Natural Language Query (NLQ) to SQL Translator This project is an assignment for the subject of Database Management Systems (DBMS). The goal is to build a program that can translate natural language questions (in plain English) into executable SQL queries.
The project is built iteratively, with each version adding new functionality and complexity.
Current Features As of now, the translator can handle:
Basic Queries: Simple, single-condition queries on a known table. Multi-Condition Queries: Queries containing two conditions linked by AND or OR. Rule-Based Parsing: The logic is built on a rule-based system using Regular Expressions in Python to identify and extract key query components. Project Structure & Solutions The project is divided into different versions, each contained in its own folder. Each folder is a self-contained solution with its own README explaining its specific features and how to run it.
V1: Basic Rule-Based: The foundational script that handles single conditions (e.g., "marks above 80"). V2: Multi-Condition Queries: An upgraded script that adds support for AND / OR clauses. Technology Used Python 3 Regular Expressions (Regex) How to Use Clone this repository. Navigate into one of the version folders (e.g., cd V2_Multi_Condition). Follow the instructions in that folder's specific README.md file to run the script.