This article shows you how to apply a given function to each element of a tuple.
The best way to apply a function to each element of a tuple is the Python built-in
map(function, iterable) function that takes a function and an iterable as arguments and applies the function to each iterable element. An alternate way is to use list comprehension.
Note: All the solutions provided below have been verified in Python 3.9.5.
Imagine the following tuple of strings in Python.
my_tuple = ('you', 'cannot', 'exercise', 'away', 'a', 'bad', 'diet')
How does one apply a function
string.upper() to uppercase each string in the tuple?
('YOU', 'CANNOT', 'EXERCISE', 'AWAY', 'A', 'BAD', 'DIET')
I’ll start with the “naive approach” first and show you the more Pythonic solutions afterward. So, let’s get started!
Method 1: Simple For Loop
The above problem, like many others, has quite a simple solution in Python.
A simple solution uses a vanilla Python loop to iterate over each element of the original tuple. Apply the function to each element in the loop body and store the elements in a mutable container type such as a list. Finally, create a new tuple using the
tuple() constructor and pass the new elements as arguments.
The result is a tuple of new elements — here stored in the variable
new_tuple after applying the function
string.upper() to each element of a Python tuple:
my_tuple = ('you', 'cannot', 'exercise', 'away', 'a', 'bad', 'diet') tmp =  for element in my_tuple: # Apply function to each element here: tmp.append(element.upper()) # Create a new tuple here: new_tuple = tuple(tmp) print(new_tuple) # ('YOU', 'CANNOT', 'EXERCISE', 'AWAY', 'A', 'BAD', 'DIET')
However, this is not the most Pythonic way to approach this problem.
Method 2: map()
Using the Python built-in
map() function is the most efficient and elegant way to solve the problem. The
map(function, iterable) function takes a function and an iterable as arguments and applies the given
function to each element of the
For example, to apply the
string.upper() function to each element of a Python tuple, use the
map(str.upper, my_tuple) function to obtain a generator object. Now, convert the result to a tuple using the
tuple() constructor and you’ve solved the problem!
This method is shown in the following code snippet:
# 'my_tuple' is the original tuple whose string elements need to be # fully uppercased. Note that 'my_tuple' is an object of the Python # built-in Tuple class. Lists, Sets, Dicts and Tuples are considered # iterables. my_tuple = ('you', 'cannot', 'exercise', 'away', 'a', 'bad', 'diet') # Use the upper() function of Python's built-in str class, to modify # each element of the my_tuple iterable. my_generic_iterable = map(str.upper, my_tuple) # map() returns an iterable (or generator) object. # It contains all the modified elements. Generators are temporary container # objects. They can be iterated upon only once, to extract the elements # within them. For example, use the 'tuple()' constructor to go thru each # element of the 'my_generic_iterable' generator and generate a tuple. new_tuple = tuple(my_generic_iterable) print(new_tuple) # Output: # ['YOU', 'CANNOT', 'EXERCISE', 'AWAY', 'A', 'BAD', 'DIET']
If you need a quick explanation of the
map() function, feel free to watch my training video here:
Personally, I’d use the following method—but this is only a matter of personal style.
Method 3: Generator Expression
You can use generator expressions to apply a function to each element of a tuple.
Here’s how to accomplish that:
my_tuple = ('you', 'cannot', 'exercise', 'away', 'a', 'bad', 'diet') new_tuple = tuple(str.upper(x) for x in my_tuple) print(new_tuple) # Output: # ['YOU', 'CANNOT', 'EXERCISE', 'AWAY', 'A', 'BAD', 'DIET']
Generator expressions are similar to list comprehensions. You can learn more about list comprehensions in the following video—generator expressions work analogously but are more generally applicable:
The following video shows how to apply a function to each element of a Python list. This is very similar to our problem, so it applies analogously to the solutions presented here:
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