_id stringlengths 2 7 | title stringlengths 1 88 | partition stringclasses 3
values | text stringlengths 75 19.8k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
q100 | Step.invoke_step | train | def invoke_step(self, context):
"""Invoke 'run_step' in the dynamically loaded step module.
Don't invoke this from outside the Step class. Use
pypyr.dsl.Step.run_step instead.
invoke_step just does the bare module step invocation, it does not
evaluate any of the decorator logic ... | python | {
"resource": ""
} |
q101 | Step.run_conditional_decorators | train | def run_conditional_decorators(self, context):
"""Evaluate the step decorators to decide whether to run step or not.
Use pypyr.dsl.Step.run_step if you intend on executing the step the
same way pypyr does.
Args:
context: (pypyr.context.Context) The pypyr context. This arg w... | python | {
"resource": ""
} |
q102 | Step.run_foreach_or_conditional | train | def run_foreach_or_conditional(self, context):
"""Run the foreach sequence or the conditional evaluation.
Args:
context: (pypyr.context.Context) The pypyr context. This arg will
mutate.
"""
logger.debug("starting")
# friendly reminder [] list obj... | python | {
"resource": ""
} |
q103 | Step.run_step | train | def run_step(self, context):
"""Run a single pipeline step.
Args:
context: (pypyr.context.Context) The pypyr context. This arg will
mutate.
"""
logger.debug("starting")
# the in params should be added to context before step execution.
sel... | python | {
"resource": ""
} |
q104 | Step.set_step_input_context | train | def set_step_input_context(self, context):
"""Append step's 'in' parameters to context, if they exist.
Append the[in] dictionary to the context. This will overwrite
existing values if the same keys are already in there. I.e if
in_parameters has {'eggs': 'boiled'} and key 'eggs' already
... | python | {
"resource": ""
} |
q105 | RetryDecorator.exec_iteration | train | def exec_iteration(self, counter, context, step_method):
"""Run a single retry iteration.
This method abides by the signature invoked by poll.while_until_true,
which is to say (counter, *args, **kwargs). In a normal execution
chain, this method's args passed by self.retry_loop where con... | python | {
"resource": ""
} |
q106 | RetryDecorator.retry_loop | train | def retry_loop(self, context, step_method):
"""Run step inside a retry loop.
Args:
context: (pypyr.context.Context) The pypyr context. This arg will
mutate - after method execution will contain the new
updated context.
step_method: (meth... | python | {
"resource": ""
} |
q107 | WhileDecorator.exec_iteration | train | def exec_iteration(self, counter, context, step_method):
"""Run a single loop iteration.
This method abides by the signature invoked by poll.while_until_true,
which is to say (counter, *args, **kwargs). In a normal execution
chain, this method's args passed by self.while_loop where cont... | python | {
"resource": ""
} |
q108 | WhileDecorator.while_loop | train | def while_loop(self, context, step_method):
"""Run step inside a while loop.
Args:
context: (pypyr.context.Context) The pypyr context. This arg will
mutate - after method execution will contain the new
updated context.
step_method: (meth... | python | {
"resource": ""
} |
q109 | run_step | train | def run_step(context):
"""Load a yaml file into the pypyr context.
Yaml parsed from the file will be merged into the pypyr context. This will
overwrite existing values if the same keys are already in there.
I.e if file yaml has {'eggs' : 'boiled'} and context {'eggs': 'fried'}
already exists, retur... | python | {
"resource": ""
} |
q110 | run_step | train | def run_step(context):
"""pypyr step saves current utc datetime to context.
Args:
context: pypyr.context.Context. Mandatory.
The following context key is optional:
- nowUtcIn. str. Datetime formatting expression. For full list
of possible expressions, ... | python | {
"resource": ""
} |
q111 | run_step | train | def run_step(context):
"""Assert that something is True or equal to something else.
Args:
context: dictionary-like pypyr.context.Context. context is mandatory.
Uses the following context keys in context:
- assert
- this. mandatory. Any type. If assert['equals'] not s... | python | {
"resource": ""
} |
q112 | tar_archive | train | def tar_archive(context):
"""Archive specified path to a tar archive.
