partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | BigtableClient.mutate_rows | Mutates multiple rows in a batch. Each individual row is mutated
atomically as in MutateRow, but the entire batch is not executed
atomically.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
... | bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py | def mutate_rows(
self,
table_name,
entries,
app_profile_id=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Mutates multiple rows in a batch. Each individual row is muta... | def mutate_rows(
self,
table_name,
entries,
app_profile_id=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
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train | BigtableClient.check_and_mutate_row | Mutates a row atomically based on the output of a predicate Reader filter.
Example:
>>> from google.cloud import bigtable_v2
>>>
>>> client = bigtable_v2.BigtableClient()
>>>
>>> table_name = client.table_path('[PROJECT]', '[INSTANCE]', '[TABLE]')
... | bigtable/google/cloud/bigtable_v2/gapic/bigtable_client.py | def check_and_mutate_row(
self,
table_name,
row_key,
app_profile_id=None,
predicate_filter=None,
true_mutations=None,
false_mutations=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
meta... | def check_and_mutate_row(
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app_profile_id=None,
predicate_filter=None,
true_mutations=None,
false_mutations=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
meta... | [
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train | Instance._update_from_pb | Refresh self from the server-provided protobuf.
Helper for :meth:`from_pb` and :meth:`reload`. | bigtable/google/cloud/bigtable/instance.py | def _update_from_pb(self, instance_pb):
"""Refresh self from the server-provided protobuf.
Helper for :meth:`from_pb` and :meth:`reload`.
"""
if not instance_pb.display_name: # Simple field (string)
raise ValueError("Instance protobuf does not contain display_name")
... | def _update_from_pb(self, instance_pb):
"""Refresh self from the server-provided protobuf.
Helper for :meth:`from_pb` and :meth:`reload`.
"""
if not instance_pb.display_name: # Simple field (string)
raise ValueError("Instance protobuf does not contain display_name")
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train | Instance.name | Instance name used in requests.
.. note::
This property will not change if ``instance_id`` does not,
but the return value is not cached.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_instance_name]
:end-before: [END bigt... | bigtable/google/cloud/bigtable/instance.py | def name(self):
"""Instance name used in requests.
.. note::
This property will not change if ``instance_id`` does not,
but the return value is not cached.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_instance_name]
... | def name(self):
"""Instance name used in requests.
.. note::
This property will not change if ``instance_id`` does not,
but the return value is not cached.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_instance_name]
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train | Instance.create | Create this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_prod_instance]
:end-before: [END bigtable_create_prod_instance]
.. note::
Uses the ``project`` and ``instance_id`` on the current
:class:`In... | bigtable/google/cloud/bigtable/instance.py | def create(
self,
location_id=None,
serve_nodes=None,
default_storage_type=None,
clusters=None,
):
"""Create this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_prod_instance]
:end-... | def create(
self,
location_id=None,
serve_nodes=None,
default_storage_type=None,
clusters=None,
):
"""Create this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_prod_instance]
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train | Instance.exists | Check whether the instance already exists.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_check_instance_exists]
:end-before: [END bigtable_check_instance_exists]
:rtype: bool
:returns: True if the table exists, else False. | bigtable/google/cloud/bigtable/instance.py | def exists(self):
"""Check whether the instance already exists.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_check_instance_exists]
:end-before: [END bigtable_check_instance_exists]
:rtype: bool
:returns: True if the table ... | def exists(self):
"""Check whether the instance already exists.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_check_instance_exists]
:end-before: [END bigtable_check_instance_exists]
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train | Instance.reload | Reload the metadata for this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_reload_instance]
:end-before: [END bigtable_reload_instance] | bigtable/google/cloud/bigtable/instance.py | def reload(self):
"""Reload the metadata for this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_reload_instance]
:end-before: [END bigtable_reload_instance]
"""
instance_pb = self._client.instance_admin_client.get_i... | def reload(self):
"""Reload the metadata for this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_reload_instance]
:end-before: [END bigtable_reload_instance]
"""
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train | Instance.update | Updates an instance within a project.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_update_instance]
:end-before: [END bigtable_update_instance]
.. note::
Updates any or all of the following values:
``display_name``... | bigtable/google/cloud/bigtable/instance.py | def update(self):
"""Updates an instance within a project.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_update_instance]
:end-before: [END bigtable_update_instance]
.. note::
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For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_update_instance]
:end-before: [END bigtable_update_instance]
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train | Instance.get_iam_policy | Gets the access control policy for an instance resource.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_get_iam_policy]
:end-before: [END bigtable_get_iam_policy]
:rtype: :class:`google.cloud.bigtable.policy.Policy`
:returns: The cur... | bigtable/google/cloud/bigtable/instance.py | def get_iam_policy(self):
"""Gets the access control policy for an instance resource.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_get_iam_policy]
:end-before: [END bigtable_get_iam_policy]
:rtype: :class:`google.cloud.bigtable.pol... | def get_iam_policy(self):
"""Gets the access control policy for an instance resource.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_get_iam_policy]
:end-before: [END bigtable_get_iam_policy]
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train | Instance.set_iam_policy | Sets the access control policy on an instance resource. Replaces any
existing policy.
For more information about policy, please see documentation of
class `google.cloud.bigtable.policy.Policy`
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtab... | bigtable/google/cloud/bigtable/instance.py | def set_iam_policy(self, policy):
"""Sets the access control policy on an instance resource. Replaces any
existing policy.
For more information about policy, please see documentation of
class `google.cloud.bigtable.policy.Policy`
For example:
.. literalinclude:: snippe... | def set_iam_policy(self, policy):
"""Sets the access control policy on an instance resource. Replaces any
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For more information about policy, please see documentation of
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train | Instance.cluster | Factory to create a cluster associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_cluster]
:end-before: [END bigtable_create_cluster]
:type cluster_id: str
:param cluster_id: The ID of the cluster.
... | bigtable/google/cloud/bigtable/instance.py | def cluster(
self, cluster_id, location_id=None, serve_nodes=None, default_storage_type=None
):
"""Factory to create a cluster associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_cluster]
:end-befo... | def cluster(
self, cluster_id, location_id=None, serve_nodes=None, default_storage_type=None
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.. literalinclude:: snippets.py
:start-after: [START bigtable_create_cluster]
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train | Instance.list_clusters | List the clusters in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_clusters_on_instance]
:end-before: [END bigtable_list_clusters_on_instance]
:rtype: tuple
:returns:
(clusters, failed_locations), whe... | bigtable/google/cloud/bigtable/instance.py | def list_clusters(self):
"""List the clusters in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_clusters_on_instance]
:end-before: [END bigtable_list_clusters_on_instance]
:rtype: tuple
:returns:
... | def list_clusters(self):
"""List the clusters in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_clusters_on_instance]
:end-before: [END bigtable_list_clusters_on_instance]
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train | Instance.table | Factory to create a table associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_table]
:end-before: [END bigtable_create_table]
:type table_id: str
:param table_id: The ID of the table.
