Class Client (3.20.1)

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Client(
    project=None,
    credentials=None,
    _http=None,
    location=None,
    default_query_job_config=None,
    default_load_job_config=None,
    client_info=None,
    client_options=None,
)

Client to bundle configuration needed for API requests.

Parameters
Name	Description
project	Optional[str] Project ID for the project which the client acts on behalf of. Will be passed when creating a dataset / job. If not passed, falls back to the default inferred from the environment.
credentials	Optional[google.auth.credentials.Credentials] The OAuth2 Credentials to use for this client. If not passed (and if no _http object is passed), falls back to the default inferred from the environment.
_http	Optional[requests.Session] HTTP object to make requests. Can be any object that defines request() with the same interface as requests.Session.request. If not passed, an _http object is created that is bound to the credentials for the current object. This parameter should be considered private, and could change in the future.
location	Optional[str] Default location for jobs / datasets / tables.
default_query_job_config	Optional[google.cloud.bigquery.job.QueryJobConfig] Default QueryJobConfig. Will be merged into job configs passed into the query method.
default_load_job_config	Optional[google.cloud.bigquery.job.LoadJobConfig] Default LoadJobConfig. Will be merged into job configs passed into the load_table_* methods.
client_info	Optional[google.api_core.client_info.ClientInfo] The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own library or partner tool.
client_options	Optional[Union[google.api_core.client_options.ClientOptions, Dict]] Client options used to set user options on the client. API Endpoint should be set through client_options.

Properties

default_load_job_config

Default LoadJobConfig. Will be merged into job configs passed into the load_table_* methods.

default_query_job_config

Default QueryJobConfig or None.

Will be merged into job configs passed into the query or query_and_wait methods.

location

Default location for jobs / datasets / tables.

Methods

__getstate__

__getstate__()

Explicitly state that clients are not pickleable.

cancel_job

cancel_job(job_id: str, project: typing.Optional[str] = None, location: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> typing.Union[google.cloud.bigquery.job.load.LoadJob, google.cloud.bigquery.job.copy_.CopyJob, google.cloud.bigquery.job.extract.ExtractJob, google.cloud.bigquery.job.query.QueryJob]

Attempt to cancel a job from a job ID.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/cancel

Parameters
Name	Description
job_id	Union[ str, google.cloud.bigquery.job.LoadJob, google.cloud.bigquery.job.CopyJob, google.cloud.bigquery.job.ExtractJob, google.cloud.bigquery.job.QueryJob ] Job identifier.
project	Optional[str] ID of the project which owns the job (defaults to the client's project).
location	Optional[str] Location where the job was run. Ignored if job_id is a job object.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
Union[ google.cloud.bigquery.job.LoadJob, google.cloud.bigquery.job.CopyJob, google.cloud.bigquery.job.ExtractJob, google.cloud.bigquery.job.QueryJob, ]	Job instance, based on the resource returned by the API.

close

close()

Close the underlying transport objects, releasing system resources.

Note: The client instance can be used for making additional requests even after closing, in which case the underlying connections are automatically re-created.

copy_table

copy_table(sources: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, typing.Sequence[typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str]]], destination: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], job_id: typing.Optional[str] = None, job_id_prefix: typing.Optional[str] = None, location: typing.Optional[str] = None, project: typing.Optional[str] = None, job_config: typing.Optional[google.cloud.bigquery.job.copy_.CopyJobConfig] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.job.copy_.CopyJob

Copy one or more tables to another table.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfigurationtablecopy

Parameters
Name	Description
sources	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, Sequence[ Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] ], ] Table or tables to be copied.
destination	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] Table into which data is to be copied.
job_id	Optional[str] The ID of the job.
job_id_prefix	Optional[str] The user-provided prefix for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of any source table as well as the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
job_config	Optional[google.cloud.bigquery.job.CopyJobConfig] Extra configuration options for the job.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Exceptions
Type	Description
TypeError	If job_config is not an instance of CopyJobConfig class.

Returns
Type	Description
google.cloud.bigquery.job.CopyJob	A new copy job instance.

create_dataset

create_dataset(dataset: typing.Union[str, google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem], exists_ok: bool = False, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.dataset.Dataset

API call: create the dataset via a POST request.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/insert

Parameters
Name	Description
dataset	Union[ google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str, ] A Dataset to create. If dataset is a reference, an empty dataset is created with the specified ID and client's default location.
exists_ok	Optional[bool] Defaults to False. If True, ignore "already exists" errors when creating the dataset.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Exceptions
Type	Description
google.cloud.exceptions.Conflict	If the dataset already exists. .. rubric:: Example >>> from google.cloud import bigquery >>> client = bigquery.Client() >>> dataset = bigquery.Dataset('my_project.my_dataset') >>> dataset = client.create_dataset(dataset)

Returns
Type	Description
google.cloud.bigquery.dataset.Dataset	A new Dataset returned from the API.

create_job

create_job(job_config: dict, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> typing.Union[google.cloud.bigquery.job.load.LoadJob, google.cloud.bigquery.job.copy_.CopyJob, google.cloud.bigquery.job.extract.ExtractJob, google.cloud.bigquery.job.query.QueryJob]

Create a new job.

Parameters
Name	Description
job_config	dict configuration job representation returned from the API.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
Union[ google.cloud.bigquery.job.LoadJob, google.cloud.bigquery.job.CopyJob, google.cloud.bigquery.job.ExtractJob, google.cloud.bigquery.job.QueryJob ]	A new job instance.

create_routine

create_routine(routine: google.cloud.bigquery.routine.routine.Routine, exists_ok: bool = False, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.routine.routine.Routine

[Beta] Create a routine via a POST request.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/routines/insert

Parameters
Name	Description
routine	google.cloud.bigquery.routine.Routine A Routine to create. The dataset that the routine belongs to must already exist.
exists_ok	Optional[bool] Defaults to False. If True, ignore "already exists" errors when creating the routine.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Exceptions
Type	Description
google.cloud.exceptions.Conflict	If the routine already exists.

Returns
Type	Description
google.cloud.bigquery.routine.Routine	A new Routine returned from the service.

create_table

create_table(table: typing.Union[str, google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem], exists_ok: bool = False, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.table.Table

API call: create a table via a PUT request

See https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/insert

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] A Table to create. If table is a reference, an empty table is created with the specified ID. The dataset that the table belongs to must already exist.
exists_ok	Optional[bool] Defaults to False. If True, ignore "already exists" errors when creating the table.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Exceptions
Type	Description
google.cloud.exceptions.Conflict	If the table already exists.

Returns
Type	Description
google.cloud.bigquery.table.Table	A new Table returned from the service.

dataset

dataset(
    dataset_id: str, project: typing.Optional[str] = None
) -> google.cloud.bigquery.dataset.DatasetReference

Deprecated: Construct a reference to a dataset.

deprecated: Construct a xref_DatasetReference using its constructor or use a string where previously a reference object was used.

As of google-cloud-bigquery version 1.7.0, all client methods that take a xref_DatasetReference or xref_TableReference also take a string in standard SQL format, e.g. project.dataset_id or project.dataset_id.table_id.

Parameters
Name	Description
dataset_id	str ID of the dataset.
project	Optional[str] Project ID for the dataset (defaults to the project of the client).

Returns
Type	Description
google.cloud.bigquery.dataset.DatasetReference	a new DatasetReference instance.

delete_dataset

delete_dataset(dataset: typing.Union[google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str], delete_contents: bool = False, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, not_found_ok: bool = False) -> None

Delete a dataset.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/delete

Parameters
Name	Description
dataset	Union[ google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str, ] A reference to the dataset to delete. If a string is passed in, this method attempts to create a dataset reference from a string using from_string.
delete_contents	Optional[bool] If True, delete all the tables in the dataset. If False and the dataset contains tables, the request will fail. Default is False.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
not_found_ok	Optional[bool] Defaults to False. If True, ignore "not found" errors when deleting the dataset.

delete_job_metadata

delete_job_metadata(job_id: typing.Union[str, google.cloud.bigquery.job.load.LoadJob, google.cloud.bigquery.job.copy_.CopyJob, google.cloud.bigquery.job.extract.ExtractJob, google.cloud.bigquery.job.query.QueryJob], project: typing.Optional[str] = None, location: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, not_found_ok: bool = False)

[Beta] Delete job metadata from job history.

Note: This does not stop a running job. Use xref_cancel_job instead.

Parameters
Name	Description
job_id	Union[ str, LoadJob, CopyJob, ExtractJob, QueryJob ] Job or job identifier.
project	Optional[str] ID of the project which owns the job (defaults to the client's project).
location	Optional[str] Location where the job was run. Ignored if job_id is a job object.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
not_found_ok	Optional[bool] Defaults to False. If True, ignore "not found" errors when deleting the job.

delete_model

delete_model(model: typing.Union[google.cloud.bigquery.model.Model, google.cloud.bigquery.model.ModelReference, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, not_found_ok: bool = False) -> None

[Beta] Delete a model

See https://cloud.google.com/bigquery/docs/reference/rest/v2/models/delete

Parameters
Name	Description
model	Union[ google.cloud.bigquery.model.Model, google.cloud.bigquery.model.ModelReference, str, ] A reference to the model to delete. If a string is passed in, this method attempts to create a model reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
not_found_ok	Optional[bool] Defaults to False. If True, ignore "not found" errors when deleting the model.

delete_routine

delete_routine(routine: typing.Union[google.cloud.bigquery.routine.routine.Routine, google.cloud.bigquery.routine.routine.RoutineReference, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, not_found_ok: bool = False) -> None

[Beta] Delete a routine.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/routines/delete

Parameters
Name	Description
routine	Union[ google.cloud.bigquery.routine.Routine, google.cloud.bigquery.routine.RoutineReference, str, ] A reference to the routine to delete. If a string is passed in, this method attempts to create a routine reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
not_found_ok	Optional[bool] Defaults to False. If True, ignore "not found" errors when deleting the routine.

delete_table

delete_table(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, not_found_ok: bool = False) -> None

Delete a table

See https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/delete

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] A reference to the table to delete. If a string is passed in, this method attempts to create a table reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
not_found_ok	Optional[bool] Defaults to False. If True, ignore "not found" errors when deleting the table.

extract_table

extract_table(source: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, google.cloud.bigquery.model.Model, google.cloud.bigquery.model.ModelReference, str], destination_uris: typing.Union[str, typing.Sequence[str]], job_id: typing.Optional[str] = None, job_id_prefix: typing.Optional[str] = None, location: typing.Optional[str] = None, project: typing.Optional[str] = None, job_config: typing.Optional[google.cloud.bigquery.job.extract.ExtractJobConfig] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, source_type: str = 'Table') -> google.cloud.bigquery.job.extract.ExtractJob

Start a job to extract a table into Cloud Storage files.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfigurationextract

Parameters
Name	Description
source	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, google.cloud.bigquery.model.Model, google.cloud.bigquery.model.ModelReference, src, ] Table or Model to be extracted.
destination_uris	Union[str, Sequence[str]] URIs of Cloud Storage file(s) into which table data is to be extracted; in format gs://<bucket_name>/<object_name_or_glob>.
job_id	Optional[str] The ID of the job.
job_id_prefix	Optional[str] The user-provided prefix for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of the source table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
job_config	Optional[google.cloud.bigquery.job.ExtractJobConfig] Extra configuration options for the job.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
source_type	Optional[str] Type of source to be extracted.Table or Model. Defaults to Table.

Exceptions
Type	Description
TypeError	If job_config is not an instance of ExtractJobConfig class.
ValueError	If source_type is not among Table,Model.

Returns
Type	Description
google.cloud.bigquery.job.ExtractJob	A new extract job instance.

from_service_account_info

from_service_account_info(info, *args, **kwargs)

Factory to retrieve JSON credentials while creating client.

Parameters
Name	Description
args	tuple Remaining positional arguments to pass to constructor.
info	dict The JSON object with a private key and other credentials information (downloaded from the Google APIs console).

Exceptions
Type	Description
TypeError	if there is a conflict with the kwargs and the credentials created by the factory.