Args:
context: dictionary-like. context is mandatory.
context['tar']['archive'] must exist. It's a dictionary.
keys are the paths to archive.
values are the destination output paths.
Example:
... | python | {
"resource": ""
} |
q113 | tar_extract | train | def tar_extract(context):
"""Extract all members of tar archive to specified path.
Args:
context: dictionary-like. context is mandatory.
context['tar']['extract'] must exist. It's a dictionary.
keys are the path to the tar to extract.
values are the destination paths... | python | {
"resource": ""
} |
q114 | run_step | train | def run_step(context):
"""Run shell command without shell interpolation.
Context is a dictionary or dictionary-like.
Context must contain the following keys:
cmd: <<cmd string>> (command + args to execute.)
OR, as a dict
cmd:
run: str. mandatory. <<cmd string>> command + args to execu... | python | {
"resource": ""
} |
q115 | get_args | train | def get_args(get_item):
"""Parse env, key, default out of input dict.
Args:
get_item: dict. contains keys env/key/default
Returns:
(env, key, has_default, default) tuple, where
env: str. env var name.
key: str. save env value to this context key.
has_def... | python | {
"resource": ""
} |
q116 | run_step | train | def run_step(context):
"""Executes dynamic python code.
Context is a dictionary or dictionary-like.
Context must contain key 'pycode'
Will exec context['pycode'] as dynamically interpreted python statements.
context is mandatory. When you execute the pipeline, it should look
something like thi... | python | {
"resource": ""
} |
q117 | get_parser | train | def get_parser():
"""Return ArgumentParser for pypyr cli."""
parser = argparse.ArgumentParser(
allow_abbrev=True,
description='pypyr pipeline runner')
parser.add_argument('pipeline_name',
help='Name of pipeline to run. It should exist in the '
... | python | {
"resource": ""
} |
q118 | main | train | def main(args=None):
"""Entry point for pypyr cli.
The setup_py entry_point wraps this in sys.exit already so this effectively
becomes sys.exit(main()).
The __main__ entry point similarly wraps sys.exit().
"""
if args is None:
args = sys.argv[1:]
parsed_args = get_args(args)
t... | python | {
"resource": ""
} |
q119 | run_step | train | def run_step(context):
"""Remove specified keys from context.
Args:
Context is a dictionary or dictionary-like.
context['contextClear'] must exist. It's a dictionary.
Will iterate context['contextClear'] and remove those keys from
context.
For example, say input context is:... | python | {
"resource": ""
} |
q120 | run_step | train | def run_step(context):
"""Run command, program or executable.
Context is a dictionary or dictionary-like.
Context must contain the following keys:
cmd: <<cmd string>> (command + args to execute.)
OR, as a dict
cmd:
run: str. mandatory. <<cmd string>> command + args to execute.
... | python | {
"resource": ""
} |
q121 | run_step | train | def run_step(context):
"""Set hierarchy into context with substitutions if it doesn't exist yet.
context is a dictionary or dictionary-like.
context['defaults'] must exist. It's a dictionary.
Will iterate context['defaults'] and add these as new values where
their keys don't already exist. While i... | python | {
"resource": ""
} |
q122 | get_pipeline_steps | train | def get_pipeline_steps(pipeline, steps_group):
"""Get the steps attribute of module pipeline.
If there is no steps sequence on the pipeline, return None. Guess you
could theoretically want to run a pipeline with nothing in it.
"""
logger.debug("starting")
assert pipeline
assert steps_group
... | python | {
"resource": ""
} |
q123 | run_failure_step_group | train | def run_failure_step_group(pipeline, context):
"""Run the on_failure step group if it exists.
This function will swallow all errors, to prevent obfuscating the error
condition that got it here to begin with.
"""
logger.debug("starting")
try:
assert pipeline
# if no on_failure ex... | python | {
"resource": ""
} |
q124 | run_step_group | train | def run_step_group(pipeline_definition, step_group_name, context):
"""Get the specified step group from the pipeline and run its steps."""
logger.debug(f"starting {step_group_name}")
assert step_group_name
steps = get_pipeline_steps(pipeline=pipeline_definition,
steps_gro... | python | {
"resource": ""
} |
q125 | ensure_dir | train | def ensure_dir(path):
"""Create all parent directories of path if they don't exist.
