If you don't want to drag-and-drop or you chose Jupyter notebooks (classic notebook interface) make a text file and paste in the content you showed. It will get a gray dashed line around it when you have dragged it to the right place. I'd suggest JupyterLab as the steps outline below are made easier as you have the file navigation pane on the left.Īfter your session spins up in your browser, if you chose JupyterLab, drag your file from your local machine into the file navigation pane on the left side. Go to Try Jupyter and select either 'JupyterLab' or 'Jupyter Notebook' from the offerings presented. You can use Jupyter running in your browser and backed by a free Jupyter community-run service to view the notebook file as an active notebook, on what is equivalent to a temporary remote machine. This rendering form is also very nice for sharing with non-programmers as the GitHub cruft is not surrounding the content. In fact, although it is technically 'static', nbviewer can render some interactive Plotly plots and widget controls that enable playing back animations comprised of frames. If the notebook can be posted to Github (repository or gist) or online, you can point nbviewer at it and have it rendered nicely. It would provide you with a link to view the notebook you have and can be private if you limit sharing the link. Similarly, you can upload it to the notebookspace which is billed as "the fastest way to share your notebooks". It remains in your browser's local cache so it is useful for sensitive stuff that cannot be public. When you go there it asks you to choose a local file. One of the easiest ways to just view a notebook file that is also 100% secure in case what you are being sent is sensitive: nbpreview.
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