I've used Python a lot over the last ~10 years. It's probably my favorite language, although I'm not immune to its weak points.
To answer your questions in order,
a) I haven't done much work with embedded Python, but like any dynamically-typed language that runs in a VM there's a lot of runtime infrastructure that adds latency, complexity, energy consumption, bundle size, etc. It sounds like this project aims to remove the vast majority of that. So take startup time, for instance: Normal Python takes ~50ms to fire up the interpreter and get into actual user code. If I'm understanding it correctly, with PyXL that would be vastly lower. Although I guess the ARM chip still has to load the code onto the FPGA, so maybe not, idk.
b) and c) are kind of the same question, to me - at least, "why use Python for embedded" is a subset of "why use Python at all."
For me, Python more than any other language is great at getting out of its own way, so that you can spend your precious brain energy on whatever problem you're solving and less on the tool you're using to solve it. This is maybe less true in recent years, as later Pythons have added a lot more complex features (like async/await, for instance, which I actually really like in Python but definitely adds complexity to the language).
Finally, I think a lot of it comes down to personal style/taste/chance (i.e. if Python is the first language you encounter, you're probably more likely to end up liking Python.) The Zen of Python[0], which you may have seen, does a good job of explaining the Python way of approaching problems, although like I said a few of those principles have been less-rigidly adhered to in recent years (like "there should be only one way to do it.")
If you hang out in Python circles, you'll probably come across the phrase "Python fits your brain." I'm not sure where it was originally coined but it very definitely describes my experience with Python: it (mostly) just works like I expect it to, whether that's with regard to syntax, semantics, stdlib, etc.
Not that it doesn't have its bad points, of course. Dependency management, as you mentioned, can be a bit hellish at times. A lot of it comes down to the fact that dependencies in Python were originally conceived as systemwide state, much like dynamically-loaded C libs on Linux. This works fine until you need to use two different, mutually-incompatible versions of the same lib, at which point all hell breaks loose. There have been various attempts to improve on this more recently, so far uv[1] looks pretty promising, but time will tell.
The one saving grace of Python dependencies is that it has a very rich standard library, so the average Python project tends to have way fewer total dependencies than the average project in, say, JS or Rust.
The typing story for Python is also a bit lacking. Yes, there are now optional type hints and things like MyPy to make use of them, but even if your own code is all completely typed, in my experience it's usually not long before you need to call out to something that isn't well-typed and then your whole house of cards starts to fall apart.
To answer your questions in order,
a) I haven't done much work with embedded Python, but like any dynamically-typed language that runs in a VM there's a lot of runtime infrastructure that adds latency, complexity, energy consumption, bundle size, etc. It sounds like this project aims to remove the vast majority of that. So take startup time, for instance: Normal Python takes ~50ms to fire up the interpreter and get into actual user code. If I'm understanding it correctly, with PyXL that would be vastly lower. Although I guess the ARM chip still has to load the code onto the FPGA, so maybe not, idk.
b) and c) are kind of the same question, to me - at least, "why use Python for embedded" is a subset of "why use Python at all."
For me, Python more than any other language is great at getting out of its own way, so that you can spend your precious brain energy on whatever problem you're solving and less on the tool you're using to solve it. This is maybe less true in recent years, as later Pythons have added a lot more complex features (like async/await, for instance, which I actually really like in Python but definitely adds complexity to the language).
Finally, I think a lot of it comes down to personal style/taste/chance (i.e. if Python is the first language you encounter, you're probably more likely to end up liking Python.) The Zen of Python[0], which you may have seen, does a good job of explaining the Python way of approaching problems, although like I said a few of those principles have been less-rigidly adhered to in recent years (like "there should be only one way to do it.")
If you hang out in Python circles, you'll probably come across the phrase "Python fits your brain." I'm not sure where it was originally coined but it very definitely describes my experience with Python: it (mostly) just works like I expect it to, whether that's with regard to syntax, semantics, stdlib, etc.
Not that it doesn't have its bad points, of course. Dependency management, as you mentioned, can be a bit hellish at times. A lot of it comes down to the fact that dependencies in Python were originally conceived as systemwide state, much like dynamically-loaded C libs on Linux. This works fine until you need to use two different, mutually-incompatible versions of the same lib, at which point all hell breaks loose. There have been various attempts to improve on this more recently, so far uv[1] looks pretty promising, but time will tell.
The one saving grace of Python dependencies is that it has a very rich standard library, so the average Python project tends to have way fewer total dependencies than the average project in, say, JS or Rust.
The typing story for Python is also a bit lacking. Yes, there are now optional type hints and things like MyPy to make use of them, but even if your own code is all completely typed, in my experience it's usually not long before you need to call out to something that isn't well-typed and then your whole house of cards starts to fall apart.
Anyway, just my rambling $0.02.
[0] https://peps.python.org/pep-0020/