Introduction
Python is one of the most popular and versatile programming languages in the world. Whether you’re an aspiring software developer, data scientist, or automation expert, learning Python is a great place to start. This tutorial will guide you through the fundamentals of Python, complete with examples, exercises, and best practices.
1. What is Python?
Python is a high-level, interpreted programming language known for its simplicity and readability. Created by Guido van Rossum and first released in 1991, Python emphasizes code readability and uses significant indentation. It supports multiple programming paradigms including procedural, object-oriented, and functional programming.
Why Python?
- Easy to learn and use: Python’s syntax is clean and beginner-friendly.
- Extensive standard libraries: Offers ready-to-use modules for everything from regular expressions to web services.
- Active community: Tons of support, tutorials, and open-source contributions
- Cross-platform compatibility: Works on Windows, macOS, Linux.
- Widely used: In web development, data analysis, machine learning, automation, and more.
2. Installing Python
- Visit https://www.python.org/downloads/
- Download the latest version suitable for your OS.
- During installation on Windows, ensure you check the “Add Python to PATH” option.
- On Linux/macOS, you can also use a package manager like brew or apt.
Verify Installation
Use the terminal or command prompt to check if Python is installed:
python –version
Install pip (if not included):
python -m ensurepip –upgrade
Check pip:
pip –version
pip is Python’s package manager used to install external libraries.
3. Writing Your First Python Program Python scripts use .py extensions.
Example:
print(“Hello, World!”)
Save it as hello.py and run:
python hello.py
Interactive Mode: Python also supports interactive mode which is great for testing quick snippets:
python
Then try:
print(“Welcome to Python”)
- Python Basics A strong foundation in the basics is critical. Here are the core elements:
Comments
Comments are lines that the interpreter ignores. Use them to explain code:
Variables and Data Types
Python does not require explicit declaration of variables. It automatically infers the type.
name = “Alice” # String
age = 25 # Integer
height = 5.6 # Float
is_student = True # Boolean
Type Checking
To confirm a variable’s type:
print(type(name)) # Output:
Type Conversion
You can convert between data types using built-in functions:
int(“10”) # Converts string to integer
str(10) # Converts integer to string
float(“5.6”) # Converts string to float
Operators
- Arithmetic: +, -, *, /, //, %, **
- Comparison: ==, !=, <, >, <=, >=
- Logical: and, or, not
Control Flow
Used to control program execution:
if age >= 18:
print(“Adult”)
elif age == 17:
print(“Almost there”)
else:
print(“Minor”)
Loops
For Loop iterates over a sequence:
for i in range(5):
print(i)
While Loop continues as long as condition is true:
while age > 0:
print(age)
age -= 1
Break and Continue
- break exits the loop early.
- continue skips the current iteration.
for i in range(10):
if i == 5:
break
print(i)
5. Functions: Functions are reusable blocks of code.
Basic Function
def greet(name):
return f”Hello, {name}!”
print(greet(“Alice”))
Default Parameters
def greet(name=”Guest”):
return f”Welcome, {name}!”
Keyword Arguments
def student_info(name, age):
print(f”{name} is {age} years old”)
student_info(age=20, name=”Sam”)
Lambda Functions : Useful for short, anonymous functions
multiply = lambda x, y: x * y
print(multiply(2, 3))
6. Data Structures : Efficient storage and manipulation of data.
Lists : Ordered and mutable:
fruits = [“apple”, “banana”]
fruits.append(“cherry”)
print(fruits[1]) # Output: banana
Tuples : Ordered but immutable:
person = (“Alice”, 25)
print(person[0])
Dictionaries : Key-value storage
student = {“name”: “John”, “age”: 22}
print(student[“name”])
Sets : Unordered and unique elements.
unique = {1, 2, 3, 1}
print(unique) # Output: {1, 2, 3}
7. File Handling : Used for reading/writing files on disk.
Reading Files
with open(“file.txt”, “r”) as f:
content = f.read()
print(content)
Writing to Files
with open(“file.txt”, “w”) as f:
f.write(“Hello”)
Appending to Files
with open(“file.txt”, “a”) as f:
f.write(“\nWorld”)
8. Error Handling: Allows graceful handling of exceptions.
try:
number = int(input(“Enter a number: “))
print(10 / number)
except ValueError:
print(“Enter a valid number”)
except ZeroDivisionError:
print(“Can’t divide by zero”)
finally:
print(“Done”)
9. Modules and Packages: Promotes code reusability.
Built-in Modules
import math
print(math.pi)
Custom Modules
Create mymodule.py:
def add(a, b):
return a + b
Then use it:
from mymodule import add
print(add(5, 3))
External Packages
Install with pip:
pip install requests
Use in code:
import requests
print(requests.get(“https://example.com”)
.status_code)
10. Advanced Python Concepts
Object-Oriented Programming (OOP) : Organize code using classes and objects.
class Person:
def init(self, name):
self.name = name
def greet(self):
print(f"Hi, I'm {self.name}")Inheritance : Reuse behavior from parent classes.
class Student(Person):
def init(self, name, subject):
super().init(name)
self.subject = subject
Decorators : Wrap a function with additional functionality.
def my_decorator(func):
def wrapper():
print(“Before function”)
func()
print(“After function”)
return wrapper
@my_decorator
def say_hello():
print(“Hello!”)
say_hello()
Generators : Efficiently return values one at a time.
def countdown(n):
while n > 0:
yield n
n -= 1
for number in countdown(5):
print(number)
List Comprehensions : Short way to create lists.
squares = [x**2 for x in range(10)]
print(squares)
*Async Programming :* Handle asynchronous tasks.
import asyncio
async def main():
print(“Start”)
await asyncio.sleep(1)
print(“End”)
asyncio.run(main())
