Mastering Python len() Function [In-Depth Tutorial]


Getting started with Python len()

The len() function in Python is a built-in function that returns the number of items in an object. It's one of the simplest and most frequently used functions in Python for determining the length or size of various types of data structures like lists, tuples, strings, dictionaries, and sets. The function helps to make code more readable and allows for more efficient manipulation of data. Whether you're iterating through a list or validating the length of a string input, len() provides a convenient way to evaluate the size of your data.


Syntax of len()

The basic syntax of the len() function in Python is quite simple. It takes a single argument: the object whose length you want to determine.


Here, object can be various Python data types like lists, tuples, strings, dictionaries, etc.


Basic Examples

Let's look at some straightforward examples to understand how to use len().

For a String:

string = "Hello, World!"
length = len(string)
print(length)  # Output: 13

For a List:

my_list = [1, 2, 3, 4, 5]
length = len(my_list)
print(length)  # Output: 5

For a Tuple:

my_tuple = (1, 2, 3, 4, 5)
length = len(my_tuple)
print(length)  # Output: 5

For a Dictionary:

my_dict = {'one': 1, 'two': 2, 'three': 3}
length = len(my_dict)
print(length)  # Output: 3

For a Set:

my_set = {1, 2, 3, 4, 5}
length = len(my_set)
print(length)  # Output: 5


Working with Sequences

len() with Lists, Tuples, and Strings

The len() function works seamlessly with sequences like lists, tuples, and strings. Here's how you can use it:

With Lists:

# Define a list of integers
my_list = [1, 2, 3, 4, 5, 6]

# Use len() to find the length of the list
list_length = len(my_list)

print("Length of the list:", list_length)  # Output: Length of the list: 6

With Tuples:

# Define a tuple of integers
my_tuple = (10, 20, 30, 40, 50)

# Use len() to find the length of the tuple
tuple_length = len(my_tuple)

print("Length of the tuple:", tuple_length)  # Output: Length of the tuple: 5

With Strings:

# Define a string
my_string = "Python is awesome"

# Use len() to find the length of the string
string_length = len(my_string)

print("Length of the string:", string_length)  # Output: Length of the string: 17


Objects Supported by len()

The len() function is quite versatile and works with various types of objects in Python. Below are some of the most common objects you can use with len().


Using len() with a list returns the number of elements in the list.

len([1, 2, 3, 4])  # Output: 4


With tuples, len() returns the number of elements.

len((1, 2, 3))  # Output: 3


In the case of strings, len() returns the number of characters in the string.


len() can also be used with dictionaries to find the number of key-value pairs.

len({"name": "Alice", "age": 30})  # Output: 2


With sets, len() returns the number of unique elements.

len({1, 2, 3, 3, 4})  # Output: 4

Custom Objects

For custom objects, you can define the __len__() method to make them compatible with the len() function.

class MyClass:
    def __len__(self):
        return 5

my_instance = MyClass()
len(my_instance)  # Output: 5


Working with Collections

When dealing with collections like dictionaries and sets, the len() function can be a handy tool for quickly determining the size or length of the collection. Here's how you can use len() for these types:


In dictionaries, len() returns the number of key-value pairs. This can be particularly useful when you want to check if a dictionary has elements before performing operations on it.

# Create a dictionary with three key-value pairs
my_dict = {'apple': 1, 'banana': 2, 'cherry': 3}

# Get the number of key-value pairs
length = len(my_dict)

print(f"The dictionary has {length} key-value pairs.")  # Output: The dictionary has 3 key-value pairs.


When it comes to sets, len() returns the number of unique elements. This can be useful in scenarios where you want to ensure that a set has elements before looping through it, or to simply check how many unique items are in the set.

# Create a set with some duplicate elements
my_set = {1, 2, 3, 3, 4}

# Get the number of unique elements
length = len(my_set)

print(f"The set has {length} unique elements.")  # Output: The set has 4 unique elements.


Working with Custom Objects

When working with custom objects, you can also make them compatible with the len() function by defining a __len__() method in the class. The __len__() method should return an integer, which will be returned when len() is called on an object of that class.

Implementing __len__() Method

To make a custom object compatible with len(), you should implement the __len__() method within the class. This method should return the length or size of the object in some meaningful way.

Here's a simple example where a class MyList mimics a list, and we implement __len__() to return the number of elements in the list.

class MyList:
    def __init__(self, items=[]):
        self.items = items

    def __len__(self):
        return len(self.items)

# Create an object of MyList
my_list = MyList([1, 2, 3, 4])

# Get the length of my_list
length = len(my_list)

print(f"MyList object has {length} items.")  # Output: MyList object has 4 items.

In this example, when len(my_list) is called, Python internally calls my_list.__len__() and returns the result.

This way, you can make your custom objects work seamlessly with Python's built-in len() function by defining a suitable __len__() method.


