Python is valuable due to the ecosystem of libraries it offers. The language itself is extremely poor. I think this is not something most Python users are aware of since if you are doing ML, data-science or simple scripting there is little reason to step outside of the ecosystem. - Weird scoping rules - Very limited list-comprehensions - Ability to monkey patch things is a liability - Mutability by default - Lack of…
Weird scoping rules? This will rarely if-ever impact you in the real world.
The list comprehensions in Python are incredible, in fact people over-use them all the time in really gnarly ways. Like [x for x in [y for y in [z... and the consistency with the same system supporting all datastructures (sets, dictionaries, tuples, etc) is very intuitive.
Monkey patching is a liability? This is like saying a car is a liability because I am free to drive it off a cliff. You're technically correct, but you are the one in the drivers seat. The ecosystem does not do or encourage this behavior, with the exception of things like gevent where it is required.
Mutability by default is common in virtually every language. You can't say it is good or bad, it's just a fact of life. There is a cost to immutable datastructures unless the language is designed from the get-go to utilize them efficiently.
Lack of support for functional programming? Functions are first class in Python. You can pass them around all over the place, as args, put them in datastructures, etc. When you combine this with comprehensions and generators it is very powerful and lets you do lazy evaluation of complex transformations. There are lots of built-in tools in the stdlib to do functional programming. This is just straight up false.
Deployment story remains extremely painful - again false, I do not know why people say stuff like this. Create a virtualenv (built into the standard library), and pip install your requirements. If you are using conda and all the other noise you are going to have problems.
Slow execution of pure python code - this is the ONLY area where you are perhaps correct... but compared to what? For a lot of use cases, the speed of Python is not a problem. When it becomes a problem, you off-load that responsibility to something else. There is also something to be said for writing software quickly, which is a perk of Python for sure.