Python Course Summary

Jul 11, 2024

Python Course Summary

Course Overview

  • Covers key Python topics: web development, data science, machine learning, automation, etc.
  • Structure: Introduction, Data Types, Variables/Functions, Conditionals, Loops, Modules, Packages, OOP, API Requests.

Python Introduction

  • Popularity and applications of Python.
  • Benefits of learning Python: Easy to learn and flexible.

Python Setup

  • Download and install Python.
  • Configuring IDE (PyCharm): Download, install, and basic setup.

Programming Basics

Data Types

  • Strings: Text data within quotes.
  • Integers: Whole numbers.
  • Floats: Numbers with decimals.
  • Booleans: True/False values.
  • Lists: Ordered collection of items (allows duplicates).
  • Sets: Unordered collection without duplicates.
  • Dictionaries: Key-value pairs.

Variables and Functions

  • Variables: Hold values for reuse.
  • Functions: Block of code to perform tasks, avoid duplication.

Hands-On Examples

Example 1: User Input and Validation

  • Input Function: Accepts user data.
  • String Concatenation: Combine text and variables.
  • Type Conversion: Convert input types (e.g., string to int).

Example 2: Conditional Statements

  • If-Else: Execute code based on conditions.
  • Comparison Operators: >, <, ==, !=.

Example 3: Loops

  • For Loop: Iterate through a sequence (list/dictionary).
  • While Loop: Execute code as long as a condition is true.

Modularization

  • Modules: Python files (.py) containing functions/variables.
  • Importing Modules: Use functions/variables from other files.
  • Built-in Modules: Python's built-in functionality (e.g., datetime, os).
  • External Packages: Install and use third-party packages (e.g., via pip).

Projects

Project 1: Program Automation with Excel

  • Open PyXL Module: Read/write Excel files.
  • Example: Calculate product inventory values, create new Excel files.

Project 2: Date Handling

  • Datetime Module: Convert, compare and manipulate dates.

Object-Oriented Programming (OOP)

Classes and Objects

  • Class: Blueprint for objects with attributes and methods.
  • Object: Instance of a class.
  • Example: User class with email, name, and methods to change attributes.
  • Special Methods: __init__ constructor for initializing objects.

Inheritance

  • Subclass: Inherit attributes/methods from another class.
  • Example: Extend functionality of existing classes.

Interacting with APIs

  • HTTP Requests Module: Communicate with web services (e.g., GitLab API).
  • JSON Handling: Convert API responses into Python data types.
  • Example: Fetching project details from GitLab and printing.

Conclusion

  • Utilization of Python across various areas in technology.
  • Recommendation to explore more DevOps-related Python capabilities and other resources for DevOps learning and automation.
  • Importance of continuous learning and application of Python skills.