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.
Compared to… basically everything? Python’s performance is unacceptable, especially given that single threaded processor performance isn’t really improving any longer.
It can be a problem if you have nested loops. Things would have been less error-prone if Python introduced a let keyword.
> 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.
They have been completely surpassed by those in other languages. For example, you can't do this in Python list-comprehensions:
xs = [
if some_flag:
yield 1
for y in ys:
yield y * 2
]
Only if you are a solo developer. Unfortunately the Python ecosystem is built around things that compose poorly like annotations and exceptions.
> 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.
It's a mistake, even though it is common. The cost is low in true FP langauges, because they can be optimized away.
> 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.
Python lacks do-notation. It doesn't give you tail-call optimization. Function calls are slow. Immutability is very much opt-in. Lambdas can only be one line. If you do lots of FP in Python, you're in for a bad time.
> 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.
In other language stacks it's pretty trivial to cross-compile from e.g. MacOS to Linux and things just work. In Python this basically requires Docker. Note that Pip install doesn't give reproducible builds. There's nothing like Go static binaries out-of-the-box, either.
> 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.
Python is about 100x slower than mainstream GC languages such as Java and C#. Having to drop into native code is not always possible and it's extra work besides.
Pick your poison
shell #expand all the strings, but those pipes are nice, why can't more languages have pipes.
awk #not a bad language, but very very small, and an AWKward(see what I did there) implied data loop
perl #can do anything but the syntax is, well it is a real frankenstein monster of a syntax
python #well designed syntax, has a strange block structure but at least it is always nicely formatted
tcl #all the strings! but other than that not half bad
ruby #pretty, but wow, that is a lot of magic
php #just graft on whatever to the language as you need it, don't worry about how it all fits together.> The language itself is extremely poor
> I think this is not something most Python users are aware of
These two statements are contradictory. If it was indeed so "poor", people would notice :) If they instead increasingly adopt it (out of appreciation, not because they are lobbied into doing it) it becomes really difficult to logically demonstrate that it's a poor choice. Software development is a very efficient market. Everyone is (or can be) aware of (almost) everything. So if most people (including experienced devs) gravitate towards a certain technology, the only acceptable explanation is that the technology, as a whole, is good.
Deconstructing and pointing out the flaws of the individual components is a common flawed thought process IMHO. Python is great despite all the issues you point out. To me this is equivalent to comparing individual components when shopping for a product, missing the fact that it's the ensemble of all those (flawed) components that make the product (or the language, in this case) work. The easy syntax, the packages, the community, those are all things that make "weird scoping rules" pretty much irrelevant.
The main difference with JS is that we don't know whether it would be so commonly used if it wasn't for browsers. Still, it seems that the majority of efforts are towards augmenting JS' capabilities rather than finding ways to use alternative languages on the web (yes, I'm aware of WASM and maybe in the long run this statement will be proven false).
Would they? The history of programming is full of great ideas that took a very long time to reach mainstream adoption. We also did some things that in hindsight were bad ideas, but for a time were very popular.
This is because the programming language "market" is not rational. It moves at the speed of education, not the speed of innovation. People learn a language and they make useful things with it. Why would they stray into niche languages and PL research?
What I'm saying is that considering Python a bad language, just because there are some languages that improve on some of its shortcomings, is just wrong.
As of today, Python is the most popular, hence (as a corollary) the best choice for most people. One day that might change, sure. These aren't mutually exclusive.
I don't agree with the claim about the market not being "rational". Someone who adopts Python even when given requirements that are clearly beyond the language's capabilities isn't going to last long in such market (and neither will their choices).
On the other hand there are plenty of people (myself included) who prefer using Python whenever possible, even though they have been "educated" in the use of other languages (I'd say I'm fairly comfortable with Typescript or even C building non trivial systems). I guess I'm not innovative enough :)
You're thinking about the programmer effort put into making certain libraries efficient, but think about the users who are reaping the benefits of low barrier to entry! More people are coding, getting comfortable with the idea of programming, and we should welcome them!
I think it's simply what they already knew. Very few programmers learn multiple languages to any kind of depth.
Is there any evidence that Python is an easy language to learn? I think we've reached a situation where beginners learn Python because it's seen as beginner friendly... because beginners learn Python!
Admittedly, that's just an opinion. I don't know of any relevant studies, but Python wasn't always the preferred language for beginners, and it changed at some point. It feels like there must be a reason for that.
- Weird scoping rules
- Very limited list-comprehensions
- Ability to monkey patch things is a liability
- Mutability by default
- Lack of support for functional programming
- Deployment story remains extremely painful
- Tacked on type-system
- Slow execution of pure Python code
If this sounds like a rant... it sort of is. I find it really sad that so much programmer effort is being put into something with poor fundamentals. Many of these issues cannot be fixed with breaking changes.