nbtopy
papermill
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nbtopy | papermill | |
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1 | 26 | |
2 | 5,630 | |
- | 1.4% | |
3.2 | 8.0 | |
10 months ago | 3 days ago | |
Python | Python | |
- | BSD 3-clause "New" or "Revised" License |
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nbtopy
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VS code interactive mode
I very often convert a downloaded directory of notebooks and convert them to python files so I can run them in VS Code interactive mode. So often, that I created this utility to facilitate that.
papermill
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Spreadsheet errors can have disastrous consequences – yet we keep making them
Pandas docs > Comparison with spreadsheets: https://pandas.pydata.org/docs/getting_started/comparison/co...
Pandas docs > I/O > Excel files: https://pandas.pydata.org/docs/user_guide/io.html#excel-file...
nteract/papermill: https://github.com/nteract/papermill :
> papermill is a tool for parameterizing, executing, and analyzing Jupyter Notebooks. [...]
> This opens up new opportunities for how notebooks can be used. For example:
> - Perhaps you have a financial report that you wish to run with different values on the first or last day of a month or at the beginning or end of the year, using parameters makes this task easier.
"The World Excel Championship is being broadcast on ESPN" (2022) https://news.ycombinator.com/item?id=32420925 :
> Computational notebook speedrun ideas:
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Jupyter Kernel Architecture
There is Papermill ... https://github.com/nteract/papermill
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Git and Jupyter Notebooks Guide
https://github.com/jupyter/enhancement-proposals/pull/103#is...
Papermill is one tool for running Jupyter notebooks as reports; with the date in the filename. https://papermill.readthedocs.io/en/latest/
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JupyterLab 4.0
You may be interested in papermill to address the parametrized analysis problem [1]. I think (but I'm not positive) this is what the data team at a previous job used to automate running notebooks for all sorts nightly reports.
[1] https://papermill.readthedocs.io/en/latest/#
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Show HN: Mercury – convert Jupyter Notebooks to Web Apps without code rewriting
I'm using Papermill to operationalize Notebooks (https://github.com/nteract/papermill), it e.g. also has airflow support. I'm really happy with papermill for automatic notebook execution, in my field it's nice that we can go very quickly from analysis to operations -- while having super transparent "logging" in the executed notebooks.
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What's the best thing/library you learned this year ?
papermill bcpandas fastapi
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Does the Jupyter API allow using Jupyter from the CL?
But you can execute your notebook using Jupyter-run or papermill.
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Running Jupyter notebooks in parallel
As a first option, we will use Papermill, which has a Python API that allows us to run different notebooks using some functions:
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Tips for using Jupyter Notebooks with GitHub
Papermill can also target cloud storage outputs for hosting rendered notebooks, execute notebooks from custom Python code, and even be used within distributed data pipelines like Dagster (see Dagstermill). For more information, see the papermill documentation.
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Three Tools for Executing Jupyter Notebooks
Papermill Source Code
What are some alternatives?
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
nbconvert - Jupyter Notebook Conversion
pretty-jupyter - Creates dynamic html report from jupyter notebook.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
nbviewer - nbconvert as a web service: Render Jupyter Notebooks as static web pages
airflow-notebook - This repository is no longer maintained.
docker-stacks - Ready-to-run Docker images containing Jupyter applications
nbdev - Create delightful software with Jupyter Notebooks
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
voila - Voilà turns Jupyter notebooks into standalone web applications
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows