jsf
datamodel-code-generator
| jsf | datamodel-code-generator | |
|---|---|---|
| 5 | 9 | |
| 173 | 2,933 | |
| 1.2% | 3.0% | |
| 5.7 | 9.0 | |
| 3 months ago | 4 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
jsf
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Automatic fake JSON data creation from schema
So using the mentions jsf package it can generate as many random objects that you want that have that form, for example
- jsf - Faking JSON data from a schema
- Fake Data Creation
- Easy Fake JSON data generation with Python using jsf
datamodel-code-generator
- Datamodel-code-generator: Pydantic model/dataclass from OpenAPI, JSON, YAML
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tRPC – Move Fast and Break Nothing. End-to-end typesafe APIs made easy
Like generating pydantic models or dataclasses for an OpenAPI schema? I haven't needed to go in that direction myself, but this[0] looks promising!
Apologies if I've misunderstood your comment
https://koxudaxi.github.io/datamodel-code-generator/
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OpenAPI v4 Proposal
I'm sorry, but you have completely misunderstood the purpose of Open API.
It is not a specification to define your business logic classes and objects -- either client or server side. Its goal is to define the interface of an API, and to provide a single source of truth that requests and responses can be validated against. It contains everything you need to know to make requests to an API; code generation is nice to have (and I use it myself, but mainly on the server side, for routing and validation), but not something required or expected from OpenAPI
For what it's worth, my personal preferred workflow to build an API is as follows:
1. Build the OpenAPI spec first. A smaller spec could easily be done by hand, but I prefer using a design tool like Stoplight [0]; it has the best Web-based OpenAPI (and JSON Schema) editor I have encountered, and integrates with git nearly flawlessly.
2. Use an automated tool to generate the API code implementation. Again, a static generation tool such as datamodel-code-generator [1] (which generates Pydantic models) would suffice, but for Python I prefer the dynamic request routing and validation provided by pyapi-server [2].
3. Finally, I use automated testing tools such as schemathesis [3] to test the implementation against the specification.
[0] https://stoplight.io/
[1] https://koxudaxi.github.io/datamodel-code-generator/
[2] https://pyapi-server.readthedocs.io
[3] https://schemathesis.readthedocs.io
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Create Pydantic datamodel from huge JSON file with local datamodel-code-generator
The site also provide a link to the github repo of the underlying program.
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PSA: I think this JSON to Pydantic converter is extremely useful for boilerplate model creation
Not sure who owns/hosts the site, but its based on this github repo.
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My top python library
That's what datamodel-code-generator propose.
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I use attrs instead of pydantic
had generally good experience creating typed wrappers for api's with json-schema-to-pydantic[0] converter
[0] https://github.com/koxudaxi/datamodel-code-generator
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What's the best libraries to build a REST API with Openapi compatibility
To save you some work, if you have already an OpenAPI specification at hand, you can use datamodel-code-generator to generate your Pydantic models from the spec.
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This is what I pushed today, I don't know why but I was very positive about the code until someone reviewed it and pointed out the obvious. Also 'internal_data' field is very essential for other parts of the code. It is so embarrassing I want to disappear from the face of the earth.
And there are code generators for it! https://github.com/koxudaxi/datamodel-code-generator/
What are some alternatives?
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
fakeapi - An API to generate fake data based on a JSON payload
pydantic-factories - Simple and powerful mock data generation using pydantic or dataclasses
cattrs - Composable custom class converters for attrs, dataclasses and friends.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production [Moved to: https://github.com/fastapi/fastapi]
pydantic - Data validation using Python type hints
Pyverilog - Python-based Hardware Design Processing Toolkit for Verilog HDL
pydantic-i18n - pydantic-i18n is an extension to support an i18n for the pydantic error messages.
python-project-template - DO NOT FORK, CLICK ON "Use this template" - A github template to start a Python Project - this uses github actions to generate your project based on the template.
odmantic - Sync and Async ODM (Object Document Mapper) for MongoDB based on python type hints