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-__website (automatic):__ Update website when code get pushed to the repository.
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-__test (automatic):__ Validate PR and code based on the current tests implemented.
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-__release (manual):__ Will look at git history to generate version bump with associated changelog. This will publish a new version to PyPI. Then conda-forge will catchup the new version and will automatically publish it the next day or so.
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-__package (automatic):__ Will generate the desktop bundle and link them to the release entry inside Github.
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## WebSite
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The WebSite is using VitePress to present the various markdown files living under `./docs/**/*.md` into a website available at https://kitware.github.io/QuickView/.
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## Release
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This workflow needs to be [triggered manually on this page](https://github.com/Kitware/QuickView/actions/workflows/release.yml) by clicking on the __Run workflow__ button.
For Python development while you can use a mix of conda and pip install, it is generally not recommended. So we will provide 2 setups and it will be up to the user to choose what better match his usage.
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## Conda setup
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```sh
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# Grab the code you aim to work with
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git clone <repository-url>
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cd<repository-name>
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# Set up conda environment
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conda env create -f quickview-env.yml
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conda activate quickview
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# Install QuickView
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pip install -e .
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```
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Then to run the application
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```sh
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quickview # or the name of the executable your application is providing
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```
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## UV setup + Downloaded ParaView
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```
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# Grab the code you aim to work with
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git clone <repository-url>
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cd <repository-name>
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# Setup your python environment
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uv venv -p 3.12 # force python version to match ParaView 6
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uv sync --all-extras --dev
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# Activate environment
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source .venv/bin/activate
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# Install commit analysis
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pre-commit install
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pre-commit install --hook-type commit-msg
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# Allow live code edit
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uv pip install -e .
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```
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Then to run the application, you will need ParaView. The example below provide an example for macOS.
Since the QuickView applications are just Python packages, we install them inside conda environment related to their funding project (`/global/common/software/m4359/`).
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## Custom conda environments
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Create a directory for all the conda environments we aim to enable for our users.
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```sh
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mkdir -p /global/common/software/m4359/conda-envs
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```
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Then for each project we will create an environment inside that directory.
In order to use the NERSC facilities, you need to obtain a NERSC account and your user account must be tied to a NERSC Allocation. Before logging into any compute resource, you will need to set a strong password. Please see our password rules if you need help creating a strong password. Once you have an account, you can log in to Iris to manage account details. This will include setting up multi-factor authentication (MFA) which is required to access all NERSC systems and services.
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Please refer to [NERSC documentation on how to get started](https://docs.nersc.gov/getting-started/).
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## Login
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[Connect to Perlmutter](https://jupyter.nersc.gov/hub/login)
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