:type a... | bigtable/google/cloud/bigtable/instance.py | def table(self, table_id, mutation_timeout=None, app_profile_id=None):
"""Factory to create a table associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_table]
:end-before: [END bigtable_create_table]
... | def table(self, table_id, mutation_timeout=None, app_profile_id=None):
"""Factory to create a table associated with this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_create_table]
:end-before: [END bigtable_create_table]
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train | Instance.list_tables | List the tables in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_tables]
:end-before: [END bigtable_list_tables]
:rtype: list of :class:`Table <google.cloud.bigtable.table.Table>`
:returns: The list of tables own... | bigtable/google/cloud/bigtable/instance.py | def list_tables(self):
"""List the tables in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_tables]
:end-before: [END bigtable_list_tables]
:rtype: list of :class:`Table <google.cloud.bigtable.table.Table>`
... | def list_tables(self):
"""List the tables in this instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_tables]
:end-before: [END bigtable_list_tables]
:rtype: list of :class:`Table <google.cloud.bigtable.table.Table>`
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train | Instance.app_profile | Factory to create AppProfile associated with this instance.
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:start-after: [START bigtable_create_app_profile]
:end-before: [END bigtable_create_app_profile]
:type app_profile_id: str
:param app_profile_id: The ID of ... | bigtable/google/cloud/bigtable/instance.py | def app_profile(
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"""Factory to create AppProfile associated with this instance.
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):
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train | Instance.list_app_profiles | Lists information about AppProfiles in an instance.
For example:
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:start-after: [START bigtable_list_app_profiles]
:end-before: [END bigtable_list_app_profiles]
:rtype: :list:[`~google.cloud.bigtable.app_profile.AppProfile`]
:retu... | bigtable/google/cloud/bigtable/instance.py | def list_app_profiles(self):
"""Lists information about AppProfiles in an instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_app_profiles]
:end-before: [END bigtable_list_app_profiles]
:rtype: :list:[`~google.cloud.bigtabl... | def list_app_profiles(self):
"""Lists information about AppProfiles in an instance.
For example:
.. literalinclude:: snippets.py
:start-after: [START bigtable_list_app_profiles]
:end-before: [END bigtable_list_app_profiles]
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train | system | Run the system test suite. | bigtable/noxfile.py | def system(session):
"""Run the system test suite."""
system_test_path = os.path.join("tests", "system.py")
system_test_folder_path = os.path.join("tests", "system")
# Sanity check: Only run tests if the environment variable is set.
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS", ""):
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"""Run the system test suite."""
system_test_path = os.path.join("tests", "system.py")
system_test_folder_path = os.path.join("tests", "system")
# Sanity check: Only run tests if the environment variable is set.
if not os.environ.get("GOOGLE_APPLICATION_CREDENTIALS", ""):
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train | _reference_getter | A :class:`~google.cloud.bigquery.table.TableReference` pointing to
this table.
Returns:
google.cloud.bigquery.table.TableReference: pointer to this table. | bigquery/google/cloud/bigquery/table.py | def _reference_getter(table):
"""A :class:`~google.cloud.bigquery.table.TableReference` pointing to
this table.
Returns:
google.cloud.bigquery.table.TableReference: pointer to this table.
"""
from google.cloud.bigquery import dataset
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train | _view_use_legacy_sql_getter | bool: Specifies whether to execute the view with Legacy or Standard SQL.
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train | _row_from_mapping | Convert a mapping to a row tuple using the schema.
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Mapping of row data: must contain keys for all required fields in
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schema (List[google.cloud.bigquer... | bigquery/google/cloud/bigquery/table.py | def _row_from_mapping(mapping, schema):
"""Convert a mapping to a row tuple using the schema.
Args:
mapping (Dict[str, object])
Mapping of row data: must contain keys for all required fields in
the schema. Keys which do not correspond to a field in the schema
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train | _item_to_row | Convert a JSON row to the native object.
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:type iterator: :class:`~google.api_core.page_iterator.Iterator`
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.. note::
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:type iterator: :class:`~google.api_core.page_iterator.Ite... | def _item_to_row(iterator, resource):
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train | _rows_page_start | Grab total rows when :class:`~google.cloud.iterator.Page` starts.
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:param iterator: The iterator that is currently in use.
:type page: :class:`~google.api_core.page_iterator.Page`
:param page: The page that was just created.
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:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that is currently in use.
:type page: :class:`~google.api_core.page_iterator.Page`
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train | _table_arg_to_table_ref | Helper to convert a string or Table to TableReference.
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"""Helper to convert a string or Table to TableReference.
This function keeps TableReference and other kinds of objects unchanged.
"""
if isinstance(value, six.string_types):
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"""Helper to convert a string or Table to TableReference.
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train | _table_arg_to_table | Helper to convert a string or TableReference to a Table.
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"""Helper to convert a string or TableReference to a Table.
This function keeps Table and other kinds of objects unchanged.
"""
if isinstance(value, six.string_types):
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train | TableReference.from_string | Construct a table reference from table ID string.
Args:
table_id (str):
A table ID in standard SQL format. If ``default_project``
is not specified, this must included a project ID, dataset
ID, and table ID, each separated by ``.``.
default... | bigquery/google/cloud/bigquery/table.py | def from_string(cls, table_id, default_project=None):
"""Construct a table reference from table ID string.
Args:
table_id (str):
A table ID in standard SQL format. If ``default_project``
is not specified, this must included a project ID, dataset
... | def from_string(cls, table_id, default_project=None):
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table_id (str):
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train | TableReference.from_api_repr | Factory: construct a table reference given its API representation
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resource (Dict[str, object]):
Table reference representation returned from the API
Returns:
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"""Factory: construct a table reference given its API representation
Args:
resource (Dict[str, object]):
Table reference representation returned from the API
Returns:
google.cloud.bigquery.table.TableReference:
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resource (Dict[str, object]):
Table reference representation returned from the API
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train | TableReference.to_bqstorage | Construct a BigQuery Storage API representation of this table.
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If the ``table_id`` contains a partition identifier (e.g.
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"""Construct a BigQuery Storage API representation of this table.
Install the ``google-cloud-bigquery-storage`` package to use this
feature.
If the ``table_id`` contains a partition identifier (e.g.
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Install the ``google-cloud-bigquery-storage`` package to use this
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train | Table.encryption_configuration | google.cloud.bigquery.table.EncryptionConfiguration: Custom
encryption configuration for the table.
Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
if using default encryption.
See `protecting data with Cloud KMS keys
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encryption configuration for the table.
Custom encryption configuration (e.g., Cloud KMS keys) or :data:`None`
if using default encryption.
