Syntax
sequence[start:stop:step]Examples
Basic Slicing
Extracting a portion of a list or string by index range.
numbers = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
print(numbers[2:5]) # [2, 3, 4] (index 5 is excluded)
print(numbers[:4]) # [0, 1, 2, 3] (from the start)
print(numbers[6:]) # [6, 7, 8, 9] (to the end)
print(numbers[:]) # a full copy of the listNegative Indices
Counting from the end of a sequence.
text = "Codectionary"
print(text[-1]) # y (last character)
print(text[-4:]) # nary (last four characters)
print(text[:-4]) # Codectio (everything except the last four)Step Slicing
Skipping elements using the step parameter.
numbers = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
print(numbers[::2]) # [0, 2, 4, 6, 8] (every second item)
print(numbers[1::2]) # [1, 3, 5, 7, 9] (odd indices)Reversing with Slicing
A common idiom: [::-1] reverses any sequence.
text = "Python"
print(text[::-1]) # nohtyP
numbers = [1, 2, 3, 4, 5]
print(numbers[::-1]) # [5, 4, 3, 2, 1]Best practices
- Remember the stop index in a slice is exclusive - sequence[2:5] gives 3 items (indices 2, 3, 4), not 4
- Use sequence[:] to make a shallow copy of a list, a common and idiomatic pattern
- Use [::-1] for a quick, readable way to reverse a string, list, or tuple
- Slicing never raises an IndexError even with out-of-range indices - it just returns as much as is available, unlike direct indexing
At a glance
- Purpose
- Scripting and general-purpose applications
- File extension
- .py
- Runs in
- Python interpreter
- Usually used with
- Python standard library and packages
Specifications & further reading
Related Python documentation
Lists
A list is Python's built-in ordered, mutable collection type, created with square brackets. Lists can hold items of any type - even a mix of types - and support indexing, slicing, and a wide range of built-in methods for adding, removing, and reordering elements. Because they are mutable, lists can be changed in place after creation, which makes them the go-to structure for collections that grow or shrink over time.Tuples
A tuple is an ordered, immutable collection, created with parentheses (or often just commas). Once created, a tuple's contents cannot be changed, added to, or removed - this immutability makes tuples faster than lists and safe to use as dictionary keys or in sets. Tuples are commonly used for fixed collections of related values, like coordinates or RGB colors, and for returning multiple values from a function.Dictionaries
A dictionary stores data as key-value pairs, created with curly braces. Keys must be unique and hashable (strings, numbers, or tuples are common choices), while values can be anything, including other dictionaries or lists. Since Python 3.7, dictionaries maintain insertion order. They are one of the most heavily used data structures in Python, ideal for representing structured records, lookups, and mappings.Sets
A set is an unordered collection of unique, hashable items, created with curly braces or the set() function. Sets automatically eliminate duplicates and support fast membership testing, along with mathematical set operations like union, intersection, and difference. They're especially useful for deduplicating data and for comparing two collections to find overlaps or differences.
A list is Python's built-in ordered, mutable collection type, created with square brackets. Lists can hold items of any type - even a mix of types - and support indexing, slicing, and a wide range of built-in methods for adding, removing, and reordering elements. Because they are mutable, lists can be changed in place after creation, which makes them the go-to structure for collections that grow or shrink over time.Tuples
A tuple is an ordered, immutable collection, created with parentheses (or often just commas). Once created, a tuple's contents cannot be changed, added to, or removed - this immutability makes tuples faster than lists and safe to use as dictionary keys or in sets. Tuples are commonly used for fixed collections of related values, like coordinates or RGB colors, and for returning multiple values from a function.Dictionaries
A dictionary stores data as key-value pairs, created with curly braces. Keys must be unique and hashable (strings, numbers, or tuples are common choices), while values can be anything, including other dictionaries or lists. Since Python 3.7, dictionaries maintain insertion order. They are one of the most heavily used data structures in Python, ideal for representing structured records, lookups, and mappings.Sets
A set is an unordered collection of unique, hashable items, created with curly braces or the set() function. Sets automatically eliminate duplicates and support fast membership testing, along with mathematical set operations like union, intersection, and difference. They're especially useful for deduplicating data and for comparing two collections to find overlaps or differences.