Why are Python lambdas useful? [closed]

Answer 1

Are you talking about lambda functions? Like

lambda x: x**2 + 2*x - 5

Those things are actually quite useful. Python supports a style of programming called functional programming where you can pass functions to other functions to do stuff. Example:

mult3 = filter(lambda x: x % 3 == 0, [1, 2, 3, 4, 5, 6, 7, 8, 9])

sets mult3 to [3, 6, 9], those elements of the original list that are multiples of 3. This is shorter (and, one could argue, clearer) than

def filterfunc(x):
    return x % 3 == 0
mult3 = filter(filterfunc, [1, 2, 3, 4, 5, 6, 7, 8, 9])

Of course, in this particular case, you could do the same thing as a list comprehension:

mult3 = [x for x in [1, 2, 3, 4, 5, 6, 7, 8, 9] if x % 3 == 0]

(or even as range(3,10,3)), but there are many other, more sophisticated use cases where you can't use a list comprehension and a lambda function may be the shortest way to write something out.

• Returning a function from another function

  >>> def transform(n):
  ...     return lambda x: x + n
  ...
  >>> f = transform(3)
  >>> f(4)
  7
  

  This is often used to create function wrappers, such as Python's decorators.

• Combining elements of an iterable sequence with reduce()

  >>> reduce(lambda a, b: '{}, {}'.format(a, b), [1, 2, 3, 4, 5, 6, 7, 8, 9])
  '1, 2, 3, 4, 5, 6, 7, 8, 9'
  

• Sorting by an alternate key

  >>> sorted([1, 2, 3, 4, 5, 6, 7, 8, 9], key=lambda x: abs(5-x))
  [5, 4, 6, 3, 7, 2, 8, 1, 9]
  

I use lambda functions on a regular basis. It took me a while to get used to them, but eventually I came to understand that they're a very valuable part of the language.

Answer 2

Lambdas are actually very powerful constructs that stem from ideas in functional programming, and it is something that by no means will be easily revised, redefined or removed in the near future of Python. They help you write code that is more powerful as it allows you to pass functions as parameters, thus the idea of functions as first-class citizens.

Lambdas do tend to get confusing, but once a solid understanding is obtained, you can write clean elegant code like this:

squared = map(lambda x: x*x, [1, 2, 3, 4, 5])

The above line of code returns a list of the squares of the numbers in the list. Ofcourse, you could also do it like:

def square(x):
    return x*x

squared = map(square, [1, 2, 3, 4, 5])

It is obvious the former code is shorter, and this is especially true if you intend to use the map function (or any similar function that takes a function as a parameter) in only one place. This also makes the code more intuitive and elegant.

Also, as @David Zaslavsky mentioned in his answer, list comprehensions are not always the way to go especially if your list has to get values from some obscure mathematical way.

From a more practical standpoint, one of the biggest advantages of lambdas for me recently has been in GUI and event-driven programming. If you take a look at callbacks in Tkinter, all they take as arguments are the event that triggered them. E.g.

def define_bindings(widget):
    widget.bind("<Button-1>", do-something-cool)

def do-something-cool(event):
    #Your code to execute on the event trigger

Now what if you had some arguments to pass? Something as simple as passing 2 arguments to store the coordinates of a mouse-click. You can easily do it like this:

def main():
    # define widgets and other imp stuff
    x, y = None, None
    widget.bind("<Button-1>", lambda event: do-something-cool(x, y))

def do-something-cool(event, x, y):
    x = event.x
    y = event.y
    #Do other cool stuff

Now you can argue that this can be done using global variables, but do you really want to bang your head worrying about memory management and leakage especially if the global variable will just be used in one particular place? That would be just poor programming style.

In short, lambdas are awesome and should never be underestimated. Python lambdas are not the same as LISP lambdas though (which are more powerful), but you can really do a lot of magical stuff with them.

Answer 3

I use lambdas to avoid code duplication. It would make the function easily comprehensible Eg:

def a_func()
  ...
  if some_conditon:
     ...
     call_some_big_func(arg1, arg2, arg3, arg4...)
  else
     ...
     call_some_big_func(arg1, arg2, arg3, arg4...)

I replace that with a temp lambda

def a_func()
  ...
  call_big_f = lambda args_that_change: call_some_big_func(arg1, arg2, arg3, args_that_change)
  if some_conditon:
     ...
     call_big_f(argX)
  else
     ...
     call_big_f(argY)

Answer 4

First congrats that managed to figure out lambda. In my opinion this is really powerful construct to act with. The trend these days towards functional programming languages is surely an indicator that it neither should be avoided nor it will be redefined in the near future.

You just have to think a little bit different. I'm sure soon you will love it. But be careful if you deal only with python. Because the lambda is not a real closure, it is "broken" somehow: pythons lambda is broken

Answer 5

I doubt lambda will go away. See Guido's post about finally giving up trying to remove it. Also see an outline of the conflict.

You might check out this post for more of a history about the deal behind Python's functional features: http://python-history.blogspot.com/2009/04/origins-of-pythons-functional-features.html

Curiously, the map, filter, and reduce functions that originally motivated the introduction of lambda and other functional features have to a large extent been superseded by list comprehensions and generator expressions. In fact, the reduce function was removed from list of builtin functions in Python 3.0. (However, it's not necessary to send in complaints about the removal of lambda, map or filter: they are staying. :-)

My own two cents: Rarely is lambda worth it as far as clarity goes. Generally there is a more clear solution that doesn't include lambda.

Answer 6

I use it quite often, mainly as a null object or to partially bind parameters to a function.

Here are examples:

to implement null object pattern:

{
    DATA_PACKET: self.handle_data_packets
    NET_PACKET: self.handle_hardware_packets
}.get(packet_type, lambda x : None)(payload)

for parameter binding:

let say that I have the following API

def dump_hex(file, var)
    # some code
    pass

class X(object):
    #...
    def packet_received(data):
        # some kind of preprocessing
        self.callback(data)
    #...

Then, when I wan't to quickly dump the recieved data to a file I do that:

dump_file = file('hex_dump.txt','w')
X.callback = lambda (x): dump_hex(dump_file, x)
...
dump_file.close()