📚 Scooter Service: API Automation Framework

✅ Table of Contents

1. Description
2. Tech Stack & Tools
3. Project Architecture
4. Allure Reporting Features
5. Test Coverage
6. Execution Guide
7. CI/CD Workflow

💫 Description

This project contains automated API tests for the Yandex Scooter service. The framework validates the core backend functionality including courier management and order processing. Official API Documentation: Yandex Scooter API.

🧑‍💻Tech Stack & Tools

• Language: Python 3.13+
• Framework: Pytest
• HTTP Client: Requests
• Reporting: Allure Framework
• CI/CD: GitHub Actions

📁 Project Architecture

    ├── .github/workflows/     # CI/CD pipeline configuration 
    ├── allure-results/        # Raw test execution data (generated after run)
    ├── srs/                   # Support modules
    │   ├── config.py          # API Endpoints and Base URL
    │   ├── data.py            # Test data and Response messages
    │   ├── helpers.py         # Data generators (random strings, etc.)
    │ 
    ├── tests/                 # Test scenarios
    │   ├── test_create_courier.py
    │   ├── test_create_order.py
    │   ├── test_get_orders_list.py
    │   ├── test_login_courier.py
    │   
    ├── conftest.py              # Pytest fixtures
    ├── pytest.ini               # Configuration file (Allure flags)
    ├── requirements.txt         # Project dependencies
    └── .gitignore               # Files to exclude from Git

📊 Allure Reporting Features

The project is integrated with the Allure Framework to provide deep visibility into the API automation process. Key features include:

• Request & Response Transparency: Detailed logging of HTTP requests (Body, Headers) and Server responses, enabling rapid debugging directly from the report.
• Hierarchical Grouping: Tests are logically organized by Features (e.g., Courier Management) and Stories (e.g., Courier Authorization) for structured analysis.
• Dynamic Documentation: Detailed @allure.title and @allure.description transform technical code into readable business scenarios for stakeholders.
• Step-by-Step Execution: Comprehensive @allure.step logging tracks every action, from generating random test data to validating final JSON response structures.
• Parametrization Support: Clear visualization of multiple test variations (e.g., different scooter colors) within a single test suite.

🧪 Test Coverage

The automation suite provides comprehensive coverage for the following functional modules of the Yandex Scooter API:

1. Courier Management

• Registration Flow:
  • Successful courier creation with valid data.
  • Verification of error handling when creating a duplicate courier (409 Conflict).
  • Validation of mandatory fields: ensuring an account cannot be created if required data is missing (400 Bad Request).
• Authorization (Login):
  • Successful login and retrieval of the courier ID.
  • Error handling for incorrect login/password combinations (404 Not Found).
  • Validation of missing mandatory fields in the login request.
  • Verification of system behavior when attempting to log in as a non-existent user.

2. Order Management

• Order Creation:
  • Functional testing of the order placement process with various color combinations (Black, Grey, both, or none).
  • Verification of successful response status codes (201 Created).
  • Validation of the order track number presence and data type in the response.
• Order Retrieval:
  • Verification of the global order list retrieval (200 OK).
  • Data structure validation to ensure the response contains a non-empty list of orders.

3. Technical Implementation Details

• Data Parameterization: Using @pytest.mark.parametrize to execute multiple test variations efficiently.
• Response Validation: Strict verification of HTTP status codes, JSON keys, and specific error messages.
• Clean Code Practices: Centralized configuration for endpoints and reusable test data to ensure maintainability.

⚙️ 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_7
cd Sprint_7

📦 Repository: Sprint_5

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

The framework is pre-configured via pytest.ini. You can execute the full test suite and collect Allure results with a single command:

pytest

Note: This will automatically clear previous results and generate new data in the allure-results folder.

3. Generatig Allure Report

To transform the raw execution data into a visual, interactive HTML report, use the following command:

allure serve allure-results

This will launch a local web server and open the report in your default browser.

⚙️ CI/CD Workflow

The project is fully automated using GitHub Actions. Upon every push to the main branch or any Pull Request creation:

1. Environment Provisioning: A clean Ubuntu runner is initialized in the cloud environment.
2. Dependency Management: The Python 3.13 environment is set up, and all required libraries (Requests, Pytest, Allure) are installed from requirements.txt.
3. Automated Execution: The full API test suite is executed against the Stellar Burgers (or Scooter) production/staging environment.
4. Artifact Generation: Test results are collected, and the Allure report is prepared for analysis, ensuring that any API regression is caught immediately.
5. Status Reporting: Real-time feedback on build success or failure is provided via GitHub status badges.