📚 BooksCollector: Unit Testing Framework

🎯 Project Overview

This repository showcases an approach to unit testing for the BooksCollector application. The project implements a scalable testing architecture with deep reporting and automated validation. The test suite ensures 100% reliability of core features: book inventory, genre categorization (including age-rating logic), and user favorites management.

🧑‍💻 Tech Stack & Tools

• Language: Python 3.10+
• Testing: pytest (utilizing fixtures, parametrization, and clean code principles)
• Reporting: Allure Framework (rich, human-readable HTML reports)
• CI/CD: GitHub Actions (automated test execution on every push)

📁 Project Architecture

The project is organized to ensure clean code separation and transparency:

Sprint_4/
    ├── .github/workflows/        # CI/CD pipeline configuration (GitHub Actions)
    ├── allure-results/           # Raw test execution data (generated after run)
    ├── main.py                   # Core application logic (BooksCollector class)
    ├── tests.py                  # Unit test suite with Allure annotations & fixtures
    ├── requirements.txt          # List of project dependencies
    └── README.md                 # Comprehensive project documentation

📊 Allure Reporting Features

I have integrated the Allure Framework to provide high-level visibility into test execution and simplify debugging:

• Dynamic Test Titles: Uses @allure.title to generate descriptive, human-readable test names that automatically update based on input parameters.
• Granular Execution Steps: Implements @allure.step annotations to track the logic flow within each test, making it easy to pinpoint exactly where a failure occurred.
• Logical Test Suites: Categorizes tests into functional suites using @allure.suite for better navigation and structured analysis of the test results.
• Environment Details: Provides a clear overview of the test environment and execution parameters.

🚀 Execution Guide

1. Environment Setup

Clone the repository and set up a local virtual environment to ensure dependency isolation:

1. Clone repository

git clone https://github.com/AlyaSmirnova/Sprint_4
cd Sprint_4

📦 Repository: Sprint_4

2. Create a virtual environment

python -m venv venv

3. Activate the virtual environment

source venv/bin/activate

4. Install required dependencies

$ pip install -r requirements.txt

2. Running Tests

Execute the full test suite and collect raw data for the Allure report:

pytest -v --alluredir=allure-results

3. Generatig Allure Report

Transform the raw data into a visual, interactive HTML report:

allure serve allure-results