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here is the log from the commit of package python-emcee for openSUSE:Factory 
checked in at 2022-10-01 17:43:58
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-emcee (Old)
 and      /work/SRC/openSUSE:Factory/.python-emcee.new.2275 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Package is "python-emcee"

Sat Oct  1 17:43:58 2022 rev:6 rq:1007387 version:3.1.3

Changes:
--------
--- /work/SRC/openSUSE:Factory/python-emcee/python-emcee.changes        
2022-05-30 12:44:50.320461462 +0200
+++ /work/SRC/openSUSE:Factory/.python-emcee.new.2275/python-emcee.changes      
2022-10-01 17:44:24.409806564 +0200
@@ -1,0 +2,10 @@
+Wed Sep 28 14:06:25 UTC 2022 - Arun Persaud <a...@gmx.de>
+
+- specfile:
+  * be more specific in %file section
+
+- update to version 3.1.3:
+  * Pass on random generator to KDE resample method
+  * seed longdouble test
+
+-------------------------------------------------------------------

Old:
----
  emcee-3.1.2.tar.gz

New:
----
  emcee-3.1.3.tar.gz

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Other differences:
------------------
++++++ python-emcee.spec ++++++
--- /var/tmp/diff_new_pack.XtmRtR/_old  2022-10-01 17:44:24.869807400 +0200
+++ /var/tmp/diff_new_pack.XtmRtR/_new  2022-10-01 17:44:24.873807407 +0200
@@ -20,7 +20,7 @@
 # NEP 29: python36-numpy and -scipy are no longer available in TW
 %define         skip_python36 1
 Name:           python-emcee
-Version:        3.1.2
+Version:        3.1.3
 Release:        0
 Summary:        Python affine-invariant ensemble MCMC sampling
 License:        MIT
@@ -67,6 +67,7 @@
 %files %{python_files}
 %license LICENSE
 %doc AUTHORS.rst README.rst
-%{python_sitelib}/*
+%{python_sitelib}/emcee
+%{python_sitelib}/emcee-%{version}-py*.egg-info
 
 %changelog

++++++ emcee-3.1.2.tar.gz -> emcee-3.1.3.tar.gz ++++++
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' old/emcee-3.1.2/.pre-commit-config.yaml 
new/emcee-3.1.3/.pre-commit-config.yaml
--- old/emcee-3.1.2/.pre-commit-config.yaml     2022-05-10 17:20:45.000000000 
+0200
+++ new/emcee-3.1.3/.pre-commit-config.yaml     2022-09-27 22:03:48.000000000 
+0200
@@ -1,7 +1,7 @@
 
 repos:
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.2.0
+  rev: v4.3.0
   hooks:
   - id: trailing-whitespace
   - id: end-of-file-fixer
@@ -16,7 +16,7 @@
     exclude: docs/tutorials
 
 - repo: https://github.com/psf/black
-  rev: "22.3.0"
+  rev: "22.8.0"
   hooks:
   - id: black
 
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' old/emcee-3.1.2/PKG-INFO new/emcee-3.1.3/PKG-INFO
--- old/emcee-3.1.2/PKG-INFO    2022-05-10 17:20:57.214236000 +0200
+++ new/emcee-3.1.3/PKG-INFO    2022-09-27 22:04:02.255622600 +0200
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: emcee
-Version: 3.1.2
+Version: 3.1.3
 Summary: The Python ensemble sampling toolkit for MCMC
 Home-page: https://emcee.readthedocs.io
 Author: Daniel Foreman-Mackey
@@ -9,7 +9,6 @@
 Maintainer-email: foreman.mac...@gmail.com
 License: MIT
 Project-URL: Source, https://github.com/dfm/emcee
-Platform: UNKNOWN
 Classifier: Development Status :: 5 - Production/Stable
 Classifier: Intended Audience :: Developers
 Classifier: Intended Audience :: Science/Research
@@ -79,5 +78,3 @@
 
 emcee is free software made available under the MIT License. For details see
 the LICENSE file.
-
-
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' old/emcee-3.1.2/docs/index.rst 
new/emcee-3.1.3/docs/index.rst
--- old/emcee-3.1.2/docs/index.rst      2022-05-10 17:20:45.000000000 +0200
+++ new/emcee-3.1.3/docs/index.rst      2022-09-27 22:03:48.000000000 +0200
@@ -3,7 +3,7 @@
 
 **emcee** is an MIT licensed pure-Python implementation of Goodman & Weare's
 `Affine Invariant Markov chain Monte Carlo (MCMC) Ensemble sampler
-<https://msp.berkeley.edu/camcos/2010/5-1/p04.xhtml>`_ and these pages will
+<https://msp.org/camcos/2010/5-1/p04.xhtml>`_ and these pages will
 show you how to use it.
 
