robmarkcole / Useful Python
Licence: mit
Python code and notebooks for reference
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Useful-python
Python code and Jupyter notebooks for reference.
Run locally with docker
Run a notebook server in docker, mounting in this directory with:
docker run --rm -p 8888:8888 \
-e JUPYTER_ENABLE_LAB=yes \
-e AWS_ACCESS_KEY_ID=xyz \
-e AWS_SECRET_ACCESS_KEY=aaa \
-v "$PWD":/home/jovyan/work \
--name jupyter \
jupyter/scipy-notebook:latest
Then run docker logs jupyter to extract the url & token and place these in your browser (something like http://127.0.0.1:8888/?token=33ebd), or use vscode to connect. When you are finished docker stop jupyter. Alternative environments are listed on https://github.com/jupyter/docker-stacks. I use scipy-notebook when only python is required, or datascience-notebook if R or Julia are required.
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