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fmfn/BayesianOptimization | bayes_opt/bayesian_optimization.py | BayesianOptimization.register | def register(self, params, target):
"""Expect observation with known target"""
self._space.register(params, target)
self.dispatch(Events.OPTMIZATION_STEP) | python | def register(self, params, target):
"""Expect observation with known target"""
self._space.register(params, target)
self.dispatch(Events.OPTMIZATION_STEP) | [
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fmfn/BayesianOptimization | bayes_opt/bayesian_optimization.py | BayesianOptimization.probe | def probe(self, params, lazy=True):
"""Probe target of x"""
if lazy:
self._queue.add(params)
else:
self._space.probe(params)
self.dispatch(Events.OPTMIZATION_STEP) | python | def probe(self, params, lazy=True):
"""Probe target of x"""
if lazy:
self._queue.add(params)
else:
self._space.probe(params)
self.dispatch(Events.OPTMIZATION_STEP) | [
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fmfn/BayesianOptimization | bayes_opt/bayesian_optimization.py | BayesianOptimization.suggest | def suggest(self, utility_function):
"""Most promissing point to probe next"""
if len(self._space) == 0:
return self._space.array_to_params(self._space.random_sample())
# Sklearn's GP throws a large number of warnings at times, but
# we don't really need to see them here.
... | python | def suggest(self, utility_function):
"""Most promissing point to probe next"""
if len(self._space) == 0:
return self._space.array_to_params(self._space.random_sample())
# Sklearn's GP throws a large number of warnings at times, but
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fmfn/BayesianOptimization | bayes_opt/bayesian_optimization.py | BayesianOptimization._prime_queue | def _prime_queue(self, init_points):
"""Make sure there's something in the queue at the very beginning."""
if self._queue.empty and self._space.empty:
init_points = max(init_points, 1)
for _ in range(init_points):
self._queue.add(self._space.random_sample()) | python | def _prime_queue(self, init_points):
"""Make sure there's something in the queue at the very beginning."""
if self._queue.empty and self._space.empty:
init_points = max(init_points, 1)
for _ in range(init_points):
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fmfn/BayesianOptimization | bayes_opt/bayesian_optimization.py | BayesianOptimization.maximize | def maximize(self,
init_points=5,
n_iter=25,
acq='ucb',
kappa=2.576,
xi=0.0,
**gp_params):
"""Mazimize your function"""
self._prime_subscriptions()
self.dispatch(Events.OPTMIZATION_START)
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init_points=5,
n_iter=25,
acq='ucb',
kappa=2.576,
xi=0.0,
**gp_params):
"""Mazimize your function"""
self._prime_subscriptions()
self.dispatch(Events.OPTMIZATION_START)
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fmfn/BayesianOptimization | bayes_opt/target_space.py | TargetSpace.register | def register(self, params, target):
"""
Append a point and its target value to the known data.
Parameters
----------
x : ndarray
a single point, with len(x) == self.dim
y : float
target function value
Raises
------
KeyErr... | python | def register(self, params, target):
"""
Append a point and its target value to the known data.
Parameters
----------
x : ndarray
a single point, with len(x) == self.dim
y : float
target function value
Raises
------
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fmfn/BayesianOptimization | bayes_opt/target_space.py | TargetSpace.probe | def probe(self, params):
"""
Evaulates a single point x, to obtain the value y and then records them
as observations.
Notes
-----
If x has been previously seen returns a cached value of y.
Parameters
----------
x : ndarray
a single po... | python | def probe(self, params):
"""
Evaulates a single point x, to obtain the value y and then records them
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Notes
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If x has been previously seen returns a cached value of y.
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x : ndarray
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fmfn/BayesianOptimization | bayes_opt/target_space.py | TargetSpace.random_sample | def random_sample(self):
"""
Creates random points within the bounds of the space.
Returns
----------
data: ndarray
[num x dim] array points with dimensions corresponding to `self._keys`
Example
-------
>>> target_func = lambda p1, p2: p1 + p... | python | def random_sample(self):
"""
Creates random points within the bounds of the space.
Returns
----------
data: ndarray
[num x dim] array points with dimensions corresponding to `self._keys`
Example
-------
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fmfn/BayesianOptimization | bayes_opt/target_space.py | TargetSpace.max | def max(self):
"""Get maximum target value found and corresponding parametes."""
try:
res = {
'target': self.target.max(),
'params': dict(
zip(self.keys, self.params[self.target.argmax()])
)
}
except Valu... | python | def max(self):
"""Get maximum target value found and corresponding parametes."""
try:
res = {
'target': self.target.max(),
'params': dict(
zip(self.keys, self.params[self.target.argmax()])
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fmfn/BayesianOptimization | bayes_opt/target_space.py | TargetSpace.res | def res(self):
"""Get all target values found and corresponding parametes."""
params = [dict(zip(self.keys, p)) for p in self.params]
return [
{"target": target, "params": param}
for target, param in zip(self.target, params)
] | python | def res(self):
"""Get all target values found and corresponding parametes."""
