An open API service indexing awesome lists of open source software.

https://github.com/melikaworks/performance-evaluation-system

Enterprise-grade performance evaluation system with multi-organization support, approval workflows, system signatures, and analytical reports.
https://github.com/melikaworks/performance-evaluation-system

django enterprise-application hr-system multi-tenant performance-evaluation postgresql python rbac reporting workflow

Last synced: 4 months ago
JSON representation

Enterprise-grade performance evaluation system with multi-organization support, approval workflows, system signatures, and analytical reports.

Awesome Lists containing this project

README

          

# Performance Evaluation System (Django)

A web-based performance evaluation platform built with Django, designed for multi-organization environments (holding / factory / department groups) with role-based access, workflow approvals, and manager/admin reporting.

## Key Features
- Multi-organization scoping (Holding, Factory, DepartmentGroup)
- Role-based access for Admins and Managers
- Evaluation workflow and approval states (signatures and audit-ready structure)
- Manager dashboards and reports (including print-friendly views)
- CSV / PDF / Print-ready reporting paths
- Structured import and maintenance scripts

## Tech Stack
- Python / Django
- PostgreSQL (intended for production)
- HTML, CSS, JavaScript (server-rendered templates)
- Chart.js for reporting visuals
- SharePoint Lists, Libraries, and Custom Views
- Portfolio & Resource Management Concepts

## Repository Structure
- `core/` – Main application logic (models, views, approvals, workflow, templates, static files)
- `project/` – Django project configuration (settings, URLs, WSGI/ASGI)
- `scripts/` – Utility scripts for imports, analysis, and maintenance
- `docs/` – Technical documentation and design notes

### Database Design
The database schema is defined and managed through Django models and migrations, ensuring consistency across environments.

## Local Setup
1. Create and activate a virtual environment

2. Install dependencies:
```bash
pip install -r requirements.txt
```

3. Configure environment variables locally (`.env` is excluded from version control)

4. Run migrations and start the server:
```bash
python manage.py migrate
python manage.py runserver
```

## Notes
- Sensitive data and local artifacts are excluded using `.gitignore`
- The project follows a clean commit history and modular structure

## Project Management
Project lifecycle was managed using **Azure DevOps**, including backlog tracking, task breakdown, and release coordination.

## Author

👩‍💻 **Melika Mehranpour**
Senior Software Engineer | Backend & Enterprise Systems
Python (Django) • PostgreSQL • System Design • Agile

🔗 [LinkedIn](https://www.linkedin.com/in/melika-mehranpour-41b627161/) | [GitHub](https://github.com/MelikaWorks)

## License
See the [LICENSE](LICENSE) file for license information.