Returns
Type	Description
_ClientFactoryMixin	The client created with the retrieved JSON credentials.

from_service_account_json

from_service_account_json(json_credentials_path, *args, **kwargs)

Factory to retrieve JSON credentials while creating client.

Parameters
Name	Description
args	tuple Remaining positional arguments to pass to constructor.
json_credentials_path	str The path to a private key file (this file was given to you when you created the service account). This file must contain a JSON object with a private key and other credentials information (downloaded from the Google APIs console).

Exceptions
Type	Description
TypeError	if there is a conflict with the kwargs and the credentials created by the factory.

Returns
Type	Description
_ClientFactoryMixin	The client created with the retrieved JSON credentials.

get_dataset

get_dataset(dataset_ref: typing.Union[google.cloud.bigquery.dataset.DatasetReference, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.dataset.Dataset

Fetch the dataset referenced by dataset_ref

Parameters
Name	Description
dataset_ref	Union[ google.cloud.bigquery.dataset.DatasetReference, str, ] A reference to the dataset to fetch from the BigQuery API. If a string is passed in, this method attempts to create a dataset reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.dataset.Dataset	A Dataset instance.

get_iam_policy

get_iam_policy(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], requested_policy_version: int = 1, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.api_core.iam.Policy

Return the access control policy for a table resource.

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] The table to get the access control policy for. If a string is passed in, this method attempts to create a table reference from a string using from_string.
requested_policy_version	int Optional. The maximum policy version that will be used to format the policy. Only version 1 is currently supported. See: https://cloud.google.com/bigquery/docs/reference/rest/v2/GetPolicyOptions
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.api_core.iam.Policy	The access control policy.

get_job

get_job(job_id: typing.Union[str, google.cloud.bigquery.job.load.LoadJob, google.cloud.bigquery.job.copy_.CopyJob, google.cloud.bigquery.job.extract.ExtractJob, google.cloud.bigquery.job.query.QueryJob], project: typing.Optional[str] = None, location: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> typing.Union[google.cloud.bigquery.job.load.LoadJob, google.cloud.bigquery.job.copy_.CopyJob, google.cloud.bigquery.job.extract.ExtractJob, google.cloud.bigquery.job.query.QueryJob, google.cloud.bigquery.job.base.UnknownJob]

Fetch a job for the project associated with this client.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/get

Parameters
Name	Description
job_id	Union[ str, job.LoadJob, job.CopyJob, job.ExtractJob, job.QueryJob ] Job identifier.
project	Optional[str] ID of the project which owns the job (defaults to the client's project).
location	Optional[str] Location where the job was run. Ignored if job_id is a job object.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
Union[job.LoadJob, job.CopyJob, job.ExtractJob, job.QueryJob, job.UnknownJob]	Job instance, based on the resource returned by the API.

get_model

get_model(model_ref: typing.Union[google.cloud.bigquery.model.ModelReference, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.model.Model

[Beta] Fetch the model referenced by model_ref.

Parameters
Name	Description
model_ref	Union[ google.cloud.bigquery.model.ModelReference, str, ] A reference to the model to fetch from the BigQuery API. If a string is passed in, this method attempts to create a model reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.model.Model	A Model instance.

get_routine

get_routine(routine_ref: typing.Union[google.cloud.bigquery.routine.routine.Routine, google.cloud.bigquery.routine.routine.RoutineReference, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.routine.routine.Routine

[Beta] Get the routine referenced by routine_ref.

Parameters
Name	Description
routine_ref	Union[ google.cloud.bigquery.routine.Routine, google.cloud.bigquery.routine.RoutineReference, str, ] A reference to the routine to fetch from the BigQuery API. If a string is passed in, this method attempts to create a reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the API call.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.routine.Routine	A Routine instance.

get_service_account_email

get_service_account_email(project: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> str

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.

Parameters
Name	Description
project	Optional[str] Project ID to use for retreiving service account email. Defaults to the client's project.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
str .. rubric:: Example >>> from google.cloud import bigquery >>> client = bigquery.Client() >>> client.get_service_account_email() [e-mail]	service account email address

get_table

get_table(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.table.Table

Fetch the table referenced by table.

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] A reference to the table to fetch from the BigQuery API. If a string is passed in, this method attempts to create a table reference from a string using from_string.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.table.Table	A Table instance.

insert_rows

insert_rows(
    table: typing.Union[
        google.cloud.bigquery.table.Table,
        google.cloud.bigquery.table.TableReference,
        str,
    ],
    rows: typing.Union[
        typing.Iterable[typing.Tuple], typing.Iterable[typing.Mapping[str, typing.Any]]
    ],
    selected_fields: typing.Optional[
        typing.Sequence[google.cloud.bigquery.schema.SchemaField]
    ] = None,
    **kwargs
) -> typing.Sequence[typing.Dict[str, typing.Any]]

Insert rows into a table via the streaming API.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/tabledata/insertAll

BigQuery will reject insertAll payloads that exceed a defined limit (10MB). Additionally, if a payload vastly exceeds this limit, the request is rejected by the intermediate architecture, which returns a 413 (Payload Too Large) status code.

See https://cloud.google.com/bigquery/quotas#streaming_inserts

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, str, ] The destination table for the row data, or a reference to it.
rows	Union[Sequence[Tuple], Sequence[Dict]] Row data to be inserted. If a list of tuples is given, each tuple should contain data for each schema field on the current table and in the same order as the schema fields. If a list of dictionaries is given, the keys must include all required fields in the schema. Keys which do not correspond to a field in the schema are ignored.
selected_fields	Sequence[google.cloud.bigquery.schema.SchemaField] The fields to return. Required if table is a TableReference.
kwargs	dict Keyword arguments to insert_rows_json.

Exceptions
Type	Description
ValueError	if table's schema is not set or rows is not a Sequence.

Returns
Type	Description
Sequence[Mappings]	One mapping per row with insert errors: the "index" key identifies the row, and the "errors" key contains a list of the mappings describing one or more problems with the row.

insert_rows_from_dataframe

insert_rows_from_dataframe(
    table: typing.Union[
        google.cloud.bigquery.table.Table,
        google.cloud.bigquery.table.TableReference,
        str,
    ],
    dataframe,
    selected_fields: typing.Optional[
        typing.Sequence[google.cloud.bigquery.schema.SchemaField]
    ] = None,
    chunk_size: int = 500,
    **kwargs: typing.Dict
) -> typing.Sequence[typing.Sequence[dict]]

Insert rows into a table from a dataframe via the streaming API.

