rdce 0.1.0

Runtime Data Contract Enforcer

rdce

Runtime Data Contract Enforcer: A lightweight Python 3 library for recursively validating and diffing nested JSON payloads against explicit Pydantic schemas.

Current Status

🚀 v0.1.0 Complete 🚀 The core recursive validation engine, Pydantic extractor, and public API are complete and fully tested with 100% coverage.

🌟 Features

• Pydantic Native: Define your data contracts using standard Pydantic BaseModel classes.
• Recursive Type Validation: Deeply inspects nested dictionaries and payloads without flattening them.
• Path Tracking: Returns exact dot-notation breadcrumbs for schema drift (e.g., user.address.zip_code).
• Zero Bloat: Built to do one thing perfectly—diffing data schemas.

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📦 Installation

(Note: Pending PyPI release)

pip install rdce
# Or using poetry
poetry add rdce

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🚀 Quick Start

rdce is designed to be a transparent bridge between your Pydantic models and incoming, untrusted dictionary payloads.

1. Define your Contract

Use standard Pydantic models. Nested models are fully supported.

from pydantic import BaseModel

class Address(BaseModel):
    city: str
    zip_code: int

class UserContract(BaseModel):
    username: str
    is_active: bool
    address: Address

2. Enforce the Payload

Pass the model class and your raw dictionary payload into the enforce_contract engine.

from rdce import enforce_contract

# A payload with schema drift (wrong type for zip_code, missing is_active)
incoming_payload = {
    "username": "alice_data",
    "address": {
        "city": "London",
        "zip_code": "E1 6AN" # Expected int, got string
    }
}

errors = enforce_contract(UserContract, incoming_payload)

for error in errors:
    print(error)

Output:

[
  {"path": "is_active", "expected": "bool", "actual": "MISSING"},
  {"path": "address.zip_code", "expected": "int", "actual": "str"}
]

🤝 Contributing

We welcome contributions! To set up the project locally:

1 Clone the repository.
2 Initialize the environment: poetry install
3 We strictly enforce formatting and linting via Ruff:
4 Linter: 
    poetry run python3 -m ruff check .
5 Formatter: 
    poetry run python3 -m ruff format .
6 Run the test suite: 
    poetry run pytest
7 Ensure 100% test coverage before submitting a Pull Request.