Args:
path. Path-like object. Create parent dirs to this path.
Return:
None.
"""
os.makedirs(os.path.abspath(os.path.dirname(path)), exist_ok=True) | python | {
"resource": ""
} |
q126 | get_glob | train | def get_glob(path):
"""Process the input path, applying globbing and formatting.
Do note that this will returns files AND directories that match the glob.
No tilde expansion is done, but *, ?, and character ranges expressed with
[] will be correctly matched.
Escape all special characters ('?', '*... | python | {
"resource": ""
} |
q127 | is_same_file | train | def is_same_file(path1, path2):
"""Return True if path1 is the same file as path2.
The reason for this dance is that samefile throws if either file doesn't
exist.
Args:
path1: str or path-like.
path2: str or path-like.
Returns:
bool. True if the same file, False if not.
... | python | {
"resource": ""
} |
q128 | move_file | train | def move_file(src, dest):
"""Move source file to destination.
Overwrites dest.
Args:
src: str or path-like. source file
dest: str or path-like. destination file
Returns:
None.
Raises:
FileNotFoundError: out path parent doesn't exist.
OSError: if any IO ope... | python | {
"resource": ""
} |
q129 | move_temp_file | train | def move_temp_file(src, dest):
"""Move src to dest. Delete src if something goes wrong.
Overwrites dest.
Args:
src: str or path-like. source file
dest: str or path-like. destination file
Returns:
None.
Raises:
FileNotFoundError: out path parent doesn't exist.
... | python | {
"resource": ""
} |
q130 | FileRewriter.files_in_to_out | train | def files_in_to_out(self, in_path, out_path=None):
"""Write in files to out, calling the line_handler on each line.
Calls file_in_to_out under the hood to format the in_path payload. The
formatting processing is done by the self.formatter instance.
Args:
in_path: str, path-... | python | {
"resource": ""
} |
q131 | ObjectRewriter.in_to_out | train | def in_to_out(self, in_path, out_path=None):
"""Load file into object, formats, writes object to out.
If in_path and out_path point to the same thing it will in-place edit
and overwrite the in path. Even easier, if you do want to edit a file
in place, don't specify out_path, or set it t... | python | {
"resource": ""
} |
q132 | StreamRewriter.in_to_out | train | def in_to_out(self, in_path, out_path=None):
"""Write a single file in to out, running self.formatter on each line.
If in_path and out_path point to the same thing it will in-place edit
and overwrite the in path. Even easier, if you do want to edit a file
in place, don't specify out_pat... | python | {
"resource": ""
} |
q133 | JsonRepresenter.dump | train | def dump(self, file, payload):
"""Dump json oject to open file output.
Writes json with 2 spaces indentation.
Args:
file: Open file-like object. Must be open for writing.
payload: The Json object to write to file.
Returns:
None.
"""
... | python | {
"resource": ""
} |
q134 | run_step | train | def run_step(context):
"""Parse input file and replace a search string.
This also does string substitutions from context on the fileReplacePairs.
It does this before it search & replaces the in file.
Be careful of order. If fileReplacePairs is not an ordered collection,
replacements could evaluate... | python | {
"resource": ""
} |
q135 | set_logging_config | train | def set_logging_config(log_level, handlers):
"""Set python logging library config.
Run this ONCE at the start of your process. It formats the python logging
module's output.
Defaults logging level to INFO = 20)
"""
logging.basicConfig(
format='%(asctime)s %(levelname)s:%(name)s:%(funcNa... | python | {
"resource": ""
} |
q136 | set_root_logger | train | def set_root_logger(root_log_level, log_path=None):
"""Set the root logger 'pypyr'. Do this before you do anything else.
Run once and only once at initialization.
"""
handlers = []
console_handler = logging.StreamHandler()
handlers.append(console_handler)
if log_path:
file_handler ... | python | {
"resource": ""
} |
q137 | get_parsed_context | train | def get_parsed_context(pipeline, context_in_string):
"""Execute get_parsed_context handler if specified.