BigQuery will reject insertAll payloads that exceed a defined limit (10MB). Additionally, if a payload vastly exceeds this limit, the request is rejected by the intermediate architecture, which returns a 413 (Payload Too Large) status code.

See https://cloud.google.com/bigquery/quotas#streaming_inserts

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, str, ] The destination table for the row data, or a reference to it.
selected_fields	Sequence[google.cloud.bigquery.schema.SchemaField] The fields to return. Required if table is a TableReference.
chunk_size	int The number of rows to stream in a single chunk. Must be positive.
kwargs	Dict Keyword arguments to insert_rows_json.
dataframe	pandas.DataFrame A pandas.DataFrame containing the data to load. Any NaN values present in the dataframe are omitted from the streaming API request(s).

Exceptions
Type	Description
ValueError	if table's schema is not set

Returns
Type	Description
Sequence[Sequence[Mappings]]	A list with insert errors for each insert chunk. Each element is a list containing one mapping per row with insert errors: the "index" key identifies the row, and the "errors" key contains a list of the mappings describing one or more problems with the row.

insert_rows_json

insert_rows_json(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], json_rows: typing.Sequence[typing.Mapping[str, typing.Any]], row_ids: typing.Optional[typing.Union[typing.Iterable[typing.Optional[str]], google.cloud.bigquery.enums.AutoRowIDs]] = AutoRowIDs.GENERATE_UUID, skip_invalid_rows: typing.Optional[bool] = None, ignore_unknown_values: typing.Optional[bool] = None, template_suffix: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> typing.Sequence[dict]

Insert rows into a table without applying local type conversions.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/tabledata/insertAll

BigQuery will reject insertAll payloads that exceed a defined limit (10MB). Additionally, if a payload vastly exceeds this limit, the request is rejected by the intermediate architecture, which returns a 413 (Payload Too Large) status code.

See https://cloud.google.com/bigquery/quotas#streaming_inserts

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str ] The destination table for the row data, or a reference to it.
json_rows	Sequence[Dict] Row data to be inserted. Keys must match the table schema fields and values must be JSON-compatible representations.
row_ids	Union[Iterable[str], AutoRowIDs, None] Unique IDs, one per row being inserted. An ID can also be None, indicating that an explicit insert ID should not be used for that row. If the argument is omitted altogether, unique IDs are created automatically. .. versionchanged:: 2.21.0 Can also be an iterable, not just a sequence, or an AutoRowIDs enum member. .. deprecated:: 2.21.0 Passing None to explicitly request autogenerating insert IDs is deprecated, use AutoRowIDs.GENERATE_UUID instead.
skip_invalid_rows	Optional[bool] Insert all valid rows of a request, even if invalid rows exist. The default value is False, which causes the entire request to fail if any invalid rows exist.
ignore_unknown_values	Optional[bool] Accept rows that contain values that do not match the schema. The unknown values are ignored. Default is False, which treats unknown values as errors.
template_suffix	Optional[str] Treat name as a template table and provide a suffix. BigQuery will create the table based on the schema of the template table. See https://cloud.google.com/bigquery/streaming-data-into-bigquery#template-tables
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Exceptions
Type	Description
TypeError	if json_rows is not a Sequence.

Returns
Type	Description
Sequence[Mappings]	One mapping per row with insert errors: the "index" key identifies the row, and the "errors" key contains a list of the mappings describing one or more problems with the row.

job_from_resource

job_from_resource(
    resource: dict,
) -> typing.Union[
    google.cloud.bigquery.job.copy_.CopyJob,
    google.cloud.bigquery.job.extract.ExtractJob,
    google.cloud.bigquery.job.load.LoadJob,
    google.cloud.bigquery.job.query.QueryJob,
    google.cloud.bigquery.job.base.UnknownJob,
]

Detect correct job type from resource and instantiate.

Parameter
Name	Description
resource	Dict one job resource from API response

Returns
Type	Description
Union[job.CopyJob, job.ExtractJob, job.LoadJob, job.QueryJob, job.UnknownJob]	The job instance, constructed via the resource.

list_datasets

list_datasets(project: typing.Optional[str] = None, include_all: bool = False, filter: typing.Optional[str] = None, max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, page_size: typing.Optional[int] = None) -> google.api_core.page_iterator.Iterator

List datasets for the project associated with this client.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list

Parameters
Name	Description
project	Optional[str] Project ID to use for retreiving datasets. Defaults to the client's project.
include_all	Optional[bool] True if results include hidden datasets. Defaults to False.
filter	Optional[str] An expression for filtering the results by label. For syntax, see https://cloud.google.com/bigquery/docs/reference/rest/v2/datasets/list#body.QUERY_PARAMETERS.filter
max_results	Optional[int] Maximum number of datasets to return.
page_token	Optional[str] Token representing a cursor into the datasets. If not passed, the API will return the first page of datasets. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of the google.api_core.page_iterator.HTTPIterator.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
page_size	Optional[int] Maximum number of datasets to return per page.

Returns
Type	Description
google.api_core.page_iterator.Iterator	Iterator of DatasetListItem. associated with the project.

list_jobs

list_jobs(project: typing.Optional[str] = None, parent_job: typing.Optional[typing.Union[google.cloud.bigquery.job.query.QueryJob, str]] = None, max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, all_users: typing.Optional[bool] = None, state_filter: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, min_creation_time: typing.Optional[datetime.datetime] = None, max_creation_time: typing.Optional[datetime.datetime] = None, page_size: typing.Optional[int] = None) -> google.api_core.page_iterator.Iterator

List jobs for the project associated with this client.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/list

Parameters
Name	Description
project	Optional[str] Project ID to use for retreiving datasets. Defaults to the client's project.
parent_job	Optional[Union[ google.cloud.bigquery.job._AsyncJob, str, ]] If set, retrieve only child jobs of the specified parent.
max_results	Optional[int] Maximum number of jobs to return.
page_token	Optional[str] Opaque marker for the next "page" of jobs. If not passed, the API will return the first page of jobs. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of google.api_core.page_iterator.HTTPIterator.
all_users	Optional[bool] If true, include jobs owned by all users in the project. Defaults to :data:False.
state_filter	Optional[str] If set, include only jobs matching the given state. One of: * "done" * "pending" * "running"
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
min_creation_time	Optional[datetime.datetime] Min value for job creation time. If set, only jobs created after or at this timestamp are returned. If the datetime has no time zone assumes UTC time.
max_creation_time	Optional[datetime.datetime] Max value for job creation time. If set, only jobs created before or at this timestamp are returned. If the datetime has no time zone assumes UTC time.
page_size	Optional[int] Maximum number of jobs to return per page.

