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+# Python/Python parity testing in Python SDK interface
+
+> Given the same SDK call and identical provider behavior, does the PyO3 implementation behave same as Python?
+
+## What the harness compares
+
+- A fixture contains a LiteLLM SDK input and a recorded upstream provider response
+- The same LiteLLM input is transformed by isolated Python and Rust workers
+- The resulting provider requests must match in method, path, headers, and body, excluding runtime-specific HTTP metadata
+- The recorded provider response is then replayed unchanged to both workers
+- Each worker serializes its normalized LiteLLM SDK response to JSON, and the results must match
+
+## Hypothesis and property-based testing
+
+- Hypothesis is Python libary for property-based testing
+- Example-based tests use inputs selected by the test author
+- Property-based tests define strategies for valid inputs and properties that must hold for every generated example
+- Hypothesis generates combinations from those strategies and normally shrinks a failing example to a smaller reproducible case
+- In this harness, Hypothesis is used only during fixture generation to expand the LiteLLM input corpus
+- The current OCR strategy varies supported optional parameters while keeping inputs valid
+- Fixture generation is deterministic, and each generated input is recorded with the raw provider response it received
+- The parity tests use committed fixtures and do not call the provider or generate new Hypothesis examples
+- Provider responses are replayed unchanged, so the parity test does not fuzz or validate provider behavior
+- Because Hypothesis does not run the parity assertion directly, parity failures are not automatically shrunk
+
+## References
+
+- [Hypothesis documentation](https://hypothesis.readthedocs.io/en/latest/)
+- [Hypothesis quick start](https://hypothesis.readthedocs.io/en/latest/quickstart.html)