Learn Python Programming
Start with getting started, installation, and core basics. Clear explanations and practical examples to help you learn faster.
Python Operator Overloading
Operator overloading lets you define how operators like +, -, ==, and < behave with your custom classes by implementing special dunder methods.
Arithmetic Operators
class Vector:
def __init__(self, x, y):
self.x = x
self.y = y
def __add__(self, other):
"""v1 + v2"""
return Vector(self.x + other.x, self.y + other.y)
def __sub__(self, other):
"""v1 - v2"""
return Vector(self.x - other.x, self.y - other.y)
def __mul__(self, scalar):
"""v * number (scalar multiplication)"""
return Vector(self.x * scalar, self.y * scalar)
def __rmul__(self, scalar):
"""number * v (reverse multiplication)"""
return self.__mul__(scalar)
def __neg__(self):
"""-v (unary negation)"""
return Vector(-self.x, -self.y)
def __abs__(self):
"""abs(v) — magnitude"""
return (self.x**2 + self.y**2) ** 0.5
def __repr__(self):
return f"Vector({self.x}, {self.y})"
v1 = Vector(3, 4)
v2 = Vector(1, 2)
print(v1 + v2) # Vector(4, 6)
print(v1 - v2) # Vector(2, 2)
print(v1 * 3) # Vector(9, 12)
print(2 * v1) # Vector(6, 8) — uses __rmul__
print(-v1) # Vector(-3, -4)
print(abs(v1)) # 5.0
Comparison Operators
from functools import total_ordering
@total_ordering # auto-generates <=, >, >= from __eq__ and __lt__
class Temperature:
def __init__(self, celsius):
self.celsius = celsius
def __eq__(self, other):
"""=="""
return self.celsius == other.celsius
def __lt__(self, other):
"""<"""
return self.celsius < other.celsius
def __repr__(self):
return f"{self.celsius}°C"
t1 = Temperature(20)
t2 = Temperature(30)
t3 = Temperature(20)
print(t1 == t3) # True
print(t1 < t2) # True
print(t2 >= t1) # True (auto-generated by @total_ordering)
# Now sorting works!
temps = [Temperature(30), Temperature(10), Temperature(25)]
print(sorted(temps)) # [10°C, 25°C, 30°C]
Container Operators
class Playlist:
def __init__(self, name):
self.name = name
self._songs = []
def __len__(self):
"""len(playlist)"""
return len(self._songs)
def __getitem__(self, index):
"""playlist[i] and slicing"""
return self._songs[index]
def __setitem__(self, index, value):
"""playlist[i] = song"""
self._songs[index] = value
def __contains__(self, song):
"""song in playlist"""
return song in self._songs
def __iter__(self):
"""for song in playlist"""
return iter(self._songs)
def __iadd__(self, song):
"""playlist += song"""
self._songs.append(song)
return self
def __repr__(self):
return f"Playlist('{self.name}', {len(self)} songs)"
playlist = Playlist("Road Trip")
playlist += "Hotel California"
playlist += "Bohemian Rhapsody"
playlist += "Stairway to Heaven"
print(len(playlist)) # 3
print(playlist[0]) # Hotel California
print("Bohemian Rhapsody" in playlist) # True
print(playlist[1:]) # [Bohemian..., Stairway...]
for song in playlist:
print(f" ♪ {song}")
Operator Reference Table
| Operator | Method | Reverse |
|---|---|---|
+ | __add__ | __radd__ |
- | __sub__ | __rsub__ |
* | __mul__ | __rmul__ |
/ | __truediv__ | __rtruediv__ |
== | __eq__ | — |
< | __lt__ | __gt__ |
[] | __getitem__ | — |
len() | __len__ | — |
in | __contains__ | — |
str() | __str__ | — |
- Implement
__add__,__sub__, etc. to make your objects work with+,-operators. - Use
@total_orderingto only define__eq__and__lt__— the rest auto-generate. - Implement
__rmul__(reverse) so bothobj * 3and3 * objwork. - Implement
__getitem__and__len__to make objects behave like collections. - Overloaded operators should return new objects — avoid modifying
self(except__iadd__).