Returns
Type	Description
google.api_core.page_iterator.Iterator	Iterable of job instances.

list_models

list_models(dataset: typing.Union[google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str], max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, page_size: typing.Optional[int] = None) -> google.api_core.page_iterator.Iterator

[Beta] List models in the dataset.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/models/list

Parameters
Name	Description
dataset	Union[ google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str, ] A reference to the dataset whose models to list from the BigQuery API. If a string is passed in, this method attempts to create a dataset reference from a string using from_string.
max_results	Optional[int] Maximum number of models to return. Defaults to a value set by the API.
page_token	Optional[str] Token representing a cursor into the models. If not passed, the API will return the first page of models. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of the google.api_core.page_iterator.HTTPIterator.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
page_size	Optional[int] Returns: google.api_core.page_iterator.Iterator: Iterator of Model contained within the requested dataset. Maximum number of models to return per page. Defaults to a value set by the API.

list_partitions

list_partitions(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> typing.Sequence[str]

List the partitions in a table.

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] The table or reference from which to get partition info
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry. If multiple requests are made under the hood, timeout applies to each individual request.

Returns
Type	Description
List[str]	A list of the partition ids present in the partitioned table

list_projects

list_projects(max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, page_size: typing.Optional[int] = None) -> google.api_core.page_iterator.Iterator

List projects for the project associated with this client.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/projects/list

Parameters
Name	Description
max_results	Optional[int] Maximum number of projects to return. Defaults to a value set by the API.
page_token	Optional[str] Token representing a cursor into the projects. If not passed, the API will return the first page of projects. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of the google.api_core.page_iterator.HTTPIterator.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
page_size	Optional[int] Maximum number of projects to return in each page. Defaults to a value set by the API.

Returns
Type	Description
google.api_core.page_iterator.Iterator	Iterator of Project accessible to the current client.

list_routines

list_routines(dataset: typing.Union[google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str], max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, page_size: typing.Optional[int] = None) -> google.api_core.page_iterator.Iterator

[Beta] List routines in the dataset.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/routines/list

Parameters
Name	Description
dataset	Union[ google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str, ] A reference to the dataset whose routines to list from the BigQuery API. If a string is passed in, this method attempts to create a dataset reference from a string using from_string.
max_results	Optional[int] Maximum number of routines to return. Defaults to a value set by the API.
page_token	Optional[str] Token representing a cursor into the routines. If not passed, the API will return the first page of routines. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of the google.api_core.page_iterator.HTTPIterator.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
page_size	Optional[int] Returns: google.api_core.page_iterator.Iterator: Iterator of all Routines contained within the requested dataset, limited by max_results. Maximum number of routines to return per page. Defaults to a value set by the API.

list_rows

list_rows(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableListItem, google.cloud.bigquery.table.TableReference, str], selected_fields: typing.Optional[typing.Sequence[google.cloud.bigquery.schema.SchemaField]] = None, max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, start_index: typing.Optional[int] = None, page_size: typing.Optional[int] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.table.RowIterator

List the rows of the table.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/tabledata/list

Note: This method assumes that the provided schema is up-to-date with the schema as defined on the back-end: if the two schemas are not identical, the values returned may be incomplete. To ensure that the local copy of the schema is up-to-date, call client.get_table.

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableListItem, google.cloud.bigquery.table.TableReference, str, ] The table to list, or a reference to it. When the table object does not contain a schema and selected_fields is not supplied, this method calls get_table to fetch the table schema.
selected_fields	Sequence[google.cloud.bigquery.schema.SchemaField] The fields to return. If not supplied, data for all columns are downloaded.
max_results	Optional[int] Maximum number of rows to return.
page_token	Optional[str] Token representing a cursor into the table's rows. If not passed, the API will return the first page of the rows. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of the RowIterator.
start_index	Optional[int] The zero-based index of the starting row to read.
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.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry. If multiple requests are made under the hood, timeout applies to each individual request.

Returns
Type	Description
google.cloud.bigquery.table.RowIterator	Iterator of row data Row-s. During each page, the iterator will have the total_rows attribute set, which counts the total number of rows **in the table** (this is distinct from the total number of rows in the current page: iterator.page.num_items).

list_tables

list_tables(dataset: typing.Union[google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str], max_results: typing.Optional[int] = None, page_token: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, page_size: typing.Optional[int] = None) -> google.api_core.page_iterator.Iterator

List tables in the dataset.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/list

Parameters
Name	Description
dataset	Union[ google.cloud.bigquery.dataset.Dataset, google.cloud.bigquery.dataset.DatasetReference, google.cloud.bigquery.dataset.DatasetListItem, str, ] A reference to the dataset whose tables to list from the BigQuery API. If a string is passed in, this method attempts to create a dataset reference from a string using from_string.
max_results	Optional[int] Maximum number of tables to return. Defaults to a value set by the API.
page_token	Optional[str] Token representing a cursor into the tables. If not passed, the API will return the first page of tables. The token marks the beginning of the iterator to be returned and the value of the page_token can be accessed at next_page_token of the google.api_core.page_iterator.HTTPIterator.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
page_size	Optional[int] Maximum number of tables to return per page. Defaults to a value set by the API.

