# Thun Documentation Documentation Most of the docs take the form of some [Jupyter](https://jupyter.org/index.html) notebooks. The notebooks are converted (using [nbconvert](https://nbconvert.readthedocs.io/en/latest/install.html)) to HTML, Markdown, and ReST files so you can view them without running Jupyter. ## Running the Notebooks with [Jupyter](https://jupyter.org/index.html) In order to run the [Jupyter](https://jupyter.org/index.html) notebooks you need [Jupyter](https://jupyter.org/index.html) (obviously): [Installing the classic Jupyter Notebook interface](https://jupyter.readthedocs.io/en/latest/install/notebook-classic.html) And, of course, you should install `Thun` (see the main project README or the [online docs](https://joypy.osdn.io/#quick-start)). Once that's done you should be able to start Jupyter Notebook server in the `joypy/docs` directory and run the notebooks. ## ``notebook_preamble.py`` ...something about the `notebook_preamble.py` file. ## Installing the [Joy Jupyter Kernel](https://osdn.net/projects/joypy/scm/git/Thun/tree/master/docs/jupyter_kernel/) [Joy Jupyter Kernel](https://osdn.net/projects/joypy/scm/git/Thun/tree/master/docs/jupyter_kernel/) Tracking down the deets: - [Installing Kernels](https://jupyter.readthedocs.io/en/latest/install/kernels.html) - [Kernels](https://jupyter.readthedocs.io/en/latest/projects/kernels.html#kernels-langs) - [Jupyter kernels](https://github.com/ipython/ipython/wiki/IPython-kernels-for-other-languages) - [Jupyter kernels](https://github.com/jupyter/jupyter/wiki/Jupyter-kernels) - [Creating new Jupyter kernels](https://github.com/jupyter/jupyter/wiki/Jupyter-kernels#creating-new-jupyter-kernels) - "[Making kernels for Jupyter](https://jupyter-client.readthedocs.io/en/latest/kernels.html) in the documentation." From [Making simple Python wrapper kernels](https://jupyter-client.readthedocs.io/en/latest/wrapperkernels.html): > Now create a JSON kernel spec file and install it using ``jupyter kernelspec install ``. Place your kernel module anywhere Python can import it (try current directory for testing). The current list of kernels: % jupyter kernelspec list Available kernels: python3 /usr/home/sforman/.local/share/jupyter/kernels/python3 > Place your kernel module anywhere Python can import it Yah, okay. sforman@bock:~/src/Joypy/docs/jupyter_kernel % setenv PYTHONPATH `pwd` Let's go! sforman@bock:~/src/Joypy/docs/jupyter_kernel % jupyter kernelspec install . [Errno 13] Permission denied: '/usr/local/share/jupyter' Perhaps you want to install with `sudo` or `--user`? Okay sforman@bock:~/src/Joypy/docs/jupyter_kernel % jupyter kernelspec install --user . [InstallKernelSpec] Removing existing kernelspec in /usr/home/sforman/.local/share/jupyter/kernels/. Traceback (most recent call last): File "/home/sforman/.local/bin/jupyter-kernelspec", line 8, in sys.exit(KernelSpecApp.launch_instance()) File "/home/sforman/.local/lib/python3.7/site-packages/traitlets/config/application.py", line 846, in launch_instance app.start() File "/home/sforman/.local/lib/python3.7/site-packages/jupyter_client/kernelspecapp.py", line 323, in start return self.subapp.start() File "/home/sforman/.local/lib/python3.7/site-packages/jupyter_client/kernelspecapp.py", line 151, in start replace=self.replace, File "/home/sforman/.local/lib/python3.7/site-packages/jupyter_client/kernelspec.py", line 404, in install_kernel_spec shutil.rmtree(destination) File "/usr/local/lib/python3.7/shutil.py", line 498, in rmtree onerror(os.rmdir, path, sys.exc_info()) File "/usr/local/lib/python3.7/shutil.py", line 496, in rmtree os.rmdir(path) OSError: [Errno 22] Invalid argument: '/usr/home/sforman/.local/share/jupyter/kernels/.' __Looks at code__ Oh FFS cp -Rv /usr/home/sforman/src/Joypy/docs/jupyter_kernel /usr/home/sforman/.local/share/jupyter/kernels/thun /usr/home/sforman/src/Joypy/docs/jupyter_kernel -> /usr/home/sforman/.local/share/jupyter/kernels/thun /usr/home/sforman/src/Joypy/docs/jupyter_kernel/Try out the Joypy Jupyter Kernel.ipynb -> /usr/home/sforman/.local/share/jupyter/kernels/thun/Try out the Joypy Jupyter Kernel.ipynb /usr/home/sforman/src/Joypy/docs/jupyter_kernel/joy_kernel.py -> /usr/home/sforman/.local/share/jupyter/kernels/thun/joy_kernel.py /usr/home/sforman/src/Joypy/docs/jupyter_kernel/kernel.json -> /usr/home/sforman/.local/share/jupyter/kernels/thun/kernel.json Done. Can start joy kernal notebooks. ## Table of Contents - 1. Basic Use of Joy in a Notebook - 2. Library Examples - Short examples of each word in the dictionary. Various formats. - 3. Developing a Program - Working with the first problem from Project Euler, "Find the sum of all the multiples of 3 or 5 below 1000", several forms of the program are derived. - 4. Replacing Functions in the Dictionary - Shows the basics of defining new "primitive" functions in Python or as definitions and adding them to the dictionary. - Factorial Function and Paramorphisms - A basic pattern of recursive control-flow. - Generator Programs - Using the x combinator to make generator programs which can be used to create unbounded streams of values. - Hylo-, Ana-, Cata-morphisms - Some basic patterns of recursive control-flow structures. - Quadratic - Not-so-annoying Quadratic Formula. - Trees - Ordered Binary Trees in Joy and more recursion. - Zipper - A preliminary examination of the idea of data-structure "zippers" for traversing datastructures. - notebook_preamble.py - Imported into notebooks to simplify the preamble code. - pe1.py pe1.txt - Set up and execute a Joy program for the first problem from Project Euler. The pe1.txt file is the trace. It's 2.8M uncompressed. Compressed with gzip it becomes just 0.12M. - repl.py - Run this script to start a REPL. Useful for e.g. running Joy code in a debugger. ## Notes One of the things that interests me about Joy is how programming becomes less about writing code and more about sound reasoning about simple (almost geometric) programs. Many of the notebooks in this collection consist of several pages of discussion to arrive at a few lines of Joy definitions. I think this is a good thing. This is "literate programming". The "programs" resemble mathematical proofs. You aren't implementing so much as deriving. The structure of Joy seems to force you to think clearly about the task in a way that is reliable but extremely flexible. It feels like a puzzle game, and the puzzles are often simple, and the solutions build on each other.