Lesson 5 — Types

Data Types

Python's built-in types are rich and cover most needs. Understanding how they behave — especially mutability — prevents a whole class of subtle bugs.

Core Built-In Types

PYTHON — Core types 
# Numbers:
age     = 24          # int — arbitrary precision, no overflow
mark    = 74.5        # float — double precision floating point
complex_n = 3 + 4j   # complex — rarely used in general programming

# Text:
name   = "Thandi"    # str — immutable Unicode sequence
char   = "A"         # str of length 1 (no separate char type)

# Boolean:
active = True         # bool — subclass of int! True == 1, False == 0

# Nothing:
result = None         # NoneType — the only value of NoneType

# Check types:
print(type(age))      # <class 'int'>
print(type(mark))     # <class 'float'>
print(type(name))     # <class 'str'>
print(isinstance(age, int))   # True
print(isinstance(True, int))  # True — bool IS-A int in Python

Integer Precision

Python integers have arbitrary precision — they never overflow. You can compute 2 ** 1000 and get the exact answer. This is unlike Java's int which overflows at ~2.1 billion.

PYTHON — Arbitrary precision 
# No overflow:
print(2 ** 100)         # 1267650600228229401496703205376
print(factorial := 1)   # walrus operator := assigns and returns
for i in range(1, 21):
    factorial *= i
print(f"20! = {factorial}")  # exact

String Operations

PYTHON — String operations 
s = "Thandi Mokoena"

print(len(s))           # 15
print(s.upper())        # THANDI MOKOENA
print(s.lower())        # thandi mokoena
print(s.split(" "))     # ['Thandi', 'Mokoena']
print(s.replace("a","@")) # Th@ndi Moke@n@
print(s.startswith("T"))  # True
print(s.strip())          # removes leading/trailing whitespace
print("Mokoena" in s)     # True — membership test

# String slicing:
print(s[0])     # T
print(s[-1])    # a
print(s[0:6])   # Thandi
print(s[7:])    # Mokoena
print(s[::-1])  # anekoM idnahT — reversed

Type Conversion

PYTHON — Conversion 
# Explicit conversions:
age_str  = "22"
age_int  = int(age_str)         # "22" → 22

price_str = "250.50"
price     = float(price_str)    # "250.50" → 250.5

bool_val = bool(0)              # 0, "", [], None → False; everything else → True

marks = [65, 72, 80]
marks_str = str(marks)          # "[65, 72, 80]"

# Falsy values in Python (evaluate to False in boolean context):
# 0, 0.0, 0j, "", [], {}, set(), None, False
# Everything else is truthy

Practice Task

Your Turn

Create variables of each core type. Use isinstance() to verify each type. Convert a mark stored as a string to float. Write a function that accepts any value and returns a description of its type and whether it is truthy or falsy.

Common Mistakes

  • Adding int and str raises TypeError — convert explicitly: str(n) or int(s).
  • int('74.5') raises ValueError — use float() first then int() if you need truncation.
  • True and False are capitalised — true is a NameError.
  • None is not False — None == False is False. Test with is None.

Professional Tip

Python's falsy values are a useful feature — if user_input: is cleaner than if user_input != "" and user_input is not None:. Learn them by heart.

Mini Quiz

What is the result of bool(0) in Python?