best-of-jupyter
docker-stacks
best-of-jupyter | docker-stacks | |
---|---|---|
3 | 13 | |
836 | 7,751 | |
2.4% | 0.5% | |
7.9 | 9.5 | |
7 days ago | 3 days ago | |
Python | ||
Creative Commons Attribution Share Alike 4.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
best-of-jupyter
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Spreadsheet errors can have disastrous consequences – yet we keep making them
What are some Software Development methods for reducing errors:
1. AUTOMATED TESTS; test assertions
To write spreadsheet tests:
A. Write your own test assertion library for their macro language; write assertEqual() in VBscript and Apps Script.
B. Use another language with a test library and a test runner; e.g. Python and the `assert` keyword, unittest.TestCase().assertEqual() or pytest.
C. Test the spreadsheet GUI with something like AutoHotKey.
From https://news.ycombinator.com/item?id=35896192 :
> The Scientific Method is testing, so testing (tests, assertions, fixtures) should be core to any scientific workflow system.
> awesome-jupyter#testing: https://github.com/markusschanta/awesome-jupyter#testing
> ml-tooling/best-of-jupyter lists papermill/papermill under "Interactive Widgets/Visualization" https://github.com/ml-tooling/best-of-jupyter#interactive-wi...
- Mathics: A free, open-source alternative to Mathematica
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[P] best-of-ml-python: A ranked list of awesome machine learning Python libraries
best-of-jupyter: Jupyter Notebook, Hub, and Lab projects.
docker-stacks
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Linux or Windows for coding??
See https://github.com/jupyter/docker-stacks
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Connecting IPython notebook to spark master running in different machines
I have an IPython notebook running in a docker container in Google Container Engine, the container is based on this image jupyter/all-spark-notebook
- Looking for a solution to sandbox python remotely.
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A short tutorial on running Spark with Jupyter using Docker
Yes sir :) love the jupyter docker stacks: https://github.com/jupyter/docker-stacks
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(RANT) I think I'll die trying to setup and run Spark with Python in my local environment
I use an image that allows me to run spark on jupyter notebooks and use files from my local machine to test code. Here is a good one https://github.com/jupyter/docker-stacks/tree/main/pyspark-notebook
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How we made Jupyter Docker Stacks multi-arch
Today I will tell you a story behind making Jupyter Docker Stacks able to build aarch64 images without many (almost any) compromises. If you want to read how it is implemented now, you can skip to the last section of this post.
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3.51 GB Bloated Image for Coqui TTS Server
FROM ubuntu:20.04 LABEL maintainer="PhysicsReplicatorAI " ARG NB_USER="coqui_user" \ NB_UID="1000" \ NB_GID="100" USER root ENV DEBIAN_FRONTEND=noninteractive \ TERM=xterm \ TZ=America/New_York # -------------------------------------------------------------------------------- # Update/Install the basics # -------------------------------------------------------------------------------- RUN apt-get update -y && \ apt-get install -y --no-install-recommends \ sudo locales apt-utils g++ libsndfile1-dev && \ apt-get -y clean autoclean && \ apt-get -y autoremove --purge && \ echo "en_US.UTF-8 UTF-8" > /etc/locale.gen && \ locale-gen # -------------------------------------------------------------------------------- # Configure environment # -------------------------------------------------------------------------------- ENV SHELL=/bin/bash \ NB_USER="${NB_USER}" \ NB_UID=${NB_UID} \ NB_GID=${NB_GID} \ LC_ALL=en_US.UTF-8 \ LANG=en_US.UTF-8 \ LANGUAGE=en_US.UTF-8 \ PATH="/home/${NB_USER}/.local/bin:${PATH}" \ HOME="/home/${NB_USER}" # -------------------------------------------------------------------------------- # Create coqui_user # User creation method/pattern obtained from: # https://github.com/jupyter/docker-stacks/blob/master/base-notebook/Dockerfile # -------------------------------------------------------------------------------- COPY fix-permissions /usr/local/bin/fix-permissions RUN chmod a+rx /usr/local/bin/fix-permissions && \ sed -i 's/^#force_color_prompt=yes/force_color_prompt=yes/' /etc/skel/.bashrc && \ echo "auth requisite pam_deny.so" >> /etc/pam.d/su && \ sed -i.bak -e 's/^%admin/#%admin/' /etc/sudoers && \ sed -i.bak -e 's/^%sudo/#%sudo/' /etc/sudoers && \ useradd -l -m -s /bin/bash -N -u "${NB_UID}" "${NB_USER}" && \ chmod g+w /etc/passwd && \ fix-permissions "${HOME}" && \ cd "${HOME}" && \ apt-get install -y --no-install-recommends python3-dev python3-pip && \ apt-get -y autoclean && \ apt-get -y autoremove --purge && \ apt-get -y purge $(dpkg --get-selections | grep deinstall | sed s/deinstall//g) && \ rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* # -------------------------------------------------------------------------------- # Install TTS # -------------------------------------------------------------------------------- USER ${NB_UID} RUN fix-permissions "${HOME}" && \ python3 -m pip install --no-cache-dir --upgrade TTS && \ rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* EXPOSE 5002 ENTRYPOINT ["tts-server"]
- New to dockerfiles and was wondering if somebody can help with user switching?
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How do I create a Docker image building on another image?
Pretty much what title says. I want to build an image on top of the scy-py image with my preferred libraries such as NLTK, spaCy and stanza. Is there a way to do that?
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Docker + Python Environment Management
The disadvantages are that everytime I rebuild the entire docker image I have to pray that all the dependencies that I did not list did not change, because if they did, the build fails with a cryptic error message. Also if the list of pip installs gets too long, pip is no longer able to resolve all the dependencies and then the docker image does not build either. So actually not having a requirements.txt might be a disadvantage. Further, I do not like the fact that I have both Miniconda and "regular Python" in one file. This happened, because this Dockerfile evolved from one of the Jupyter Notebook Dockerfiles. My development environment is Jupyter and I wanted my production environment as close as possible to my development environment.
What are some alternatives?
ocaml-jupyter - An OCaml kernel for Jupyter (IPython) notebook
the-littlest-jupyterhub - Simple JupyterHub distribution for 1-100 users on a single server
ubelt - A Python utility library with a stdlib like feel and extra batteries. Paths, Progress, Dicts, Downloads, Caching, Hashing: ubelt makes it easy!
nbgrader - A system for assigning and grading notebooks
best-of-generator - 🏆 Generates a ranked list of awesome libraries and tools.
nbmake - 📝 Pytest plugin for testing notebooks
mathquill - Easily type math in your webapp
pangeo-binder - Pangeo + Binder (dev repo for a binder/pangeo fusion concept)
best-of-web-python - 🏆 A ranked list of awesome python libraries for web development. Updated weekly.
zero-to-jupyterhub-k8s - Helm Chart & Documentation for deploying JupyterHub on Kubernetes
awesome-notebooks - A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.
eaf-jupyter - Jupyter client