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Provider package apache-airflow-providers-google for Apache Airflow

Project description

Package apache-airflow-providers-google

Release: 4.1.0rc1

Google services including:

Provider package

This is a provider package for google provider. All classes for this provider package are in airflow.providers.google python package.

You can find package information and changelog for the provider in the documentation.

Installation

You can install this package on top of an existing airflow 2.1+ installation via pip install apache-airflow-providers-google

The package supports the following python versions: 3.6,3.7,3.8,3.9

PIP requirements

PIP package

Version required

apache-airflow

>=2.1.0

PyOpenSSL

google-ads

>=4.0.0,<8.0.0

google-api-core

>=1.25.1,<2.0.0

google-api-python-client

>=1.6.0,<2.0.0

google-auth-httplib2

>=0.0.1

google-auth

>=1.0.0,<2.0.0

google-cloud-automl

>=2.1.0,<3.0.0

google-cloud-bigquery-datatransfer

>=3.0.0,<4.0.0

google-cloud-bigtable

>=1.0.0,<2.0.0

google-cloud-container

>=0.1.1,<2.0.0

google-cloud-datacatalog

>=3.0.0,<4.0.0

google-cloud-dataproc

>=2.2.0,<3.0.0

google-cloud-dlp

>=0.11.0,<2.0.0

google-cloud-kms

>=2.0.0,<3.0.0

google-cloud-language

>=1.1.1,<2.0.0

google-cloud-logging

>=2.1.1,<3.0.0

google-cloud-memcache

>=0.2.0,<1.1.0

google-cloud-monitoring

>=2.0.0,<3.0.0

google-cloud-os-login

>=2.0.0,<3.0.0

google-cloud-pubsub

>=2.0.0,<3.0.0

google-cloud-redis

>=2.0.0,<3.0.0

google-cloud-secret-manager

>=0.2.0,<2.0.0

google-cloud-spanner

>=1.10.0,<2.0.0

google-cloud-speech

>=0.36.3,<2.0.0

google-cloud-storage

>=1.30,<2.0.0

google-cloud-tasks

>=2.0.0,<3.0.0

google-cloud-texttospeech

>=0.4.0,<2.0.0

google-cloud-translate

>=1.5.0,<2.0.0

google-cloud-videointelligence

>=1.7.0,<2.0.0

google-cloud-vision

>=0.35.2,<2.0.0

google-cloud-workflows

>=0.1.0,<2.0.0

grpcio-gcp

>=0.2.2

httpx

json-merge-patch

~=0.2

pandas-gbq

<0.15.0

Cross provider package dependencies

Those are dependencies that might be needed in order to use all the features of the package. You need to install the specified provider packages in order to use them.

You can install such cross-provider dependencies when installing from PyPI. For example:

pip install apache-airflow-providers-google[amazon]

Dependent package

Extra

apache-airflow-providers-amazon

amazon

apache-airflow-providers-apache-beam

apache.beam

apache-airflow-providers-apache-cassandra

apache.cassandra

apache-airflow-providers-cncf-kubernetes

cncf.kubernetes

apache-airflow-providers-facebook

facebook

apache-airflow-providers-microsoft-azure

microsoft.azure

apache-airflow-providers-microsoft-mssql

microsoft.mssql

apache-airflow-providers-mysql

mysql

apache-airflow-providers-oracle

oracle

apache-airflow-providers-postgres

postgres

apache-airflow-providers-presto

presto

apache-airflow-providers-salesforce

salesforce

apache-airflow-providers-sftp

sftp

apache-airflow-providers-ssh

ssh

apache-airflow-providers-trino

trino

Changelog

4.1.0

Features

  • Standardise dataproc location param to region (#16034)

Bug Fixes

  • Update alias for field_mask in Google Memmcache (#16975)

4.0.0

Breaking changes

  • Auto-apply apply_default decorator (#15667)

  • Move plyvel to google provider extra (#15812)

  • Fixes AzureFileShare connection extras (#16388)

Features

  • Add extra links for google dataproc (#10343)

  • add oracle connection link (#15632)

  • pass wait_for_done parameter down to _DataflowJobsController (#15541)

  • Use api version only in GoogleAdsHook not operators (#15266)