See `protecting data with Cloud KMS key... | def encryption_configuration(self):
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train | Table.time_partitioning | google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
Raises:
ValueError:
If the value is not :class:`TimePartitioning` or :data:`None`. | bigquery/google/cloud/bigquery/table.py | def time_partitioning(self):
"""google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
Raises:
ValueError:
If the value is not :class:`TimePartitioning` or :data:`None`.
"""
prop = self._properties.get("timeParti... | def time_partitioning(self):
"""google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
Raises:
ValueError:
If the value is not :class:`TimePartitioning` or :data:`None`.
"""
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train | Table.partition_expiration | Union[int, None]: Expiration time in milliseconds for a partition.
If :attr:`partition_expiration` is set and :attr:`type_` is
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:attr:`~google.cloud.bigquery.table.TimePartitioningType.DAY`. | bigquery/google/cloud/bigquery/table.py | def partition_expiration(self):
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"""
war... | def partition_expiration(self):
"""Union[int, None]: Expiration time in milliseconds for a partition.
If :attr:`partition_expiration` is set and :attr:`type_` is
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train | Table.clustering_fields | Union[List[str], None]: Fields defining clustering for the table
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Clustering fields are immutable after table creation.
.. note::
As of 2018-06-29, clustering fields cannot be set on a table
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.. note::
As of 2018-06-29, clustering fields cannot be set on a table
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train | Table.clustering_fields | Union[List[str], None]: Fields defining clustering for the table
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"""Union[List[str], None]: Fields defining clustering for the table
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train | Table.expires | Union[datetime.datetime, None]: Datetime at which the table will be
deleted.
Raises:
ValueError: For invalid value types. | bigquery/google/cloud/bigquery/table.py | def expires(self):
"""Union[datetime.datetime, None]: Datetime at which the table will be
deleted.
Raises:
ValueError: For invalid value types.
"""
expiration_time = self._properties.get("expirationTime")
if expiration_time is not None:
# expirati... | def expires(self):
"""Union[datetime.datetime, None]: Datetime at which the table will be
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train | Table.external_data_configuration | Union[google.cloud.bigquery.ExternalConfig, None]: Configuration for
an external data source (defaults to :data:`None`).
Raises:
ValueError: For invalid value types. | bigquery/google/cloud/bigquery/table.py | def external_data_configuration(self):
"""Union[google.cloud.bigquery.ExternalConfig, None]: Configuration for
an external data source (defaults to :data:`None`).
Raises:
ValueError: For invalid value types.
"""
prop = self._properties.get("externalDataConfiguration"... | def external_data_configuration(self):
"""Union[google.cloud.bigquery.ExternalConfig, None]: Configuration for
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ValueError: For invalid value types.
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train | Table.from_api_repr | Factory: construct a table given its API representation
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resource (Dict[str, object]):
Table resource representation from the API
Returns:
google.cloud.bigquery.table.Table: Table parsed from ``resource``.
Raises:
KeyError:
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"""Factory: construct a table given its API representation
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resource (Dict[str, object]):
Table resource representation from the API
Returns:
google.cloud.bigquery.table.Table: Table parsed from ``resource``.
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Table resource representation from the API
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google.cloud.bigquery.table.Table: Table parsed from ``resource``.
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train | TableListItem.partitioning_type | Union[str, None]: Time partitioning of the table if it is
partitioned (Defaults to :data:`None`). | bigquery/google/cloud/bigquery/table.py | def partitioning_type(self):
"""Union[str, None]: Time partitioning of the table if it is
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train | Row.items | Return items as ``(key, value)`` pairs.
Returns:
Iterable[Tuple[str, object]]:
The ``(key, value)`` pairs representing this row.
Examples:
>>> list(Row(('a', 'b'), {'x': 0, 'y': 1}).items())
[('x', 'a'), ('y', 'b')] | bigquery/google/cloud/bigquery/table.py | def items(self):
"""Return items as ``(key, value)`` pairs.
Returns:
Iterable[Tuple[str, object]]:
The ``(key, value)`` pairs representing this row.
Examples:
>>> list(Row(('a', 'b'), {'x': 0, 'y': 1}).items())
[('x', 'a'), ('y', 'b')]
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train | Row.get | Return a value for key, with a default value if it does not exist.
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train | RowIterator._get_next_page_response | Requests the next page from the path provided.
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Returns:
Dict[str, object]:
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params = self._get_query_params()
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"""Requests the next page from the path provided.
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Dict[str, object]:
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params = self._get_query_params()
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train | RowIterator._to_dataframe_tabledata_list | Use (slower, but free) tabledata.list to construct a DataFrame. | bigquery/google/cloud/bigquery/table.py | def _to_dataframe_tabledata_list(self, dtypes, progress_bar=None):
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column_names = [field.name for field in self.schema]
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train | RowIterator._to_dataframe_bqstorage | Use (faster, but billable) BQ Storage API to construct DataFrame. | bigquery/google/cloud/bigquery/table.py | def _to_dataframe_bqstorage(self, bqstorage_client, dtypes, progress_bar=None):
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train | RowIterator._get_progress_bar | Construct a tqdm progress bar object, if tqdm is installed. | bigquery/google/cloud/bigquery/table.py | def _get_progress_bar(self, progress_bar_type):
"""Construct a tqdm progress bar object, if tqdm is installed."""
if tqdm is None:
if progress_bar_type is not None:
warnings.warn(_NO_TQDM_ERROR, UserWarning, stacklevel=3)
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description = "Downlo... | def _get_progress_bar(self, progress_bar_type):
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train | RowIterator.to_dataframe | Create a pandas DataFrame by loading all pages of a query.
Args:
bqstorage_client ( \
google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient \
):
**Beta Feature** Optional. A BigQuery Storage API client. If
supplied, use the faster Bi... | bigquery/google/cloud/bigquery/table.py | def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=None):
"""Create a pandas DataFrame by loading all pages of a query.
Args:
bqstorage_client ( \
google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient \
):
**Beta Fe... | def to_dataframe(self, bqstorage_client=None, dtypes=None, progress_bar_type=None):
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Args:
bqstorage_client ( \
google.cloud.bigquery_storage_v1beta1.BigQueryStorageClient \
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train | _EmptyRowIterator.to_dataframe | Create an empty dataframe.
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dtypes (Any):
Ignored. Added for compatibility with RowIterator.
progress_bar_type (Any):
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Args:
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Ignored. Added for compatibility with RowIterator.
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train | TimePartitioning.from_api_repr | Return a :class:`TimePartitioning` object deserialized from a dict.
This method creates a new ``TimePartitioning`` instance that points to
the ``api_repr`` parameter as its internal properties dict. This means
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the ``api_repr`` parameter as its internal properties dict. This means
that when a ``TimePartitioning`` instanc... | def from_api_repr(cls, api_repr):
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train | _generate_faux_mime_message | Convert response, content -> (multipart) email.message.
