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To maximize the utility of Python DTOs and enable richer tooling support, Python DTOs are generated as [dataclasses](https://docs.python.org/3/library/dataclasses.html) with support for [JSON serialization](https://pypi.org/project/dataclasses-json/) and annotated with Python 3 [type hints](https://docs.python.org/3/library/typing.html) - that's invaluable when scaling large Python code-bases and greatly improves discoverability of a remote API. DTOs are also enriched with interface markers through Python's multiple inheritance support which enables enables its optimal end-to-end typed API:
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To maximize the utility of Python DTOs and enable richer tooling support, Python DTOs are generated as [dataclasses](https://docs.python.org/3/library/dataclasses.html) with support for [JSON serialization](https://pypi.org/project/dataclasses-json/) and annotated with Python 3 [type hints](https://docs.python.org/3/library/typing.html) - that's invaluable when scaling large Python code-bases and greatly improves discoverability of a remote API. DTOs are also enriched with interface markers through Python's multiple inheritance support which enables its optimal end-to-end typed API:
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The Python DTOs and `JsonServiceClient` library follow Python's [PEP 8's naming conventions](https://www.python.org/dev/peps/pep-0008/) so they'll naturally fit into existing Python code bases. Here's a sample of [techstacks.io](https://techstacks.io) generated Python DTOs containing string and int Enums, an example AutoQuery and a standard Request & Response DTO showcasing the rich typing annotations and naming conventions used:
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