sicmutils
nbdev
sicmutils | nbdev | |
---|---|---|
13 | 45 | |
750 | 4,744 | |
0.0% | 0.6% | |
0.0 | 6.5 | |
about 1 year ago | 4 days ago | |
Clojure | Jupyter Notebook | |
GNU General Public License v3.0 only | Apache License 2.0 |
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sicmutils
- Sicmutils: Computer Algebra, Physics and Differential Geometry in Clojure
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mentat-collective/emmy: The Emmy Computer Algebra System.
They seem to be in the middle of transitioning from the old repo.
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Ask HN: What Is the SICP of Physics?
There are some good resources here including some nicely formatted HTML versions of the book: https://github.com/sicmutils/sicmutils/wiki/SICM-and-FDG-Lea...
^ The Github repo contains a Clojure version of the Scheme library used by the book.
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Space Math
If you want to try this out, give the sicmutils Computer Algebra System a go (I’m the maintainer). Repo lives here: https://github.com/sicmutils/sicmutils
The library works in the browser as well, so interactive TeX rendering from Clojure symbolic expressions and functions is available at the quickstart page here: https://nextjournal.com/try/samritchie/sicmutils
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Math notation library for CojureScript
I am the maintainer of the "sicmutils" computer algebra system in Clojure, and I think that you'll find it very nice for your project: https://github.com/sicmutils/sicmutils
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A, perhaps, naive question on (Common) Lisp
https://github.com/sicmutils/sicmutils is a really interesting development in the direction(s) you stated in b. Since terms can be rendered in various ways (latex, js, etc.), they can be embedded in documents, web pages, etc. You can go from symbolic expressions to animated dynamic systems with relevant formulae.
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Literate programming is much more than just commenting code
- multiple stories about the same piece of code, but all with the ability to IMPORT the story as a library
I've been writing sicmutils[0] as a "literate library"; see the automatic differentiation implementation as an example[1].
A talk I gave yesterday at ELS demos a much more powerful host that uses Nextjournal's Clerk to power physics animations, TeX rendering etc, but all derived from a piece of Clojure source that you can pull in as a library, ignoring all of these presentation effects.
Code should perform itself, and it would be great if when people thought "LP" they imagined the full range of media through which that performance could happen.
[0] sicmutils: https://github.com/sicmutils/sicmutils
[1] autodiff namespace: https://github.com/sicmutils/sicmutils/blob/main/src/sicmuti...
[2] Talk code: https://github.com/sritchie/programming-2022
[3] Clerk: https://github.com/nextjournal/clerk
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Physics in Clojure: Elliptical Paths
Hey, so fun to see this here! These demos feature work from https://github.com/sicmutils/sicmutils and the newly maintained-by-me Mathbox library.
I’m around and happy to answer any questions about the library, future plans, etc.
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Neural network capable of solving university-level Mathematics problems at scale
Give my SICMUtils computer algebra system a look as well, if you like Lisp / Clojure: https://github.com/sicmutils/sicmutils
Works on the web too, which is a big boost for sharing work.
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MIT Scheme on Apple Silicon
It is good enough! Almost all code forms from the book live in the tests (see the FDG directory[0], for example), and there are a few nice environments like Nextjournal[1] where everything from the books works in the browser.
The Clojure port is quite fast, faster than the original for all benchmarks GJS has sent me, and more fleshed out. (That will change, as I've been pushing bugfixes and performance improvements back upstream as I go, as a meager gift to GJS for making this huge, amazing library in the first place.)
I actually wrote to GJS this morning asking for instructions on how to compile the original "scmutils", since I have the same problem. He responded saying he'll get back to me this afternoon, so I'll post here once I have details.
If you are still interested in getting the books going with MIT-Scheme, I put a decent amount of work into the exercises using the original codebase here[2], including a dockerized version of mit-scheme[3] and the scmutils package[4] that might be useful.
- [0] https://github.com/sicmutils/sicmutils/tree/main/test/sicmut...
- [1] https://nextjournal.com/try/samritchie/sicmutils/
- [2] https://github.com/sicmutils/sicm-exercises
- [3] https://hub.docker.com/r/sritchie/mit-scheme
- [4] https://hub.docker.com/r/sritchie/mechanics
nbdev
- The Jupyter+Git problem is now solved
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What is literate programming used for?
One example I've seen is ML/DL folks using jupyter notebooks to develop DL libraries in jupyter notebooks, see https://github.com/fastai/nbdev
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GitHub Accelerator: our first cohort and what's next
- https://github.com/fastai/nbdev: Increase developer productivity by 10x with a new exploratory programming workflow.
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Startups are in first batch of GitHub OS Accelerator
9. Nbdev: Boost developer productivity with an exploratory programming workflow - https://nbdev.fast.ai/
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Start learning python for a Statistician with SAS experience and little R experience
See if you like nbdev way of working with data through python and jupyter. nbdev is an optional part that will create python packages from jupyter notebooks. Also even the simple tutorials are opinionated and will guide you to unit test your code and write CICD pipelines.
- FastKafka - free open source python lib for building Kafka-based services
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isn't this just too much for a take home assignment?
You probably don’t have time for this for the purposes of your task, but I will also throw in the recommendation of nbdev especially if you’re a Python person. I haven’t had a project to use it on yet, but I’ve gone through the docs and the walkthrough and it seems like a great framework for starting potential projects with all the infrastructure needed for if/when they eventually get big and need all the packaging and stuff
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Any experience dealing with a non-technical manager?
nbdev: jupyter notebooks -> python package
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Resources to bridge the gap between jupyter notebooks and regular python development
Take a look at https://github.com/fastai/nbdev - haven't used it but supposedly the whole if fast.ai library was written that way. It sounds like a natural direction in your scenario - allowing your to keep working in a familiar environment and still producing production ready code (will, at least in paper 😅)
- Rant: Jupyter notebooks are trash.
What are some alternatives?
sicm-scheme-exercises - Exercises and notes on Structure and Interpretation of Classical Mechanics.
papermill - 📚 Parameterize, execute, and analyze notebooks
clerk - ⚡️ Moldable Live Programming for Clojure
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
ChezScheme - Chez Scheme
dbt - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications. [Moved to: https://github.com/dbt-labs/dbt-core]
clj-maxima - Maxima as a clojure library
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
programming-2022 - Talks at the <Programming> 2022 Conference in Porto, Portugal
rr - Record and Replay Framework
Algebird - Abstract Algebra for Scala
Jupyter-PowerShell - Jupyter Kernel for PowerShell