srakapatch.blogg.se - Scala filter method map

#SCALA FILTER METHOD MAP GENERATOR#

Let me clarify this with another example. So, if the function you're passing requires two, or three, or n arguments, then you need to pass in two, three or n iterables to it. What's more important to note is that the str.upper function requires only one argument by definition and so we passed just one iterable to it. Also note that we did not call the str.upper function (doing this: str.upper()), as the map function does that for us on each element in the my_pets list. Note that using the defined map() syntax above, func in this case is str.upper and iterables is the my_pets list - just one iterable. Uppered_pets = list(map(str.upper, my_pets)) With map() functions, it's not only easier, but it's also much more flexible. Traditonally, in normal pythoning, I would do something like this: my_pets = Say I have a list ( iterable) of my favourite pet names, all in lower case and I need them in uppercase. Let's see how these rules play out with the following examples.

The number of arguments to func must be the number of iterables listed.

To get the result as a list, the built-in list() function can be called on the map object.

#SCALA FILTER METHOD MAP GENERATOR#

In Python 3, however, the function returns a map object which is a generator object.

In Python 2, the map() function returns a list.

Before we move on to an example, it's important that you note the following: Notice the asterisk( *) on iterables? It means there can be as many iterables as possible, in so far func has that exact number as required input arguments.

Where func is the function on which each element in iterables (as many as they are) would be applied on. The map() function in python has the following syntax:

Let's get a better understanding of how they all work, starting with map. reduce, however, needs to be imported as it resides in the functools module. map and filter come built-in with Python (in the _builtins_ module) and require no importing. They allow the programmer (you) to write simpler, shorter code, without neccessarily needing to bother about intricacies like loops and branching.Įssentially, these three functions allow you to apply a function across a number of iterables, in one fell swoop. Map, Filter, and Reduce are paradigms of functional programming.