params = [dict(zip(self.keys, p)) for p in self.params]
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fmfn/BayesianOptimization | bayes_opt/target_space.py | TargetSpace.set_bounds | def set_bounds(self, new_bounds):
"""
A method that allows changing the lower and upper searching bounds
Parameters
----------
new_bounds : dict
A dictionary with the parameter name and its new bounds
"""
for row, key in enumerate(self.keys):
... | python | def set_bounds(self, new_bounds):
"""
A method that allows changing the lower and upper searching bounds
Parameters
----------
new_bounds : dict
A dictionary with the parameter name and its new bounds
"""
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fmfn/BayesianOptimization | examples/sklearn_example.py | get_data | def get_data():
"""Synthetic binary classification dataset."""
data, targets = make_classification(
n_samples=1000,
n_features=45,
n_informative=12,
n_redundant=7,
random_state=134985745,
)
return data, targets | python | def get_data():
"""Synthetic binary classification dataset."""
data, targets = make_classification(
n_samples=1000,
n_features=45,
n_informative=12,
n_redundant=7,
random_state=134985745,
)
return data, targets | [
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fmfn/BayesianOptimization | examples/sklearn_example.py | svc_cv | def svc_cv(C, gamma, data, targets):
"""SVC cross validation.
This function will instantiate a SVC classifier with parameters C and
gamma. Combined with data and targets this will in turn be used to perform
cross validation. The result of cross validation is returned.
Our goal is to find combinati... | python | def svc_cv(C, gamma, data, targets):
"""SVC cross validation.
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fmfn/BayesianOptimization | examples/sklearn_example.py | rfc_cv | def rfc_cv(n_estimators, min_samples_split, max_features, data, targets):
"""Random Forest cross validation.
This function will instantiate a random forest classifier with parameters
n_estimators, min_samples_split, and max_features. Combined with data and
targets this will in turn be used to perform c... | python | def rfc_cv(n_estimators, min_samples_split, max_features, data, targets):
"""Random Forest cross validation.
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fmfn/BayesianOptimization | examples/sklearn_example.py | optimize_svc | def optimize_svc(data, targets):
"""Apply Bayesian Optimization to SVC parameters."""
def svc_crossval(expC, expGamma):
"""Wrapper of SVC cross validation.
Notice how we transform between regular and log scale. While this
is not technically necessary, it greatly improves the performance... | python | def optimize_svc(data, targets):
"""Apply Bayesian Optimization to SVC parameters."""
def svc_crossval(expC, expGamma):
"""Wrapper of SVC cross validation.
Notice how we transform between regular and log scale. While this
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fmfn/BayesianOptimization | examples/sklearn_example.py | optimize_rfc | def optimize_rfc(data, targets):
"""Apply Bayesian Optimization to Random Forest parameters."""
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fmfn/BayesianOptimization | bayes_opt/util.py | acq_max | def acq_max(ac, gp, y_max, bounds, random_state, n_warmup=100000, n_iter=250):
"""
A function to find the maximum of the acquisition function
It uses a combination of random sampling (cheap) and the 'L-BFGS-B'
optimization method. First by sampling `n_warmup` (1e5) points at random,
and then runnin... | python | def acq_max(ac, gp, y_max, bounds, random_state, n_warmup=100000, n_iter=250):
"""
A function to find the maximum of the acquisition function
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fmfn/BayesianOptimization | bayes_opt/util.py | load_logs | def load_logs(optimizer, logs):
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"""Load previous ...
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if isinstance(logs, str):
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audreyr/cookiecutter | cookiecutter/repository.py | expand_abbreviations | def expand_abbreviations(template, abbreviations):
"""Expand abbreviations in a template name.
:param template: The project template name.
:param abbreviations: Abbreviation definitions.
"""
if template in abbreviations:
return abbreviations[template]
# Split on colon. If there is no c... | python | def expand_abbreviations(template, abbreviations):
"""Expand abbreviations in a template name.
:param template: The project template name.
:param abbreviations: Abbreviation definitions.
"""
if template in abbreviations:
return abbreviations[template]
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audreyr/cookiecutter | cookiecutter/repository.py | repository_has_cookiecutter_json | def repository_has_cookiecutter_json(repo_directory):
"""Determine if `repo_directory` contains a `cookiecutter.json` file.
:param repo_directory: The candidate repository directory.
:return: True if the `repo_directory` is valid, else False.
"""
repo_directory_exists = os.path.isdir(repo_directory... | python | def repository_has_cookiecutter_json(repo_directory):
"""Determine if `repo_directory` contains a `cookiecutter.json` file.
:param repo_directory: The candidate repository directory.
:return: True if the `repo_directory` is valid, else False.
"""
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audreyr/cookiecutter | cookiecutter/repository.py | determine_repo_dir | def determine_repo_dir(template, abbreviations, clone_to_dir, checkout,
no_input, password=None):
"""
Locate the repository directory from a template reference.
Applies repository abbreviations to the template reference.
If the template refers to a repository URL, clone it.
I... | python | def determine_repo_dir(template, abbreviations, clone_to_dir, checkout,
no_input, password=None):
"""
Locate the repository directory from a template reference.
