Google has released version 2 of its Python client library to query the Data Commons platform, which organizes the world’s publicly available statistical data. The library supports custom instances, among other capabilities.
Announced June 26, the Data Commons Python library can be used to explore the Data Common knowledge graph and retrieve statistical data from more than 200 datasets. Available domains include demographics, economy, education, environment, energy, health, and housing. Developers can use the library’s custom instances to programmatically query any public or private instance, whether hosted locally or on the Google Cloud Platform. Developers can use custom instances to seamlessly integrate proprietary datasets with the Data Commons knowledge graph, according to Google.
Based on the V2 REST API, the Data Commons Python library in version 2 supports Pandas dataframe APIs as an integral module, with a single installation package allowing seamless use with other API endpoints in the same client, Google says. API key management and other stateful operations are built into the client class. Integration with Pydantic libraries improves type safety, serialization, and validation. Additionally, multiple response formats are supported, including JSON and Python dictionaries. With the library, developers can map entities from other datasets to entities in Data Commons. The Data Commons Python API client library is hosted on GitHub and available on pypi.org.