 This documentation won't teach you too much about MCMC but there are a lot
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' old/emcee-3.1.2/src/emcee/emcee_version.py 
new/emcee-3.1.3/src/emcee/emcee_version.py
--- old/emcee-3.1.2/src/emcee/emcee_version.py  2022-05-10 17:20:55.000000000 
+0200
+++ new/emcee-3.1.3/src/emcee/emcee_version.py  2022-09-27 22:04:02.000000000 
+0200
@@ -1 +1 @@
-__version__ = "3.1.2"
+__version__ = "3.1.3"
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' old/emcee-3.1.2/src/emcee/moves/kde.py 
new/emcee-3.1.3/src/emcee/moves/kde.py
--- old/emcee-3.1.2/src/emcee/moves/kde.py      2022-05-10 17:20:45.000000000 
+0200
+++ new/emcee-3.1.3/src/emcee/moves/kde.py      2022-09-27 22:03:48.000000000 
+0200
@@ -38,6 +38,6 @@
     def get_proposal(self, s, c, random):
         c = np.concatenate(c, axis=0)
         kde = gaussian_kde(c.T, bw_method=self.bw_method)
-        q = kde.resample(len(s))
+        q = kde.resample(len(s), random)
         factor = kde.logpdf(s.T) - kde.logpdf(q)
         return q.T, factor
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' 
old/emcee-3.1.2/src/emcee/tests/integration/test_longdouble.py 
new/emcee-3.1.3/src/emcee/tests/integration/test_longdouble.py
--- old/emcee-3.1.2/src/emcee/tests/integration/test_longdouble.py      
2022-05-10 17:20:45.000000000 +0200
+++ new/emcee-3.1.3/src/emcee/tests/integration/test_longdouble.py      
2022-09-27 22:03:48.000000000 +0200
@@ -9,6 +9,7 @@
     def log_prob(x, ivar):
         return -0.5 * np.sum(ivar * x**2)
 
+    np.random.seed(0)
     ndim, nwalkers = 5, 20
     ivar = 1.0 / np.random.rand(ndim).astype(np.longdouble)
     p0 = np.random.randn(nwalkers, ndim).astype(np.longdouble)
@@ -29,6 +30,7 @@
         assert x.dtype == np.longdouble
         return -0.5 * np.sum(((x - mjd) / sigma) ** 2)
 
+    np.random.seed(0)
     ndim, nwalkers = 1, 20
     steps = 1000
     p0 = sigma * np.random.randn(nwalkers, ndim).astype(np.longdouble) + mjd
diff -urN '--exclude=CVS' '--exclude=.cvsignore' '--exclude=.svn' 
'--exclude=.svnignore' old/emcee-3.1.2/src/emcee.egg-info/PKG-INFO 
new/emcee-3.1.3/src/emcee.egg-info/PKG-INFO
--- old/emcee-3.1.2/src/emcee.egg-info/PKG-INFO 2022-05-10 17:20:56.000000000 
+0200
+++ new/emcee-3.1.3/src/emcee.egg-info/PKG-INFO 2022-09-27 22:04:02.000000000 
+0200
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: emcee
-Version: 3.1.2
+Version: 3.1.3
 Summary: The Python ensemble sampling toolkit for MCMC
 Home-page: https://emcee.readthedocs.io
 Author: Daniel Foreman-Mackey
@@ -9,7 +9,6 @@
 Maintainer-email: foreman.mac...@gmail.com
 License: MIT
 Project-URL: Source, https://github.com/dfm/emcee
-Platform: UNKNOWN
 Classifier: Development Status :: 5 - Production/Stable
 Classifier: Intended Audience :: Developers
 Classifier: Intended Audience :: Science/Research
@@ -79,5 +78,3 @@
 
 emcee is free software made available under the MIT License. For details see
 the LICENSE file.
-
-

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