As of January 1, 2020 this library no longer supports Python 2 on the latest released version.
Library versions released prior to that date will continue to be available. For more information please
visit Python 2 support on Google Cloud.
Source code for google.cloud.bigquery.table
# Copyright 2015 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Define API Tables."""
from __future__ import absolute_import
import copy
import datetime
import functools
import logging
import operator
import warnings
import six
try:
# Needed for the to_bqstorage() method.
from google.cloud import bigquery_storage_v1beta1
except ImportError: # pragma: NO COVER
bigquery_storage_v1beta1 = None
try:
import pandas
except ImportError: # pragma: NO COVER
pandas = None
try:
import pyarrow
except ImportError: # pragma: NO COVER
pyarrow = None
try:
import tqdm
except ImportError: # pragma: NO COVER
tqdm = None
import google.api_core.exceptions
from google.api_core.page_iterator import HTTPIterator
import google.cloud._helpers
from google.cloud.bigquery import _helpers
from google.cloud.bigquery import _pandas_helpers
from google.cloud.bigquery.schema import _build_schema_resource
from google.cloud.bigquery.schema import _parse_schema_resource
from google.cloud.bigquery.schema import _to_schema_fields
from google.cloud.bigquery.exceptions import PyarrowMissingWarning
from google.cloud.bigquery.external_config import ExternalConfig
from google.cloud.bigquery.encryption_configuration import EncryptionConfiguration
_LOGGER = logging.getLogger(__name__)
_NO_BQSTORAGE_ERROR = (
"The google-cloud-bigquery-storage library is not installed, "
"please install google-cloud-bigquery-storage to use bqstorage features."
)
_NO_PANDAS_ERROR = (
"The pandas library is not installed, please install "
"pandas to use the to_dataframe() function."
)
_NO_PYARROW_ERROR = (
"The pyarrow library is not installed, please install "
"pyarrow to use the to_arrow() function."
)
_NO_TQDM_ERROR = (
"A progress bar was requested, but there was an error loading the tqdm "
"library. Please install tqdm to use the progress bar functionality."
)
_TABLE_HAS_NO_SCHEMA = 'Table has no schema: call "client.get_table()"'
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
dataset_ref = dataset.DatasetReference(table.project, table.dataset_id)
return TableReference(dataset_ref, table.table_id)
def _view_use_legacy_sql_getter(table):
"""bool: Specifies whether to execute the view with Legacy or Standard SQL.
This boolean specifies whether to execute the view with Legacy SQL
(:data:`True`) or Standard SQL (:data:`False`). The client side default is
:data:`False`. The server-side default is :data:`True`. If this table is
not a view, :data:`None` is returned.
Raises:
ValueError: For invalid value types.
"""
view = table._properties.get("view")
if view is not None:
# The server-side default for useLegacySql is True.
return view.get("useLegacySql", True)
# In some cases, such as in a table list no view object is present, but the
# resource still represents a view. Use the type as a fallback.
if table.table_type == "VIEW":
# The server-side default for useLegacySql is True.
return True
[docs]class TableReference(object):
"""TableReferences are pointers to tables.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablereference
Args:
dataset_ref (google.cloud.bigquery.dataset.DatasetReference):
A pointer to the dataset
table_id (str): The ID of the table
"""
[docs] def __init__(self, dataset_ref, table_id):
self._project = dataset_ref.project
self._dataset_id = dataset_ref.dataset_id
self._table_id = table_id
@property
def project(self):
"""str: Project bound to the table"""
return self._project
@property
def dataset_id(self):
"""str: ID of dataset containing the table."""
return self._dataset_id
@property
def table_id(self):
"""str: The table ID."""
return self._table_id
@property
def path(self):
"""str: URL path for the table's APIs."""
return "/projects/%s/datasets/%s/tables/%s" % (
self._project,
self._dataset_id,
self._table_id,
)
[docs] @classmethod
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
ID, and table ID, each separated by ``.``.
default_project (Optional[str]):
The project ID to use when ``table_id`` does not
include a project ID.
Returns:
TableReference: Table reference parsed from ``table_id``.
Examples:
>>> TableReference.from_string('my-project.mydataset.mytable')
TableRef...(DatasetRef...('my-project', 'mydataset'), 'mytable')
Raises:
ValueError:
If ``table_id`` is not a fully-qualified table ID in
standard SQL format.
"""
from google.cloud.bigquery.dataset import DatasetReference
(
output_project_id,
output_dataset_id,
output_table_id,
) = _helpers._parse_3_part_id(
table_id, default_project=default_project, property_name="table_id"
)
return cls(
DatasetReference(output_project_id, output_dataset_id), output_table_id
)
[docs] @classmethod
def from_api_repr(cls, resource):
"""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:
Table reference parsed from ``resource``.
"""
from google.cloud.bigquery.dataset import DatasetReference
project = resource["projectId"]
dataset_id = resource["datasetId"]
table_id = resource["tableId"]
return cls(DatasetReference(project, dataset_id), table_id)
[docs] def to_api_repr(self):
"""Construct the API resource representation of this table reference.
Returns:
Dict[str, object]: Table reference represented as an API resource
"""
return {
"projectId": self._project,
"datasetId": self._dataset_id,
"tableId": self._table_id,
}
[docs] def to_bqstorage(self, v1beta1=False):
"""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.
``my_table$201812``) or a snapshot identifier (e.g.
``mytable@1234567890``), it is ignored. Use
:class:`google.cloud.bigquery_storage_v1.types.ReadSession.TableReadOptions`
to filter rows by partition. Use
:class:`google.cloud.bigquery_storage_v1.types.ReadSession.TableModifiers`
to select a specific snapshot to read from.
Args:
v1beta1 (Optiona[bool]):
If :data:`True`, return representation compatible with BigQuery
Storage ``v1beta1`` version. Defaults to :data:`False`.
Returns:
Union[str, google.cloud.bigquery_storage_v1beta1.types.TableReference:]:
A reference to this table in the BigQuery Storage API.
Raises:
ValueError:
If ``v1beta1`` compatibility is requested, but the
:mod:`google.cloud.bigquery_storage_v1beta1` module cannot be imported.
"""
if v1beta1 and bigquery_storage_v1beta1 is None:
raise ValueError(_NO_BQSTORAGE_ERROR)
table_id, _, _ = self._table_id.partition("@")
table_id, _, _ = table_id.partition("$")
if v1beta1:
table_ref = bigquery_storage_v1beta1.types.TableReference(
project_id=self._project,
dataset_id=self._dataset_id,
table_id=table_id,
)
else:
table_ref = "projects/{}/datasets/{}/tables/{}".format(
self._project, self._dataset_id, table_id,
)
return table_ref
def _key(self):
"""A tuple key that uniquely describes this field.
Used to compute this instance's hashcode and evaluate equality.
Returns:
Tuple[str]: The contents of this :class:`DatasetReference`.
"""
return (self._project, self._dataset_id, self._table_id)
def __eq__(self, other):
if not isinstance(other, TableReference):
return NotImplemented
return self._key() == other._key()
def __ne__(self, other):
return not self == other
def __hash__(self):
return hash(self._key())
def __repr__(self):
from google.cloud.bigquery.dataset import DatasetReference
dataset_ref = DatasetReference(self._project, self._dataset_id)
return "TableReference({}, '{}')".format(repr(dataset_ref), self._table_id)
[docs]class Table(object):
"""Tables represent a set of rows whose values correspond to a schema.
