Why isn't Python very good for functional programming? [closed]

Question

I have always thought that functional programming can be done in Python. Thus, I was surprised that Python didn't get much of a mention in this question, and when it was mentioned, it normally wasn't very positive. However, not many reasons were given for this (lack of pattern matching and algebraic data types were mentioned). So my question is: why isn't Python very good for functional programming? Are there more reasons than its lack of pattern matching and algebraic data types? Or are these concepts so important to functional programming that a language that doesn't support them can only be classed as a second rate functional programming language? (Keep in mind that my experience with functional programming is quite limited.)

Answer 1

The question you reference asks which languages promote both OO and functional programming. Python does not promote functional programming even though it works fairly well.

The best argument against functional programming in Python is that imperative/OO use cases are carefully considered by Guido, while functional programming use cases are not. When I write imperative Python, it's one of the prettiest languages I know. When I write functional Python, it becomes as ugly and unpleasant as your average language that doesn't have a BDFL.

Which is not to say that it's bad, just that you have to work harder than you would if you switched to a language that promotes functional programming or switched to writing OO Python.

Here are the functional things I miss in Python:

• Pattern matching
• Tail recursion
• Large library of list functions
• Functional dictionary class
• Automatic currying
• Concise way to compose functions
• Lazy lists
• Simple, powerful expression syntax (Python's simple block syntax prevents Guido from adding it)

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• No pattern matching and no tail recursion mean your basic algorithms have to be written imperatively. Recursion is ugly and slow in Python.
• A small list library and no functional dictionaries mean that you have to write a lot of stuff yourself.
• No syntax for currying or composition means that point-free style is about as full of punctuation as explicitly passing arguments.
• Iterators instead of lazy lists means that you have to know whether you want efficiency or persistence, and to scatter calls to list around if you want persistence. (Iterators are use-once)
• Python's simple imperative syntax, along with its simple LL1 parser, mean that a better syntax for if-expressions and lambda-expressions is basically impossible. Guido likes it this way, and I think he's right.

Answer 2

Guido has a good explanation of this here. Here's the most relevant part:

I have never considered Python to be heavily influenced by functional languages, no matter what people say or think. I was much more familiar with imperative languages such as C and Algol 68 and although I had made functions first-class objects, I didn't view Python as a functional programming language. However, earlier on, it was clear that users wanted to do much more with lists and functions.

...

It is also worth noting that even though I didn't envision Python as a functional language, the introduction of closures has been useful in the development of many other advanced programming features. For example, certain aspects of new-style classes, decorators, and other modern features rely upon this capability.

Lastly, even though a number of functional programming features have been introduced over the years, Python still lacks certain features found in “real” functional programming languages. For instance, Python does not perform certain kinds of optimizations (e.g., tail recursion). In general, because Python's extremely dynamic nature, it is impossible to do the kind of compile-time optimization known from functional languages like Haskell or ML. And that's fine.

I pull two things out of this:

1. The language's creator doesn't really consider Python to be a functional language. Therefore, it's possible to see "functional-esque" features, but you're unlikely to see anything that is definitively functional.
2. Python's dynamic nature inhibits some of the optimizations you see in other functional languages. Granted, Lisp is just as dynamic (if not more dynamic) as Python, so this is only a partial explanation.