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UCL for Code in Research
Peter Schmidt
20 episodes
3 weeks ago
In this last episode of this course, I talk to Itamar Turner-Trauring who created the website PythonSpeed and spent a considerable time on finding ways to make Python code faster and more efficient. Python and its ecosystem also have great tools how you can measure performance. Links: https://pythonspeed.com a set of articles and recommendations on how to improve your performancehttps://blog.sentry.io/python-performance-testing-a-comprehensive-guide/ a general blog post on performance testing...
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All content for UCL for Code in Research is the property of Peter Schmidt and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
In this last episode of this course, I talk to Itamar Turner-Trauring who created the website PythonSpeed and spent a considerable time on finding ways to make Python code faster and more efficient. Python and its ecosystem also have great tools how you can measure performance. Links: https://pythonspeed.com a set of articles and recommendations on how to improve your performancehttps://blog.sentry.io/python-performance-testing-a-comprehensive-guide/ a general blog post on performance testing...
Show more...
Technology
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TEASER: Research Computing with C++
UCL for Code in Research
16 minutes
1 year ago
TEASER: Research Computing with C++
Welcome to the new podcast from the Advanced Research Computing Centre of the University College London, UK. A companion podcast for courses on Research Computing at UCL.In this first season we'll be presenting the course on Research Computing with C++. And this short teaser explains how it all works. Have fun!Don't be shy - say HiThis podcast is brought to you by the Advanced Research Computing Centre of the University College London, UK. Producer and Host: Peter Schmidt
UCL for Code in Research
In this last episode of this course, I talk to Itamar Turner-Trauring who created the website PythonSpeed and spent a considerable time on finding ways to make Python code faster and more efficient. Python and its ecosystem also have great tools how you can measure performance. Links: https://pythonspeed.com a set of articles and recommendations on how to improve your performancehttps://blog.sentry.io/python-performance-testing-a-comprehensive-guide/ a general blog post on performance testing...