Python for Scripting and Data Pipeline automation

1. Python Overview
– Core Concepts
– Python Data Model

2. Installing Python
– Bundled Python (Linux / MacOS)
– Installing Anaconda
– Managing Environments
– Installing Packages

3. Data Types Recap
– Integers
– Floats
– Strings
– String Functions
– String Formatting
– Booleans
– NoneType
– Practice Lab: Working with Python Data Types

4. Data Structures Recap
– Lists
– Indexing and Slicing
– List operations
– List methods
– Tuples
– Tuples vs Lists
– Tuples Immutability
– Dictionaries
– Dictionary Methods
– Sets
– Set methods
– Sets vs Lists
– Practice Lab: Working with Python Data Structures

5. Programming Fundamentals Recap
– Loops
– Pattern Matching
– Functions
– Function arguments
– Positional vs Keyword arguments
– Default arguments
– Function Scoping
– Practice Lab: Conditionals, Loops and Functions
– Functional Programming
– Lambda functions
– Map
– Filter
– Decorators
– Practice Project: Implementing a Calculator Application (with FP)

6. Object Oriented Programming
– Creating a Simple Class
– Dunder Methods. Constructors. Operators.
– Inheritance, Polymorphism, Encapsulation, Abstraction
– Practice Project: Implementing a NoteApp Class

7. Input / Output
– Reading from stdin
– Writing to stdout
– Practice Project: Building a Tic-Tac-Toe Game
– Opening and Closing Files
– Reading from Files
– Writing to Files
– The Context Manager
– Network IO
– The requests package
– Practice Project: Playing Tic-Tac-Toe Against an Online Server

8. File System Manipulation
– Processing Files
– The os module
– Traversing Directories
– Practice Project: Aggregating CSV Files
– Creating, Moving and Deleting Files and Directories
– Creating Archives
– Practice Project: Automating Daily Backups

9. Concurrency and Asynchronous Operations
– Multithreading in Python
– The queue module
– ThreadPoolExecutor
– Multithreading vs Parallel Processing
– Async IO
– async and await
– Practice Project: Scraping an E-Commerce Website

10. Writing Scripts
– Processing Command Line Arguments
– The sys Module
– The argparse Module
– Using Environment Variables
– Practice Project: Building a CLI Task Manager Application
– Exception Handling
– The subprocess module
– The signal module
– Turning Scripts Into Executables
– Schedule Scripts to Run at a Specific Time
– Unit Testing with pytest
– Organizing Scripts in Modules and Packages
– Best Practices

11. Pandas
– Introduction to Jupyter Notebooks
– Series and DataFrames
– Reading and Writing .csv files
– Indexing DataFrames
– Creating, manipulating and deleting DataFrame columns
– Merging data from multiple DataFrames
– Plotting data using the built-in API
– Time Series
– The datetime module
– Practice Project: Cleaning data from multiple sources and visualizing it

12. Apache Airflow
– Airflow Concepts
– DAGs and Operators
– Extending Operators
– Tasks and relationships
– Connections
– Job scheduling
– Practice Project: Scheduling a periodic data extraction and cleaning job