Lists and Dictionaries

In This Chapter

• How to store and manipulate ordered data with lists
• How to use list comprehensions for clean, concise transformations
• How to work with key-value pairs using dictionaries
• The difference between [] and .get() — and why it matters in production
• Time complexity of common list and dict operations (asked in interviews)

Lists

A list is an ordered, mutable collection of items. Items can be of any type.

fruits = ["apple", "banana", "cherry"]
nums = [1, 2, 3, 4, 5]
mixed = [1, "hello", True, 3.14]

Accessing Items

Use zero-based indexing. Negative indexes count from the end:

fruits = ["apple", "banana", "cherry"]

fruits[0]   # "apple"
fruits[-1]  # "cherry"
fruits[1:3] # ["banana", "cherry"]  — slicing

Common List Methods

fruits = ["apple", "banana"]

fruits.append("cherry")       # add to end
fruits.insert(1, "mango")     # insert at index
fruits.remove("banana")       # remove by value
fruits.pop()                  # remove and return last item
fruits.pop(0)                 # remove and return at index
fruits.sort()                 # sort in place
fruits.reverse()              # reverse in place
len(fruits)                   # length
"apple" in fruits             # True/False membership check

List Comprehensions

A concise way to create a new list from an existing one:

# basic
squares = [x ** 2 for x in range(5)]
# [0, 1, 4, 9, 16]

# with condition
evens = [x for x in range(10) if x % 2 == 0]
# [0, 2, 4, 6, 8]

# transform strings
words = ["hello", "world"]
upper = [w.upper() for w in words]
# ["HELLO", "WORLD"]

For simple transformations, list comprehensions are often cleaner and often faster than a for loop with .append(). Once the logic gets complex, a regular loop is easier to read.

Dictionaries

A dictionary stores key-value pairs. Keys must be unique and hashable.

person = {
    "name": "Alan",
    "age": 25,
    "city": "San Francisco"
}

Accessing and Modifying

person["name"]              # "Alan"
person.get("age")           # 25
person.get("email", "N/A")  # "N/A" — default if key missing

person["age"] = 26          # update
person["email"] = "a@b.com" # add new key
del person["city"]          # delete key

Use .get() when a missing key is expected and you want a fallback. Use [] when a missing key should be treated as a real bug.

Common Dict Methods

person.keys()    # dict_keys(["name", "age"])
person.values()  # dict_values(["Alan", 26])
person.items()   # dict_items([("name", "Alan"), ("age", 26)])

"name" in person  # True — check if key exists
person.pop("age") # remove and return value

Iterating

for key, value in person.items():
    print(f"{key}: {value}")

Dict Comprehensions

squares = {x: x ** 2 for x in range(5)}
# {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

Key Questions

Q: What is the difference between a list and a tuple?

Both are ordered sequences, but lists are mutable (you can add, remove, or change items) while tuples are immutable (fixed after creation). Use tuples for data that should not change, like coordinates or function return values. Tuples can be used as dictionary keys only when all of their contents are hashable.

Q: What is the time complexity of common list operations?

Appending to the end is O(1). Inserting or removing at an arbitrary index is O(n) because all subsequent items must shift. Checking membership with in is O(n). For fast membership checks, use a set or dict instead — both offer O(1) lookup.

Q: What is the difference between remove() and pop()?

remove(value) searches for the first occurrence of a value and removes it — raises ValueError if not found. pop(index) removes and returns the item at a given index (defaults to the last item). Use remove when you know the value, pop when you know the position or need the removed item.

Q: What is the difference between dict[key] and dict.get(key)?

dict[key] raises a KeyError if the key does not exist. dict.get(key) returns None by default, or a custom fallback. Use .get() when missing keys are part of normal control flow; use [] when absence should fail loudly.

Q: How do you merge two dictionaries?

In Python 3.9+, use the | operator: merged = dict1 | dict2. In earlier versions, use { **dict1, ** dict2}. If both dicts share a key, the right-hand side wins.

Q: What is a list comprehension and when should you use it?

A list comprehension is a concise, readable way to create a list by transforming or filtering another iterable — [expr for item in iterable if condition]. Use it for simple transformations. If the logic requires multiple lines or nested conditions, a regular for loop is more readable.

Q: How is a dictionary ordered in Python?

As of Python 3.7, dictionaries maintain insertion order — the order you add keys is the order you get them back when iterating. Before 3.7, order was not guaranteed. In practice, you can rely on this behavior in any modern Python code.