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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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4/10 On Polymorphism
UCL for Code in Research
26 minutes
10 months ago
4/10 On Polymorphism
Inheritance, templates, function overloading - they all fall into the category of polymorphism in programming. My guest Klaus Iglberger and I discuss the different aspects of how this could be done with C++. Links https://www.stroustrup.com/glossary.html#Gpolymorphism Glossary provided by Bjarne Stroustruphttps://cplusplus.com/doc/tutorial/polymorphism/https://ics.uci.edu/~jajones/INF102-S18/readings/05_stratchey_1967.pdf Christian Strachey's article where he introduces polymorphismhttp...
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...