Learn Python Programming

Start with getting started, installation, and core basics. Clear explanations and practical examples to help you learn faster.

Python Exceptions

Exceptions are errors detected during execution. When Python encounters an error it cannot handle, it raises an exception that interrupts normal program flow.

What Are Exceptions?

# Exceptions occur when something goes wrong at runtime
# (as opposed to syntax errors, which are caught before running)

# Common built-in exceptions:
print(10 / 0)           # ZeroDivisionError
print(int("hello"))     # ValueError
print(my_var)           # NameError (undefined variable)
print([1, 2][5])        # IndexError
print({"a": 1}["b"])    # KeyError
print("hello" + 5)      # TypeError
open("missing.txt")     # FileNotFoundError

Exception Hierarchy

# All exceptions inherit from BaseException
# Most user-facing exceptions inherit from Exception

# BaseException
# ├── SystemExit
# ├── KeyboardInterrupt
# ├── GeneratorExit
# └── Exception
#     ├── ValueError
#     ├── TypeError
#     ├── KeyError
#     ├── IndexError
#     ├── FileNotFoundError (subclass of OSError)
#     ├── ZeroDivisionError (subclass of ArithmeticError)
#     ├── AttributeError
#     ├── ImportError
#     │   └── ModuleNotFoundError
#     ├── RuntimeError
#     │   └── RecursionError
#     └── StopIteration

# You can inspect the hierarchy:
print(ValueError.__mro__)
# (ValueError, Exception, BaseException, object)

Basic Exception Handling

# try/except catches exceptions and prevents crashes
try:
    number = int(input("Enter a number: "))
    result = 100 / number
    print(f"Result: {result}")
except ValueError:
    print("That is not a valid number!")
except ZeroDivisionError:
    print("Cannot divide by zero!")

# Catch the exception object for details
try:
    data = [1, 2, 3]
    print(data[10])
except IndexError as e:
    print(f"Error: {e}")        # list index out of range
    print(f"Type: {type(e)}")   # <class 'IndexError'>

Common Exception Types and When They Occur

ExceptionWhen It OccursExample
ValueErrorWrong value for the typeint("abc")
TypeErrorWrong type for operation"a" + 1
KeyErrorDict key not foundd["missing"]
IndexErrorList index out of range[1,2][5]
FileNotFoundErrorFile does not existopen("x.txt")
ZeroDivisionErrorDivision by zero10/0
AttributeErrorObject has no attributeNone.upper()
ImportErrorModule not foundimport fake_lib
PermissionErrorNo permission for operationopen("/etc/shadow")

Raising Exceptions

# Use raise to throw an exception intentionally
def set_age(age):
    if age < 0:
        raise ValueError("Age cannot be negative")
    if age > 150:
        raise ValueError("Age seems unrealistic")
    return age

try:
    set_age(-5)
except ValueError as e:
    print(e)  # Age cannot be negative

# Re-raise an exception after logging
try:
    result = risky_operation()
except Exception as e:
    print(f"Error occurred: {e}")
    raise  # re-raises the same exception
  • Exceptions are runtime errors — different from syntax errors which prevent execution.
  • Use try/except to handle exceptions gracefully instead of crashing.
  • Catch specific exceptions (not bare except:) to avoid hiding bugs.
  • Use raise to signal errors in your own functions with descriptive messages.
  • All exceptions form a hierarchy — catching a parent catches all its children.

Frequently Asked Questions

Answers to common Python getting-started questions

You can use an online Python editor that runs in your browser. It provides a Python interpreter so you can execute code instantly without setup. This is ideal for quick practice and learning.

Download the latest Python installer from the official Python website, run the installer, and select "Add python.exe to PATH" before clicking "Install Now". After installation, verify with the command: python --version.

Download the macOS installer from the Python website, run it, and follow the steps. Verify the installation with python3 --version in the Terminal. macOS often uses python3 to refer to Python 3.

Open your terminal or command prompt and run python --version (Windows) or python3 --version (macOS/Linux). If you see a version number, Python is installed correctly.

On macOS and Linux, python may refer to Python 2.x while python3 refers to Python 3.x. Use python3 to ensure you are running Python 3.

Yes. Python runs on Windows, macOS, and Linux. Code is generally portable across platforms, especially for beginner-level scripts.

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

FeaturePythonJavaJavaScriptC++
SyntaxVery clean, readableVerboseModerateComplex
TypingDynamic, strongStatic, strongDynamic, weakStatic, strong
SpeedSlower (interpreted)Fast (JIT)Fast (V8 JIT)Fastest (native)
Best ForAI/ML, data, automationEnterprise, AndroidWeb frontend/backendSystems, games
Learning Time2–4 weeks basics4–6 weeks basics3–4 weeks basics8–12 weeks basics

How to Get Started

  1. Run Python online: Use our free Python Compiler — no installation needed.
  2. Install locally: Download Python 3 from python.org (Windows/Mac) or use apt install python3 (Linux).
  3. Verify: Run python3 --version in your terminal to confirm installation.
  4. Choose an editor: VS Code with Python extension (free), PyCharm Community (free), or Jupyter Notebook for data science.
  5. Follow this tutorial in order: Start from Introduction and work through each topic sequentially.

Frequently Asked Questions

Do I need prior programming experience?

No. Python is designed to be beginner-friendly. This tutorial starts from absolute zero and builds up gradually.

Which Python version should I use?

Python 3.10+ is recommended. Python 2 reached end-of-life in 2020. All examples in this tutorial use Python 3 syntax.

How long does it take to learn Python?

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.

Is this tutorial free?

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.