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Google Search Console for Python

google-searchconsole takes the pain out of working with the Google Search Console Search Analytics Query API. It is written in Python and provides convenient features to make querying a site's search analytics data easier.

• Authentication. We provide a few different ways to make generating credentials and authenticating with your account easier. You can use stored fies as well as a way to do the OAuth2 flow interactively.
• Querying. Easier to query by date ranges and filter by various dimensions. No longer posting large nested JSON, the query object lets you make complex queries with ease.
• Exploration. You can traverse your account hierarchy, with an account containing webproperties with clear permission levels.
• Exports. Clean JSON and pandas.DataFrame outputs so you can easily analyse your data in Python or Excel.

This package is built on top of Google's own API Client and is heavily inspired, from design to implementation, by @debrouwere's fantastic google-analytics package.

Quickstart

First, install the package using:

pip3 install git+https://github.com/joshcarty/google-searchconsole

Then, create a new project in the Google Developers Console, enable the Google Search Console API under "APIs & Services". Next, create credentials for an OAuth client ID, choosing the Other Application type. Download a JSON copy of your client secrets.

After that, executing your first query is as easy as

import searchconsole
account = searchconsole.authenticate(client_config='client_secrets.json')
webproperty = account['https://www.example.com/']
report = webproperty.query.range('today', days=-7).dimension('query').get()
print(report.rows)

The above example will use your client configuration file to interactively generate your credentials.

Saving Credentials

If you wish to save your credentials, to avoid going through the OAuth consent screen in the future, you can specify a path to save them by specifying serialize='path/to/credentials.json.

When you want to authenticate a new account you run:

account = searchconsole.authenticate(client_config='client_secrets.json',
                                     serialize='credentials.json')

Which will save your credentials to a file called credentials.json.

From then on, you can authenticate with:

account = searchconsole.authenticate(client_config='client_secrets.json',
                                     credentials='credentials.json')

Integration with Pandas DataFrame

If you wish to load your data directly into a pandas DataFrame, to avoid loading it manually after the extraction, you can do it easily:

report = webproperty.query.range('today',days=-7).dimension('page').get().to_dataframe()

Search types

You can specify the search type data you want to retrieve by using the search_type method with your query. The following values are currently supported by the API: news, video, image, web, discover & googleNews. If you don't use this method, the default value used will be web,

report = webproperty.query.search_type('discover').range('today',days=-7).dimension('page').get().to_dataframe()

Filters

You can apply filters while executing a query. The filter types supported by the API are the same available in the UI: contains, equals, notContains, notEquals, includingRegex & excludingRegex.

report = webproperty.query.range('today',days=-7).dimension('page').filter('page','/blog/','contains').get().to_dataframe()

Note that if you use Regex in your filter, you must follow RE2 syntax.