See
https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#resource-table
Args:
table_ref (Union[google.cloud.bigquery.table.TableReference, str]):
A pointer to a table. If ``table_ref`` is a string, it must
included a project ID, dataset ID, and table ID, each separated
by ``.``.
schema (Optional[Sequence[Union[ \
:class:`~google.cloud.bigquery.schema.SchemaField`, \
Mapping[str, Any] \
]]]):
The table's schema. If any item is a mapping, its content must be
compatible with
:meth:`~google.cloud.bigquery.schema.SchemaField.from_api_repr`.
"""
_PROPERTY_TO_API_FIELD = {
"friendly_name": "friendlyName",
"expires": "expirationTime",
"time_partitioning": "timePartitioning",
"partitioning_type": "timePartitioning",
"partition_expiration": "timePartitioning",
"view_use_legacy_sql": "view",
"view_query": "view",
"external_data_configuration": "externalDataConfiguration",
"encryption_configuration": "encryptionConfiguration",
"require_partition_filter": "requirePartitionFilter",
}
[docs] def __init__(self, table_ref, schema=None):
table_ref = _table_arg_to_table_ref(table_ref)
self._properties = {"tableReference": table_ref.to_api_repr(), "labels": {}}
# Let the @property do validation.
if schema is not None:
self.schema = schema
@property
def project(self):
"""str: Project bound to the table."""
return self._properties["tableReference"]["projectId"]
@property
def dataset_id(self):
"""str: ID of dataset containing the table."""
return self._properties["tableReference"]["datasetId"]
@property
def table_id(self):
"""str: ID of the table."""
return self._properties["tableReference"]["tableId"]
reference = property(_reference_getter)
@property
def path(self):
"""str: URL path for the table's APIs."""
return "/projects/%s/datasets/%s/tables/%s" % (
self.project,
self.dataset_id,
self.table_id,
)
@property
def require_partition_filter(self):
"""bool: If set to true, queries over the partitioned table require a
partition filter that can be used for partition elimination to be
specified.
"""
return self._properties.get("requirePartitionFilter")
@require_partition_filter.setter
def require_partition_filter(self, value):
self._properties["requirePartitionFilter"] = value
@property
def schema(self):
"""Sequence[Union[ \
:class:`~google.cloud.bigquery.schema.SchemaField`, \
Mapping[str, Any] \
]]:
Table's schema.
Raises:
Exception:
If ``schema`` is not a sequence, or if any item in the sequence
is not a :class:`~google.cloud.bigquery.schema.SchemaField`
instance or a compatible mapping representation of the field.
"""
prop = self._properties.get("schema")
if not prop:
return []
else:
return _parse_schema_resource(prop)
@schema.setter
def schema(self, value):
if value is None:
self._properties["schema"] = None
else:
value = _to_schema_fields(value)
self._properties["schema"] = {"fields": _build_schema_resource(value)}
@property
def labels(self):
"""Dict[str, str]: Labels for the table.
This method always returns a dict. To change a table's labels,
modify the dict, then call ``Client.update_table``. To delete a
label, set its value to :data:`None` before updating.
Raises:
ValueError: If ``value`` type is invalid.
"""
return self._properties.setdefault("labels", {})
@labels.setter
def labels(self, value):
if not isinstance(value, dict):
raise ValueError("Pass a dict")
self._properties["labels"] = value
@property
def encryption_configuration(self):
"""google.cloud.bigquery.encryption_configuration.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
<https://cloud.google.com/bigquery/docs/customer-managed-encryption>`_
in the BigQuery documentation.
"""
prop = self._properties.get("encryptionConfiguration")
if prop is not None:
prop = EncryptionConfiguration.from_api_repr(prop)
return prop
@encryption_configuration.setter
def encryption_configuration(self, value):
api_repr = value
if value is not None:
api_repr = value.to_api_repr()
self._properties["encryptionConfiguration"] = api_repr
@property
def created(self):
"""Union[datetime.datetime, None]: Datetime at which the table was
created (:data:`None` until set from the server).
"""
creation_time = self._properties.get("creationTime")
if creation_time is not None:
# creation_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(creation_time)
)
@property
def etag(self):
"""Union[str, None]: ETag for the table resource (:data:`None` until
set from the server).
"""
return self._properties.get("etag")
@property
def modified(self):
"""Union[datetime.datetime, None]: Datetime at which the table was last
modified (:data:`None` until set from the server).
"""
modified_time = self._properties.get("lastModifiedTime")
if modified_time is not None:
# modified_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(modified_time)
)
@property
def num_bytes(self):
"""Union[int, None]: The size of the table in bytes (:data:`None` until
set from the server).
"""
return _helpers._int_or_none(self._properties.get("numBytes"))
@property
def num_rows(self):
"""Union[int, None]: The number of rows in the table (:data:`None`
until set from the server).
"""
return _helpers._int_or_none(self._properties.get("numRows"))
@property
def self_link(self):
"""Union[str, None]: URL for the table resource (:data:`None` until set
from the server).
"""
return self._properties.get("selfLink")
@property
def full_table_id(self):
"""Union[str, None]: ID for the table (:data:`None` until set from the
server).
In the format ``project_id:dataset_id.table_id``.
"""
return self._properties.get("id")
@property
def table_type(self):
"""Union[str, None]: The type of the table (:data:`None` until set from
the server).
Possible values are ``'TABLE'``, ``'VIEW'``, or ``'EXTERNAL'``.
"""
return self._properties.get("type")
@property
def range_partitioning(self):
"""Optional[google.cloud.bigquery.table.RangePartitioning]:
Configures range-based partitioning for a table.
.. note::
**Beta**. The integer range partitioning feature is in a
pre-release state and might change or have limited support.
Only specify at most one of
:attr:`~google.cloud.bigquery.table.Table.time_partitioning` or
:attr:`~google.cloud.bigquery.table.Table.range_partitioning`.
Raises:
ValueError:
If the value is not
:class:`~google.cloud.bigquery.table.RangePartitioning` or
:data:`None`.
"""
resource = self._properties.get("rangePartitioning")
if resource is not None:
return RangePartitioning(_properties=resource)
@range_partitioning.setter
def range_partitioning(self, value):
resource = value
if isinstance(value, RangePartitioning):
resource = value._properties
elif value is not None:
raise ValueError(
"Expected value to be RangePartitioning or None, got {}.".format(value)
)
self._properties["rangePartitioning"] = resource
@property
def time_partitioning(self):
"""Optional[google.cloud.bigquery.table.TimePartitioning]: Configures time-based
partitioning for a table.
Only specify at most one of
:attr:`~google.cloud.bigquery.table.Table.time_partitioning` or
:attr:`~google.cloud.bigquery.table.Table.range_partitioning`.
Raises:
ValueError:
If the value is not
:class:`~google.cloud.bigquery.table.TimePartitioning` or
:data:`None`.