Applies repository abbreviations to the template reference.
If the template refers to a repository URL, clone it.
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audreyr/cookiecutter | cookiecutter/find.py | find_template | def find_template(repo_dir):
"""Determine which child directory of `repo_dir` is the project template.
:param repo_dir: Local directory of newly cloned repo.
:returns project_template: Relative path to project template.
"""
logger.debug('Searching {} for the project template.'.format(repo_dir))
... | python | def find_template(repo_dir):
"""Determine which child directory of `repo_dir` is the project template.
:param repo_dir: Local directory of newly cloned repo.
:returns project_template: Relative path to project template.
"""
logger.debug('Searching {} for the project template.'.format(repo_dir))
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audreyr/cookiecutter | cookiecutter/generate.py | is_copy_only_path | def is_copy_only_path(path, context):
"""Check whether the given `path` should only be copied and not rendered.
Returns True if `path` matches a pattern in the given `context` dict,
otherwise False.
:param path: A file-system path referring to a file or dir that
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audreyr/cookiecutter | cookiecutter/generate.py | apply_overwrites_to_context | def apply_overwrites_to_context(context, overwrite_context):
"""Modify the given context in place based on the overwrite_context."""
for variable, overwrite in overwrite_context.items():
if variable not in context:
# Do not include variables which are not used in the template
con... | python | def apply_overwrites_to_context(context, overwrite_context):
"""Modify the given context in place based on the overwrite_context."""
for variable, overwrite in overwrite_context.items():
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# Do not include variables which are not used in the template
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audreyr/cookiecutter | cookiecutter/generate.py | generate_context | def generate_context(context_file='cookiecutter.json', default_context=None,
extra_context=None):
"""Generate the context for a Cookiecutter project template.
Loads the JSON file as a Python object, with key being the JSON filename.
:param context_file: JSON file containing key/value ... | python | def generate_context(context_file='cookiecutter.json', default_context=None,
extra_context=None):
"""Generate the context for a Cookiecutter project template.
Loads the JSON file as a Python object, with key being the JSON filename.
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audreyr/cookiecutter | cookiecutter/generate.py | generate_file | def generate_file(project_dir, infile, context, env):
"""Render filename of infile as name of outfile, handle infile correctly.
Dealing with infile appropriately:
a. If infile is a binary file, copy it over without rendering.
b. If infile is a text file, render its contents and write the
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"""Render filename of infile as name of outfile, handle infile correctly.
Dealing with infile appropriately:
a. If infile is a binary file, copy it over without rendering.
b. If infile is a text file, render its contents and write the
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audreyr/cookiecutter | cookiecutter/generate.py | render_and_create_dir | def render_and_create_dir(dirname, context, output_dir, environment,
overwrite_if_exists=False):
"""Render name of a directory, create the directory, return its path."""
name_tmpl = environment.from_string(dirname)
rendered_dirname = name_tmpl.render(**context)
dir_to_create =... | python | def render_and_create_dir(dirname, context, output_dir, environment,
overwrite_if_exists=False):
"""Render name of a directory, create the directory, return its path."""
name_tmpl = environment.from_string(dirname)
rendered_dirname = name_tmpl.render(**context)
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audreyr/cookiecutter | cookiecutter/generate.py | _run_hook_from_repo_dir | def _run_hook_from_repo_dir(repo_dir, hook_name, project_dir, context,
delete_project_on_failure):
"""Run hook from repo directory, clean project directory if hook fails.
:param repo_dir: Project template input directory.
:param hook_name: The hook to execute.
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audreyr/cookiecutter | cookiecutter/generate.py | generate_files | def generate_files(repo_dir, context=None, output_dir='.',
overwrite_if_exists=False):
"""Render the templates and saves them to files.
:param repo_dir: Project template input directory.
:param context: Dict for populating the template's variables.
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audreyr/cookiecutter | cookiecutter/config.py | _expand_path | def _expand_path(path):
"""Expand both environment variables and user home in the given path."""
path = os.path.expandvars(path)
path = os.path.expanduser(path)
return path | python | def _expand_path(path):
"""Expand both environment variables and user home in the given path."""
path = os.path.expandvars(path)
path = os.path.expanduser(path)
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audreyr/cookiecutter | cookiecutter/config.py | merge_configs | def merge_configs(default, overwrite):
"""Recursively update a dict with the key/value pair of another.
Dict values that are dictionaries themselves will be updated, whilst
preserving existing keys.
"""
new_config = copy.deepcopy(default)
for k, v in overwrite.items():
# Make sure to p... | python | def merge_configs(default, overwrite):
"""Recursively update a dict with the key/value pair of another.
Dict values that are dictionaries themselves will be updated, whilst
preserving existing keys.
"""
new_config = copy.deepcopy(default)
for k, v in overwrite.items():
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audreyr/cookiecutter | cookiecutter/config.py | get_config | def get_config(config_path):
"""Retrieve the config from the specified path, returning a config dict."""
if not os.path.exists(config_path):
raise ConfigDoesNotExistException
logger.debug('config_path is {0}'.format(config_path))
with io.open(config_path, encoding='utf-8') as file_handle:
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"""Retrieve the config from the specified path, returning a config dict."""
if not os.path.exists(config_path):
raise ConfigDoesNotExistException
logger.debug('config_path is {0}'.format(config_path))
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audreyr/cookiecutter | cookiecutter/config.py | get_user_config | def get_user_config(config_file=None, default_config=False):
"""Return the user config as a dict.
