Thrilled to discover nbdev from & . It's an attempt to solve a big problem with computational notebooks like Jupyter: you explore problems with a notebook, but usually need to "switch" to a more powerful tool for "real" impls:
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nbdev tries to solve this problem by giving you
- automatically turning notebooks into publishable Python modules
- bidirectional sync with plaintext .py for IDE usage
- fixes for other "real" project needs: tests, continuous integration, documentation export, conflict resolution
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While nbdev seems focused on helping individual developers avoid the "switch" when implementing their own projects, I think layers like this could help solve a big problem with "executable books": the huge barrier for *readers* to build on embedded code to do anything real.
Replying to
The fast.ai docs get at something pretty exciting, then. Like many notebooks, it contains narrative content which explains computational material and lets readers explore. But the executable book is *also* the implementation of a published production-level library
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The narrative in those docs is a bit limited: it's more documentation than prose. "Deep Learning for Coders" is the expository text from the same authors, but it isn't made available in an executable context AFAICT. I think that could be really powerful!
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(For more on these themes and on dreams of executable books, see numinous.productions/ttft/#executab)
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My wishlist for exec. books:
– author did their "real thinking" in the authoring computational environment
– reading environment invites + supports meaningful experimentation/exploration
– book elements transparently and usefully reusable by author and readers in derivative works
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Update: I was wrong; "Deep Learning for Coders" is in fact available in notebook format! Most excellent!
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Replying to @andy_matuschak
The book is in fact available in executable format, for free! :D
github.com/fastai/fastbook
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