Beside legacy code, in what context would you start a new project
un java?
* Maven (or at the very least transitive dependency management) is a defacto standard. While some solutions exist such as Poetry, there is no such as thing as a centralized repository with POMs that tell you all the related dependencies easily. And managing virtual environments feels like a huge step backward.
* I ended up using FastAPI + Dependency Injector for the Python project, and while great, it is less robust, less well documented than things like Spring + JAX-RS
* Because Python sucks at multithreading and is slow, everyone has a bunch of C in their libraries, so when there is a bug (which there will always be), it's very hard to debug. In Java land I can easily step through any code, including the JVM.
* Lack of typing metadata - even relatively new libraries like the OpenAI client lack typing information, leaving you guessing about what data is available to work with.
* SQL Alchemy is vastly inferior to Java ORM solutions IMO (no, I don't want to discuss ORMs...)
* IDE support is still relatively primitive for pytest. Until a couple weeks ago, you couldn't see the output of all your tests in the VS Code console log until it was done executing. Or when you get an error, you can't just click on the stack trace to go to the failing line.
* Lack of autogenerated API documentation, e.g. equivalent of Javadoc
Love the Python syntax, but I still feel like I was more productive in Java for writing webapps. YMMV
It's fascinating just observing at a higher level our different systems and what makes it through as bugs after all testing, code review etc is done.
Java - null pointers are the main thing.
Python - it's a dogs breakfast. Latest bug was someone forgetting a comma in a list of strings since ['foo' 'bar'] is valid. But all kinds of crazy stuff - kwargs everywhere with people putting invalid values or types in. Straight up incorrect numbers of args going into functions which our linters don't notice for some reason. Refactoring anything widely used is a highly risky endeavour. Even with type hinting across all the exposed interfaces, Python is like a sieve for bugs, they just fall straight through. Once you get a complicated enough system, you just have to rely on total test coverage (ideally integration / end to end) or just letting your users find the bugs.
Also what all others have mentioned below.
It's mature and absurdly stable, both the language and the ecosystem; the tooling is best in class, and a lot of the awkward chafing points are going away to the point where the language is pretty pleasant to work with...
It isn't an exciting language. It's boring, it's the last to get new cool features, and that's by design. It also never breaks. There's extremely rarely any library churn or surprises. You can spend all the time working instead of putting out fires caused by the ecosystem.