The Hacker's Guide to Scaling Python/

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Functional Programming Toolkit: "next", "first", and "itertools"

Functional Programming Toolkit: "next", "first", and "itertools"

Learn functional programming in Python.

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There’s still one essential tool missing from this list. One common task when working with lists is finding the first item that satisfies a specific condition. This is usually accomplished with a function like this:

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def first_positive_number(numbers):
  for n in numbers:
    if n > 0:
      return n
mylist = [-1, -10, 5, 7, -3, 8]
print( first_positive_number(mylist) )

We can also write this in functional style:

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def first(predicate, items):
    for item in items:
        if predicate(item):
            return item
print( first(lambda x: x > 0, [-1, 0, 1, 2]) )

Using next

You can also return first positive number more concisely like this:

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# Less efficient
list(filter(lambda x: x > 0, [-1, 0, 1, 2]))[0]
# Efficient but for Python 3
next(filter(lambda x: x > 0, [-1, 0, 1, 2]))
# Efficient but for Python 2
next(itertools.ifilter(lambda x: x > 0, [-1, 0, 1, 2]))

Note: list(filter(lambda x: x > 0, [-1, 0, 1, 2]))[0] may elicit an IndexError if no items satisfy the condition, causing list(filter()) to return an empty list.

For simple cases you can also rely on next:

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a = range(10)
print(next(x for x in a if x > 3))

This will raise StopIteration if a condition can never be satisfied. In that case, the second argument of next can be used:

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a = range(10)
print(next((x for x in a if x > 10), 'default'))

Using first

Instead of writing this same function in every program you make, you can include the small, but very useful Python package first:

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from first import first
# Returns 42 because it is the first element in the list which is True
print(first([0, False, None, [], (), 42]))
# Returns -1 as it is the first element in the list which is True
print(first([-1, 0, 1, 2]))
# Returns 1 as it is the first element in the list which is True 
# according to the condition provided: (x > 0)
print(first([-1, 0, 1, 2], key=lambda x: x > 0))

The key argument can be used to provide a function which receives each item as an argument and returns a Boolean indicating whether it satisfies the condition.

You will notice that we used lambda in a good number of the examples so far in this chapter. In the first place, lambda was added to Python to facilitate functional programming functions such as map and ...

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