"""
prop = self._properties.get("timePartitioning")
if prop is not None:
return TimePartitioning.from_api_repr(prop)
@time_partitioning.setter
def time_partitioning(self, value):
api_repr = value
if isinstance(value, TimePartitioning):
api_repr = value.to_api_repr()
elif value is not None:
raise ValueError(
"value must be google.cloud.bigquery.table.TimePartitioning " "or None"
)
self._properties["timePartitioning"] = api_repr
@property
def partitioning_type(self):
"""Union[str, None]: Time partitioning of the table if it is
partitioned (Defaults to :data:`None`).
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"Table.time_partitioning.type_ instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.type_
@partitioning_type.setter
def partitioning_type(self, value):
warnings.warn(
"This method will be deprecated in future versions. Please use "
"Table.time_partitioning.type_ instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is None:
self._properties["timePartitioning"] = {}
self._properties["timePartitioning"]["type"] = value
@property
def partition_expiration(self):
"""Union[int, None]: Expiration time in milliseconds for a partition.
If :attr:`partition_expiration` is set and :attr:`type_` is
not set, :attr:`type_` will default to
:attr:`~google.cloud.bigquery.table.TimePartitioningType.DAY`.
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"Table.time_partitioning.expiration_ms instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.expiration_ms
@partition_expiration.setter
def partition_expiration(self, value):
warnings.warn(
"This method will be deprecated in future versions. Please use "
"Table.time_partitioning.expiration_ms instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is None:
self._properties["timePartitioning"] = {"type": TimePartitioningType.DAY}
self._properties["timePartitioning"]["expirationMs"] = str(value)
@property
def clustering_fields(self):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
Clustering fields are immutable after table creation.
.. note::
As of 2018-06-29, clustering fields cannot be set on a table
which does not also have time partioning defined.
"""
prop = self._properties.get("clustering")
if prop is not None:
return list(prop.get("fields", ()))
@clustering_fields.setter
def clustering_fields(self, value):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
"""
if value is not None:
prop = self._properties.setdefault("clustering", {})
prop["fields"] = value
else:
if "clustering" in self._properties:
del self._properties["clustering"]
@property
def description(self):
"""Union[str, None]: Description of the table (defaults to
:data:`None`).
Raises:
ValueError: For invalid value types.
"""
return self._properties.get("description")
@description.setter
def description(self, value):
if not isinstance(value, six.string_types) and value is not None:
raise ValueError("Pass a string, or None")
self._properties["description"] = value
@property
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:
# expiration_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(expiration_time)
)
@expires.setter
def expires(self, value):
if not isinstance(value, datetime.datetime) and value is not None:
raise ValueError("Pass a datetime, or None")
value_ms = google.cloud._helpers._millis_from_datetime(value)
self._properties["expirationTime"] = _helpers._str_or_none(value_ms)
@property
def friendly_name(self):
"""Union[str, None]: Title of the table (defaults to :data:`None`).
Raises:
ValueError: For invalid value types.
"""
return self._properties.get("friendlyName")
@friendly_name.setter
def friendly_name(self, value):
if not isinstance(value, six.string_types) and value is not None:
raise ValueError("Pass a string, or None")
self._properties["friendlyName"] = value
@property
def location(self):
"""Union[str, None]: Location in which the table is hosted
Defaults to :data:`None`.
"""
return self._properties.get("location")
@property
def view_query(self):
"""Union[str, None]: SQL query defining the table as a view (defaults
to :data:`None`).
By default, the query is treated as Standard SQL. To use Legacy
SQL, set :attr:`view_use_legacy_sql` to :data:`True`.
Raises:
ValueError: For invalid value types.
"""
view = self._properties.get("view")
if view is not None:
return view.get("query")
@view_query.setter
def view_query(self, value):
if not isinstance(value, six.string_types):
raise ValueError("Pass a string")
view = self._properties.get("view")
if view is None:
view = self._properties["view"] = {}
view["query"] = value
# The service defaults useLegacySql to True, but this
# client uses Standard SQL by default.
if view.get("useLegacySql") is None:
view["useLegacySql"] = False
@view_query.deleter
def view_query(self):
"""Delete SQL query defining the table as a view."""
self._properties.pop("view", None)
view_use_legacy_sql = property(_view_use_legacy_sql_getter)
@view_use_legacy_sql.setter
def view_use_legacy_sql(self, value):
if not isinstance(value, bool):
raise ValueError("Pass a boolean")
if self._properties.get("view") is None:
self._properties["view"] = {}
self._properties["view"]["useLegacySql"] = value
@property
def streaming_buffer(self):
"""google.cloud.bigquery.StreamingBuffer: Information about a table's
streaming buffer.
"""
sb = self._properties.get("streamingBuffer")
if sb is not None:
return StreamingBuffer(sb)
@property
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")
if prop is not None:
prop = ExternalConfig.from_api_repr(prop)
return prop
@external_data_configuration.setter
def external_data_configuration(self, value):
if not (value is None or isinstance(value, ExternalConfig)):
raise ValueError("Pass an ExternalConfig or None")
api_repr = value
if value is not None:
api_repr = value.to_api_repr()
self._properties["externalDataConfiguration"] = api_repr
[docs] @classmethod
def from_string(cls, full_table_id):
"""Construct a table from fully-qualified table ID.
Args:
full_table_id (str):
A fully-qualified table ID in standard SQL format. Must
included a project ID, dataset ID, and table ID, each
separated by ``.``.
Returns:
Table: Table parsed from ``full_table_id``.
Examples:
>>> Table.from_string('my-project.mydataset.mytable')
Table(TableRef...(D...('my-project', 'mydataset'), 'mytable'))
Raises:
ValueError:
If ``full_table_id`` is not a fully-qualified table ID in
standard SQL format.
"""
return cls(TableReference.from_string(full_table_id))
[docs] @classmethod
def from_api_repr(cls, resource):
"""Factory: construct a table given its API representation
Args:
resource (Dict[str, object]):
Table resource representation from the API
Returns:
google.cloud.bigquery.table.Table: Table parsed from ``resource``.
Raises:
KeyError:
If the ``resource`` lacks the key ``'tableReference'``, or if
the ``dict`` stored within the key ``'tableReference'`` lacks
the keys ``'tableId'``, ``'projectId'``, or ``'datasetId'``.
"""
from google.cloud.bigquery import dataset
if (
"tableReference" not in resource
or "tableId" not in resource["tableReference"]
):
raise KeyError(
"Resource lacks required identity information:"
'["tableReference"]["tableId"]'
)
project_id = resource["tableReference"]["projectId"]
table_id = resource["tableReference"]["tableId"]
dataset_id = resource["tableReference"]["datasetId"]
dataset_ref = dataset.DatasetReference(project_id, dataset_id)
table = cls(dataset_ref.table(table_id))
table._properties = resource
return table
[docs] def to_api_repr(self):
"""Constructs the API resource of this table
Returns:
Dict[str, object]: Table represented as an API resource
"""
return copy.deepcopy(self._properties)
[docs] def to_bqstorage(self, v1beta1=False):
"""Construct a BigQuery Storage API representation of this table.
Args:
v1beta1 (Optiona[bool]):
If :data:`True`, return representation compatible with BigQuery
Storage ``v1beta1`` version. Defaults to :data:`False`.
Returns:
Union[str, google.cloud.bigquery_storage_v1beta1.types.TableReference:]:
A reference to this table in the BigQuery Storage API.
