",
"r'\\b\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\.\\d{1,3}\\b'",
",",
"text",
")",
"ip",
"=",
"ip_matches",
"[",
"0",
"]",
"if",
"ip_matches",
"else",
"None",
"return",
"ip"
] | Extract an IPv4 IP from a text string
Uses an IP Address Regex: http://www.regular-expressions.info/examples.html | [
"Extract",
"an",
"IPv4",
"IP",
"from",
"a",
"text",
"string",
"Uses",
"an",
"IP",
"Address",
"Regex",
":",
"http",
":",
"//",
"www",
".",
"regular",
"-",
"expressions",
".",
"info",
"/",
"examples",
".",
"html"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/plugins/save_ip.py#L11-L18 |
tobami/littlechef | plugins/save_xen_info.py | execute | def execute(node):
"""Uses ohai to get virtualization information which is then saved to then
node file
"""
with hide('everything'):
virt = json.loads(sudo('ohai virtualization'))
if not len(virt) or virt[0][1] != "host":
# It may work for virtualization solutions other than Xen
... | python | def execute(node):
"""Uses ohai to get virtualization information which is then saved to then
node file
"""
with hide('everything'):
virt = json.loads(sudo('ohai virtualization'))
if not len(virt) or virt[0][1] != "host":
# It may work for virtualization solutions other than Xen
... | [
"def",
"execute",
"(",
"node",
")",
":",
"with",
"hide",
"(",
"'everything'",
")",
":",
"virt",
"=",
"json",
".",
"loads",
"(",
"sudo",
"(",
"'ohai virtualization'",
")",
")",
"if",
"not",
"len",
"(",
"virt",
")",
"or",
"virt",
"[",
"0",
"]",
"[",
... | Uses ohai to get virtualization information which is then saved to then
node file | [
"Uses",
"ohai",
"to",
"get",
"virtualization",
"information",
"which",
"is",
"then",
"saved",
"to",
"then",
"node",
"file"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/plugins/save_xen_info.py#L11-L40 |
tobami/littlechef | littlechef/runner.py | new_kitchen | def new_kitchen():
"""Create LittleChef directory structure (Kitchen)"""
def _mkdir(d, content=""):
if not os.path.exists(d):
os.mkdir(d)
# Add a README so that it can be added to version control
readme_path = os.path.join(d, 'README')
if not os.path.exist... | python | def new_kitchen():
"""Create LittleChef directory structure (Kitchen)"""
def _mkdir(d, content=""):
if not os.path.exists(d):
os.mkdir(d)
# Add a README so that it can be added to version control
readme_path = os.path.join(d, 'README')
if not os.path.exist... | [
"def",
"new_kitchen",
"(",
")",
":",
"def",
"_mkdir",
"(",
"d",
",",
"content",
"=",
"\"\"",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"d",
")",
":",
"os",
".",
"mkdir",
"(",
"d",
")",
"# Add a README so that it can be added to vers... | Create LittleChef directory structure (Kitchen) | [
"Create",
"LittleChef",
"directory",
"structure",
"(",
"Kitchen",
")"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L51-L89 |
tobami/littlechef | littlechef/runner.py | nodes_with_role | def nodes_with_role(rolename):
"""Configures a list of nodes that have the given role in their run list"""
nodes = [n['name'] for n in
lib.get_nodes_with_role(rolename, env.chef_environment)]
if not len(nodes):
print("No nodes found with role '{0}'".format(rolename))
sys.exit(0)... | python | def nodes_with_role(rolename):
"""Configures a list of nodes that have the given role in their run list"""
nodes = [n['name'] for n in
lib.get_nodes_with_role(rolename, env.chef_environment)]
if not len(nodes):
print("No nodes found with role '{0}'".format(rolename))
sys.exit(0)... | [
"def",
"nodes_with_role",
"(",
"rolename",
")",
":",
"nodes",
"=",
"[",
"n",
"[",
"'name'",
"]",
"for",
"n",
"in",
"lib",
".",
"get_nodes_with_role",
"(",
"rolename",
",",
"env",
".",
"chef_environment",
