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Bump pyvista and dolfinx to v0.7.2 (#159)
* Bump pyvista and dolfinx to v0.7.2 * remove -r * Add further pyvista deps * Bump versions
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.github/workflows/book_stable.yml

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jobs:
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build-book:
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runs-on: ubuntu-latest
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container: ghcr.io/fenics/dolfinx/lab:v0.7.1
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container: ghcr.io/fenics/dolfinx/lab:v0.7.2
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env:
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PYVISTA_TRAME_SERVER_PROXY_PREFIX: "/proxy/"
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PYVISTA_TRAME_SERVER_PROXY_ENABLED: "True"
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PYVISTA_OFF_SCREEN: false
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PYVISTA_JUPYTER_BACKEND: "panel"
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PYVISTA_JUPYTER_BACKEND: "html"
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steps:
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- uses: actions/checkout@v4
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uses: ./.github/actions/install-dependencies
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- name: Install book deps
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run: python3 -m pip install -r docker/requirements.txt
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run: python3 -m pip install --no-binary=h5py .
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- name: Build the book
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run: jupyter-book build . -W

.github/workflows/deploy.yml

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uses: actions/checkout@v4
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- name: Setup Pages
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uses: actions/configure-pages@v2
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uses: actions/configure-pages@v4
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- name: Download docs artifact
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uses: actions/download-artifact@v3
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path: "./public"
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- name: Upload page artifact
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uses: actions/upload-pages-artifact@v1
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uses: actions/upload-pages-artifact@v2
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with:
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path: "./public"
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- name: Deploy coverage report to GH Pages
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id: deployment
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uses: actions/deploy-pages@v1
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uses: actions/deploy-pages@v3

.github/workflows/publish_docker.yml

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- name: Build and push Docker image
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uses: docker/build-push-action@v3
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with:
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context: ./docker
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context: .
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push: true
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file: docker/Dockerfile
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platforms: linux/amd64,linux/arm64

.github/workflows/test_nightly.yml

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test-nightly:
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# The type of runner that the job will run on
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runs-on: ubuntu-latest
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container: ghcr.io/fenics/dolfinx/lab:v0.7.1
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container: ghcr.io/fenics/dolfinx/lab:nightly
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env:
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HDF5_MPI: "ON"
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uses: ./.github/actions/install-dependencies
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- name: Install requirements
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run: python3 -m pip install --no-cache-dir -r docker/requirements.txt --upgrade
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run: python3 -m pip install --no-cache-dir --no-binary=h5py . --upgrade
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- name: Test complex notebooks in parallel
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run: |

.github/workflows/test_stable.yml

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test:
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# The type of runner that the job will run on
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runs-on: ubuntu-latest
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container: ghcr.io/fenics/dolfinx/lab:v0.7.1
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container: ghcr.io/fenics/dolfinx/lab:v0.7.2
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env:
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PYVISTA_OFF_SCREEN: true
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- name: Install additional deps
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run: |
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python3 -m pip install -r docker/requirements.txt
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python3 -m pip install --no-binary=h5py .
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- name: Test complex notebooks in parallel
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run: |

.gitignore

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**/.cache
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*.png
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*.pvtu
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*.msh
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*.msh
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*.bp

Changelog.md

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# Changelog
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## v0.7.2
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- Change pyvista backend to `html`, using Pyvista main branch
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- Using DOLFINx v0.7.2 https://github.com/FEniCS/dolfinx/releases/tag/v0.7.2 as base
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## v0.7.1
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- No API changes, release due to various bug-fixes from the 0.7.0 release, see:
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https://github.com/FEniCS/dolfinx/releases/tag/v0.7.1 for more information

Dockerfile

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FROM ghcr.io/jorgensd/dolfinx-tutorial:v0.7.1
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FROM ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
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# create user with a home directory
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ARG NB_USER=jovyan

