Dictionaries

Before we can model a country, a class, or any structured data in Python, we must deeply understand dictionaries — the container every later session builds on.

1. Learning Objective

2. Pre-Coding Quiz

Answer these before reading the concept explanation or writing any code. It is fine to get these wrong — that is the point. You need 4/5 to proceed to the lab.

3. The Concept — Python Dictionaries

What is a dictionary?

A dictionary groups related data together under one name, using key-value pairs. Instead of three separate variables for a country's data, you have one container that holds all of them.

# Without a dictionary — three unrelated variables
country_name = "Kenya"
country_region = "Africa"
country_population = 54000000

# With a dictionary — one container, logically grouped
country = {
    "name": "Kenya",
    "region": "Africa",
    "population": 54000000,
}

Reading values — bracket access vs .get()

There are two ways to read a value from a dictionary, and they behave differently on a missing key.

country = {"name": "Kenya", "region": "Africa"}

print(country["name"])          # "Kenya"
print(country["region"])        # "Africa"

# Missing key with bracket access -> KeyError, program crashes
# print(country["capital"])

# Missing key with .get() -> None, no crash
print(country.get("capital"))            # None
print(country.get("capital", "Unknown")) # "Unknown" — explicit default

Dictionaries are mutable — this is critical

In Python there are mutable types (dict, list, set) and immutable types (str, int, float, bool, tuple). Immutable values are copied when assigned. Mutable objects are not copied — only the reference is copied.

# Immutable — a new value is bound, the old one is untouched
x = 5
y = x
y = 99
print(x)  # still 5

# Mutable — reference is shared, NOT copied
a = {"score": 5}
b = a          # b now refers to the SAME dict as a
b["score"] = 99
print(a["score"])  # 99 — because a and b are the same object

Adding, updating, and deleting keys

Dictionaries grow and shrink after creation. Adding an unused key creates it; assigning an existing key overwrites it.

country = {"name": "Kenya"}

# Add a new key
country["capital"] = "Nairobi"
print(country)  # {'name': 'Kenya', 'capital': 'Nairobi'}

# Update an existing key
country["name"] = "Kenya (updated)"

# Delete a key
del country["capital"]
print(country)  # {'name': 'Kenya (updated)'}

Nested dictionaries

Values can themselves be dictionaries — this is how you model structured, hierarchical data.

country = {
    "name": "Kenya",
    "location": {
        "continent": "Africa",
        "coordinates": {"lat": -0.0236, "lng": 37.9062},
    },
}

print(country["location"]["continent"])            # "Africa"
print(country["location"]["coordinates"]["lat"])    # -0.0236

We are not writing classes yet, but when we do in Session 12, you will recognise this pattern immediately: an object's internal attributes are stored and looked up the same way you just looked up dictionary keys.

4. Lab

What you will build

A file called country.py that demonstrates every dictionary concept from this session. Nothing more.

Step-by-step instructions

# country.py

country = {
    "name": "Kenya",
    "capital": "Nairobi",
    "region": "Africa",
    "population": 54000000,
    "independent": True,
}

print("Name (bracket):", country["name"])
print("Capital (bracket):", country["capital"])
print("Region (bracket):", country["region"])

print("Flag (.get, missing):", country.get("flag"))
print("Flag with default:", country.get("flag", "🏳"))

original = {"name": "Kenya", "score": 0}
copy = original       # This is NOT a copy
copy["score"] = 99

print("original[score]:", original["score"])  # What do you expect?
print("copy[score]:", copy["score"])

country["flag"] = "🇰🇪"
print("After add:", country["flag"])
del country["independent"]
print("After delete:", country)

country["location"] = {
    "continent": "Africa",
    "coordinates": {"lat": -0.0236, "lng": 37.9062},
}
print("Continent:", country["location"]["continent"])
print("Latitude:", country["location"]["coordinates"]["lat"])

5. Expected Files Changed

6. Commit Checkpoint

Once the lab is complete and you can explain every line, make this exact commit:

git add country.py docs/sessions/session-05/index.html
git commit -m "session-05: define country as a dict, explore lookup and reference behaviour"

7. Code Review Checklist

Go through your code line by line and check each item:

8. Post-Coding Quiz

Same 5 questions. Take it again now that you have written and run the code. You need 4/5 to mark this session complete.

9. Reflection Questions

Think through these after the post-quiz. No right answer — they are for discussion.

10. What Breaks If This Knowledge Is Missing?

11. What We Learned