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https://github.com/vinit-180/rule-engine-with-ast
3-tier rule engine app using AST for dynamic user eligibility based on age, dept, salary, experience.
https://github.com/vinit-180/rule-engine-with-ast
flask js mongodb nosql python react
Last synced: about 1 month ago
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3-tier rule engine app using AST for dynamic user eligibility based on age, dept, salary, experience.
- Host: GitHub
- URL: https://github.com/vinit-180/rule-engine-with-ast
- Owner: Vinit-180
- Created: 2024-10-19T21:50:04.000Z (2 months ago)
- Default Branch: master
- Last Pushed: 2024-10-24T09:51:00.000Z (2 months ago)
- Last Synced: 2024-10-25T07:41:58.383Z (2 months ago)
- Topics: flask, js, mongodb, nosql, python, react
- Language: JavaScript
- Homepage:
- Size: 210 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# Rule Engine Application
This project is a simple 3-tier rule engine designed to dynamically evaluate user eligibility based on attributes like age, department, salary and experience. The application uses an **Abstract Syntax Tree (AST)** to represent conditional rules, allowing for flexible rule creation, modification, and evaluation.
# Overview
The system is divided into three main components:
- **Frontend (UI)**: A simple interface built using React where users can define rules and attributes.
- **API Layer**: A Flask-based backend that handles rule creation, combination, and evaluation using AST (Abstract Syntax Tree).
- **Backend (Data Storage)**: Utilizes MongoDB to store rules and application metadata efficiently.
## Data Structure
- Define a data structure to represent the AST.
- The data structure should allow rule changes.
- For example, one data structure could be a `Node` with the following fields:
- `type`: String indicating the node type ("operator" for AND/OR, "operand" for conditions).
- `left`: Reference to another Node (left child).
- `right`: Reference to another Node (right child for operators).
- `value`: Optional value for operand nodes (e.g., number for comparisons).
## Features
- **Create Rules**: Enter strings in a simple format to convert them into rules.
- **Evaluate Rules**: Easily evaluate rules by entering them in a simple format.
- **Combine Rules**: Combine multiple rules using logical operators such as AND and OR.
- **Get All Rules**: Retrieve all the rules stored in the system.
- **Modify Rules**: Dynamically manage your rules by adding or editing them as needed.
## Requirements
- React (for the frontend)
- Flask (for the backend)
- MongoDB (for data storage)
- Docker (for containerization)
## Installation
### Frontend Setup
1. Navigate to the frontend directory:
```bash
cd AST/frontend
```
2. Install the required packages:
```bash
npm install
```
3. Start the frontend application:
```bash
npm start
```
### Backend Setup
1. Navigate to the backend directory:
```bash
cd AST/backend
```
2. Install the required Python packages:
```bash
pip install -r requirements.txt
```
3. Ensure MongoDB is running on your local machine.
4. Start the backend application (assuming you have a Flask app):
```bash
python app.py
```
### Docker Setup
1. Build and run the application using Docker Compose:
```bash
docker-compose up
```
This command will use the Docker images which were built by `Dockerfile` for the frontend and backend to create containers and start the entire system.
## Configuration
- Update the `MONGO_DATABASE_URI` in `config.py` if you are using a different database or you can directly create .env file and set your `URI` there.
## Usage
1. Access the application in your web browser at `http://localhost:3000` and the Flask API on `http://localhost:5000`..
2. Use the navigation bar to access different functionalities such as creating rules, evaluating them, and managing existing rules.
## API Endpoints
- `POST /api/rules/create_rule` - Create a new rule.
- `POST /api/rules/evaluate_rule` - Evaluate a rule.
- `POST /api/rules/combine_rules` - Combine multiple rules.
- `PUT /api/rules/update_rule` - Update an existing rule.
- `GET /api/rules` - Retrieve all rules.