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I've been a procedural programmer for a while now, and just trying to switch my mindset to use functional programming (in Python 3 for now). So, instead of writing a for-each loop, I'm trying to grasp the interaction between map and list(map(..))

Lets say I have a simple for-in loop which does some resource heavy computation (which I'll replace with print here for the sake of simplicity):

arr = [1,2,3,4]    
for x in arr:
    print(x)

Now, when I try to do the following

map(lambda x: print(x), arr)

nothing happens, UNTIL, i wrap this in a list and it does my super heavy print function:

list(map(lambda x: print(x), arr))

Why? What am I missing? I understand map returns an iterator which is supposed to save memory instead of just holding the entire list right away. But when is my super heavy print function going to be triggered then?

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  • Okay, I understand those concepts, they're not foreign to me. My question is, why doesn't the function work when I'm not applying the list wrapper? Because I have to trigger it through the iterator? Commented Feb 26, 2018 at 22:10
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    Yes @OgnjenMišić. map is what's commonly know as being lazy. It won't do any work (i.e. call you function to compute any values) unless it has to. You can force map to compute a single value using next. When you cast the map iterator to be a list however, you're forcing map to compute all of its values and thus call your function. Commented Feb 26, 2018 at 22:13
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    Because it does not return you a list of values. It returns the iterator itself. Then you call next(some_iterator) on it to consume the next value, one by one. Until all values are consumed. Applying list to it will make it for all the values and returns you a list with all the iterator values. Or you can use a for loop Commented Feb 26, 2018 at 22:16
  • Okay, tried it out, thanks guys, it's much more clear now. @ChristianDean post your response so I can accept :) Commented Feb 26, 2018 at 22:17
  • And to be frank, I was expecting it to work like the JS version of map, but then again now that one also makes sense. Commented Feb 26, 2018 at 22:18

2 Answers 2

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Why? What am I missing? I understand map returns an iterator which is supposed to save memory instead of just holding the entire list right away. But when is my super heavy print function going to be triggered then?

The map function is what's commonly known in programmer terminology as lazy. It won't do any work unless it has to. This is more broadly known as in functional programming as lazy evaluation. Rather than immediately compute any values, the map function instead returns what's known as an iterator. By doing this, it's delegating the job of compute the values it was given back to you.

A single value can be computed by the iterator using next:

>>> arr = [1, 2, 3]
>>> it = map(lambda x: print(x), arr)
>>> next(it)
1
>>>

However, when you casted the map iterator to be a list, you were forcing map to compute all of its values and thus call your function:

>>> it = map(lambda x: print(x), arr)
>>> list(it)
1
2
3
4
[None, None, None, None]
>>>
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As you said, you have to switch your mindset to use functional programming. One of the key concepts of functional programming is lazy evaluation, which is the default policy in languages such as Haskell.

The purpose of this policy is to save both time and memory, by calculating something only when it is needed. In that sense Python generators are also close to the functional paradigm.

If you want to execute it as soon as possible, you shouldn't write it in a functional style and fix it with list() if you don't care about the results. Using a loop is totally ok.

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4 Comments

Nice answer Louis! This sums up the idea and purpose behind map and lazy evaluation nicely. +1
Thanks for the response. I know that using a loop is fine, but then when does one write functional and when procedural? Lets say I have some nested for loops, is it fine to just inline them with list wrapper and execute one list-map-lambda one after another or to still stick with nesting?
It real depends @OgnjenMišić. There both valid programming paradigms that each have pros and cons. In the case of your specific example, I'd opt to use nested for loops rather than nested map calls as it'd generally be faster. Also look into comprehensions and see the question "OOP vs Functional Programming vs Procedural "
@OgnjenMišić in general, list-comprehensions are preferred over map + lambda and filter + lambda, note, list/generator/set/dict comprehensions are more efficient when you want to map and filter at the same time. But in Python, you should only go with these constructs when readable, and don't use side-effects inside of them (... like print...)

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