")",
"]",
"if",
"not",
"len",
"(",
"nodes",
")",... | Configures a list of nodes that have the given role in their run list | [
"Configures",
"a",
"list",
"of",
"nodes",
"that",
"have",
"the",
"given",
"role",
"in",
"their",
"run",
"list"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L92-L99 |
tobami/littlechef | littlechef/runner.py | nodes_with_recipe | def nodes_with_recipe(recipename):
"""Configures a list of nodes that have the given recipe in their run list
"""
nodes = [n['name'] for n in
lib.get_nodes_with_recipe(recipename, env.chef_environment)]
if not len(nodes):
print("No nodes found with recipe '{0}'".format(recipename))
... | python | def nodes_with_recipe(recipename):
"""Configures a list of nodes that have the given recipe in their run list
"""
nodes = [n['name'] for n in
lib.get_nodes_with_recipe(recipename, env.chef_environment)]
if not len(nodes):
print("No nodes found with recipe '{0}'".format(recipename))
... | [
"def",
"nodes_with_recipe",
"(",
"recipename",
")",
":",
"nodes",
"=",
"[",
"n",
"[",
"'name'",
"]",
"for",
"n",
"in",
"lib",
".",
"get_nodes_with_recipe",
"(",
"recipename",
",",
"env",
".",
"chef_environment",
")",
"]",
"if",
"not",
"len",
"(",
"nodes"... | Configures a list of nodes that have the given recipe in their run list | [
"Configures",
"a",
"list",
"of",
"nodes",
"that",
"have",
"the",
"given",
"recipe",
"in",
"their",
"run",
"list"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L102-L110 |
tobami/littlechef | littlechef/runner.py | nodes_with_tag | def nodes_with_tag(tag):
"""Sets a list of nodes that have the given tag assigned and calls node()"""
nodes = lib.get_nodes_with_tag(tag, env.chef_environment,
littlechef.include_guests)
nodes = [n['name'] for n in nodes]
if not len(nodes):
print("No nodes foun... | python | def nodes_with_tag(tag):
"""Sets a list of nodes that have the given tag assigned and calls node()"""
nodes = lib.get_nodes_with_tag(tag, env.chef_environment,
littlechef.include_guests)
nodes = [n['name'] for n in nodes]
if not len(nodes):
print("No nodes foun... | [
"def",
"nodes_with_tag",
"(",
"tag",
")",
":",
"nodes",
"=",
"lib",
".",
"get_nodes_with_tag",
"(",
"tag",
",",
"env",
".",
"chef_environment",
",",
"littlechef",
".",
"include_guests",
")",
"nodes",
"=",
"[",
"n",
"[",
"'name'",
"]",
"for",
"n",
"in",
... | Sets a list of nodes that have the given tag assigned and calls node() | [
"Sets",
"a",
"list",
"of",
"nodes",
"that",
"have",
"the",
"given",
"tag",
"assigned",
"and",
"calls",
"node",
"()"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L113-L121 |
tobami/littlechef | littlechef/runner.py | node | def node(*nodes):
"""Selects and configures a list of nodes. 'all' configures all nodes"""
chef.build_node_data_bag()
if not len(nodes) or nodes[0] == '':
abort('No node was given')
elif nodes[0] == 'all':
# Fetch all nodes and add them to env.hosts
for node in lib.get_nodes(env.... | python | def node(*nodes):
"""Selects and configures a list of nodes. 'all' configures all nodes"""
chef.build_node_data_bag()
if not len(nodes) or nodes[0] == '':
abort('No node was given')
elif nodes[0] == 'all':
# Fetch all nodes and add them to env.hosts
for node in lib.get_nodes(env.... | [
"def",
"node",
"(",
"*",
"nodes",
")",
":",
"chef",
".",
"build_node_data_bag",
"(",
")",
"if",
"not",
"len",
"(",
"nodes",
")",
"or",
"nodes",
"[",
"0",
"]",
"==",
"''",
":",
"abort",
"(",
"'No node was given'",
")",
"elif",
"nodes",
"[",
"0",
"]"... | Selects and configures a list of nodes. 'all' configures all nodes | [
"Selects",
"and",
"configures",
"a",
"list",
"of",
"nodes",
".",
"all",
"configures",
"all",
