nb_conda_kernels | managing conda environment-based kernels | Code Editor library

by Anaconda-Platform Python Version: 2.3.0 License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(9)Vulnerabilities Install Support

kandi X-RAY | nb_conda_kernels Summary

nb_conda_kernels is a Python library typically used in Editor, Code Editor, Visual Studio Code, Jupyter applications. nb_conda_kernels has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This extension enables a Jupyter Notebook or JupyterLab application in one conda environment to access kernels for Python, R, and other languages found in other environments. When a kernel from an external environment is selected, the kernel conda environment is automatically activated before the kernel is launched. This allows you to utilize different versions of Python, R, and other languages from a single Jupyter installation. The package works by defining a custom KernelSpecManager that scans the current set of conda environments for kernel specifications. It dynamically modifies each KernelSpec so that it can be properly run from the notebook environment. When you create a new notebook, these modified kernels will be made available in the selection list.

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Quality

Security

License

Reuse

Support

nb_conda_kernels has a low active ecosystem.

It has 513 star(s) with 62 fork(s). There are 20 watchers for this library.

It had no major release in the last 12 months.

There are 40 open issues and 100 have been closed. On average issues are closed in 110 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of nb_conda_kernels is 2.3.0

Quality

nb_conda_kernels has 0 bugs and 0 code smells.

Security

nb_conda_kernels has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nb_conda_kernels code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nb_conda_kernels is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

nb_conda_kernels releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

nb_conda_kernels saves you 1023 person hours of effort in developing the same functionality from scratch.

It has 2324 lines of code, 84 functions and 20 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed nb_conda_kernels and discovered the below as its top functions. This is intended to give you an instant insight into nb_conda_kernels implemented functionality, and help decide if they suit your requirements.

Return a dict of the cmdclass to use .
Install the C ++ kernels .
Get all kernel specs
Generator for git pieces from VCS .
Create the versioneer config file .
Extract git versions from keywords .
Return git versions .
Returns the project root directory .
Install versioneer .
Run git commands .

Get all kandi verified functions for this library.

nb_conda_kernels Key Features

No Key Features are available at this moment for nb_conda_kernels.

nb_conda_kernels Examples and Code Snippets

No Code Snippets are available at this moment for nb_conda_kernels.

Community Discussions

Trending Discussions on nb_conda_kernels

Don't start JupyterLab if configuration is invalid

Python: matplotlib.pyplot.show() is not showing the plot

How to prevent running a command in a Docker image

what is nb_conda_kernels equivalent for python 3.9+?

Jupyter Notebook Cannot Connect to Kernel, Likely due to Zipline / AssertionError

Conda Environment and Jupyter Notebook, Python 3.9.2

jupyter notebook can't detect conda kernels only on boot

CalledProcessError: Command '['convert', '--version']' returned non-zero exit status 1

ModuleNotFoundError: No module named 'snorkel.labeling'

QUESTION

Don't start JupyterLab if configuration is invalid

Asked 2022-Feb-04 at 00:48

When JupyterLab tries to start, in some occasions, the config file may be invalid, and Jupyterlab starts regardless in default port 8888.

Currently I have a JupyterLab service defined as follows, but I also try to start it manually and got the same results. An example when config file may be invalid is when a library is not available to be imported. I want to prevent Jupyter to start and fail gracefully.

...

ANSWER

Answered 2022-Feb-04 at 00:48

You can enforce failure on configuration errors by configuring environment variable TRAITLETS_APPLICATION_RAISE_CONFIG_FILE_ERROR to 1 or true (see docs); on Linux this can be done by prepending the startup command like so:

Source https://stackoverflow.com/questions/70952321

QUESTION

Python: matplotlib.pyplot.show() is not showing the plot

Asked 2021-Nov-03 at 13:35

import matplotlib.pyplot as plt

plt.plot([1,2,3])
plt.show()

input("Press enter to continue...")

...

ANSWER

Answered 2021-Nov-03 at 13:32

As of late, conda and matplotlib have been having issues.

You can try to downgrade freetype from 2.11.0 to 2.10.4 by doing conda install freetype=2.10.4

Source https://stackoverflow.com/questions/69825742

QUESTION

How to prevent running a command in a Docker image

Asked 2021-Sep-03 at 00:39

I'm new to Docker. The image I am using is kaggle/python https://github.com/Kaggle/docker-python/blob/main/Dockerfile

Using this image, I would like to create a new image which:

(1) Has some more packages

(2) Prevents Jupyter from starting up automatically each time the container is run (the source image does this - I can't seem to find the command in the docker file where this is invoked)

Edit: I have found the line where Jupyter is invoked, however I am unsure as to how it can get ignored in my new image

...

ANSWER

Answered 2021-Sep-03 at 00:39

This barebones Dockerfile should get you going.

Source https://stackoverflow.com/questions/69037571

QUESTION

what is nb_conda_kernels equivalent for python 3.9+?

Asked 2021-Apr-21 at 21:48

conda install nb_conda_kernels in the base environment throws the following error:

...

ANSWER

Answered 2021-Apr-21 at 21:48

Conda Forge builds it for Python 3.9, so

Source https://stackoverflow.com/questions/67202874

QUESTION

Jupyter Notebook Cannot Connect to Kernel, Likely due to Zipline / AssertionError

Asked 2021-Apr-12 at 04:17

All of my virtual environments work fine, except for one in which the jupyter notebook won't connect for kernel. This environment has Zipline in it, so I expect there is some dependency that is a problem there, even though I installed all packages with Conda.

I've read the question and answers here, and unfortunately downgrading tornado to 5.1.1 didn't work nor do I get ValueErrors. I am, however, getting an AssertionError that appears related to the Class NSProcessInfo.

I'm on an M1 Mac. Log from terminal showing the error below, and my environment file is below that. Can someone help me get this kernel working? Thank you!

...

ANSWER

Answered 2021-Apr-04 at 18:14

Figured it out.

What works:

Source https://stackoverflow.com/questions/66907180

QUESTION

Conda Environment and Jupyter Notebook, Python 3.9.2

Asked 2021-Mar-02 at 00:45

My Conda Environments are not showing up in my Jupiter Notebooks. I've reviewed all the (excellent) dialogue here, but it doesn't appear to work for python 3.9.2.

I tried the following, which didn't work:

...

ANSWER

Answered 2021-Mar-02 at 00:40

Try using the conda-forge channel, e.g.:

Source https://stackoverflow.com/questions/66359821

QUESTION

jupyter notebook can't detect conda kernels only on boot

Asked 2020-Nov-02 at 01:00

I'm trying to automatically start jupyter server on boot. (ec2, amazon linux)

I got the jupyter server working and correctly loading all the conda kernels.

and I tried to run jupyter on boot. (tried rc.local, systemd, crontab and all fails to load conda kernels and only loads basic python2 and python3 kernels)

I've traced it down to the nb_conda_kernels not finding being able to call 'conda' on boot, as below:

...

ANSWER

Answered 2020-Oct-30 at 11:40

conda has not been configured yet when rc.local is executed. This is usually done through the .bashrc file. But you can try to just add it to the rc.local script (before launching jupyter):

Source https://stackoverflow.com/questions/64601665

QUESTION

CalledProcessError: Command '['convert', '--version']' returned non-zero exit status 1

Asked 2020-Sep-24 at 21:01

Got the DLC-GPU.yaml from here: https://github.com/DeepLabCut/DeepLabCut/blob/master/conda-environments/DLC-GPU.yaml

...

ANSWER

Answered 2020-Sep-24 at 21:01

matplotlib.animation requires ffmpeg for saving movies and ImageMagick for saving animated gifs.

See https://matplotlib.org/users/installing.html#install-requirements

Install them with your system package manager:

Source https://stackoverflow.com/questions/64053840

QUESTION

ModuleNotFoundError: No module named 'snorkel.labeling'

Asked 2020-Aug-04 at 09:12

I installed snorkel using conda and when I try to run - from snorkel.labeling import labeling_function it throws the following error - ModuleNotFoundError: No module named 'snorkel.labeling'.

I tried looking up for a solution on Github, but unfortunately, I couldn't follow through. I have also tried installing nb_conda_kernels, to make all your conda environments available in jupyterbut it didn't help. Also tried creating a separate env, installing snorkel and launching jupyter notebook from the snorkel's environment, and it didn't work either. Any form of help is much appreciated!

Thanks in advance!

...

ANSWER

Answered 2020-Aug-04 at 09:10

Try these install instructions:

Source https://stackoverflow.com/questions/63243522

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

Vulnerabilities

No vulnerabilities reported

Install nb_conda_kernels

This package is designed to be managed solely using conda. It should be installed in the environment from which you run Jupyter Notebook or JupyterLab. This might be your base conda environment, but it need not be. For instance, if the environment notebook_env contains the notebook package, then you would run. Any other environments you wish to access in your notebooks must have an appropriate kernel package installed. For instance, to access a Python environment, it must have the ipykernel package; e.g. To utilize an R environment, it must have the r-irkernel package; e.g. For other languages, their corresponding kernels must be installed.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: