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snowflake-connector-python

The Snowflake Connector for Python is the official Python driver for connecting to Snowflake data warehouses. It provides a DB API 2.0-compliant interface for Python applications without requiring JDBC or ODBC dependencies, and is actively maintained by Snowflake.

Source: GitHub — github.com/snowflakedb/snowflake-connector-python
727
GitHub stars
562
Forks
Python
Primary language
Apache-2.0
License (OSI-approved)

Key facts

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FieldValue
Repositorysnowflakedb/snowflake-connector-python
Ownersnowflakedb
Primary languagePython
LicenseApache-2.0 — OSI-approved
Stars727
Forks562
Open issues107
Latest releasev4.7.0 (2026-07-02)
Last updated2026-07-08
Sourcehttps://github.com/snowflakedb/snowflake-connector-python

What snowflake-connector-python is

A pure Python connector implementing PEP-249 DB API 2.0 specification for Snowflake connectivity, with no external driver dependencies, built on top of Snowflake's sf_mini_core Rust library. Supports Python 3.10+, includes telemetry capabilities (user-configurable), and provides package signature verification via cosign.

Quickstart

Get the snowflake-connector-python source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/snowflakedb/snowflake-connector-python.gitcd snowflake-connector-python# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Python Data Pipeline & ETL Development

Ideal for building Snowflake-native ETL/ELT pipelines, data ingestion scripts, and scheduled batch operations in Python without Java/C++ overhead.

Analytics & BI Application Backends

Suitable for Python web applications, dashboards, and analytics tools that query Snowflake as the primary data source and need lightweight, direct SQL connectivity.

Data Science & ML Feature Engineering

Well-suited for Jupyter notebooks, scikit-learn pipelines, and ML workflows that require direct SQL access to Snowflake for feature extraction and model training.

Implementation considerations

  • Requires Python 3.10 or higher; verify your application runtime meets this baseline.
  • Package supports pip installation across Linux, macOS, and Windows; Docker-based builds available via ci/build_docker.sh.
  • Telemetry is enabled by default; set CLIENT_TELEMETRY_ENABLED session parameter or telemetry_enabled property to False if required by policy.
  • Implements DB API 2.0 standard, so basic cursor/connection patterns are familiar; refer to Snowflake docs for Snowflake-specific features.
  • Build process uses PEP-517 (python -m build); supports package signature verification for security-critical deployments.

When to avoid it — and what to weigh

  • GCP Regional Endpoint Requirements — The connector does not support GCP regional endpoints; if your workload requires Snowflake on GCP with regional endpoint enforcement, this driver is not suitable.
  • Legacy Python Versions — If your environment is constrained to Python < 3.10, this connector cannot be used; you would need to use JDBC or ODBC drivers instead.
  • Air-Gapped Environments with Telemetry Concerns — Although telemetry can be disabled, if telemetry configuration enforcement is critical, review and test the disabling mechanisms thoroughly before deployment.
  • Non-Snowflake Data Warehouses — This is a Snowflake-specific connector; it has no compatibility with other databases (Redshift, BigQuery, Synapse, etc.).

License & commercial use

Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved open-source license. The full license text is available at http://www.apache.org/licenses/LICENSE-2.0.txt.

Apache-2.0 permits commercial use, modification, and distribution. However, this connector is maintained by Snowflake and requires a valid Snowflake account/subscription to function. For production deployments, verify Snowflake's service terms and support SLA coverage separately; the license itself does not guarantee Snowflake service availability or support.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityLow
DEV.co fitGood
Assessment confidenceHigh
Security considerations

Supports package signature verification via cosign for release authenticity. Telemetry is enabled by default and transmits data to Snowflake; disable if required by compliance policy. Uses Snowflake's Rust-based sf_mini_core library (external dependency at runtime); review Snowflake's security advisories. No SQL injection or authentication flaw details disclosed in README; standard DB API practices (parameterized queries) apply. JDBC/ODBC-free design reduces supply chain risk from those components.

Alternatives to consider

snowflake-sqlalchemy

Higher-level SQLAlchemy ORM integration for Snowflake; use if you prefer ORM abstractions over raw SQL and cursor management.

dbt-snowflake

If your workflow is dbt-centric for data transformation and modeling; dbt-snowflake is the recommended tool and uses this connector under the hood.

Snowflake JDBC/ODBC Drivers

If you require Java or C++ applications, GCP regional endpoints, or Python < 3.10; JDBC and ODBC are official vendor drivers.

Software development agency

Build on snowflake-connector-python with DEV.co software developers

Start with pip install snowflake-connector-python and refer to the official Snowflake documentation for authentication and best practices. Contact Snowflake Support for production support agreements.

Talk to DEV.co

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snowflake-connector-python FAQ

Can I use this connector without a Snowflake account?
No. The connector is a client library for Snowflake data warehouse. You must have a valid Snowflake account and credentials (user, password, account ID, region) to connect.
Does the connector work with other databases (BigQuery, Redshift, etc.)?
No. This is a Snowflake-specific connector. For other warehouses, use their respective Python drivers (google-cloud-bigquery, redshift-connector, etc.).
Is telemetry data collection a security risk?
Telemetry is opt-out (enabled by default) and transmits usage data to Snowflake for product improvement. If your compliance policy forbids it, set CLIENT_TELEMETRY_ENABLED to False. Review Snowflake's data handling docs for details.
What Python versions are supported?
Python 3.10.0 or higher. Older Python versions are not supported; use JDBC/ODBC drivers if you must use Python < 3.10.

Custom software development services

DEV.co helps companies turn open-source tools like snowflake-connector-python into production software. Our software development services cover the full lifecycle — architecture, web development, integration, and maintenance — delivered by software developers and web developers who ship. Engage our software development agency to implement or customize it for your open-source databases stack.

Ready to Connect Python to Snowflake?

Start with pip install snowflake-connector-python and refer to the official Snowflake documentation for authentication and best practices. Contact Snowflake Support for production support agreements.