2. Variables, Types & Operators

Python uses Dynamic Typing, meaning you don't declare types explicitly. Variables are created when you assign values. Explore how Python handles data and performs operations below.

TRY IT Dynamic Typing Detective

Enter a value:

Try: 123, 12.5, "Python", [1,2]

Detected Type:

<class 'str'> (Default input is string)

Operator Lab

Inputs

Variable a

Variable b

Output Console

a + b = 13

a - b = 7

a * b = 30

a / b = 3.333

a // b = 3 (Floor)

a % b = 1 (Mod)

a ** b = 1000

a == b : False

a > b : True

3. Control Flow

Control structures guide the execution path of a program. Use the simulators below to visualize Decision Making (if..elif..else) and Iteration (Loops).

Vote Eligibility Checker (if-else)

Age:

if age >= 18:

print("Eligible")

else:

print("Not Eligible")

Not Eligible

For Loop Visualizer

for i in range(1, 6):
print(i)

1

2

3

4

5

Note: range(1, 6) excludes the upper limit 6.

4. Data Structures

Organizing data is crucial. Here we explore Strings (Immutable), Lists (Mutable), and Dictionaries. Interact with the tools below to understand slicing and methods.

String Slicing Laboratory

Target String S = "PYTHON"

Start

Stop

Step

S[0 : 6 : 1] = "PYTHON"

List Operations (Mutable)

Current List: [10, 20, 30]

*Lists change in-place

Dictionary (Key-Value)

Grade Book

{'Math': 90, 'Eng': 85}

5. Functions & Modules

Functions promote reusability. Modules like `random` extend capabilities. Below, visualize how `random.randint()` behaves over many trials.

Random Distribution Visualizer

Click "Generate" to simulate rolling a 6-sided die 100 times using random.randint(1, 6). The chart shows the frequency of each number.

import random
counts = [0] * 7
for _ in range(100):
roll = random.randint(1, 6)
counts[roll] += 1

PyLab | Class 12 Python Review

1. The Python Environment

Working Modes

Python Tokens