Helper for _unpack_batch_response. | storage/google/cloud/storage/batch.py | def _generate_faux_mime_message(parser, response):
"""Convert response, content -> (multipart) email.message.
Helper for _unpack_batch_response.
"""
# We coerce to bytes to get consistent concat across
# Py2 and Py3. Percent formatting is insufficient since
# it includes the b in Py3.
conte... | def _generate_faux_mime_message(parser, response):
"""Convert response, content -> (multipart) email.message.
Helper for _unpack_batch_response.
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train | _unpack_batch_response | Convert requests.Response -> [(headers, payload)].
Creates a generator of tuples of emulating the responses to
:meth:`requests.Session.request`.
:type response: :class:`requests.Response`
:param response: HTTP response / headers from a request. | storage/google/cloud/storage/batch.py | def _unpack_batch_response(response):
"""Convert requests.Response -> [(headers, payload)].
Creates a generator of tuples of emulating the responses to
:meth:`requests.Session.request`.
:type response: :class:`requests.Response`
:param response: HTTP response / headers from a request.
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:type response: :class:`requests.Response`
:param response: HTTP response / headers from a request.
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train | Batch._do_request | Override Connection: defer actual HTTP request.
Only allow up to ``_MAX_BATCH_SIZE`` requests to be deferred.
:type method: str
:param method: The HTTP method to use in the request.
:type url: str
:param url: The URL to send the request to.
:type headers: dict
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"""Override Connection: defer actual HTTP request.
Only allow up to ``_MAX_BATCH_SIZE`` requests to be deferred.
:type method: str
:param method: The HTTP method to use in the request.
:type url: str
:p... | def _do_request(self, method, url, headers, data, target_object):
"""Override Connection: defer actual HTTP request.
Only allow up to ``_MAX_BATCH_SIZE`` requests to be deferred.
:type method: str
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:type url: str
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train | Batch._prepare_batch_request | Prepares headers and body for a batch request.
:rtype: tuple (dict, str)
:returns: The pair of headers and body of the batch request to be sent.
:raises: :class:`ValueError` if no requests have been deferred. | storage/google/cloud/storage/batch.py | def _prepare_batch_request(self):
"""Prepares headers and body for a batch request.
:rtype: tuple (dict, str)
:returns: The pair of headers and body of the batch request to be sent.
:raises: :class:`ValueError` if no requests have been deferred.
"""
if len(self._requests... | def _prepare_batch_request(self):
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:rtype: tuple (dict, str)
:returns: The pair of headers and body of the batch request to be sent.
:raises: :class:`ValueError` if no requests have been deferred.
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train | Batch._finish_futures | Apply all the batch responses to the futures created.
:type responses: list of (headers, payload) tuples.
:param responses: List of headers and payloads from each response in
the batch.
:raises: :class:`ValueError` if no requests have been deferred. | storage/google/cloud/storage/batch.py | def _finish_futures(self, responses):
"""Apply all the batch responses to the futures created.
:type responses: list of (headers, payload) tuples.
:param responses: List of headers and payloads from each response in
the batch.
:raises: :class:`ValueError` if n... | def _finish_futures(self, responses):
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:param responses: List of headers and payloads from each response in
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train | Batch.finish | Submit a single `multipart/mixed` request with deferred requests.
:rtype: list of tuples
:returns: one ``(headers, payload)`` tuple per deferred request. | storage/google/cloud/storage/batch.py | def finish(self):
"""Submit a single `multipart/mixed` request with deferred requests.
:rtype: list of tuples
:returns: one ``(headers, payload)`` tuple per deferred request.
"""
headers, body = self._prepare_batch_request()
url = "%s/batch/storage/v1" % self.API_BASE_U... | def finish(self):
"""Submit a single `multipart/mixed` request with deferred requests.
:rtype: list of tuples
:returns: one ``(headers, payload)`` tuple per deferred request.
"""
headers, body = self._prepare_batch_request()
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train | _restart_on_unavailable | Restart iteration after :exc:`.ServiceUnavailable`.
:type restart: callable
:param restart: curried function returning iterator | spanner/google/cloud/spanner_v1/snapshot.py | def _restart_on_unavailable(restart):
"""Restart iteration after :exc:`.ServiceUnavailable`.
:type restart: callable
:param restart: curried function returning iterator
"""
resume_token = b""
item_buffer = []
iterator = restart()
while True:
try:
for item in iterator... | def _restart_on_unavailable(restart):
"""Restart iteration after :exc:`.ServiceUnavailable`.
:type restart: callable
:param restart: curried function returning iterator
"""
resume_token = b""
item_buffer = []
iterator = restart()
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try:
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train | _SnapshotBase.read | Perform a ``StreamingRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
... | spanner/google/cloud/spanner_v1/snapshot.py | def read(self, table, columns, keyset, index="", limit=0, partition=None):
"""Perform a ``StreamingRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be... | def read(self, table, columns, keyset, index="", limit=0, partition=None):
"""Perform a ``StreamingRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
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train | _SnapshotBase.execute_sql | Perform an ``ExecuteStreamingSql`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[... | spanner/google/cloud/spanner_v1/snapshot.py | def execute_sql(
self,
sql,
params=None,
param_types=None,
query_mode=None,
partition=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
):
"""Perform an ``ExecuteStreamingSql`` API request.
... | def execute_sql(
self,
sql,
params=None,
param_types=None,
query_mode=None,
partition=None,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
):
"""Perform an ``ExecuteStreamingSql`` API request.
... | [
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train | _SnapshotBase.partition_read | Perform a ``ParitionRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which to fetch data
:type columns: list of str
:param columns: names of columns to be retrieved
:type keyset: :class:`~google.cloud.spanner_v1.keyset.KeySet`
... | spanner/google/cloud/spanner_v1/snapshot.py | def partition_read(
self,
table,
columns,
keyset,
index="",
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which t... | def partition_read(
self,
table,
columns,
keyset,
index="",
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionRead`` API request for rows in a table.
:type table: str
:param table: name of the table from which t... | [
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train | _SnapshotBase.partition_query | Perform a ``ParitionQuery`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> column value}
:param params: values for parameter replacement. Keys must match
the names used in ``sql``.
:type param_types: dict[str -> ... | spanner/google/cloud/spanner_v1/snapshot.py | def partition_query(
self,
sql,
params=None,
param_types=None,
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionQuery`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> c... | def partition_query(
self,
sql,
params=None,
param_types=None,
partition_size_bytes=None,
max_partitions=None,
):
"""Perform a ``ParitionQuery`` API request.