Returns
Type	Description
google.api_core.page_iterator.Iterator	Iterator of TableListItem contained within the requested dataset.

load_table_from_dataframe

load_table_from_dataframe(
    dataframe: pandas.DataFrame,
    destination: typing.Union[
        google.cloud.bigquery.table.Table,
        google.cloud.bigquery.table.TableReference,
        str,
    ],
    num_retries: int = 6,
    job_id: typing.Optional[str] = None,
    job_id_prefix: typing.Optional[str] = None,
    location: typing.Optional[str] = None,
    project: typing.Optional[str] = None,
    job_config: typing.Optional[google.cloud.bigquery.job.load.LoadJobConfig] = None,
    parquet_compression: str = "snappy",
    timeout: typing.Union[None, float, typing.Tuple[float, float]] = None,
) -> google.cloud.bigquery.job.load.LoadJob

Upload the contents of a table from a pandas DataFrame.

Similar to load_table_from_uri, this method creates, starts and returns a xref_LoadJob.

Note: REPEATED fields are NOT supported when using the CSV source format. They are supported when using the PARQUET source format, but due to the way they are encoded in the parquet file, a mismatch with the existing table schema can occur, so REPEATED fields are not properly supported when using pyarrow<4.0.0 using the parquet format. https://github.com/googleapis/python-bigquery/issues/19

Parameters
Name	Description
destination	Union[ Table, TableReference, str ] The destination table to use for loading the data. If it is an existing table, the schema of the pandas.DataFrame must match the schema of the destination table. If the table does not yet exist, the schema is inferred from the pandas.DataFrame. If a string is passed in, this method attempts to create a table reference from a string using from_string.
num_retries	Optional[int] Number of upload retries. Defaults to 6.
job_id	Optional[str] Name of the job.
job_id_prefix	Optional[str] The user-provided prefix for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
job_config	Optional[LoadJobConfig] Extra configuration options for the job. To override the default pandas data type conversions, supply a value for schema with column names matching those of the dataframe. The BigQuery schema is used to determine the correct data type conversion. Indexes are not loaded. By default, this method uses the parquet source format. To override this, supply a value for source_format with the format name. Currently only CSV and PARQUET are supported.
parquet_compression	Optional[str] [Beta] The compression method to use if intermittently serializing dataframe to a parquet file. Defaults to "snappy". The argument is directly passed as the compression argument to the underlying pyarrow.parquet.write_table() method (the default value "snappy" gets converted to uppercase). https://arrow.apache.org/docs/python/generated/pyarrow.parquet.write_table.html#pyarrow-parquet-write-table If the job config schema is missing, the argument is directly passed as the compression argument to the underlying DataFrame.to_parquet() method. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_parquet.html#pandas.DataFrame.to_parquet
timeout	Optional[flaot] The number of seconds to wait for the underlying HTTP transport before using retry. Depending on the retry strategy, a request may be repeated several times using the same timeout each time. Defaults to None. Can also be passed as a tuple (connect_timeout, read_timeout). See requests.Session.request documentation for details.
dataframe	pandas.Dataframe A pandas.DataFrame containing the data to load.

Exceptions
Type	Description
ValueError	If a usable parquet engine cannot be found. This method requires pyarrow to be installed.
TypeError	If job_config is not an instance of LoadJobConfig class.

Returns
Type	Description
google.cloud.bigquery.job.LoadJob	A new load job.

load_table_from_file

load_table_from_file(
    file_obj: typing.IO[bytes],
    destination: typing.Union[
        google.cloud.bigquery.table.Table,
        google.cloud.bigquery.table.TableReference,
        google.cloud.bigquery.table.TableListItem,
        str,
    ],
    rewind: bool = False,
    size: typing.Optional[int] = None,
    num_retries: int = 6,
    job_id: typing.Optional[str] = None,
    job_id_prefix: typing.Optional[str] = None,
    location: typing.Optional[str] = None,
    project: typing.Optional[str] = None,
    job_config: typing.Optional[google.cloud.bigquery.job.load.LoadJobConfig] = None,
    timeout: typing.Union[None, float, typing.Tuple[float, float]] = None,
) -> google.cloud.bigquery.job.load.LoadJob

Upload the contents of this table from a file-like object.

Similar to load_table_from_uri, this method creates, starts and returns a xref_LoadJob.

Parameters
Name	Description
file_obj	IO[bytes] A file handle opened in binary mode for reading.
destination	Union[Table, TableReference, TableListItem, str ] Table into which data is to be loaded. If a string is passed in, this method attempts to create a table reference from a string using from_string.
rewind	Optional[bool] If True, seek to the beginning of the file handle before reading the file. Defaults to False.
size	Optional[int] The number of bytes to read from the file handle. If size is None or large, resumable upload will be used. Otherwise, multipart upload will be used.
num_retries	Optional[int] Number of upload retries. Defaults to 6.
job_id	Optional[str] Name of the job.
job_id_prefix	Optional[str] The user-provided prefix for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
job_config	Optional[LoadJobConfig] Extra configuration options for the job.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry. Depending on the retry strategy, a request may be repeated several times using the same timeout each time. Defaults to None. Can also be passed as a tuple (connect_timeout, read_timeout). See requests.Session.request documentation for details.

Exceptions
Type	Description
ValueError	If size is not passed in and can not be determined, or if the file_obj can be detected to be a file opened in text mode.
TypeError	If job_config is not an instance of LoadJobConfig class.

Returns
Type	Description
google.cloud.bigquery.job.LoadJob	A new load job.

load_table_from_json

load_table_from_json(
    json_rows: typing.Iterable[typing.Dict[str, typing.Any]],
    destination: typing.Union[
        google.cloud.bigquery.table.Table,
        google.cloud.bigquery.table.TableReference,
        google.cloud.bigquery.table.TableListItem,
        str,
    ],
    num_retries: int = 6,
    job_id: typing.Optional[str] = None,
    job_id_prefix: typing.Optional[str] = None,
    location: typing.Optional[str] = None,
    project: typing.Optional[str] = None,
    job_config: typing.Optional[google.cloud.bigquery.job.load.LoadJobConfig] = None,
    timeout: typing.Union[None, float, typing.Tuple[float, float]] = None,
) -> google.cloud.bigquery.job.load.LoadJob

Upload the contents of a table from a JSON string or dict.