README.md

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Alternatively, if you want to add a separate chapter, a Jupyter notebook can be added to a pull request, without integrating it into the tutorial. If so, the notebook will be reviewed and modified to be included in the tutorial.
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## Dependencies
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It is adviced to use a pre-installed version of DOLFINx, for instance through conda or docker. Remaining dependencies can be installed with
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```bash
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python3 -m pip install --no-binary=h5py -e .
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```
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# Docker images
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Docker images for this tutorial can be found in the [packages tab](https://github.com/jorgensd/dolfinx-tutorial/pkgs/container/dolfinx-tutorial)
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Additional requirements on top of the `dolfinx/lab:nightly` images can be found at [Dockerfile](docker/Dockerfile) and [requirements.txt](docker/requirements.txt)
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Additional requirements on top of the `dolfinx/lab:nightly` images can be found at [Dockerfile](docker/Dockerfile) and [pyproject.toml](./pyproject.toml)
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##
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An image building DOLFINx, Basix, UFL and FFCx from source can be built using:
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```bash
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cd docker
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docker build -f LocalDockerfile -t local_lab_env .
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docker build -f ./docker/Dockerfile -t local_lab_env .
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```
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and run
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from the root of this repository, and run
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```bash
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docker run --rm -ti -v $(pwd):/root/shared -w /root/shared --init -p 8888:8888 local_lab_env
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```

_config.yml

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# To avoid warning about default changing due to
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# https://github.com/pydata/pydata-sphinx-theme/issues/1492
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html_theme_options:
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navigation_with_keys: false
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# html_theme_options:
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# navigation_with_keys: false
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parse:
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myst_enable_extensions:
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- "amsmath"

docker/Dockerfile

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# Execute from root of repo as: docker buildx build --platform=linux/arm64,linux/amd64 -f docker/Dockerfile ./docker/ --progress=plain
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FROM ghcr.io/fenics/dolfinx/lab:v0.7.1
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FROM ghcr.io/fenics/dolfinx/lab:v0.7.2
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ARG TARGETPLATFORM
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RUN if [ "$TARGETPLATFORM" = "linux/arm64" ]; then python3 -m pip install "https://github.com/finsberg/vtk-aarch64/releases/download/vtk-9.2.6-cp310/vtk-9.2.6.dev0-cp310-cp310-linux_aarch64.whl"; fi
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RUN if [ "$TARGETPLATFORM" = "linux/amd64" ]; then python3 -m pip install vtk; fi
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ADD requirements.txt /tmp/requirements.txt
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RUN python3 -m pip install --no-cache-dir -v -r requirements.txt
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ADD pyproject.toml /tmp/pyproject.toml
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RUN python3 -m pip install --no-cache-dir --no-binary=h5py -v pyproject.toml
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RUN python3 -m pip cache purge
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RUN jupyter lab build
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ENTRYPOINT ["jupyter", "lab", "--ip", "0.0.0.0", "--no-browser", "--allow-root"]

docker/requirements.txt

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fem.md

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To use the notebooks in this tutorial with DOLFINx on your own computer, you should use the docker image using the following command:
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```bash
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docker run --init -p 8888:8888 -v "$(pwd)":/root/shared ghcr.io/jorgensd/dolfinx-tutorial:v0.7.1
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docker run --init -p 8888:8888 -v "$(pwd)":/root/shared ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
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```
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This image can also be used as a normal docker container by adding:
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```bash
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docker run --ti -v "$(pwd)":/root/shared --entrypoint="/bin/bash" ghcr.io/jorgensd/dolfinx-tutorial:v0.7.1
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docker run --ti -v "$(pwd)":/root/shared --entrypoint="/bin/bash" ghcr.io/jorgensd/dolfinx-tutorial:v0.7.2
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```
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The tutorials can also be exported as a notebook or PDF by clicking the ![Download](save.png)-symbol in the top right corner of the relevant tutorial. The notebook can in turn be used with a Python kernel which has DOLFINx.
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provides a definitive build recipe. As the DOLFINx docker images are hosted at Docker-hub, one can directly access the image:
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```
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docker run dolfinx/dolfinx:v0.7.1
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docker run dolfinx/dolfinx:v0.7.2
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```
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There are several ways of customizing a docker container, such as mounting volumes/sharing folder, setting a working directory, sharing graphical interfaces etc. See `docker run --help` for an extensive list.

pyproject.toml

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[build-system]
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requires = ["setuptools>=64.4.0", "wheel", "pip>=22.3"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "DOLFINx_Tutorial"
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version = "0.7.2"
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dependencies = ["jupyter-book",
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# Pin docutils due to https://github.com/executablebooks/jupyter-book/issues/1970#issuecomment-1466051277
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"docutils==0.17.1",
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"meshio",
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"h5py",
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"seaborn",
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"pandas",
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"tqdm",
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"pyvista[all]@git+https://github.com/pyvista/pyvista",
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"fenics-dolfinx>=0.7.0"
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]
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[project.optional-dependencies]
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dev = [
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"pdbpp",
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"ipython",
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]
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[tool.setuptools]
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packages = []

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