Dynamically load the module specified by the context_parser key in pipeline
dict and execute the get_parsed_context function on that module.
Args:
pipeline: dict. Pipeline object.
c... | python | {
"resource": ""
} |
q138 | main | train | def main(
pipeline_name,
pipeline_context_input,
working_dir,
log_level,
log_path,
):
"""Entry point for pypyr pipeline runner.
Call this once per pypyr run. Call me if you want to run a pypyr pipeline
from your own code. This function does some one-off 1st time initialization
befor... | python | {
"resource": ""
} |
q139 | prepare_context | train | def prepare_context(pipeline, context_in_string, context):
"""Prepare context for pipeline run.
Args:
pipeline: dict. Dictionary representing the pipeline.
context_in_string: string. Argument string used to initialize context.
context: pypyr.context.Context. Merge any new context genera... | python | {
"resource": ""
} |
q140 | load_and_run_pipeline | train | def load_and_run_pipeline(pipeline_name,
pipeline_context_input=None,
working_dir=None,
context=None,
parse_input=True,
loader=None):
"""Load and run the specified pypyr pipeline.
T... | python | {
"resource": ""
} |
q141 | run_pipeline | train | def run_pipeline(pipeline,
context,
pipeline_context_input=None,
parse_input=True):
"""Run the specified pypyr pipeline.
This function runs the actual pipeline. If you are running another
pipeline from within a pipeline, call this, not main(). Do call main... | python | {
"resource": ""
} |
q142 | run_step | train | def run_step(context):
"""Write payload out to yaml file.
Args:
context: pypyr.context.Context. Mandatory.
The following context keys expected:
- fileWriteYaml
- path. mandatory. path-like. Write output file to
here. Will create... | python | {
"resource": ""
} |
q143 | run_step | train | def run_step(context):
"""Print debug info to console.
context is a dictionary or dictionary-like.
If you use pypyr.steps.debug as a simple step (i.e you do NOT specify the
debug input context), it will just dump the entire context to stdout.
Configure the debug step with the following optional c... | python | {
"resource": ""
} |
q144 | get_error_name | train | def get_error_name(error):
"""Return canonical error name as string.
For builtin errors like ValueError or Exception, will return the bare
name, like ValueError or Exception.
For all other exceptions, will return modulename.errorname, such as
arbpackage.mod.myerror
Args:
error: Except... | python | {
"resource": ""
} |
q145 | get_module | train | def get_module(module_abs_import):
"""Use importlib to get the module dynamically.
Get instance of the module specified by the module_abs_import.
This means that module_abs_import must be resolvable from this package.
Args:
module_abs_import: string. Absolute name of module to import.
Rai... | python | {
"resource": ""
} |
q146 | set_working_directory | train | def set_working_directory(working_directory):
"""Add working_directory to sys.paths.
This allows dynamic loading of arbitrary python modules in cwd.
Args:
working_directory: string. path to add to sys.paths
"""
logger.debug("starting")
logger.debug(f"adding {working_directory} to sys... | python | {
"resource": ""
} |
q147 | Context.assert_child_key_has_value | train | def assert_child_key_has_value(self, parent, child, caller):
"""Assert that context contains key that has child which has a value.
Args:
parent: parent key
child: validate this sub-key of parent exists AND isn't None.
caller: string. calling function name - this used... | python | {
"resource": ""
} |
q148 | Context.assert_key_has_value | train | def assert_key_has_value(self, key, caller):
"""Assert that context contains key which also has a value.
Args:
key: validate this key exists in context AND has a value that isn't
None.
caller: string. calling function name - this used to construct
... | python | {
"resource": ""
} |
q149 | Context.assert_keys_exist | train | def assert_keys_exist(self, caller, *keys):
"""Assert that context contains keys.
Args:
keys: validates that these keys exists in context
caller: string. calling function or module name - this used to
construct error messages
Raises:
KeyN... | python | {
"resource": ""
} |
q150 | Context.assert_keys_have_values | train | def assert_keys_have_values(self, caller, *keys):
"""Check that keys list are all in context and all have values.
