Functional Programming in Python - II
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In my last blog, we saw how higher order functions work in Python using
filter. The filter method takes a list object and another function and another function and it uses this function to filter out the elements from a list. In this post, we learn about a new(read awesome) higher order function called
map function takes in two arguments; a function and a list. Similar to filter, it goes through the list but unlike filter, it doesn’t throw the objects away, rather it transforms them into a new list.
Let us see a simple function
li = list(range(0,5)) new_li =  def squared(x): for i in x: new_li.append(i**2) return new_li print sqared(li) # Output [0, 1, 4, 9, 16]
Boo boring!! code base wants the functional way..
Now let’s see how we can do it in functional way
li = list(range(0,5)) def squared(x): return x**2 print map(squared, li) # Output [0, 1, 4, 9, 16]
Now let’s see how if can make it one-liner using
li = list(range(0,5)) print map(lambda x: x**2, li) # Output [0, 1, 4, 9, 16]
Just gorgeous right?! With the help of map, we have just compressed the whole function in a single line. It is, however, important to note that the map function always returns a list type just like the filter.
Now we will talk about another higher order function called
reduce. The reduce function is a little less obvious in its intent. This function reduces a list to a single value by combining elements via a supplied function. Similar to map and filter, it takes two arguments; a function and a list. It is, however, notable that the return type of reduce is not always list. Let us see what we mean by that. But first let’s write a normal function in all its glory:
li = list(range(1,5)) prod = 1 def product(x): for i in x: prod = prod * i return prod print product(li) #Output 24
Now the functional way
print reduce(lambda x,y: x*y, list(range(1,5))) # Output 24
BAM! Now let us see another example of reduce:
fox = ['What ', 'does ', 'the ', 'fox ', 'say', '?'] print reduce(lambda x,y: x+y, fox) # Output # What does the fox say?
Over here, lambda function takes two arguments x and y. The x is what it iterates from the list and y is what is returned from lambda. Like so:
|I||“What “||“does “||“What does “||[‘What does ‘, ‘the ‘, ‘fox ‘, ‘say’, ‘?’]|
|II||“What does “||“the “||“What does the “||[‘What does the ‘, ‘fox ‘, ‘say’, ‘?’]|
|III||“What does the “||“fox “||“What does the fox “||[‘What does the fox ‘, ‘say’, ‘?’]|
|IV||“What does the fox “||“say “||“What does the fox say”||[‘What does the fox say’, ‘?’]|
|V||“What does the fox say”||”?”||“What does the fox say?”||[‘What does the fox say?’]|
If you don’t see the beauty in this, I really am tending to believe that you are an alien and you have devised a super neat and better trick on your planet.
That concludes the Functional Programming with Python. FPs take a bit to master on but once you start using it, you will see its application practically everywhere in your codebase.