Parameters
Name	Description
json_rows	Iterable[Dict[str, Any]] Row data to be inserted. Keys must match the table schema fields and values must be JSON-compatible representations. .. note:: If your data is already a newline-delimited JSON string, it is best to wrap it into a file-like object and pass it to load_table_from_file:: import io from google.cloud import bigquery data = u'{"foo": "bar"}' data_as_file = io.StringIO(data) client = bigquery.Client() client.load_table_from_file(data_as_file, ...)
destination	Union[ Table, TableReference, TableListItem, str ] Table into which data is to be loaded. If a string is passed in, this method attempts to create a table reference from a string using from_string.
num_retries	Optional[int] Number of upload retries. Defaults to 6.
job_id	Optional[str] Name of the job.
job_id_prefix	Optional[str] The user-provided prefix for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
job_config	Optional[LoadJobConfig] Extra configuration options for the job. The source_format setting is always set to NEWLINE_DELIMITED_JSON.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry. Depending on the retry strategy, a request may be repeated several times using the same timeout each time. Defaults to None. Can also be passed as a tuple (connect_timeout, read_timeout). See requests.Session.request documentation for details.

Exceptions
Type	Description
TypeError	If job_config is not an instance of LoadJobConfig class.

Returns
Type	Description
google.cloud.bigquery.job.LoadJob	A new load job.

load_table_from_uri

load_table_from_uri(source_uris: typing.Union[str, typing.Sequence[str]], destination: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], job_id: typing.Optional[str] = None, job_id_prefix: typing.Optional[str] = None, location: typing.Optional[str] = None, project: typing.Optional[str] = None, job_config: typing.Optional[google.cloud.bigquery.job.load.LoadJobConfig] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.job.load.LoadJob

Starts a job for loading data into a table from Cloud Storage.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfigurationload

Parameters
Name	Description
source_uris	Union[str, Sequence[str]] URIs of data files to be loaded; in format gs://<bucket_name>/<object_name_or_glob>.
destination	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] Table into which data is to be loaded. If a string is passed in, this method attempts to create a table reference from a string using from_string.
job_id	Optional[str] Name of the job.
job_id_prefix	Optional[str] The user-provided prefix for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
job_config	Optional[google.cloud.bigquery.job.LoadJobConfig] Extra configuration options for the job.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Exceptions
Type	Description
TypeError	If job_config is not an instance of LoadJobConfig class.

Returns
Type	Description
google.cloud.bigquery.job.LoadJob	A new load job.

query

query(query: str, job_config: typing.Optional[google.cloud.bigquery.job.query.QueryJobConfig] = None, job_id: typing.Optional[str] = None, job_id_prefix: typing.Optional[str] = None, location: typing.Optional[str] = None, project: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, job_retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, api_method: typing.Union[str, google.cloud.bigquery.enums.QueryApiMethod] = QueryApiMethod.INSERT) -> google.cloud.bigquery.job.query.QueryJob

Run a SQL query.

See https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfigurationquery

Parameters
Name	Description
query	str SQL query to be executed. Defaults to the standard SQL dialect. Use the job_config parameter to change dialects.
job_config	Optional[google.cloud.bigquery.job.QueryJobConfig] Extra configuration options for the job. To override any options that were previously set in the default_query_job_config given to the Client constructor, manually set those options to None, or whatever value is preferred.
job_id	Optional[str] ID to use for the query job.
job_id_prefix	Optional[str] The prefix to use for a randomly generated job ID. This parameter will be ignored if a job_id is also given.
location	Optional[str] Location where to run the job. Must match the location of the table used in the query as well as the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC. This only applies to making RPC calls. It isn't used to retry failed jobs. This has a reasonable default that should only be overridden with care.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
job_retry	Optional[google.api_core.retry.Retry] How to retry failed jobs. The default retries rate-limit-exceeded errors. Passing None disables job retry. Not all jobs can be retried. If job_id is provided, then the job returned by the query will not be retryable, and an exception will be raised if a non-None (and non-default) value for job_retry is also provided. Note that errors aren't detected until result() is called on the job returned. The job_retry specified here becomes the default job_retry for result(), where it can also be specified.
api_method	Union[str, enums.QueryApiMethod] Method with which to start the query job. See QueryApiMethod for details on the difference between the query start methods.

Exceptions
Type	Description
TypeError	If job_config is not an instance of QueryJobConfig class, or if both job_id and non-None non-default job_retry are provided.

Returns
Type	Description
google.cloud.bigquery.job.QueryJob	A new query job instance.

query_and_wait

query_and_wait(query, *, job_config: typing.Optional[google.cloud.bigquery.job.query.QueryJobConfig] = None, location: typing.Optional[str] = None, project: typing.Optional[str] = None, api_timeout: typing.Optional[float] = None, wait_timeout: typing.Optional[float] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, job_retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, page_size: typing.Optional[int] = None, max_results: typing.Optional[int] = None) -> google.cloud.bigquery.table.RowIterator

Run the query, wait for it to finish, and return the results.

While jobCreationMode=JOB_CREATION_OPTIONAL is in preview in the jobs.query REST API, use the default jobCreationMode unless the environment variable QUERY_PREVIEW_ENABLED=true. After jobCreationMode is GA, this method will always use jobCreationMode=JOB_CREATION_OPTIONAL. See: https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query

Parameters
Name	Description
query	str SQL query to be executed. Defaults to the standard SQL dialect. Use the job_config parameter to change dialects.
job_config	Optional[google.cloud.bigquery.job.QueryJobConfig] Extra configuration options for the job. To override any options that were previously set in the default_query_job_config given to the Client constructor, manually set those options to None, or whatever value is preferred.
location	Optional[str] Location where to run the job. Must match the location of the table used in the query as well as the destination table.
project	Optional[str] Project ID of the project of where to run the job. Defaults to the client's project.
api_timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
wait_timeout	Optional[float] The number of seconds to wait for the query to finish. If the query doesn't finish before this timeout, the client attempts to cancel the query.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC. This only applies to making RPC calls. It isn't used to retry failed jobs. This has a reasonable default that should only be overridden with care.
job_retry	Optional[google.api_core.retry.Retry] How to retry failed jobs. The default retries rate-limit-exceeded errors. Passing None disables job retry. Not all jobs can be retried.
page_size	Optional[int] The maximum number of rows in each page of results from this request. Non-positive values are ignored.
max_results	Optional[int] The maximum total number of rows from this request.