"""
return self.reference.to_bqstorage(v1beta1=v1beta1)
def _build_resource(self, filter_fields):
"""Generate a resource for ``update``."""
return _helpers._build_resource_from_properties(self, filter_fields)
def __repr__(self):
return "Table({})".format(repr(self.reference))
[docs]class TableListItem(object):
"""A read-only table resource from a list operation.
For performance reasons, the BigQuery API only includes some of the table
properties when listing tables. Notably,
:attr:`~google.cloud.bigquery.table.Table.schema` and
:attr:`~google.cloud.bigquery.table.Table.num_rows` are missing.
For a full list of the properties that the BigQuery API returns, see the
`REST documentation for tables.list
<https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/list>`_.
Args:
resource (Dict[str, object]):
A table-like resource object from a table list response. A
``tableReference`` property is required.
Raises:
ValueError:
If ``tableReference`` or one of its required members is missing
from ``resource``.
"""
[docs] def __init__(self, resource):
if "tableReference" not in resource:
raise ValueError("resource must contain a tableReference value")
if "projectId" not in resource["tableReference"]:
raise ValueError(
"resource['tableReference'] must contain a projectId value"
)
if "datasetId" not in resource["tableReference"]:
raise ValueError(
"resource['tableReference'] must contain a datasetId value"
)
if "tableId" not in resource["tableReference"]:
raise ValueError("resource['tableReference'] must contain a tableId value")
self._properties = resource
@property
def created(self):
"""Union[datetime.datetime, None]: Datetime at which the table was
created (:data:`None` until set from the server).
"""
creation_time = self._properties.get("creationTime")
if creation_time is not None:
# creation_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(creation_time)
)
@property
def expires(self):
"""Union[datetime.datetime, None]: Datetime at which the table will be
deleted.
"""
expiration_time = self._properties.get("expirationTime")
if expiration_time is not None:
# expiration_time will be in milliseconds.
return google.cloud._helpers._datetime_from_microseconds(
1000.0 * float(expiration_time)
)
@property
def project(self):
"""str: Project bound to the table."""
return self._properties["tableReference"]["projectId"]
@property
def dataset_id(self):
"""str: ID of dataset containing the table."""
return self._properties["tableReference"]["datasetId"]
@property
def table_id(self):
"""str: ID of the table."""
return self._properties["tableReference"]["tableId"]
reference = property(_reference_getter)
@property
def labels(self):
"""Dict[str, str]: Labels for the table.
This method always returns a dict. To change a table's labels,
modify the dict, then call ``Client.update_table``. To delete a
label, set its value to :data:`None` before updating.
"""
return self._properties.setdefault("labels", {})
@property
def full_table_id(self):
"""Union[str, None]: ID for the table (:data:`None` until set from the
server).
In the format ``project_id:dataset_id.table_id``.
"""
return self._properties.get("id")
@property
def table_type(self):
"""Union[str, None]: The type of the table (:data:`None` until set from
the server).
Possible values are ``'TABLE'``, ``'VIEW'``, or ``'EXTERNAL'``.
"""
return self._properties.get("type")
@property
def time_partitioning(self):
"""google.cloud.bigquery.table.TimePartitioning: Configures time-based
partitioning for a table.
"""
prop = self._properties.get("timePartitioning")
if prop is not None:
return TimePartitioning.from_api_repr(prop)
@property
def partitioning_type(self):
"""Union[str, None]: Time partitioning of the table if it is
partitioned (Defaults to :data:`None`).
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"TableListItem.time_partitioning.type_ instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.type_
@property
def partition_expiration(self):
"""Union[int, None]: Expiration time in milliseconds for a partition.
If this property is set and :attr:`type_` is not set, :attr:`type_`
will default to :attr:`TimePartitioningType.DAY`.
"""
warnings.warn(
"This method will be deprecated in future versions. Please use "
"TableListItem.time_partitioning.expiration_ms instead.",
PendingDeprecationWarning,
stacklevel=2,
)
if self.time_partitioning is not None:
return self.time_partitioning.expiration_ms
@property
def friendly_name(self):
"""Union[str, None]: Title of the table (defaults to :data:`None`)."""
return self._properties.get("friendlyName")
view_use_legacy_sql = property(_view_use_legacy_sql_getter)
@property
def clustering_fields(self):
"""Union[List[str], None]: Fields defining clustering for the table
(Defaults to :data:`None`).
Clustering fields are immutable after table creation.
.. note::
As of 2018-06-29, clustering fields cannot be set on a table
which does not also have time partioning defined.
"""
prop = self._properties.get("clustering")
if prop is not None:
return list(prop.get("fields", ()))
[docs] @classmethod
def from_string(cls, full_table_id):
"""Construct a table from fully-qualified table ID.
Args:
full_table_id (str):
A fully-qualified table ID in standard SQL format. Must
included a project ID, dataset ID, and table ID, each
separated by ``.``.
Returns:
Table: Table parsed from ``full_table_id``.
Examples:
>>> Table.from_string('my-project.mydataset.mytable')
Table(TableRef...(D...('my-project', 'mydataset'), 'mytable'))
Raises:
ValueError:
If ``full_table_id`` is not a fully-qualified table ID in
standard SQL format.
"""
return cls(
{"tableReference": TableReference.from_string(full_table_id).to_api_repr()}
)
[docs] def to_bqstorage(self, v1beta1=False):
"""Construct a BigQuery Storage API representation of this table.
Args:
v1beta1 (Optiona[bool]):
If :data:`True`, return representation compatible with BigQuery
Storage ``v1beta1`` version. Defaults to :data:`False`.
Returns:
Union[str, google.cloud.bigquery_storage_v1beta1.types.TableReference:]:
A reference to this table in the BigQuery Storage API.
"""
return self.reference.to_bqstorage(v1beta1=v1beta1)
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
are ignored.
schema (List[google.cloud.bigquery.schema.SchemaField]):
The schema of the table destination for the rows
Returns:
Tuple[object]:
Tuple whose elements are ordered according to the schema.
Raises:
ValueError: If schema is empty.
"""
if len(schema) == 0:
raise ValueError(_TABLE_HAS_NO_SCHEMA)
row = []
for field in schema:
if field.mode == "REQUIRED":
row.append(mapping[field.name])
elif field.mode == "REPEATED":
row.append(mapping.get(field.name, ()))
elif field.mode == "NULLABLE":
row.append(mapping.get(field.name))
else:
raise ValueError("Unknown field mode: {}".format(field.mode))
return tuple(row)
class StreamingBuffer(object):
"""Information about a table's streaming buffer.
See https://cloud.google.com/bigquery/streaming-data-into-bigquery.
Args:
resource (Dict[str, object]):
streaming buffer representation returned from the API
"""
def __init__(self, resource):
self.estimated_bytes = None
if "estimatedBytes" in resource:
self.estimated_bytes = int(resource["estimatedBytes"])
self.estimated_rows = None
if "estimatedRows" in resource:
self.estimated_rows = int(resource["estimatedRows"])
self.oldest_entry_time = None
if "oldestEntryTime" in resource:
self.oldest_entry_time = google.cloud._helpers._datetime_from_microseconds(
1000.0 * int(resource["oldestEntryTime"])
)
[docs]class Row(object):
"""A BigQuery row.
Values can be accessed by position (index), by key like a dict,
or as properties.
