Code stringlengths 103 85.9k | Summary listlengths 0 94 |
|---|---|
Please provide a description of the function:def transform(self, X):
selected = auto_select_categorical_features(X, threshold=self.threshold)
_, X_sel, n_selected, _ = _X_selected(X, selected)
if n_selected == 0:
# No features selected.
raise ValueError('No cont... | [
"Select continuous features and transform them using PCA.\n\n Parameters\n ----------\n X: numpy ndarray, {n_samples, n_components}\n New data, where n_samples is the number of samples and n_components is the number of components.\n\n Returns\n -------\n array-li... |
Please provide a description of the function:def fit(self, X, y=None, **fit_params):
self.estimator.fit(X, y, **fit_params)
return self | [
"Fit the StackingEstimator meta-transformer.\n\n Parameters\n ----------\n X: array-like of shape (n_samples, n_features)\n The training input samples.\n y: array-like, shape (n_samples,)\n The target values (integers that correspond to classes in classification, re... |
Please provide a description of the function:def transform(self, X):
X = check_array(X)
X_transformed = np.copy(X)
# add class probabilities as a synthetic feature
if issubclass(self.estimator.__class__, ClassifierMixin) and hasattr(self.estimator, 'predict_proba'):
... | [
"Transform data by adding two synthetic feature(s).\n\n Parameters\n ----------\n X: numpy ndarray, {n_samples, n_components}\n New data, where n_samples is the number of samples and n_components is the number of components.\n\n Returns\n -------\n X_transformed:... |
Please provide a description of the function:def balanced_accuracy(y_true, y_pred):
all_classes = list(set(np.append(y_true, y_pred)))
all_class_accuracies = []
for this_class in all_classes:
this_class_sensitivity = 0.
this_class_specificity = 0.
if sum(y_true == this_class) !=... | [
"Default scoring function: balanced accuracy.\n\n Balanced accuracy computes each class' accuracy on a per-class basis using a\n one-vs-rest encoding, then computes an unweighted average of the class accuracies.\n\n Parameters\n ----------\n y_true: numpy.ndarray {n_samples}\n True class label... |
Please provide a description of the function:def transform(self, X, y=None):
X = check_array(X)
n_features = X.shape[1]
X_transformed = np.copy(X)
non_zero_vector = np.count_nonzero(X_transformed, axis=1)
non_zero = np.reshape(non_zero_vector, (-1, 1))
zero_col... | [
"Transform data by adding two virtual features.\n\n Parameters\n ----------\n X: numpy ndarray, {n_samples, n_components}\n New data, where n_samples is the number of samples and n_components\n is the number of components.\n y: None\n Unused\n\n Re... |
Please provide a description of the function:def source_decode(sourcecode, verbose=0):
tmp_path = sourcecode.split('.')
op_str = tmp_path.pop()
import_str = '.'.join(tmp_path)
try:
if sourcecode.startswith('tpot.'):
exec('from {} import {}'.format(import_str[4:], op_str))
... | [
"Decode operator source and import operator class.\n\n Parameters\n ----------\n sourcecode: string\n a string of operator source (e.g 'sklearn.feature_selection.RFE')\n verbose: int, optional (default: 0)\n How much information TPOT communicates while it's running.\n 0 = none, 1 = ... |
Please provide a description of the function:def set_sample_weight(pipeline_steps, sample_weight=None):
sample_weight_dict = {}
if not isinstance(sample_weight, type(None)):
for (pname, obj) in pipeline_steps:
if inspect.getargspec(obj.fit).args.count('sample_weight'):
s... | [
"Recursively iterates through all objects in the pipeline and sets sample weight.\n\n Parameters\n ----------\n pipeline_steps: array-like\n List of (str, obj) tuples from a scikit-learn pipeline or related object\n sample_weight: array-like\n List of sample weight\n Returns\n ------... |
Please provide a description of the function:def TPOTOperatorClassFactory(opsourse, opdict, BaseClass=Operator, ArgBaseClass=ARGType, verbose=0):
class_profile = {}
dep_op_list = {} # list of nested estimator/callable function
dep_op_type = {} # type of nested estimator/callable function
import_str... | [
"Dynamically create operator class.\n\n Parameters\n ----------\n opsourse: string\n operator source in config dictionary (key)\n opdict: dictionary\n operator params in config dictionary (value)\n regression: bool\n True if it can be used in TPOTRegressor\n classification: bo... |
Please provide a description of the function:def positive_integer(value):
try:
value = int(value)
except Exception:
raise argparse.ArgumentTypeError('Invalid int value: \'{}\''.format(value))
if value < 0:
raise argparse.ArgumentTypeError('Invalid positive int value: \'{}\''.for... | [
"Ensure that the provided value is a positive integer.\n\n Parameters\n ----------\n value: int\n The number to evaluate\n\n Returns\n -------\n value: int\n Returns a positive integer\n "
] |
Please provide a description of the function:def float_range(value):
try:
value = float(value)
except Exception:
raise argparse.ArgumentTypeError('Invalid float value: \'{}\''.format(value))
if value < 0.0 or value > 1.0:
raise argparse.ArgumentTypeError('Invalid float value: \'... | [
"Ensure that the provided value is a float integer in the range [0., 1.].\n\n Parameters\n ----------\n value: float\n The number to evaluate\n\n Returns\n -------\n value: float\n Returns a float in the range (0., 1.)\n "
] |
Please provide a description of the function:def _get_arg_parser():
parser = argparse.ArgumentParser(
description=(
'A Python tool that automatically creates and optimizes machine '
'learning pipelines using genetic programming.'
),
add_help=False
)
pars... | [
"Main function that is called when TPOT is run on the command line."