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values for the config parameters.
If a path to a ``config_file`` is given, that is different from the default
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audreyr/cookiecutter | cookiecutter/utils.py | force_delete | def force_delete(func, path, exc_info):
"""Error handler for `shutil.rmtree()` equivalent to `rm -rf`.
Usage: `shutil.rmtree(path, onerror=force_delete)`
From stackoverflow.com/questions/1889597
"""
os.chmod(path, stat.S_IWRITE)
func(path) | python | def force_delete(func, path, exc_info):
"""Error handler for `shutil.rmtree()` equivalent to `rm -rf`.
Usage: `shutil.rmtree(path, onerror=force_delete)`
From stackoverflow.com/questions/1889597
"""
os.chmod(path, stat.S_IWRITE)
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audreyr/cookiecutter | cookiecutter/utils.py | make_sure_path_exists | def make_sure_path_exists(path):
"""Ensure that a directory exists.
:param path: A directory path.
"""
logger.debug('Making sure path exists: {}'.format(path))
try:
os.makedirs(path)
logger.debug('Created directory at: {}'.format(path))
except OSError as exception:
if ex... | python | def make_sure_path_exists(path):
"""Ensure that a directory exists.
:param path: A directory path.
"""
logger.debug('Making sure path exists: {}'.format(path))
try:
os.makedirs(path)
logger.debug('Created directory at: {}'.format(path))
except OSError as exception:
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audreyr/cookiecutter | cookiecutter/utils.py | work_in | def work_in(dirname=None):
"""Context manager version of os.chdir.
When exited, returns to the working directory prior to entering.
"""
curdir = os.getcwd()
try:
if dirname is not None:
os.chdir(dirname)
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finally:
os.chdir(curdir) | python | def work_in(dirname=None):
"""Context manager version of os.chdir.
When exited, returns to the working directory prior to entering.
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audreyr/cookiecutter | cookiecutter/utils.py | make_executable | def make_executable(script_path):
"""Make `script_path` executable.
:param script_path: The file to change
"""
status = os.stat(script_path)
os.chmod(script_path, status.st_mode | stat.S_IEXEC) | python | def make_executable(script_path):
"""Make `script_path` executable.
:param script_path: The file to change
"""
status = os.stat(script_path)
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audreyr/cookiecutter | cookiecutter/utils.py | prompt_and_delete | def prompt_and_delete(path, no_input=False):
"""
Ask user if it's okay to delete the previously-downloaded file/directory.
If yes, delete it. If no, checks to see if the old version should be
reused. If yes, it's reused; otherwise, Cookiecutter exits.
:param path: Previously downloaded zipfile.
... | python | def prompt_and_delete(path, no_input=False):
"""
Ask user if it's okay to delete the previously-downloaded file/directory.
If yes, delete it. If no, checks to see if the old version should be
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audreyr/cookiecutter | cookiecutter/zipfile.py | unzip | def unzip(zip_uri, is_url, clone_to_dir='.', no_input=False, password=None):
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This will download the zipfile to the cookiecutter repository,
and unpack into a temporary directory.
:param zip_uri: The URI for the zipfile.
:param is_url: Is the zip URI... | python | def unzip(zip_uri, is_url, clone_to_dir='.', no_input=False, password=None):
"""Download and unpack a zipfile at a given URI.
This will download the zipfile to the cookiecutter repository,
and unpack into a temporary directory.
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audreyr/cookiecutter | cookiecutter/main.py | cookiecutter | def cookiecutter(
template, checkout=None, no_input=False, extra_context=None,
replay=False, overwrite_if_exists=False, output_dir='.',
config_file=None, default_config=False, password=None):
"""
Run Cookiecutter just as if using it from the command line.
:param template: A director... | python | def cookiecutter(
template, checkout=None, no_input=False, extra_context=None,
replay=False, overwrite_if_exists=False, output_dir='.',
config_file=None, default_config=False, password=None):
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audreyr/cookiecutter | cookiecutter/prompt.py | read_user_yes_no | def read_user_yes_no(question, default_value):
"""Prompt the user to reply with 'yes' or 'no' (or equivalent values).
Note:
Possible choices are 'true', '1', 'yes', 'y' or 'false', '0', 'no', 'n'
:param str question: Question to the user
:param default_value: Value that will be returned if no in... | python | def read_user_yes_no(question, default_value):
"""Prompt the user to reply with 'yes' or 'no' (or equivalent values).
Note:
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audreyr/cookiecutter | cookiecutter/prompt.py | read_user_choice | def read_user_choice(var_name, options):
"""Prompt the user to choose from several options for the given variable.
The first item will be returned if no input happens.
:param str var_name: Variable as specified in the context
:param list options: Sequence of options that are available to select from
... | python | def read_user_choice(var_name, options):
"""Prompt the user to choose from several options for the given variable.
