/googleads-python-lib

The Python client library for Google's Ads APIs

Primary LanguagePythonApache License 2.0Apache-2.0

The googleads Python client library

This client library simplifies accessing Google's SOAP Ads APIs - AdWords, and DoubleClick for Publishers. The library provides easy ways to store your authentication and create SOAP web service clients. It also contains example code to help you get started integrating with our APIs.

The Google AdWords API will sunset on April 27, 2022.
Upgrade to the Google Ads API.

NOTE: As of v20.0.0 this library is not compatible with Python versions less than Python 3.6. Also suds is no longer supported in this library, zeep is now the only supported SOAP client.

Getting started

  1. Download and install the library

    setuptools is a pre-requisite for installing the googleads library

    It is recommended that you install the library and its dependencies from PyPI using pip. This can be accomplished with a single command:

    $ pip install googleads

    As an alternative, you can download the library as a tarball. To start the installation, navigate to the directory that contains your downloaded unzipped client library and run the "setup.py" script as follows:

    $ python setup.py build install

  2. Copy the googleads.yaml file to your home directory.

    This will be used to store credentials and other settings that can be loaded to initialize a client.

  3. Set up your OAuth2 credentials

    The AdWords and DoubleClick for Publishers APIs use OAuth2 as the authentication mechanism. Follow the appropriate guide below based on your use case.

    If you're accessing an API using your own credentials...

    If you're accessing an API on behalf of clients...

Where can I find samples?

You can find code examples for the latest versions of AdWords or Ad Manager on the releases page.

Alternatively, you can find AdWords or Ad Manager samples in the examples directory of this repository.

Where can I find the pydocs?

Our pydocs can be found here.

Caching authentication information

It is possible to cache your API authentication information. The library includes a sample file showing how to do this named googleads.yaml. Fill in the fields for the API and features you plan to use. The library's LoadFromStorage methods default to looking for a file with this name in your home directory, but you can pass in a path to any file with the correct yaml contents.

# Use the default location - your home directory:
adwords_client = adwords.AdWordsClient.LoadFromStorage()

# Alternatively, pass in the location of the file:
ad_manager_client = ad_manager.AdManagerClient.LoadFromStorage('C:\My\Directory\googleads.yaml')

How do I change the Client Customer Id at runtime?

You can change the Client Customer Id with the following:

adwords_client = AdWordsClient.LoadFromStorage()
adwords_client.SetClientCustomerId('my_client_customer_id')

Where do I submit bug reports and/or feature requests?

If you have issues directly related to the client library, use the issue tracker.

If you have issues pertaining to a specific API, use the product support forums:

How do I log SOAP interactions?

The library uses Python's built in logging framework. You can specify your configuration via the configuration file; see googleads.yaml for an example.

Alternatively, you can manually specify your logging configuration. For example, if you want to log your SOAP interactions to stdout, and you are using the Zeep soap library, you can do the following:

logging.basicConfig(level=logging.INFO, format=googleads.util.LOGGER_FORMAT)
logging.getLogger('googleads.soap').setLevel(logging.DEBUG)

If you wish to log to a file, you'll need to attach a log handler to this source which is configured to write the output to a file.

How do I disable log filters?

The zeep plugin used for logging strips sensitive data from its output. If you would like this data included in logs, you'll need to implement your own simple logging plugin. For example:

class DangerousZeepLogger(zeep.Plugin):
  def ingress(self, envelope, http_headers, operation):
    logging.debug('Incoming response: \n%s', etree.tostring(envelope, pretty_print=True))
    return envelope, http_headers

  def egress(self, envelope, http_headers, operation, binding_options):
    logging.debug('Incoming response: \n%s', etree.tostring(envelope, pretty_print=True))
    return envelope, http_headers

adwords_client.zeep_client.plugins.append(DangerousZeepLogger())

How can I configure or disable caching?

By default, clients are cached because reading and digesting the WSDL can be expensive. However, the default caching method requires permission to access a local file system that may not be available in certain hosting environments such as App Engine.

You can pass an implementation of zeep.cache.Base to the AdWordsClient or AdManagerClient initializer to modify the default caching behavior.

For example, configuring a different location and duration of the cache file with zeep

doc_cache = zeep.cache.SqliteCache(path=cache_path)
adwords_client = adwords.AdWordsClient(
  developer_token, oauth2_client, user_agent,
  client_customer_id=client_customer_id, cache=doc_cache)

You can also disable caching in similar fashion with zeep

adwords_client = adwords.AdWordsClient(
  developer_token, oauth2_client, user_agent,
  client_customer_id=client_customer_id,
  cache=googleads.common.ZeepServiceProxy.NO_CACHE)

Requirements

Python Versions

This library only supports Python 3.6+.

External Dependencies:

- httplib2             -- https://pypi.python.org/pypi/httplib2/
- oauth2client         -- https://pypi.python.org/pypi/oauth2client/
- pysocks              -- https://pypi.python.org/pypi/PySocks/
- pytz                 -- https://pypi.python.org/pypi/pytz
- pyYAML               -- https://pypi.python.org/pypi/pyYAML/
- xmltodict            -- https://pypi.python.org/pypi/xmltodict/
- zeep                 -- https://pypi.python.org/pypi/zeep
- mock                 -- https://pypi.python.org/pypi/mock
                          (only needed to run unit tests)
- pyfakefs             -- https://pypi.python.org/pypi/pyfakefs
                          (only needed to run unit tests)

Authors:

Mark Saniscalchi
David Wihl
Ben Karl