Operators & Control Flow

Where this fits

This builds directly on Python Fundamentals. You already know values, variables, and data types. Now you learn to combine values with operators and to control the order in which code runs, which is what turns a list of statements into a real program.

By default a program runs top to bottom, one line after another. That alone cannot express most real logic, which needs to combine values, make decisions, and repeat work. This note covers the three tools that make that possible: operators that act on values, conditional statements that choose between paths, and loops that repeat a block of code.

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Operators

An operator is a symbol that performs an operation on one or more values. The values an operator works on are called its operands. In 2 + 3, the + is the operator and 2 and 3 are the operands. Python groups its operators into six families.

Arithmetic operators

These are the mathematical operators you already know, plus three that are worth calling out.

Operator	Name	a = 5, b = 2	Result
+	addition	a + b	7
-	subtraction	a - b	3
*	multiplication	a * b	10
/	division	a / b	2.5
//	integer (floor) division	a // b	2
%	modulus (remainder)	a % b	1
**	power	a ** b	25

Three of these are easy to miss:

• Integer division // divides and then throws away the decimal part, so 5 // 2 is 2, not 2.5.
• Modulus % gives the remainder of a division, so 5 % 2 is 1. When the left number is smaller than the right, the remainder is the left number itself, so 3 % 10 is 3.
• Power ** raises to an exponent, so 5 ** 2 is 25.

Example

Modulus and integer division together let you pull digits out of a number. Given a three-digit number, number % 10 gives the last digit, and number // 10 removes it. Repeat, and you extract every digit.

number = 345
a = number % 10        # 5   (last digit)
number = number // 10  # 34  (drop the last digit)
b = number % 10        # 4
number = number // 10  # 3
c = number % 10        # 3
print(a + b + c)       # 12

Relational operators

Relational operators, also called comparison operators, compare two values and always return a boolean (True or False).

Operator	Meaning
>	greater than
<	less than
>=	greater than or equal to
<=	less than or equal to
==	equal to
!=	not equal to

print(4 > 5)    # False
print(4 == 4)   # True

Warning

A single = assigns a value; a double == compares two values. x = 5 stores 5 in x, while x == 5 asks whether x equals 5. Mixing them up is one of the most common beginner mistakes.

Logical operators

Logical operators combine boolean values and are the backbone of decision logic. There are three: and, or, and not.

• and is True only when both sides are True.
• or is True when at least one side is True.
• not flips a value: not True is False.

print(True and False)   # False
print(True or False)    # True
print(not True)         # False

Note

Do not confuse the word operators and, or, not with the bitwise symbols &, |, ~ below. The word versions work on whole boolean values and are what you use for logic. The symbols work on the individual bits of numbers.

Bitwise operators

Bitwise operators work on the binary representation of integers, bit by bit. They convert each operand to binary, apply the operation to each pair of bits, and convert back.

Operator	Name
&	bitwise and
|	bitwise or
^	bitwise xor
~	bitwise not
<<	left shift
>>	right shift

print(2 & 3)   # 2

To see why 2 & 3 is 2, line up the bits and apply and to each column, where and gives 1 only when both bits are 1:

  1 0   (2)
  1 1   (3)
  -----
  1 0   = 2

Note

Bitwise operators are rarely needed in everyday programming or data science. You might meet & and | in image processing or computer vision, but you can safely treat the rest as background knowledge for now.

Assignment operators

The single = is the assignment operator: it stores the value on its right into the variable on its left. You can combine it with an arithmetic operator as a shorthand.

a = 5
a += 2    # same as: a = a + 2
print(a)  # 7

a += 2 means “take the current value of a, add 2, and store the result back in a.” The same works for -=, *=, /=, %=, and the others.

Note

Python has no ++ or -- operators. Where C uses a++, Python uses a += 1. This was a deliberate choice to avoid the confusion those operators can cause.