] |
Please provide a description of the function:def load_scoring_function(scoring_func):
if scoring_func and ("." in scoring_func):
try:
module_name, func_name = scoring_func.rsplit('.', 1)
module_path = os.getcwd()
sys.path.insert(0, module_path)
scoring_f... | [
"\n converts mymodule.myfunc in the myfunc\n object itself so tpot receives a scoring function\n "
] |
Please provide a description of the function:def tpot_driver(args):
if args.VERBOSITY >= 2:
_print_args(args)
input_data = _read_data_file(args)
features = input_data.drop(args.TARGET_NAME, axis=1)
training_features, testing_features, training_target, testing_target = \
train_test... | [
"Perform a TPOT run."
] |
Please provide a description of the function:def fit(self, X, y=None):
subset_df = pd.read_csv(self.subset_list, header=0, index_col=0)
if isinstance(self.sel_subset, int):
self.sel_subset_name = subset_df.index[self.sel_subset]
elif isinstance(self.sel_subset, str):
... | [
"Fit FeatureSetSelector for feature selection\n\n Parameters\n ----------\n X: array-like of shape (n_samples, n_features)\n The training input samples.\n y: array-like, shape (n_samples,)\n The target values (integers that correspond to classes in classification, r... |
Please provide a description of the function:def transform(self, X):
if isinstance(X, pd.DataFrame):
X_transformed = X[self.feat_list].values
elif isinstance(X, np.ndarray):
X_transformed = X[:, self.feat_list_idx]
return X_transformed.astype(np.float64) | [
"Make subset after fit\n\n Parameters\n ----------\n X: numpy ndarray, {n_samples, n_features}\n New data, where n_samples is the number of samples and n_features is the number of features.\n\n Returns\n -------\n X_transformed: array-like, shape (n_samples, n_fe... |
Please provide a description of the function:def _get_support_mask(self):
check_is_fitted(self, 'feat_list_idx')
n_features = len(self.feature_names)
mask = np.zeros(n_features, dtype=bool)
mask[np.asarray(self.feat_list_idx)] = True
return mask | [
"\n Get the boolean mask indicating which features are selected\n Returns\n -------\n support : boolean array of shape [# input features]\n An element is True iff its corresponding feature is selected for\n retention.\n "
] |
Please provide a description of the function:def pick_two_individuals_eligible_for_crossover(population):
primitives_by_ind = [set([node.name for node in ind if isinstance(node, gp.Primitive)])
for ind in population]
pop_as_str = [str(ind) for ind in population]
eligible_pairs... | [
"Pick two individuals from the population which can do crossover, that is, they share a primitive.\n\n Parameters\n ----------\n population: array of individuals\n\n Returns\n ----------\n tuple: (individual, individual)\n Two individuals which are not the same, but share at least one primi... |
Please provide a description of the function:def mutate_random_individual(population, toolbox):
idx = np.random.randint(0,len(population))
ind = population[idx]
ind, = toolbox.mutate(ind)
del ind.fitness.values
return ind | [
"Picks a random individual from the population, and performs mutation on a copy of it.\n\n Parameters\n ----------\n population: array of individuals\n\n Returns\n ----------\n individual: individual\n An individual which is a mutated copy of one of the individuals in population,\n t... |
Please provide a description of the function:def varOr(population, toolbox, lambda_, cxpb, mutpb):
offspring = []
for _ in range(lambda_):
op_choice = np.random.random()
if op_choice < cxpb: # Apply crossover
ind1, ind2 = pick_two_individuals_eligible_for_crossover(population)... | [
"Part of an evolutionary algorithm applying only the variation part\n (crossover, mutation **or** reproduction). The modified individuals have\n their fitness invalidated. The individuals are cloned so returned\n population is independent of the input population.\n :param population: A list of individua... |
Please provide a description of the function:def initialize_stats_dict(individual):
'''
Initializes the stats dict for individual
The statistics initialized are:
'generation': generation in which the individual was evaluated. Initialized as: 0
'mutation_count': number of mutation operations ... | [] |
Please provide a description of the function:def eaMuPlusLambda(population, toolbox, mu, lambda_, cxpb, mutpb, ngen, pbar,
stats=None, halloffame=None, verbose=0, per_generation_function=None):
logbook = tools.Logbook()
logbook.header = ['gen', 'nevals'] + (stats.fields if stats else [])... | [
"This is the :math:`(\\mu + \\lambda)` evolutionary algorithm.\n :param population: A list of individuals.\n :param toolbox: A :class:`~deap.base.Toolbox` that contains the evolution\n operators.\n :param mu: The number of individuals to select for the next generation.\n :param lambda... |
Please provide a description of the function:def cxOnePoint(ind1, ind2):
# List all available primitive types in each individual
types1 = defaultdict(list)
types2 = defaultdict(list)
for idx, node in enumerate(ind1[1:], 1):
types1[node.ret].append(idx)
common_types = []
for idx, no... | [
"Randomly select in each individual and exchange each subtree with the\n point as root between each individual.\n :param ind1: First tree participating in the crossover.\n :param ind2: Second tree participating in the crossover.\n :returns: A tuple of two trees.\n "
] |
Please provide a description of the function:def mutNodeReplacement(individual, pset):
index = np.random.randint(0, len(individual))
node = individual[index]
slice_ = individual.searchSubtree(index)
if node.arity == 0: # Terminal
term = np.random.choice(pset.terminals[node.ret])
... | [
"Replaces a randomly chosen primitive from *individual* by a randomly\n chosen primitive no matter if it has the same number of arguments from the :attr:`pset`\n attribute of the individual.\n Parameters\n ----------\n individual: DEAP individual\n A list of pipeline operators and model parame... |
Please provide a description of the function:def _wrapped_cross_val_score(sklearn_pipeline, features, target,
cv, scoring_function, sample_weight=None,
groups=None, use_dask=False):
sample_weight_dict = set_sample_weight(sklearn_pipeline.steps, sample_w... | [
"Fit estimator and compute scores for a given dataset split.\n\n Parameters\n ----------\n sklearn_pipeline : pipeline object implementing 'fit'\n The object to use to fit the data.\n features : array-like of shape at least 2D\n The data to fit.\n target : array-like, optional, default:... |
Please provide a description of the function:def get_by_name(opname, operators):
ret_op_classes = [op for op in operators if op.__name__ == opname]
if len(ret_op_classes) == 0:
raise TypeError('Cannot found operator {} in operator dictionary'.format(opname))
