Python in Practice - 15 Projects to Master Python

Python in Practice - 15 Projects to Master Python

by Rahul Mula
Released October 2022
Publisher(s): Packt Publishing
ISBN: 9781804618486

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Video description

In this course, the initial few sections help you take a tour of programming in Python, covering all the basic to advanced concepts that are further used to build projects from scratch.

You will create 15+ applications with Python. First, you will be creating a Dice Roller (a Python GUI application with Tkinter to generate random dice outputs) and Total Seconds and Days Counter. After that, you will create a Length Converter Python GUI application. Next, you will work on the image-to-icon converter to convert .png, .jpg, and .jpeg images into icons. You will work on a random element selector, perform data analysis and data visualization with the help of NumPy, Pandas, and matplotlib. You will also create a trees survey report, user credentials data, and sales data report. You will create eBook Store with Django 3 and an eCommerce website with HTML, CSS, and Bootstrap. You will also create a weight predictor, rainy or clear weather, and flavor predictor.

Finally, you will make a rating bot, which will create a natural language processing model to rate comments and reviews automatically, and Face Recognizer that performs human face recognition with computer vision and OpenCV.

By the end of this course, you will have learned the programming fundamentals to an advanced level with Python 3 and become an advanced-level programmer.

What You Will Learn

  • Learn about built-in functions in Python and how to create one
  • Create a Python GUI application with Tkinter to generate random dice outputs
  • Analyze the sales report in a week with Python data analysis
  • Generate a survey report with data science
  • Create an NLP model to rate comments and reviews automatically
  • Perform human face recognition with computer vision and OpenCV

Audience

This course is ideal for individuals curious about Python programming, beginners at programming, and Python developers curious about data science, data analysis, and data visualization. This will also help full-stack web developers, artificial intelligence researchers, machine learning researchers, and GUI application developers.

You just need curiosity and enthusiasm to get going with this course; the rest of everything will be taught from scratch.

About The Author

Rahul Mula: Rahul Mula is a developer specializing in Python, Flutter, and web development. He was really intrigued the first time he learned about programming and realized what could be done with it. He loves to explore different technologies and create applications to build something new. He has developed Keyviz—the free and open-source tool to visualize keystrokes in real-time. He has written books and created courses on Python programming teaching thousands of students.

