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pyro-ppl
pyro
Python2017–2025
pyro-ppl / pyro

pyro

Deep universal probabilistic programming with Python and PyTorch

8Distinct people
9Mentions
0Explicit recommenders
9.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Deep universal probabilistic programming with Python and PyTorch

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:03:16 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year9 dated mentions

Observed mentions: 2017-11-06 19:04:38 UTC to 2025-11-14 10:44:57 UTC.

01232017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 3 mentions; 0 submissions, 3 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20212022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC303
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC312
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC110
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC110

What Hacker News says

9 sources
This is a post from my Linkedin page on my hopes for Jupyter notebooks and git. Anyone know of progress along this line? #Jupyter notebook and git As much as Jupyter Notebooks have been a great tool for data science, the transition to deployment, and the general software engineering friendliness of Jupyter Notebooks could use some work. From time to time, I have explored how others have dealt with turning notebooks into an organized codebase and outputs. To date, I have not found a comfortable approach for me. The ideal approach for me would be to use something like 'node metadata' in the way of [Leo Editor](https://leo-editor.github.io/leo-editor/) to function as 'decorators' for a notebook cell for integration with git. By this I mean using something like special markers in Python comments (since much of data science is done with Python
Read the rest
) to map the content of a cell (or output) to a git repository. Better yet, define a special cell type for git metadata preceding a code cell. Then implement some basic git operations on the contents of a cell. Let's suppose we use @@git as a marker for metadata in comments for git. --- beginning of cell --- # @@git %upstream%=https://github.com/pyro-ppl/pyro # @@git %local%=~/repo/pyrodev # @@git %branch%=burnburnburn # @@git %file%=examples/cvae/util.py # Here begins the contents of the util.py file ... --- end of cell --- An extension would implement items in the menubar for various git operations: stage - stage the content as util.py file checkout - checkout from upstream, replace local copy, and refresh content of cell commit - commit stage file specified by %file% status - ... Imagined workflow is that once a working idea scattered throughout a notebook has been sketched out, the user would mark the notebook cells that should be mapped to files in a git repository. Also this could be used in a mixed dev/data science environment where library code under development can be pulled right into a notebook. Yes, there will be problems with committing code with comments that are specific to one user which is why a special cell type makes sense. Yes, there will be problems that I can't even imagine right now but ... Please message me if you know of a cell-based git extension for Jupyter Notebooks.
In The Jupyter+Git problem is now solved (2022)
I was not speaking about either, actually, https://github.com/uber/pyro/ and https://github.com/uber/horovod Im by no means a machine learning expert, but sometimes on a Sunday i'll pour myself a mug of coffee and go through some neat tutorial, and sometimes the stuff is Ubers. They are by no means free from criticism for their wrongs, but to ignore what they have done correctly paints the world far too simply.
In The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work
Another lesson about the dangers of relying on a separate team to maintain core part of your software. Not that using dependencies is a bad thing, but one should still be aware of what tradeoff they are making. In terms of a new backend, there's uber's pyro [1] that's based on pytorch, and then there's Edward [2] that's based on tensorflow (and I think recently got integrated into tensorflow repo). Would be interesting to see pyMC adopt MXNet as its backend. I'm sure Amazon will become a heavy user and might sponsor the development. Or at least the authors will be able to get jobs there without a whiteboarding interview phase. [1] https://github.com/uber/pyro [2] http://edwardlib.org/
In Theano and the Future of PyMC

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