After coding for a long time, one inevitably develops a certain “paranoia.”
One is a paranoia for order—unified naming, neat indentation, clean and crisp formatting.
The other is a paranoia for simplicity—the more automated, the better; the more out-of-the-box, the better; the more seamless, the better.
Especially when you’re excitedly trying a new open-source project and hit enter after typing the installation command, what you expect to see is:
- Lines of green progress bars
- An easily understandable “Successfully installed”
Not:
- A screen full of red errors
- A cold, blunt message “Please install XXX system dependency first”
That feeling is like opening a takeout box when you’re starving, only to find—
The restaurant forgot to give you chopsticks. The food is right there, the aroma is wafting, but you just can’t get it into your mouth.
This sense of frustration is a common pain for all developers.
Recently, while maintaining my own open-source project, I was deeply bothered by these “chopsticks.” To thoroughly solve it, I simply… built a new “wheel.”
Today, let’s talk about the story behind it.
The Genesis: gitstats and its Only “Less Smooth” Aspect#
I’ve been maintaining a tool called gitstats, primarily used to generate statistical reports for Git repositories:
- Commit activity
- Contributor ranking
- Project growth trends
- Graphical visualization
It’s open-source, simple, and easy to use—except for one point: It depends on gnuplot.
gnuplot is a very mature plotting tool, commonly found in scientific research and data analysis.
The problem is: it must be installed manually at the system level.
Linux requires apt install;
macOS requires brew install;
Windows… you know, it’s even more troublesome.
This is like the only grain of sand in the process, making the whole experience less smooth.
I started thinking:
Can gnuplot be made into a Python package, installable with a single pip install command?
- No administrator privileges required
- Does not pollute the system environment
- Automatically adapts whether you’re on Linux / Windows / macOS
- Runs as long as Python is available
This way, developers can include gnuplot just like installing any ordinary Python package.
Thus, gnuplot-wheel was Born#
After some research and effort, I finally packaged gnuplot’s binary files into Python wheel files.
From now on, you just need to type:
pip install gnuplot-wheel
- gnuplot’s binary files will be automatically installed into the virtual environment
- No system-level dependencies required
- Will not conflict with already installed gnuplot
- No administrator privileges required
After installation, you can directly execute the gnuplot command—
without installing anything extra.
When I first saw it running smoothly in a clean environment, I had only one thought:
Ah, this is the romance of technology—keeping the complexity for oneself, and simplicity for the user.
Who Will Use This Little Wheel?#
Actually, this wheel isn’t complex, but it’s very practical.
If You Work in Scientific Research or Data Visualization#
You can directly call gnuplot within your Python programs, without bothering with system dependencies.
If You Work in DevOps or Automation#
You can have your scripts automatically render curve plots and trend graphs, without having to manually install gnuplot on every machine.
If You Are Developing Tools That Depend on gnuplot (Like Me)#
You can directly add gnuplot-wheel to your dependencies, making it zero-cost for users to get started.
Currently, gnuplot-wheel supports mainstream platforms and is published on PyPI.
This “Little Wheel” Also Benefited gitstats#
I have already integrated it into gitstats.
Now, the latest version of gitstats no longer requires users to manually install gnuplot.
As long as:
pip install gitstats
It will automatically prepare all dependencies, and users don’t need to care about what’s happening behind the scenes.
This is the most charming aspect of the open-source community:
I built a ‘back scratcher’ to solve my own little pain point, and it turned out it could help others relieve their itching too.
Want to Give It a Try?#
If your project, workflow, or script needs to use gnuplot, why not give it a try? It won’t change the world, but it can make your development process—just a little bit smoother.
Project links:
Feel free to check it out, use it, open an Issue, or even contribute together.
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