whispem

whispem / dprism

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A terminal-native tool that lets you explore, profile, and understand datasets instantly — without leaving your terminal, without spinning up Jupyter, without writing a single line of code. Built with Polars for lightning-fast data processing and Ratatui for a beautiful, responsive TUI.

data-science datascience datasets polars ratatui
14
0
100% credibility
Found Mar 12, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

dprism is a fast terminal application for interactively exploring, profiling, filtering, validating, and comparing tabular datasets like CSV and Parquet files.

How It Works

1
📖 Discover dprism

You hear about a handy tool that lets you quickly peek inside big data files right from your terminal, like a supercharged file viewer for spreadsheets.

2
💻 Set it up

You get the tool ready on your computer so it's always there when you need to check data.

3
📁 Pick a data file

You choose a file like your sales records or customer list to explore.

4
🚀 Launch the explorer

With one simple command, your data loads super fast and a beautiful screen fills with column lists, stats, and previews – it feels magical!

5
🔍 Dive into details

You scroll up and down columns, search by name, switch to see raw data or relationships between numbers, and spot patterns instantly.

6
✂️ Filter and compare

You narrow down rows with easy searches like 'sales over 1000' or check two files side-by-side to see what's changed.

✅ Unlock data insights

You walk away understanding your data's story – missing values, trends, outliers – all in minutes, ready to make decisions.

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Star Growth

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AI-Generated Review

What is dprism?

dprism is a terminal-native app built in Rust that lets you explore, profile, and understand datasets instantly—without leaving your terminal, spinning up Jupyter, or writing code. Load CSV, Parquet, or Arrow files (or pipe from stdin), get column stats, histograms, correlations, and top values in a beautiful Ratatui TUI. Use commands like `dprism explore data.csv` for interactive navigation with vim keys, or `dprism validate` against YAML schemas.

Why is it gaining traction?

It stands out by delivering htop-style interactivity for data with Polars' lightning-fast processing—no heavy IDEs or notebooks needed. Features like inline filtering (`f` key or `--filter "age>30"`), data diffs (`dprism diff`), and JSON stats export hook terminal-first devs tired of context-switching. Keyboard-driven views (profile, preview, corr via Tab/c) make profiling feel native, not bolted-on.

Who should use this?

Data engineers validating ETL outputs via schemas, analysts quick-profiling GB-scale CSVs in SSH sessions, or ML folks spot-checking features without Jupyter overhead. Ideal for CI/CD data quality gates or local dataset triage before deeper analysis.

Verdict

Try it for terminal data workflows—solid docs, MIT license, and production-ready claim make the 11 stars and 1.0% credibility score forgivable for v1.0. Early stage means watch for edge cases on massive files, but cargo install dprism gets you productive fast.

(198 words)

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