datamodel-code-generator
swag
datamodel-code-generator | swag | |
---|---|---|
9 | 36 | |
2,315 | 9,812 | |
- | 1.8% | |
9.4 | 8.1 | |
5 days ago | 8 days ago | |
Python | Go | |
MIT License | MIT License |
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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.
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/
swag
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Seeking Advice on the Best Swagger Generation Approach for REST API
Hey Gophers, I'm exploring Swagger generation for a REST API in Go (using go-chi). Currently, I'm testing https://github.com/swaggo/swag/, but I'm uncertain if it's the optimal solution. What are your thoughts or recommendations?
- Como deixar o Swagger com tema dark mode usando Swaggo e Golang
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Building RESTful API with Hexagonal Architecture in Go
Swaggo is a tool that creates Swagger documentation for Go APIs. It makes documenting API endpoints easier, helping developers understand and use the API.
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go-ecommerce-microservices: A practical e-commerce microservices, built with cqrs, event sourcing, vertical slice architecture, event-driven architecture.
Some of the features: - ✅ Using Vertical Slice Architecture as a high level architecture - ✅ Using Event Driven Architecture on top of RabbitMQ Message Broker with a custom [Event Bus](pkg/messaging/bus/) - ✅ Using Event Sourcing in Audit Based services like [Orders Service](services/orders/) - ✅ Using CQRS Pattern and Mediator Patternon top of Go-MediatR library - ✅ Using Dependency Injection and Inversion of Controlon top of uber-go/fx library - ✅ Using RESTFul api with Echo framework and using swagger with swaggo/swag library - ✅ Using Postgres and EventStoreDB to write databases with fully supports transactions(ACID) - ✅ Using MongoDB and Elastic Search for read databases (NOSQL) - ✅ Using OpenTelemetry for collection Distributed Tracing with using Jaeger and Zipkin - ✅ Using OpenTelemetry for collection Metrics with using Prometheus and Grafana - ✅ Using Unit Test for testing small units with mocking dependent classes and using Mockery for mocking dependencies - ✅ Using End2End Test and Integration Test for testing features with all of their real dependeinces using docker containers (cleanup tests) and testcontainers-go library
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OpenAPI v4 Proposal
[1]https://github.com/swaggo/swag/issues/386
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[Request] Library Recommendation for Auto Swagger/OpenAPIv3 Documentation
I used this the other day and found it very easy to set up: https://github.com/swaggo/swag
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Public API documentation. What to use?
I use the fizz for developing my webservices + docs, it's smooth! There is swaggo but I don`t like it because the source code get dirty (lots of comments)
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Any Working Example for Swagger integartion with golang?
You can use swaggo/swag with code annotations
- Change host in Swagger API
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Swagger codegen or custom tool
checkout swaggo/swag.
What are some alternatives?
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
GoSwagger - Swagger 2.0 implementation for go
pydantic - Data validation using Python type hints
gin-swagger - gin middleware to automatically generate RESTful API documentation with Swagger 2.0.
pydantic-factories - Simple and powerful mock data generation using pydantic or dataclasses
fiber-swagger - fiber middleware to automatically generate RESTful API documentation with Swagger 2.0.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Nginx Proxy Manager - Docker container for managing Nginx proxy hosts with a simple, powerful interface
odmantic - Sync and Async ODM (Object Document Mapper) for MongoDB based on python type hints
echo-swagger - echo middleware to automatically generate RESTful API documentation with Swagger 2.0.
cattrs - Composable custom class converters for attrs.
jaeger - CNCF Jaeger, a Distributed Tracing Platform