conda_kernupdate | simple script that register all the conda env
kandi X-RAY | conda_kernupdate Summary
kandi X-RAY | conda_kernupdate Summary
conda_kernupdate is a Python library. conda_kernupdate has no bugs, it has no vulnerabilities and it has low support. However conda_kernupdate build file is not available. You can download it from GitLab.
This is a small and simple script that register all the conda env with ipykernel installed in order to access them into a notebook. You can install it with. in your conda root env (conda activate base). will list all the available envs, and try to run ipykernel install for each. With the optional cku link -i, the script will try to run conda install ipykernel in the env that does not have ipykernel yet. With cku link -f you will force the linkage even if the kernel is already there, and with cku link -c you will clean the kernel (and then relink it). You can run it after a environment creation, or use a systemd path / service to watch every time that an env is created for a fully automated workflow. will simply remove the linkage between one env and its kernel.
This is a small and simple script that register all the conda env with ipykernel installed in order to access them into a notebook. You can install it with. in your conda root env (conda activate base). will list all the available envs, and try to run ipykernel install for each. With the optional cku link -i, the script will try to run conda install ipykernel in the env that does not have ipykernel yet. With cku link -f you will force the linkage even if the kernel is already there, and with cku link -c you will clean the kernel (and then relink it). You can run it after a environment creation, or use a systemd path / service to watch every time that an env is created for a fully automated workflow. will simply remove the linkage between one env and its kernel.
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Support
conda_kernupdate has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are no watchers for this library.
It had no major release in the last 6 months.
conda_kernupdate has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of conda_kernupdate is current.
Quality
conda_kernupdate has no bugs reported.
Security
conda_kernupdate has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
conda_kernupdate does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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conda_kernupdate releases are not available. You will need to build from source code and install.
conda_kernupdate has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
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conda_kernupdate Key Features
No Key Features are available at this moment for conda_kernupdate.
conda_kernupdate Examples and Code Snippets
No Code Snippets are available at this moment for conda_kernupdate.
Community Discussions
No Community Discussions are available at this moment for conda_kernupdate.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install conda_kernupdate
You can download it from GitLab.
You can use conda_kernupdate like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use conda_kernupdate like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitLab.
If you have any questions check and ask questions on community page Stack Overflow .
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