One install. 260 tools. Zero dependencies.
$ pip install evolver-tools
Python 3.8+ | Linux / macOS / Windows | ~2MB
1
Explore your data
You have a CSV with 15 orders. What's in it? One command tells you everything — column types, distributions, correlations.
$ evtool csv-stats orders.csv
File: orders.csv | Rows: 15 | Columns: 8
order_id (int) Mean: 1,008 Min: 1,001 Max: 1,015
product (text) 15 unique values
category (text) Electronics(8) Home Office(7)
quantity (int) Mean: 4.53 Min: 1 Max: 15
unit_price (float) Mean: ¥117.66 Min: ¥9.99 Max: ¥399.99
total (float) Mean: ¥329.29 Min: ¥89.97 Max: ¥999.96
date (text) 14 unique dates
region (text) North(5) South(4) East(3) West(3)
Correlation Matrix
unit_price × total +0.82 ████████████░░░
order_id × total +0.59 ████████░░░░░░░
quantity × unit_price −0.48 ███████░░░░░░░░
💡 One command, full picture. csv-stats infers types, computes histograms, and shows correlations — no pandas, no Jupyter, no setup.
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2
Visualize with a bar chart
Who's buying the most? Total sales by region, right in your terminal.
$ evtool chart-cli bar "North:1499.88,South:1409.86,East:389.74,West:839.91" --sort
条形图 (垂直)
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Nor Sou Wes Eas
1499.9 1409.9 839.9 389.7
North leads with ¥1,499.88. South is close behind. East is under ¥400 — maybe a growth opportunity?
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3
Drill deeper with filters
Filter to high-value orders only — anything over ¥500. Then sort by total descending.
$ evtool csv-filter orders.csv --where 'total > 500' | evtool csv-sort --by total --desc
order_id,product,category,quantity,unit_price,total,date,region
1015,Noise Cancelling Headphones,Electronics,4,249.99,999.96,2025-02-12,South
1011,Ergonomic Chair,Home Office,2,399.99,799.98,2025-02-03,North
1014,Standing Desk Converter,Home Office,2,299.99,599.98,2025-02-10,North
1013,Docking Station,Electronics,3,149.99,449.97,2025-02-08,West
🔗 Pipe-friendly. Every tool reads from stdin and writes to stdout. Chain them like Unix pipes.
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4
Export to JSON & report
Convert the filtered result to JSON for your app, and generate a formatted report.
$ evtool csv2json orders.csv --pretty
[
{ "order_id": 1001, "product": "Wireless Mouse", "total": 89.97, ... },
{ "order_id": 1002, "product": "USB-C Hub", "total": 90.00, ... },
...
]
$ evtool csv-pretty orders.csv
┌──────────┬──────────────────────────┬──────────────┬─────────┐
│ order_id │ product │ category │ total │
├──────────┼──────────────────────────┼──────────────┼─────────┤
│ 1001 │ Wireless Mouse │ Electronics │ 89.97 │
│ 1002 │ USB-C Hub │ Electronics │ 90.00 │
│ 1003 │ Desk Lamp │ Home Office │ 89.99 │
│ ... │ ... │ ... │ ... │
│ 1015 │ Noise Cancelling Headph. │ Electronics │ 999.96 │
└──────────┴──────────────────────────┴──────────────┴─────────┘
★
Bonus: Find the right tool
Forgot a tool name? Fuzzy-search all 260 tools by name or description.
$ evtool search json
18 matching tools:
● json2csv JSON to CSV converter with nested key flattening
● json2yaml Convert JSON to YAML
● json-merge Deep-merge multiple JSON files
● json-pretty Pretty-print JSON with syntax highlighting
● json-schema JSON Schema validator
● json-sort Sort JSON keys alphabetically
● json-stats JSON structure analysis
● json-validate Validate JSON file format
● json2env Convert JSON to .env format
● ... and 9 more
🔍 evtool search <keyword> — instantly finds tools across all 260 commands. Try "csv", "net", "crypto", "git", "text".
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The whole pipeline in one line
From raw CSV to filtered, sorted, visualized output — one chained command:
$ evtool csv-stats orders.csv && \
evtool csv-filter orders.csv --where 'total > 100' | \
evtool csv-sort --by total --desc | \
evtool csv-pretty
That's 4 tools, 1 pipeline, zero imports, zero config, zero dependencies.