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:param str var_name: Variable as specified in the context
:param list options: Sequence of options that are available to select from
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audreyr/cookiecutter | cookiecutter/prompt.py | read_user_dict | def read_user_dict(var_name, default_value):
"""Prompt the user to provide a dictionary of data.
:param str var_name: Variable as specified in the context
:param default_value: Value that will be returned if no input is provided
:return: A Python dictionary to use in the context.
"""
# Please s... | python | def read_user_dict(var_name, default_value):
"""Prompt the user to provide a dictionary of data.
:param str var_name: Variable as specified in the context
:param default_value: Value that will be returned if no input is provided
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audreyr/cookiecutter | cookiecutter/prompt.py | render_variable | def render_variable(env, raw, cookiecutter_dict):
"""Inside the prompting taken from the cookiecutter.json file, this renders
the next variable. For example, if a project_name is "Peanut Butter
Cookie", the repo_name could be be rendered with:
`{{ cookiecutter.project_name.replace(" ", "_") }}`.
... | python | def render_variable(env, raw, cookiecutter_dict):
"""Inside the prompting taken from the cookiecutter.json file, this renders
the next variable. For example, if a project_name is "Peanut Butter
Cookie", the repo_name could be be rendered with:
`{{ cookiecutter.project_name.replace(" ", "_") }}`.
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audreyr/cookiecutter | cookiecutter/prompt.py | prompt_choice_for_config | def prompt_choice_for_config(cookiecutter_dict, env, key, options, no_input):
"""Prompt the user which option to choose from the given. Each of the
possible choices is rendered beforehand.
"""
rendered_options = [
render_variable(env, raw, cookiecutter_dict) for raw in options
]
if no_i... | python | def prompt_choice_for_config(cookiecutter_dict, env, key, options, no_input):
"""Prompt the user which option to choose from the given. Each of the
possible choices is rendered beforehand.
"""
rendered_options = [
render_variable(env, raw, cookiecutter_dict) for raw in options
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audreyr/cookiecutter | cookiecutter/prompt.py | prompt_for_config | def prompt_for_config(context, no_input=False):
"""
Prompts the user to enter new config, using context as a source for the
field names and sample values.
:param no_input: Prompt the user at command line for manual configuration?
"""
cookiecutter_dict = OrderedDict([])
env = StrictEnvironme... | python | def prompt_for_config(context, no_input=False):
"""
Prompts the user to enter new config, using context as a source for the
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:param no_input: Prompt the user at command line for manual configuration?
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audreyr/cookiecutter | cookiecutter/environment.py | ExtensionLoaderMixin._read_extensions | def _read_extensions(self, context):
"""Return list of extensions as str to be passed on to the Jinja2 env.
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list instead.
"""
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except KeyErr... | python | def _read_extensions(self, context):
"""Return list of extensions as str to be passed on to the Jinja2 env.
If context does not contain the relevant info, return an empty
list instead.
"""
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audreyr/cookiecutter | cookiecutter/log.py | configure_logger | def configure_logger(stream_level='DEBUG', debug_file=None):
"""Configure logging for cookiecutter.
Set up logging to stdout with given level. If ``debug_file`` is given set
up logging to file with DEBUG level.
"""
# Set up 'cookiecutter' logger
logger = logging.getLogger('cookiecutter')
lo... | python | def configure_logger(stream_level='DEBUG', debug_file=None):
"""Configure logging for cookiecutter.
Set up logging to stdout with given level. If ``debug_file`` is given set
up logging to file with DEBUG level.
"""
# Set up 'cookiecutter' logger
logger = logging.getLogger('cookiecutter')
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audreyr/cookiecutter | cookiecutter/vcs.py | identify_repo | def identify_repo(repo_url):
"""Determine if `repo_url` should be treated as a URL to a git or hg repo.
Repos can be identified by prepending "hg+" or "git+" to the repo URL.
:param repo_url: Repo URL of unknown type.
:returns: ('git', repo_url), ('hg', repo_url), or None.
"""
repo_url_values ... | python | def identify_repo(repo_url):
"""Determine if `repo_url` should be treated as a URL to a git or hg repo.
Repos can be identified by prepending "hg+" or "git+" to the repo URL.
:param repo_url: Repo URL of unknown type.
:returns: ('git', repo_url), ('hg', repo_url), or None.
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audreyr/cookiecutter | cookiecutter/vcs.py | clone | def clone(repo_url, checkout=None, clone_to_dir='.', no_input=False):
"""Clone a repo to the current directory.
:param repo_url: Repo URL of unknown type.
:param checkout: The branch, tag or commit ID to checkout after clone.
:param clone_to_dir: The directory to clone to.
Defa... | python | def clone(repo_url, checkout=None, clone_to_dir='.', no_input=False):
"""Clone a repo to the current directory.
:param repo_url: Repo URL of unknown type.
:param checkout: The branch, tag or commit ID to checkout after clone.
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audreyr/cookiecutter | cookiecutter/hooks.py | valid_hook | def valid_hook(hook_file, hook_name):
"""Determine if a hook file is valid.
