Python Tutorial: From Beginner to Pro in 150+ Topics

Python Tutorial – Welcome to your ultimate Python programming tutorial! Whether you’re a complete beginner or looking to enhance your skills, our comprehensive guide will help you master Python from the ground up.

Contents hide

1 Python Tutorial – Getting Started

10 Modules & Packages

11 File Handling

12 Python Directory Handling

13 Python Tutorial – Third-Party Packages, PIP & Virtual Environments

14 About Editorial Team

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Python Tutorial – Getting Started

What is Python – Discover why Python is one of the most popular programming languages today.
How to Install Python on Windows? – Step-by-step guide to setting up Python on Windows.
How to Install Python on MacOS? – Learn how to install Python on your Mac.
How to Install Python on Linux? – Get Python up and running on Linux.
Setup Visual Studio Code for Python – Configure VS Code for Python development.
Hello, World! Program in Python – Write and run your first Python program.

Fundamentals

Indentation in Python – Understand the importance of indentation in Python syntax.
Python Comments – Learn how to add comments to your code for better readability.
Variables in Python – Explore how to declare and use variables effectively.
Strings – Manipulate text data with string operations.
Numbers – Perform calculations using numerical data types.
Booleans – Use Boolean logic to control program flow.
Constants – Define constants and understand their usage.
Python Keywords and Identifiers – Get familiar with reserved words and naming conventions.
Literals in Python – Learn about different literal types in Python.
Operators in Python – Use arithmetic, logical, and comparison operators.
Python Input and Output – Interact with users through input and output functions.
Implicit Type Conversion in Python – Let Python handle automatic type conversions.
Explicit Type Conversion in Python – Convert data types manually when needed.

Flow Control

Conditional Statements (if, if-else, if-elif-else) – Control the execution flow with conditions.
Else in Loops – Understand how else works with loops.
Ternary Operator – Write concise conditional statements.
Nested Conditions – Implement complex logic with nested conditions.
While Loop – Repeat actions using while loops.
For Loop – Iterate over sequences with for loops.
Loop Control Break – Exit loops prematurely with break.
Loop Control Continue – Skip iterations in loops with continue.
Loop Control Pass – Use pass as a placeholder in your code.
Iterating with Range() – Generate sequences of numbers efficiently.

Strings

String Basics and Syntax – Master string creation and manipulation.
String Indexing and Slicing – Access specific characters and substrings.
String Methods and Functions – Utilize built-in string methods for processing.
String Concatenation – Combine strings seamlessly.
String Formatting (f-strings, format(), %) – Format strings dynamically.
Escape Characters in Strings – Include special characters in your strings.
String Comparison – Compare strings for equality and ordering.
Checking Substrings – Determine if a substring exists within a string.
String Iteration with Loops – Loop through strings character by character.
String Immutability – Understand why strings cannot be altered in place.
Regular Expressions (Regex) Basics – Use regex for advanced string matching.

Functions

Python Functions – Define and invoke reusable code blocks.
Scope of Variable in Python – Learn about local and global variables.
Python Function Arguments – Pass data to functions effectively.
Default Parameters – Set default values for function parameters.
Keyword Arguments – Call functions using keyword arguments.
Packing and Unpacking Arguments in Python – Handle multiple arguments gracefully.
*args and **kwargs in Python – Work with variable-length argument lists.
Recursive Functions / Recursion in Python – Solve problems using recursion.
Lambda Expressions / Python Lambda – Write anonymous functions for short operations.
Python Docstrings – Documenting functions and modules.

Lists

What is List in Python? – Learn about Python’s versatile list data type.
Iterate over a List – Understand different methods to loop through list elements.
Slice a List – Extract portions of a list using slicing techniques.
Unpack a List – Assign list elements to variables with list unpacking.
Sort a List in Place – Sort list elements directly within the list.
Sort a List – Learn sorting techniques for lists in Python.
Find the Index of an Element – Locate the position of specific elements in a list.
Transform List Elements with map() – Apply a function to each element in a list using map().
Filter List Elements with filter() – Select elements meeting certain criteria using filter().
Reduce List Elements into a Value with reduce() – Aggregate list elements into a single value using reduce().
List Comprehensions – Create lists efficiently with list comprehension syntax.
Tuple in Python – Learn about immutable tuple data type in Python.
Differences between Tuples and Lists – Understand key differences between tuples and lists.
Iterables – Explore Python’s iterable objects and their usage.

Dictionary

Dictionary in Python – Store data using key-value pairs.
Dictionary Methods – Manipulate dictionaries with built-in methods.
Dictionary Comprehension – Construct dictionaries dynamically.