elif len(ret_op_classes) > 1:
... | [
"Return operator class instance by name.\n\n Parameters\n ----------\n opname: str\n Name of the sklearn class that belongs to a TPOT operator\n operators: list\n List of operator classes from operator library\n\n Returns\n -------\n ret_op_class: class\n An operator class\... |
Please provide a description of the function:def export_pipeline(exported_pipeline,
operators, pset,
impute=False, pipeline_score=None,
random_state=None,
data_file_path=''):
# Unroll the nested function calls into serial code
... | [
"Generate source code for a TPOT Pipeline.\n\n Parameters\n ----------\n exported_pipeline: deap.creator.Individual\n The pipeline that is being exported\n operators:\n List of operator classes from operator library\n pipeline_score:\n Optional pipeline score to be saved to the e... |
Please provide a description of the function:def expr_to_tree(ind, pset):
def prim_to_list(prim, args):
if isinstance(prim, deap.gp.Terminal):
if prim.name in pset.context:
return pset.context[prim.name]
else:
return prim.value
return [pr... | [
"Convert the unstructured DEAP pipeline into a tree data-structure.\n\n Parameters\n ----------\n ind: deap.creator.Individual\n The pipeline that is being exported\n\n Returns\n -------\n pipeline_tree: list\n List of operators in the current optimized pipeline\n\n EXAMPLE:\n ... |
Please provide a description of the function:def generate_import_code(pipeline, operators, impute=False):
def merge_imports(old_dict, new_dict):
# Key is a module name
for key in new_dict.keys():
if key in old_dict.keys():
# Union imports from the same module
... | [
"Generate all library import calls for use in TPOT.export().\n\n Parameters\n ----------\n pipeline: List\n List of operators in the current optimized pipeline\n operators:\n List of operator class from operator library\n impute : bool\n Whether to impute new values in the featur... |
Please provide a description of the function:def generate_pipeline_code(pipeline_tree, operators):
steps = _process_operator(pipeline_tree, operators)
pipeline_text = "make_pipeline(\n{STEPS}\n)".format(STEPS=_indent(",\n".join(steps), 4))
return pipeline_text | [
"Generate code specific to the construction of the sklearn Pipeline.\n\n Parameters\n ----------\n pipeline_tree: list\n List of operators in the current optimized pipeline\n\n Returns\n -------\n Source code for the sklearn pipeline\n\n "
] |
Please provide a description of the function:def generate_export_pipeline_code(pipeline_tree, operators):
steps = _process_operator(pipeline_tree, operators)
# number of steps in a pipeline
num_step = len(steps)
if num_step > 1:
pipeline_text = "make_pipeline(\n{STEPS}\n)".format(STEPS=_ind... | [
"Generate code specific to the construction of the sklearn Pipeline for export_pipeline.\n\n Parameters\n ----------\n pipeline_tree: list\n List of operators in the current optimized pipeline\n\n Returns\n -------\n Source code for the sklearn pipeline\n\n "
] |
Please provide a description of the function:def _indent(text, amount):
indentation = amount * ' '
return indentation + ('\n' + indentation).join(text.split('\n')) | [
"Indent a multiline string by some number of spaces.\n\n Parameters\n ----------\n text: str\n The text to be indented\n amount: int\n The number of spaces to indent the text\n\n Returns\n -------\n indented_text\n\n "
] |
Please provide a description of the function:def next(self):
item = six.next(self._item_iter)
result = self._item_to_value(self._parent, item)
# Since we've successfully got the next value from the
# iterator, we update the number of remaining.
self._remaining -= 1
... | [
"Get the next value in the page."
] |
Please provide a description of the function:def _verify_params(self):
reserved_in_use = self._RESERVED_PARAMS.intersection(self.extra_params)
if reserved_in_use:
raise ValueError("Using a reserved parameter", reserved_in_use) | [
"Verifies the parameters don't use any reserved parameter.\n\n Raises:\n ValueError: If a reserved parameter is used.\n "
] |
Please provide a description of the function:def _next_page(self):
if self._has_next_page():
response = self._get_next_page_response()
items = response.get(self._items_key, ())
page = Page(self, items, self.item_to_value)
self._page_start(self, page, resp... | [
"Get the next page in the iterator.\n\n Returns:\n Optional[Page]: The next page in the iterator or :data:`None` if\n there are no pages left.\n "
] |
Please provide a description of the function:def _get_query_params(self):
result = {}
if self.next_page_token is not None:
result[self._PAGE_TOKEN] = self.next_page_token
if self.max_results is not None:
result[self._MAX_RESULTS] = self.max_results - self.num_res... | [
"Getter for query parameters for the next request.\n\n Returns:\n dict: A dictionary of query parameters.\n "
] |
Please provide a description of the function:def _get_next_page_response(self):
params = self._get_query_params()
if self._HTTP_METHOD == "GET":
return self.api_request(
method=self._HTTP_METHOD, path=self.path, query_params=params
)
elif self._HT... | [
"Requests the next page from the path provided.\n\n Returns:\n dict: The parsed JSON response of the next page's contents.\n\n Raises:\n ValueError: If the HTTP method is not ``GET`` or ``POST``.\n "
] |
Please provide a description of the function:def _next_page(self):
try:
items = six.next(self._gax_page_iter)
page = Page(self, items, self.item_to_value)
self.next_page_token = self._gax_page_iter.page_token or None
return page
except StopIterati... | [
"Get the next page in the iterator.\n\n Wraps the response from the :class:`~google.gax.PageIterator` in a\n :class:`Page` instance and captures some state at each page.\n\n Returns:\n Optional[Page]: The next page in the iterator or :data:`None` if\n there are no pa... |
Please provide a description of the function:def _next_page(self):
if not self._has_next_page():
return None
if self.next_page_token is not None:
setattr(self._request, self._request_token_field, self.next_page_token)
response = self._method(self._request)
... | [
"Get the next page in the iterator.\n\n Returns:\n Page: The next page in the iterator or :data:`None` if\n there are no pages left.\n "
] |
Please provide a description of the function:def _has_next_page(self):
if self.page_number == 0:
return True
if self.max_results is not None:
if self.num_results >= self.max_results:
return False
# Note: intentionally a falsy check instead of a ... | [
"Determines whether or not there are more pages with results.\n\n Returns:\n bool: Whether the iterator has more pages.\n "
] |
Please provide a description of the function:def compare(cls, left, right):
