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Python Lists — Tutorial with Examples

Master Python lists in 7 minutes. Indexing, slicing, the most-used methods, and a runnable browser editor so you can practice without installing anything.

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Runs in your browser via Pyodide — no signup, no install. Want auto-graded full exercises + videos? See the 7-Day Python Sprint.

A list in Python is an ordered, mutable collection. You create one with square brackets:

fruits = ["apple", "banana", "cherry"]
scores = [85, 92, 78, 95, 88]
mixed = ["alice", 30, True]   # legal but discouraged in real code

Lists are *the* workhorse data structure of Python — you'll see them everywhere.

Indexing

Python uses zero-based indexing. fruits[0] is "apple". Even more useful: negative indexing wraps from the end. fruits[-1] is "cherry", fruits[-2] is "banana". No need to write fruits[len(fruits) - 1] ever again.

Slicing

fruits[start:stop] gives you a sub-list. The stop index is exclusive.

nums = [10, 20, 30, 40, 50]
nums[1:3]     # [20, 30]
nums[:3]      # [10, 20, 30] — from start
nums[2:]      # [30, 40, 50] — to end
nums[::-1]    # [50, 40, 30, 20, 10] — reversed in one line

The most-used list methods

Method	What it does
`.append(x)`	Add `x` to the end
`.insert(i, x)`	Insert at position `i`
`.pop()`	Remove and return last item
`.pop(0)`	Remove and return first item (slow on large lists)
`.remove(value)`	Remove first matching value
`.sort()`	Sort in place
`.reverse()`	Reverse in place
`len(nums)`	How many items
`value in nums`	Membership check (returns True/False)

Lists vs tuples — when to use which

A tuple is the immutable cousin of a list (you'll meet them on Day 1 too). The rule: use a tuple when the size and meaning is fixed (a coordinate, an RGB color, a database row). Use a list when items will be added, removed, or reordered.

Common mistakes

List as default argument: never write def add(item, basket=[]). The list is created *once* and reused across every call to the function. Use basket=None and check inside.
.pop(0) on big lists: O(n). Use collections.deque if you need a fast queue.
Mistaking shallow copy for deep copy: b = a doesn't copy — b and a point to the same list. Use b = a.copy() (or list(a)) for a shallow copy.

Where this fits in the 7-Day Python Sprint

Lists are introduced on Day 1 and used throughout the sprint — from the contact-book lab on Day 1 to the email analyzer on Day 7.

Practice

Auto-graded — run in your browser, no signup.

Exercise 1: Add `'mango'` to the `fruits` list, then assign the second item to a variable `second`.