"nodes"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L124-L158 |
tobami/littlechef | littlechef/runner.py | _node_runner | def _node_runner():
"""This is only used by node so that we can execute in parallel"""
env.host_string = lib.get_env_host_string()
node = lib.get_node(env.host_string)
_configure_fabric_for_platform(node.get("platform"))
if __testing__:
print "TEST: would now configure {0}".format(env.host... | python | def _node_runner():
"""This is only used by node so that we can execute in parallel"""
env.host_string = lib.get_env_host_string()
node = lib.get_node(env.host_string)
_configure_fabric_for_platform(node.get("platform"))
if __testing__:
print "TEST: would now configure {0}".format(env.host... | [
"def",
"_node_runner",
"(",
")",
":",
"env",
".",
"host_string",
"=",
"lib",
".",
"get_env_host_string",
"(",
")",
"node",
"=",
"lib",
".",
"get_node",
"(",
"env",
".",
"host_string",
")",
"_configure_fabric_for_platform",
"(",
"node",
".",
"get",
"(",
"\"... | This is only used by node so that we can execute in parallel | [
"This",
"is",
"only",
"used",
"by",
"node",
"so",
"that",
"we",
"can",
"execute",
"in",
"parallel"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L167-L180 |
tobami/littlechef | littlechef/runner.py | deploy_chef | def deploy_chef(ask="yes", version="11"):
"""Install chef-solo on a node"""
env.host_string = lib.get_env_host_string()
if ask == "no" or littlechef.noninteractive:
print("Deploying Chef using omnibus installer version: ...".format(version))
else:
message = ('\nAre you sure you want to i... | python | def deploy_chef(ask="yes", version="11"):
"""Install chef-solo on a node"""
env.host_string = lib.get_env_host_string()
if ask == "no" or littlechef.noninteractive:
print("Deploying Chef using omnibus installer version: ...".format(version))
else:
message = ('\nAre you sure you want to i... | [
"def",
"deploy_chef",
"(",
"ask",
"=",
"\"yes\"",
",",
"version",
"=",
"\"11\"",
")",
":",
"env",
".",
"host_string",
"=",
"lib",
".",
"get_env_host_string",
"(",
")",
"if",
"ask",
"==",
"\"no\"",
"or",
"littlechef",
".",
"noninteractive",
":",
"print",
... | Install chef-solo on a node | [
"Install",
"chef",
"-",
"solo",
"on",
"a",
"node"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L183-L215 |
tobami/littlechef | littlechef/runner.py | recipe | def recipe(recipe):
"""Apply the given recipe to a node
Sets the run_list to the given recipe
If no nodes/hostname.json file exists, it creates one
"""
env.host_string = lib.get_env_host_string()
lib.print_header(
"Applying recipe '{0}' on node {1}".format(recipe, env.host_string))
... | python | def recipe(recipe):
"""Apply the given recipe to a node
Sets the run_list to the given recipe
If no nodes/hostname.json file exists, it creates one
"""
env.host_string = lib.get_env_host_string()
lib.print_header(
"Applying recipe '{0}' on node {1}".format(recipe, env.host_string))
... | [
"def",
"recipe",
"(",
"recipe",
")",
":",
"env",
".",
"host_string",
"=",
"lib",
".",
"get_env_host_string",
"(",
")",
"lib",
".",
"print_header",
"(",
"\"Applying recipe '{0}' on node {1}\"",
".",
"format",
"(",
"recipe",
",",
"env",
".",
"host_string",
")",
... | Apply the given recipe to a node
Sets the run_list to the given recipe
If no nodes/hostname.json file exists, it creates one | [
"Apply",
"the",
"given",
"recipe",
"to",
"a",
"node",
"Sets",
"the",
"run_list",
"to",
"the",
"given",
"recipe",
"If",
"no",
"nodes",
"/",
"hostname",
".",
"json",
"file",
"exists",
"it",
"creates",
"one"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L218-L234 |
tobami/littlechef | littlechef/runner.py | ssh | def ssh(name):