Membership operators

Membership operators check whether a value exists inside a sequence. There are two: in and not in. Both return a boolean.

print('D' in 'Delhi')       # True
print(1 in [2, 3, 4, 5])    # False

Tip

in is more than a convenience. Checking membership by hand would need a loop over every element. The in operator does it in one readable, optimized expression, and it works on strings, lists, tuples, sets, and dictionaries alike.

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Making decisions with if, elif, and else

Sometimes a program reaches a point where it must choose between paths based on a condition. This is called branching, and it is handled by if, elif, and else.

Consider a login page. When a user submits an email and password, there are two possibilities: the credentials are correct, or they are not. Each possibility needs different code, so the program branches.

email = input('Enter email: ')
password = input('Enter password: ')

if email == 'aarav@gmail.com' and password == '1234':
    print('Welcome')
else:
    print('Incorrect email or password')

Two things are worth noticing.

• The condition uses and, because both the email and the password must be correct. Using or would let anyone in with just a correct email.
• The code inside each branch is indented.

Indentation defines a block

Where C and Java use curly braces { } to group the code inside an if, Python uses indentation: the lines belonging to a branch are shifted to the right by one level. There are no braces and no semicolons.

if condition:
    # this indented line runs when the condition is true
    print('inside the if')
print('this always runs, it is outside the if')

Indentation is not optional styling in Python; it is the syntax. This is a deliberate design choice that forces every Python program to be cleanly formatted and readable. When you type the colon and press enter, the editor indents the next line for you.

More than two paths with elif

if and else handle two possibilities. For three or more, add one or more elif (short for “else if”) branches between them.

if email == 'aarav@gmail.com' and password == '1234':
    print('Welcome')
elif email == 'aarav@gmail.com' and password != '1234':
    print('Wrong password, try again')
else:
    print('Incorrect email')

Python checks each condition from top to bottom and runs the block of the first one that is true, then skips the rest. If none are true, the else block runs.

Tip

Chained if, elif, else statements are how you build a menu-driven program: ask the user to pick an option, store their choice, then branch to the matching action. An ATM screen or a command-line menu is built exactly this way.

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Modules

As a program grows, you will want to reuse code that someone has already written rather than write everything yourself. A module is a file of Python code, holding functions and values, that you can pull into your own program. Python ships with a large collection of them, its standard library, which is what “batteries included” means in practice.

You bring a module in with the import keyword. Once imported, you reach its contents through the module name and a dot.

import math

print(math.sqrt(25))      # 5.0
print(math.pi)            # 3.141592653589793

Here math is a module, sqrt is a function inside it, and pi is a value inside it. The dot says “look inside math for this name”.

You do not have to import the whole module. When you need one or two names, import them directly, and then you can use them without the module prefix.

from math import sqrt, pi

print(sqrt(25))           # 5.0, no math. prefix needed

Tip

A few standard modules come up constantly: math for mathematical functions, random for random numbers, and datetime for dates and times. Beyond the standard library, the data science tools you will meet later, such as NumPy and pandas, are modules too, imported the same way. Learning import now is what unlocks all of them.

Note

You can rename a module on import with as, which is why data science code almost always begins import numpy as np. The alias is shorter to type and is a shared convention, so np means NumPy to every reader.

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Loops

A loop repeats a block of code. Without loops you would have to copy the same lines over and over. Python has two loops: while and for.

The while loop

A while loop repeats its body as long as a condition stays true. You typically set up a counter, check it in the condition, and update it inside the loop.

number = int(input('Enter a number: '))
i = 1
while i < 11:
    print(number * i)
    i += 1

This prints the multiplication table of a number. Read it as a cycle:

1. Check the condition i < 11. If false, stop and leave the loop.
2. If true, run the body: print number * i.
3. Update the counter with i += 1.
4. Go back to step 1.

Warning

If you forget to update the counter (i += 1), the condition never becomes false and the loop runs forever. An infinite loop is the most common loop bug. Always make sure something inside the loop moves the condition toward becoming false.