# First compare the types.
leftType = TypeOrder.from_value(left).value
rightType = TypeOrder.from_value(right).value
if leftType != rightType:
if leftType < rightType:
return... | [
"\n Main comparison function for all Firestore types.\n @return -1 is left < right, 0 if left == right, otherwise 1\n "
] |
Please provide a description of the function:def batch_annotate_files(
self,
requests,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
# Wrap the transport method to add retry and timeout logic... | [
"\n Service that performs image detection and annotation for a batch of files.\n Now only \"application/pdf\", \"image/tiff\" and \"image/gif\" are supported.\n\n This service will extract at most the first 10 frames (gif) or pages\n (pdf or tiff) from each file provided and perform dete... |
Please provide a description of the function:def async_batch_annotate_images(
self,
requests,
output_config,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
# Wrap the transport method ... | [
"\n Run asynchronous image detection and annotation for a list of images.\n\n Progress and results can be retrieved through the\n ``google.longrunning.Operations`` interface. ``Operation.metadata``\n contains ``OperationMetadata`` (metadata). ``Operation.response``\n contains ``As... |
Please provide a description of the function:def async_batch_annotate_files(
self,
requests,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
# Wrap the transport method to add retry and timeout... | [
"\n Run asynchronous image detection and annotation for a list of generic\n files, such as PDF files, which may contain multiple pages and multiple\n images per page. Progress and results can be retrieved through the\n ``google.longrunning.Operations`` interface. ``Operation.metadata``\n... |
Please provide a description of the function:def load_ipython_extension(ipython):
from google.cloud.bigquery.magics import _cell_magic
ipython.register_magic_function(
_cell_magic, magic_kind="cell", magic_name="bigquery"
) | [
"Called by IPython when this module is loaded as an IPython extension."
] |
Please provide a description of the function:def from_http_status(status_code, message, **kwargs):
error_class = exception_class_for_http_status(status_code)
error = error_class(message, **kwargs)
if error.code is None:
error.code = status_code
return error | [
"Create a :class:`GoogleAPICallError` from an HTTP status code.\n\n Args:\n status_code (int): The HTTP status code.\n message (str): The exception message.\n kwargs: Additional arguments passed to the :class:`GoogleAPICallError`\n constructor.\n\n Returns:\n GoogleAPICa... |
Please provide a description of the function:def from_http_response(response):
try:
payload = response.json()
except ValueError:
payload = {"error": {"message": response.text or "unknown error"}}
error_message = payload.get("error", {}).get("message", "unknown error")
errors = payl... | [
"Create a :class:`GoogleAPICallError` from a :class:`requests.Response`.\n\n Args:\n response (requests.Response): The HTTP response.\n\n Returns:\n GoogleAPICallError: An instance of the appropriate subclass of\n :class:`GoogleAPICallError`, with the message and errors populated\n ... |
Please provide a description of the function:def from_grpc_status(status_code, message, **kwargs):
error_class = exception_class_for_grpc_status(status_code)
error = error_class(message, **kwargs)
if error.grpc_status_code is None:
error.grpc_status_code = status_code
return error | [
"Create a :class:`GoogleAPICallError` from a :class:`grpc.StatusCode`.\n\n Args:\n status_code (grpc.StatusCode): The gRPC status code.\n message (str): The exception message.\n kwargs: Additional arguments passed to the :class:`GoogleAPICallError`\n constructor.\n\n Returns:\n... |
Please provide a description of the function:def from_grpc_error(rpc_exc):
if isinstance(rpc_exc, grpc.Call):
return from_grpc_status(
rpc_exc.code(), rpc_exc.details(), errors=(rpc_exc,), response=rpc_exc
)
else:
return GoogleAPICallError(str(rpc_exc), errors=(rpc_exc,)... | [
"Create a :class:`GoogleAPICallError` from a :class:`grpc.RpcError`.\n\n Args:\n rpc_exc (grpc.RpcError): The gRPC error.\n\n Returns:\n GoogleAPICallError: An instance of the appropriate subclass of\n :class:`GoogleAPICallError`.\n "
] |
Please provide a description of the function:def _request(http, project, method, data, base_url):
headers = {
"Content-Type": "application/x-protobuf",
"User-Agent": connection_module.DEFAULT_USER_AGENT,
connection_module.CLIENT_INFO_HEADER: _CLIENT_INFO,
}
api_url = build_api_u... | [
"Make a request over the Http transport to the Cloud Datastore API.\n\n :type http: :class:`requests.Session`\n :param http: HTTP object to make requests.\n\n :type project: str\n :param project: The project to make the request for.\n\n :type method: str\n :param method: The API call method name (... |
Please provide a description of the function:def _rpc(http, project, method, base_url, request_pb, response_pb_cls):
req_data = request_pb.SerializeToString()
response = _request(http, project, method, req_data, base_url)
return response_pb_cls.FromString(response) | [
"Make a protobuf RPC request.\n\n :type http: :class:`requests.Session`\n :param http: HTTP object to make requests.\n\n :type project: str\n :param project: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type method: str\n :param metho... |
Please provide a description of the function:def build_api_url(project, method, base_url):
return API_URL_TEMPLATE.format(
api_base=base_url, api_version=API_VERSION, project=project, method=method
) | [
"Construct the URL for a particular API call.\n\n This method is used internally to come up with the URL to use when\n making RPCs to the Cloud Datastore API.\n\n :type project: str\n :param project: The project to connect to. This is\n usually your project name in the cloud console.\... |
Please provide a description of the function:def lookup(self, project_id, keys, read_options=None):
