Is it possible to evaluate code in a jupyter notebook only within a certain section? Can you place a stopping point in the notebook, for example? Or delimit a section by headers?
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I was trying to using !date to print date-related information in jupyter notebook, but it seems that it just hang around there without running, what might be reason. I am using Anaconda virtual environment on windows.
In IPython syntax, the exclamation mark (!) allows users to run shell commands from inside a Jupyter Notebook code cell.
If you are on Windows, date will show the system data and allows you to set a new one. This doesn't make much sense from inside Jupyter Notebooks.
If you want to see the current date and time in IPython, instead use
import time
time.strftime("%c")
Say I have a simple notebook orchestration :
Notebook A -> Notebook B
Notebook A finish first then trigger Notebook B
I am wondering if there is an out of box method to allow Notebook A to terminate the entire job? (without running Notebook B).
Putting dbutils.notebook.exit in Notebook A will exit Notebook A but Notebook B still can run.
P.S.
Passing parameters between Notebooks to terminate all the down streamNotebooks one-by-one is an alternative solution but not ideal.
I want a solution to kill the job at the root Notebook.
And, I do not want to raise Exceptions in Notebook Aand kill the job by running into an "error" status.
As of now there is no way to stop the present cell after a successful run in "run all" scenario.
Additionally, you can always put an error in the cell where you want run all to stop since errors stop "run all".
Also, you can run all cells above and run all cells below. For example: If you want to run all cells up to cell X, go to cell X+1 and “run all cells above”.
I am learning how to do equation numbering using ams math in local Jupyter notebook. As per the documentation, it says to make changes in _config.yml file. But I am not sure where to find it on my Mac. If it helps, I have the file jupyter_notebook_config.py in ~/.jupyter directory. But they don't look the same.
Can I kindly get some help here (example'll be appreciated), how to work with _config.yml file. thanks in advance.
The documentation you linked to is for a project called jupyter-book. If you're using that, then, as #MattDMo said, follow the example from the tutorial and add the _config.yml in the folder that contains your book.
If you're using a regular Jupyter Notebook, you can disregard that and just write the LaTeX in a Markdown cell, where it will be rendered (by MathJax rather than MyST), without any extra config.
I am trying to test the speed of a cell's execution using "%%timeit" but it is not working as expected. All it ever prints is "`not found".
What's going on?
Here is a screenshot to show you what I see:
I am using python 3.6.10 and am using a jupyter notebook environment in vscode.
As the title suggests, I'm looking to find the run time for my entire Jupyter notebook.
Perhaps something like %%time for the entire notebook. Have tried looking around for a solution, but I can't seem to find one that doesn't require me to define a function.
Any help would be appreciated, thank you guys!
You can install and enable the Execute Time extension mentioned under section entitled '4. ExecuteTime: show when and how long cells ran', here. In the metadata, is the start_time and end_time for each cell, see here. You can use the start time for the first cell and the end_time for the last cell to give you the total time.
Alternatively, you can use an external call to run the notebook from another notebook and use %%time in that. For example to run the index.ipynb notebook, in a new notebook execute:
%%time
%run index.ipynb
You could use jupytext, papermill, or nbconvert to run the notebook instead of %run if you didn't want output displaying in your timing notebook. (I imagine the time to show that output might contribute and could matter in case of somethings you wish to time?) There is an example of using nbconvert and using the -t flag with the call to scripted version of the notebook to time it here.
Or you could use IPython to call to run the notebook and time this if you didn't want to use an actual separate Jupyter notebook since the %%time magic is inherited from IPython.