  • Implement BigQuery Table Schema Update Operator (#15367)

  • Add BigQueryToMsSqlOperator (#15422)

Bug Fixes

  • Fix: GCS To BigQuery source_object (#16160)

  • Fix: Unnecessary downloads in ``GCSToLocalFilesystemOperator (#16171)``

  • Fix bigquery type error when export format is parquet (#16027)

  • Fix argument ordering and type of bucket and object (#15738)

  • Fix sql_to_gcs docstring lint error (#15730)

  • fix: ensure datetime-related values fully compatible with MySQL and BigQuery (#15026)

  • Fix deprecation warnings location in google provider (#16403)

3.0.0

Breaking changes

Change in AutoMLPredictOperator

The params parameter in airflow.providers.google.cloud.operators.automl.AutoMLPredictOperator class was renamed operation_params because it conflicted with a param parameter in the BaseOperator class.

Integration with the apache.beam provider

In 3.0.0 version of the provider we’ve changed the way of integrating with the apache.beam provider. The previous versions of both providers caused conflicts when trying to install them together using PIP > 20.2.4. The conflict is not detected by PIP 20.2.4 and below but it was there and the version of Google BigQuery python client was not matching on both sides. As the result, when both apache.beam and google provider were installed, some features of the BigQuery operators might not work properly. This was cause by apache-beam client not yet supporting the new google python clients when apache-beam[gcp] extra was used. The apache-beam[gcp] extra is used by Dataflow operators and while they might work with the newer version of the Google BigQuery python client, it is not guaranteed.

This version introduces additional extra requirement for the apache.beam extra of the google provider and symmetrically the additional requirement for the google extra of the apache.beam provider. Both google and apache.beam provider do not use those extras by default, but you can specify them when installing the providers. The consequence of that is that some functionality of the Dataflow operators might not be available.

Unfortunately the only complete solution to the problem is for the apache.beam to migrate to the new (>=2.0.0) Google Python clients.

This is the extra for the google provider:

extras_require = (
    {
        # ...
        "apache.beam": ["apache-airflow-providers-apache-beam", "apache-beam[gcp]"],
        # ...
    },
)

And likewise this is the extra for the apache.beam provider:

extras_require = ({"google": ["apache-airflow-providers-google", "apache-beam[gcp]"]},)

You can still run this with PIP version <= 20.2.4 and go back to the previous behaviour:

pip install apache-airflow-providers-google[apache.beam]

or

pip install apache-airflow-providers-apache-beam[google]

But be aware that some BigQuery operators functionality might not be available in this case.

Features

  • [Airflow-15245] - passing custom image family name to the DataProcClusterCreateoperator (#15250)

Bug Fixes

  • Bugfix: Fix rendering of ''object_name'' in ''GCSToLocalFilesystemOperator'' (#15487)

  • Fix typo in DataprocCreateClusterOperator (#15462)

  • Fixes wrongly specified path for leveldb hook (#15453)

2.2.0

Features

  • Adds 'Trino' provider (with lower memory footprint for tests) (#15187)

  • update remaining old import paths of operators (#15127)

  • Override project in dataprocSubmitJobOperator (#14981)

  • GCS to BigQuery Transfer Operator with Labels and Description parameter (#14881)

  • Add GCS timespan transform operator (#13996)

  • Add job labels to bigquery check operators. (#14685)

  • Use libyaml C library when available. (#14577)

  • Add Google leveldb hook and operator (#13109) (#14105)

Bug fixes

  • Google Dataflow Hook to handle no Job Type (#14914)

2.1.0

Features

  • Corrects order of argument in docstring in GCSHook.download method (#14497)

  • Refactor SQL/BigQuery/Qubole/Druid Check operators (#12677)

  • Add GoogleDriveToLocalOperator (#14191)

  • Add 'exists_ok' flag to BigQueryCreateEmptyTable(Dataset)Operator (#14026)

  • Add materialized view support for BigQuery (#14201)

  • Add BigQueryUpdateTableOperator (#14149)

  • Add param to CloudDataTransferServiceOperator (#14118)

  • Add gdrive_to_gcs operator, drive sensor, additional functionality to drive hook (#13982)

  • Improve GCSToSFTPOperator paths handling (#11284)

Bug Fixes

  • Fixes to dataproc operators and hook (#14086)

  • #9803 fix bug in copy operation without wildcard (#13919)

2.0.0

Breaking changes

Updated google-cloud-* libraries

This release of the provider package contains third-party library updates, which may require updating your DAG files or custom hooks and operators, if you were using objects from those libraries. Updating of these libraries is necessary to be able to use new features made available by new versions of the libraries and to obtain bug fixes that are only available for new versions of the library.

