Devart Python Connector for BigCommerce

Connect BigCommerce with Python applications
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Publisher

Devart

Subcategories

Connectivity Drivers & ETL

About this software

Python Connector for BigCommerce provides a DB-API 2.0 compatible interface to access and modify BigCommerce store data from Python applications. It converts SQL queries into BigCommerce API calls, supports ANSI SQL features, and includes connection pooling and local caching to improve performance. The connector installs from PyPI or a wheel and supports OAuth 2.0 and basic authentication. Supported environments include Windows, macOS (including Apple silicon), and Linux, and it integrates with pandas and SQLAlchemy.

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Devart Python Connector for BigCommerce

Devart Python Connector for BigCommerce
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Benefits

  • SQL access to BigCommerce: Execute ANSI SQL queries that map to BigCommerce API operations.
  • DB-API 2.0 compatible: Implements Python DB-API 2.0 for standard Python database usage patterns.
  • Connection pooling and caching: Supports connection pooling and local caching to improve throughput.
  • Cross-platform support: Available for Windows, macOS (including ARM), and Linux.
  • Easy installation options: Install from PyPI or deploy wheel packages for each platform.

Available languages

  • English

Support information

  • Documentation and guides: Product documentation includes installation, usage examples, and API reference.
  • Installation instructions: Step-by-step install guides for Windows, macOS, and Linux are provided.
  • License activation: Supports license-key activation and subscription license types as documented in release notes.
  • Community forum: A Python Connectors Forum is available for discussion and feedback.
  • Request support: Link to request support is provided on the product documentation pages.

Frequently asked questions

What authentication methods are supported?
OAuth 2.0 and Basic authentication are supported, with example connection parameters provided in the official documentation.
Which Python versions and libraries are supported?
Supports Python 3.7 through 3.13 and integrates with libraries such as SQLAlchemy, pandas, and petl.
How is the connector installed?
Install via pip from PyPI or by installing a downloaded wheel package per platform; installation steps are in the documentation.
Does the connector support SQL query execution?
Yes. The connector supports ANSI SQL; complex queries are transformed into simpler API calls and processed by the local embedded SQL engine.
What platforms does the connector support?
Supported on Windows (32- and 64-bit), Windows Server, macOS (64-bit and ARM), and Linux 64-bit.