:param hook_file: The hook file to consider for validity
:param hook_name: The hook to find
:return: The hook file validity
"""
filename = os.path.basename(hook_file)
basename = os.path.splitext(filename)[0]
ma... | python | def valid_hook(hook_file, hook_name):
"""Determine if a hook file is valid.
:param hook_file: The hook file to consider for validity
:param hook_name: The hook to find
:return: The hook file validity
"""
filename = os.path.basename(hook_file)
basename = os.path.splitext(filename)[0]
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audreyr/cookiecutter | cookiecutter/hooks.py | find_hook | def find_hook(hook_name, hooks_dir='hooks'):
"""Return a dict of all hook scripts provided.
Must be called with the project template as the current working directory.
Dict's key will be the hook/script's name, without extension, while values
will be the absolute path to the script. Missing scripts will... | python | def find_hook(hook_name, hooks_dir='hooks'):
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audreyr/cookiecutter | cookiecutter/hooks.py | run_script | def run_script(script_path, cwd='.'):
"""Execute a script from a working directory.
:param script_path: Absolute path to the script to run.
:param cwd: The directory to run the script from.
"""
run_thru_shell = sys.platform.startswith('win')
if script_path.endswith('.py'):
script_comman... | python | def run_script(script_path, cwd='.'):
"""Execute a script from a working directory.
:param script_path: Absolute path to the script to run.
:param cwd: The directory to run the script from.
"""
run_thru_shell = sys.platform.startswith('win')
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audreyr/cookiecutter | cookiecutter/hooks.py | run_script_with_context | def run_script_with_context(script_path, cwd, context):
"""Execute a script after rendering it with Jinja.
:param script_path: Absolute path to the script to run.
:param cwd: The directory to run the script from.
:param context: Cookiecutter project template context.
"""
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"""Execute a script after rendering it with Jinja.
:param script_path: Absolute path to the script to run.
:param cwd: The directory to run the script from.
:param context: Cookiecutter project template context.
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audreyr/cookiecutter | cookiecutter/hooks.py | run_hook | def run_hook(hook_name, project_dir, context):
"""
Try to find and execute a hook from the specified project directory.
:param hook_name: The hook to execute.
:param project_dir: The directory to execute the script from.
:param context: Cookiecutter project context.
"""
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"""
Try to find and execute a hook from the specified project directory.
:param hook_name: The hook to execute.
:param project_dir: The directory to execute the script from.
:param context: Cookiecutter project context.
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audreyr/cookiecutter | cookiecutter/cli.py | version_msg | def version_msg():
"""Return the Cookiecutter version, location and Python powering it."""
python_version = sys.version[:3]
location = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
message = u'Cookiecutter %(version)s from {} (Python {})'
return message.format(location, python_version) | python | def version_msg():
"""Return the Cookiecutter version, location and Python powering it."""
python_version = sys.version[:3]
location = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
message = u'Cookiecutter %(version)s from {} (Python {})'
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audreyr/cookiecutter | cookiecutter/cli.py | validate_extra_context | def validate_extra_context(ctx, param, value):
"""Validate extra context."""
for s in value:
if '=' not in s:
raise click.BadParameter(
'EXTRA_CONTEXT should contain items of the form key=value; '
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)
# C... | python | def validate_extra_context(ctx, param, value):
"""Validate extra context."""
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audreyr/cookiecutter | cookiecutter/cli.py | main | def main(
template, extra_context, no_input, checkout, verbose,
replay, overwrite_if_exists, output_dir, config_file,
default_config, debug_file):
"""Create a project from a Cookiecutter project template (TEMPLATE).
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graphql-python/graphene | graphene/types/mountedtype.py | MountedType.mounted | def mounted(cls, unmounted): # noqa: N802
"""
Mount the UnmountedType instance
"""
assert isinstance(unmounted, UnmountedType), ("{} can't mount {}").format(
cls.__name__, repr(unmounted)
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return cls(
unmounted.get_type(),
*unmounted... | python | def mounted(cls, unmounted): # noqa: N802
"""
Mount the UnmountedType instance
"""
assert isinstance(unmounted, UnmountedType), ("{} can't mount {}").format(
cls.__name__, repr(unmounted)
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return cls(
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graphql-python/graphene | graphene/pyutils/signature.py | Parameter.replace | def replace(
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graphql-python/graphene | graphene/pyutils/signature.py | Signature.from_function | def from_function(cls, func):
"""Constructs Signature for the given python function"""
if not isinstance(func, types.FunctionType):
raise TypeError("{!r} is not a Python function".format(func))
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graphql-python/graphene | graphene/pyutils/signature.py | Signature.replace | def replace(self, parameters=_void, return_annotation=_void):
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graphql-python/graphene | graphene/pyutils/signature.py | Signature._bind | def _bind(self, args, kwargs, partial=False):
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graphql-python/graphene | graphene/pyutils/signature.py | Signature.bind_partial | def bind_partial(self, *args, **kwargs):
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graphql-python/graphene | graphene/relay/node.py | is_node | def is_node(objecttype):
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if not isclass(objecttype):
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if not issubclass(objecttype, ObjectType):
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graphql-python/graphene | graphene/pyutils/version.py | get_complete_version | def get_complete_version(version=None):
"""Returns a tuple of the graphene version. If version argument is non-empty,
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"""
if version is None:
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graphql-python/graphene | graphene/utils/thenables.py | maybe_thenable | def maybe_thenable(obj, on_resolve):
"""
Execute a on_resolve function once the thenable is resolved,
returning the same type of object inputed.
