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    How to Setup Jupyter in Pipenv / Poetry

    August 11, 2021  |  3 min read  |  496 views

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    I tend to forget how to setup Jupyter in a newly created Poetry / Pipenv environment, so I leave a note here. It contains four ways to setup Jupyter: [Poetry, Pipenv] x [Native Jupyter, VSCode].

    Poetry

    Let’s say you’re going to use NumPy in your project. With Poetry, you can create a new virtual environment and install dependencies in the following commands:

    $ poetry init
    $ poetry add numpy # libraries you want to use
    $ poetry add -D jupyter # libraries for development use only

    poetry add -D jupyter installs all the packages required to use Jupyter (e.g., ipykernel). Now, pyproject.toml should look like below.

    pyproject.toml
    [tool.poetry]
    name = "poetry"
    version = "0.1.0"
    description = ""
    authors = [""]
    
    [tool.poetry.dependencies]
    python = "^3.8"
    numpy = "^1.21.1"
    
    [tool.poetry.dev-dependencies]
    jupyter = "^1.0.0"
    
    [build-system]
    requires = ["poetry-core>=1.0.0"]
    build-backend = "poetry.core.masonry.api"

    Now you are ready to go 🚀

    Native Jupyter

    The following command launches Jupyter server inside the virtual environment you just created.

    $ poetry run jupyter notebook

    If you are using globally installed Jupyter, create a kernel before launching Jupyter:

    $ poetry run ipython kernel install --user --name=<KERNEL_NAME>
    $ jupyter notebook

    And then select the created kernel in “Kernel” -> “Change kernel”.

    VSCode

    Sometimes it’s more confortable to open Jupyter notebooks in VSCode than in web browsers. In VSCode, you can select your preferred kernel without any additional commands.

    Click the “Python” button located near the bottom left corner and select the Python interpreter path.

    2021 08 11 10 37 17

    When settings are done, the selected interpreter is displayed in the top right corner.

    vscode

    Pipenv

    With Pipenv, you can do the same thing in the following commands:

    $ pipenv install numpy # libraries you want to use
    $ pipenv install --dev jupyter # libraries for development use only

    pipenv install --dev jupyter installs all the packages required to use Jupyter (e.g., ipykernel). Now, Pipfile should look like below.

    Pipfile
    [[source]]
    url = "https://pypi.org/simple"
    verify_ssl = true
    name = "pypi"
    
    [packages]
    numpy = "*"
    
    [dev-packages]
    jupyter = "*"
    
    [requires]
    python_version = "3.9"

    Now you are ready to go 🚀

    Native Jupyter

    The following command launches Jupyter server inside the virtual environment you just created.

    $ pipenv run jupyter notebook

    If you are using globally installed Jupyter, create a kernel before launching Jupyter:

    $ pipenv run ipython kernel install --user --name=<KERNEL_NAME>
    $ jupyter notebook

    And then select the created kernel in “Kernel” -> “Change kernel”.

    VSCode

    See the above VSCode section. It’s all the same.

    References

    [1] Python in Visual Studio Code – August 2021 Release | Python
    [2] Introduction | Documentation | Poetry - Python dependency management and packaging made easy
    [3] Pipenv: Python Dev Workflow for Humans — pipenv 2021.5.29 documentation


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