Args:
values (Sequence[object]): The row values
field_to_index (Dict[str, int]):
A mapping from schema field names to indexes
"""
# Choose unusual field names to try to avoid conflict with schema fields.
__slots__ = ("_xxx_values", "_xxx_field_to_index")
[docs] def __init__(self, values, field_to_index):
self._xxx_values = values
self._xxx_field_to_index = field_to_index
[docs] def values(self):
"""Return the values included in this row.
Returns:
Sequence[object]: A sequence of length ``len(row)``.
"""
return copy.deepcopy(self._xxx_values)
[docs] def keys(self):
"""Return the keys for using a row as a dict.
Returns:
Iterable[str]: The keys corresponding to the columns of a row
Examples:
>>> list(Row(('a', 'b'), {'x': 0, 'y': 1}).keys())
['x', 'y']
"""
return six.iterkeys(self._xxx_field_to_index)
[docs] 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')]
"""
for key, index in six.iteritems(self._xxx_field_to_index):
yield (key, copy.deepcopy(self._xxx_values[index]))
[docs] def get(self, key, default=None):
"""Return a value for key, with a default value if it does not exist.
Args:
key (str): The key of the column to access
default (object):
The default value to use if the key does not exist. (Defaults
to :data:`None`.)
Returns:
object:
The value associated with the provided key, or a default value.
Examples:
When the key exists, the value associated with it is returned.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('x')
'a'
The default value is :data:`None` when the key does not exist.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z')
None
The default value can be overrided with the ``default`` parameter.
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', '')
''
>>> Row(('a', 'b'), {'x': 0, 'y': 1}).get('z', default = '')
''
"""
index = self._xxx_field_to_index.get(key)
if index is None:
return default
return self._xxx_values[index]
def __getattr__(self, name):
value = self._xxx_field_to_index.get(name)
if value is None:
raise AttributeError("no row field {!r}".format(name))
return self._xxx_values[value]
def __len__(self):
return len(self._xxx_values)
def __getitem__(self, key):
if isinstance(key, six.string_types):
value = self._xxx_field_to_index.get(key)
if value is None:
raise KeyError("no row field {!r}".format(key))
key = value
return self._xxx_values[key]
def __eq__(self, other):
if not isinstance(other, Row):
return NotImplemented
return (
self._xxx_values == other._xxx_values
and self._xxx_field_to_index == other._xxx_field_to_index
)
def __ne__(self, other):
return not self == other
def __repr__(self):
# sort field dict by value, for determinism
items = sorted(self._xxx_field_to_index.items(), key=operator.itemgetter(1))
f2i = "{" + ", ".join("%r: %d" % item for item in items) + "}"
return "Row({}, {})".format(self._xxx_values, f2i)
class _NoopProgressBarQueue(object):
"""A fake Queue class that does nothing.
This is used when there is no progress bar to send updates to.
"""
def put_nowait(self, item):
"""Don't actually do anything with the item."""
[docs]class RowIterator(HTTPIterator):
"""A class for iterating through HTTP/JSON API row list responses.
Args:
client (google.cloud.bigquery.Client): The API client.
api_request (Callable[google.cloud._http.JSONConnection.api_request]):
The function to use to make API requests.
path (str): The method path to query for the list of items.
schema (Sequence[Union[ \
:class:`~google.cloud.bigquery.schema.SchemaField`, \
Mapping[str, Any] \
]]):
The table's schema. If any item is a mapping, its content must be
compatible with
:meth:`~google.cloud.bigquery.schema.SchemaField.from_api_repr`.
page_token (str): A token identifying a page in a result set to start
fetching results from.
max_results (Optional[int]): The maximum number of results to fetch.
page_size (Optional[int]): The maximum number of rows in each page
of results from this request. Non-positive values are ignored.
Defaults to a sensible value set by the API.
extra_params (Optional[Dict[str, object]]):
Extra query string parameters for the API call.
table (Optional[Union[ \
google.cloud.bigquery.table.Table, \
google.cloud.bigquery.table.TableReference, \
]]):
The table which these rows belong to, or a reference to it. Used to
call the BigQuery Storage API to fetch rows.
selected_fields (Optional[Sequence[google.cloud.bigquery.schema.SchemaField]]):
A subset of columns to select from this table.
"""
[docs] def __init__(
self,
client,
api_request,
path,
schema,
page_token=None,
max_results=None,
page_size=None,
extra_params=None,
table=None,
selected_fields=None,
):
super(RowIterator, self).__init__(
client,
api_request,
path,
item_to_value=_item_to_row,
items_key="rows",
page_token=page_token,
max_results=max_results,
extra_params=extra_params,
page_start=_rows_page_start,
next_token="pageToken",
)
schema = _to_schema_fields(schema)
self._field_to_index = _helpers._field_to_index_mapping(schema)
self._page_size = page_size
self._preserve_order = False
self._project = client.project
self._schema = schema
self._selected_fields = selected_fields
self._table = table
self._total_rows = getattr(table, "num_rows", None)
def _get_next_page_response(self):
"""Requests the next page from the path provided.
Returns:
Dict[str, object]:
The parsed JSON response of the next page's contents.
"""
params = self._get_query_params()
if self._page_size is not None:
if self.page_number and "startIndex" in params:
del params["startIndex"]
params["maxResults"] = self._page_size
return self.api_request(
method=self._HTTP_METHOD, path=self.path, query_params=params
)
@property
def schema(self):
"""List[google.cloud.bigquery.schema.SchemaField]: The subset of
columns to be read from the table."""
return list(self._schema)
@property
def total_rows(self):
"""int: The total number of rows in the table."""
return self._total_rows
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)
return None
description = "Downloading"
unit = "rows"
try:
if progress_bar_type == "tqdm":
return tqdm.tqdm(desc=description, total=self.total_rows, unit=unit)
elif progress_bar_type == "tqdm_notebook":
return tqdm.tqdm_notebook(
desc=description, total=self.total_rows, unit=unit
)
elif progress_bar_type == "tqdm_gui":
return tqdm.tqdm_gui(desc=description, total=self.total_rows, unit=unit)
except (KeyError, TypeError):
# Protect ourselves from any tqdm errors. In case of
# unexpected tqdm behavior, just fall back to showing
# no progress bar.
warnings.warn(_NO_TQDM_ERROR, UserWarning, stacklevel=3)
return None
def _to_page_iterable(
self, bqstorage_download, tabledata_list_download, bqstorage_client=None
):
if bqstorage_client is not None:
for item in bqstorage_download():
yield item
return
for item in tabledata_list_download():
yield item
def _to_arrow_iterable(self, bqstorage_client=None):
"""Create an iterable of arrow RecordBatches, to process the table as a stream."""
bqstorage_download = functools.partial(
_pandas_helpers.download_arrow_bqstorage,
self._project,
self._table,
bqstorage_client,
preserve_order=self._preserve_order,
selected_fields=self._selected_fields,
)
tabledata_list_download = functools.partial(
_pandas_helpers.download_arrow_tabledata_list, iter(self.pages), self.schema
)
return self._to_page_iterable(
bqstorage_download,
tabledata_list_download,
bqstorage_client=bqstorage_client,
)
# If changing the signature of this method, make sure to apply the same
# changes to job.QueryJob.to_arrow()
[docs] def to_arrow(
self,
progress_bar_type=None,
bqstorage_client=None,
create_bqstorage_client=True,
):
"""[Beta] Create a class:`pyarrow.Table` by loading all pages of a
table or query.
