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jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n- JupyterLab\n- Installation of conda via Anaconda or Miniconda conda >=4.6.11 (the script\n  will try to update your base installation anyway)\n\n## Installation\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda<2 or 3> install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). 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jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n- JupyterLab\n- Installation of conda via Anaconda or Miniconda conda >=4.6.11 (the script\n  will try to update your base installation anyway)\n\n## Installation\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda<2 or 3> install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\nNext, clone the jupyter-vcdat github repo:\n\n```\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n## Sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run 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jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n- JupyterLab\n- Installation of conda via Anaconda or Miniconda conda >=4.6.11 (the script\n  will try to update your base installation anyway)\n\n## Installation\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda<2 or 3> install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\nNext, clone the jupyter-vcdat github repo:\n\n```\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n## Sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"86a3355c8ca7aeb7891acb12cccd3ed86c00a416","_id":"jupyter-vcdat@2.1.6","_nodeVersion":"12.10.0","_npmVersion":"6.10.3","dist":{"integrity":"sha512-rX2zvnSdi5FkIFQzCA7/2V98SxpzkHx5bjG9kzP9W7oxordCwuYo21nrjiBnZe/v1x6AM1FnvL0VufbCoPfwOA==","shasum":"2b69ed11160999f00b207ab5b214fdbc03540b38","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.1.6.tgz","fileCount":69,"unpackedSize":784015,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"b7fd8a77479bd82e82b355a7b30e6c6e561ab2b1","_id":"jupyter-vcdat@2.1.7","_nodeVersion":"12.10.0","_npmVersion":"6.10.3","dist":{"integrity":"sha512-9AEJklq85NOZQGlIqIGi+zyUMdAEX9SmXHdKXgmeXrvg3twp7IOQzFkG0/i2XdUA/DjleexNMZ92XwmQA0CAHw==","shasum":"e2de9541876878f7d25da0f1ba548be4d5b57b37","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.1.7.tgz","fileCount":69,"unpackedSize":784360,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"27be82f60f72f5574bbb8524d747a16a7f92cf08","_id":"jupyter-vcdat@2.1.8","_nodeVersion":"12.10.0","_npmVersion":"6.10.3","dist":{"integrity":"sha512-0EIuZGVhQ80Nqh1W/AO78MMO6yo+R6gSJ4IyBTKh01A8ES4yA6bVJ2xf18TpakZ9yoWwZEry/A+Je1B2vMUgdw==","shasum":"81cec3f82652bb8467cae9a887e1cef974d59f7b","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.1.8.tgz","fileCount":69,"unpackedSize":784360,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"1b489fed59b98b9d89b424a1ac8f5926ea70bcd9","_id":"jupyter-vcdat@2.2.1","_nodeVersion":"12.10.0","_npmVersion":"6.10.3","dist":{"integrity":"sha512-tmLC1C7xXEMnUbvJaG/PrDbX09vCQzzMyz/07PUsRUrRp2npuGi0M2fDgxPtVRoEo3H0dLKc2LrdBQFXVYeDag==","shasum":"39ddbb91f685ba482ad90ce44fad031f72d3eedb","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.2.1.tgz","fileCount":74,"unpackedSize":829048,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./scripts/install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./scripts/install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"f23c2343d81347378b156ab20dbb4d15b9d372ed","_id":"jupyter-vcdat@2.2.3","_nodeVersion":"12.10.0","_npmVersion":"6.10.3","dist":{"integrity":"sha512-sjr9jpIhC54spaYbMY17w8U4quP9UGGVhsvBDfIMTkDVhEbnMXKHuZ78liMeu8YFsamrKaQvEC39inY0qmZxPw==","shasum":"675730a6ddbb16b1b3b4df580299e38852f44c3d","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.2.3.tgz","fileCount":74,"unpackedSize":836283,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./scripts/install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest jupyter lab #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./scripts/install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n       