Args:
*keys: Will check each of these keys in context
caller: string. Calling function name - just used for informational
messages
Raise... | python | {
"resource": ""
} |
q151 | Context.get_formatted_iterable | train | def get_formatted_iterable(self, obj, memo=None):
"""Recursively loop through obj, formatting as it goes.
Interpolates strings from the context dictionary.
This is not a full on deepcopy, and it's on purpose not a full on
deepcopy. It will handle dict, list, set, tuple for iteration, w... | python | {
"resource": ""
} |
q152 | Context.get_formatted_string | train | def get_formatted_string(self, input_string):
"""Return formatted value for input_string.
get_formatted gets a context[key] value.
get_formatted_string is for any arbitrary string that is not in the
context.
Only valid if input_string is a type string.
Return a string i... | python | {
"resource": ""
} |
q153 | Context.get_formatted_as_type | train | def get_formatted_as_type(self, value, default=None, out_type=str):
"""Return formatted value for input value, returns as out_type.
Caveat emptor: if out_type is bool and value a string,
return will be True if str is 'True'. It will be False for all other
cases.
Args:
... | python | {
"resource": ""
} |
q154 | Context.get_processed_string | train | def get_processed_string(self, input_string):
"""Run token substitution on input_string against context.
You probably don't want to call this directly yourself - rather use
get_formatted, get_formatted_iterable, or get_formatted_string because
these contain more friendly error handling ... | python | {
"resource": ""
} |
q155 | Context.keys_of_type_exist | train | def keys_of_type_exist(self, *keys):
"""Check if keys exist in context and if types are as expected.
Args:
*keys: *args for keys to check in context.
Each arg is a tuple (str, type)
Returns:
Tuple of namedtuple ContextItemInfo, same order as *keys.
... | python | {
"resource": ""
} |
q156 | Context.merge | train | def merge(self, add_me):
"""Merge add_me into context and applies interpolation.
Bottom-up merge where add_me merges into context. Applies string
interpolation where the type is a string. Where a key exists in
context already, add_me's value will overwrite what's in context
alre... | python | {
"resource": ""
} |
q157 | Context.set_defaults | train | def set_defaults(self, defaults):
"""Set defaults in context if keys do not exist already.
Adds the input dict (defaults) into the context, only where keys in
defaults do not already exist in context. Supports nested hierarchies.
Example:
Given a context like this:
... | python | {
"resource": ""
} |
q158 | FileInRewriterStep.run_step | train | def run_step(self, rewriter):
"""Do the file in to out rewrite.
Doesn't do anything more crazy than call files_in_to_out on the
rewriter.
Args:
rewriter: pypyr.filesystem.FileRewriter instance.
"""
assert rewriter, ("FileRewriter instance required to run "
... | python | {
"resource": ""
} |
q159 | ObjectRewriterStep.run_step | train | def run_step(self, representer):
"""Do the object in-out rewrite.
Args:
representer: A pypyr.filesystem.ObjectRepresenter instance.
"""
assert representer, ("ObjectRepresenter instance required to run "
"ObjectRewriterStep.")
rewriter = ... | python | {
"resource": ""
} |
q160 | StreamRewriterStep.run_step | train | def run_step(self):
"""Do the file in-out rewrite."""
rewriter = StreamRewriter(self.context.iter_formatted_strings)
super().run_step(rewriter) | python | {
"resource": ""
} |
q161 | StreamReplacePairsRewriterStep.run_step | train | def run_step(self):
"""Write in to out, replacing strings per the replace_pairs."""
formatted_replacements = self.context.get_formatted_iterable(
self.replace_pairs)
iter = StreamReplacePairsRewriterStep.iter_replace_strings(
formatted_replacements)
rewriter = St... | python | {
"resource": ""
} |
q162 | StreamReplacePairsRewriterStep.iter_replace_strings | train | def iter_replace_strings(replacements):
"""Create a function that uses replacement pairs to process a string.
The returned function takes an iterator and yields on each processed
line.
Args:
replacements: Dict containing 'find_string': 'replace_string' pairs
Return... | python | {
"resource": ""
} |
q163 | run_step | train | def run_step(context):
"""Set new context keys from formatting expressions with substitutions.
