python-scripting-basics

Python Scripting: Basics

A practical, reusable training course for learning Python scripting, automation, and object-oriented programming.

The course begins with small command-line scripts and gradually introduces reusable functions, modules, packages, file processing, command-line interfaces, logging, configuration, testing, and maintainable object-oriented design.

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Course Objectives

By the end of this course participants will be able to:

• Create and use Python virtual environments
• Write portable Python scripts with explicit entry points and exit codes
• Work with strings, numbers, lists, tuples, dictionaries, and sets
• Use conditions, loops, comprehensions, and common built-in functions
• Design reusable functions with type hints and clear responsibilities
• Organize code into modules and packages
• Read and write text, JSON, and CSV files
• Work safely with paths through pathlib
• Handle expected failures with meaningful exceptions
• Build command-line tools with argparse
• Add logging and predictable configuration precedence
• Create classes, objects, methods, properties, and dataclasses
• Apply encapsulation, inheritance, composition, abstract base classes, and protocols
• Write automated tests with unittest
• Apply formatting, linting, documentation, and maintainability practices
• Build an object-oriented automation utility

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Target Audience

This training is suitable for:

• System administrators and DevOps engineers automating operational work
• Developers who want a structured introduction to Python scripting
• QA, support, and platform engineers who create command-line utilities
• Learners with basic programming knowledge who are new to Python
• Python beginners who want a practical introduction to OOP

Basic command-line knowledge is helpful but not required.

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Course Structure

Session	Topic
0	Course introduction and environment setup
1	Python script fundamentals
2	Data types, collections, and control flow
3	Functions, modules, and packages
4	Files, paths, JSON, CSV, and exceptions
5	CLI arguments, logging, and configuration
6	OOP fundamentals: classes and objects
7	OOP design: inheritance, composition, ABCs, and protocols
8	Testing, type hints, code quality, and packaging
9	Final automation project workshop

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Learning Path

flowchart LR
    A[Environment] --> B[Script basics]
    B --> C[Collections and control flow]
    C --> D[Functions and modules]
    D --> E[Files and exceptions]
    E --> F[CLI and logging]
    F --> G[Classes and objects]
    G --> H[Composition and interfaces]
    H --> I[Testing and quality]
    I --> J[Automation project]

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Repository Structure

python-scripting-basics/
├── README.md
├── MANIFEST.md
├── LICENSE.md
├── Makefile
├── requirements.txt
├── .gitignore
├── slides/
├── docs/
├── labs/
├── examples/
├── scripts/
└── quizzes/

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Getting Started

Clone the main repository and enter the module:

git clone https://github.com/VLD62/technical-trainings.git
cd technical-trainings/python-scripting-basics

Create and activate a virtual environment:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install -r requirements.txt

Windows PowerShell:

py -m venv .venv
.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install -r requirements.txt

Validate the environment and repository:

python scripts/validate_environment.py --check-repository
make validate

Run the first example:

python examples/01_basics/system_report.py

Run the tests:

make test

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Recommended Learning Approach

For every session:

1. Review the matching presentation
2. Read the related guide
3. Run and modify the examples
4. Complete the practical lab
5. Explain the design decisions
6. Complete the relevant knowledge-check questions
7. Commit the result to a practice repository

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Final Project

The final project is an object-oriented log analysis CLI demonstrating:

• File parsing and validation
• Dataclasses and type hints
• Composition between parser, analyzer, and report writer objects
• Command-line arguments and exit codes
• Logging
• Text and JSON reports
• Unit testing
• Separation of responsibilities

Try it:

python examples/09_project/log_analyzer.py \
  examples/09_project/sample.log \
  --level ERROR \
  --format json

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Validation

make validate
make test
make clean

The executable examples use the Python standard library. The packages in requirements.txt are optional development tools.

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License

Educational materials are licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International.

Source code and executable examples are licensed under the MIT License.