My favorite ping tool is fping, mainly because I can do bash expansion with it eg `fping mail{1..10}` .. very useful and saves me from doing a "for i" one-liner.
This idea is also very useful for host/dig DNS queries which I would also often previously do a one-liner for, but recently had a gpt script me a tool for it:
> It's easy to install if you have pip. (Available at service-ping-sping on PyPi)
Consider rewriting the program in Go, then you’ll have a statically linked binary that’s much easier to install (less dependencies) and will be much faster too.
If that is the objective, there's a few options available; a more pragmatic one is to use a tool that bundles a Python runtime and the application into a single executable, there's a few options there. Rewriting in a different language should always be a last resort given the time investment required.
> Rewriting in a different language should always be a last resort given the time investment required.
Makes no sense. This is a relatively small program that can easily be rewritten by a large large model like ChatGPT, Claude, Gemini, etc. in a day session.
Not here to advise rewriting from scratch but I found myself considering using go/rust/c stuff instead of Python in the last few years. Less headache and more predictable
I would add a link to the gitlab to the page also, clicking the LICENCE brings me to the source code but other than that there did not seem to be a link .
Out of curiosity, did you use LLM's to code this? My gut feeling tells me at minimum the readme was written by one, or maybe it's normal to use emojis everywhere :-) Also I am not meaning to judge it as good or bad, I'm just curious.
I think one thing that LLM's and coding agents enables, is creating these customised solution which solve a specific problem, in a specific way. Some might consider it wasteful. I bet many thinks your effort would have been better spent contributing to one of the existing ones instead of doing yet another tool, but I find fascinating that we can finally tell our computers what we need and the will do it.
If you hand-wrote everything, then apologies for the unrelated rant :-)
Yes, I used LLMs to develop this. I think the README has more emojis than any mortal could summon. Hehe
I used ChatGPT to design the solution that I wanted and Claude Sonnet to do most of the coding.
I'm trying to figure out what works for me in the brave new world of AI enabled development, so that I can make recommendations to my team.
A few things that really helped me here were:
- Having the gitlab cli (glab) installed and configured was very helpful because it allowed me to do things like lint the CI file and inspect the build output in the LLM context.
- Having the zereight/gitlab-mcp installed was useful as well. Even though I can make Issues and MRs using the CLI, the LLM frequently made escaping mistakes when writing long comment sections. The mcp tool was great for this.
- Almost all of my process started with me describing a bug or feature, then asking the LLM to investigate the feature and create an Issue. From there I tried as much as possible to keep the scope of my work small and exclusively tied to an issue branch.
I'm a reasonably good programmer - I've been at it for 30 years. I think there's no question that LLMs expand my "radius of capability." Just like everyone else, I'm trying to figure out the best way to safely maximize this new world of tools.
My favorite ping tool is fping, mainly because I can do bash expansion with it eg `fping mail{1..10}` .. very useful and saves me from doing a "for i" one-liner.
This idea is also very useful for host/dig DNS queries which I would also often previously do a one-liner for, but recently had a gpt script me a tool for it:
https://gist.github.com/jgbrwn/7dd4b262c544f750cb0291161b2ec...
> It's easy to install if you have pip. (Available at service-ping-sping on PyPi)
Consider rewriting the program in Go, then you’ll have a statically linked binary that’s much easier to install (less dependencies) and will be much faster too.
If that is the objective, there's a few options available; a more pragmatic one is to use a tool that bundles a Python runtime and the application into a single executable, there's a few options there. Rewriting in a different language should always be a last resort given the time investment required.
> Rewriting in a different language should always be a last resort given the time investment required.
..or, a refreshing and exciting experience.
> Rewriting in a different language should always be a last resort given the time investment required.
Makes no sense. This is a relatively small program that can easily be rewritten by a large large model like ChatGPT, Claude, Gemini, etc. in a day session.
These days, once you have https://docs.astral.sh/uv/ installed, `uvx --from service-ping-sping sping` is pretty much zero effort to run this software.
Except if you don't like pulling random programs from the internet.
Not here to advise rewriting from scratch but I found myself considering using go/rust/c stuff instead of Python in the last few years. Less headache and more predictable
You're certainly right that statically linked binary is the most optimal expression of this goal. Especially for use in a secure environment.
Alas, this is just a python tool :)
Looks nice.
I would add a link to the gitlab to the page also, clicking the LICENCE brings me to the source code but other than that there did not seem to be a link .
Out of curiosity, did you use LLM's to code this? My gut feeling tells me at minimum the readme was written by one, or maybe it's normal to use emojis everywhere :-) Also I am not meaning to judge it as good or bad, I'm just curious.
I think one thing that LLM's and coding agents enables, is creating these customised solution which solve a specific problem, in a specific way. Some might consider it wasteful. I bet many thinks your effort would have been better spent contributing to one of the existing ones instead of doing yet another tool, but I find fascinating that we can finally tell our computers what we need and the will do it.
If you hand-wrote everything, then apologies for the unrelated rant :-)
Yes, I used LLMs to develop this. I think the README has more emojis than any mortal could summon. Hehe
I used ChatGPT to design the solution that I wanted and Claude Sonnet to do most of the coding.
I'm trying to figure out what works for me in the brave new world of AI enabled development, so that I can make recommendations to my team.
A few things that really helped me here were:
- Having the gitlab cli (glab) installed and configured was very helpful because it allowed me to do things like lint the CI file and inspect the build output in the LLM context.
- Having the zereight/gitlab-mcp installed was useful as well. Even though I can make Issues and MRs using the CLI, the LLM frequently made escaping mistakes when writing long comment sections. The mcp tool was great for this.
- Almost all of my process started with me describing a bug or feature, then asking the LLM to investigate the feature and create an Issue. From there I tried as much as possible to keep the scope of my work small and exclusively tied to an issue branch.
I'm a reasonably good programmer - I've been at it for 30 years. I think there's no question that LLMs expand my "radius of capability." Just like everyone else, I'm trying to figure out the best way to safely maximize this new world of tools.
Just fyi, looks like the shortened command defaults has a bug based on the docs @ https://pypi.org/project/service-ping-sping/
(i.e. # HTTP monitoring with interactive UI sping google.com )
Thank you for reporting this!
Would you mind telling me what environment you found this behavior in, and how you installed the app?
I've been testing in ubuntu containers doing:
Thank you so much!!*EDIT:*
I think this is to do with me not being specific about what version of typer I depend upon... working on it now!
This is now fixed in 0.2.11. Thanks @johnQdeveloper
Yeah it was popos which is basically ubuntu.
pip install service-ping-sping
was how it was installed
Thanks for fixing.
I'm a bit curious why some times like 190ms don't get even slightly highlighted as an outlier when regular traffic is clearly 125+/-5ms
Beautiful and useful at the same time. Love it.
I absolutely love this! What a great tool.
Very nice! We all really need a tool that IT can use to diagnose problems along the path. Like more user friendly nping —tr
mtr is my goto as a network engineer. tracepath and other variants can be useful as well.
Like mtrace/mtr?
FYI: the final summary gets hidden if the graph writes a frame after the summary is output.
That's a great catch! thank you!
Thank you looks super helpful!
thanks~