Python also lets you attach an else to a loop. The else block runs once, after the loop finishes normally.

x = 1
while x < 3:
    print(x)
    x += 1
else:
    print('limit crossed')

The for loop and range

A for loop repeats once for each item in a sequence. It is simpler and more powerful than the C-style loop, because you do not manage a counter by hand. The most common way to drive a for loop is the built-in range function, which generates a sequence of numbers.

for i in range(1, 11):
    print(i)          # prints 1 to 10

range takes up to three arguments:

• range(1, 11) generates 1 to 10. The first number is included, the second is excluded.
• A third argument sets the step size: range(1, 10, 2) gives 1, 3, 5, 7, 9.
• A negative step counts down: range(10, 0, -1) gives 10, 9, ..., 1.

A for loop can also walk directly through the items of a string, list, tuple, set, or dictionary, without any range at all.

for char in 'DELHI':
    print(char)       # prints D, E, L, H, I

Note

The difference from other languages is that you never specify a start, end, and increment as three separate pieces. You hand the loop a sequence, and it walks through it. This is why Python loops are shorter and harder to get wrong.

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Controlling loops: break, continue, and pass

Three statements let you control a loop from the inside. They are called loop control statements.

break stops the loop immediately and moves on to the code after it.

for i in range(1, 10):
    if i == 5:
        break
    print(i)          # prints 1, 2, 3, 4

break is what you use in a search: the moment you find what you are looking for, there is no reason to keep looping, so you break out.

continue skips the rest of the current iteration and jumps straight to the next one.

for i in range(1, 10):
    if i == 5:
        continue
    print(i)          # prints 1 to 9, but not 5

pass does nothing. It is a placeholder for a spot where Python’s syntax requires a statement but you have no code to put there yet.

for i in range(1, 10):
    if i == 5:
        pass          # a reminder to add logic here later
    print(i)          # prints 1 to 9, including 5

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Nested loops

A nested loop is a loop inside another loop. The inner loop runs completely for every single pass of the outer loop. Use one whenever you need to pair every item from one set with every item from another.

for i in range(1, 5):
    for j in range(1, 5):
        print(i, j)

This prints every pair from (1, 1) up to (4, 4). Trace the order: the outer loop fixes i = 1, then the inner loop runs fully with j = 1, 2, 3, 4. Only then does the outer loop move to i = 2, and the inner loop runs fully again.

Example

To print every student in every class of a school, the outer loop walks through the classes and, for each class, the inner loop walks through that class’s students. Any time the task is “for each X, do something with every Y”, a nested loop fits.

Warning

Nested loops multiply their work. An outer loop of 1000 items with an inner loop of 1000 items runs the inner body a million times. This cost matters, and Time Complexity gives you the tools to reason about it.

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Summary

1. An operator acts on operands. Python has arithmetic (+ - * / // % **), relational (> < >= <= == !=), logical (and or not), bitwise (& | ^ ~ << >>), assignment (= and its shorthands like +=), and membership (in, not in) operators.
2. Integer division // drops the decimal part and modulus % gives the remainder; together they extract digits from numbers.
3. Use == to compare and = to assign; confusing them is a common bug.
4. if, elif, and else branch the program. Python runs the first true branch and uses indentation, not braces, to mark which lines belong to each branch.
5. A module is a file of reusable code; import brings it in, and you reach its contents with a dot, or import names directly with from. The standard library and tools like NumPy and pandas are all modules.
6. A while loop repeats while a condition holds; always update something so the condition can eventually become false.
7. A for loop walks through a sequence. range(start, stop, step) generates numbers, with stop excluded, and a for loop can also iterate directly over any collection.
8. break exits a loop early, continue skips to the next iteration, and pass is a do-nothing placeholder.
9. A nested loop runs the inner loop fully for each pass of the outer loop, which pairs every item with every other and multiplies the total work.

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Continues to

With decisions and repetition in hand, the next topic is Strings, where you apply loops, indexing, and membership to work with text.