Query Purpose Extractor (QPE)

QPE is an application built with the goal of making Structured Query Language (SQL) more accessible and understandable to non-technical or beginning-to-be-technical users.

https://query-pe.dev

Installation

1. Clone this repository into a local directory on your machine.
2. Navigate to your new repository root in your terminal. Execute the below commands:

# Create a new virtual environment
python3 -m venv venv

# Activate virtual environment
source venv/bin/activate

# Install python dependencies
pip install -r requirements.txt

# If you encountered an error referencing 'python setup.py egg_info', uncomment 
# and run the below command inside your virtual environment. Then, try to install 
# the python dependencies again.
# pip install --upgrade setuptools

# Deactivate virtual environment
deactivate

# Install npm dependencies
npm install

Running the Application

1. Open two terminal windows. Navigate to the root of your cloned repository in both windows.
2. In the first window, run the command yarn start-api. This will begin your backend instance.
3. In the second window, run the command yarn start. This will begin your frontend instance.
4. A browser window should appear, but if it does not open one and navigate to localhost:3000
5. You should be greeted with the landing page and can now interact with the application.

API Documentation

Feel free to send a POST request to the API endpoint using your web application, Postman, or similar API handling service. The API endpoint is located at https://qpe.onrender.com/parse and the payload you send should be in JSON format following the below convention:

{
    "inputQuery": "SELECT 1",
    "path": 1
}

Where inputQuery is your SQL statement, and path is the result you would like to receive (1 for the JSON abstract syntax tree, 2 for the English paraphrases). The return expected from the above request is:

{
    "dict": {
        "Distinct": false,
        "From": {
            "joinvalue": [],
            "relname": []
        },
        "Group": {
            "groups": []
        },
        "Having": {
            "conditions": []
        },
        "Limit": "Unlimited results",
        "Select": {
            "targets": [
                [
                    "VALUE",
                    "1"
                ]
            ]
        },
        "Where": {
            "conditions": []
        }
    },
    "output": "A total of 0 tables were used in this query.\n\nThe following values were included in the result set: 1.\n\nThe number of returned results was unlimited."
}

dict will be returned in both paths 1 and 2 and contains a simplified dictionary of values representing the relations, projections, and other attributes. output will return either the JSON abstract parse tree with new line indicators for formatting purposes (when path = 1) or the English paraphrases (when path = 2).