A TUI pager for exploring and analyzing tabular data from logs, CSV, JSON, and streams with vi-like keybindings.
nless is a terminal user interface (TUI) pager designed for exploring and analyzing tabular data in real-time. It automatically infers structure from piped input, allowing users to filter, sort, pivot, and reshape data without configuration. Built for streaming data like logs and Kubernetes events, it combines the power of a spreadsheet with the efficiency of a command-line tool.
Developers, DevOps engineers, and data analysts who work with streaming or static tabular data in the terminal, such as logs, Kubernetes events, CSV files, and JSON output. It is particularly suited for those who prefer vi-like keybindings and zero-configuration exploration.
Developers choose nless for its zero-configuration approach, automatic format inference, and stream-native design that handles live data updates. Its unique selling point is combining vi-like efficiency with interactive features like pivoting, filtering, and JSON parsing directly in the terminal, without needing to switch tools or write scripts.
A TUI pager with advanced support for tabular data, inferring/swapping delimiters, and real-time event parsing.
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nless automatically infers structure from piped input without manual setup, as emphasized in the README's 'Zero config' philosophy, allowing instant analysis of CSV, JSON, logs, and more.
Built for real-time data with features like tail mode and arrival timestamps, highlighted in the streaming demos, making it ideal for live logs and Kubernetes events.
Offers vi-inspired keybindings for fast navigation and manipulation, catering to Vim users, with additional keymaps and mouse support for flexibility.
Handles diverse data formats including CSV, TSV, JSON, and raw logs via automatic delimiter inference and on-the-fly swapping with the 'D' key, reducing tool-switching overhead.
Requires Python 3.13+ for installation, as stated in the README, which can be a limitation for legacy systems or environments with older Python versions.
Lacks SQL querying and Python expression support, as shown in the alternatives table, making it less capable for complex data transformations compared to VisiData or lnav.
Confined to the terminal without web or GUI options, which may not suit users needing graphical visualizations or remote access via browsers.