Args:
progress_bar_type (Optional[str]):
If set, use the `tqdm <https://tqdm.github.io/>`_ library to
display a progress bar while the data downloads. Install the
``tqdm`` package to use this feature.
Possible values of ``progress_bar_type`` include:
``None``
No progress bar.
``'tqdm'``
Use the :func:`tqdm.tqdm` function to print a progress bar
to :data:`sys.stderr`.
``'tqdm_notebook'``
Use the :func:`tqdm.tqdm_notebook` function to display a
progress bar as a Jupyter notebook widget.
``'tqdm_gui'``
Use the :func:`tqdm.tqdm_gui` function to display a
progress bar as a graphical dialog box.
bqstorage_client (Optional[google.cloud.bigquery_storage_v1.BigQueryReadClient]):
A BigQuery Storage API client. If supplied, use the faster BigQuery
Storage API to fetch rows from BigQuery. This API is a billable API.
This method requires the ``pyarrow`` and
``google-cloud-bigquery-storage`` libraries.
This method only exposes a subset of the capabilities of the
BigQuery Storage API. For full access to all features
(projections, filters, snapshots) use the Storage API directly.
create_bqstorage_client (Optional[bool]):
If ``True`` (default), create a BigQuery Storage API client using
the default API settings. The BigQuery Storage API is a faster way
to fetch rows from BigQuery. See the ``bqstorage_client`` parameter
for more information.
This argument does nothing if ``bqstorage_client`` is supplied.
..versionadded:: 1.24.0
Returns:
pyarrow.Table
A :class:`pyarrow.Table` populated with row data and column
headers from the query results. The column headers are derived
from the destination table's schema.
Raises:
ValueError: If the :mod:`pyarrow` library cannot be imported.
..versionadded:: 1.17.0
"""
if pyarrow is None:
raise ValueError(_NO_PYARROW_ERROR)
if (
bqstorage_client or create_bqstorage_client
) and self.max_results is not None:
warnings.warn(
"Cannot use bqstorage_client if max_results is set, "
"reverting to fetching data with the tabledata.list endpoint.",
stacklevel=2,
)
create_bqstorage_client = False
bqstorage_client = None
owns_bqstorage_client = False
if not bqstorage_client and create_bqstorage_client:
owns_bqstorage_client = True
bqstorage_client = self.client._create_bqstorage_client()
try:
progress_bar = self._get_progress_bar(progress_bar_type)
record_batches = []
for record_batch in self._to_arrow_iterable(
bqstorage_client=bqstorage_client
):
record_batches.append(record_batch)
if progress_bar is not None:
# In some cases, the number of total rows is not populated
# until the first page of rows is fetched. Update the
# progress bar's total to keep an accurate count.
progress_bar.total = progress_bar.total or self.total_rows
progress_bar.update(record_batch.num_rows)
if progress_bar is not None:
# Indicate that the download has finished.
progress_bar.close()
finally:
if owns_bqstorage_client:
bqstorage_client.transport.channel.close()
if record_batches:
return pyarrow.Table.from_batches(record_batches)
else:
# No records, use schema based on BigQuery schema.
arrow_schema = _pandas_helpers.bq_to_arrow_schema(self._schema)
return pyarrow.Table.from_batches(record_batches, schema=arrow_schema)
[docs] def to_dataframe_iterable(self, bqstorage_client=None, dtypes=None):
"""Create an iterable of pandas DataFrames, to process the table as a stream.
Args:
bqstorage_client (Optional[google.cloud.bigquery_storage_v1.BigQueryReadClient]):
A BigQuery Storage API client. If supplied, use the faster
BigQuery Storage API to fetch rows from BigQuery.
This method requires the ``pyarrow`` and
``google-cloud-bigquery-storage`` libraries.
This method only exposes a subset of the capabilities of the
BigQuery Storage API. For full access to all features
(projections, filters, snapshots) use the Storage API directly.
dtypes (Optional[Map[str, Union[str, pandas.Series.dtype]]]):
A dictionary of column names pandas ``dtype``s. The provided
``dtype`` is used when constructing the series for the column
specified. Otherwise, the default pandas behavior is used.
Returns:
pandas.DataFrame:
A generator of :class:`~pandas.DataFrame`.
Raises:
ValueError:
If the :mod:`pandas` library cannot be imported.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
if dtypes is None:
dtypes = {}
column_names = [field.name for field in self._schema]
bqstorage_download = functools.partial(
_pandas_helpers.download_dataframe_bqstorage,
self._project,
self._table,
bqstorage_client,
column_names,
dtypes,
preserve_order=self._preserve_order,
selected_fields=self._selected_fields,
)
tabledata_list_download = functools.partial(
_pandas_helpers.download_dataframe_tabledata_list,
iter(self.pages),
self.schema,
dtypes,
)
return self._to_page_iterable(
bqstorage_download,
tabledata_list_download,
bqstorage_client=bqstorage_client,
)
# If changing the signature of this method, make sure to apply the same
# changes to job.QueryJob.to_dataframe()
[docs] def to_dataframe(
self,
bqstorage_client=None,
dtypes=None,
progress_bar_type=None,
create_bqstorage_client=True,
date_as_object=True,
):
"""Create a pandas DataFrame by loading all pages of a query.
Args:
bqstorage_client (Optional[google.cloud.bigquery_storage_v1.BigQueryReadClient]):
A BigQuery Storage API client. If supplied, use the faster
BigQuery Storage API to fetch rows from BigQuery.
This method requires the ``pyarrow`` and
``google-cloud-bigquery-storage`` libraries.
This method only exposes a subset of the capabilities of the
BigQuery Storage API. For full access to all features
(projections, filters, snapshots) use the Storage API directly.
dtypes (Optional[Map[str, Union[str, pandas.Series.dtype]]]):
A dictionary of column names pandas ``dtype``s. The provided
``dtype`` is used when constructing the series for the column
specified. Otherwise, the default pandas behavior is used.
progress_bar_type (Optional[str]):
If set, use the `tqdm <https://tqdm.github.io/>`_ library to
display a progress bar while the data downloads. Install the
``tqdm`` package to use this feature.
Possible values of ``progress_bar_type`` include:
``None``
No progress bar.
``'tqdm'``
Use the :func:`tqdm.tqdm` function to print a progress bar
to :data:`sys.stderr`.
``'tqdm_notebook'``
Use the :func:`tqdm.tqdm_notebook` function to display a
progress bar as a Jupyter notebook widget.
``'tqdm_gui'``
Use the :func:`tqdm.tqdm_gui` function to display a
progress bar as a graphical dialog box.
..versionadded:: 1.11.0
create_bqstorage_client (Optional[bool]):
If ``True`` (default), create a BigQuery Storage API client
using the default API settings. The BigQuery Storage API
is a faster way to fetch rows from BigQuery. See the
``bqstorage_client`` parameter for more information.
This argument does nothing if ``bqstorage_client`` is supplied.
..versionadded:: 1.24.0
date_as_object (Optional[bool]):
If ``True`` (default), cast dates to objects. If ``False``, convert
to datetime64[ns] dtype.
..versionadded:: 1.26.0
Returns:
pandas.DataFrame:
A :class:`~pandas.DataFrame` populated with row data and column
headers from the query results. The column headers are derived
from the destination table's schema.