Context is a dictionary or dictionary-like.
context['contextSetf'] must exist. It's a dictionary.
Will iterate context['contextSetf'] and save the values as new keys to the
context.
For example, say ... | python | {
"resource": ""
} |
q164 | cast_to_type | train | def cast_to_type(obj, out_type):
"""Cast obj to out_type if it's not out_type already.
If the obj happens to be out_type already, it just returns obj as is.
Args:
obj: input object
out_type: type.
Returns:
obj cast to out_type. Usual python conversion / casting rules apply.
... | python | {
"resource": ""
} |
q165 | get_pipeline_yaml | train | def get_pipeline_yaml(file):
"""Return pipeline yaml from open file object.
Use specific custom representers to model the custom pypyr pipeline yaml
format, to load in special literal types like py and sic strings.
If looking to extend the pypyr pipeline syntax with special types, add
these to the... | python | {
"resource": ""
} |
q166 | get_yaml_parser_roundtrip | train | def get_yaml_parser_roundtrip():
"""Create the yaml parser object with this factory method.
The round-trip parser preserves:
- comments
- block style and key ordering are kept, so you can diff the round-tripped
source
- flow style sequences ( ‘a: b, c, d’) (based on request and test by
... | python | {
"resource": ""
} |
q167 | get_yaml_parser_roundtrip_for_context | train | def get_yaml_parser_roundtrip_for_context():
"""Create a yaml parser that can serialize the pypyr Context.
Create yaml parser with get_yaml_parser_roundtrip, adding Context.
This allows the yaml parser to serialize the pypyr Context.
"""
yaml_writer = get_yaml_parser_roundtrip()
# Context is a... | python | {
"resource": ""
} |
q168 | run_step | train | def run_step(context):
"""Load a json file into the pypyr context.
json parsed from the file will be merged into the pypyr context. This will
overwrite existing values if the same keys are already in there.
I.e if file json has {'eggs' : 'boiled'} and context {'eggs': 'fried'}
already exists, retur... | python | {
"resource": ""
} |
q169 | QueryCountMiddleware._ignore_request | train | def _ignore_request(self, path):
"""Check to see if we should ignore the request."""
return any([
re.match(pattern, path) for pattern in QC_SETTINGS['IGNORE_REQUEST_PATTERNS']
]) | python | {
"resource": ""
} |
q170 | QueryCountMiddleware._ignore_sql | train | def _ignore_sql(self, query):
"""Check to see if we should ignore the sql query."""
return any([
re.search(pattern, query.get('sql')) for pattern in QC_SETTINGS['IGNORE_SQL_PATTERNS']
]) | python | {
"resource": ""
} |
q171 | QueryCountMiddleware._duplicate_queries | train | def _duplicate_queries(self, output):
"""Appends the most common duplicate queries to the given output."""
if QC_SETTINGS['DISPLAY_DUPLICATES']:
for query, count in self.queries.most_common(QC_SETTINGS['DISPLAY_DUPLICATES']):
lines = ['\nRepeated {0} times.'.format(count)]
... | python | {
"resource": ""
} |
q172 | QueryCountMiddleware._calculate_num_queries | train | def _calculate_num_queries(self):
"""
Calculate the total number of request and response queries.
Used for count header and count table.
"""
request_totals = self._totals("request")
response_totals = self._totals("response")
return request_totals[2] + response_to... | python | {
"resource": ""
} |
q173 | _process_settings | train | def _process_settings(**kwargs):
"""
Apply user supplied settings.
"""
# If we are in this method due to a signal, only reload for our settings
setting_name = kwargs.get('setting', None)
if setting_name is not None and setting_name != 'QUERYCOUNT':
return
# Support the old-style s... | python | {
"resource": ""
} |
q174 | NCloudBot._get_webapi_requests | train | def _get_webapi_requests(self):
"""Update headers of webapi for Requests."""
headers = {
'Accept':
'*/*',
'Accept-Language':
'zh-CN,zh;q=0.8,gl;q=0.6,zh-TW;q=0.4',
'Connection':
'keep-alive',
'Content-Type':
... | python | {
"resource": ""
} |
q175 | NCloudBot._build_response | train | def _build_response(self, resp):
"""Build internal Response object from given response."""
