Devart Python Connector for Snowflake

Windows Python connector for Snowflake
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Publisher

Devart

About this software

Python Connector for Snowflake provides a Windows wheel package that implements the Python DB API 2.0 for connecting Python applications to the Snowflake data cloud. It supports Python 3.7–3.13 and integrates with SQLAlchemy, pandas, and petl. Features include connection pooling, local caching, batch updates, Unicode handling, and support for Snowflake data types and standard SQL syntax.

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Devart Python Connector for Snowflake

Devart Python Connector for Snowflake
In Stock
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€331.26
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Benefits

  • DB API 2.0 compliance: Implements Python DB API 2.0 for standard database interactions.
  • Windows wheel distribution: Distributed as wheel packages for Windows 32-bit and 64-bit.
  • Data type and SQL support: Supports Snowflake data types and standard SQL syntax.
  • Performance features: Offers connection pooling, local caching, and batch update execution.
  • Ecosystem integration: Works with SQLAlchemy, pandas, and petl for data workflows.

Available languages

  • English

Support information

  • Documentation access: Product documentation and API references are available on Devart's documentation site.
  • License activation: Activation keys are provided after purchase and can be entered using the license.activate() method.
  • Technical support channels: Support and requests can be submitted through Devart's support portal and resources.
  • Updates during subscription: Software updates and improvements are available while the subscription term is active.
  • Community forum: A Python Connectors forum is provided for user discussions and feedback.

Frequently asked questions

What is Devart Python Connector for Snowflake?
A Python connector that enables Python applications to connect to Snowflake, execute SQL queries, retrieve results, and manage database connections.
What common tasks can it perform?
Common tasks include executing SQL queries, fetching result sets, managing connection lifecycles, and integrating Snowflake access into ETL or analytics workflows.
How is it typically used in Python applications?
Used as a database connector within Python code to run SQL, obtain result data structures, and incorporate Snowflake access into scripts, jobs, or services.
Is it suitable for ETL and analytics workflows?
It is intended for programmatic access to Snowflake from Python, making it applicable for ETL, analytics, reporting, and automation tasks that require database queries.