Saravanan666/pypi-org huggingface dataset:
Package: google-cloud-contentwarehouse
Document AI Warehouse:Client Library DocumentationProduct DocumentationQuick StartIn 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 Document AI Warehouse.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-contentwarehouseWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-contentwarehouseNext StepsRead theClient Library Documentationfor Document AI Warehouse
to see other available methods on the client.Read theDocument AI Warehouse Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-core
This library is not meant to stand-alone. Instead it defines
common helpers (e.g. baseClientclasses) used by all of thegoogle-cloud-*packages.DocumentationQuick Start$pipinstall--upgradegoogle-cloud-coreFor more information on setting up your Python development environment,
such as installingpipandvirtualenvon your system, please refer
toPython Development Environment Setup Guidefor Google Cloud Platform.Supported Python VersionsPython >= 3.7Unsupported Python VersionsPython == 2.7: the last version of this library which supported Python 2.7
isgoogle.cloud.core 1.7.2.Python == 3.6: the last version of this library which supported Python 3.6
isgoogle.cloud.core 2.3.1.
Package: google-cloud-datacatalog
Google Cloud Data Catalog: is a fully managed and highly scalable data discovery and metadata management service.Client Library DocumentationProduct DocumentationQuick StartIn 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 Data Catalog.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-datacatalogWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-datacatalogNext StepsRead theClient Library Documentationfor Google Cloud Data Catalog
to see other available methods on the client.Read theGoogle Cloud Data Catalog Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-datacatalog-lineage
Data Lineage API: Data lineage is a Dataplex feature that lets you track how data moves through your systems: where it comes from, where it is passed to, and what transformations are applied to it.Client Library DocumentationProduct DocumentationQuick StartIn 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 Data Lineage API.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-datacatalog-lineageWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-datacatalog-lineageNext StepsRead theClient Library Documentationfor Data Lineage API
to see other available methods on the client.Read theData Lineage API Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-dataflow-client
Dataflow: Unified stream and batch data processing that’s serverless, fast, and cost-effective.Client Library DocumentationProduct DocumentationQuick StartIn 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 Dataflow.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-dataflow-clientWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-dataflow-clientNext StepsRead theClient Library Documentationfor Dataflow
to see other available methods on the client.Read theDataflow Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-dataform
Cloud Dataform:Client Library DocumentationProduct DocumentationQuick StartIn 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 Cloud Dataform.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-dataformWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-dataformNext StepsRead theClient Library Documentationfor Cloud Dataform
to see other available methods on the client.Read theCloud Dataform Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-data-fusion
Cloud Data Fusion: is a fully managed, cloud-native, enterprise data integration service for quickly building and managing data pipelines.Client Library DocumentationProduct DocumentationQuick StartIn 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 Cloud Data Fusion.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-data-fusionWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-data-fusionNext StepsRead theClient Library Documentationfor Cloud Data Fusion
to see other available methods on the client.Read theCloud Data Fusion Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-datalabeling
Google Cloud Data Labeling: is a service that lets you work with human labelers to generate highly accurate labels for a collection of data that you can use to train your machine learning models.Client Library DocumentationProduct DocumentationQuick StartIn 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 Data Labeling.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-datalabelingWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-datalabelingNext StepsRead theClient Library Documentationfor Google Cloud Data Labeling
to see other available methods on the client.Read theGoogle Cloud Data Labeling Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-dataplex
Cloud Dataplex: provides intelligent data fabric that enables organizations to centrally manage, monitor, and govern their data across data lakes, data warehouses, and data marts with consistent controls, providing access to trusted data and powering analytics at scale.Client Library DocumentationProduct DocumentationQuick StartIn 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 Cloud Dataplex.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-dataplexWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-dataplexNext StepsRead theClient Library Documentationfor Cloud Dataplex
to see other available methods on the client.Read theCloud Dataplex Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-dataproc
Google Cloud Dataproc: is a faster, easier, more cost-effective way to run Apache Spark and Apache Hadoop.Client Library DocumentationProduct DocumentationQuick StartIn 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.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-dataprocWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-dataprocNext StepsRead theClient Library Documentationfor Google Cloud Dataproc
to see other available methods on the client.Read theGoogle Cloud Dataproc Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-dataproc-metastore
Dataproc Metastore: is a fully managed, highly available, autoscaled, autohealing, OSS-native metastore service that greatly simplifies technical metadata management. Dataproc Metastore service is based on Apache Hive metastore and serves as a critical component towards enterprise data lakes.Client Library DocumentationProduct DocumentationQuick StartIn 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 Dataproc Metastore.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-dataproc-metastoreWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-dataproc-metastoreNext StepsRead theClient Library Documentationfor Dataproc Metastore
to see other available methods on the client.Read theDataproc Metastore Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-dataproc-momovn
Google Cloud Dataproc API: is a faster, easier, more cost-effective way to run Apache Spark and Apache Hadoop.Client Library DocumentationProduct DocumentationQuick StartIn 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.InstallationInstall this library in avirtualenvusing pip.virtualenvis a tool to
create isolated Python environments. The basic problem it addresses is one of
dependencies and versions, and indirectly permissions.Withvirtualenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install google-cloud-dataproc-momovnWindowspip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install google-cloud-dataproc-momovnNext StepsRead theClient Library Documentationfor Google Cloud Dataproc API
to see other available methods on the client.Read theGoogle Cloud Dataproc API Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-data-qna
Data QnA: Data QnA is a natural language question and answer service for BigQuery data.Client Library DocumentationProduct DocumentationQuick StartIn 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 Data QnA.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-data-qnaWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-data-qnaNext StepsRead theClient Library Documentationfor Data QnA
to see other available methods on the client.Read theData QnA Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.
Package: google-cloud-datastore
Google Cloud Datastore API: is a fully managed, schemaless database for
storing non-relational data. Cloud Datastore automatically scales with
your users and supports ACID transactions, high availability of reads and
writes, strong consistency for reads and ancestor queries, and eventual
consistency for all other queries.Client Library DocumentationProduct DocumentationQuick StartIn 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 Datastore API.Setup Authentication.InstallationInstall this library in a virtual environment usingvenv.venvis 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.Withvenv, it’s possible to install this library without needing system
install permissions, and without clashing with the installed system
dependencies.Code samples and snippetsCode samples and snippets live in thesamples/folder.Supported Python VersionsOur client libraries are compatible with all currentactiveandmaintenanceversions of
Python.Python >= 3.7Unsupported Python VersionsPython <= 3.6If you are using anend-of-lifeversion of Python, we recommend that you update as soon as possible to an actively supported version.Mac/Linuxpython3 -m venv <your-env>
source <your-env>/bin/activate
pip install google-cloud-datastoreWindowspy -m venv <your-env>
.\<your-env>\Scripts\activate
pip install google-cloud-datastoreNext StepsRead theClient Library Documentationfor Google Cloud Datastore API
to see other available methods on the client.Read theGoogle Cloud Datastore API Product documentationto learn
more about the product and see How-to Guides.View thisREADMEto see the full list of Cloud
APIs that we cover.