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.

3.0.0 Migration Guide

New Required Dependencies

Some of the previously optional dependencies are now required in 3.x versions of the library, namely google-cloud-bigquery-storage (minimum version 2.0.0) and pyarrow (minimum version 3.0.0).

The behavior of some of the package “extras” has thus also changed:

  • The pandas extra now requires the db-types package.

  • The bqstorage extra has been preserved for comaptibility reasons, but it is now a no-op and should be omitted when installing the BigQuery client library.

    Before:

    $ pip install google-cloud-bigquery[bqstorage]

    After:

    $ pip install google-cloud-bigquery

  • The bignumeric_type extra has been removed, as BIGNUMERIC type is now automatically supported. That extra should thus not be used.

    Before:

    $ pip install google-cloud-bigquery[bignumeric_type]

    After:

    $ pip install google-cloud-bigquery

Type Annotations

The library is now type-annotated and declares itself as such. If you use a static type checker such as mypy, you might start getting errors in places where google-cloud-bigquery package is used.

It is recommended to update your code and/or type annotations to fix these errors, but if this is not feasible in the short term, you can temporarily ignore type annotations in google-cloud-bigquery, for example by using a special # type: ignore comment:

from google.cloud import bigquery  # type: ignore

But again, this is only recommended as a possible short-term workaround if immediately fixing the type check errors in your project is not feasible.

Re-organized Types

The auto-generated parts of the library has been removed, and proto-based types formerly found in google.cloud.bigquery_v2 have been replaced by the new implementation (but see the section below).

For example, the standard SQL data types should new be imported from a new location:

Before:

from google.cloud.bigquery_v2 import StandardSqlDataType
from google.cloud.bigquery_v2.types import StandardSqlField
from google.cloud.bigquery_v2.types.standard_sql import StandardSqlStructType

After:

from google.cloud.bigquery import StandardSqlDataType
from google.cloud.bigquery.standard_sql import StandardSqlField
from google.cloud.bigquery.standard_sql import StandardSqlStructType

The TypeKind enum defining all possible SQL types for schema fields has been renamed and is not nested anymore under StandardSqlDataType:

Before:

from google.cloud.bigquery_v2 import StandardSqlDataType

if field_type == StandardSqlDataType.TypeKind.STRING:
    ...

After:


from google.cloud.bigquery import StandardSqlTypeNames

if field_type == StandardSqlTypeNames.STRING:
    ...

Issuing queries with Client.create_job preserves destination table

The Client.create_job method no longer removes the destination table from a query job’s configuration. Destination table for the query can thus be explicitly defined by the user.

Changes to data types when reading a pandas DataFrame

The default dtypes returned by the to_dataframe method have changed.

  • Now, the BigQuery BOOLEAN data type maps to the pandas boolean dtype. Previously, this mapped to the pandas bool dtype when the column did not contain NULL values and the pandas object dtype when NULL values are present.

  • Now, the BigQuery INT64 data type maps to the pandas Int64 dtype. Previously, this mapped to the pandas int64 dtype when the column did not contain NULL values and the pandas float64 dtype when NULL values are present.

  • Now, the BigQuery DATE data type maps to the pandas dbdate dtype, which is provided by the db-dtypes package. If any date value is outside of the range of pandas.Timestamp.min (1677-09-22) and pandas.Timestamp.max (2262-04-11), the data type maps to the pandas object dtype. The date_as_object parameter has been removed.

  • Now, the BigQuery TIME data type maps to the pandas dbtime dtype, which is provided by the db-dtypes package.

Changes to data types loading a pandas DataFrame

In the absence of schema information, pandas columns with naive datetime64[ns] values, i.e. without timezone information, are recognized and loaded using the DATETIME type. On the other hand, for columns with timezone-aware datetime64[ns, UTC] values, the TIMESTAMP type is continued to be used.

Changes to Model, Client.get_model, Client.update_model, and Client.list_models

The types of several Model properties have been changed.

  • Model.feature_columns now returns a sequence of google.cloud.bigquery.standard_sql.StandardSqlField.

  • Model.label_columns now returns a sequence of google.cloud.bigquery.standard_sql.StandardSqlField.

  • Model.model_type now returns a string.

  • Model.training_runs now returns a sequence of dictionaries, as recieved from the BigQuery REST API.

Legacy Protocol Buffers Types

For compatibility reasons, the legacy proto-based types still exists as static code and can be imported:

from google.cloud.bigquery_v2 import Model  # a sublcass of proto.Message

Mind, however, that importing them will issue a warning, because aside from being importable, these types are not maintained anymore. They may differ both from the types in google.cloud.bigquery, and from the types supported on the backend.

Maintaining compatibility with google-cloud-bigquery version 2.0

If you maintain a library or system that needs to support both google-cloud-bigquery version 2.x and 3.x, it is recommended that you detect when version 2.x is in use and convert properties that use the legacy protocol buffer types, such as Model.training_runs, into the types used in 3.x.

Call the to_dict method on the protocol buffers objects to get a JSON-compatible dictionary.

from google.cloud.bigquery_v2 import Model

training_run: Model.TrainingRun = ...
training_run_dict = training_run.to_dict()

2.0.0 Migration Guide

The 2.0 release of the google-cloud-bigquery client drops support for Python versions below 3.6. The client surface itself has not changed, but the 1.x series will not be receiving any more feature updates or bug fixes. You are thus encouraged to upgrade to the 2.x series.

If you experience issues or have questions, please file an issue.

Supported Python Versions

WARNING: Breaking change

The 2.0.0 release requires Python 3.6+.

Supported BigQuery Storage Clients

The 2.0.0 release requires BigQuery Storage >= 2.0.0, which dropped support for v1beta1 and v1beta2 versions of the BigQuery Storage API. If you want to use a BigQuery Storage client, it must be the one supporting the v1 API version.

Changed GAPIC Enums Path

WARNING: Breaking change

Generated GAPIC enum types have been moved under types. Import paths need to be adjusted.

Before:

from google.cloud.bigquery_v2.gapic import enums

distance_type = enums.Model.DistanceType.COSINE

After:

from google.cloud.bigquery_v2 import types

distance_type = types.Model.DistanceType.COSINE