How do I generate a Python client from an OpenAPI spec with custom templates?

Use the --custom-template-path flag with the generate command, copying templates from the default directory. Note that this feature is beta-level and the API is unstable, so proceed with caution for production use.

What's the difference between openapi-python-client and openapi-generator for Python?

openapi-python-client is Python-native, focusing on modern Python features and customization via Jinja2, while openapi-generator is Java-based with broader language support but more complex installation. Choose openapi-python-client for a tailored Python experience if you can handle its development status.

Can openapi-python-client handle OpenAPI 2.0 documents?

No, it only supports OpenAPI 3.0 and 3.1. The README recommends upgrading older specs with converters, so you'll need a separate tool for OpenAPI 2.x files.

How to customize class names in the generated client?

Use the class_overrides parameter in a config YAML/JSON file to map original schema names to new class and module names, as shown in the README example with _PrivateInternalLongName to ShortName.

Does openapi-python-client support asynchronous API calls?

No, the generated clients use synchronous HTTP calls by default. The README doesn't mention async support, so you'd need to manually modify the templates or code for asynchronous operations.

What happens if my OpenAPI spec has unsupported features?

The generator will skip or mishandle those features, as it's still in development. You might need to pre-process the spec, use workarounds in templates, or consider alternative tools with fuller support.

Open-Awesome

openapi-python-client

MITPythonv0.28.3

Generate modern, type-annotated Python client libraries from OpenAPI 3.0 and 3.1 specifications.

GitHub

1.9k stars277 forks0 contributors

What is openapi-python-client?

openapi-python-client is a Python tool that automatically generates modern, type-annotated client libraries from OpenAPI 3.0 and 3.1 specifications. It solves the problem of manually writing API clients by producing ready-to-use Python modules with models, API functions, and authentication classes. The generated code is designed to be clean, maintainable, and leverage the latest Python features.

Target Audience

Python developers and teams who need to interact with REST APIs described by OpenAPI specifications and want an automated, customizable way to generate type-safe client SDKs.

Value Proposition

Developers choose this tool because it's written in Python, making it easy to install and extend, and it focuses on generating high-quality, modern Python code with extensive configuration options. Unlike some generators, it provides a tailored experience for Python developers with features like custom templates and post-generation formatting.

Overview

Generate modern Python clients from OpenAPI

Use Cases

Best For

Generating type-safe Python clients for internal or public REST APIs
Automating SDK creation as part of a CI/CD pipeline
Customizing generated client code structure with Jinja2 templates
Integrating with Poetry or PDM for dependency management
Ensuring consistent code style with automatic Ruff formatting
Handling OpenAPI 3.1 specifications with modern Python features

Not Ideal For

Projects relying on OpenAPI 2.x (Swagger) specifications without conversion tools
APIs requiring full OpenAPI 3.x feature support, as the generator is still in development
Teams needing a zero-configuration, out-of-the-box solution without customization or template tweaks

Pros & Cons

Pros

Modern Type Safety

Generates clients using Python type annotations, dataclasses, and enums, ensuring robust and maintainable code as highlighted in the README's focus on 'latest and greatest Python features'.

Template Customization

Supports custom Jinja2 templates via the --custom-template-path flag, allowing developers to tailor generated code structure and style without overriding all templates.

Configurable Output

Offers extensive YAML/JSON configuration for class names, package metadata, enums, and post-generation hooks, enabling fine-tuned control over the generated client.

Tool Integration

Automatically runs Ruff for code formatting via post_hooks and supports multiple package managers (Poetry, PDM, setup.py), fitting into modern Python workflows.

Cons

Incomplete OpenAPI Support

The README explicitly states 'This project is still in development and does not support all OpenAPI features,' limiting its use for complex or advanced APIs.

Unstable Customization API

Custom templates are labeled a 'beta-level feature' with an 'undocumented and unstable' API, posing risks for teams relying on deep customization.

Setup Complexity

Requires pipx with --include-deps for optimal installation to ensure Ruff is available, adding an extra step compared to simpler, all-in-one tools.

Frequently Asked Questions

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