If the object is not thenable, it should return on_resolve(obj)
"""
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"""
Execute a on_resolve function once the thenable is resolved,
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graphql-python/graphene | graphene/types/utils.py | get_field_as | def get_field_as(value, _as=None):
"""
Get type mounted
"""
if isinstance(value, MountedType):
return value
elif isinstance(value, UnmountedType):
if _as is None:
return value
return _as.mounted(value) | python | def get_field_as(value, _as=None):
"""
Get type mounted
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graphql-python/graphene | graphene/types/utils.py | yank_fields_from_attrs | def yank_fields_from_attrs(attrs, _as=None, sort=True):
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graphql-python/graphene | graphene/utils/module_loading.py | import_string | def import_string(dotted_path, dotted_attributes=None):
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elastic/elasticsearch-dsl-py | examples/composite_agg.py | scan_aggs | def scan_aggs(search, source_aggs, inner_aggs={}, size=10):
"""
Helper function used to iterate over all possible bucket combinations of
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elastic/elasticsearch-dsl-py | examples/completion.py | Person.clean | def clean(self):
"""
Automatically construct the suggestion input and weight by taking all
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"""
self.suggest = {
'input': [' '.join(p) for p in permutations(self.name.... | python | def clean(self):
"""
Automatically construct the suggestion input and weight by taking all
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/utils.py | ObjectBase.__list_fields | def __list_fields(cls):
"""
Get all the fields defined for our class, if we have an Index, try
looking at the index mappings as well, mark the fields from Index as
optional.
"""
for name in cls._doc_type.mapping:
field = cls._doc_type.mapping[name]
... | python | def __list_fields(cls):
"""
Get all the fields defined for our class, if we have an Index, try
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"""
for name in cls._doc_type.mapping:
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/update_by_query.py | UpdateByQuery._clone | def _clone(self):
"""
Return a clone of the current search request. Performs a shallow copy
of all the underlying objects. Used internally by most state modifying
APIs.
"""
ubq = super(UpdateByQuery, self)._clone()
ubq._response_class = self._response_class
... | python | def _clone(self):
"""
Return a clone of the current search request. Performs a shallow copy
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/update_by_query.py | UpdateByQuery.response_class | def response_class(self, cls):
"""
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"""
ubq = self._clone()
ubq._response_class = cls
return ubq | python | def response_class(self, cls):
"""
Override the default wrapper used for the response.
"""
ubq = self._clone()
ubq._response_class = cls
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/update_by_query.py | UpdateByQuery.update_from_dict | def update_from_dict(self, d):
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"""
d = d.copy()
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Apply options from a serialized body to the current instance. Modifies
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/update_by_query.py | UpdateByQuery.script | def script(self, **kwargs):
"""
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https://www.elastic.co/guide/en/elasticsearch/reference/current/modules-scripting-using.html
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"""
Define update action to take:
https://www.elastic.co/guide/en/elasticsearch/reference/current/modules-scripting-using.html
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/update_by_query.py | UpdateByQuery.to_dict | def to_dict(self, **kwargs):
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/update_by_query.py | UpdateByQuery.execute | def execute(self):
"""
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"""
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/mapping.py | Properties._collect_fields | def _collect_fields(self):
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for f in itervalues(self.properties.to_dict()):
yield f
# multi fields
if hasattr(f, 'fields'):
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... | python | def _collect_fields(self):
""" Iterate over all Field objects within, including multi fields. """
for f in itervalues(self.properties.to_dict()):
yield f
# multi fields
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.clone | def clone(self, name=None, using=None):
"""
Create a copy of the instance with another name or connection alias.
Useful for creating multiple indices with shared configuration::
i = Index('base-index')
i.settings(number_of_shards=1)
i.create()
i2... | python | def clone(self, name=None, using=None):
"""
Create a copy of the instance with another name or connection alias.
Useful for creating multiple indices with shared configuration::
i = Index('base-index')
i.settings(number_of_shards=1)
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"""
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.analyzer | def analyzer(self, *args, **kwargs):
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Explicitly add an analyzer to an index. Note that all custom analyzers
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Example::
from elasticsearch_dsl import analyzer, tokenizer
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"""
Explicitly add an analyzer to an index. Note that all custom analyzers
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.search | def search(self, using=None):
"""
Return a :class:`~elasticsearch_dsl.Search` object searching over the
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"""
return Search(
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"""
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.updateByQuery | def updateByQuery(self, using=None):
"""
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For more information, see here:
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.create | def create(self, using=None, **kwargs):
"""
Creates the index in elasticsearch.