Raises:
ValueError:
If the :mod:`pandas` library cannot be imported, or the
:mod:`google.cloud.bigquery_storage_v1` module is
required but cannot be imported.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
if dtypes is None:
dtypes = {}
if (
bqstorage_client or create_bqstorage_client
) and self.max_results is not None:
warnings.warn(
"Cannot use bqstorage_client if max_results is set, "
"reverting to fetching data with the tabledata.list endpoint.",
stacklevel=2,
)
create_bqstorage_client = False
bqstorage_client = None
if pyarrow is not None:
# If pyarrow is available, calling to_arrow, then converting to a
# pandas dataframe is about 2x faster. This is because pandas.concat is
# rarely no-copy, whereas pyarrow.Table.from_batches + to_pandas is
# usually no-copy.
record_batch = self.to_arrow(
progress_bar_type=progress_bar_type,
bqstorage_client=bqstorage_client,
create_bqstorage_client=create_bqstorage_client,
)
df = record_batch.to_pandas(date_as_object=date_as_object)
for column in dtypes:
df[column] = pandas.Series(df[column], dtype=dtypes[column])
return df
else:
warnings.warn(
"Converting to a dataframe without pyarrow installed is "
"often slower and will become unsupported in the future. "
"Please install the pyarrow package.",
PyarrowMissingWarning,
stacklevel=2,
)
# The bqstorage_client is only used if pyarrow is available, so the
# rest of this method only needs to account for tabledata.list.
progress_bar = self._get_progress_bar(progress_bar_type)
frames = []
for frame in self.to_dataframe_iterable(dtypes=dtypes):
frames.append(frame)
if progress_bar is not None:
# In some cases, the number of total rows is not populated
# until the first page of rows is fetched. Update the
# progress bar's total to keep an accurate count.
progress_bar.total = progress_bar.total or self.total_rows
progress_bar.update(len(frame))
if progress_bar is not None:
# Indicate that the download has finished.
progress_bar.close()
# Avoid concatting an empty list.
if not frames:
column_names = [field.name for field in self._schema]
return pandas.DataFrame(columns=column_names)
return pandas.concat(frames, ignore_index=True)
class _EmptyRowIterator(object):
"""An empty row iterator.
This class prevents API requests when there are no rows to fetch or rows
are impossible to fetch, such as with query results for DDL CREATE VIEW
statements.
"""
schema = ()
pages = ()
total_rows = 0
def to_arrow(
self,
progress_bar_type=None,
bqstorage_client=None,
create_bqstorage_client=True,
):
"""[Beta] Create an empty class:`pyarrow.Table`.
Args:
progress_bar_type (str): Ignored. Added for compatibility with RowIterator.
bqstorage_client (Any): Ignored. Added for compatibility with RowIterator.
create_bqstorage_client (bool): Ignored. Added for compatibility with RowIterator.
Returns:
pyarrow.Table: An empty :class:`pyarrow.Table`.
"""
if pyarrow is None:
raise ValueError(_NO_PYARROW_ERROR)
return pyarrow.Table.from_arrays(())
def to_dataframe(
self,
bqstorage_client=None,
dtypes=None,
progress_bar_type=None,
create_bqstorage_client=True,
date_as_object=True,
):
"""Create an empty dataframe.
Args:
bqstorage_client (Any): Ignored. Added for compatibility with RowIterator.
dtypes (Any): Ignored. Added for compatibility with RowIterator.
progress_bar_type (Any): Ignored. Added for compatibility with RowIterator.
create_bqstorage_client (bool): Ignored. Added for compatibility with RowIterator.
date_as_object (bool): Ignored. Added for compatibility with RowIterator.
Returns:
pandas.DataFrame: An empty :class:`~pandas.DataFrame`.
"""
if pandas is None:
raise ValueError(_NO_PANDAS_ERROR)
return pandas.DataFrame()
def __iter__(self):
return iter(())
[docs]class PartitionRange(object):
"""Definition of the ranges for range partitioning.
.. note::
**Beta**. The integer range partitioning feature is in a pre-release
state and might change or have limited support.
Args:
start (Optional[int]):
Sets the
:attr:`~google.cloud.bigquery.table.PartitionRange.start`
property.
end (Optional[int]):
Sets the
:attr:`~google.cloud.bigquery.table.PartitionRange.end`
property.
interval (Optional[int]):
Sets the
:attr:`~google.cloud.bigquery.table.PartitionRange.interval`
property.
_properties (Optional[dict]):
Private. Used to construct object from API resource.
"""
[docs] def __init__(self, start=None, end=None, interval=None, _properties=None):
if _properties is None:
_properties = {}
self._properties = _properties
if start is not None:
self.start = start
if end is not None:
self.end = end
if interval is not None:
self.interval = interval
@property
def start(self):
"""int: The start of range partitioning, inclusive."""
return _helpers._int_or_none(self._properties.get("start"))
@start.setter
def start(self, value):
self._properties["start"] = _helpers._str_or_none(value)
@property
def end(self):
"""int: The end of range partitioning, exclusive."""
return _helpers._int_or_none(self._properties.get("end"))
@end.setter
def end(self, value):
self._properties["end"] = _helpers._str_or_none(value)
@property
def interval(self):
"""int: The width of each interval."""
return _helpers._int_or_none(self._properties.get("interval"))
@interval.setter
def interval(self, value):
self._properties["interval"] = _helpers._str_or_none(value)
def _key(self):
return tuple(sorted(self._properties.items()))
def __eq__(self, other):
if not isinstance(other, PartitionRange):
return NotImplemented
return self._key() == other._key()
def __ne__(self, other):
return not self == other
def __repr__(self):
key_vals = ["{}={}".format(key, val) for key, val in self._key()]
return "PartitionRange({})".format(", ".join(key_vals))
__hash__ = None
[docs]class RangePartitioning(object):
"""Range-based partitioning configuration for a table.
.. note::
**Beta**. The integer range partitioning feature is in a pre-release
state and might change or have limited support.
Args:
range_ (Optional[google.cloud.bigquery.table.PartitionRange]):
Sets the
:attr:`google.cloud.bigquery.table.RangePartitioning.range_`
property.
field (Optional[str]):
Sets the
:attr:`google.cloud.bigquery.table.RangePartitioning.field`
property.
_properties (Optional[dict]):
Private. Used to construct object from API resource.
"""
[docs] def __init__(self, range_=None, field=None, _properties=None):
if _properties is None:
_properties = {}
self._properties = _properties
if range_ is not None:
self.range_ = range_
if field is not None:
self.field = field
# Trailing underscore to prevent conflict with built-in range() function.
@property
def range_(self):
"""google.cloud.bigquery.table.PartitionRange: Defines the
ranges for range partitioning.
Raises:
ValueError:
If the value is not a :class:`PartitionRange`.
"""
range_properties = self._properties.setdefault("range", {})
return PartitionRange(_properties=range_properties)
@range_.setter
def range_(self, value):
if not isinstance(value, PartitionRange):
raise ValueError("Expected a PartitionRange, but got {}.".format(value))
self._properties["range"] = value._properties
@property
def field(self):
"""str: The table is partitioned by this field.
The field must be a top-level ``NULLABLE`` / ``REQUIRED`` field. The
only supported type is ``INTEGER`` / ``INT64``.
