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I really enjoy this long and insightful discussion. Let’s see how deep we can go (in terms of the thread tree and thought itself). Declarative constraints driv

I really enjoy this long and insightful discussion. Let’s see how deep we can go (in terms of the thread tree and thought itself). Declarative constraints driven problem solver was pioneered by https://en.m.wikipedia.org/wiki/Sketchpad https://en.m.wikipedia.org/wiki/Sketchpad and also used in places like Apple’s https://en.wikipedia.org/wiki/Interface_Builder https://en.wikipedia.org/wiki/Interface_Builder It is interesting that you use "texture description" for byte stream based artifact that we call code, which is runtime independent. On the other hand, the term "graph" in your second paragraph has double meanings: visual representation for human eye and brain to parse, and mathematical graph that has can be serialized in JSON, XML or whatever byte stream. I think many people are excited about GUI revolution pioneered by Doug Engelbart, Ivan Sutherland and Alan Kay for different reasons. Some people are excited about the implementations: bitmap display, mouse, etc., some people are excited about the principles and abstraction: MVC, constraints, data flow, messaging, etc, etc. With Jupyter notebook system, which is based on three state machines: a persistent kernel process, a DOM session in the browser, and a message queue, it is the first time that we might have a nice abstraction to capture a graph in space and time. That is at least why I am getting excited. The other features are just bells and whistles.

TuringTest 8y ago
Earlier today, I took a note to myself saying this: The next-generation development environment will be a combination of: * a wiki (outlining content + version control), * a spreadsheet (functional reactive coding + lightweight schema definition + easy working on collections), and * a mockup wireframe builder (visual layout + visual state machines + rapid prototyping). Pluggable connectors to constraint solvers and machine learning would be a plus. I'm not sure that Jupyter fully captures all parts of the computation graph; most of all, restoring a previous state after closing and reopening it is cumbersome (if I'm not mistaken you need to run each individual cell by hand in the right order). There are theoretical models that could fix that, though, like those allowing for time travel debugging. And the visuals are simple and flexible enough to support many use cases. So yes, web notebooks are a good basis for a knowledge-building programmable platform.
- ontouchstart 8y ago
  Jupyter system has three different subsystems that communicate via message passing: browser state, ZeroMQ and kernel process. Each system has its own leaky abstraction. That is why the version controls and time travel debugging in the traditional sense become impossible. We shoud embrace this challenge and think beyond document based IDEs. For example, you can think of rendered notebooks as caching. I have even played with the concept of using rendered notebook as the input/data source of another notebook. This looks like a radical idea. But it is exactly how https://nbviewer.jupyter.org/ https://nbviewer.jupyter.org/ works.
  - TuringTest 8y ago
    > the concept of using rendered notebook as the input/data source of another notebook Isn't that essentially what a spreadsheet does? Each table contains the results of a previous computation, intertwined with input and configuration data, and you just keep chaining more and more programs through a single unifying metaphor (the cell coordinate system plus function expressions). This model also gets you reactive recomputation for free. It's a powerful system, but quite old; I'd say the only radical thing is convincing classic developers that there's a better model than their beloved imperative, one-step-at-a-time idea of what running a program means.
    - ontouchstart 8y ago
      Not exactly the same model as spreadsheets. In spreadsheets, a cell is a value in memory. The sheet is a graph of states. In Jupyter Notebook, the cells are nothing but messages. And the saved notebook files are JSON serialized byte stream of the message and metadata. It doesn’t keep the states, just data, a digital artifact.
      - TuringTest 8y ago
        Yet spreadsheet cells may also be formulas, which are akin to method calls / message passing / function application. The value of a cell with a formula is the memoized result of its latest function call execution. I don't see an essential difference with a notebook cell, other than the layout - grid vs linear. (Although I might be missing something; I don't have broad experience with Jupyter's computation model). Plus, spreadsheets may also be distributed.

TuringTest 8y ago

Earlier today, I took a note to myself saying this: The next-generation development environment will be a combination of: * a wiki (outlining content + version control), * a spreadsheet (functional reactive coding + lightweight schema definition + easy working on collections), and * a mockup wireframe builder (visual layout + visual state machines + rapid prototyping). Pluggable connectors to constraint solvers and machine learning would be a plus. I'm not sure that Jupyter fully captures all parts of the computation graph; most of all, restoring a previous state after closing and reopening it is cumbersome (if I'm not mistaken you need to run each individual cell by hand in the right order). There are theoretical models that could fix that, though, like those allowing for time travel debugging. And the visuals are simple and flexible enough to support many use cases. So yes, web notebooks are a good basis for a knowledge-building programmable platform.

ontouchstart 8y ago
Jupyter system has three different subsystems that communicate via message passing: browser state, ZeroMQ and kernel process. Each system has its own leaky abstraction. That is why the version controls and time travel debugging in the traditional sense become impossible. We shoud embrace this challenge and think beyond document based IDEs. For example, you can think of rendered notebooks as caching. I have even played with the concept of using rendered notebook as the input/data source of another notebook. This looks like a radical idea. But it is exactly how https://nbviewer.jupyter.org/ https://nbviewer.jupyter.org/ works.
- TuringTest 8y ago
  > the concept of using rendered notebook as the input/data source of another notebook Isn't that essentially what a spreadsheet does? Each table contains the results of a previous computation, intertwined with input and configuration data, and you just keep chaining more and more programs through a single unifying metaphor (the cell coordinate system plus function expressions). This model also gets you reactive recomputation for free. It's a powerful system, but quite old; I'd say the only radical thing is convincing classic developers that there's a better model than their beloved imperative, one-step-at-a-time idea of what running a program means.
  - ontouchstart 8y ago
    Not exactly the same model as spreadsheets. In spreadsheets, a cell is a value in memory. The sheet is a graph of states. In Jupyter Notebook, the cells are nothing but messages. And the saved notebook files are JSON serialized byte stream of the message and metadata. It doesn’t keep the states, just data, a digital artifact.
    - TuringTest 8y ago
      Yet spreadsheet cells may also be formulas, which are akin to method calls / message passing / function application. The value of a cell with a formula is the memoized result of its latest function call execution. I don't see an essential difference with a notebook cell, other than the layout - grid vs linear. (Although I might be missing something; I don't have broad experience with Jupyter's computation model). Plus, spreadsheets may also be distributed.