DataQuery

A web app for preview, query, edit and export data files.

DataQuery provides a Streamlit based Web UI and a SQL Engine using DuckDb.

Try it on Streamlit: here.

Features

Load data files of various formats (avro, csv, json, parquet, txt, xlsx, xml)
Files can be loaded also as zip archives. Each file has a Load this file toggle to include or exclude it individually (useful to drop single files from a zip archive). For xlsx files, select which sheets to load and optionally assign custom table aliases. For csv, txt and xlsx files, header, delimiter, quoting settings and table alias can be defined.
Preview data of every file loaded
Get a preview of the data loaded and, if needed, refine data loading settings
Query loaded data in sql language
Join, transform, modify, analyze data in a relational in-memory database
Visual editing of the query results
Edit your data applying changes directly in the table that shows you query result
Export query results on file, in various format (avro, csv, json, parquet, txt, xlsx, xml)
For csv, txt and xlsx file define setting for header, delimiter and quoting settings
Save query results as a session table
After running a query, save its result (including manual edits) as a new named table, reusable in further queries
Save the whole session
Download all session tables as a single ZIP of parquet files. The bundle can be re-uploaded to restore the session

All the tasks are managed in memory, no data are saved on the server.

Install the package:

pip install .

Or install in editable mode for development:

pip install -e .

Run with the console entry point:

dataquery

Or with Streamlit directly:

streamlit run src/dataquery/app.py

This project is licensed under the GNU GPLv3 License. See the LICENSE file for details.