Shorter alternative for 'lambda' keyword?

Question

Background:

Python is about simplicity and readable code. It has gotten better over the versions and I am a huge fan! However, typing l a m b d a every time I have to define a lambda is not fun (you may disagree). The problem is, these 6 characters l a m b d a make my statements longer, especially if I nest a couple of lambdas inside maps and filters. I am not nesting more than 2 or three, because it takes away the readability of python, even then typing l a m b d a feels too verbose.

The actual question (is in comments):

# How to rename/alias a keyword to a nicer one? 
lines = map(lmd x: x.strip(), sys.stdin)

# OR, better yet, how to define my own operator like -> in python?
lines = map(x -> x.strip(), sys.stdin)
# Or may be :: operator is pythonic
lines = map(x :: x.strip(), sys.stdin)

# INSTEAD of this ugly one. Taking out this is my goal!
lines = map(lambda x: x.strip(), sys.stdin)

I am happy to add import like this:

from myfuture import lmd_as_lambda
# OR
from myfuture import lambda_operator

Answer 1

The good news is: You don't need to use map or filter at all, you can use generator expressions (lazy) or list comprehensions (eager) instead and thus avoid lambdas completely.

So instead of:

lines = map(lambda x: x.strip(), sys.stdin)

Just use:

# You can use either of those in Python 2 and 3, but map has changed between
# Python 2 and Python 3 so I'll present both equivalents:
lines = (x.strip() for x in sys.stdin)  # generator expression (Python 3 map equivalent)
lines = [x.strip() for x in sys.stdin]  # list comprehension   (Python 2 map equivalent)

It's probably also faster if you use comprehensions. Very few functions are actually faster when used in map or filter - and using a lambda there is more of an anti-pattern (and slow).

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The question only contained an example for map, but you can also replace filter. For example if you want to filter out odd numbers:

filter(lambda x: x%2==0, whatever)

You can use a conditional comprehension instead:

(x for x in whatever if x%2==0)
[x for x in whatever if x%2==0]

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You could even combine a map and filter in one comprehension:

(x*2 for x in whatever if x%2==0)

Just consider how that would look like with map and filter:

map(lambda x: x*2, filter(lambda x: x%2==0, whatever))

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Note: That doesn't mean lambda isn't useful! There are lots of places where lambdas are very handy. Consider the key argument for sorted (and likewise for min and max) or functools.reduce (but better keep away from that function, most of the times a normal for-loop is more readable) or itertools that require a predicate function: itertools.accumulate, itertools.dropwhile, itertools.groupby and itertools.takewhile. Just to name a few examples where a lambda could be useful, there are probably lots of other places as well.

Answer 2

To answer your specific question, the operator module provides several functions intended to replace specific uses of a lambda expression. Here, you can use the methodcaller function to create a function that calls a given method on an object.

from operator import methodcaller as mc

lines = map(mc('strip'), sys.stdin)

However, list comprehensions tend to be preferred to many, if not most, uses of map.

lines = [x.strip() for x in sys.stdin]

Answer 3

As a person who never uses lambdas in his code except for debugging purposes, I can suggest several alternatives.

I won't speak about defining your own syntax in an editor (you can't define operators in a pure Python though: Python: defining my own operators?) but just about built-in stuff.

1. Methods of built-in types:
   Compare the following:

   words = ['cat', 'dog', 'shark']
   result_1 = map(lambda x: x.upper(), words)
   result_2 = (x.upper() for x in words)
   result_3 = map(str.upper, words)
   # ['CAT', 'DOG', 'SHARK']
   

   Using map with str.upper is shorter than both map with lambda and a generator expression proposed in another answer.
   You can find lots of other methods in the docs for different types such as int, float, str, bytes and others, which you can use in the same manner. For example, checking if numbers are integers:

   numbers = [1.0, 1.5, 2.0, 2.5]
   result_1 = map(lambda x: x.is_integer(), numbers)
   result_2 = (x.is_integer() for x in numbers)
   result_3 = map(float.is_integer, numbers)
   # [True, False, True, False]
   