:type sql: str
:param sql: SQL query statement
:type params: dict, {str -> c... | [
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train | Snapshot._make_txn_selector | Helper for :meth:`read`. | spanner/google/cloud/spanner_v1/snapshot.py | def _make_txn_selector(self):
"""Helper for :meth:`read`."""
if self._transaction_id is not None:
return TransactionSelector(id=self._transaction_id)
if self._read_timestamp:
key = "read_timestamp"
value = _datetime_to_pb_timestamp(self._read_timestamp)
... | def _make_txn_selector(self):
"""Helper for :meth:`read`."""
if self._transaction_id is not None:
return TransactionSelector(id=self._transaction_id)
if self._read_timestamp:
key = "read_timestamp"
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train | Snapshot.begin | Begin a read-only transaction on the database.
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train | ClientInfo.to_user_agent | Returns the user-agent string for this client info. | api_core/google/api_core/gapic_v1/client_info.py | def to_user_agent(self):
"""Returns the user-agent string for this client info."""
# Note: the order here is important as the internal metrics system
# expects these items to be in specific locations.
ua = ""
if self.user_agent is not None:
ua += "{user_agent} "
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# Note: the order here is important as the internal metrics system
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ua = ""
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train | BigQueryStorageClient.read_rows | Reads rows from the table in the format prescribed by the read
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individual rows larger than this will fail.
Each request also returns a set of stream statis... | bigquery_storage/google/cloud/bigquery_storage_v1beta1/client.py | def read_rows(
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metadata=None,
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train | make_trace_api | Create an instance of the gapic Trace API.
Args:
client (~google.cloud.trace.client.Client): The client that holds
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Returns:
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"""
Create an instance of the gapic Trace API.
Args:
client (~google.cloud.trace.client.Client): The client that holds
configuration details.
Returns:
A :class:`~google.cloud.trace._gapic._TraceAPI` instance with the
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Create an instance of the gapic Trace API.
Args:
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Returns:
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train | _TraceAPI.patch_traces | Sends new traces to Stackdriver Trace or updates existing traces.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
traces (dict): Required. The traces to be patched in the API call. | trace/google/cloud/trace/v1/_gapic.py | def patch_traces(self, project_id, traces):
"""
Sends new traces to Stackdriver Trace or updates existing traces.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
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traces (dict): Required. The traces to be patched i... | def patch_traces(self, project_id, traces):
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Sends new traces to Stackdriver Trace or updates existing traces.
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project_id (Optional[str]): ID of the Cloud project where the trace
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train | _TraceAPI.get_trace | Gets a single trace by its ID.
Args:
trace_id (str): ID of the trace to return.
project_id (str): Required. ID of the Cloud project where the trace
data is stored.
Returns:
A Trace dict. | trace/google/cloud/trace/v1/_gapic.py | def get_trace(self, project_id, trace_id):
"""
Gets a single trace by its ID.
Args:
trace_id (str): ID of the trace to return.
project_id (str): Required. ID of the Cloud project where the trace
data is stored.
Returns:
A Trace dict.
... | def get_trace(self, project_id, trace_id):
"""
Gets a single trace by its ID.
Args:
trace_id (str): ID of the trace to return.
project_id (str): Required. ID of the Cloud project where the trace
data is stored.
Returns:
A Trace dict.
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train | _TraceAPI.list_traces | Returns of a list of traces that match the filter conditions.
Args:
project_id (Optional[str]): ID of the Cloud project where the trace
data is stored.
view (Optional[~google.cloud.trace_v1.gapic.enums.
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filter_=None,
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Returns of a list of traces that match the filter conditions.
Args:
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order_by=None,
page_token=None,
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Returns of a list of traces that match the filter conditions.
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train | _item_to_bucket | Convert a JSON bucket to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that has retrieved the item.
:type item: dict
:param item: An item to be converted to a bucket.
:rtype: :class:`.Bucket`
:returns: The next bucket in the ... | storage/google/cloud/storage/client.py | def _item_to_bucket(iterator, item):
"""Convert a JSON bucket to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that has retrieved the item.
:type item: dict
:param item: An item to be converted to a bucket.
:rtype: :class:`.B... | def _item_to_bucket(iterator, item):
"""Convert a JSON bucket to the native object.
:type iterator: :class:`~google.api_core.page_iterator.Iterator`
:param iterator: The iterator that has retrieved the item.
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train | Client.create_anonymous_client | Factory: return client with anonymous credentials.
.. note::
Such a client has only limited access to "public" buckets:
listing their contents and downloading their blobs.
:rtype: :class:`google.cloud.storage.client.Client`
:returns: Instance w/ anonymous credentials and... | storage/google/cloud/storage/client.py | def create_anonymous_client(cls):
"""Factory: return client with anonymous credentials.
.. note::
Such a client has only limited access to "public" buckets:
listing their contents and downloading their blobs.
:rtype: :class:`google.cloud.storage.client.Client`
:r... | def create_anonymous_client(cls):
"""Factory: return client with anonymous credentials.
.. note::
Such a client has only limited access to "public" buckets:
listing their contents and downloading their blobs.
:rtype: :class:`google.cloud.storage.client.Client`
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train | Client.get_service_account_email | Get the email address of the project's GCS service account
:type project: str
:param project:
(Optional) Project ID to use for retreiving GCS service account
email address. Defaults to the client's project.
:rtype: str
:returns: service account email address | storage/google/cloud/storage/client.py | def get_service_account_email(self, project=None):
"""Get the email address of the project's GCS service account
:type project: str
:param project:
(Optional) Project ID to use for retreiving GCS service account
email address. Defaults to the client's project.
... | def get_service_account_email(self, project=None):
"""Get the email address of the project's GCS service account
:type project: str
:param project:
(Optional) Project ID to use for retreiving GCS service account
email address. Defaults to the client's project.
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train | Client.bucket | Factory constructor for bucket object.
.. note::
This will not make an HTTP request; it simply instantiates
a bucket object owned by this client.
:type bucket_name: str
:param bucket_name: The name of the bucket to be instantiated.
:type user_project: str
:... | storage/google/cloud/storage/client.py | def bucket(self, bucket_name, user_project=None):
"""Factory constructor for bucket object.
.. note::
This will not make an HTTP request; it simply instantiates
a bucket object owned by this client.
:type bucket_name: str
:param bucket_name: The name of the bucket t... | def bucket(self, bucket_name, user_project=None):
"""Factory constructor for bucket object.
.. note::
This will not make an HTTP request; it simply instantiates
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train | Client.get_bucket | Get a bucket by name.
If the bucket isn't found, this will raise a
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For example:
.. literalinclude:: snippets.py
:start-after: [START get_bucket]
:end-before: [END get_bucket]
This implements "storage.buckets.g... | storage/google/cloud/storage/client.py | def get_bucket(self, bucket_name):
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For example:
.. literalinclude:: snippets.py
:start-after: [START get_bucket]
:end-before: [END get_bucke... | def get_bucket(self, bucket_name):
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train | Client.create_bucket | Create a new bucket.
