This directory contains samples for Google Cloud Data Catalog. Google Cloud Data Catalog is a fully managed and scalable metadata management service that empowers organizations to quickly discover, manage, and understand all their data in Google Cloud.
This sample requires you to have authentication setup. Refer to the Authentication Getting Started Guide for instructions on setting up credentials for applications.
Clone python-docs-samples and change directory to the sample directory you want to use.
$ git clone https://github.com/GoogleCloudPlatform/python-docs-samples.git
Install pip and virtualenv if you do not already have them. You may want to refer to the Python Development Environment Setup Guide for Google Cloud Platform for instructions.
Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.
$ virtualenv env $ source env/bin/activate
Install the dependencies needed to run the samples.
$ pip install -r requirements.txt
To run this sample:
$ python lookup_entry.py
usage: lookup_entry.py [-h]
project_id
{bigquery-dataset,bigquery-table,pubsub-topic} ...
This application demonstrates how to perform basic operations on entries
with the Cloud Data Catalog API.
For more information, see the README.md under /datacatalog and the
documentation at https://cloud.google.com/data-catalog/docs.
positional arguments:
project_id Your Google Cloud project ID
{bigquery-dataset,bigquery-table,pubsub-topic}
bigquery-dataset Retrieves Data Catalog entry for the given BigQuery
Dataset.
bigquery-table Retrieves Data Catalog entry for the given BigQuery
Table.
pubsub-topic Retrieves Data Catalog entry for the given Pub/Sub
Topic.
optional arguments:
-h, --help show this help message and exit
This sample uses the Google Cloud Client Library for Python. You can read the documentation for more details on API usage and use GitHub to browse the source and report issues.