Introduction to Python Tools

Lesson 1 • Installing Python and Tooling

Covers Python installation, version management, and essential editor setup. Grounds students in the environment they will use throughout the course.

Lesson 2 • Python Syntax and Data Types

Introduces variables, built-in data types, and type conversion. Provides the vocabulary needed for every subsequent coding task.

Lesson 3 • Running Scripts and the REPL

Demonstrates executing scripts from the command line and using the interactive REPL. Builds confidence in iterative, exploratory coding.

Lesson 4 • Functions and Scope

Defines reusable functions and explains variable scope rules. Prepares students to organize code into maintainable, callable units.

Lesson 1 • Tuples and Immutability

Explains tuples as immutable sequences and their practical use cases. Contrasts with lists to sharpen students' data-structure decision-making.

Lesson 2 • Lists and List Operations

Covers list creation, indexing, slicing, and mutation methods. Lists are the most frequently used sequence type and underpin later data work.

Lesson 3 • Choosing and Combining Structures

Guides selection among lists, tuples, dicts, and sets based on performance and semantics. Reinforces all prior structures through comparative exercises.

Lesson 4 • Sets and Membership Testing

Introduces sets for unique-value storage and fast membership checks. Connects to real-world deduplication and filtering tasks.

Lesson 1 • Path and Directory Management

Navigates the filesystem using pathlib for cross-platform compatibility. Enables robust script portability across different operating systems.

Lesson 2 • JSON Data Handling

Serializes and deserializes JSON using the json module. Prepares students for API responses and configuration file management.

Lesson 3 • Reading and Writing Text Files

Covers open(), file modes, and context managers for safe file access. Establishes the foundation for all file-based data processing tasks.

Lesson 4 • Error Handling in File Operations

Applies try/except blocks to handle I/O errors gracefully. Prevents script crashes from missing files or permission issues.

Lesson 1 • Organizing Code into Packages

Structures multiple modules into a package with __init__.py. Teaches the directory layout used in real-world Python projects.

Lesson 2 • Managing Dependencies with pip

Installs, upgrades, and removes third-party packages using pip. Connects students to the broader Python ecosystem of open-source tools.

Lesson 3 • Introduction to pyproject.toml

Introduces the modern project configuration file for packaging and tooling. Prepares students for professional project scaffolding standards.

Lesson 4 • Importing and Creating Modules

Explains the import system and how to write reusable module files. Modular code is the basis of maintainable, scalable Python projects.

Lesson 1 • Inheritance and Method Overriding

Extends base classes to share and specialize behavior across subclasses. Reduces code duplication and models hierarchical relationships.

Lesson 2 • Special Methods and Operator Overloading

Implements dunder methods to integrate custom classes with Python syntax. Enables intuitive use of operators and built-in functions on custom objects.

Lesson 3 • Encapsulation and Properties

Controls attribute access using private conventions and property decorators. Protects internal state while providing clean public interfaces.

Lesson 4 • Composition and Design Principles

Applies composition as an alternative to deep inheritance hierarchies. Introduces SOLID principles at a practical, beginner-accessible level.

Lesson 1 • HTTP Requests with the requests Library

Sends GET and POST requests and processes API responses using requests. Enables integration with web services and external data sources.

Lesson 2 • Visualization with Matplotlib

Generates line, bar, and scatter plots to communicate data insights visually. Connects analytical results to presentation-ready outputs.

Lesson 3 • Numerical Computing with NumPy

Performs fast array operations and mathematical computations using NumPy. Underpins pandas and most scientific Python libraries.

Lesson 4 • Scheduling and Automation with schedule

Automates recurring tasks using the schedule library for time-based execution. Bridges scripting skills with real-world automation requirements.

Lesson 1 • Mocking and Isolating Dependencies

Replaces external dependencies with mocks using unittest.mock. Enables reliable testing of code that calls APIs, files, or databases.

Lesson 2 • Unit Testing with unittest

Writes and runs unit tests using Python's built-in unittest framework. Establishes a testing habit that prevents regressions in evolving codebases.

Lesson 3 • Debugging Techniques and Tools

Uses print statements, logging, and the pdb debugger to locate and fix bugs. Systematic debugging reduces time spent on error resolution.

Lesson 4 • Testing with pytest

Leverages pytest for concise test syntax, fixtures, and rich output. pytest is the industry-standard tool for Python testing in professional teams.

Lesson 1 • Packaging a Python Project

Builds distributable packages using build and setuptools. Enables sharing tools internally or publishing them to a package repository.

Lesson 2 • Command-Line Interface Design with argparse

Builds user-friendly CLI tools using argparse for argument parsing. Transforms scripts into professional, self-documenting command-line applications.

Lesson 3 • Continuous Integration Basics

Automates testing and linting on every code push using a CI pipeline. Enforces quality gates and reduces manual verification overhead.

Lesson 4 • Configuration Management

Manages runtime settings via environment variables and config files. Separates configuration from code for secure, flexible deployments.