docker-stacks | Ready-to-run Docker images containing Jupyter applications | Continuous Deployment library

 by   jupyter Python Version: Current License: Non-SPDX

kandi X-RAY | docker-stacks Summary

kandi X-RAY | docker-stacks Summary

docker-stacks is a Python library typically used in Devops, Continuous Deployment, Jupyter, Docker applications. docker-stacks has no bugs, it has no vulnerabilities and it has medium support. However docker-stacks build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Jupyter Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications and interactive computing tools. You can use a stack image to do any of the following (and more):.

            kandi-support Support

              docker-stacks has a medium active ecosystem.
              It has 7297 star(s) with 2896 fork(s). There are 190 watchers for this library.
              It had no major release in the last 6 months.
              There are 21 open issues and 802 have been closed. On average issues are closed in 100 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of docker-stacks is current.

            kandi-Quality Quality

              docker-stacks has 0 bugs and 0 code smells.

            kandi-Security Security

              docker-stacks has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              docker-stacks code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              docker-stacks has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              docker-stacks releases are not available. You will need to build from source code and install.
              docker-stacks has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions, examples and code snippets are available.
              docker-stacks saves you 320 person hours of effort in developing the same functionality from scratch.
              It has 1580 lines of code, 115 functions and 40 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed docker-stacks and discovered the below as its top functions. This is intended to give you an instant insight into docker-stacks implemented functionality, and help decide if they suit your requirements.
            • Create a manifest for a given short image
            • Append a build history line
            • Write manifest file
            • Return taggers and manifests for a given short image
            • Return the current platform
            • Return a markdown piece of packages
            • Return a quoted output string
            • Merge tags
            • Writes tags to tags_dir
            • Apply tags to image
            • Update the wiki page
            • Return markdown as a string
            • Return markdown as a markdown string
            • Return a markdown piece of a container
            • Return a markdown section of the given container
            Get all kandi verified functions for this library.

            docker-stacks Key Features

            No Key Features are available at this moment for docker-stacks.

            docker-stacks Examples and Code Snippets

            ihaskell-notebook,Stack ,Installing Haskell packages
            Jupyter Notebookdot img1Lines of Code : 12dot img1License : Permissive (MIT)
            copy iconCopy
            :1:1: error:
               Could not find module ‘Numeric.LinearAlgebra’
               Use -v to see a list of the files searched for.
            stack build hmatrix
            :!stack build hmatrix
            :!stack build hmatrix
            import Numeric.LinearAlgebra
            ident 3
             [ 1.0, 0.0, 0.0
            Jupyter Notebookdot img2Lines of Code : 9dot img2License : Permissive (MIT)
            copy iconCopy
            stack build ihaskell-magic
            stack exec ghc-pkg -- list | grep ihaskell
            copy iconCopy
            docker run -d -p 8888:8888 \
                -v /some/host/folder:/etc/ssl/notebook \
                jupyter/all-spark-notebook \
            docker ru  

            Community Discussions


            Mamba installing a package into wrong environment
            Asked 2021-Sep-10 at 12:21

            The background is, I'm responsible for maintaining a fancy Docker image that is used by our team for analytics. It uses a Jupyter notebook image as the base, and then adds various customisations, extra packages, etc.

            One of the team members recently wanted to run Tensorflow. No problem, I'll just run mamba install and add it to the image. However, this created an issue: Tensorflow 2.4.3 (the latest version) is somehow incompatible with R 4.1.1 (also the latest version) or something else in the ecosystem, causing R to to be downgraded to 3.6.3. So I created a new environment and installed TF into that:



            Answered 2021-Sep-10 at 12:21

            Not an expert on dockerfiles, but in general you could just use the -n flag to the install command to specify the target environment for the installation like so:



            css "tooltips" for both mouse hover & keyboard focus
            Asked 2021-Sep-08 at 08:28

            I have a website where I document a list of installed pythonic libraries.

            For each library, I want to have available:

            • The name of the library (obviously)
            • A link to the documentation for the library (because documentation is useful)
            • A brief description of the library (so people can quickly see what the library does)
            • The currently installed version (to stop people asking me "Are you using version x.y?")

            My current solution is to use the name as the text of a link, href'd to its documentation, and accept that the version & description are supplementary information, and can be made available to the user using a tool-tip - so they can sit in a title attribute




            Answered 2021-Sep-08 at 08:25

            Use focus-within rather than focus



            How to update interactive figure in loop with JupyterLab
            Asked 2020-Dec-21 at 22:40

            I am trying to update an interactive matplotlib figure while in a loop using JupyterLab. I am able to do this if I create the figure in a different cell from the loop, but I would prefer to create the figure and run the loop in the same cell.

            Simple Code Example:



            Answered 2020-Aug-21 at 06:52

            You can use asyncio, taking advantage of the IPython event loop:



            How to make Jupyter Terminal fully functional?
            Asked 2020-May-04 at 23:28

            Jupyter Lab application features nice Terminas with in-browser terminal shell that support colours, navigation keys, and pretty much all standard features of a terminal application. In this question I mean /lab app, not classic Notebook (/tree) app.

            If I launch Jupyter server using this Docker image it works great. I need to build my own image, and preferably not based on that. I do it simply as documented:



            Answered 2020-May-04 at 23:28

            So I figured out the reason. Apparently the Terminal web app just replicates the behaviour of the default shell of the user under which Jupyter is run. In this image they enable colouring in .bashrc template and then create a new user specifying a shell for him (lines 52 and 59).

            EDIT: also SHELL=/bin/bash must be set in environment.



            Include additional R pkg in custom JupyterHub user notebook image?
            Asked 2020-Apr-23 at 21:54

            I customize the user notebook environment like so (installing custom python packages)



            Answered 2020-Apr-21 at 03:41

            If you want to use R packages and jupyter notebook, I would suggest using jupyter/r-notebook as a base image. To install R packages afterwards, install them with conda.


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install docker-stacks

            You can try a relatively recent build of the jupyter/base-notebook image on by simply clicking the preceding link. Otherwise, the examples below may help you get started if you have Docker installed, know which Docker image you want to use and want to launch a single Jupyter Server in a container. The User Guide on ReadTheDocs describes additional uses and features in detail.
            hostname is the name of the computer running Docker
            token is the secret token printed in the console.


            Please see the Contributor Guide on ReadTheDocs for information about how to contribute package updates, recipes, features, tests, and community maintained stacks.
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