https://github.com/sankethsj/py-etl
A simple ETL tool that allows users to upload an Excel or CSV file, preview the data, analyze it, and load it into a PostgreSQL database.
https://github.com/sankethsj/py-etl
etl python streamlit
Last synced: 2 months ago
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A simple ETL tool that allows users to upload an Excel or CSV file, preview the data, analyze it, and load it into a PostgreSQL database.
- Host: GitHub
- URL: https://github.com/sankethsj/py-etl
- Owner: sankethsj
- License: mit
- Created: 2025-03-15T11:01:18.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2025-03-15T11:08:16.000Z (over 1 year ago)
- Last Synced: 2025-06-15T22:06:46.207Z (about 1 year ago)
- Topics: etl, python, streamlit
- Language: Python
- Homepage:
- Size: 3.91 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Py-ETL
Py-ETL is a simple ETL (Extract, Transform, Load) tool that allows users to upload an Excel or CSV file, preview the data, analyze it, and load it into a PostgreSQL database.
## Features
- Upload Excel or CSV files
- Preview the uploaded data
- Analyze the data (missing values, basic statistics)
- Connect to a PostgreSQL database
- Select schema and table from the database
- Load data into the selected table
## Installation
1. Clone the repository:
```sh
git clone https://github.com/sankethsj/py-etl.git
cd py-etl
```
2. Create a virtual environment and activate it:
```sh
python -m venv venv
source venv/bin/activate # On Windows use `venv\Scripts\activate`
```
3. Install the required packages:
```sh
pip install -r requirements.txt
```
## Usage
1. Run the Streamlit app:
```sh
streamlit run app.py
```
2. Open your web browser and go to `http://localhost:8501`.
3. Follow the steps in the app:
- Upload an Excel or CSV file.
- Preview and analyze the data.
- Enter the database connection details and connect to the database.
- Select the schema and table.
- Load the data into the selected table.
## Contributing
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Acknowledgements
- [Streamlit](https://streamlit.io/)
- [Pandas](https://pandas.pydata.org/)
- [SQLAlchemy](https://www.sqlalchemy.org/)