bambi
pdbpp
| bambi | pdbpp | |
|---|---|---|
| 5 | 9 | |
| 1,013 | 1,249 | |
| 0.9% | 0.7% | |
| 8.0 | 0.0 | |
| 5 days ago | 17 days ago | |
| Python | Python | |
| MIT License | 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.
bambi
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Bayesian Structural Equation Modeling using blavaan
It is much less challenging with Bambi[1] and brms[2].
[1] https://bambinos.github.io/bambi/ -
Ask HN: What Are You Learning?
I’m trying to learn statistics. I’m up to implementing regressions in python using sci-kit learn.
I was playing around with Bayesian modelling last night with https://bambinos.github.io/bambi/ But I’m not really sure how to interpret the outputs.
Always open to reading about learning resources/books/videos/courses from others.
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how can I build a regression model which is penalised for moving away from an assumed set of coefficients?
I would suggest using Python's bambi; it is based on PyMC and it is very straightforward to use. We simply define our priors argument as a dictionary (quite literally: my_priors = {"feature_1": bmb.Prior("Normal", mu=4, sigma=4), "feature_n": bmb.Prior("Normal", mu=0.4, sigma=0.4)}) when creating our Bambi Model object and we are ready to go. They have a lot of worked exampling in their website.
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Which not so well known Python packages do you like to use on a regular basis and why?
For those interested in Bayesian modeling in Python we also have Bambi https://github.com/bambinos/bambi
- Release Bambi 0.6.0 · bambinos/bambi
pdbpp
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The new pdbp (Pdb+) Python debugger!
Why not just use Python’s built-in pdb debugger or another existing one like ipdb or pdbpp?
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Show HN: Clamshell- an experimental Python based shell
I like pdbpp. Make sure to install from source as there hasn’t been a release in a while.
https://github.com/pdbpp/pdbpp
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Useful Python Modules for us
pdbpp: Improved pdb boltons: assorted python addtions twisted: event driven networking framework sorcery: Dark magic in python, things know where+how they are being called, helps reducing boilerplate sh: Better alternative for subprocess module, much more pythonic taskipy: npm run scipt_name like functionality snoop: pdb lite, record+replay function steps birdseye: graphical debugger remote-pdb: easy pdb from inside containers typer: wrapper around click for simpler code for CLIs arrow: Always TZ aware datetimes, plus more features more-itertools: more functions for iterators pydantic: data validation + dataclasses loguru: better logging notifiers: sending notifications from python
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For whose use Emacs and VS Code, when and why you use VSCode? #emacs #vscode
If you want to use pdbpp, install it into your Python environment you're using the debugger from and it'll automatically hook itself into pdb with no additional setup.
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What Python debugger do you use?
I love pdbpp
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Which not so well known Python packages do you like to use on a regular basis and why?
pdbpp feels like getting super powers over using pdb
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What dev tools do you use in your python projects?
Most of the tools and libraries I use have been mentioned, but I haven’t seen pdb++ brought up. It’s like ipython for debugging!
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Debug in VIM
Improved version of built-in debugger: https://github.com/pdbpp/pdbpp
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Icecream: Never use print() to debug again in Python
I like to use PDB++ which is a drop in replacement for PDB
https://github.com/pdbpp/pdbpp
What are some alternatives?
deffcode - A cross-platform High-performance FFmpeg based Real-time Video Frames Decoder in Pure Python 🎞️⚡
ipdb - Integration of IPython pdb
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
pudb - Full-screen console debugger for Python
mistletoe - A fast, extensible and spec-compliant Markdown parser in pure Python.
pdbr - pdb + Rich library
vimtk - A vim toolkit focused on gvim, IPython, and the terminal.
PySnooper - Never use print for debugging again
pyroute2 - Python Netlink and PF_ROUTE library — network configuration and monitoring
python-devtools - Dev tools for python
static-frame - Immutable and statically-typeable DataFrames with runtime type and data validation
snoop - A powerful set of Python debugging tools, based on PySnooper