Codefaker
codefaker is a lightweight open‑source library written in Python that generates realistic‑looking, syntactically valid code snippets for use in documentation, testing, and prototyping. The project was initiated in early 2022 by a small group of developers on GitHub and is maintained under the Apache‑2.0 license. Codefaker builds on top of the popular Faker library, extending its random data generation capabilities to programming language constructs such as class names, function signatures, variable names, loop structures, and sample code blocks in languages including Python, JavaScript, Java, and C++.
Key features of codefaker include:
- Random generation of fully‑qualified identifiers with configurable naming conventions (snake_case, camelCase, PascalCase).
- Support for generating boilerplate code with optional imports, docstrings, and type hints.
- Ability to embed random comments, decorators, and error handling scaffolding.
- A Python API that returns either plain text or, when requested, AST nodes that can be manipulated
- All code snippets are guaranteed to be syntactically correct, making them useful for unit tests that
Typical use cases for codefaker involve populating example sections of technical blogs, creating synthetic datasets for
As of version 1.3.0, released in September 2024, codefaker supports Python 3.8 through 3.12 and offers simple
---