dict: Key and Value

What will we learn?#

A dict (Dictionary) is a structure that holds pairs of a key and a value. Instead of accessing by position ([0]), you access by name (["name"]).

Why do we need this?#

In the tuple ("Dana", 24, "Haifa") you have to remember that position 1 is the age. With 15 fields, that is a recipe for bugs. A dict solves this:

student = {"name": "Dana", "age": 24, "city": "Haifa"}
student["age"]   # clear and readable

dict is perhaps the most important structure for the coming weeks:

• JSON (tomorrow): the format in which files are saved and information is sent over the network. In Python it becomes a dict.
• The backend and databases topics: every request and response in an API is essentially a dict. {"id": 7, "name": "Dana"}.
• Every “record”, like a user, a product or an order, is convenient to represent as a dict.

Explanation from the basics#

What is a dict?#

• Every item is a pair: a Key → a Value.
• Unique keys — there are no two identical keys. Assigning to an existing key replaces the value.
• Mutable.
• Keeps the insertion order (since Python 3.7).
• A key is usually a str or an int. A value can be anything: a number, text, a list, and even another dict.

Syntax#

# create
empty = {}
student = {"name": "Dana", "age": 24}

# read
student["name"]                 # "Dana" - KeyError if the key does not exist
student.get("email")            # None - no error if missing
student.get("email", "N/A")     # "N/A" - default value if missing

# add / update (same syntax!)
student["email"] = "dana@mail.com"   # new key -> added
student["age"] = 25                  # existing key -> updated

# delete
del student["email"]            # delete a key (KeyError if missing)
age = student.pop("age")        # delete and return the value

# check
"name" in student               # True - checks KEYS, not values
len(student)                    # number of key-value pairs

# iterate
for key in student:             # keys
for value in student.values():  # values
for key, value in student.items():   # pairs (tuples!)

First code example#

week-2/student_dict.py:

student = {"name": "Dana", "age": 24, "city": "Haifa"}

print("Name:", student["name"])
print("Age:", student["age"])

student["age"] = 25
student["email"] = "dana@mail.com"
print("Updated:", student)

del student["city"]
print("After delete:", student)

print("Has email?", "email" in student)
print("Phone:", student.get("phone", "not provided"))

Output:

Name: Dana
Age: 24
Updated: {'name': 'Dana', 'age': 25, 'city': 'Haifa', 'email': 'dana@mail.com'}
After delete: {'name': 'Dana', 'age': 25, 'email': 'dana@mail.com'}
Has email? True
Phone: not provided

Breaking down the code line by line#

Another example#

A list of dictionaries — the most common structure for “real” data (a table: every dict is a row). And also counting with a dict. week-2/products.py:

products = [
    {"id": 1, "name": "Laptop", "price": 3500, "category": "electronics"},
    {"id": 2, "name": "Mouse", "price": 80, "category": "electronics"},
    {"id": 3, "name": "Desk", "price": 900, "category": "furniture"},
    {"id": 4, "name": "Chair", "price": 450, "category": "furniture"},
]

print("--- Catalog ---")
for product in products:
    print(product["id"], product["name"], product["price"], "NIS")

expensive = []
for product in products:
    if product["price"] > 500:
        expensive.append(product["name"])
print("Over 500 NIS:", expensive)

count_by_category = {}
for product in products:
    category = product["category"]
    count_by_category[category] = count_by_category.get(category, 0) + 1
print("Count by category:", count_by_category)

for category, count in count_by_category.items():
    print(category, "->", count, "products")

Output:

--- Catalog ---
1 Laptop 3500 NIS
2 Mouse 80 NIS
3 Desk 900 NIS
4 Chair 450 NIS
Over 500 NIS: ['Laptop', 'Desk']
Count by category: {'electronics': 2, 'furniture': 2}
electronics -> 2 products
furniture -> 2 products

Breakdown:

• products is a list where every item is a dict. product["price"] = the price of the current product in the loop.
• The counting pattern: count_by_category.get(category, 0) + 1. If the category is not in the dictionary yet, get returns 0, and then 0+1 = 1. If it is already there, you get the existing count and add 1. This is a pattern that comes up again and again.
• .items() — returns (key, value) pairs as tuples, and for category, count in unpacks them (Unpacking from the previous lesson).

A dict inside a dict#

A value can be a dict itself:

user = {
    "name": "Dana",
    "address": {"city": "Haifa", "street": "Herzl 10"},
    "hobbies": ["chess", "running"],
}
print(user["address"]["city"])   # Haifa
print(user["hobbies"][0])        # chess

You access it “layer by layer”: user["address"] returns a dict, and on it ["city"]. That is exactly the structure of JSON.

Common mistake#

Mistake 1: a KeyError on a key that does not exist.

student = {"name": "Dana"}
print(student["age"])

KeyError: 'age'

The fix: student.get("age") (returns None), student.get("age", 0) (a default), or check first with if "age" in student:.