code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"93a8f8e5e8fff7cd263354af03f600b11dc462be","_id":"jupyter-vcdat@2.3.1","_nodeVersion":"12.10.0","_npmVersion":"6.10.3","dist":{"integrity":"sha512-8djdiznVo/RqrKwSFIX4RtkpWWVhxVix37CnFRlMxPzi40CiYr1XgR8nSBX8ZKApz6SkbEnB8sGPbEDhxqazsw==","shasum":"42b3cdac411c285fe213da231fb0a00e70a5a422","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.3.1.tgz","fileCount":78,"unpackedSize":857241,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.4\r\nComment: 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest jupyter lab #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n      code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest jupyter lab #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n      code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest jupyter lab #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n      code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest jupyter lab #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n      code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started 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Jupyter-vcdat\n\nA Jupyter Lab extension that integrates vCDAT features directly in a notebook.\n\n## Prerequisites\n\n### For installing locally with conda you'll need:\n- Installation of conda via Anaconda or Miniconda conda >=4.7.12 (the script\n  will try to update your base installation anyway)\n\nIf you didn't let Anaconda or Miniconda prepend the Anaconda(2 or 3) install location to PATH, make sure conda is in your PATH (for more information see the [Anaconda Documentation](https://docs.anaconda.com/anaconda/user-guide/faq/#installing-anaconda)). Assuming Ananconda is installed in ${HOME}/anaconda:\n* export PATH=${HOME}/anaconda/bin:${PATH} # for bash\n* setenv PATH ${HOME}/anaconda/bin:${PATH} # for tcsh\n\n### For running docker container, you'll need docker installed:\n- Installing Docker: https://docs.docker.com/v17.09/engine/installation/\n\n## User Installation\n\nYou can run jupyter-vcdat via a local installation, an anaconda environment or through a docker container.\n\n### New conda environment\n\nThis example will create and run a new conda environment 'jupyter-vcdat', containing JupyterLab and jupyter-vcdat\n\n```bash\nconda create -n jupyter-vcdat -c cdat/label/v82 -c conda-forge jupyter-vcdat #Create conda environment\nconda activate jupyter-vcdat #Start environment\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Existing conda environment\n\nThis example will install jupyter-vcdat to an existing conda environment.\n* Note: python3 is required and will be installed.\n\n```bash\nconda install -c cdat/label/v82 -c conda-forge jupyter-vcdat #Install jupyter-vcdat\njupyter lab build #Build jupyter lab to include jupyter-vcdat extension (only for first time installation)\n\njupyter lab #Start Jupyter Lab\n```\n\nThe browser should open automatically, if not, point your browser to: localhost:8888/lab\n\n### Jupyter-vcdat docker container\n\nThis example runs a jupyter-vcdat docker container at localhost:9000/lab, with mounted volume 'my_data':\n\n```bash\ndocker run -p 9000:8888 -v /Path/To/my_data/:/home/jovyan/my_data/ -it cdat/vcdat:latest jupyter lab #Run the image\n```\n\nAfter the container is running, obtain the token (if needed) from the output shown in the console:\n\n```bash\nThe Jupyter Notebook is running at:\nhttp://(d8a71c79a232 or 127.0.0.1):8888/?token=<Copy the token value from here>\n```\n\nOpen a browser and use this URL:\n\n### localhost:8888/lab?token=\\<Paste token value here>\n\nYou should then be able to access the jupyter lab instance on your local browser.\n\n## Obtaining sample data\n\nTo download sample data, enter the code below within a Jupyter notebook cell and run the cell:\n\n```python\nimport vcs\nimport cdms2\nimport cdat_info\nimport pkg_resources\nvcs_egg_path = pkg_resources.resource_filename(pkg_resources.Requirement.parse(\"vcs\"), \"share/vcs\")\npath = vcs_egg_path+'/sample_files.txt'\ncdat_info.download_sample_data_files(path,\"sample_data\")\n```\n\n\n## Local installation (for developers)\n\nMake sure you have met all pre-requisits noted at the top.