$ show ghandic/jsf
jsf is a Python library that generates fake data conforming to JSON schemas. It provides programmatic and CLI interfaces for creating realistic test data, supports custom data providers, maintains state for dependent data generation, validates output against schemas, and integrates with FastAPI for automatic API documentation. The architecture follows a modular design where each JSON schema type is handled by a specific class in jsf/schema_types/, with the core parsing logic in jsf/parser.py. The project uses Pants for building, has comprehensive test coverage, and maintains active CI/CD pipelines with automated releases based on conventional commits.
The LLM identified 3 files worth highlighting for reuse:
Implements multiple content encoding schemes (base64, quoted-printable, binary, etc.) using a clean enum-based strategy pattern. Self-contained with only standard library dependencies, demonstrating solid implementation of encoding standards that could be extracted for any project needing data transformation.
Provides random_fixed_length_sentence function that generates lorem ipsum text constrained to specific length ranges. Features a non-obvious algorithm for efficiently generating text that meets exact length requirements without trial-and-error. Completely self-contained with only random module dependency, making it highly reusable for any project needing constrained text generation.
Implements secure JWT token generation with proper HS256 signing using standard library cryptography functions. Demonstrates security-conscious implementation practices and could be used in any project needing JWT generation with minimal adaptation (only requires a faker-like interface for randomness).