dataview-tui 0.1.0

Keyboard-driven TUI for browsing columnar data files.

dataview-tui

dataview-tui is a keyboard-driven terminal UI for inspecting columnar data files. The command line entry point is dview.

The project supports Parquet, ORC, Avro, and optional Lance datasets. It is built for quickly moving between schema, data preview, metadata, and SQL query views without leaving the terminal.

Features

• Textual-based terminal application with a project-specific dark theme.
• Automatic format detection by extension and magic bytes.
• PyArrow-backed Parquet and ORC readers.
• fastavro-backed Avro reader.
• Optional Lance reader via the lance extra.
• Schema, Data, Metadata, and SQL sidebar views.
• Schema tree entries include field type and nullable state.
• Metadata view includes file info, row groups/fragments/blocks, and per-column details.
• DuckDB SQL engine exposing the opened file as data and t.
• CLI entry points: dview and dataview.

Installation

pipx install dataview-tui
dview --version

For Lance datasets:

pipx install "dataview-tui[lance]"

To update an existing install:

pipx upgrade dataview-tui

To install the current main branch from source:

pipx install git+https://github.com/lyne7-sc/dataview-tui.git

Quick Start

Open supported files or datasets:

dview path/to/file.parquet
dview path/to/file.orc
dview path/to/file.avro
dview path/to/dataset.lance

Choose an initial tab:

dview path/to/file.parquet --tab data

Keyboard

Key	Action
q	Quit
1 / 2 / 3	Show Schema / Data / Metadata tab
] / [	Next page / previous page
Ctrl+F	Filter columns by regex
/	Search cell contents
n / Shift+N	Next / previous match
Enter	Show full current cell value
s	Toggle SQL sidebar
Ctrl+Enter / Ctrl+J / F5	Run SQL

SQL

The SQL engine exposes the opened file as DuckDB views named data and t:

SELECT * FROM data LIMIT 20;
SELECT count(*) FROM t;

Query results are capped by the engine to keep the terminal responsive.

Terminal Setup

The app cannot force a terminal font. For a clearer table and SQL experience, use a monospaced font with readable punctuation and digits, such as JetBrains Mono or Maple Mono.

Development

Install dependencies and run checks:

uv sync --extra dev
uv run pytest -q
uv run ruff check .
uv build

Project layout:

src/dataview/
  app.py
  cli.py
  readers/
  widgets/
tests/

Publishing

Releases are built by GitHub Actions when a GitHub Release is published. PyPI publishing uses PyPI Trusted Publishing, so the PyPI project must be configured with this repository and .github/workflows/release.yml before publishing a release.

Dependencies

Runtime:

• pyarrow>=12
• textual>=0.40
• fastavro>=1.9
• duckdb>=0.9
• tree-sitter>=0.25
• tree-sitter-sql>=0.3.11

Optional:

• pylance>=0.20 via the lance extra

Development:

• pytest
• pytest-asyncio
• ruff

License

MIT