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At semantic level, coding is still about creating objects and managing their relationships with the environment. An .ipynb file itself just an object tree. Sinc

At semantic level, coding is still about creating objects and managing their relationships with the environment. An .ipynb file itself just an object tree. Since Jupyter people made the wise decision of using easy to parse JSON format instead of more efficient binary format, the platform is opened up to a big ecosystem that people can make tools for specific need. Like the document centric desktop application revolution in the 80s that gave us MS Office and Adobe Photoshop, the open, data centric web application revolution we are seeing in this decade will fundamentally change how we consume and produce software. It is a natural evolution of computing system production from hardware panels to punch card, to text code instructions to object graph management in network environments. (The buzzword is “the cloud”.)

TuringTest 8y ago
Yeah, you're right that coding is creating computational objects. I was pointing out that "coding" is traditionally understood to refer only to the sequences of instructions in source and object code that remains unmodified during runtime execution, but there are other views that extend the definition to all the other objects involved in running the software in its environment. In this view, coding is about defining automated behaviors that can execute on their own without a human leading by hand every step. I'm thinking in particular about End-User Development approaches, which allow non-developers to create such automations without ever learning the syntax of a formal language. Under this approach, the abstraction level may be lower, since the actual instances of data used are as important to understanding the system as the code that processes them.
- ontouchstart 8y ago
  Another type of coding is describing the desired state and let the runtime environment achieve the transition. Unix Makefile is one of the early examples. So are HTML/CSS etc. More recent examples are dataflow graph in tensorflow https://www.tensorflow.org/guide/graphs https://www.tensorflow.org/guide/graphs and kubernetes https://github.com/kubernetes/kubernetes/blob/release-1.3/docs/design/README.md https://github.com/kubernetes/kubernetes/blob/release-1.3/do... A new idea just occurred to me during a technical lunch meeting with a bunch of friends today: since Jupyter Notebook itself is nothing but a object graph, it might be possible to use a "computed" .ipynb for this kind of "coding", i.e., describing desired state. That would be TDD in another sense.
  - TuringTest 8y ago
    Yeah, I happen to work with declarative statements + problem solver for a living :-) In this context, a precise textual description helps to exactly define what you want to achieve, but a graphical view helps to inspect how many different cases are there in your data, and how available context are connected. Representing state machines with graphs is a relatively common thing in rapid prototyping apps, so I've thinking of building a prototyping app that would also allow embedding real code and data in them (similar to Visual GUI builders, but allowing much more code to be defined visually). There are several tools attempting to achieve that, but all fail at the abstraction problem of defining new instances for your objects (i.e. you can't create new instances of arbitrary visually defined objects, only for things in tables).
    - ontouchstart 8y ago
      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

TuringTest 8y ago

Yeah, you're right that coding is creating computational objects. I was pointing out that "coding" is traditionally understood to refer only to the sequences of instructions in source and object code that remains unmodified during runtime execution, but there are other views that extend the definition to all the other objects involved in running the software in its environment. In this view, coding is about defining automated behaviors that can execute on their own without a human leading by hand every step. I'm thinking in particular about End-User Development approaches, which allow non-developers to create such automations without ever learning the syntax of a formal language. Under this approach, the abstraction level may be lower, since the actual instances of data used are as important to understanding the system as the code that processes them.

ontouchstart 8y ago
Another type of coding is describing the desired state and let the runtime environment achieve the transition. Unix Makefile is one of the early examples. So are HTML/CSS etc. More recent examples are dataflow graph in tensorflow https://www.tensorflow.org/guide/graphs https://www.tensorflow.org/guide/graphs and kubernetes https://github.com/kubernetes/kubernetes/blob/release-1.3/docs/design/README.md https://github.com/kubernetes/kubernetes/blob/release-1.3/do... A new idea just occurred to me during a technical lunch meeting with a bunch of friends today: since Jupyter Notebook itself is nothing but a object graph, it might be possible to use a "computed" .ipynb for this kind of "coding", i.e., describing desired state. That would be TDD in another sense.
- TuringTest 8y ago
  Yeah, I happen to work with declarative statements + problem solver for a living :-) In this context, a precise textual description helps to exactly define what you want to achieve, but a graphical view helps to inspect how many different cases are there in your data, and how available context are connected. Representing state machines with graphs is a relatively common thing in rapid prototyping apps, so I've thinking of building a prototyping app that would also allow embedding real code and data in them (similar to Visual GUI builders, but allowing much more code to be defined visually). There are several tools attempting to achieve that, but all fail at the abstraction problem of defining new instances for your objects (i.e. you can't create new instances of arbitrary visually defined objects, only for things in tables).
  - ontouchstart 8y ago
    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