Python map() is an inbuilt capacity that is utilized to apply the capacity on every one of the components of determining iterable and return map objects.
The guide() work applies the offered capacity to everything of an iterable like the rundown, tuple, and so on, and returns the yield as a rundown.
The syntax of the map() is the following.
Map(function, iterable, …)
Function – The map() strategy passes everything of the iterable to this function.
Iterable – An iterable which is to be planned like a rundown, tuple, word reference, or set.
Python Map function
Python map() work applies a given to the capacity to everything of an iterable and returns a rundown of the outcomes.
Python’s map() is an implicit capacity that permits you to measure and change every one of the things in an iterable without utilizing an express for circle, a strategy generally known as planning. Map() is helpful when you need to apply a change capacity to everything in an iterable and change them into another iterable.
Map() is one of the devices that help a utilitarian programming style in Python.
If you provide multiple iterations to map(), the transformation function must accept as many parameters as you pass in the iteration. Each iteration of the map() passes the value of each iteration as a parameter to the function. The iteration stops at the most repeatable end.
Using Method of str
A fairly common way to manipulate strings is to use some methods of the str class to convert a given string into a new string. If you need to iterate through strings and apply the same transformation to each string, you can use map() in conjunction with multiple string methods.
string_it = ["processing", "strings", "with", "map"] print(list(map(str.capitalize, string_it))) print(list(map(str.upper, string_it))) print(list(map(str.lower, string_it)))
You can use the map() and string methods to perform some transformations on any element in string_it. In most cases, you will use methods without additional parameters, such as str.capitalize(), str.lower(), str.swapcase(), str.title(), and str.upper().
You can also use some methods with optional parameters with default values, for example, b.str.strip(), which accepts an optional parameter named char, and removes spaces by default.
with_spaces = ["processing", "strings", "with", "map"] print(list(map(str.strip, with_spaces)))
When you use str. strip() in this way, it relies on standard characters. In this case, use map() to remove all spaces in the with_spaces element.
In word processing, sometimes it is necessary to remove the punctuation marks left after the text is broken down into words.
To solve this problem, you can create a custom function that uses a regular expression that matches the most common punctuation to remove punctuation from a single word.
import re def remove_punctuation(word): return re.sub(r'[^\w\s]', "", word) print(remove_punctuation("Python!........"))
In remove_punctuation (), use a regular expression pattern that matches the most common punctuation found in any text written in English.
Call re.sub() to replace the appropriate punctuation with an empty string (“”) and return the empty word. Using the conversion function, you can use map() to trigger the conversion of any word in the text.