Table of contents

  1. Chapter 1 : Programming with Python: Basics and Environment Setup
    1. What Is Programming?
    2. Setting Up IDE
  2. Chapter 2 : Data Types and Variables
    1. Data Types in Python
    2. Variables
    3. Variable Names
  3. Chapter 3 : Text Data Types
    1. Python Strings
    2. Extracting Values from Strings: Strings, Slicing, and Indicing
    3. String Built-In Functions
  4. Chapter 4 : Numeric Data Types
    1. Numbers in Python
    2. Numeric Functions
  5. Chapter 5 : Boolean
    1. Python Booleans
  6. Chapter 6 : Lists
    1. Python Lists
    2. List Built-In Functions
  7. Chapter 7 : Tuples
    1. Python Tuples
    2. Tuple Operations and Tuple Built-In Functions
  8. Chapter 8 : Sets
    1. Pythons Sets
    2. Sets Built-In Functions
    3. Mathematical Sets Operations
  9. Chapter 9 : Dictionary
    1. Python Dictionaries
    2. Dictionary Built-In Functions
  10. Chapter 10 : Decision Control in Python
    1. Decision Control using if statements
    2. Creating conditions Using or and and keywords
    3. elif Statements
    4. else Statements
    5. Decision Control with Strings and Lists
  11. Chapter 11 : Loops in Python
    1. Creating Loops Using While Statements
  12. Chapter 12 : Iterating over Elements
    1. Iterating over Datatypes Using For Loops
  13. Chapter 13 : Functions
    1. Functions in Python and Defining Our Own
    2. Getting Arguments during Function Call
    3. Positional and Keyword Arguments
    4. Arguments and Parameters
    5. Arbitrary Arguments (*args)
    6. Arbitrary Keyword Arguments (**kwargs)
    7. Return Values from User-Defined Functions Using the Return Keyword
    8. Pass Keywords for Functions
    9. Lambda Functions
    10. Creating a Duplicate List Elements Remover Function
    11. Redefining the Built-In type( ) Function
    12. Creating a Function to Smartly Round Decimal Points in a Result of Addition
  14. Chapter 14 : Object-Oriented Programming
    1. What Are Classes and How to Create Them
    2. Defining Class Methods
    3. Adding, Modifying, and Deleting Class Attributes
    4. Class Attributes and Identifier Naming Convention
    5. Functions Versus Class Methods
    6. Operator Overloading on User-Defined Classes
    7. Built-Ins Overloading on User-Defined Classes
    8. Creating User-Defined Iterable Classes
  15. Chapter 15 : Inheritance
    1. Containership
    2. Inheritance
    3. Accessing Inherited Objects
    4. The Object Class
    5. Multi-Level Inheritance
    6. Multiple Inheritance
  16. Chapter 16 : Dealing with Errors
    1. Error Handling in Python
    2. User-Defined Errors
    3. Catching Errors with Except Block
    4. Use of else and finally Blocks
  17. Chapter 17 : Modules and Packages
    1. Modules and Packages
    2. random Module
    3. datetime Module
  18. Chapter 18 : All Built-In Functions
    1. abs( )
    2. all( )
    3. any( )
    4. ascii( )
    5. bin( )
    6. callable( )
    7. compile( ), exec( ), and eval( )
    8. delattr( )
    9. dir( )
    10. enumerate( )
    11. filter( )
    12. format( )
    13. getattr( )
    14. globals( )
    15. hasattr( )
    16. hash( )
    17. help( )
    18. hex( )
    19. id( )
    20. input( )
    21. isinstance( )
    22. issubclass( )
    23. iter( ) and next( )
    24. locals( )
    25. map( )
    26. oct( )
    27. open( )
    28. print( )
    29. range( )
    30. repr( )
    31. reversed( )
    32. setattr( )
    33. vars( )
    34. zip( )
  19. Chapter 19 : PyCharm IDE
    1. Creating Files in PyCharm
    2. Editing the Themes and Color Schemes
    3. Keymapping Shortcuts
    4. Executing Python Programs
  20. Chapter 20 : Advanced Level: Python GUI
    1. GUI Introduction
    2. Creating GUI Application Tk( ) Windows and Widgets
    3. Creating Button Widgets
    4. Getting Input from the User Using Entry Field Widgets
    5. Using Grid System to Place Widgets
    6. Button States
    7. Customizing Colors and Fonts
    8. Adding Color Theme to Your Applications
    9. Stylizing the Appearance of the Widgets (Relief)
    10. Creating Checkbox Widgets
    11. Creating Radio Button Widgets
    12. Creating Slider Widgets
    13. Creating Dropdown Menu widgets
    14. Adding more windows on top of our existing main window
    15. Working with Images
    16. File Dialog Boxes for Application
  21. Chapter 21 : Applications with Python GUI
    1. Dice Roller
    2. Age Calculator (Total Days and Seconds Lived)
    3. Length Converter Applications
    4. Image to Icon Converter
  22. Chapter 22 : Advanced Level: Data Science
    1. Data Science with Python
    2. Anaconda
    3. Jupyter Notebook
    4. Data Processing with NumPy Package
    5. Pandas Series
    6. n-darrays to Pandas Series
    7. Slicing Values from Pandas Series
    8. Pandas DataFrames
    9. Slicing Columns, Rows, and Values from Pandas DataFrames
    10. Matplotlib Library
    11. Data Processing
    12. Data Cleaning
    13. Data Analysis
    14. Data Visualization
    15. Customizing Visualizations with Matplotlib
    16. Different Types of Plots with Matplotlib
  23. Chapter 23 : Data Science Project 1
    1. Inspecting the Data
    2. Importing the Data
    3. Data Processing and Cleaning
    4. Data Analysis
    5. Data Visualization
    6. Generating the Final Report
  24. Chapter 24 : eBook Web Store
    1. Web Development with Python and Django
    2. How Websites Work and How We Can Create One?
    3. Starting Our Website Project with Django
    4. Customizing the Homepage View
    5. HTML Basics
    6. Admin Application and Creating Our Own Applications
    7. Creating Our Store View
    8. Creating Models and Storing eBooks in the Database
    9. Adding eBooks Through the Admin Application
    10. Django Template and Context System for html Views
    11. Web Design: Stylizing Our html Tags with CSS
    12. Bootstrap as Base Template
    13. Adding Bootstrap Cards as eBooks in Our Store Webpage
    14. Adding Bootstrap Navigation Bar to Our Website
    15. Adding the Cart to Our Website
    16. Bootstrap Containers
    17. Creating Model for Cart Items
    18. Getting Book ID from the Add to Cart Button
    19. Defining add_to_cart( ) View Function
    20. Displaying the Cart Sub-Total
    21. Adding a Delete Button to Cart Items
    22. Defining del_cart_item( ) View Function
    23. What to Display When the Cart Is Empty?
    24. Using Bootstrap Icons for html Elements
  25. Chapter 25 : Machine Learning with Python
    1. What Is Machine Learning?
    2. How Machines Learn
    3. Creating a Machine Learning Model with Dataset
    4. Preparing Data to Train the Machine Learning Model
    5. Asking the Model to Make Predictions
    6. Testing the Performance of the Model
    7. How to Make Training and Testing Sets Easily
    8. Working of the Regression Model
    9. Creating a Classification Model
    10. Predicting Whether It Will Rain or Not and Testing the Predictions
  26. Chapter 26 : Flavor Predictor
    1. Preparing the Data
    2. Training the Model
    3. Asking the Model to Make Predictions
  27. Chapter 27 : Artificial Intelligence
    1. What Is Artificial Intelligence?
    2. Natural Language Processing
    3. Feature Extraction from Text Data with CountVectorization
    4. Finding TF and IDF in Extracted Features from Text Data: Text Analytics
    5. Working with Images: Computer Vision
    6. Changing Color-Spaces of Images from BGR to RGB to GRAY
  28. Chapter 28 : Rating Bot
    1. Reviews and Ratings Data to Create the Model
    2. Extracting Features and Transforming the Reviews Data
    3. Training the Model to Rate Reviews
    4. Creating the Function to Rate Reviews (In Raw Format)
  29. Chapter 29 : Face Recognition Model
    1. Getting the Data to Create the Model
    2. Detecting Faces in Images with Our Model
    3. Creating a Function to Detect Faces and Show Them

Product information

  • Title: Python in Practice - 15 Projects to Master Python
  • Author(s): Rahul Mula
  • Release date: October 2022
  • Publisher(s): Packt Publishing
  • ISBN: 9781804618486