Common Use-Cases

The len() function is one of the most frequently used built-in functions in Python due to its versatility. Here are some common use-cases where len() comes in handy:

Finding the Number of Items in a List

You can find the number of items in a list by passing it as an argument to the len() function. This is especially useful when you need to iterate over the list or allocate resources based on its size.

my_list = [1, 2, 3, 4, 5]
print(len(my_list))  # Output: 5

Length of a String

Finding the length of a string is a common operation in text processing. The len() function returns the number of characters in a string.

my_string = "Hello, World!"
print(len(my_string))  # Output: 13

Number of Keys in a Dictionary

When working with dictionaries, you may want to know the number of key-value pairs in it. You can use len() to get the count of keys.

my_dict = {'a': 1, 'b': 2, 'c': 3}
print(len(my_dict))  # Output: 3


Performance Considerations

The performance of len() can vary depending on the type of object you're dealing with. However, for Python's built-in types like lists, strings, and dictionaries, the len() function generally operates in constant time, O(1), making it a fast and efficient option.

Time Complexity of len()

  • Lists, Strings, and Tuples: O(1)
  • Dictionaries and Sets: O(1)

This means that regardless of the size of the sequence or collection, len() will return the result in constant time.

len() vs Alternative Methods

You could manually iterate over a list or string to count the number of elements, but that would be inefficient compared to len().

Example 1: Counting list elements using len()

import time

my_list = list(range(1, 1000000))

start_time = time.time()
length = len(my_list)
end_time = time.time()

print(f"Length using len(): {length}")
print(f"Time taken using len(): {end_time - start_time}")

Example 2: Counting list elements using a loop

start_time = time.time()

length = 0
for item in my_list:
    length += 1

end_time = time.time()

print(f"Length using loop: {length}")
print(f"Time taken using loop: {end_time - start_time}")

Output Data

The time taken by len() will almost always be significantly less than the time taken by the loop, proving the efficiency of len().

Length using len(): 999999
Time taken using len(): 0.0000012
Length using loop: 999999
Time taken using loop: 0.0826

These examples prove that len() is the most efficient way to find the length of most built-in Python objects.


Common Pitfalls and Mistakes

Using len() seems straightforward, but there are some common pitfalls and mistakes that both beginners and sometimes even experienced professionals make.

len() on Unsupported Types

The len() function doesn't support all types. Using len() on unsupported types will throw a TypeError. For example, trying to use len() on an integer or a float will result in an error.


# This will throw a TypeError


TypeError: object of type 'int' has no len()

Always make sure that the object you are passing to len() actually supports the operation.

len() vs count()

len() and count() serve different purposes, and confusing the two can lead to bugs in your code. The len() function tells you the number of elements in a sequence or collection, while count() is generally used to count the occurrence of a particular element within a sequence.

Example 1: Using len() on a list

my_list = [1, 2, 2, 3, 4]
length = len(my_list)  # Output will be 5

Example 2: Using count() on a list

count_of_twos = my_list.count(2)  # Output will be 2

In the first example, len() returns the total number of elements in the list, which is 5. In the second example, count() returns the number of occurrences of the integer 2, which is 2.

Using count() when you meant to use len() (or vice versa) can lead to completely different outcomes, so it's important to choose the right function for your needs.


Frequently Asked Questions

Is len() only for lists?

No, len() works with many types of collections, including strings, tuples, dictionaries, and sets. It also works with custom objects if they implement the __len__() method.

Is len() the same as .size or .count?

No, len() gives the number of elements in a sequence or collection. .size and .count are specific methods that serve different purposes depending on the object they are applied to.

Can len() return a negative number?

No, len() returns a non-negative integer, which can be zero if the sequence or collection is empty.

Is len() time-consuming for large lists?

Generally, no. The time complexity of len() is O(1) for built-in types like lists, strings, and dictionaries.

Can I use len() on a generator?

No, generators are not sized collections, and using len() on a generator will throw a TypeError.

Does len() work with nested lists or dictionaries?

len() will return the length of the outer list or dictionary. If you want to find the length of nested lists or dictionaries, you need to access them first.

What happens when I use len() on a string with multi-byte characters?

len() will return the number of characters, not the byte count. For Unicode strings, each character can be more than one byte.

Is len(None) valid?

No, attempting to find the length of None will result in a TypeError.

Why does len() not work on an integer or float?

len() is designed to work on sequences and collections. Integers and floats are not sequences.

Is len() different in Python 2 and Python 3?

The basic functionality is the same, but Python 3's len() has better support for Unicode strings.



  • What is len(): The len() function in Python is a built-in function that returns the number of items in an object.
  • Versatility: len() can be used on various types of objects like strings, lists, tuples, dictionaries, and sets.
  • Custom Objects: You can enable the len() function for your custom objects by defining a __len__() method.
  • Performance: The len() function generally has a time complexity of O(1) for built-in types, making it a fast and efficient way to get the size of a collection.
  • Common Pitfalls: Using len() on unsupported types like integers or generators will result in a TypeError.
  • Alternative Methods: Although len() is widely applicable, some objects have their own methods for similar operations, like .count() for lists or .size for NumPy arrays.


Additional Resources

For those who wish to dive deeper into the workings of Python's len() function, the following resources are invaluable:


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Deepak Prasad

Deepak Prasad

He is the founder of GoLinuxCloud and brings over a decade of expertise in Linux, Python, Go, Laravel, DevOps, Kubernetes, Git, Shell scripting, OpenShift, AWS, Networking, and Security. With extensive experience, he excels in various domains, from development to DevOps, Networking, and Security, ensuring robust and efficient solutions for diverse projects. You can connect with him on his LinkedIn profile.

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