<div align="center"><h1> DBCrafter </h1></div> <div align="center"> <a href="#"> <img src="https://img.shields.io/badge/Python-3776AB?logo=python&logoColor=fff" alt="Python Badge" width="100"> <img src="https://img.shields.io/badge/Flask-000000?logo=flask&logoColor=fff" alt="Flask Badge" width="100"> <img src="https://img.shields.io/badge/Pandas-150458?logo=pandas&logoColor=fff" alt="Pandas Badge" width="100"> <img src="https://img.shields.io/badge/Docker-2496ED?logo=docker&logoColor=fff" alt="Docker Badge" width="100"> </a> </div>

DBCrafter is a lightweight web application that generates SQL INSERT statements from CSV files. Users can upload a file, specify the table name, and download an SQL script with the generated commands.

🌟 Features

📄 CSV, Excel & JSON Upload: Upload '.csv', '.xlsx' or '.json' files with the data to enter into the database.
📝 Table Name Selection: User defines the name of the destination table.
⚡ Automatic SQL Generation: Automatically creates 'INSERT INTO' commands based on the file.
💾 SQLite Integration: Inserts data directly into a local 'SQLite' database ('dados.db').
📥 Download SQL Script: Generates a '.sql' file with the insert commands to import into other databases.

🛠 Technologies Used

Python: Core language for backend development.
Flask: Micro web framework for handling routes and HTTP requests.
Pandas: Used for reading and processing CSV files.
HTML & CSS: Frontend user interface.
Docker: For easy application deployment.
SQLite3: Lightweight relational database used to store data locally.

🗃 Local Database (SQLite)

In addition to generating the 'INSERT' commands, the data is also automatically entered into the local 'dados.db' database. This database can be accessed with any SQLite viewer (e.g., DB Browser for SQLite).

Location: 'src/dados.db'

🚀 Getting Started

🔹 Install Dependencies

If running locally (without Docker), install dependencies manually:

pip install flask pandas

🔹 Clone the Repository

git clone https://github.com/ThiagoRosa21/DBCrafter
cd DBCrafter

🏃 Running the Application

🔹 Running Locally (Without Docker)

python src/main.py

🔗 Access the application in your browser:

http://127.0.0.1:5000/

🐳 Running with Docker

🔹 Build the Docker Image

docker build -t insert-builder .

🔹 Run the Docker Container

docker run -d -p 5000:5000 --name DBCrafter-container DBCrafter

🔗 Access the application in your browser:

http://localhost:5000/

🔹 Stop and Remove the Container

docker stop DBCrafter-container
docker rm DBCrafter-container

📂 Project Structure

DBCrafter/
├── src/
│   ├── __pycache__/               # Python cache files
│   ├── templates/                 # HTML templates
│   │   ├── homepage.html          # User interface template
│   ├── main.py                    # Flask main application file
│   ├── views.py                    # Route logic
├── Dockerfile                      # Docker configuration
├── docker-compose.yml               # Docker Compose file
├── README.md                        # Project documentation

📌 Example Usage

📂 Input (CSV, Excel, JSON) <br> csv

id,name,email
1,John Doe,john.doe@example.com
2,Jane Doe,jane.doe@example.com

json

[
  {"id": 1, "name": "Alice", "email": "alice@example.com"},
  {"id": 2, "name": "Bob", "email": "bob@example.com"}
]

📜 Output (SQL)

INSERT INTO clients (id, name, email) VALUES ('1', 'John Doe', 'john.doe@example.com');
INSERT INTO clients (id, name, email) VALUES ('2', 'Jane Doe', 'jane.doe@example.com');

Access the link for this application:

https://dbcrafter.onrender.com/

🤝 Contributing

Pull requests are welcome! Please open an issue first to discuss any major changes.

📝 License

This project is licensed under the MIT License.
📜 See the LICENSE file for more details.

DBCrafter

Install / Use

README