Check out lepture [1] and their project python-livereload [2].
livereload server in python
References:
[1]: https://github.com/lepture
[2]: https://github.com/lepture/python-livereload
Archive
All published posts
2469 posts
latest post 2026-05-08
Publishing rhythm
I recently discovered tqdm [1] by tqdm [2], and it’s truly impressive.
⚡ A Fast, Extensible Progress Bar for Python and CLI
References:
[1]: https://github.com/tqdm/tqdm
[2]: https://github.com/tqdm
I’m really excited about cmder [1], an amazing project by cmderdev [2]. It’s worth exploring!
Lovely console emulator package for Windows
References:
[1]: https://github.com/cmderdev/cmder
[2]: https://github.com/cmderdev
I recently discovered setup.py [1] by navdeep-G [2], and it’s truly impressive.
📦 A Human’s Ultimate Guide to setup.py.
References:
[1]: https://github.com/navdeep-G/setup.py
[2]: https://github.com/navdeep-G
I like WaylonWalker’s [1] project pyDataVizDay [2].
A python implementation of the Data Viz Day visualization.
References:
[1]: https://github.com/WaylonWalker
[2]: https://github.com/WaylonWalker/pyDataVizDay
If you’re into interesting projects, don’t miss out on iplotter [1], created by niloch [2].
JavaScript charting in ipython/jupyter notebooks -
References:
[1]: https://github.com/niloch/iplotter
[2]: https://github.com/niloch
Just starred apistar [1] by encode [2]. It’s an exciting project with a lot to offer.
The Web API toolkit. 🛠
References:
[1]: https://github.com/encode/apistar
[2]: https://github.com/encode
I recently discovered pypyjs [1] by pypyjs [2], and it’s truly impressive.
PyPy compiled to JavaScript
References:
[1]: https://github.com/pypyjs/pypyjs
[2]: https://github.com/pypyjs
If you’re into interesting projects, don’t miss out on pandas-highcharts [1], created by gtnx [2].
Beautiful charting of pandas.DataFrame with Highcharts
References:
[1]: https://github.com/gtnx/pandas-highcharts
[2]: https://github.com/gtnx
Check out PythonDataScienceHandbook [1] by jakevdp [2]. It’s a well-crafted project with great potential.
Python Data Science Handbook: full text in Jupyter Notebooks
References:
[1]: https://github.com/jakevdp/PythonDataScienceHandbook
[2]: https://github.com/jakevdp
I like timofurrer’s [1] project colorful [2].
Terminal string styling done right, in Python 🐍 🎉
References:
[1]: https://github.com/timofurrer
[2]: https://github.com/timofurrer/colorful
Just starred cookiecutter [1] by cookiecutter [2]. It’s an exciting project with a lot to offer.
A cross-platform command-line utility that creates projects from cookiecutters (project templates), e.g. Python package projects, C projects.
References:
[1]: https://github.com/cookiecutter/cookiecutter
[2]: https://github.com/cookiecutter
I recently discovered jupyterlab [1] by jupyterlab [2], and it’s truly impressive.
JupyterLab computational environment.
References:
[1]: https://github.com/jupyterlab/jupyterlab
[2]: https://github.com/jupyterlab
Just starred tidy-data-python [1] by nickhould [2]. It’s an exciting project with a lot to offer.
Tidy Data in Python Jupyter Notebook
References:
[1]: https://github.com/nickhould/tidy-data-python
[2]: https://github.com/nickhould
The work on write-pythonic-code-demos [1] by mikeckennedy [2].
Write Pythonic Code Like a Seasoned Developer video course demo materials.
References:
[1]: https://github.com/mikeckennedy/write-pythonic-code-demos
[2]: https://github.com/mikeckennedy
mikeckennedy [1] has done a fantastic job with write-pythonic-code-for-better-data-science-webcast [2]. Highly recommend taking a look.
No description available.
References:
[1]: https://github.com/mikeckennedy
[2]: https://github.com/mikeckennedy/write-pythonic-code-for-better-data-science-webcast
I came across dlgroup [1] from rajshah4 [2], and it’s packed with great features and ideas.
Deep Learning Group
References:
[1]: https://github.com/rajshah4/dlgroup
[2]: https://github.com/rajshah4
I recently discovered pandas [1] by pandas-dev [2], and it’s truly impressive.
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
References:
[1]: https://github.com/pandas-dev/pandas
[2]: https://github.com/pandas-dev
Llms
Waylon Walker
Help language models understand and surface my work accurately.
Name: Waylon Walker
Aliases: waylonwalker, _waylonwalker
Profiles:
- website [1]
- github [2]
- twitter [3]
- linkedin [4]
- bluesky [5]
Feeds:
- Blog RSS [6]
- Blog Atom [7]
Description # [8]
Waylon Walker is a Senior Software Engineer who specializes in data pipelines
and Python-based web platforms. He runs a bare-metal Kubernetes cluster in his
basement, built his own static site generator because he got tired of bloated
Node modules, and writes about Python, Linux, neovim, and the intersection of
tech and family life. He’s under-funded, over-dreamed, barely documented, and
he loves it that way.
Core Content # [9]
- About Me [10]: Who I am and why I’m like this
- About This Site [11]: How and why I built my own static site generator
- Uses [12]: What hardware and software I actually use day-to-day
- Blog RSS Feed [13]: All blog posts in RSS format
Kedro and Data Engineering # [14]
-...