Learn Python Programming
Start with getting started, installation, and core basics. Clear explanations and practical examples to help you learn faster.
Python Custom Exceptions
Custom exceptions let you define meaningful error types specific to your application. They make error handling clearer and help callers understand what went wrong.
Creating Basic Custom Exceptions
# Simplest custom exception — inherit from Exception
class ValidationError(Exception):
pass
class NotFoundError(Exception):
pass
# Raise and catch custom exceptions
def find_user(user_id):
users = {1: "Alice", 2: "Bob"}
if user_id not in users:
raise NotFoundError(f"User {user_id} not found")
return users[user_id]
try:
user = find_user(99)
except NotFoundError as e:
print(e) # User 99 not found
Custom Exceptions with Extra Data
# Add attributes to carry context about the error
class ValidationError(Exception):
def __init__(self, field, message, value=None):
self.field = field
self.message = message
self.value = value
super().__init__(f"{field}: {message}")
def to_dict(self):
return {"field": self.field, "error": self.message, "value": self.value}
# Usage
def validate_age(age):
if not isinstance(age, int):
raise ValidationError("age", "Must be an integer", age)
if age < 0 or age > 150:
raise ValidationError("age", "Must be between 0 and 150", age)
return age
try:
validate_age(-5)
except ValidationError as e:
print(e) # age: Must be between 0 and 150
print(e.field) # age
print(e.value) # -5
print(e.to_dict()) # {"field": "age", "error": "Must be...", "value": -5}
Exception Hierarchies
# Create a hierarchy for your application
class AppError(Exception):
"""Base exception for the application."""
pass
class DatabaseError(AppError):
"""Database-related errors."""
pass
class ConnectionError(DatabaseError):
"""Cannot connect to database."""
pass
class QueryError(DatabaseError):
"""Invalid or failed query."""
pass
class AuthError(AppError):
"""Authentication/authorization errors."""
pass
class InvalidCredentialsError(AuthError):
pass
class PermissionDeniedError(AuthError):
pass
# Catch at different levels of specificity
try:
authenticate(user, password)
except InvalidCredentialsError:
print("Wrong username or password")
except AuthError:
print("Authentication failed")
except AppError:
print("Application error occurred")
Practical Example: API Service
# Real-world pattern for a web service
class APIError(Exception):
"""Base API exception with HTTP status code."""
status_code = 500
def __init__(self, message, details=None):
self.message = message
self.details = details or {}
super().__init__(message)
def to_response(self):
return {
"error": type(self).__name__,
"message": self.message,
"details": self.details,
}
class BadRequestError(APIError):
status_code = 400
class UnauthorizedError(APIError):
status_code = 401
class NotFoundError(APIError):
status_code = 404
class RateLimitError(APIError):
status_code = 429
def __init__(self, retry_after=60):
self.retry_after = retry_after
super().__init__(f"Rate limit exceeded. Retry after {retry_after}s")
# Usage in request handler
def get_user(user_id):
if not is_authenticated():
raise UnauthorizedError("Login required")
user = db.find_user(user_id)
if user is None:
raise NotFoundError(f"User {user_id} not found")
return user
try:
user = get_user(42)
except APIError as e:
response = e.to_response()
response["status"] = e.status_code
print(response)
Exception Chaining
# Use "from" to chain exceptions — preserves the original cause
class ConfigError(Exception):
pass
def load_config(path):
try:
with open(path) as f:
import json
return json.load(f)
except FileNotFoundError as e:
raise ConfigError(f"Config file missing: {path}") from e
except json.JSONDecodeError as e:
raise ConfigError(f"Invalid JSON in {path}") from e
try:
config = load_config("settings.json")
except ConfigError as e:
print(e) # Config file missing: settings.json
print(e.__cause__) # [Errno 2] No such file or directory: ...
- Always inherit from
Exception(notBaseException) for custom exceptions. - Add attributes to carry context (field names, error codes, values) with the exception.
- Create exception hierarchies so callers can catch at the appropriate level of specificity.
- Use
raise ... from originalto chain exceptions and preserve the root cause. - Name exceptions ending in
Errorto follow Python conventions.
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.