Supercharge your API testing, catch bugs, and ensure compliance (by schemathesis)

Schemathesis Alternatives

Similar projects and alternatives to Schemathesis

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better Schemathesis alternative or higher similarity.

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Schemathesis reviews and mentions

Posts with mentions or reviews of Schemathesis. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-03-21.
  • Ask HN: Any Good Fuzzer for gRPC?
    3 projects | | 21 Mar 2024
    I am not aware of any tools like that, but eventually, I plan to add support for gRPC fuzzing to Schemathesis. There were already some discussions and it is more or less clear how to move forward. See
  • Show HN: Auto-generate load tests/synthetic test data from OpenAPI spec/HAR file
    1 project | | 18 Jan 2024
    Why is AI needed for this at all? Have you heard about Schemathesis (
  • A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
    31 projects | | 12 Nov 2023
    SchemaThesis is a powerful tool, especially when working with web APIs, and here's how it can enhance your testing capabilities:
  • Hurl 4.0.0
    6 projects | | 30 Jun 2023
  • OpenAPI v4 Proposal
    24 projects | | 31 May 2023
    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.





  • Faster time-to-market with API-first
    12 projects | | 25 Oct 2022
    Consolidating the API specification with OpenAPI was a turning point for the project. From that moment we were able to run mock servers to build and test the UI before integrating with the backend, and we were able to validate the backend implementation against the specification. We used prism to run mock servers, and Dredd to validate the server implementation (these days I’d rather use schemathesis).
  • Show HN: Step CI – API Testing and Monitoring Made Simple
    11 projects | | 10 Oct 2022
  • API-first development maturity framework
    3 projects | | 6 Sep 2022
    In this approach, you produce an API specification first, then you build the API against the specification, and then you validate your implementation against the specification using automated API testing tools. This is the most reliable approach for building API servers, since it’s the only one that holds the server accountable and validates the implementation against the source of truth. Unfortunately, this approach isn’t as common as it should be. One of the reasons why it isn’t so common is because it requires you to produce the API specification first, which, as we saw earlier, puts off many developers who don’t know how to work with OpenAPI. However, like I said before, generating OpenAPI specifications doesn’t need to be painful since you can use tools for that. In this approach, you use automated API testing tools to validate your implementation. Tools like Dredd and schemathesis. These tools work by parsing your API specification and automatically generating tests that ensure your implementation complies with the specification. They look at every aspect of your API implementation, including use of headers, status codes, compliance with schemas, and so on. The most advanced of these tools at the moment is schemathesis, which I highly encourage you to check out.
  • How do you manage microservices API versions and branching strategies?
    1 project | /r/devops | 17 Aug 2022
    Keep all API versions in the code Another strategy is to have all the different API versions in the same code. So you may have a folder structure that looks like this: api ├── v1 └── v2 Within the API folder, you have one folder for v1 and another one for v2. Each folder has its own schemas and routes as required by the API version they implement. If you use URL-based versioning, v1 is accessible through the endpoint or the subdomain (whichever strategy you use), and same for v2. Deprecating a version is a simple as its corresponding folder. In any case, I'd recommend you also validate your API implementations in the CI using something like schemathesis. Schemathesis looks at the API documentation and automatically generates hundreds of tests to make sure you're using the right schemas, status codes, and so on. It works best if you design and document the API before implementing, which allows you to include OpenAPI links and other features.
  • This Week in Python
    4 projects | | 12 Aug 2022
    schemathesis – Run generated test scenarios based on your OpenAPI specification
  • A note from our sponsor - Scout Monitoring | 12 Jun 2024
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