For those with more experience, is it still relevant? Can the same be accomplished with python and jupyter notebooks?
The idea of Glamorous Toolkit is that it’s a collection of tools you use to solve software problems by making little explanatory tools. You might start out with some bigger problem like “I need to make this service fast”, come up with a question like “what does the flow of data I care about look like through the service?” and then try to answer that question by making tools that could analyze/visualize logging output or a stack trace or whatever makes sense in your software’s context.
The technique of “making little tools that explain to help answer a question” is Moldable Development, similar to how Test Driven Development is “make a failing big feature test loop, write little tests and make them pass until the big one passes”.
You can make little tools to explain away questions you have while you’re working with plugins or shell scripts or whatever you’re comfortable with and that’s “Moldable Development”. The Glamorous Toolkit just happens to be a nice system of tools that make it easy to make more little tools to help explain away problems.
Hope that helps! Lmk if you want to see some examples.
Source and bias: I worked closely with the developers before I had to take a break from work and computer stuff.
So I'm a believer in the principles. But I'm also curious about throwaway743950's question. What are the things in the Glamorous Toolkit that concretely make it better for this style of programming than traditional tools? You say "[it] just happens to be a nice system of tools that make it easy to make more little tools", but that's got to be downplaying it. Switching environments is an agonizingly costly thing to do. What rewards await those who make the jump? Rubies? Emeralds? Custom views-with-nested-sub-custom-views? Curious (but not yet won over) readers want to know.
This means your tools and visualizations are just a specific context-specific view of your objects. Meaning you aren't limited in how these tools can interact with said objects, because you are never working with static data, it's always with the actual objects.
It's hard to put into words, but it's similar to the difference between println debugging and a lisp repl or smalltalk debugger. They technically do the same thing but the actual implementation of them makes a world of difference.
Because if it wasn't for the fact the graphical stack was implemented as smalltalk objects, you couldn't build tools like the driller or debugger since they would have to be implemented as a secondary piece of software that loses the original context.
Like for example, I built a custom tool for myself when I was working on this p2p network and had a section of the codebase with some non obvious control flow, since it was handling multiple different p2p networks at the same time. Normally this is where you include a diagram in the docs, but in about an hour I built a custom code editor for the class, that visualized all the control flow and explained the cases in a flow diagram by simply introspecting on the methods defined in the class. And this tool never fell out of sync like a static diagram, since it wasn't hardcoded by me. And from that point on, I worked within this tool whenever hanlding anything related to this.
And fwiw, the python story is pretty seamless from my usage of it a few months ago. I was able to integrate and use python libraries into this project without much hassle.
Also, GT is now also a distributed Smalltalk system, too. We use it in productive settings to compute large jobs on large data sets :)
It feels so open ended that I wouldn’t know where to start. And I’ve actually spent several hours exploring Glamorous Toolkit!
There are quite a number of videos and explanations now, but we are still struggling to package them in a way that seems more approachable.
We would need help with this. If you are interested, I would offer to have a session with you that we record and in which we go through your questions and I provide live explanations. Join us on Discord and we take it from there: https://discord.gg/FTJr9gP
Or look at: https://book.gtoolkit.com/working-with-the-postgresql-relati... (in the environment you can load the code which comes with live documentation)
Normal documentation pages on a website would be a good place to start. Don't bury them in a tool I have to download and fumble through
The documentation is available online at book.gtoolkit.com (linked from the menu of gtoolkit.com). Would you see ways to improve that visibility?
When consumed in the environment, that book contains live snippets that can be explored.
We already have industry standards for doing this. Why would I want to build some micro-tool/throw-away code to do what another tool does much better and battle tested?
2. All the tools work together
3. All the tools are tracked in a central repository
I can achieve the same with unix philosophy, using the tools and languages I already know.
Indeed, it is possible to build tools elsewhere. The question is: do you build them, and if yes, when?
What we show with GT is that it is possible to build such tools for every development problem. This leads to thousands of micro tools per system that should co-exist.
GT is not a large tool to rule them all. In the Unix analogy, it is Unix, not one of the tools :).
This still leaves the question of why would want to build those tools when there are standard tools already? Because systems are highly contextual. This means we can predict classes of problems but not specific ones, which then means that any clicking tool built before the problem is known will not be addressing the specificity of that problem.
This is actually not that new of an idea. Testing is already done like that. We do not download tests from the web and run them on our system. We develop them as part of development after we know the problem. It's that contextualization that makes us stop every time a single test fails as we know that each of them captures something that our system specifically cares about.
Now, a test is a tool. We can extend the same idea to any other tool.
Does this address the question?
Being married to a specific tool like GT is limiting. GT doesn't work with most industry languages _today_, even though _in theory_ it could. It's written and scripted in a language few use, which makes it unapproachable
More seriously, thank you for sparring with me.
GT is free and open-source. It's extensive. It comes with documentation, too. We even document the practices and the process, too. With public case studies. With peered reviewed publications. And we even bet our own livelihood that it works for tackling hard problems in significant systems that others cannot tackle.
So, yes, we are not just claiming that the problem exists. We have seen it validated first-hand over a large period of time (15+ years) so we are reporting on it :).
This experience points to the idea that decreasing the cost of creating a tool is much more important than the tools that exist out of the box.
Regarding the support for other languages, it's true that we only have analysis support for a couple of dozen languages. But creating the support for a new one is often measured in days. For example, it took a couple of weeks to add COBOL to the set. I challenge you to find even one properly working open-source parser (we looked and could not really found one). In GT you can find a whole free and open-source infrastructure :).
GT is certainly not a panacea. It's a documentation of how the approach can work. I am not aware of any other environment in which tools can be built in minutes and in which thousands of them practically co-exists. If this appeals to people, and it does appeal to some, now they have a vehicle to practice with. And for those that choose to not do that, that's Ok as well :).
4. New contextual tools can be built inexpensively :)
I think the idea is good, but it's a tough sell for working programmers because the whole culture of it is so foreign. I think there's a version of GT that would do well if it described itself in terms of paradigms working coders know (POSIX, IDEs, blub-y languages, text files) instead of in terms of SmallTalk. Maybe something nearly as cool can be done as a VSCode plugin? I personally think of it as kind of a supercharged Emacs for SmallTalkers.
The first goal was to help us explore how far can the idea of contextual tools go. It helped discover what today we call Moldable Development. It is also the first extensive case study of Moldable Development, itself offering 5+K contextual tools that we used to develop the environment itself. And when we work on a system, we build thousands more.
That said, now that we know what Moldable Development is, it can be copied. We want people to copy it. Our worry though is that we want people to copy everything, not only the visible parts.
For example, I understand the Emacs parallel. But think of this: while Emacs can be extended, how many extensions do you actually use that are specific to your system? We literally use thousands. Per system. That quantitative difference leads to a qualitative difference and it's made possible because of the totality of the environment.
So are there plans to copy GT/moldable development somewhere outside of Pharo/Smalltalk?
In the meantime, consider GT as an extensive blueprint of what's possible. If there is one thing we learnt is that the technology is the smallest investment. The real investment is in learning how to exploit the idea of contextual tools for solving hard problems. That's what takes the longest, but the difference to how those problems are approached today can be measured in orders of magnitude.