mkleehammer/pyodbc

Python ODBC bridge

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Summary Information

Updated 43 minutes ago
Type:Library / SDKCategory(s):Relational & SQL DatabasesDatabases & Storage
Added to GitGenius on September 22nd, 2026
Created on October 3rd, 2008
Open Issues & Pull Requests: 60 (+0)
GitHub issues: Enabled
Number of forks: 569
Total Stargazers: 3,083 (+0)
Total Subscribers: 117 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 18.2 hours
Mean response time: 77.8 days
90th percentile: 327.2 days
Tracked items: 115

How this project is maintained

90% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "Environment or Driver Issue" is answered fastest, typically in about 7 hours, while "Request" waits about 4 weeks. Three people close 75% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 39
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,355 days
Stale 30+ days: 38
Stale 90+ days: 37

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • Environment or Driver Issue (22)
  • Request (10)
  • Investigating (6)
  • v5 .connect() behavior (4)
  • Feature (3)
  • On Hold (3)
  • Bug (2)
  • Reproducible Issue (2)

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Detailed Description

pyodbc is a Python database adapter that provides access to ODBC data sources.

The tool solves the problem of connecting Python applications to databases and other data sources through the ODBC interface. It implements the Python Database API Specification, allowing developers to write database code that follows a standard interface. The bridge is written in C++ and handles the translation between Python and ODBC, managing connections, executing queries, and returning results to Python code.

Developers should choose pyodbc when they need to work with databases or data sources that expose ODBC drivers, particularly in environments where ODBC is the established connectivity standard. It suits projects that require compatibility with legacy systems or databases where ODBC is the primary or only available interface. The tool is appropriate for applications that benefit from the standardized DB-API interface, making it easier to switch between different database backends or to write database-agnostic code.

The project shows sustained maintenance with regular updates addressing compatibility and bug fixes. Development activity demonstrates responsiveness to issues and pull requests from the community. The codebase receives ongoing attention to ensure compatibility with current Python versions and ODBC driver changes across different platforms.