For example:
.. literalinclude:: snippets.py
:start-after: [START create_bucket]
:end-before: [END create_bucket]
This implements "storage.buckets.insert".
If the bucket already exists, will raise
:class:`google.cloud.exceptions.Co... | storage/google/cloud/storage/client.py | def create_bucket(self, bucket_name, requester_pays=None, project=None):
"""Create a new bucket.
For example:
.. literalinclude:: snippets.py
:start-after: [START create_bucket]
:end-before: [END create_bucket]
This implements "storage.buckets.insert".
... | def create_bucket(self, bucket_name, requester_pays=None, project=None):
"""Create a new bucket.
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.. literalinclude:: snippets.py
:start-after: [START create_bucket]
:end-before: [END create_bucket]
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train | Client.list_buckets | Get all buckets in the project associated to the client.
This will not populate the list of blobs available in each
bucket.
.. literalinclude:: snippets.py
:start-after: [START list_buckets]
:end-before: [END list_buckets]
This implements "storage.buckets.list"... | storage/google/cloud/storage/client.py | def list_buckets(
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prefix=None,
projection="noAcl",
fields=None,
project=None,
):
"""Get all buckets in the project associated to the client.
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prefix=None,
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project=None,
):
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train | _make_job_id | Construct an ID for a new job.
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:param job_id: the user-provided job ID
:type prefix: str or ``NoneType``
:param prefix: (Optional) the user-provided prefix for a job ID
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:returns: A job ID | bigquery/google/cloud/bigquery/client.py | def _make_job_id(job_id, prefix=None):
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:type job_id: str or ``NoneType``
:param job_id: the user-provided job ID
:type prefix: str or ``NoneType``
:param prefix: (Optional) the user-provided prefix for a job ID
:rtype: str
:returns: A job ID
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"""Construct an ID for a new job.
:type job_id: str or ``NoneType``
:param job_id: the user-provided job ID
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train | _check_mode | Check that a stream was opened in read-binary mode.
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:param stream: A bytes IO object open for reading.
:raises: :exc:`ValueError` if the ``stream.mode`` is a valid attribute
and is not among ``rb``, ``r+b`` or ``rb+``. | bigquery/google/cloud/bigquery/client.py | def _check_mode(stream):
"""Check that a stream was opened in read-binary mode.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:raises: :exc:`ValueError` if the ``stream.mode`` is a valid attribute
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"""
mode =... | def _check_mode(stream):
"""Check that a stream was opened in read-binary mode.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
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train | Client.get_service_account_email | Get the email address of the project's BigQuery service account
Note:
This is the service account that BigQuery uses to manage tables
encrypted by a key in KMS.
Args:
project (str, optional):
Project ID to use for retreiving service account email.
... | bigquery/google/cloud/bigquery/client.py | def get_service_account_email(self, project=None):
"""Get the email address of the project's BigQuery service account
Note:
This is the service account that BigQuery uses to manage tables
encrypted by a key in KMS.
Args:
project (str, optional):
... | def get_service_account_email(self, project=None):
"""Get the email address of the project's BigQuery service account
Note:
This is the service account that BigQuery uses to manage tables
encrypted by a key in KMS.
Args:
project (str, optional):
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train | Client.list_projects | List projects for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list
:type max_results: int
:param max_results: (Optional) maximum number of projects to return,
If not passed, defaults to a val... | bigquery/google/cloud/bigquery/client.py | def list_projects(self, max_results=None, page_token=None, retry=DEFAULT_RETRY):
"""List projects for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list
:type max_results: int
:param max_results: (Optional) maximu... | def list_projects(self, max_results=None, page_token=None, retry=DEFAULT_RETRY):
"""List projects for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list
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train | Client.list_datasets | List datasets for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list
Args:
project (str):
Optional. Project ID to use for retreiving datasets. Defaults
to the client's project.
... | bigquery/google/cloud/bigquery/client.py | def list_datasets(
self,
project=None,
include_all=False,
filter=None,
max_results=None,
page_token=None,
retry=DEFAULT_RETRY,
):
"""List datasets for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/... | def list_datasets(
self,
project=None,
include_all=False,
filter=None,
max_results=None,
page_token=None,
retry=DEFAULT_RETRY,
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"""List datasets for the project associated with this client.
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train | Client.dataset | Construct a reference to a dataset.
:type dataset_id: str
:param dataset_id: ID of the dataset.
:type project: str
:param project: (Optional) project ID for the dataset (defaults to
the project of the client).
:rtype: :class:`google.cloud.bigquery.datas... | bigquery/google/cloud/bigquery/client.py | def dataset(self, dataset_id, project=None):
"""Construct a reference to a dataset.
:type dataset_id: str
:param dataset_id: ID of the dataset.
:type project: str
:param project: (Optional) project ID for the dataset (defaults to
the project of the clien... | def dataset(self, dataset_id, project=None):
"""Construct a reference to a dataset.
:type dataset_id: str
:param dataset_id: ID of the dataset.
:type project: str
:param project: (Optional) project ID for the dataset (defaults to
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train | Client.create_dataset | API call: create the dataset via a POST request.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert
Args:
dataset (Union[ \
:class:`~google.cloud.bigquery.dataset.Dataset`, \
:class:`~google.cloud.bigquery.dataset.DatasetRefer... | bigquery/google/cloud/bigquery/client.py | def create_dataset(self, dataset, exists_ok=False, retry=DEFAULT_RETRY):
"""API call: create the dataset via a POST request.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert
Args:
dataset (Union[ \
:class:`~google.cloud.bigquery.dat... | def create_dataset(self, dataset, exists_ok=False, retry=DEFAULT_RETRY):
"""API call: create the dataset via a POST request.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert
Args:
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train | Client.create_table | API call: create a table via a PUT request
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert
Args:
table (Union[ \
:class:`~google.cloud.bigquery.table.Table`, \
:class:`~google.cloud.bigquery.table.TableReference`, \
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"""API call: create a table via a PUT request
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert
Args:
table (Union[ \
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"""API call: create a table via a PUT request
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert
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train | Client.get_dataset | Fetch the dataset referenced by ``dataset_ref``
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dataset_ref (Union[ \
:class:`~google.cloud.bigquery.dataset.DatasetReference`, \
str, \
]):
A reference to the dataset to fetch from the BigQuery API.
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"""Fetch the dataset referenced by ``dataset_ref``
Args:
dataset_ref (Union[ \
:class:`~google.cloud.bigquery.dataset.DatasetReference`, \
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]):
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dataset_ref (Union[ \
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train | Client.get_model | [Beta] Fetch the model referenced by ``model_ref``.
Args:
model_ref (Union[ \
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A reference to the model to fetch from the BigQuery API.
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"""[Beta] Fetch the model referenced by ``model_ref``.