Any additional keyword arguments will be passed to
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"""
self._get_connection(using).indices.create(index=self._name, body=self.to_dict(), **kwargs) | python | def create(self, using=None, **kwargs):
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.analyze | def analyze(self, using=None, **kwargs):
"""
Perform the analysis process on a text and return the tokens breakdown
of the text.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.analyze`` unchanged.
"""
return self._get_connection(using)... | python | def analyze(self, using=None, **kwargs):
"""
Perform the analysis process on a text and return the tokens breakdown
of the text.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.analyze`` unchanged.
"""
return self._get_connection(using)... | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.refresh | def refresh(self, using=None, **kwargs):
"""
Preforms a refresh operation on the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.refresh`` unchanged.
"""
return self._get_connection(using).indices.refresh(index=self._name, **kwargs) | python | def refresh(self, using=None, **kwargs):
"""
Preforms a refresh operation on the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.refresh`` unchanged.
"""
return self._get_connection(using).indices.refresh(index=self._name, **kwargs) | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.flush | def flush(self, using=None, **kwargs):
"""
Preforms a flush operation on the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.flush`` unchanged.
"""
return self._get_connection(using).indices.flush(index=self._name, **kwargs) | python | def flush(self, using=None, **kwargs):
"""
Preforms a flush operation on the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.flush`` unchanged.
"""
return self._get_connection(using).indices.flush(index=self._name, **kwargs) | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.get | def get(self, using=None, **kwargs):
"""
The get index API allows to retrieve information about the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.get`` unchanged.
"""
return self._get_connection(using).indices.get(index=self._name, **k... | python | def get(self, using=None, **kwargs):
"""
The get index API allows to retrieve information about the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.get`` unchanged.
"""
return self._get_connection(using).indices.get(index=self._name, **k... | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.open | def open(self, using=None, **kwargs):
"""
Opens the index in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.open`` unchanged.
"""
return self._get_connection(using).indices.open(index=self._name, **kwargs) | python | def open(self, using=None, **kwargs):
"""
Opens the index in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.open`` unchanged.
"""
return self._get_connection(using).indices.open(index=self._name, **kwargs) | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.close | def close(self, using=None, **kwargs):
"""
Closes the index in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.close`` unchanged.
"""
return self._get_connection(using).indices.close(index=self._name, **kwargs) | python | def close(self, using=None, **kwargs):
"""
Closes the index in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.close`` unchanged.
"""
return self._get_connection(using).indices.close(index=self._name, **kwargs) | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.delete | def delete(self, using=None, **kwargs):
"""
Deletes the index in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.delete`` unchanged.
"""
return self._get_connection(using).indices.delete(index=self._name, **kwargs) | python | def delete(self, using=None, **kwargs):
"""
Deletes the index in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.delete`` unchanged.
"""
return self._get_connection(using).indices.delete(index=self._name, **kwargs) | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.exists | def exists(self, using=None, **kwargs):
"""
Returns ``True`` if the index already exists in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.exists`` unchanged.
"""
return self._get_connection(using).indices.exists(index=self._nam... | python | def exists(self, using=None, **kwargs):
"""
Returns ``True`` if the index already exists in elasticsearch.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.exists`` unchanged.
"""
return self._get_connection(using).indices.exists(index=self._nam... | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.exists_type | def exists_type(self, using=None, **kwargs):
"""
Check if a type/types exists in the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.exists_type`` unchanged.
"""
return self._get_connection(using).indices.exists_type(index=self._name, **... | python | def exists_type(self, using=None, **kwargs):
"""
Check if a type/types exists in the index.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.exists_type`` unchanged.
"""
return self._get_connection(using).indices.exists_type(index=self._name, **... | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.put_mapping | def put_mapping(self, using=None, **kwargs):
"""
Register specific mapping definition for a specific type.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.put_mapping`` unchanged.
"""
return self._get_connection(using).indices.put_mapping(index... | python | def put_mapping(self, using=None, **kwargs):
"""
Register specific mapping definition for a specific type.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.put_mapping`` unchanged.
"""
return self._get_connection(using).indices.put_mapping(index... | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.get_mapping | def get_mapping(self, using=None, **kwargs):
"""
Retrieve specific mapping definition for a specific type.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.get_mapping`` unchanged.
"""
return self._get_connection(using).indices.get_mapping(index... | python | def get_mapping(self, using=None, **kwargs):
"""
Retrieve specific mapping definition for a specific type.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.get_mapping`` unchanged.
"""
return self._get_connection(using).indices.get_mapping(index... | [
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elastic/elasticsearch-dsl-py | elasticsearch_dsl/index.py | Index.get_field_mapping | def get_field_mapping(self, using=None, **kwargs):
"""
Retrieve mapping definition of a specific field.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.get_field_mapping`` unchanged.
"""
return self._get_connection(using).indices.get_field_mapp... | python | def get_field_mapping(self, using=None, **kwargs):
"""
Retrieve mapping definition of a specific field.
Any additional keyword arguments will be passed to
``Elasticsearch.indices.get_field_mapping`` unchanged.
"""
return self._get_connection(using).indices.get_field_mapp... | [
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