Skip to content

GitHubMaster07/Unified-Mobile-Python-Engine

Repository files navigation

🚀 Unified Mobile Python Engine (SOTA 2025-2026)

Python Version Appium License Python Quality Check

A high-performance, strictly typed mobile automation engine built for the 2025-2026 tech landscape. Designed with a Modular High-End Architecture, this project focuses on industrial-grade scalability, containerization, and observability.


🏗 Modular Architecture

The engine follows a decoupled layered approach to ensure zero-leakage between logic and infrastructure:

  • framework/: Core engine, WebDriver lifecycles, and robust Driver Factory.
  • app/: Application-specific logic (Page Object Model / Screen Objects).
  • config/: Fail-fast environment validation via Pydantic v2.
  • tests/: Atomic test execution powered by Pytest fixtures.

🛠 Tech Stack & DevOps

  • Core: Python 3.12+ (Strict Type Hinting)
  • Driver: Appium 2.x (UiAutomator2)
  • Infrastructure: BrowserStack Real Device Cloud
  • Validation: Pydantic v2 (Settings validation at runtime)
  • CI/CD: GitHub Actions (Automated PEP8 Quality Gates)
  • Containerization: Docker-ready for cross-platform orchestration
  • Observability: Allure Reports for advanced execution analytics

🚀 Quick Start

1. Environment Setup (Local)

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

2. Containerized Execution (Docker)

docker build -t mobile-engine .
docker run mobile-engine

3. Run Tests & Generate Reports

# Run tests
$env:PYTHONPATH="."; pytest --alluredir=allure-results

# Serve Allure Report
allure serve allure-results

📊 Cloud Monitoring & Observability

Integration with BrowserStack App Automate provides:

🎥 Live Video Streams of test execution.

📋 Device Logs & Appium Inspector data.

📈 Allure Dashboards for stakeholder reporting.

🌌 Roadmap to "QA Space Program"

This foundation is built to evolve. The following phases define the transition from Senior-level automation to an autonomous ecosystem:

[x] Phase 1: Foundation — Robust Driver Factory, Base Screen abstractions, CI/CD, and Dockerization.

[ ] Phase 2: Self-Healing AI — Integration of local LLMs/Computer Vision to recover broken selectors.

[ ] Phase 3: Visual Regression 2.0 — Pixel-perfect layout testing using OpenCV and Figma API.

[ ] Phase 4: Contract-Driven UI Testing — Aligning mobile UI tests with Backend API schemas.

Developed by Sergei Volodin

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors