GithubHelp home page GithubHelp logo

nbautoexport-feedstock's Introduction

About nbautoexport-feedstock

Feedstock license: BSD-3-Clause

Home: https://github.com/drivendataorg/nbautoexport

Package license: MIT

Summary: Automatically export Jupyter notebooks to various file formats (.py, .html, and more) on save.

Development: https://github.com/drivendataorg/nbautoexport

Documentation: https://nbautoexport.drivendata.org/

nbautoexport automatically exports Jupyter notebooks to various file formats (.py, .html, and more) upon save. One great use case is to automatically have script versions of your notebooks to facilitate code review commenting.

Current build status

All platforms:

Current release info

Name Downloads Version Platforms
Conda Recipe Conda Downloads Conda Version Conda Platforms

Installing nbautoexport

Installing nbautoexport from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, nbautoexport can be installed with conda:

conda install nbautoexport

or with mamba:

mamba install nbautoexport

It is possible to list all of the versions of nbautoexport available on your platform with conda:

conda search nbautoexport --channel conda-forge

or with mamba:

mamba search nbautoexport --channel conda-forge

Alternatively, mamba repoquery may provide more information:

# Search all versions available on your platform:
mamba repoquery search nbautoexport --channel conda-forge

# List packages depending on `nbautoexport`:
mamba repoquery whoneeds nbautoexport --channel conda-forge

# List dependencies of `nbautoexport`:
mamba repoquery depends nbautoexport --channel conda-forge

About conda-forge

Powered by NumFOCUS

conda-forge is a community-led conda channel of installable packages. In order to provide high-quality builds, the process has been automated into the conda-forge GitHub organization. The conda-forge organization contains one repository for each of the installable packages. Such a repository is known as a feedstock.

A feedstock is made up of a conda recipe (the instructions on what and how to build the package) and the necessary configurations for automatic building using freely available continuous integration services. Thanks to the awesome service provided by Azure, GitHub, CircleCI, AppVeyor, Drone, and TravisCI it is possible to build and upload installable packages to the conda-forge Anaconda-Cloud channel for Linux, Windows and OSX respectively.

To manage the continuous integration and simplify feedstock maintenance conda-smithy has been developed. Using the conda-forge.yml within this repository, it is possible to re-render all of this feedstock's supporting files (e.g. the CI configuration files) with conda smithy rerender.

For more information please check the conda-forge documentation.

Terminology

feedstock - the conda recipe (raw material), supporting scripts and CI configuration.

conda-smithy - the tool which helps orchestrate the feedstock. Its primary use is in the construction of the CI .yml files and simplify the management of many feedstocks.

conda-forge - the place where the feedstock and smithy live and work to produce the finished article (built conda distributions)

Updating nbautoexport-feedstock

If you would like to improve the nbautoexport recipe or build a new package version, please fork this repository and submit a PR. Upon submission, your changes will be run on the appropriate platforms to give the reviewer an opportunity to confirm that the changes result in a successful build. Once merged, the recipe will be re-built and uploaded automatically to the conda-forge channel, whereupon the built conda packages will be available for everybody to install and use from the conda-forge channel. Note that all branches in the conda-forge/nbautoexport-feedstock are immediately built and any created packages are uploaded, so PRs should be based on branches in forks and branches in the main repository should only be used to build distinct package versions.

In order to produce a uniquely identifiable distribution:

  • If the version of a package is not being increased, please add or increase the build/number.
  • If the version of a package is being increased, please remember to return the build/number back to 0.

Feedstock Maintainers

nbautoexport-feedstock's People

Contributors

conda-forge-admin avatar conda-forge-curator[bot] avatar jayqi avatar regro-cf-autotick-bot avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar

nbautoexport-feedstock's Issues

Clean up dependencies

Thanks to the conda-forge autotick bot, it looks like our dependencies may need some cleaning up: #1

This is captured in the source repository in this issue: drivendataorg/nbautoexport#56

We should update there first, and then let the autotick bot open a PR and then address the changes in meta.yaml.

Packages found by inspection but not in the meta.yaml:

  • traitlets
  • notebook
  • jupyter_core
  • nbformat

Packages found in the meta.yaml but not found by inspection:

  • jupyter_contrib_nbextensions

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.