:NOTE: This github repository is archived. The repository contents and history have moved to google-cloud-python
_.
.. _google-cloud-python: https://github.com/googleapis/google-cloud-python/tree/main/packages/google-cloud-dataproc
|stable| |pypi| |versions|
Google Cloud Dataproc API
_: is a faster, easier, more cost-effective way to run Apache Spark and Apache Hadoop.
Client Library Documentation
_Product Documentation
_.. |stable| image:: https://img.shields.io/badge/support-stable-gold.svg :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#stability-levels .. |pypi| image:: https://img.shields.io/pypi/v/google-cloud-dataproc.svg :target: https://pypi.org/project/google-cloud-dataproc/ .. |versions| image:: https://img.shields.io/pypi/pyversions/google-cloud-dataproc.svg :target: https://pypi.org/project/google-cloud-dataproc/ .. _Google Cloud Dataproc API: https://cloud.google.com/dataproc .. _Client Library Documentation: https://cloud.google.com/python/docs/reference/dataproc/latest .. _Product Documentation: https://cloud.google.com/dataproc
In order to use this library, you first need to go through the following steps:
Select or create a Cloud Platform project.
_Enable billing for your project.
_Enable the Google Cloud Dataproc API.
_Setup Authentication.
_.. _Select or create a Cloud Platform project.: https://console.cloud.google.com/project .. _Enable billing for your project.: https://cloud.google.com/billing/docs/how-to/modify-project#enable_billing_for_a_project .. _Enable the Google Cloud Dataproc API.: https://cloud.google.com/dataproc .. _Setup Authentication.: https://googleapis.dev/python/google-api-core/latest/auth.html
Installation
Install this library in a virtual environment using `venv`_. `venv`_ is a tool that
creates isolated Python environments. These isolated environments can have separate
versions of Python packages, which allows you to isolate one project's dependencies
from the dependencies of other projects.
With `venv`_, it's possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.
.. _`venv`: https://docs.python.org/3/library/venv.html
Code samples and snippets
Code samples and snippets live in the samples/
_ folder.
.. _samples/: https://github.com/googleapis/python-dataproc/tree/main/samples
Supported Python Versions
^^^^^^^^^^^^^^^^^^^^^^^^^
Our client libraries are compatible with all current active
and maintenance
versions of
Python.
Python >= 3.7
.. _active: https://devguide.python.org/devcycle/#in-development-main-branch .. _maintenance: https://devguide.python.org/devcycle/#maintenance-branches
Unsupported Python Versions ^^^^^^^^^^^^^^^^^^^^^^^^^^^ Python <= 3.6
If you are using an end-of-life
_
version of Python, we recommend that you update as soon as possible to an actively supported version.
.. _end-of-life: https://devguide.python.org/devcycle/#end-of-life-branches
Mac/Linux ^^^^^^^^^
.. code-block:: console
python3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-dataproc
Windows ^^^^^^^
.. code-block:: console
py -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-dataproc
Next Steps
- Read the `Client Library Documentation`_ for Google Cloud Dataproc API
to see other available methods on the client.
- Read the `Google Cloud Dataproc API Product documentation`_ to learn
more about the product and see How-to Guides.
- View this `README`_ to see the full list of Cloud
APIs that we cover.
.. _Google Cloud Dataproc API Product documentation: https://cloud.google.com/dataproc
.. _README: https://github.com/googleapis/google-cloud-python/blob/main/README.rst