bpython
papermill
bpython | papermill | |
---|---|---|
15 | 26 | |
2,563 | 5,656 | |
1.1% | 1.0% | |
5.5 | 8.0 | |
24 days ago | 27 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
bpython
- Our Team's Favourite Open Source Projects Right Now
- REPL Driven Python
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What packages replaced standard library modules in your workflow?
bpython over built-in Python interpreter
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What dev tools do you use in your python projects?
Yeah, also it's worth to mention bpython
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can I get syntax highlighting for python shell?
I use bpython, its a pretty cool python REPL, try it out
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Release of IPython 8.0
Yeah, mostly I lack time to catch up with Jonathan Slenders works, and have stronger backward compatibility requirements. b=But ptpython and pyipython are both great.
I should also look into Rich and Textual
https://bpython-interpreter.org/ is also another alternative python shell, and of course https://xon.sh
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Who needs a calculator?
It's a nicer repl for python.
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Need help setting up python on arch linux
Python comes with IDLE as /usr/bin/idle but it doesn't have a corresponding .desktop file that would let it appear in the application menu. Otherwise, /usr/bin/python has an interactive mode and bpython is a wrapper around that interactive mode that has like syntax highlighting, indenting, undo, etc.
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Easiest Django Shell/Terminal
So, in this article, we will discuss bpython-django a fork from bpython that handles Django in a better way, currently it handles Models and can be extended as desired.
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PyCharm console
Someone posted bpython which I'm pretty ecstatic about but always good to know options.
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?
ptpython - A better Python REPL
nbconvert - Jupyter Notebook Conversion
Jupyter Notebook (IPython) - Multi-user server for Jupyter notebooks
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
airflow-notebook - This repository is no longer maintained.
Spyder - Official repository for Spyder - The Scientific Python Development Environment
nbdev - Create delightful software with Jupyter Notebooks
xonsh - :shell: Python-powered, cross-platform, Unix-gazing shell.
voila - Voilà turns Jupyter notebooks into standalone web applications
jupyter_console - Jupyter Terminal Console
jupytext - Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts