5 Must-Have Python CLI Tools to Supercharge Your Terminal

Your terminal is more powerful than you think. Python is known for its beginner‑friendliness and versatility, but its rich ecosystem of command‑line tools is often overlooked; these tools can boost the workflow of developers, data enthusiasts, system administrators, and everyday users.

1. httpie — Human‑friendly curl replacement

If you often interact with APIs, httpie transforms raw curl commands into clear, readable HTTP requests, supporting syntax highlighting and formatted JSON responses.

Documentation : https://httpie.io/docs/cli/macos

Installation

pip install httpie

Example

http GET https://api.github.com/users/octocat

Supports native JSON

Intuitive syntax

Built‑in colored output

2. glances — Real‑time system monitoring

Need to check system performance at a glance? glances displays CPU, memory, disk I/O, and network usage in real time.

Documentation : https://github.com/nicolargo/glances

Installation

pip install glances

Example

glances

Cross‑platform support

Web‑based interface available

Server‑client mode for remote monitoring

3. rich‑cli — Beautify terminal output

Whether it's JSON, Markdown, or tracebacks, rich‑cli renders them with colors, formatting, and even charts.

Documentation : https://github.com/Textualize/rich-cli

Installation

pip install rich-cli

Example

To syntax‑highlight a file, run rich followed by the file path; multiple formats are supported.

rich loop.py

Make terminal output more pleasing .

4. howdoi — Get Stack Overflow answers from the terminal

Ever wonder why you keep searching the same Python list‑comprehension syntax? howdoi fetches answers directly from Stack Overflow.

Documentation : https://github.com/gleitz/howdoi

Installation

pip install howdoi

Example

$ howdoi print stack trace python
$ howdoi convert mp4 to animated gif
$ howdoi create tar archive

5. csvkit — Powerful CSV manipulation tools

If you dislike Excel, csvkit offers spreadsheet‑like functionality directly in the command line.

Documentation : https://csvkit.readthedocs.io/en/latest/

Installation

pip install csvkit

Examples

Convert Excel to CSV: in2csv data.xls > data.csv Convert JSON to CSV: in2csv data.json > data.csv Print column names: csvcut -n data.csv Run an SQL query on a CSV file:

csvsql --query "select name from data where age > 30" data.csv > new.csv

Query, explore, and clean CSV files elegantly

Final Thoughts

The command line need not feel cold or intimidating. With the right tools, it becomes a creative space—a playground for productivity.

Whether debugging APIs, managing projects, or simply speeding up copy‑paste tasks, Python’s command‑line ecosystem has you covered.