\nClone the jupyter-vcdat github repo:\n\n```bash\ngit clone https://github.com/CDAT/jupyter-vcdat.git\n```\n\nChange into the directory containing the repo and type in the following commands:\n\n```bash\n\n    #Create the environment\n    ./install_script.sh #Note: You can use -h to get help and options for installation script.\n\n    # The following two lines of code install tslint if developers want to use it (optional):\n      # For VSCode:\n      code --install-extension tslint\n\n      # For Atom:\n      apm install linter-tslint\n\n    # For all users, activate the jupyter-vcdat environment and launch the JupyterLab interface\n    conda activate jupyter-vcdat\n    jupyter lab\n\n```\n\nTo rebuild the package and the JupyterLab app:\n\n```bash\nnpm run build\njupyter lab build\n```\n\n* For more information on getting started with Jupyter-VCDAT checkout the [Getting Started Page](https://github.com/CDAT/jupyter-vcdat/wiki/Getting-Started).","readmeFilename":"README.md","gitHead":"c4dd10eda606cf7e660ec07ef12270e712a07059","_id":"jupyter-vcdat@2.3.9","_nodeVersion":"15.0.1","_npmVersion":"7.0.3","dist":{"integrity":"sha512-uDvg4owMGN0Ry9aLJ7P6j6xL2mQcSbBT7Qqr/Axm0h+B8BThsl/ESrgw/MXX+7hguiHUoBdVj9PSlhjrmETM+A==","shasum":"814e912d5939a3df51dc837d0304f5dbf3ec6acc","tarball":"https://registry.npmjs.org/jupyter-vcdat/-/jupyter-vcdat-2.3.9.tgz","fileCount":78,"unpackedSize":869209,"npm-signature":"-----BEGIN PGP SIGNATURE-----\r\nVersion: OpenPGP.js v3.0.13\r\nComment: https://openpgpjs.org\r\n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\nPBPo\r\n=DzuC\r\n-----END PGP SIGNATURE-----\r\n","signatures":[{"keyid":"SHA256:jl3bwswu80PjjokCgh0o2w5c2U4LhQAE57gj9cz1kzA","sig":"MEYCIQCg6InKY4VkQErcce282WSPV/2Wni8Ac+1amwDNgAbjkAIhAIDeG+cujx4IyHV/4qxYxOuHELrc5nSsdmLWuW6PUZmE"}]},"_npmUser":{"name":"downie4","email":"downie4@llnl.gov"},"directories":{},"maintainers":[{"name":"doutriaux1","email":"doutriaux1@llnl.gov"},{"name":"downie4","email":"downie4@llnl.gov"}],"_npmOperationalInternal":{"host":"s3://npm-registry-packages","tmp":"tmp/jupyter-vcdat_2.3.9_1604450513007_0.5032200615846907"},"_hasShrinkwrap":false}},"time":{"created":"2019-06-13T17:26:49.032Z","0.1.0":"2019-06-13T17:26:49.206Z","modified":"2022-05-07T01:12:39.354Z","2.0.0":"2019-06-13T20:41:11.177Z","2.0.1":"2019-07-17T16:00:09.352Z","2.1.0":"2019-09-16T20:25:09.854Z","2.0.5":"2019-10-04T19:11:25.183Z","2.0.9":"2019-10-04T23:57:48.667Z","2.1.1":"2019-10-05T03:03:31.447Z","2.1.2":"2019-10-18T23:58:51.039Z","2.1.3":"2019-10-28T17:25:04.754Z","2.1.5":"2019-11-01T23:07:38.367Z","2.1.6":"2019-11-07T20:34:00.563Z","2.1.7":"2019-11-08T18:45:31.958Z","2.1.8":"2019-11-09T01:09:39.670Z","2.1.9":"2019-11-11T21:35:00.090Z","2.2.0":"2019-11-15T02:19:48.771Z","2.2.1-demo":"2019-11-16T03:14:12.048Z","2.2.2-demo":"2019-11-16T20:50:21.741Z","2.2.3-demo":"2019-11-18T18:57:05.223Z","2.2.1-demo4":"2019-11-20T22:40:01.217Z","2.2.1-demo5":"2019-11-23T02:57:35.976Z","2.2.1-demo6":"2019-11-27T00:20:28.401Z","2.2.1":"2019-12-13T17:54:32.100Z","2.2.2":"2020-01-13T23:49:26.695Z","2.2.3":"2020-01-31T01:15:59.677Z","2.3.0":"2020-02-25T23:59:05.063Z","2.3.1":"2020-03-20T18:34:24.404Z","2.3.2":"2020-04-23T21:00:02.176Z","2.3.3":"2020-04-29T22:19:33.262Z","2.3.4":"2020-05-09T00:09:15.782Z","2.3.5":"2020-05-15T18:52:34.435Z","2.3.6":"2020-10-23T02:39:48.292Z","2.3.7":"2020-10-27T21:48:12.758Z","2.3.8":"2020-10-27T23:30:35.681Z","2.3.9":"2020-11-04T00:41:53.286Z"},"maintainers":[{"name":"doutriaux1","email":"doutriaux1@llnl.gov"},{"name":"downie4","email":"downie4@llnl.gov"}],"description":"A vCDAT extension for JupyterLab.","homepage":"https://github.com/CDAT/jupyter-vcdat","keywords":["jupyter","jupyterlab","jupyterlab-extension"],"repository":{"type":"git","url":"git+https://github.com/CDAT/jupyter-vcdat.git"},"author":{"name":"LLNL CDAT team"},"bugs":{"url":"https://github.com/CDAT/jupyter-vcdat.git/issues"},"license":"BSD-3-Clause","readme":"","readmeFilename":""}