Exceptions
Type	Description
TypeError	If job_config is not an instance of QueryJobConfig class.

Returns
Type	Description
google.cloud.bigquery.table.RowIterator	Iterator of row data Row-s. During each page, the iterator will have the total_rows attribute set, which counts the total number of rows **in the result set** (this is distinct from the total number of rows in the current page: iterator.page.num_items). If the query is a special query that produces no results, e.g. a DDL query, an _EmptyRowIterator instance is returned.

schema_from_json

schema_from_json(
    file_or_path: PathType,
) -> typing.List[google.cloud.bigquery.schema.SchemaField]

Takes a file object or file path that contains json that describes a table schema.

Returns
Type	Description
List[SchemaField]	List of SchemaField objects.

schema_to_json

schema_to_json(
    schema_list: typing.Sequence[google.cloud.bigquery.schema.SchemaField],
    destination: PathType,
)

Takes a list of schema field objects.

Serializes the list of schema field objects as json to a file.

Destination is a file path or a file object.

set_iam_policy

set_iam_policy(table: typing.Union[google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str], policy: google.api_core.iam.Policy, updateMask: typing.Optional[str] = None, retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None, *, fields: typing.Sequence[str] = ()) -> google.api_core.iam.Policy

Return the access control policy for a table resource.

Parameters
Name	Description
table	Union[ google.cloud.bigquery.table.Table, google.cloud.bigquery.table.TableReference, google.cloud.bigquery.table.TableListItem, str, ] The table to get the access control policy for. If a string is passed in, this method attempts to create a table reference from a string using from_string.
policy	google.api_core.iam.Policy The access control policy to set.
updateMask	Optional[str] Mask as defined by https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/setIamPolicy#body.request_body.FIELDS.update_mask Incompatible with fields.
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.
fields	Sequence[str] Which properties to set on the policy. See: https://cloud.google.com/bigquery/docs/reference/rest/v2/tables/setIamPolicy#body.request_body.FIELDS.update_mask Incompatible with updateMask.

Returns
Type	Description
google.api_core.iam.Policy	The updated access control policy.

update_dataset

update_dataset(dataset: google.cloud.bigquery.dataset.Dataset, fields: typing.Sequence[str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.dataset.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 the dataset on the server has the same ETag. Thus reading a dataset with get_dataset, changing its fields, and then passing it to update_dataset will ensure that the changes will only be saved if no modifications to the dataset occurred since the read.

Parameters
Name	Description
dataset	google.cloud.bigquery.dataset.Dataset The dataset to update.
fields	Sequence[str] The properties of dataset to change. These are strings corresponding to the properties of Dataset. For example, to update the default expiration times, specify both properties in the fields argument: .. code-block:: python bigquery_client.update_dataset( dataset, [ "default_partition_expiration_ms", "default_table_expiration_ms", ] )
retry	Optional[google.api_core.retry.Retry] How to retry the RPC.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.dataset.Dataset	The modified Dataset instance.

update_model

update_model(model: google.cloud.bigquery.model.Model, fields: typing.Sequence[str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.model.Model

[Beta] Change some fields of a model.

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, the field value will be deleted.

If model.etag is not None, the update will only succeed if the model on the server has the same ETag. Thus reading a model with get_model, changing its fields, and then passing it to update_model will ensure that the changes will only be saved if no modifications to the model occurred since the read.

Parameters
Name	Description
model	google.cloud.bigquery.model.Model The model to update.
fields	Sequence[str] The properties of model to change. These are strings corresponding to the properties of Model. For example, to update the descriptive properties of the model, specify them in the fields argument: .. code-block:: python bigquery_client.update_model( model, ["description", "friendly_name"] )
retry	Optional[google.api_core.retry.Retry] A description of how to retry the API call.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.model.Model	The model resource returned from the API call.

update_routine

update_routine(routine: google.cloud.bigquery.routine.routine.Routine, fields: typing.Sequence[str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.routine.routine.Routine

[Beta] Change some fields of a routine.

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 routine, the field value will be deleted.

Warning: During beta, partial updates are not supported. You must provide all fields in the resource.

If xref_etag is not None, the update will only succeed if the resource on the server has the same ETag. Thus reading a routine with xref_get_routine, changing its fields, and then passing it to this method will ensure that the changes will only be saved if no modifications to the resource occurred since the read.

Parameters
Name	Description
routine	google.cloud.bigquery.routine.Routine The routine to update.
fields	Sequence[str] The fields of routine to change, spelled as the Routine properties. For example, to update the description property of the routine, specify it in the fields argument: .. code-block:: python bigquery_client.update_routine( routine, ["description"] )
retry	Optional[google.api_core.retry.Retry] A description of how to retry the API call.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.routine.Routine	The routine resource returned from the API call.

update_table

update_table(table: google.cloud.bigquery.table.Table, fields: typing.Sequence[str], retry: google.api_core.retry.retry_unary.Retry = <google.api_core.retry.retry_unary.Retry object>, timeout: typing.Optional[float] = None) -> google.cloud.bigquery.table.Table

Change some fields of a table.

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, the field value will be deleted.

If table.etag is not None, the update will only succeed if the table on the server has the same ETag. Thus reading a table with get_table, changing its fields, and then passing it to update_table will ensure that the changes will only be saved if no modifications to the table occurred since the read.

Parameters
Name	Description
table	google.cloud.bigquery.table.Table The table to update.
fields	Sequence[str] The fields of table to change, spelled as the Table properties. For example, to update the descriptive properties of the table, specify them in the fields argument: .. code-block:: python bigquery_client.update_table( table, ["description", "friendly_name"] )
retry	Optional[google.api_core.retry.Retry] A description of how to retry the API call.
timeout	Optional[float] The number of seconds to wait for the underlying HTTP transport before using retry.

Returns
Type	Description
google.cloud.bigquery.table.Table	The table resource returned from the API call.