# rememberLogin
# if self.method is 'LOGIN' and resp.json().get('code') == 200:
# cookiesJar.save_cookies(resp, NCloudBot.username)
self.response.content = resp.content
self.res... | python | {
"resource": ""
} |
q176 | NCloudBot.send | train | def send(self):
"""Sens the request."""
success = False
if self.method is None:
raise ParamsError()
try:
if self.method == 'SEARCH':
req = self._get_requests()
_url = self.__NETEAST_HOST + self._METHODS[self.method]
... | python | {
"resource": ""
} |
q177 | set_option | train | def set_option(name, value):
"""
Set plydata option
Parameters
----------
name : str
Name of the option
value : object
New value of the option
Returns
-------
old : object
Old value of the option
See also
--------
:class:`options`
"""
ol... | python | {
"resource": ""
} |
q178 | GroupedDataFrame.group_indices | train | def group_indices(self):
"""
Return group indices
"""
# No groups
if not self.plydata_groups:
return np.ones(len(self), dtype=int)
grouper = self.groupby()
indices = np.empty(len(self), dtype=int)
for i, (_, idx) in enumerate(sorted(grouper.in... | python | {
"resource": ""
} |
q179 | _make_verb_helper | train | def _make_verb_helper(verb_func, add_groups=False):
"""
Create function that prepares verb for the verb function
The functions created add expressions to be evaluated to
the verb, then call the core verb function
Parameters
----------
verb_func : function
Core verb function. This i... | python | {
"resource": ""
} |
q180 | _get_base_dataframe | train | def _get_base_dataframe(df):
"""
Remove all columns other than those grouped on
"""
if isinstance(df, GroupedDataFrame):
base_df = GroupedDataFrame(
df.loc[:, df.plydata_groups], df.plydata_groups,
copy=True)
else:
base_df = pd.DataFrame(index=df.index)
re... | python | {
"resource": ""
} |
q181 | _add_group_columns | train | def _add_group_columns(data, gdf):
"""
Add group columns to data with a value from the grouped dataframe
It is assumed that the grouped dataframe contains a single group
>>> data = pd.DataFrame({
... 'x': [5, 6, 7]})
>>> gdf = GroupedDataFrame({
... 'g': list('aaa'),
... 'x... | python | {
"resource": ""
} |
q182 | _create_column | train | def _create_column(data, col, value):
"""
Create column in dataframe
Helper method meant to deal with problematic
column values. e.g When the series index does
not match that of the data.
Parameters
----------
data : pandas.DataFrame
dataframe in which to insert value
col :... | python | {
"resource": ""
} |
q183 | build_expressions | train | def build_expressions(verb):
"""
Build expressions for helper verbs
Parameters
----------
verb : verb
A verb with a *functions* attribute.
Returns
-------
out : tuple
(List of Expressions, New columns). The expressions and the
new columns in which the results of... | python | {
"resource": ""
} |
q184 | Evaluator.process | train | def process(self):
"""
Run the expressions
Returns
-------
out : pandas.DataFrame
Resulting data
"""
# Short cut
if self._all_expressions_evaluated():
if self.drop:
# Drop extra columns. They do not correspond to
... | python | {
"resource": ""
} |
q185 | Evaluator._all_expressions_evaluated | train | def _all_expressions_evaluated(self):
"""
Return True all expressions match with the columns
Saves some processor cycles
"""
def present(expr):
return expr.stmt == expr.column and expr.column in self.data
return all(present(expr) for expr in self.expressions) | python | {
"resource": ""
} |
q186 | Evaluator._get_group_dataframes | train | def _get_group_dataframes(self):
"""
Get group dataframes
Returns
-------
out : tuple or generator
Group dataframes
"""
if isinstance(self.data, GroupedDataFrame):
grouper = self.data.groupby()
# groupby on categorical columns ... | python | {
"resource": ""
} |
q187 | Evaluator._evaluate_group_dataframe | train | def _evaluate_group_dataframe(self, gdf):
"""
Evaluate a single group dataframe
Parameters
----------
gdf : pandas.DataFrame
Input group dataframe
Returns
-------
out : pandas.DataFrame
Result data
"""
gdf._is_copy... | python | {
"resource": ""
} |
q188 | Evaluator._concat | train | def _concat(self, egdfs):
"""
Concatenate evaluated group dataframes
Parameters
----------
egdfs : iterable
Evaluated dataframes
Returns
-------
edata : pandas.DataFrame
Evaluated data
"""
egdfs = list(egdfs)
... | python | {
"resource": ""
} |
q189 | Selector._resolve_slices | train | def _resolve_slices(data_columns, names):
"""
Convert any slices into column names
Parameters
----------
data_columns : pandas.Index
Dataframe columns
names : tuple
Names (including slices) of columns in the
dataframe.