request_pb = _datastore_pb2.LookupRequest(
project_id=project_id, read_options=read_options, keys=keys
)
return _rpc(
self.client._http,
project_id,
... | [
"Perform a ``lookup`` request.\n\n :type project_id: str\n :param project_id: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type keys: List[.entity_pb2.Key]\n :param keys: The keys to retrieve from the datastore.\n\n ... |
Please provide a description of the function:def run_query(
self, project_id, partition_id, read_options=None, query=None, gql_query=None
):
request_pb = _datastore_pb2.RunQueryRequest(
project_id=project_id,
partition_id=partition_id,
read_options=read_o... | [
"Perform a ``runQuery`` request.\n\n :type project_id: str\n :param project_id: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type partition_id: :class:`.entity_pb2.PartitionId`\n :param partition_id: Partition ID corr... |
Please provide a description of the function:def begin_transaction(self, project_id, transaction_options=None):
request_pb = _datastore_pb2.BeginTransactionRequest()
return _rpc(
self.client._http,
project_id,
"beginTransaction",
self.client._base... | [
"Perform a ``beginTransaction`` request.\n\n :type project_id: str\n :param project_id: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type transaction_options: ~.datastore_v1.types.TransactionOptions\n :param transacti... |
Please provide a description of the function:def commit(self, project_id, mode, mutations, transaction=None):
request_pb = _datastore_pb2.CommitRequest(
project_id=project_id,
mode=mode,
transaction=transaction,
mutations=mutations,
)
retu... | [
"Perform a ``commit`` request.\n\n :type project_id: str\n :param project_id: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type mode: :class:`.gapic.datastore.v1.enums.CommitRequest.Mode`\n :param mode: The type of co... |
Please provide a description of the function:def rollback(self, project_id, transaction):
request_pb = _datastore_pb2.RollbackRequest(
project_id=project_id, transaction=transaction
)
# Response is empty (i.e. no fields) but we return it anyway.
return _rpc(
... | [
"Perform a ``rollback`` request.\n\n :type project_id: str\n :param project_id: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type transaction: bytes\n :param transaction: The transaction ID to rollback.\n\n :rt... |
Please provide a description of the function:def allocate_ids(self, project_id, keys):
request_pb = _datastore_pb2.AllocateIdsRequest(keys=keys)
return _rpc(
self.client._http,
project_id,
"allocateIds",
self.client._base_url,
request_... | [
"Perform an ``allocateIds`` request.\n\n :type project_id: str\n :param project_id: The project to connect to. This is\n usually your project name in the cloud console.\n\n :type keys: List[.entity_pb2.Key]\n :param keys: The keys for which the backend should al... |
Please provide a description of the function:def _create_row_request(
table_name,
start_key=None,
end_key=None,
filter_=None,
limit=None,
end_inclusive=False,
app_profile_id=None,
row_set=None,
):
request_kwargs = {"table_name": table_name}
if (start_key is not None or end_k... | [
"Creates a request to read rows in a table.\n\n :type table_name: str\n :param table_name: The name of the table to read from.\n\n :type start_key: bytes\n :param start_key: (Optional) The beginning of a range of row keys to\n read from. The range will include ``start_key``. If\n ... |
Please provide a description of the function:def _mutate_rows_request(table_name, rows, app_profile_id=None):
request_pb = data_messages_v2_pb2.MutateRowsRequest(
table_name=table_name, app_profile_id=app_profile_id
)
mutations_count = 0
for row in rows:
_check_row_table_name(table_... | [
"Creates a request to mutate rows in a table.\n\n :type table_name: str\n :param table_name: The name of the table to write to.\n\n :type rows: list\n :param rows: List or other iterable of :class:`.DirectRow` instances.\n\n :type: app_profile_id: str\n :param app_profile_id: (Optional) The unique... |
Please provide a description of the function:def _check_row_table_name(table_name, row):
if row.table is not None and row.table.name != table_name:
raise TableMismatchError(
"Row %s is a part of %s table. Current table: %s"
% (row.row_key, row.table.name, table_name)
) | [
"Checks that a row belongs to a table.\n\n :type table_name: str\n :param table_name: The name of the table.\n\n :type row: :class:`~google.cloud.bigtable.row.Row`\n :param row: An instance of :class:`~google.cloud.bigtable.row.Row`\n subclasses.\n\n :raises: :exc:`~.table.TableMismatc... |
Please provide a description of the function:def name(self):
project = self._instance._client.project
instance_id = self._instance.instance_id
table_client = self._instance._client.table_data_client
return table_client.table_path(
project=project, instance=instance_i... | [
"Table name used in requests.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_table_name]\n :end-before: [END bigtable_table_name]\n\n .. note::\n\n This property will not change if ``table_id`` does not, but the\n ... |
Please provide a description of the function:def row(self, row_key, filter_=None, append=False):
if append and filter_ is not None:
raise ValueError("At most one of filter_ and append can be set")
if append:
return AppendRow(row_key, self)
elif filter_ is not Non... | [
"Factory to create a row associated with this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_table_row]\n :end-before: [END bigtable_table_row]\n\n .. warning::\n\n At most one of ``filter_`` and ``append`` can b... |
Please provide a description of the function:def create(self, initial_split_keys=[], column_families={}):
table_client = self._instance._client.table_admin_client
instance_name = self._instance.name
families = {
id: ColumnFamily(id, self, rule).to_pb()
for (id, ... | [
"Creates this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_create_table]\n :end-before: [END bigtable_create_table]\n\n .. note::\n\n A create request returns a\n :class:`._generated.table_pb2.Table... |