2. Class methods:
   In a similar way you can use map with class methods:

   class Circle:
       def __init__(self, radius):
           self.radius = radius
       def area(self):
           return 3.14 * self.radius ** 2
   
   circles = [Circle(2), Circle(10)]
   result_1 = map(lambda x: x.area(), circles)
   result_2 = (x.area() for x in circles)
   result_3 = map(Circle.area, circles)
   # [12.56, 314.0]
   

3. operator module:

   • itemgetter:
     This one is used when you want to select elements by their indices:

     from operator import itemgetter
     
     numbers = [[0, 1, 2, 3],
                [4, 5, 6, 7],
                [8, 9, 0, 1]]
     result_1 = map(lambda x: x[0], numbers)
     result_2 = (x[0] for x in numbers)
     result_3 = map(itemgetter(0), numbers)
     # [0, 4, 8]
     

     While it is longer than generator expression in the given example, it will actually be shorter when you want to select several elements at once:

     result_1 = map(lambda x: (x[0], x[2], x[3]), numbers)
     result_2 = ((x[0], x[2], x[3]) for x in numbers)
     result_3 = map(itemgetter(0, 2, 3), numbers)
     # [(0, 2, 3), (4, 6, 7), (8, 0, 1)]
     

     You can also use itemgetter with dictionaries:

     data = [{'time': 0, 'temperature': 290, 'pressure': 1.01},
             {'time': 10, 'temperature': 295, 'pressure': 1.04},
             {'time': 20, 'temperature': 300, 'pressure': 1.07}]
     
     result_1 = map(lambda x: (x['time'], x['pressure']), data)
     result_2 = ((x['time'], x['pressure']) for x in data)
     result_3 = map(itemgetter('time', 'pressure'), data)
     # [(0, 1.01), (10, 1.04), (20, 1.07)]
     

   • attrgetter
     This one is used to get attributes of objects:

     from collections import namedtuple
     from operator import attrgetter
     
     Person = namedtuple('Person', ['name', 'surname', 'age', 'car'])
     people = [Person(name='John', surname='Smith', age=40, car='Tesla'), 
               Person(name='Mike', surname='Smith', age=50, car=None)]
     result_1 = map(lambda x: (x.name, x.age, x.car), people)
     result_2 = ((x.name, x.age, x.car) for x in people)
     result_3 = map(attrgetter('name', 'age', 'car'), people)
     # [('John', 40, 'Tesla'), ('Mike', 50, None)]
     

     It is longer than the generator expression version, so I'm leaving it here just for completeness. Of course, you can import attrgetter as get and it will be shorter but nobody really does that. Using attrgetter has an advantage, though, that you could take it out as a separate callable that could be used more than once (same as lambda):

     get_features = attrgetter('name', 'age', 'car')
     group_1_features = map(get_features, people)
     group_2_features = map(get_features, other_people)
     ...
     

     Another alternative worth to mention is using fget method of properties:

     result = map(Person.age.fget, people)
     

     I've never seen anyone using it though, so prepare to give explanation to people who will read your code if you use it.

   • contains:
     Used to check if an element is present in another object/container:

     from functools import partial
     from operator import contains
     
     fruits = {'apple', 'peach', 'orange'}
     objects = ['apple', 'table', 'orange']
     result_1 = map(lambda x: x in fruits, objects)
     result_2 = (x in fruits for x in objects)
     is_fruit = partial(contains, fruits)
     result_3 = map(is_fruit, objects)
     # [True, False, True]
     

     This, though, has a drawback of creating an additional partial object. Another way to write this would be to use __contains__ method:

     result = map(fruits.__contains__, objects)
     

     But some people argue that it is a bad practice to use dunder methods as those are just for a private use.

   • Mathematical operations:
     For example, if you would want to sum pairs of numbers, you could use operator.add:

     from itertools import starmap
     from operator import add
     
     pairs = [(1, 2), (4, 3), (1, 10), (2, 5)]
     result_1 = map(lambda x: x[0] + x[1], pairs)
     result_2 = (x + y for x, y in pairs)
     result_3 = starmap(add, pairs)
     # [3, 7, 11, 7]
     

     If you are fine with two additional imports then this is the shortest option. Note that we use itertools.starmap here because we need to unpack tuples of numbers before supplying them to add(a, b) function.

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I think I covered most of the cases that I constantly encounter that could be rewritten without lambda. If you know more, please, write it in a comment, and I will add it to my answer.