How to manage Python dependencies in a Jupyter Notebook environment?
Asked 7 months ago
As a data scientist, I rely quite heavily on Jupyter Notebooks for my data analysis work. However, I have found managing dependencies within a Jupyter environment to be somewhat challenging. What's your recommended approach for me to handle Python library dependencies effectively within my Jupyter Notebook projects?
Kasey Ware
Tuesday, October 03, 2023
There are multiple ways to manage Python dependencies in Jupyter Notebooks, though it would be best to do so by using a tool like `pipenv`.
pip install pipenv
Run the following command to initialize a virtual environment for your project, creating a `Pipfile` to manage your dependencies. pipenv --python 3.x
Remember to replace "3.x" with your desired Python version. Then, simply use `pipenv` to install the dependencies and Python packages in your project.
Finally, launch your Jupyter Notebook from your project directory:pipenv run jupyter notebook
This ensures that your notebook runs within the isolated environment using the dependencies you've installed.
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