"""
return self._properties.get("field")
@field.setter
def field(self, value):
self._properties["field"] = value
def _key(self):
return (("field", self.field), ("range_", self.range_))
def __eq__(self, other):
if not isinstance(other, RangePartitioning):
return NotImplemented
return self._key() == other._key()
def __ne__(self, other):
return not self == other
def __repr__(self):
key_vals = ["{}={}".format(key, repr(val)) for key, val in self._key()]
return "RangePartitioning({})".format(", ".join(key_vals))
__hash__ = None
[docs]class TimePartitioningType(object):
"""Specifies the type of time partitioning to perform."""
DAY = "DAY"
"""str: Generates one partition per day."""
HOUR = "HOUR"
"""str: Generates one partition per hour."""
[docs]class TimePartitioning(object):
"""Configures time-based partitioning for a table.
Args:
type_ (Optional[google.cloud.bigquery.table.TimePartitioningType]):
Specifies the type of time partitioning to perform. Defaults to
:attr:`~google.cloud.bigquery.table.TimePartitioningType.DAY`,
which is the only currently supported type.
field (Optional[str]):
If set, the table is partitioned by this field. If not set, the
table is partitioned by pseudo column ``_PARTITIONTIME``. The field
must be a top-level ``TIMESTAMP`` or ``DATE`` field. Its mode must
be ``NULLABLE`` or ``REQUIRED``.
expiration_ms(Optional[int]):
Number of milliseconds for which to keep the storage for a
partition.
require_partition_filter (Optional[bool]):
DEPRECATED: Use
:attr:`~google.cloud.bigquery.table.Table.require_partition_filter`,
instead.
"""
[docs] def __init__(
self, type_=None, field=None, expiration_ms=None, require_partition_filter=None
):
self._properties = {}
if type_ is None:
self.type_ = TimePartitioningType.DAY
else:
self.type_ = type_
if field is not None:
self.field = field
if expiration_ms is not None:
self.expiration_ms = expiration_ms
if require_partition_filter is not None:
self.require_partition_filter = require_partition_filter
@property
def type_(self):
"""google.cloud.bigquery.table.TimePartitioningType: The type of time
partitioning to use.
"""
return self._properties.get("type")
@type_.setter
def type_(self, value):
self._properties["type"] = value
@property
def field(self):
"""str: Field in the table to use for partitioning"""
return self._properties.get("field")
@field.setter
def field(self, value):
self._properties["field"] = value
@property
def expiration_ms(self):
"""int: Number of milliseconds to keep the storage for a partition."""
return _helpers._int_or_none(self._properties.get("expirationMs"))
@expiration_ms.setter
def expiration_ms(self, value):
if value is not None:
# Allow explicitly setting the expiration to None.
value = str(value)
self._properties["expirationMs"] = value
@property
def require_partition_filter(self):
"""bool: Specifies whether partition filters are required for queries
DEPRECATED: Use
:attr:`~google.cloud.bigquery.table.Table.require_partition_filter`,
instead.
"""
warnings.warn(
(
"TimePartitioning.require_partition_filter will be removed in "
"future versions. Please use Table.require_partition_filter "
"instead."
),
PendingDeprecationWarning,
stacklevel=2,
)
return self._properties.get("requirePartitionFilter")
@require_partition_filter.setter
def require_partition_filter(self, value):
warnings.warn(
(
"TimePartitioning.require_partition_filter will be removed in "
"future versions. Please use Table.require_partition_filter "
"instead."
),
PendingDeprecationWarning,
stacklevel=2,
)
self._properties["requirePartitionFilter"] = value
[docs] @classmethod
def from_api_repr(cls, 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
that when a ``TimePartitioning`` instance is stored as a property of
another object, any changes made at the higher level will also appear
here::
>>> time_partitioning = TimePartitioning()
>>> table.time_partitioning = time_partitioning
>>> table.time_partitioning.field = 'timecolumn'
>>> time_partitioning.field
'timecolumn'
Args:
api_repr (Mapping[str, str]):
The serialized representation of the TimePartitioning, such as
what is output by :meth:`to_api_repr`.
Returns:
google.cloud.bigquery.table.TimePartitioning:
The ``TimePartitioning`` object.
"""
instance = cls()
instance._properties = api_repr
return instance
[docs] def to_api_repr(self):
"""Return a dictionary representing this object.
This method returns the properties dict of the ``TimePartitioning``
instance rather than making a copy. This means that when a
``TimePartitioning`` instance is stored as a property of another
object, any changes made at the higher level will also appear here.
Returns:
dict:
A dictionary representing the TimePartitioning object in
serialized form.
"""
return self._properties
def _key(self):
return tuple(sorted(self._properties.items()))
def __eq__(self, other):
if not isinstance(other, TimePartitioning):
return NotImplemented
return self._key() == other._key()
def __ne__(self, other):
return not self == other
def __hash__(self):
return hash(self._key())
def __repr__(self):
key_vals = ["{}={}".format(key, val) for key, val in self._key()]
return "TimePartitioning({})".format(",".join(key_vals))
def _item_to_row(iterator, resource):
"""Convert a JSON row to the native object.
.. note::
This assumes that the ``schema`` attribute has been
added to the iterator after being created, which
should be done by the caller.
Args:
iterator (google.api_core.page_iterator.Iterator): The iterator that is currently in use.
resource (Dict): An item to be converted to a row.
Returns:
google.cloud.bigquery.table.Row: The next row in the page.
"""
return Row(
_helpers._row_tuple_from_json(resource, iterator.schema),
iterator._field_to_index,
)
def _tabledata_list_page_columns(schema, response):
"""Make a generator of all the columns in a page from tabledata.list.
This enables creating a :class:`pandas.DataFrame` and other
column-oriented data structures such as :class:`pyarrow.RecordBatch`
"""
columns = []
rows = response.get("rows", [])
def get_column_data(field_index, field):
for row in rows:
yield _helpers._field_from_json(row["f"][field_index]["v"], field)
for field_index, field in enumerate(schema):
columns.append(get_column_data(field_index, field))
return columns
# pylint: disable=unused-argument
def _rows_page_start(iterator, page, response):
"""Grab total rows when :class:`~google.cloud.iterator.Page` starts.
Args:
iterator (google.api_core.page_iterator.Iterator): The iterator that is currently in use.
page (google.api_core.page_iterator.Page): The page that was just created.
response (Dict): The JSON API response for a page of rows in a table.
"""
# Make a (lazy) copy of the page in column-oriented format for use in data
# science packages.
page._columns = _tabledata_list_page_columns(iterator._schema, response)
total_rows = response.get("totalRows")
if total_rows is not None:
total_rows = int(total_rows)
iterator._total_rows = total_rows
# pylint: enable=unused-argument
def _table_arg_to_table_ref(value, default_project=None):
"""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):
value = TableReference.from_string(value, default_project=default_project)
if isinstance(value, (Table, TableListItem)):
value = value.reference
return value
def _table_arg_to_table(value, default_project=None):
"""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):
value = TableReference.from_string(value, default_project=default_project)
if isinstance(value, TableReference):
value = Table(value)
if isinstance(value, TableListItem):
newvalue = Table(value.reference)
newvalue._properties = value._properties
value = newvalue
return value
