ZTM Python Projects

Table of Contents

1. Project Overview
2. Folder Structure
   1. Section 3 Basics
   2. Section 6 OOP
   3. Section 7 Functional Programming
   4. Section 8 Decorators
   5. Section 9 Error Handling
   6. Section 10 Generators
   7. Section 11 Modules
   8. Section 12 Debugging
   9. Section 13 I/O File Handling
   10. Section 14 Regular Expressions
   11. Section 15 Testing in Python
   12. Section 17 Scripting
   13. Section 18 Web Scraping
   14. Section 19 Web Development
   15. Section 20 Automation
   16. Section 21 Machine Learning
   17. Section 24 HTML Forms
3. Getting Started
4. Dependencies

Project Overview

This repository contains various Python projects and exercises covered in the ZTM Python course. It includes practical examples on a wide range of topics such as object-oriented programming, functional programming, web scraping, automation, machine learning, and more.

Folder Structure

ZTM-Python-main/
├── Section 3 Basics/ - Introduction to basic Python concepts like variables, data types, and control flow, with practical examples.
├── Section 6 OOP/ - Projects related to Object-Oriented Programming, covering classes, inheritance, polymorphism, and encapsulation, with examples of designing custom classes.
├── Section 7 Functional Programing/ - Exercises on functional programming, including higher-order functions, lambdas, closures, and using map/reduce for data processing.
├── Section 8 Decorators/ - Examples showcasing the usage of decorators in Python to modify or extend the behavior of functions.
├── Section 9 Error Handling/ - Scripts demonstrating error handling techniques using try, except, and finally blocks, along with custom exceptions.
├── Section 10 Generators/ - Examples of generators and their benefits for memory efficiency, including use cases like Fibonacci sequences and data streaming.
├── Section 11 Modules/ - Explanation of Python modules, creating custom modules, and using built-in modules like `random` and `os` to organize and reuse code effectively.
├── Section 12 Debugging/ - Techniques for debugging Python code, including the use of `pdb`, logging, and understanding common errors and how to fix them.
├── Section 13 I/O File Handling/ - File handling in Python, including reading from and writing to files, working with different file types, and using context managers.
├── Section 14 Regular Expressions/ - Introduction to using regular expressions for pattern matching in strings, covering common patterns and use cases like email validation.
├── Section 15 Testing in Python/ - Writing unit tests and using the `unittest` framework to ensure code reliability, including mock testing and edge case testing.
├── Section 17 Scripting/ - Practical Python scripting projects, such as image processing, PDF handling, generating passwords, and sending automated emails.
├── Section 18 Web Scraping/ - Web scraping examples using `BeautifulSoup` and `requests` libraries to extract data from websites, including handling pagination and saving data.
├── Section 19 Web Dev/ - Introduction to web development using Python, including setting up a simple Flask server, handling routes, and serving static files.
├── Section 20 Automation/ - Automation projects using Python, including browser automation with Selenium and automating repetitive tasks like file renaming.
├── Section 21 Machine Learning/ - Basic machine learning projects, including data visualization with `matplotlib`, training simple models using `scikit-learn`, and saving models.
├── Section 24 HTML Forms/ - Working with HTML forms, handling user input, and integrating Python scripts to process form data.
├── .gitignore
├── Conda_requirements.txt
├── README.md
├── pip command lines.txt
├── requirements.txt
...

The detailed folder structure can be found in the repository.

Section 3 Basics

Introduction to basic Python concepts like variables, data types, and control flow, with practical examples.

Section 6 OOP

Projects related to Object-Oriented Programming, covering classes, inheritance, polymorphism, and encapsulation, with examples of designing custom classes.

Section 7 Functional Programming

Exercises on functional programming, including higher-order functions, lambdas, closures, and using map/reduce for data processing.

Section 8 Decorators

Examples showcasing the usage of decorators in Python to modify or extend the behavior of functions.

Section 9 Error Handling

Scripts demonstrating error handling techniques using try, except, and finally blocks, along with custom exceptions.

Section 10 Generators

Examples of generators and their benefits for memory efficiency, including use cases like Fibonacci sequences and data streaming.

Section 11 Modules

Explanation of Python modules, creating custom modules, and using built-in modules like random and os to organize and reuse code effectively.

Section 12 Debugging

Techniques for debugging Python code, including the use of pdb, logging, and understanding common errors and how to fix them.

Section 13 I/O File Handling

File handling in Python, including reading from and writing to files, working with different file types, and using context managers.

Section 14 Regular Expressions

Introduction to using regular expressions for pattern matching in strings, covering common patterns and use cases like email validation.

Section 15 Testing in Python

Writing unit tests and using the unittest framework to ensure code reliability, including mock testing and edge case testing.

Section 17 Scripting

Practical Python scripting projects, such as image processing, PDF handling, generating passwords, and sending automated emails.

Section 18 Web Scraping

Web scraping examples using BeautifulSoup and requests libraries to extract data from websites, including handling pagination and saving data.

Section 19 Web Development

Introduction to web development using Python, including setting up a simple Flask server, handling routes, and serving static files.

Section 20 Automation

Automation projects using Python, including browser automation with Selenium and automating repetitive tasks like file renaming.

Section 21 Machine Learning

Basic machine learning projects, including data visualization with matplotlib, training simple models using scikit-learn, and saving models.

Section 24 HTML Forms

Working with HTML forms, handling user input, and integrating Python scripts to process form data.

Getting Started

1. Clone the repository:

   git clone <repository-url>

2. Navigate to the project directory:

   cd ZTM-Python-main

3. Install the required dependencies.

Dependencies

• Install dependencies using pip:

  pip install -r requirements.txt

• Alternatively, use Conda:

  conda install --file Conda_requirements.txt