Mistake 2: searching for a value with in.

student = {"name": "Dana"}
print("Dana" in student)

False

in on a dict checks keys. To check values: "Dana" in student.values().

Mistake 3: a typo in a key, which creates a new key instead of updating.

student = {"name": "Dana", "age": 24}
student["Age"] = 25
print(student)

{'name': 'Dana', 'age': 24, 'Age': 25}

No error! A new key "Age" was simply added, and "age" stayed 24. Keys are case-sensitive. It is a silent Logical Error, so keep the key names consistent (snake_case).

Mistake 4: a list as a key.

locations = {[32, 35]: "Haifa"}

TypeError: unhashable type: 'list'

A key must be Immutable. If you need a key made of several values, use a tuple: {(32, 35): "Haifa"}. (We will explain the connection to Immutable in the next lesson.)

Practice#

The exercises use only what was taught in this lesson and the lessons before it. Try on your own first, and only then open the solution.

Exercise 1: A student card#

Create a dictionary student with the name "Dana", the age 24 and the city "Haifa". Then:

1. Update the age to 25.
2. Add an email "dana@mail.com".
3. Delete the city.
4. Print the dictionary, and the phone using get with the default "none".

Expected output:

{'name': 'Dana', 'age': 25, 'email': 'dana@mail.com'}
none

student = {"name": "Dana", "age": 24, "city": "Haifa"}

student["age"] = 25
student["email"] = "dana@mail.com"
del student["city"]

print(student)
print(student.get("phone", "none"))

{'name': 'Dana', 'age': 25, 'email': 'dana@mail.com'}
none

Exercise 2: Counting words#

Write a function count_words(text) that returns a dictionary: every word (in lowercase) → how many times it appears.

counts = count_words("the cat and the dog and THE bird")
print(counts)

Expected output:

{'the': 3, 'cat': 1, 'and': 2, 'dog': 1, 'bird': 1}

def count_words(text):
    counts = {}
    for word in text.lower().split():
        counts[word] = counts.get(word, 0) + 1
    return counts


counts = count_words("the cat and the dog and THE bird")
print(counts)

{'the': 3, 'cat': 1, 'and': 2, 'dog': 1, 'bird': 1}

Exercise 3: A list of dictionaries#

products = [
    {"name": "Laptop", "price": 3500, "category": "electronics"},
    {"name": "Mouse", "price": 80, "category": "electronics"},
    {"name": "Desk", "price": 900, "category": "furniture"},
]

1. Print the names of the products whose price is below 1000.
2. Build a dictionary that counts how many products there are in each category, and print it.

Expected output:

Mouse
Desk
{'electronics': 2, 'furniture': 1}

products = [
    {"name": "Laptop", "price": 3500, "category": "electronics"},
    {"name": "Mouse", "price": 80, "category": "electronics"},
    {"name": "Desk", "price": 900, "category": "furniture"},
]

for product in products:
    if product["price"] < 1000:
        print(product["name"])

counts = {}
for product in products:
    category = product["category"]
    counts[category] = counts.get(category, 0) + 1
print(counts)

Mouse
Desk
{'electronics': 2, 'furniture': 1}

Exercise 4: Looping over a dictionary#

stock = {"apple": 12, "banana": 0, "cherry": 5}

Loop over the dictionary with items() and print every item and its quantity. For an item whose quantity is 0, print out of stock.

Expected output:

apple -> 12
banana -> out of stock
cherry -> 5

stock = {"apple": 12, "banana": 0, "cherry": 5}

for name, quantity in stock.items():
    if quantity == 0:
        print(name, "->", "out of stock")
    else:
        print(name, "->", quantity)

apple -> 12
banana -> out of stock
cherry -> 5

Exercise 5: A nested dictionary#

user = {
    "name": "Dana",
    "address": {"city": "Haifa", "street": "Herzl"},
    "hobbies": ["chess", "running"],
}

Print the city, the first hobby, and add a hobby "music". At the end, print the list of hobbies.

Expected output:

Haifa
chess
['chess', 'running', 'music']

user = {
    "name": "Dana",
    "address": {"city": "Haifa", "street": "Herzl"},
    "hobbies": ["chess", "running"],
}

print(user["address"]["city"])
print(user["hobbies"][0])
user["hobbies"].append("music")
print(user["hobbies"])

Haifa
chess
['chess', 'running', 'music']

Summary#

• dict {key: value} — access by key and not by position. Keys are unique.
• d[key] = value — adds if new, updates if it exists.
• d[key] throws a KeyError on a missing key. d.get(key, default) does not throw.
• in checks keys. Looping: keys(), values(), items() (pairs).
• A list of dictionaries = a table. A dict inside a dict = JSON.
• The counting pattern: counts[x] = counts.get(x, 0) + 1.

Official documentation#

• Python Tutorial — Dictionaries
• Built-in Types — Mapping Types (dict)