"""Executes the given command"""
env.host_string = lib.get_env_host_string()
print("\nExecuting the command '{0}' on node {1}...".format(
name, env.host_string))
# Execute remotely using either the sudo or the run fabric functions
with settings(hide("warnings"), warn_only=Tr... | python | def ssh(name):
"""Executes the given command"""
env.host_string = lib.get_env_host_string()
print("\nExecuting the command '{0}' on node {1}...".format(
name, env.host_string))
# Execute remotely using either the sudo or the run fabric functions
with settings(hide("warnings"), warn_only=Tr... | [
"def",
"ssh",
"(",
"name",
")",
":",
"env",
".",
"host_string",
"=",
"lib",
".",
"get_env_host_string",
"(",
")",
"print",
"(",
"\"\\nExecuting the command '{0}' on node {1}...\"",
".",
"format",
"(",
"name",
",",
"env",
".",
"host_string",
")",
")",
"# Execut... | Executes the given command | [
"Executes",
"the",
"given",
"command"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L256-L266 |
tobami/littlechef | littlechef/runner.py | plugin | def plugin(name):
"""Executes the selected plugin
Plugins are expected to be found in the kitchen's 'plugins' directory
"""
env.host_string = lib.get_env_host_string()
plug = lib.import_plugin(name)
lib.print_header("Executing plugin '{0}' on "
"{1}".format(name, env.host_s... | python | def plugin(name):
"""Executes the selected plugin
Plugins are expected to be found in the kitchen's 'plugins' directory
"""
env.host_string = lib.get_env_host_string()
plug = lib.import_plugin(name)
lib.print_header("Executing plugin '{0}' on "
"{1}".format(name, env.host_s... | [
"def",
"plugin",
"(",
"name",
")",
":",
"env",
".",
"host_string",
"=",
"lib",
".",
"get_env_host_string",
"(",
")",
"plug",
"=",
"lib",
".",
"import_plugin",
"(",
"name",
")",
"lib",
".",
"print_header",
"(",
"\"Executing plugin '{0}' on \"",
"\"{1}\"",
"."... | Executes the selected plugin
Plugins are expected to be found in the kitchen's 'plugins' directory | [
"Executes",
"the",
"selected",
"plugin",
"Plugins",
"are",
"expected",
"to",
"be",
"found",
"in",
"the",
"kitchen",
"s",
"plugins",
"directory"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L269-L282 |
tobami/littlechef | littlechef/runner.py | list_envs | def list_envs():
"""List all environments"""
for env in lib.get_environments():
margin_left = lib.get_margin(len(env['name']))
print("{0}{1}{2}".format(
env['name'], margin_left,
env.get('description', '(no description)'))) | python | def list_envs():
"""List all environments"""
for env in lib.get_environments():
margin_left = lib.get_margin(len(env['name']))
print("{0}{1}{2}".format(
env['name'], margin_left,
env.get('description', '(no description)'))) | [
"def",
"list_envs",
"(",
")",
":",
"for",
"env",
"in",
"lib",
".",
"get_environments",
"(",
")",
":",
"margin_left",
"=",
"lib",
".",
"get_margin",
"(",
"len",
"(",
"env",
"[",
"'name'",
"]",
")",
")",
"print",
"(",
"\"{0}{1}{2}\"",
".",
"format",
"(... | List all environments | [
"List",
"all",
"environments"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L310-L316 |
tobami/littlechef | littlechef/runner.py | list_nodes_with_tag | def list_nodes_with_tag(tag):
"""Show all nodes which have assigned a given tag"""
lib.print_nodes(lib.get_nodes_with_tag(tag, env.chef_environment,
littlechef.include_guests)) | python | def list_nodes_with_tag(tag):
"""Show all nodes which have assigned a given tag"""
lib.print_nodes(lib.get_nodes_with_tag(tag, env.chef_environment,
littlechef.include_guests)) | [
"def",
"list_nodes_with_tag",
"(",
"tag",
")",
":",
"lib",
".",
"print_nodes",
"(",
"lib",
".",
"get_nodes_with_tag",
"(",
"tag",
",",
"env",
".",
"chef_environment",