Details are covered in the UPDATING.md files for each library, but there are some details that you should pay attention to.

Library name

Previous constraints

Current constraints

Upgrade Documentation

google-cloud-automl

>=0.4.0,<2.0.0

>=2.1.0,<3.0.0

Upgrading google-cloud-automl

google-cloud-bigquery-datatransfer

>=0.4.0,<2.0.0

>=3.0.0,<4.0.0

Upgrading google-cloud-bigquery-datatransfer

google-cloud-datacatalog

>=0.5.0,<0.8

>=3.0.0,<4.0.0

Upgrading google-cloud-datacatalog

google-cloud-dataproc

>=1.0.1,<2.0.0

>=2.2.0,<3.0.0

Upgrading google-cloud-dataproc

google-cloud-kms

>=1.2.1,<2.0.0

>=2.0.0,<3.0.0

Upgrading google-cloud-kms

google-cloud-logging

>=1.14.0,<2.0.0

>=2.0.0,<3.0.0

Upgrading google-cloud-logging

google-cloud-monitoring

>=0.34.0,<2.0.0

>=2.0.0,<3.0.0

Upgrading google-cloud-monitoring

google-cloud-os-login

>=1.0.0,<2.0.0

>=2.0.0,<3.0.0

Upgrading google-cloud-os-login

google-cloud-pubsub

>=1.0.0,<2.0.0

>=2.0.0,<3.0.0

Upgrading google-cloud-pubsub

google-cloud-tasks

>=1.2.1,<2.0.0

>=2.0.0,<3.0.0

Upgrading google-cloud-task

The field names use the snake_case convention

If your DAG uses an object from the above mentioned libraries passed by XCom, it is necessary to update the naming convention of the fields that are read. Previously, the fields used the CamelSnake convention, now the snake_case convention is used.

Before:

set_acl_permission = GCSBucketCreateAclEntryOperator(
    task_id="gcs-set-acl-permission",
    bucket=BUCKET_NAME,
    entity="user-{{ task_instance.xcom_pull('get-instance')['persistenceIamIdentity']"
    ".split(':', 2)[1] }}",
    role="OWNER",
)

After:

set_acl_permission = GCSBucketCreateAclEntryOperator(
    task_id="gcs-set-acl-permission",
    bucket=BUCKET_NAME,
    entity="user-{{ task_instance.xcom_pull('get-instance')['persistence_iam_identity']"
    ".split(':', 2)[1] }}",
    role="OWNER",
)

Features

  • Add Apache Beam operators (#12814)

  • Add Google Cloud Workflows Operators (#13366)

  • Replace 'google_cloud_storage_conn_id' by 'gcp_conn_id' when using 'GCSHook' (#13851)

  • Add How To Guide for Dataflow (#13461)

  • Generalize MLEngineStartTrainingJobOperator to custom images (#13318)

  • Add Parquet data type to BaseSQLToGCSOperator (#13359)

  • Add DataprocCreateWorkflowTemplateOperator (#13338)

  • Add OracleToGCS Transfer (#13246)

  • Add timeout option to gcs hook methods. (#13156)

  • Add regional support to dataproc workflow template operators (#12907)

  • Add project_id to client inside BigQuery hook update_table method (#13018)

Bug fixes

  • Fix four bugs in StackdriverTaskHandler (#13784)

  • Decode Remote Google Logs (#13115)

  • Fix and improve GCP BigTable hook and system test (#13896)

  • updated Google DV360 Hook to fix SDF issue (#13703)

  • Fix insert_all method of BigQueryHook to support tables without schema (#13138)

  • Fix Google BigQueryHook method get_schema() (#13136)

  • Fix Data Catalog operators (#13096)

1.0.0

Initial version of the provider.

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