DB-API 2.0

Q: Which Python libraries follow DB-API 2.0?

Popular adapters like psycopg2 (PostgreSQL) and sqlite3 (SQLite) implement it, and DuckDB's Python client follows the same specification for a familiar experience.

DB-API 2.0 is a standardized Python interface for accessing relational databases.

DB-API 2.0 is a standardized Python interface for accessing relational databases. It defines a set of methods and behaviors that database adapters should implement, allowing Python programmers to write code that can work with different database systems without major modifications. This specification includes guidelines for connecting to databases, executing SQL queries, and handling result sets. By adhering to DB-API 2.0, database libraries ensure compatibility and interoperability across various database management systems, making it easier for developers to switch between databases or work with multiple databases in a single project. Popular database adapters like psycopg2 for PostgreSQL and sqlite3 for SQLite follow this specification, providing a consistent experience for Python developers working with relational data.

Related terms

DB-API →

DB-API is a standardized interface for Python to interact with relational databases.

relational database →

A relational database is a structured collection of data organized into tables with rows and columns.

relational object →

A relational object is a fundamental concept in relational databases, representing a structured collection of data organized into rows and columns.

relational API →

The relational API in DuckDB provides a fluent, Pythonic interface for constructing and executing SQL queries programmatically.

Python →

Python is a high-level, interpreted programming language known for its simplicity and readability.

SQL →

SQL (Structured Query Language) is the standard language for working with relational databases.

FAQS

DB-API 2.0 (PEP 249) is a standardized Python interface for relational databases. It defines the methods and behaviors database adapters should implement so Python code can work across different databases with minimal changes.

It provides consistency and interoperability—code written against DB-API works across compliant databases, making it easy to switch databases or use several in one project.

Popular adapters like psycopg2 (PostgreSQL) and sqlite3 (SQLite) implement it, and DuckDB's Python client follows the same specification for a familiar experience.