Frequently Asked Questions
Answers to common Python getting-started questions
Python Programming Tutorial — Learn Python from Scratch
Python is the world's most popular programming language for beginners, data science, AI/ML, web development, and automation. This tutorial teaches Python step-by-step with clear explanations and runnable code examples. You can try every example in our free Python Compiler without installing anything.
Each topic builds on the previous one, starting from installation and Hello World through advanced concepts like decorators, generators, and file I/O. Whether you are a complete beginner or refreshing specific skills, every page gives you immediately usable code.
What This Tutorial Covers
- Getting Started: Install Python, run online, Hello World
- Basics: Variables, data types, type conversion, input/output
- Operators: Arithmetic, comparison, logical, assignment
- Control Flow: if/elif/else, for loops, while, break/continue
- Data Structures: Lists, tuples, sets, dictionaries
- Strings: Methods, slicing, formatting, f-strings
- Functions: Parameters, return values, *args, **kwargs, scope
- OOP: Classes, objects, inheritance, polymorphism
- File I/O: Reading, writing, CSV, JSON handling
- Exceptions: try/except, custom exceptions, raise
- Advanced: List comprehensions, lambda, generators, decorators
- Modules: import, pip, packages, __name__ == "__main__"
Why Learn Python in 2026?
- #1 most popular language: Ranked first on TIOBE, Stack Overflow, and GitHub for multiple years running.
- AI and Data Science: The primary language for machine learning (TensorFlow, PyTorch, scikit-learn), data analysis (Pandas, NumPy), and AI development.
- Web development: Django and Flask power backends at companies like Instagram, Spotify, and Pinterest.
- Automation: Automate files, emails, web scraping, reports, and system administration tasks in minutes.
- Beginner-friendly: Clean syntax with enforced indentation makes code readable from day one — no curly braces or semicolons.
- Massive job market: Python developers are in high demand across tech, finance, healthcare, and research.
Python vs Other Languages
| Feature | Python | Java | JavaScript | C++ |
|---|---|---|---|---|
| Syntax | Very clean, readable | Verbose | Moderate | Complex |
| Typing | Dynamic, strong | Static, strong | Dynamic, weak | Static, strong |
| Speed | Slower (interpreted) | Fast (JIT) | Fast (V8 JIT) | Fastest (native) |
| Best For | AI/ML, data, automation | Enterprise, Android | Web frontend/backend | Systems, games |
| Learning Time | 2–4 weeks basics | 4–6 weeks basics | 3–4 weeks basics | 8–12 weeks basics |
How to Get Started
- Run Python online: Use our free Python Compiler — no installation needed.
- Install locally: Download Python 3 from
python.org(Windows/Mac) or useapt install python3(Linux). - Verify: Run
python3 --versionin your terminal to confirm installation. - Choose an editor: VS Code with Python extension (free), PyCharm Community (free), or Jupyter Notebook for data science.
- Follow this tutorial in order: Start from Introduction and work through each topic sequentially.
Frequently Asked Questions
No. Python is designed to be beginner-friendly. This tutorial starts from absolute zero and builds up gradually.
Python 3.10+ is recommended. Python 2 reached end-of-life in 2020. All examples in this tutorial use Python 3 syntax.
Basics (syntax, loops, functions) take 2–4 weeks. Intermediate (OOP, file I/O, modules) adds 3–4 weeks. Specialisation (Django, data science, ML) takes another 2–3 months.
Yes, completely free. No account, no sign-up. All topics and examples available without restriction.
Who Is This For?
Complete beginners choosing their first programming language. Students in CS courses needing a Python reference. Data analysts transitioning from Excel to Python (Pandas). Self-taught developers adding Python to their skill set. Professionals automating repetitive tasks. Anyone preparing for Python coding interviews.