Quick tool to browse and view data files (json,csv,parquet,more) on local disk and s3
Project description
databrowser
A terminal file browser for quickly viewing data files, from local disk or S3.
Supports csv, tsv, parquet, feather, orc, json, xlsx, xls, xml and html — read into pandas DataFrames and shown in a scrollable table (with a dtype view). Built on Textual.
Originally based on the example code_browser from Textual.
install
Run without installing (uvx)
With uv, run it in a throwaway environment — no install needed:
uvx databrowser [path]
uvx databrowser s3://bucket/dir/
uvx databrowser hf://datasets/org/name
For Google Cloud Storage or Azure, pull in the matching extra:
uvx --from 'databrowser[gcs]' databrowser gs://bucket/dir/
uvx --from 'databrowser[azure]' databrowser az://container/dir/
Install from PyPI
The package is published on pypi https://pypi.org/project/databrowser/
run pip install databrowser (pip install databrowser --upgrade to get latest version).
Then just execute databrowser. The gcs / azure / all extras add those cloud backends.
Build
This project uses uv (Python >= 3.13).
Execute uv sync to create the virtual env and install the package and its dependencies.
Run uv run databrowser to execute in the virtual env
(or uv run python src/databrowser/data_browser.py).
Usage
databrowser [optional path] (defaults to the current directory)
Remote filesystems
Any fsspec URL works, not just local paths:
databrowser s3://bucket/path/— S3 (uses the default AWS credentials in the environment)databrowser hf://datasets/org/name— Hugging Face datasets (setHF_TOKENfor private ones)databrowser gs://bucket/path/— Google Cloud Storage (needsgcsfsinstalled)
The protocol is resolved automatically, so the same browsing works for every backend.
Select a data file to view
-
press F to hide the filebrowser
-
press D to show the dtypes
-
press S to save a screenshot in svg
-
press Q to quit
By default the preview shows the first 100 rows. Set DATABROWSER_ROWS to change it,
e.g. DATABROWSER_ROWS=500 databrowser data/ (or pass --rows 500).
Run databrowser --help for all options.
examples
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