Please provide a description of the function:def exists(self):
table_client = self._instance._client.table_admin_client
try:
table_client.get_table(name=self.name, view=VIEW_NAME_ONLY)
return True
except NotFound:
return False | [
"Check whether the table exists.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_check_table_exists]\n :end-before: [END bigtable_check_table_exists]\n\n :rtype: bool\n :returns: True if the table exists, else False.\n ... |
Please provide a description of the function:def delete(self):
table_client = self._instance._client.table_admin_client
table_client.delete_table(name=self.name) | [
"Delete this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_delete_table]\n :end-before: [END bigtable_delete_table]\n\n "
] |
Please provide a description of the function:def list_column_families(self):
table_client = self._instance._client.table_admin_client
table_pb = table_client.get_table(self.name)
result = {}
for column_family_id, value_pb in table_pb.column_families.items():
gc_rule... | [
"List the column families owned by this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_list_column_families]\n :end-before: [END bigtable_list_column_families]\n\n :rtype: dict\n :returns: Dictionary of column famil... |
Please provide a description of the function:def get_cluster_states(self):
REPLICATION_VIEW = enums.Table.View.REPLICATION_VIEW
table_client = self._instance._client.table_admin_client
table_pb = table_client.get_table(self.name, view=REPLICATION_VIEW)
return {
clu... | [
"List the cluster states owned by this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_get_cluster_states]\n :end-before: [END bigtable_get_cluster_states]\n\n :rtype: dict\n :returns: Dictionary of cluster states fo... |
Please provide a description of the function:def read_row(self, row_key, filter_=None):
row_set = RowSet()
row_set.add_row_key(row_key)
result_iter = iter(self.read_rows(filter_=filter_, row_set=row_set))
row = next(result_iter, None)
if next(result_iter, None) is not No... | [
"Read a single row from this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_read_row]\n :end-before: [END bigtable_read_row]\n\n :type row_key: bytes\n :param row_key: The key of the row to read from.\n\n :ty... |
Please provide a description of the function:def read_rows(
self,
start_key=None,
end_key=None,
limit=None,
filter_=None,
end_inclusive=False,
row_set=None,
retry=DEFAULT_RETRY_READ_ROWS,
):
request_pb = _create_row_request(
... | [
"Read rows from this table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_read_rows]\n :end-before: [END bigtable_read_rows]\n\n :type start_key: bytes\n :param start_key: (Optional) The beginning of a range of row keys t... |
Please provide a description of the function:def yield_rows(self, **kwargs):
warnings.warn(
"`yield_rows()` is depricated; use `red_rows()` instead",
DeprecationWarning,
stacklevel=2,
)
return self.read_rows(**kwargs) | [
"Read rows from this table.\n\n .. warning::\n This method will be removed in future releases. Please use\n ``read_rows`` instead.\n\n :type start_key: bytes\n :param start_key: (Optional) The beginning of a range of row keys to\n read from. The ran... |
Please provide a description of the function:def mutate_rows(self, rows, retry=DEFAULT_RETRY):
retryable_mutate_rows = _RetryableMutateRowsWorker(
self._instance._client,
self.name,
rows,
app_profile_id=self._app_profile_id,
timeout=self.mutat... | [
"Mutates multiple rows in bulk.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_mutate_rows]\n :end-before: [END bigtable_mutate_rows]\n\n The method tries to update all specified rows.\n If some of the rows weren't updated... |
Please provide a description of the function:def sample_row_keys(self):
data_client = self._instance._client.table_data_client
response_iterator = data_client.sample_row_keys(
self.name, app_profile_id=self._app_profile_id
)
return response_iterator | [
"Read a sample of row keys in the table.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_sample_row_keys]\n :end-before: [END bigtable_sample_row_keys]\n\n The returned row keys will delimit contiguous sections of the table of\n ... |
Please provide a description of the function:def truncate(self, timeout=None):
client = self._instance._client
table_admin_client = client.table_admin_client
if timeout:
table_admin_client.drop_row_range(
self.name, delete_all_data_from_table=True, timeout=ti... | [
"Truncate the table\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_truncate_table]\n :end-before: [END bigtable_truncate_table]\n\n :type timeout: float\n :param timeout: (Optional) The amount of time, in seconds, to wait\... |
Please provide a description of the function:def mutations_batcher(self, flush_count=FLUSH_COUNT, max_row_bytes=MAX_ROW_BYTES):
return MutationsBatcher(self, flush_count, max_row_bytes) | [
"Factory to create a mutation batcher associated with this instance.\n\n For example:\n\n .. literalinclude:: snippets_table.py\n :start-after: [START bigtable_mutations_batcher]\n :end-before: [END bigtable_mutations_batcher]\n\n :type table: class\n :param table: ... |
Please provide a description of the function:def _do_mutate_retryable_rows(self):
retryable_rows = []
index_into_all_rows = []
for index, status in enumerate(self.responses_statuses):
if self._is_retryable(status):
retryable_rows.append(self.rows[index])
... | [
"Mutate all the rows that are eligible for retry.\n\n A row is eligible for retry if it has not been tried or if it resulted\n in a transient error in a previous call.\n\n :rtype: list\n :return: The responses statuses, which is a list of\n :class:`~google.rpc.status_pb2.... |
Please provide a description of the function:def heartbeat(self):
while self._manager.is_active and not self._stop_event.is_set():
self._manager.heartbeat()
_LOGGER.debug("Sent heartbeat.")
self._stop_event.wait(timeout=self._period)
_LOGGER.info("%s exiting... | [
"Periodically send heartbeats."
