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libyt ★ 23

In-situ analysis with Python, C/C++ simulation, and Jupyter

C++
website ★ 8

The source for http://yt-project.org/

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# Use via CDN

jsDelivr

jsDelivr serves any public GitHub repository as a CDN with zero setup. Pick a version and a file to get a ready-to-paste link and snippet.

Link
Example

Command Glossary

Commands referenced in this DOCs, explained below.

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conda activate

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Activate a conda environment.
See also: `conda deactivate`.

conda activate myenv

Activate an existing environment named `myenv`:

conda activate {{path/to/myenv}}

Activate an existing environment located at custom path:

conda activate --stack myenv

Stack `myenv` environment on top of a previous environment making libraries/commands/variables from both accessible:

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conda create

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Create new conda environments.

conda create {{[-y|--yes]}} {{[-n|--name]}} py39 python=3.9 "numpy>=1.11" scipy

Create a new environment named `py39`, install Python 3.9, NumPy v1.11 or above in it, and the latest stable version of SciPy. Say yes to all confirmations:

conda create {{[-n|--name]}} myenv --file {{file1.yml}} --file {{file2.yml}}

Create a new environment named `myenv` and install packages listed in files:

conda create {{[-p|--prefix]}} {{path/to/myenv}}

Create a new environment at a custom path (i.e. prefix):

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git clone

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Clone an existing repository.

git clone {{remote_repository_location}} {{path/to/directory}}

Clone an existing repository into a new directory (the default directory is the repository name):

git clone --recursive {{remote_repository_location}}

Clone an existing repository and its submodules:

git clone {{[-n|--no-checkout]}} {{remote_repository_location}}

Clone only the `.git` directory of an existing repository:

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jupyter lab

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Interactive development environment for Jupyter notebooks.

jupyter lab

Start JupyterLab:

jupyter lab {{path/to/notebook}}.ipynb

Open a specific notebook:

jupyter lab --notebook-dir {{path/to/directory}}

Start JupyterLab in a specific directory:

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jupyter

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Web application to create and share documents that contain code, visualizations, and notes.
Primarily used for data analysis, scientific computing, and machine learning.

jupyter notebook

Start a Jupyter notebook server in the current directory:

jupyter notebook {{path/to/file}}.ipynb

Open a specific Jupyter notebook:

jupyter nbconvert --to {{html|markdown|pdf|script|...}} {{path/to/file}}.ipynb

Export a specific Jupyter notebook into another format:

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jupyterlab

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This command is an alias of `jupyter lab`.

tldr jupyter lab

View documentation for the original command:

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pip install

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Install Python packages.

pip install {{package1 package2 ...}}

Install one or more packages:

pip install {{package1 package2 ...}} {{[-U|--upgrade]}}

Upgrade all specified packages to the latest version, installing any that are not already present:

pip install {{package}}=={{version}}

Install a specific version of a package:

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yarn

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JavaScript and Node.js package manager alternative.

yarn global add {{module_name}}

Install a module globally:

yarn install

Install all dependencies referenced in the `package.json` file (the `install` is optional):

yarn add {{module_name}}@{{version}}

Install a module and save it as a dependency to the `package.json` file (add `--dev` to save as a dev dependency):

// repository documentation