Variables & Types

A variable in Python isn’t really a “box” that holds a value — it’s a name that points to an object somewhere in memory. This is more than a trivia; it explains some Python behaviors that surprise people coming from other languages.

A name → an object

▶ Python

Ready

x = [1, 2, 3]
y = x            # y points to the SAME list as x
y.append(4)

print("x =", x)  # [1, 2, 3, 4]
print("y =", y)  # [1, 2, 3, 4]
print("same object?", x is y)

Output

(click Run)

x is y is True because both names point to the same object. The = did not copy the list; it just bound another name to it. To get an independent copy, you’d write y = x.copy() or y = list(x).

The core built-in types

These six show up everywhere:

Type	Example	Mutable?
`int`	`42`, `-1000`	—
`float`	`3.14`, `1e-9`	—
`str`	`"hello"`	no
`bool`	`True`, `False`	—
`list`	`[1, 2, 3]`	yes
`dict`	`{"a": 1}`	yes

You’ll also meet tuple ((1, 2), immutable list), set ({1, 2}, unordered, unique elements), and None (the absence-of-value singleton).

▶ Python

Ready

# Built-in types and what they hold.
n = 42
pi = 3.14159
greeting = "hello"
ok = True
items = [10, 20, 30]
user = {"name": "Aarav", "age": 28}

for value in (n, pi, greeting, ok, items, user):
  print(f"{type(value).__name__:<6}  {value!r}")

Output

(click Run)

type(x).__name__ gives the type name as a string. !r in the f-string calls repr(), which gives an unambiguous representation — useful when inspecting values.

Dynamic typing, but typed values

Python doesn’t require you to declare types — a variable can point at any type at any time. But every value has a type, and operations only work on compatible types.

▶ Python

Ready

x = 10
print(type(x))

x = "now I'm a string"
print(type(x))

# Type errors only show up at runtime:
try:
  result = "5" + 5
except TypeError as e:
  print("TypeError:", e)

Output

(click Run)

In production code you’ll add type hints to make the intent explicit and let mypy or pyright catch type errors before runtime. We cover that in a later lesson.

Casting between types

▶ Python

Ready

# Explicit conversion. Always do this when input comes from outside Python.
age = int("28")           # str → int
price = float("9.99")     # str → float
flag = bool("")           # "" → False, any non-empty string → True
text = str(42)            # int → str

print(age, price, flag, text)

# These each raise ValueError if the string can't be parsed:
try:
  int("twenty-eight")
except ValueError as e:
  print("ValueError:", e)

Output

(click Run)

isinstance vs type ==

Prefer isinstance(x, T) over type(x) == T — it respects inheritance, which matters once you start using classes.

isinstance(True, int)   # True — bool is a subclass of int
type(True) == int       # False

Quick check

✦ Quick check

0/3 answered

Q1.After `x = [1, 2]; y = x; y.append(3)`, what is `x`?

Q2.Which expression is the idiomatic 'is this empty string or None?' check?

Q3.What does `bool('False')` return?

What you'll learn

A name → an object

The core built-in types

Dynamic typing, but typed values

Casting between types

isinstance vs type ==

Quick check

✦ Quick check

Finished the lesson?