",",
"littlechef",
".",
"include_guests",
")",
")"
] | Show all nodes which have assigned a given tag | [
"Show",
"all",
"nodes",
"which",
"have",
"assigned",
"a",
"given",
"tag"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L320-L323 |
tobami/littlechef | littlechef/runner.py | list_recipes | def list_recipes():
"""Show a list of all available recipes"""
for recipe in lib.get_recipes():
margin_left = lib.get_margin(len(recipe['name']))
print("{0}{1}{2}".format(
recipe['name'], margin_left, recipe['description'])) | python | def list_recipes():
"""Show a list of all available recipes"""
for recipe in lib.get_recipes():
margin_left = lib.get_margin(len(recipe['name']))
print("{0}{1}{2}".format(
recipe['name'], margin_left, recipe['description'])) | [
"def",
"list_recipes",
"(",
")",
":",
"for",
"recipe",
"in",
"lib",
".",
"get_recipes",
"(",
")",
":",
"margin_left",
"=",
"lib",
".",
"get_margin",
"(",
"len",
"(",
"recipe",
"[",
"'name'",
"]",
")",
")",
"print",
"(",
"\"{0}{1}{2}\"",
".",
"format",
... | Show a list of all available recipes | [
"Show",
"a",
"list",
"of",
"all",
"available",
"recipes"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L327-L332 |
tobami/littlechef | littlechef/runner.py | list_roles | def list_roles():
"""Show a list of all available roles"""
for role in lib.get_roles():
margin_left = lib.get_margin(len(role['fullname']))
print("{0}{1}{2}".format(
role['fullname'], margin_left,
role.get('description', '(no description)'))) | python | def list_roles():
"""Show a list of all available roles"""
for role in lib.get_roles():
margin_left = lib.get_margin(len(role['fullname']))
print("{0}{1}{2}".format(
role['fullname'], margin_left,
role.get('description', '(no description)'))) | [
"def",
"list_roles",
"(",
")",
":",
"for",
"role",
"in",
"lib",
".",
"get_roles",
"(",
")",
":",
"margin_left",
"=",
"lib",
".",
"get_margin",
"(",
"len",
"(",
"role",
"[",
"'fullname'",
"]",
")",
")",
"print",
"(",
"\"{0}{1}{2}\"",
".",
"format",
"(... | Show a list of all available roles | [
"Show",
"a",
"list",
"of",
"all",
"available",
"roles"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L343-L349 |
tobami/littlechef | littlechef/runner.py | _check_appliances | def _check_appliances():
"""Looks around and return True or False based on whether we are in a
kitchen
"""
filenames = os.listdir(os.getcwd())
missing = []
for dirname in ['nodes', 'environments', 'roles', 'cookbooks', 'data_bags']:
if (dirname not in filenames) or (not os.path.isdir(dir... | python | def _check_appliances():
"""Looks around and return True or False based on whether we are in a
kitchen
"""
filenames = os.listdir(os.getcwd())
missing = []
for dirname in ['nodes', 'environments', 'roles', 'cookbooks', 'data_bags']:
if (dirname not in filenames) or (not os.path.isdir(dir... | [
"def",
"_check_appliances",
"(",
")",
":",
"filenames",
"=",
"os",
".",
"listdir",
"(",
"os",
".",
"getcwd",
"(",
")",
")",
"missing",
"=",
"[",
"]",
"for",
"dirname",
"in",
"[",
"'nodes'",
",",
"'environments'",
",",
"'roles'",
",",
"'cookbooks'",
","... | Looks around and return True or False based on whether we are in a
kitchen | [
"Looks",
"around",
"and",
"return",
"True",
"or",
"False",
"based",
"on",
"whether",
"we",
"are",
"in",
"a",
"kitchen"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L365-L374 |
tobami/littlechef | littlechef/runner.py | _readconfig | def _readconfig():
"""Configures environment variables"""
config = ConfigParser.SafeConfigParser()
try:
found = config.read(littlechef.CONFIGFILE)
except ConfigParser.ParsingError as e:
abort(str(e))
if not len(found):
try:
