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Top 23 Ipython Open-Source Projects
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ipython
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
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powerline
Powerline is a statusline plugin for vim, and provides statuslines and prompts for several other applications, including zsh, bash, tmux, IPython, Awesome and Qtile.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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hydrogen
:atom: Run code interactively, inspect data, and plot. All the power of Jupyter kernels, inside your favorite text editor.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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jupyterlab-lsp
Coding assistance for JupyterLab (code navigation + hover suggestions + linters + autocompletion + rename) using Language Server Protocol
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ipyvizzu
Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.
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watermark
An IPython magic extension for printing date and time stamps, version numbers, and hardware information
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
If you’re already using ipython, this isn’t a problem because you’ll already need to download most of these dependencies anyway. But if you’re not using ipython… you’ll still need to download those dependencies.
See https://github.com/jupyter/docker-stacks
Project mention: The free pandas visualizer, D-Tale, has now been integrated with ArcticDB which will allow users to load huge datasets and easily navigate their databases | /r/algotrading | 2023-07-06[D-Tale](https://github.com/man-group/dtale) has recently released version 3.2.0 on pypi & conda-forge: ``` pip install -U dtale conda install dtale -c conda-forge ``` But if you want to take it one step further you can now integrate it with [ArcticDB](https://github.com/man-group/ArcticDB): ``` pip install -U dtale[arcticdb] ``` This allows you the ability to navigate your libraries of datasets saved to your ArcticDB database! But the best part is that all the reads are occuring directly against ArcticDB so some of the memory constraints you may have been hit with before are now a thing of the past. Here's a full write up how to use this functionality along with a quick demo: https://github.com/man-group/dtale/blob/master/docs/arcticdb/ARCTICDB\_INTEGRATION.md Hope this helps & please support open-source by throwing your star on the [repo](https://github.com/man-group/dtale). Thanks! 🙏
Hydrogen got an update to fix this issue, but it was never published on Pulsar's backend. You can install it with pulsar -p https://github.com/nteract/hydrogen.git -t v2.16.5
Project mention: Spreadsheet errors can have disastrous consequences – yet we keep making them | news.ycombinator.com | 2024-01-25What are some Software Development methods for reducing errors:
1. AUTOMATED TESTS; test assertions
To write spreadsheet tests:
A. Write your own test assertion library for their macro language; write assertEqual() in VBscript and Apps Script.
B. Use another language with a test library and a test runner; e.g. Python and the `assert` keyword, unittest.TestCase().assertEqual() or pytest.
C. Test the spreadsheet GUI with something like AutoHotKey.
From https://news.ycombinator.com/item?id=35896192 :
> The Scientific Method is testing, so testing (tests, assertions, fixtures) should be core to any scientific workflow system.
> awesome-jupyter#testing: https://github.com/markusschanta/awesome-jupyter#testing
> ml-tooling/best-of-jupyter lists papermill/papermill under "Interactive Widgets/Visualization" https://github.com/ml-tooling/best-of-jupyter#interactive-wi...
Project mention: What python library you are using for interactive visualisation?(other than plotly) | /r/datascience | 2023-06-01didn't see anyone mention bqplot https://github.com/bqplot/bqplot
I simply use the superb pudb. Press ctrl+e to open the current file at the current line in your editor.
I had a lot of long input-related hang ups using the base R shell when a lot of code was involved and I never had an issue like that after I switched to radian. It is supported (and recommended) by the VSCode R extension and just much easier to use w/ long blocks of code.
Why not just use Python’s built-in pdb debugger or another existing one like ipdb or pdbpp?
Currently it's part of euporie-notebook, but I'm planning on splitting it out and publishing the web-browser as an independent project.
Project mention: IPyVizzu: Build animated charts with simple Python syntax | news.ycombinator.com | 2024-03-24
Self plug. If you're looking for something less-integrated into JupyterLab (with support for ipython and Jupyter Notebooks), check out: https://github.com/santiagobasulto/ipython-gpt
I wrote the package to solve my own issue, I need a really lightweight interface to GPT and primarily from ipython.
Ipython related posts
- CalcPy: Terminal calculator and advanced math solver (Python, IPython, SymPy)
- The new pdbp (Pdb+) Python debugger!
- Trouble with Hydrogen Plug-In (error text included)
- vim-replica: enjoy Jupyter with Vim 9.0!
- Show HN: ICortex: LLM Powered Python Interpreter
- Neovim workflow for machine learning / data scientist. Struggling with jupyter notebooks.
- Interactive evaluation: demo [2 Mb gif]
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A note from our sponsor - InfluxDB
www.influxdata.com | 24 Apr 2024
Index
What are some of the best open-source Ipython projects? This list will help you:
Project | Stars | |
---|---|---|
1 | ipython | 16,134 |
2 | powerline | 14,189 |
3 | docker-stacks | 7,738 |
4 | Jupyter Notebook (IPython) | 7,573 |
5 | nteract | 6,151 |
6 | dtale | 4,539 |
7 | hydrogen | 3,903 |
8 | awesome-jupyter | 3,764 |
9 | bqplot | 3,550 |
10 | doitlive | 3,398 |
11 | pudb | 2,866 |
12 | radian | 1,913 |
13 | PyInquirer | 1,888 |
14 | ipdb | 1,812 |
15 | jupyterlab-lsp | 1,730 |
16 | euporie | 1,449 |
17 | nbstripout | 1,138 |
18 | pyheatmagic | 1,020 |
19 | ipyvizzu | 923 |
20 | watermark | 864 |
21 | ipyida | 687 |
22 | ipykernel | 613 |
23 | ipython-gpt | 597 |
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