Dictionaries in Python

A dictionary stores pairs: a key, and the value that key points at.

student = {
    "name": "Simran",
    "course": "Python",
    "months": 4,
}

student["name"]        # 'Simran'
student["months"] = 5  # change it
student["city"] = "Amritsar"   # add a new pair

Keys are usually strings, but any immutable value works — numbers and tuples are fine, lists are not.

Looking things up without crashing

student["phone"]              # KeyError — the key is not there
student.get("phone")          # None, no crash
student.get("phone", "n/a")   # 'n/a'

Use .get() whenever the key might be missing — reading an API response, a config file, or anything a user typed. Use square brackets when a missing key means something is genuinely broken and you want to hear about it immediately.

To check first:

if "phone" in student:
    print(student["phone"])

Looping

for key in student:
    print(key)                    # keys only

for key, value in student.items():
    print(key, "=", value)        # both

.items() is what you want nine times out of ten. There is also .keys() and .values().

Why this beats parallel lists

Students often start with two lists that have to stay lined up:

names = ["Simran", "Ravi"]
marks = [88, 72]

Now every sort, insert and delete has to happen twice, in step, or the data silently goes wrong. A dictionary keeps the pairing:

marks = {"Simran": 88, "Ravi": 72}
marks["Ravi"]        # 72

Nesting

Real data is usually a list of dictionaries:

batch = [
    {"name": "Simran", "marks": 88},
    {"name": "Ravi", "marks": 72},
]

for s in batch:
    print(s["name"], s["marks"])

top = max(batch, key=lambda s: s["marks"])

That shape — a list of dictionaries — is what you get back from almost every JSON API, so it is worth being comfortable with it before you touch one.