] |
Please provide a description of the function:def report_error_event(
self,
project_name,
event,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
# Wrap the transport method to add retry ... | [
"\n Report an individual error event.\n\n Example:\n >>> from google.cloud import errorreporting_v1beta1\n >>>\n >>> client = errorreporting_v1beta1.ReportErrorsServiceClient()\n >>>\n >>> project_name = client.project_path('[PROJECT]')\n ... |
Please provide a description of the function:def scalar_to_query_parameter(value, name=None):
parameter_type = None
if isinstance(value, bool):
parameter_type = "BOOL"
elif isinstance(value, numbers.Integral):
parameter_type = "INT64"
elif isinstance(value, numbers.Real):
p... | [
"Convert a scalar value into a query parameter.\n\n :type value: any\n :param value: A scalar value to convert into a query parameter.\n\n :type name: str\n :param name: (Optional) Name of the query parameter.\n\n :rtype: :class:`~google.cloud.bigquery.ScalarQueryParameter`\n :returns:\n A ... |
Please provide a description of the function:def to_query_parameters_dict(parameters):
return [
scalar_to_query_parameter(value, name=name)
for name, value in six.iteritems(parameters)
] | [
"Converts a dictionary of parameter values into query parameters.\n\n :type parameters: Mapping[str, Any]\n :param parameters: Dictionary of query parameter values.\n\n :rtype: List[google.cloud.bigquery.query._AbstractQueryParameter]\n :returns: A list of named query parameters.\n "
] |
Please provide a description of the function:def to_query_parameters(parameters):
if parameters is None:
return []
if isinstance(parameters, collections_abc.Mapping):
return to_query_parameters_dict(parameters)
return to_query_parameters_list(parameters) | [
"Converts DB-API parameter values into query parameters.\n\n :type parameters: Mapping[str, Any] or Sequence[Any]\n :param parameters: A dictionary or sequence of query parameter values.\n\n :rtype: List[google.cloud.bigquery.query._AbstractQueryParameter]\n :returns: A list of query parameters.\n "
... |
Please provide a description of the function:def _refresh_http(api_request, operation_name):
path = "operations/{}".format(operation_name)
api_response = api_request(method="GET", path=path)
return json_format.ParseDict(api_response, operations_pb2.Operation()) | [
"Refresh an operation using a JSON/HTTP client.\n\n Args:\n api_request (Callable): A callable used to make an API request. This\n should generally be\n :meth:`google.cloud._http.Connection.api_request`.\n operation_name (str): The name of the operation.\n\n Returns:\n ... |
Please provide a description of the function:def _cancel_http(api_request, operation_name):
path = "operations/{}:cancel".format(operation_name)
api_request(method="POST", path=path) | [
"Cancel an operation using a JSON/HTTP client.\n\n Args:\n api_request (Callable): A callable used to make an API request. This\n should generally be\n :meth:`google.cloud._http.Connection.api_request`.\n operation_name (str): The name of the operation.\n "
] |
Please provide a description of the function:def from_http_json(operation, api_request, result_type, **kwargs):
operation_proto = json_format.ParseDict(operation, operations_pb2.Operation())
refresh = functools.partial(_refresh_http, api_request, operation_proto.name)
cancel = functools.partial(_cancel... | [
"Create an operation future using a HTTP/JSON client.\n\n This interacts with the long-running operations `service`_ (specific\n to a given API) via `HTTP/JSON`_.\n\n .. _HTTP/JSON: https://cloud.google.com/speech/reference/rest/\\\n v1beta1/operations#Operation\n\n Args:\n operation (... |
Please provide a description of the function:def _refresh_grpc(operations_stub, operation_name):
request_pb = operations_pb2.GetOperationRequest(name=operation_name)
return operations_stub.GetOperation(request_pb) | [
"Refresh an operation using a gRPC client.\n\n Args:\n operations_stub (google.longrunning.operations_pb2.OperationsStub):\n The gRPC operations stub.\n operation_name (str): The name of the operation.\n\n Returns:\n google.longrunning.operations_pb2.Operation: The operation.\n... |
Please provide a description of the function:def _cancel_grpc(operations_stub, operation_name):
request_pb = operations_pb2.CancelOperationRequest(name=operation_name)
operations_stub.CancelOperation(request_pb) | [
"Cancel an operation using a gRPC client.\n\n Args:\n operations_stub (google.longrunning.operations_pb2.OperationsStub):\n The gRPC operations stub.\n operation_name (str): The name of the operation.\n "
] |
Please provide a description of the function:def from_grpc(operation, operations_stub, result_type, **kwargs):
refresh = functools.partial(_refresh_grpc, operations_stub, operation.name)
cancel = functools.partial(_cancel_grpc, operations_stub, operation.name)
return Operation(operation, refresh, cance... | [
"Create an operation future using a gRPC client.\n\n This interacts with the long-running operations `service`_ (specific\n to a given API) via gRPC.\n\n .. _service: https://github.com/googleapis/googleapis/blob/\\\n 050400df0fdb16f63b63e9dee53819044bffc857/\\\n google/long... |
Please provide a description of the function:def from_gapic(operation, operations_client, result_type, **kwargs):
refresh = functools.partial(operations_client.get_operation, operation.name)
cancel = functools.partial(operations_client.cancel_operation, operation.name)
return Operation(operation, refre... | [
"Create an operation future from a gapic client.\n\n This interacts with the long-running operations `service`_ (specific\n to a given API) via a gapic client.\n\n .. _service: https://github.com/googleapis/googleapis/blob/\\\n 050400df0fdb16f63b63e9dee53819044bffc857/\\\n g... |
Please provide a description of the function:def metadata(self):
if not self._operation.HasField("metadata"):
return None
return protobuf_helpers.from_any_pb(
self._metadata_type, self._operation.metadata
) | [
"google.protobuf.Message: the current operation metadata."
