1. What is Python, really?
Python is a high-level, interpreted programming language designed to be easy to
read and write. When you run a Python program, the interpreter (not a compiler)
reads your code line by line and executes it immediately. This makes Python
excellent for rapid prototyping, experimentation, and learning, though it can be
slower than compiled languages like C++ or Rust.
Python emphasizes clarity over cleverness. The syntax is clean and often resembles
pseudocode � code you might write on a whiteboard to explain logic. This is why
Python is a first choice for beginners, but it�s also powerful enough to be used by
Google, NASA, Netflix, and most machine learning research.
2. Variables and Data Types
Variables
In Python, you don�t declare types explicitly � you just assign values:
x = 42 # integer
name = "Alice" # string
pi = 3.14159 # floating-point
is_happy = True # boolean
Python is dynamically typed. The type of x can change later if you assign something
else:
x = "Hello!" # now it's a string
This is convenient but can cause bugs if you�re careless � many developers use type
hints (optional annotations) to add clarity:
def greet(name: str) -> str:
return f"Hello, {name}!"
Core Data Types
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int � integers (5, -42)
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float � real numbers (3.14, -0.001)
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str � text ("Python")
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bool � logical (True or False)
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list � ordered collection ([1, 2, 3])
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tuple � immutable ordered collection ((1, 2, 3))
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dict � key-value map ({"name": "Alice", "age": 30})
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set � unordered unique values ({1, 2, 3})
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3. Control Flow: Decisions and Loops
Python code is structured using indentation, not curly braces. Indentation is not
just style � it�s part of the language.
If statements
age = 20if age >= 18:
print("Adult")elif age >= 13:
print("Teenager")else:
print("Child")
Loops
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for loop (iterates over sequences):
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for i in range(5): # 0,1,2,3,4
print(i)
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while loop (runs until a condition is false):
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count = 0while count < 3:
print("Hello")
count += 1
4. Functions
Functions group code into reusable blocks:
def add(a, b):
return a + b
print(add(3, 5)) # outputs 8
Functions can have default arguments:
def greet(name="world"):
print(f"Hello, {name}!")
greet() # Hello, world!
greet("Bob") # Hello, Bob!
They can also return multiple values (technically a tuple):
def divide(a, b):
quotient = a // b
remainder = a % b
return quotient, remainder
q, r = divide(10, 3) # q=3, r=1
5. Collections in Depth
Lists
Lists are mutable, ordered sequences:
nums = [1, 2, 3]
nums.append(4)
nums[0] = 10print(nums) # [10, 2, 3, 4]
Tuples
Tuples are immutable, often used for fixed data structures:
point = (3, 4)
x, y = point # tuple unpacking
Dictionaries
Dictionaries store data as key-value pairs:
person = {"name": "Alice", "age": 30}print(person["name"])
person["age"] = 31
Sets
Sets store unique items only:
unique = {1, 2, 2, 3}print(unique) # {1, 2, 3}
6. Strings
Strings are sequences of characters. You can use single ' or double " quotes, and
triple quotes for multiline:
text = "Hello"print(text.upper()) # HELLOprint(text[1]) #
eprint(text[::-1]) # reverse
Formatted strings (f-strings) make interpolation easy:
name = "Bob"
age = 25print(f"{name} is {age} years old")
7. Modules and Imports
A module is just a Python file with functions, classes, or variables you can reuse.
Use import:
import mathprint(math.sqrt(16)) # 4.0
You can also import selectively:
from math import pi, sin
Or rename imports:
import numpy as np
8. Error Handling
Python uses exceptions to signal errors:
try:
result = 10 / 0except ZeroDivisionError:
print("Cannot divide by zero")finally:
print("This always runs")
This prevents your program from crashing abruptly.
9. Classes and Objects
Python supports object-oriented programming (OOP). A class is a blueprint for
creating objects (instances):
class Dog:
def __init__(self, name):
self.name = name
def bark(self):
print(f"{self.name} says woof!")
dog = Dog("Fido")
dog.bark()
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__init__ is the constructor.
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self refers to the current object.
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Attributes (self.name) hold data.
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Methods (bark) define behavior.
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10. Files and I/O
Reading and writing files is straightforward:
# Writewith open("hello.txt", "w") as f:
f.write("Hello, world!")
# Readwith open("hello.txt", "r") as f:
content = f.read()
print(content)
The with statement automatically closes the file, even if errors occur.
11. Pythonic Style
�Pythonic� means writing code that feels natural in Python:
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Use list comprehensions:
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squares = [x*x for x in range(5)]
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Use enumerate for loops:
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for i, val in enumerate(["a","b"]):
print(i, val)
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Avoid reinventing the wheel � Python�s standard library is rich and powerful.
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12. Virtual Environments and Packages
Python has thousands of external libraries. To avoid conflicts, developers use
virtual environments:
python -m venv venvsource venv/bin/activate # Linux/Mac
venv\Scripts\activate # Windows
pip install requests
This keeps project dependencies isolated.
13. Advanced Features You�ll See Around
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Generators (yield) for streaming data efficiently.
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Decorators (@something) to modify functions dynamically.
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Type hints with typing module to write self-documenting code.
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Asynchronous programming (async/await) for concurrent tasks.
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14. Why Python is So Popular
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Readability: Syntax is clear and friendly.
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Huge ecosystem: Libraries for data science, AI, web, automation.
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Community support: Tons of tutorials, Q&A, documentation.
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Versatility: Works for scripts, websites, games, machine learning, hardware control
� you name it.
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