shshemi/tabiew

A lightweight TUI application to view and query tabular data files, such as CSV, TSV, and parquet.

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Summary Information

Updated 2 hours ago
Added to GitGenius on September 22nd, 2026
Created on April 27th, 2024
Open Issues & Pull Requests: 17 (+0)
GitHub issues: Enabled
Number of forks: 93
Total Stargazers: 3,121 (+0)
Total Subscribers: 11 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 20.9 hours
Mean response time: 11.6 days
90th percentile: 30.3 days
Tracked items: 83

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Issue Activity (beta)

Open issues: 14
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 161 days
Stale 30+ days: 11
Stale 90+ days: 6

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • feature request (16)
  • bug (8)
  • distribution (3)

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Detailed Description

Tabiew is a lightweight terminal user interface application for viewing and querying tabular data files in formats including CSV, TSV, Parquet, JSON, Arrow, SQLite, Excel, and others.

The tool addresses the need to quickly inspect and analyze structured data without leaving the terminal. It automatically detects file formats based on extension and allows users to execute SQL queries directly against loaded data. The interface uses Vim-style keybindings for navigation and supports fuzzy search across table contents. Users can work with multiple tables simultaneously and visualize data through built-in plotting capabilities.

Tabiew suits developers and data analysts who work frequently with tabular datasets and prefer command-line workflows. It is particularly valuable for rapid data exploration and validation before processing in larger pipelines, with a preview mode that loads only the first rows of large files for schema inspection. The tool's broad format support makes it useful across different data sources without requiring format conversion. The extensive theme library with over four hundred options allows customization of the visual environment.

The project maintains active engagement with community feedback, having evolved from a simple CSV viewer into a feature-rich application. Documentation is organized in a dedicated wiki covering feature explanations and usage best practices. Installation is available through multiple channels including package managers for Linux distributions, Homebrew for macOS, and direct compilation from source with Rust.