found = config.read(['config.cfg', 'auth... | python | def _readconfig():
"""Configures environment variables"""
config = ConfigParser.SafeConfigParser()
try:
found = config.read(littlechef.CONFIGFILE)
except ConfigParser.ParsingError as e:
abort(str(e))
if not len(found):
try:
found = config.read(['config.cfg', 'auth... | [
"def",
"_readconfig",
"(",
")",
":",
"config",
"=",
"ConfigParser",
".",
"SafeConfigParser",
"(",
")",
"try",
":",
"found",
"=",
"config",
".",
"read",
"(",
"littlechef",
".",
"CONFIGFILE",
")",
"except",
"ConfigParser",
".",
"ParsingError",
"as",
"e",
":"... | Configures environment variables | [
"Configures",
"environment",
"variables"
] | train | https://github.com/tobami/littlechef/blob/aab8c94081b38100a69cc100bc4278ae7419c58e/littlechef/runner.py#L377-L552 |
jbittel/django-mama-cas | mama_cas/views.py | LoginView.get | def get(self, request, *args, **kwargs):
"""
(2.1) As a credential requestor, /login accepts three optional
parameters:
1. ``service``: the identifier of the application the client is
accessing. We assume this identifier to be a URL.
2. ``renew``: requires a client to... | python | def get(self, request, *args, **kwargs):
"""
(2.1) As a credential requestor, /login accepts three optional
parameters:
1. ``service``: the identifier of the application the client is
accessing. We assume this identifier to be a URL.
2. ``renew``: requires a client to... | [
"def",
"get",
"(",
"self",
",",
"request",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"service",
"=",
"request",
".",
"GET",
".",
"get",
"(",
"'service'",
")",
"renew",
"=",
"to_bool",
"(",
"request",
".",
"GET",
".",
"get",
"(",
"'rene... | (2.1) As a credential requestor, /login accepts three optional
parameters:
1. ``service``: the identifier of the application the client is
accessing. We assume this identifier to be a URL.
2. ``renew``: requires a client to present credentials
regardless of any existing si... | [
"(",
"2",
".",
"1",
")",
"As",
"a",
"credential",
"requestor",
"/",
"login",
"accepts",
"three",
"optional",
"parameters",
":"
] | train | https://github.com/jbittel/django-mama-cas/blob/03935d97442b46d8127ab9e1cd8deb96953fe156/mama_cas/views.py#L68-L108 |
jbittel/django-mama-cas | mama_cas/views.py | LoginView.form_valid | def form_valid(self, form):
"""
(2.2) As a credential acceptor, /login requires two parameters:
1. ``username``: the username provided by the client
2. ``password``: the password provided by the client
If authentication is successful, the single sign-on session is
creat... | python | def form_valid(self, form):
"""
(2.2) As a credential acceptor, /login requires two parameters:
1. ``username``: the username provided by the client
2. ``password``: the password provided by the client
If authentication is successful, the single sign-on session is
creat... | [
"def",
"form_valid",
"(",
"self",
",",
"form",
")",
":",
"login",
"(",
"self",
".",
"request",
",",
"form",
".",
"user",
")",
"logger",
".",
"info",
"(",
"\"Single sign-on session started for %s\"",
"%",
"form",
".",
"user",
")",
"if",
"form",
".",
"clea... | (2.2) As a credential acceptor, /login requires two parameters:
1. ``username``: the username provided by the client
2. ``password``: the password provided by the client
If authentication is successful, the single sign-on session is
created. If a service is provided, a ``ServiceTicket`... | [
"(",
"2",
".",
"2",
")",
"As",
"a",
"credential",
"acceptor",
"/",
"login",
"requires",
"two",
"parameters",
":"
] | train | https://github.com/jbittel/django-mama-cas/blob/03935d97442b46d8127ab9e1cd8deb96953fe156/mama_cas/views.py#L117-L150 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.