Nested Data & in

Nested data — a list of dicts

This is one of the most common shapes you'll deal with in backend code: a list of dictionaries, e.g. a list of users from a database.

JavaScript:

const users = [
  { id: 1, name: 'John' },
  { id: 2, name: 'David' },
];

for (const user of users) {
  console.log(user.name);
}

Python:

users = [
    {
        "id": 1,
        "name": "John"
    },
    {
        "id": 2,
        "name": "David"
    }
]

for user in users:
    print(user["name"])

Each loop iteration gives you one dict, and you read from it with brackets — exactly like a standalone dict.

in — membership check

in checks whether something exists inside a collection. It works on lists, dicts, sets, and strings.

Checking a list — checks if a value is present:

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

"banana" in fruits   # True
"mango" in fruits    # False

Checking a dict — checks if a key is present (not a value):

user = {"id": 1, "name": "John"}

"name" in user   # True
"John" in user   # False — "John" is a value, not a key

Checking a string — checks for a substring:

"John" in "John Doe"   # True

A gotcha coming from JS

JS also has an in operator, but for arrays it checks the index, not the value — which is a common source of confusion:

const fruits = ['apple', 'banana', 'cherry'];

0 in fruits; // true  — index 0 exists
'banana' in fruits; // false — this is NOT how you check for a value in JS
fruits.includes('banana'); // true — this is what you actually want in JS

Python's in on a list always checks values, which matches JS's arr.includes(x) — not JS's own in operator. Keep that distinction in mind when moving between the two languages.