Data Structures: Lists, Tuples, Dicts and Sets

Lists: ordered, changeable

tasks = ["write tests", "fix bug"]
tasks.append("deploy")
tasks.insert(0, "plan")
tasks.remove("fix bug")
last = tasks.pop()
tasks.sort()
tasks[0]       tasks[-1]       tasks[1:3]
len(tasks)

Tuples: ordered, fixed

point = (3, 4)
x, y = point                    # unpacking
def min_max(values):
    return min(values), max(values)   # returns a tuple
low, high = min_max([4, 1, 9])

Use tuples for records that should not change and as dictionary keys.

Dictionaries: key → value

user = {"name": "Ada", "role": "admin", "points": 120}
user["email"] = "ada@example.com"        # add / update
user.get("phone", "not set")             # safe lookup with default
del user["role"]
for key, value in user.items():
    print(key, value)
"name" in user                           # key check

Dicts keep insertion order and lookups are very fast, whatever their size.

Sets: unique, unordered

tags = {"python", "flask", "python"}     # {'python', 'flask'}
a = {"python", "sql"}; b = {"python", "docker"}
a & b    # intersection {'python'}
a | b    # union
a - b    # difference {'sql'}

Converting a list to a set is the fastest way to remove duplicates or test membership in large collections.

Choosing

Nested data (like JSON)

order = {
    "id": 1001,
    "customer": {"name": "Ada", "email": "ada@example.com"},
    "items": [
        {"sku": "HOOD-1", "qty": 2, "price": 39.0},
        {"sku": "MUG-3", "qty": 1, "price": 12.5},
    ],
}
total = sum(i["qty"] * i["price"] for i in order["items"])

The collections module

from collections import Counter, defaultdict
Counter("mississippi").most_common(2)     # [('i', 4), ('s', 4)]
by_role = defaultdict(list)
for u in users:
    by_role[u["role"]].append(u["name"])

A common trap: mutable copies

a = [1, 2, 3]
b = a          # same list!
b.append(4)    # a is now [1, 2, 3, 4]
c = a.copy()   # independent copy

Exercise

Given a list of order dicts, compute revenue per customer with a defaultdict(float), then print the top three customers.

Check yourself

• When would you choose a set over a list?
• Why does b = a not copy a list?
• What does dict.get(key, default) protect against?