Args:
model_ref (Union[ \
:class:`~google.cloud.bigquery.model.ModelReference`, \
str, \
]):
A reference to the model to f... | def get_model(self, model_ref, retry=DEFAULT_RETRY):
"""[Beta] Fetch the model referenced by ``model_ref``.
Args:
model_ref (Union[ \
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train | Client.get_table | Fetch the table referenced by ``table``.
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table (Union[ \
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:class:`~google.cloud.bigquery.table.TableReference`, \
str, \
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"""Fetch the table referenced by ``table``.
Args:
table (Union[ \
:class:`~google.cloud.bigquery.table.Table`, \
:class:`~google.cloud.bigquery.table.TableReference`, \
str, \
]):
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train | Client.update_dataset | Change some fields of a dataset.
Use ``fields`` to specify which fields to update. At least one field
must be provided. If a field is listed in ``fields`` and is ``None`` in
``dataset``, it will be deleted.
If ``dataset.etag`` is not ``None``, the update will only
succeed if th... | bigquery/google/cloud/bigquery/client.py | def update_dataset(self, dataset, fields, retry=DEFAULT_RETRY):
"""Change some fields of a dataset.
Use ``fields`` to specify which fields to update. At least one field
must be provided. If a field is listed in ``fields`` and is ``None`` in
``dataset``, it will be deleted.
If `... | def update_dataset(self, dataset, fields, retry=DEFAULT_RETRY):
"""Change some fields of a dataset.
Use ``fields`` to specify which fields to update. At least one field
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train | Client.update_model | [Beta] Change some fields of a model.
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If ``model.etag`` is not ``None``, the update will only succeed if
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Use ``fields`` to specify which fields to update. At least one field
must be provided. If a field is listed in ``fields`` and is ``None``
in ``model``, it will be deleted.
If ``... | def update_model(self, model, fields, retry=DEFAULT_RETRY):
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train | Client.update_table | Change some fields of a table.
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in ``table``, it will be deleted.
If ``table.etag`` is not ``None``, the update will only succeed if
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Use ``fields`` to specify which fields to update. At least one field
must be provided. If a field is listed in ``fields`` and is ``None``
in ``table``, it will be deleted.
If ``table.e... | def update_table(self, table, fields, retry=DEFAULT_RETRY):
"""Change some fields of a table.
Use ``fields`` to specify which fields to update. At least one field
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train | Client.list_models | [Beta] List models in the dataset.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/models/list
Args:
dataset (Union[ \
:class:`~google.cloud.bigquery.dataset.Dataset`, \
:class:`~google.cloud.bigquery.dataset.DatasetReference`, \
... | bigquery/google/cloud/bigquery/client.py | def list_models(
self, dataset, max_results=None, page_token=None, retry=DEFAULT_RETRY
):
"""[Beta] List models in the dataset.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/models/list
Args:
dataset (Union[ \
:class:`~google.cloud... | def list_models(
self, dataset, max_results=None, page_token=None, retry=DEFAULT_RETRY
):
"""[Beta] List models in the dataset.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/models/list
Args:
dataset (Union[ \
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train | Client.delete_dataset | Delete a dataset.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/delete
Args
dataset (Union[ \
:class:`~google.cloud.bigquery.dataset.Dataset`, \
:class:`~google.cloud.bigquery.dataset.DatasetReference`, \
str, ... | bigquery/google/cloud/bigquery/client.py | def delete_dataset(
self, dataset, delete_contents=False, retry=DEFAULT_RETRY, not_found_ok=False
):
"""Delete a dataset.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/delete
Args
dataset (Union[ \
:class:`~google.cloud.bi... | def delete_dataset(
self, dataset, delete_contents=False, retry=DEFAULT_RETRY, not_found_ok=False
):
"""Delete a dataset.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/delete
Args
dataset (Union[ \
:class:`~google.cloud.bi... | [
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train | Client.delete_model | [Beta] Delete a model
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/models/delete
Args:
model (Union[ \
:class:`~google.cloud.bigquery.model.Model`, \
:class:`~google.cloud.bigquery.model.ModelReference`, \
str, \
... | bigquery/google/cloud/bigquery/client.py | def delete_model(self, model, retry=DEFAULT_RETRY, not_found_ok=False):
"""[Beta] Delete a model
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/models/delete
Args:
model (Union[ \
:class:`~google.cloud.bigquery.model.Model`, \
:... | def delete_model(self, model, retry=DEFAULT_RETRY, not_found_ok=False):
"""[Beta] Delete a model
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/models/delete
Args:
model (Union[ \
:class:`~google.cloud.bigquery.model.Model`, \
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train | Client.delete_table | Delete a table
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/delete
Args:
table (Union[ \
:class:`~google.cloud.bigquery.table.Table`, \
:class:`~google.cloud.bigquery.table.TableReference`, \
str, \
... | bigquery/google/cloud/bigquery/client.py | def delete_table(self, table, retry=DEFAULT_RETRY, not_found_ok=False):
"""Delete a table
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/delete
Args:
table (Union[ \
:class:`~google.cloud.bigquery.table.Table`, \
:class:`... | def delete_table(self, table, retry=DEFAULT_RETRY, not_found_ok=False):
"""Delete a table
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/delete
Args:
table (Union[ \
:class:`~google.cloud.bigquery.table.Table`, \
:class:`... | [
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] | googleapis/google-cloud-python | python | https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L791-L821 | [
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train | Client._get_query_results | Get the query results object for a query job.
Arguments:
job_id (str): Name of the query job.
retry (google.api_core.retry.Retry):
(Optional) How to retry the RPC.
project (str):
(Optional) project ID for the query job (defaults to the
... | bigquery/google/cloud/bigquery/client.py | def _get_query_results(
self, job_id, retry, project=None, timeout_ms=None, location=None
):
"""Get the query results object for a query job.
Arguments:
job_id (str): Name of the query job.
retry (google.api_core.retry.Retry):
(Optional) How to retry ... | def _get_query_results(
self, job_id, retry, project=None, timeout_ms=None, location=None
):
"""Get the query results object for a query job.
Arguments:
job_id (str): Name of the query job.
retry (google.api_core.retry.Retry):
(Optional) How to retry ... | [
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train | Client.job_from_resource | Detect correct job type from resource and instantiate.
:type resource: dict
:param resource: one job resource from API response
:rtype: One of:
:class:`google.cloud.bigquery.job.LoadJob`,
:class:`google.cloud.bigquery.job.CopyJob`,
:class:`google... | bigquery/google/cloud/bigquery/client.py | def job_from_resource(self, resource):
"""Detect correct job type from resource and instantiate.
:type resource: dict
:param resource: one job resource from API response
:rtype: One of:
:class:`google.cloud.bigquery.job.LoadJob`,
:class:`google.cloud.big... | def job_from_resource(self, resource):
"""Detect correct job type from resource and instantiate.
