CData Python Connector for Pinterest
The CData Python Connector for Pinterest allows developers to write Python scripts with connectivity to Pinterest. The connector wraps the complexity of accessing Pinterest data in an interface commonly used by python connectors to common database systems.
- A variety of WHL files that accommodate several execution environments after installation with "pip install".
- Supported for Python 3.6 and Python 3.7 (including Anacondas), within both Windows and Linux, whether 64-bit or 32-bit. A wheel for for Python 3.8 distributions on Mac is also available.
- Write and execute SQL queries to fetch data in Pinterest.
- Custom dialect class that enables SQLAlchemy ORM to use this connector.
See Getting Started to install the connector to your python distribution and to create a basic connection to Pinterest.
Using the Python Connector
See Using the Connector for examples of executing basic SELECT, INSERT, UPDATE, DELETE, and EXECUTE queries with the module's provided classes. See to connect Pinterest data to tools such as Pandas.
SQLAlchemy can be leveraged to model the tables in Pinterest with mapped classes. See From SQLAlchemy for instructions for configuring the Python connector with SQLAlchemy.
Pandas' DataFrames can be used alongside the connector to generate analytical graphics. See From Pandas for a guide.
See Schema Discovery to query the provided system tables, which allows users to discover the available tables, views, and stored procedure, alongside additional information about their columns or parameters.
See SQL Compliance for a syntax reference and code examples outlining the supported SQL.
See Caching Data to configure replication and caching for a range of scenarios common to remote data access. Configurations include:
- Autocache: Automatically cache data to a lightweight database. Save data for later offline use or enable fast reporting from the cache.
- Replication: Copy data to local and cloud data stores such as Oracle, SQL Server, Google Cloud SQL, and so on. The replication commands allow for intelligent incremental updates to cached data.
- No caching: Work with remote data only. No local cache file is created.
See Data Model for the available database objects. This section also provides more detailed information on querying specific Pinterest entities.
Connection String Options
The Connection properties describe the various options that can be used to establish a connection.