📊 Metric Review System

Metric Review System is a lightweight, extensible web application for conducting peer reviews based on customizable performance metrics. Built with Streamlit, it enables teams to collect, manage, and analyze feedback efficiently through a simple browser-based interface.

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🚀 Getting Started

📦 Installation

1. Clone this repository:

   git clone https://github.com/vknov21/metric-review-system
   cd metric-review-system

2. Install required dependencies:

   pip install -r requirements.txt

3. Customize the Config to add the peers to review Go to the config.py file, and modify the necessary entries.

▶️ Running the App

Start the application using Streamlit:

streamlit run metric_review.py

• The app opens in your default browser.
• Select your reviewer name from the dropdown to begin a session.
• Fill in ratings for each teammate based on the defined metrics.
• Confirm and submit your reviews.

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✨ Features

🖥️ User Interface

• Browser-based experience – no installation required for end users.
• Session Management: Each reviewer logs in with a unique identity and can review each other or assigned users.
• Live Validation: All inputs are validated for proper range and type before submission.
• Progress Tracking: Once a review is finalized, it is locked to prevent duplicate submissions.
• Confirmation Dialogs: Confirms before final submission for each review.

📊 Metrics & Customization

• Configurable Metrics: Easily extend or modify the list of metrics in config.py to fit your team’s needs.
• Flexible Reviewer Mapping: Assign specific review responsibilities via the configuration.
• Database Storage: All review data is securely stored in a local SQLite database (sprint_06-06-2024.db by default).

🔒 Access & Security

• Browser-specific sessions: Prevents multiple logins with the same reviewer identity and restricts review access appropriately.

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🧰 Framework Extensibility

• Add new metrics or update the review structure by editing config.py.
• Extend database schema for advanced analytics or reporting.

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🛠️ Contributing

Contributions, bug reports, and suggestions are welcome! Fork the repository and submit a pull request to get involved.

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📝 Example Metrics

The default metrics include:

• Code Quality Metrics
• Development Efficiency
• Collaboration & Communication
• Learning and Growth
• Task and Time Management
• Customer/End-User Focus
• Innovation and Initiative
• Consistency and Reliability
• Team Support & Mentorship
• Work-Life Balance

Modify these in config.py as per your review workflow.

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📌 Note

• This tool is intended for internal team use.
• Ensure that you run the app via Streamlit as direct execution with Python is not supported.
• Currently, clearing cache on the browser will lock one out, once signed in, so currently avoid doing that.
• Private browsing may also lead to the above mentioned issue, and currently, the tab needs a refresh to start working due to cache unavailable for the first time