I’m beginning to explore API testing, both to improve the quality of my own (small FastAPI-based) project and to build skills that will help me land a QA or test automation role.
Right now, I’ve used Postman manually, and while it’s great for quick tests and exploring endpoints, I’ve found its automation and data-driven features a bit clunky. I enjoy coding and feel more in control using tools like Python’s requests module with pytest, which seem to offer more flexibility and transparency.
If you’re actively doing API testing at your job:
What tools do you use daily?
Are they GUI-based like Postman or code-first like REST-assured or pytest?
If you had the freedom to choose your stack, would you stick with your current tools?
And for someone new to testing—do you think a portfolio project in Postman + Newman looks better, or should I focus on building an automated suite using Python with GitHub Actions or Jenkins?
Would love to hear your thoughts!
I’ve been working in automation for about 6 years now, and flexibility has always been a priority for me.
We started with Postman because it’s great for getting something up and running quickly—especially when you’re validating endpoints manually or doing quick smoke checks. But when maintainability and CI/CD integration became priorities, we moved to Python + Pytest + Requests. This combo gives full control—fixtures handle dynamic token management, retries, and even data seeding.
It’s also much easier to scale and debug when everything’s written as code. Plus, combining this with GitHub Actions means we get a fully automated pipeline that mirrors real-world CI environments. If you’re building a portfolio or prepping for interviews, a structured Python test suite can really help showcase your design thinking.
There’s definitely value in Postman, especially as an entry-level API testing tool, but when you want true control, Python gives you that edge.
Coming from a QA background with 8+ years of team coordination, I’ll admit: not everyone on a team loves code.
That’s exactly why we’ve stuck with Postman + Newman for most of our API testing workflows. Postman allows even non-devs on the QA team to participate—using shared collections, environment variables, and pre-request scripting. Then we use Newman to integrate those tests into Jenkins pipelines.
Sure, Postman scripting can hit a ceiling, but for microservices-based projects and cross-functional teams, the speed and collaboration it brings is tough to beat. We also leverage mock servers and public documentation features—something you don’t get natively in Python.
If you’re aiming for larger QA-driven orgs, a cleanly structured Postman + Newman setup can be just as impressive. That said, I totally agree with Tom—pairing Postman with a Python suite for deeper test coverage gives you the best of both worlds.
And yeah, there’s no one-size-fits-all API testing tool—this blog breaks down some of the top tools out there that might suit your workflow better.
In my 10+ years working across enterprise systems, I’ve learned one thing—tooling must align with the ecosystem.
In our enterprise environment, we’re deeply invested in Java—so REST-assured with JUnit/TestNG is our standard. It integrates seamlessly into our Maven pipeline, and we pair it with TestContainers for spinning up services dynamically. REST-assured gives strong typing, detailed response assertions, and excellent support for things like JSON schema validation and OAuth token flows.
Sure, it’s a bit more verbose than Python, but it aligns better with our Java-based microservices and dev culture. Plus, using Allure Reports with REST-assured brings visibility into test runs—useful for compliance reporting.
@kumari_babitaa and @mark-mazay both make great points. If you’re career-focused, pick the API testing tool that fits your language and project context. Python and Postman are fantastic, but REST-assured still rules the roost in many large-scale systems. Start by scanning job descriptions—they’ll tell you what’s hot in your domain.