:type resource: dict
:param resource: one job resource from API response
:rtype: One of:
:class:`google.cloud.bigquery.job.LoadJob`,
:class:`google.cloud.big... | [
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train | Client.cancel_job | Attempt to cancel a job from a job ID.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/cancel
Arguments:
job_id (str): Unique job identifier.
Keyword Arguments:
project (str):
(Optional) ID of the project which owns the job (de... | bigquery/google/cloud/bigquery/client.py | def cancel_job(self, job_id, project=None, location=None, retry=DEFAULT_RETRY):
"""Attempt to cancel a job from a job ID.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/cancel
Arguments:
job_id (str): Unique job identifier.
Keyword Arguments:
... | def cancel_job(self, job_id, project=None, location=None, retry=DEFAULT_RETRY):
"""Attempt to cancel a job from a job ID.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/cancel
Arguments:
job_id (str): Unique job identifier.
Keyword Arguments:
... | [
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train | Client.list_jobs | List jobs for the project associated with this client.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/list
Args:
project (str, optional):
Project ID to use for retreiving datasets. Defaults
to the client's project.
max_... | bigquery/google/cloud/bigquery/client.py | def list_jobs(
self,
project=None,
max_results=None,
page_token=None,
all_users=None,
state_filter=None,
retry=DEFAULT_RETRY,
min_creation_time=None,
max_creation_time=None,
):
"""List jobs for the project associated with this client.
... | def list_jobs(
self,
project=None,
max_results=None,
page_token=None,
all_users=None,
state_filter=None,
retry=DEFAULT_RETRY,
min_creation_time=None,
max_creation_time=None,
):
"""List jobs for the project associated with this client.
... | [
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"=... | 85e80125a59cb10f8cb105f25ecc099e4b940b50 |
train | Client.load_table_from_uri | Starts a job for loading data into a table from CloudStorage.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.load
Arguments:
source_uris (Union[str, Sequence[str]]):
URIs of data files to be loaded; in format
``gs://<... | bigquery/google/cloud/bigquery/client.py | def load_table_from_uri(
self,
source_uris,
destination,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
retry=DEFAULT_RETRY,
):
"""Starts a job for loading data into a table from CloudStorage.
Se... | def load_table_from_uri(
self,
source_uris,
destination,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
retry=DEFAULT_RETRY,
):
"""Starts a job for loading data into a table from CloudStorage.
Se... | [
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"job",
"for",
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"data",
"into",
"a",
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"from",
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"."
] | googleapis/google-cloud-python | python | https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L1062-L1129 | [
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... | 85e80125a59cb10f8cb105f25ecc099e4b940b50 |
train | Client.load_table_from_file | Upload the contents of this table from a file-like object.
Similar to :meth:`load_table_from_uri`, this method creates, starts and
returns a :class:`~google.cloud.bigquery.job.LoadJob`.
Arguments:
file_obj (file): A file handle opened in binary mode for reading.
destina... | bigquery/google/cloud/bigquery/client.py | def load_table_from_file(
self,
file_obj,
destination,
rewind=False,
size=None,
num_retries=_DEFAULT_NUM_RETRIES,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
):
"""Upload the contents o... | def load_table_from_file(
self,
file_obj,
destination,
rewind=False,
size=None,
num_retries=_DEFAULT_NUM_RETRIES,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
):
"""Upload the contents o... | [
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train | Client.load_table_from_dataframe | Upload the contents of a table from a pandas DataFrame.
Similar to :meth:`load_table_from_uri`, this method creates, starts and
returns a :class:`~google.cloud.bigquery.job.LoadJob`.
Arguments:
dataframe (pandas.DataFrame):
A :class:`~pandas.DataFrame` containing th... | bigquery/google/cloud/bigquery/client.py | def load_table_from_dataframe(
self,
dataframe,
destination,
num_retries=_DEFAULT_NUM_RETRIES,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
):
"""Upload the contents of a table from a pandas DataFrame.
... | def load_table_from_dataframe(
self,
dataframe,
destination,
num_retries=_DEFAULT_NUM_RETRIES,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
):
"""Upload the contents of a table from a pandas DataFrame.
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",... | 85e80125a59cb10f8cb105f25ecc099e4b940b50 |
train | Client._do_resumable_upload | Perform a resumable upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type num_retries: int
:param num_retries: Number of upload retries. (Deprecated: This
... | bigquery/google/cloud/bigquery/client.py | def _do_resumable_upload(self, stream, metadata, num_retries):
"""Perform a resumable upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type num_retries: in... | def _do_resumable_upload(self, stream, metadata, num_retries):
"""Perform a resumable upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type num_retries: in... | [
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train | Client._initiate_resumable_upload | Initiate a resumable upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type num_retries: int
:param num_retries: Number of upload retries. (Deprecated: This... | bigquery/google/cloud/bigquery/client.py | def _initiate_resumable_upload(self, stream, metadata, num_retries):
"""Initiate a resumable upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type num_retr... | def _initiate_resumable_upload(self, stream, metadata, num_retries):
"""Initiate a resumable upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type num_retr... | [
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"_connection",... | 85e80125a59cb10f8cb105f25ecc099e4b940b50 |
train | Client._do_multipart_upload | Perform a multipart upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type size: int
:param size: The number of bytes to be uploaded (which will be read
... | bigquery/google/cloud/bigquery/client.py | def _do_multipart_upload(self, stream, metadata, size, num_retries):
"""Perform a multipart upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type size: int... | def _do_multipart_upload(self, stream, metadata, size, num_retries):
"""Perform a multipart upload.
:type stream: IO[bytes]
:param stream: A bytes IO object open for reading.
:type metadata: dict
:param metadata: The metadata associated with the upload.
:type size: int... | [
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] | googleapis/google-cloud-python | python | https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L1377-L1418 | [
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"_READ_LESS_THAN_S... | 85e80125a59cb10f8cb105f25ecc099e4b940b50 |
train | Client.copy_table | Copy one or more tables to another table.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs#configuration.copy
Arguments:
sources (Union[ \
:class:`~google.cloud.bigquery.table.Table`, \
:class:`~google.cloud.bigquery.table.TableRefer... | bigquery/google/cloud/bigquery/client.py | def copy_table(
self,
sources,
destination,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
retry=DEFAULT_RETRY,
):
"""Copy one or more tables to another table.
See
https://cloud.google.co... | def copy_table(
self,
sources,
destination,
job_id=None,
job_id_prefix=None,
location=None,
project=None,
job_config=None,
retry=DEFAULT_RETRY,
):
"""Copy one or more tables to another table.
See
https://cloud.google.co... | [
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] | googleapis/google-cloud-python | python | https://github.com/googleapis/google-cloud-python/blob/85e80125a59cb10f8cb105f25ecc099e4b940b50/bigquery/google/cloud/bigquery/client.py#L1420-L1509 | [
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