Sets

Introduction to Sets – Discover the set data type for unique elements.
Creating Sets – Initialize sets in Python.
Accessing Set Elements – Access and modify set elements.
Adding Elements to a Set – Add new items to a set.
Removing Elements from a Set – Remove items safely.
Set Operations: Union, Intersection, Difference, Symmetric Difference – Perform mathematical set operations.
Checking Set Membership – Test if an element exists in a set.
Iterating Through a Set – Loop over set elements.
Set Methods Overview (add(), remove(), discard(), clear(), etc.) – Utilize various set methods.
Set Comprehension – Create sets using set comprehensions.
Frozen Sets (Immutable Sets) – Work with immutable sets.
Sets vs. Lists and Tuples – Compare sets with other collections.
Handling Duplicates with Sets – Use sets to eliminate duplicate items.
Subset, Superset, and Disjoint Sets – Understand set relationships.
Using Sets for Data Filtering – Filter data efficiently using sets.

Exception Handling

Introduction to Exceptions and Basic Try-Except Blocks – Handle errors gracefully.
Handling Specific Exceptions and Using Else and Finally – Fine-tune your exception handling.
Raising Exceptions and Creating Custom Exceptions – Generate exceptions when necessary.
Understanding Exception Hierarchy and Chaining – Dive deeper into exception handling.
The Assert Statement, Debugging, and Best Practices – Debug your code effectively.
Context Managers (with Statement) and Exception Handling – Manage resources with context managers.
Logging Exceptions Using the Logging Module – Record exceptions for analysis.

Modules & Packages

Introduction to Modules in Python – Organize code with modules.
Creating and Using Your First Module – Build reusable components.
Importing Modules (import, from … import, import … as) – Import code from other modules.
Understanding Python’s Built-in Modules – Leverage Python’s standard library.
Using the dir() Function to Explore Module Contents – Discover what’s inside a module.
Creating and Structuring Python Packages – Organize large codebases.
The __init__.py File in Packages – Initialize your Python packages.
Importing from Packages – Access modules within packages.
Absolute vs. Relative Imports – Choose the right import style.
Using sys.path to Manage Module Search Paths – Modify where Python looks for modules.
Using __name__ == “__main__” for Module Execution – Write modules that can be run or imported.

File Handling

Introduction to File Handling in Python – Read from and write to files.
Opening Files with the open() Function – Open files for various operations.
Reading Files (read(), readline(), readlines()) – Extract data from files.
Writing to Files (write(), writelines()) – Output data to files.
Appending to Files – Add new data without overwriting.
Using with Statement for File Handling – Ensure files are properly closed.
Working with File Modes (r, w, a, r+, etc.) – Understand different file access modes.
Checking File Existence and Size (os.path) – Verify files before operations.
Reading and Writing Binary Files – Handle non-text files.
Handling File Exceptions – Manage errors during file operations.
Reading and Writing CSV Files (csv Module) – Work with spreadsheet data.
Reading and Writing JSON Files (json Module) – Parse and generate JSON data.
Reading and Writing Excel Files (pandas, openpyxl Modules) – Interact with Excel files.
Working with File Paths (os, pathlib Modules) – Manipulate file system paths.
File Compression and Decompression (zipfile, gzip Modules) – Compress files to save space.

Python Directory Handling

Introduction to Directory Handling in Python – Navigate the file system.
Navigating the File System – Change directories programmatically.
Creating and Removing Directories – Modify the directory structure.
Listing Directory Contents – Retrieve lists of files and folders.
Using os.path for Path Operations – Perform common path manipulations.
Using the pathlib Module for Directory Operations – Simplify path handling with pathlib.
Recursive Directory Traversal – Process files in nested directories.
Copying, Moving, and Deleting Files – Manage file locations.
Handling Directory Permissions – Access files with the correct permissions.
File and Directory Compression – Compress directories efficiently.

Python Tutorial – Third-Party Packages, PIP & Virtual Environments

Introduction to Third-Party Packages – Extend Python’s capabilities.
PIP Basics and Usage – Install packages using PIP.
Installing & Managing Packages – Keep your packages up to date.
Introduction to Virtual Environments – Isolate your Python projects.
Creating & Activating Virtual Environments – Set up separate environments.
Installing Packages in Virtual Environments – Manage dependencies per project.
Requirements Files (requirements.txt) – Document your project’s packages.
Updating & Uninstalling Packages – Maintain a clean environment.

About Editorial Team

Our Editorial Team is made up of tech enthusiasts who are highly skilled in Apache Spark, PySpark, and Machine Learning. They are also proficient in Python, Pandas, R, Hive, PostgreSQL, Snowflake, and Databricks. They aren't just experts; they are passionate teachers. They are dedicated to making complex data concepts easy to understand through engaging and simple tutorials with examples.