Hi all! I am supposed to be maintaining and creating API tests in Python for our platform. I know about Postman and Swagger, and I’ve done a basic Python tutorial (some time ago). I suppose I am looking for tutorials for beginners which apply directly to my situation rather than relating ... More on club.ministryoftesting.com

Really appreciate you putting this guide together, super helpful and honestly felt like it came from someone who's been there lol. Would love to share something that helped our team recently, someone on Reddit actually suggested this tool called Keploy for API and integration testing, and we decided to give it a shot. Didn't expect much at first, but it turned out to be crazily good. We’ve got a small QA team and used to spend a ton of time doing manual testing. Keploy basically records API calls while you're using the app (via a Chrome extension), then turns those into test cases automatically. It seriously saved us so much time, especially during sprints. Just thought I’d share in case someone else finds it useful, definitely wasn’t on my radar until that Reddit comment, and now it’s part of our workflow. Again, loved the guide, bookmarking this one! More on reddit.com

Pytest+Requests More on reddit.com

asserting on HTTP responses If you dont want to use the built in assertions, there are modules like pyresttest and pyhttptest. Honestly using assertions with requests is going to be easier. I guess you are looking for something like RestAssured from Java but for Python. Python doesn't really embrace the same kind of API style that Java does, so you probably wont find many things like that in this space. You can always use stuff like json path libraries and xpath libraries on pypi to deal with body assertions if you want to use that. mocking Assuming you mean mocking external services rather than object mocking as that is generally aimed at unit testing. If you need to mock network requests at an integration level, I'd probably suggest using tooling such as testcontainers. That lets you spin up a container within Docker for whatever you want (it supports Kafka, Mockserver (HTTP), localstack (full AWS API) etc out of the box). You can also then make use of WireMock and the Python WireMock Admin API if you want something more involved (again, using test containers). Testcontainers will also let you run databases and other stuff programmatically too. Verifying OpenAPI That isn't really Python specific, and is not possible to fully automate from a black box perspective (since you cant really just infer what operations and payloads and headers are needed in a standard way from just observing a running REST API). You could avoid this by using something like APIFlask for Flask, or drf-spectacular for Django to create your OA3 specs from your code at runtime instead though. From an API level, you could alternatively consider using a transport like gRPC rather than a pure REST API, or use protobuf for your serialization format. That would enable you to write your payloads in protobuf files and distribute them to the end users so they can recreate the API clients/payloads on their side directly via protoc. That would reduce the need for such heavy documentation using OpenAPI 3 as you'd then be mostly just documenting the parameters on the generated code like any other library API. Ideas If you are doing acceptance testing, I'd probably suggest using behavioural-driven-development using a tool like behave rather than using pytest or unittest or nose directly. That way you can keep your test logic in readable feature requirements files. https://behave.readthedocs.io/en/stable/tutorial.html https://cucumber.io/ Pytest has a BDD plugin but last time I used it, it was overly clunky and awkward in comparison to behave. It felt like it didnt really capture the spirit of BDD features being more agnostic since there were a bunch of fairly common requirements that it didnt really fulfill for me. If you need something like awaitility in Java and do not want to just write a basic shim around threads or asyncio, there is this library too: https://pypi.org/project/busypie/ I leave with an unpopular opinion here: a lot of the testing frameworks in Python do not feel as developed as other languages which is unfortunate. For example, Java has full support for Cucumber rather than using a separately maintained API. Testcontainers is far more robust and customizable (esp. with respect to Kafka), higher level libraries like JooQ exist for expressing stuff like SQL with a DSL without needing to delegate to an ORM and hope that the ORM supports all the features of SQL that you need. You also have tools like awaitility, first class support for Wiremock and Mockserver, proper in memory databases for testing like H2 and Derby. Stuff like Restassured also exists. You also have tools like Skyscreamer JSON Assert, XML Assert, etc. Python does seem to lack in this regard, so you will likely find yourself having to write some common code in a library eventually to achieve some more bespoke common stuff you may need to do in tests. (Disclaimer, I work writing cloud Java and Python APIs and systems; I cant speak as well for other langs like C#, Ruby, PHP, Rust, Go, etc). More on reddit.com