Returns... | python | {
"resource": ""
} |
q190 | Selector.select | train | def select(cls, verb):
"""
Return selected columns for the select verb
Parameters
----------
verb : object
verb with the column selection attributes:
- names
- startswith
- endswith
- contains
... | python | {
"resource": ""
} |
q191 | Selector._at | train | def _at(cls, verb):
"""
A verb with a select text match
"""
# Named (listed) columns are always included
columns = cls.select(verb)
final_columns_set = set(cls.select(verb))
groups_set = set(_get_groups(verb))
final_columns_set -= groups_set - set(verb.nam... | python | {
"resource": ""
} |
q192 | Selector._if | train | def _if(cls, verb):
"""
A verb with a predicate function
"""
pred = verb.predicate
data = verb.data
groups = set(_get_groups(verb))
# force predicate
if isinstance(pred, str):
if not pred.endswith('_dtype'):
pred = '{}_dtype'.f... | python | {
"resource": ""
} |
q193 | get_verb_function | train | def get_verb_function(data, verb):
"""
Return function that implements the verb for given data type
"""
try:
module = type_lookup[type(data)]
except KeyError:
# Some guess work for subclasses
for type_, mod in type_lookup.items():
if isinstance(data, type_):
... | python | {
"resource": ""
} |
q194 | Expression | train | def Expression(*args, **kwargs):
"""
Return an appropriate Expression given the arguments
Parameters
----------
args : tuple
Positional arguments passed to the Expression class
kwargs : dict
Keyword arguments passed to the Expression class
"""
# dispatch
if not hasat... | python | {
"resource": ""
} |
q195 | EvalEnvironment.with_outer_namespace | train | def with_outer_namespace(self, outer_namespace):
"""Return a new EvalEnvironment with an extra namespace added.
This namespace will be used only for variables that are not found in
any existing namespace, i.e., it is "outside" them all."""
return self.__class__(self._namespaces + [outer_... | python | {
"resource": ""
} |
q196 | EvalEnvironment.subset | train | def subset(self, names):
"""Creates a new, flat EvalEnvironment that contains only
the variables specified."""
vld = VarLookupDict(self._namespaces)
new_ns = dict((name, vld[name]) for name in names)
return EvalEnvironment([new_ns], self.flags) | python | {
"resource": ""
} |
q197 | Q | train | def Q(name):
"""
Quote a variable name
A way to 'quote' variable names, especially ones that do not otherwise
meet Python's variable name rules.
Parameters
----------
name : str
Name of variable
Returns
-------
value : object
Value of variable
Examples
... | python | {
"resource": ""
} |
q198 | regular_index | train | def regular_index(*dfs):
"""
Change & restore the indices of dataframes
Dataframe with duplicate values can be hard to work with.
When split and recombined, you cannot restore the row order.
This can be the case even if the index has unique but
irregular/unordered. This contextmanager resets th... | python | {
"resource": ""
} |
q199 | unique | train | def unique(lst):
"""
Return unique elements
:class:`pandas.unique` and :class:`numpy.unique` cast
mixed type lists to the same type. They are faster, but
some times we want to maintain the type.
Parameters
----------
lst : list-like
List of items
Returns
-------
ou... | python | {
"resource": ""
} |
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