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https://lists.gnu.org/archive/html/emacs-devel/2011-02/msg00710.html

# Re: A new major-mode for Python From: Fabian Ezequiel Gallina Subject: Re: A new major-mode for Python Date: Wed, 16 Feb 2011 03:46:47 -0300 2011/2/15 Stefan Monnier <address@hidden>: >> I have come up with a *new* major-mode[1] for Python > > Help!!! > > More seriously. Rather than a new python mode I'm interested in > a maintainer for our python mode (i.e. someone who will fix bugs in it, > add new features, and will accept to work with us when we want to make > changes that he does not like, typica

https://discourse.julialang.org/t/fitting-mixed-effects-models-python-julia-or-r/74955

I’ve written a blog post bench-marking Julia, Python and R when fitting a mixed effects model. Julia comes out top (by quite a bit!), so if you ever need to convince someone, hopefully this will help

https://www.itzhai.com/tags/Python/index.html

标签为Python的文章

https://memotut.com/en/52c4addd1c4818b93ff2/

Python, math, python3

https://koji.fedoraproject.org/koji/taskinfo?taskID=1939019

Packages Builds Tags Build Targets Users Hosts RPMs - Summary - Packages - Builds - Tasks - Tags - Build Targets - Users - Hosts - Reports - Search - API #### Information for task buildSRPMFromSCM (/cvs/pkgs:rpms/python/devel:python-2_6_4-8_fc13) ID 1939019 Method buildSRPMFromSCM Parameters Build tag: dist-f13-build Url: cvs://cvs.fedoraproject.org/cvs/pkgs?rpms/python/devel#python-2_6_4-8_fc13 Options: repo_id = 99659 State closed Created Fri, 22 Jan 2010 15:49:50 UTC Completed Fri, 22 Jan 2010

https://towardsdatascience.com/k-means-clustering-a-comprehensive-guide-to-its-successful-use-in-python-c3893957667d/

Explanation of K-Means algorithm with a Python demonstration on real-life data

https://discuss.circleci.com/t/parallel-stock-python-unit-tests-with-2-0/24121

I read this (https://circleci.com/docs/2.0/parallelism-faster-jobs/) but it’s not clear how the circleci tool helps me in Python, where you don’t really use filename globbing to identify and split up tasks. circleci 1

http://prometheus.github.io/client_python/instrumenting/labels/

All metrics can have labels, allowing grouping of related time series. See the best practices on naming and labels. Taking a counter as an example: from prometheus_client import Counter c = Counter('my_requests_total', 'HTTP Failures', ['method', 'endpoint']) c.labels('get', '/').inc() c.labels('post', '/submit').inc() Labels can also be passed as keyword-arguments: from prometheus_client import Counter c = Counter('my_requests_total', 'HTTP Failures', ['method', 'endpoint']) c.labels(method='get', endpoint

https://precice.discourse.group/t/numpy-error-when-installing-precice-python-bindings/2555

I am facing an issue while installing pyprecice using pip. Here are some of the details for context. I have created a fresh environment in conda and am installing all necessary python packages inside it. OS: Linux (dis

https://discourse.numenta.org/t/python-3-migration-tms-not-matching/3395

I’m debugging an issue I have with backtracking_tm_cpp2_test.py. I set the verbosity to 10 and I get the following output. Can someone spot what is going wrong? D:\nupic\src\python\python3\tests\unit\nupic\algorithms>py

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