] |
Please provide a description of the function:def _set_result_from_operation(self):
# This must be done in a lock to prevent the polling thread
# and main thread from both executing the completion logic
# at the same time.
with self._completion_lock:
# If the operatio... | [
"Set the result or exception from the operation if it is complete."
] |
Please provide a description of the function:def _refresh_and_update(self):
# If the currently cached operation is done, no need to make another
# RPC as it will not change once done.
if not self._operation.done:
self._operation = self._refresh()
self._set_result... | [
"Refresh the operation and update the result if needed."
] |
Please provide a description of the function:def cancelled(self):
self._refresh_and_update()
return (
self._operation.HasField("error")
and self._operation.error.code == code_pb2.CANCELLED
) | [
"True if the operation was cancelled."
] |
Please provide a description of the function:def revoke(self, role):
if role in self.roles:
self.roles.remove(role) | [
"Remove a role from the entity.\n\n :type role: str\n :param role: The role to remove from the entity.\n "
] |
Please provide a description of the function:def validate_predefined(cls, predefined):
predefined = cls.PREDEFINED_XML_ACLS.get(predefined, predefined)
if predefined and predefined not in cls.PREDEFINED_JSON_ACLS:
raise ValueError("Invalid predefined ACL: %s" % (predefined,))
... | [
"Ensures predefined is in list of predefined json values\n\n :type predefined: str\n :param predefined: name of a predefined acl\n\n :type predefined: str\n :param predefined: validated JSON name of predefined acl\n\n :raises: :exc: `ValueError`: If predefined is not a valid acl\n... |
Please provide a description of the function:def entity_from_dict(self, entity_dict):
entity = entity_dict["entity"]
role = entity_dict["role"]
if entity == "allUsers":
entity = self.all()
elif entity == "allAuthenticatedUsers":
entity = self.all_authen... | [
"Build an _ACLEntity object from a dictionary of data.\n\n An entity is a mutable object that represents a list of roles\n belonging to either a user or group or the special types for all\n users and all authenticated users.\n\n :type entity_dict: dict\n :param entity_dict: Dictio... |
Please provide a description of the function:def get_entity(self, entity, default=None):
self._ensure_loaded()
return self.entities.get(str(entity), default) | [
"Gets an entity object from the ACL.\n\n :type entity: :class:`_ACLEntity` or string\n :param entity: The entity to get lookup in the ACL.\n\n :type default: anything\n :param default: This value will be returned if the entity\n doesn't exist.\n\n :rtype: :c... |
Please provide a description of the function:def add_entity(self, entity):
self._ensure_loaded()
self.entities[str(entity)] = entity | [
"Add an entity to the ACL.\n\n :type entity: :class:`_ACLEntity`\n :param entity: The entity to add to this ACL.\n "
] |
Please provide a description of the function:def entity(self, entity_type, identifier=None):
entity = _ACLEntity(entity_type=entity_type, identifier=identifier)
if self.has_entity(entity):
entity = self.get_entity(entity)
else:
self.add_entity(entity)
ret... | [
"Factory method for creating an Entity.\n\n If an entity with the same type and identifier already exists,\n this will return a reference to that entity. If not, it will\n create a new one and add it to the list of known entities for\n this ACL.\n\n :type entity_type: str\n ... |
Please provide a description of the function:def reload(self, client=None):
path = self.reload_path
client = self._require_client(client)
query_params = {}
if self.user_project is not None:
query_params["userProject"] = self.user_project
self.entities.clear... | [
"Reload the ACL data from Cloud Storage.\n\n If :attr:`user_project` is set, bills the API request to that project.\n\n :type client: :class:`~google.cloud.storage.client.Client` or\n ``NoneType``\n :param client: Optional. The client to use. If not passed, falls back\n ... |
Please provide a description of the function:def _save(self, acl, predefined, client):
query_params = {"projection": "full"}
if predefined is not None:
acl = []
query_params[self._PREDEFINED_QUERY_PARAM] = predefined
if self.user_project is not None:
... | [
"Helper for :meth:`save` and :meth:`save_predefined`.\n\n :type acl: :class:`google.cloud.storage.acl.ACL`, or a compatible list.\n :param acl: The ACL object to save. If left blank, this will save\n current entries.\n\n :type predefined: str\n :param predefined:\n ... |
Please provide a description of the function:def save(self, acl=None, client=None):
if acl is None:
acl = self
save_to_backend = acl.loaded
else:
save_to_backend = True
if save_to_backend:
self._save(acl, None, client) | [
"Save this ACL for the current bucket.\n\n If :attr:`user_project` is set, bills the API request to that project.\n\n :type acl: :class:`google.cloud.storage.acl.ACL`, or a compatible list.\n :param acl: The ACL object to save. If left blank, this will save\n current entries... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.