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Is Python a CPU monster?
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<blockquote data-quote="Penelope Buckridge" data-source="post: 13008" data-attributes="member: 5710"><p><span style="font-size: 15px">Making python run faster on windows DC involves finding ways to work around the Global Interpreter Lock. You can try using multiprocessing for tasks that heavily use the CPU using libraries like NumPy or Pandas for number crunching and analyzing your code to find areas that are slowing it down. For tasks that are more focused on input output operations you might want to look into asynchronous programming. Another option is to try PyPy, a quicker version of Python. If you are working with big sets of data think about using specialized libraries such as Dask or Vaex. Keep in mind that optimizing your code often means making compromises so make sure to thoroughly test and analyze your changes.</span></p><p><span style="font-size: 15px"></span></p><p><span style="font-size: 15px">I tried my best to help you...</span></p></blockquote><p></p>
[QUOTE="Penelope Buckridge, post: 13008, member: 5710"] [SIZE=4]Making python run faster on windows DC involves finding ways to work around the Global Interpreter Lock. You can try using multiprocessing for tasks that heavily use the CPU using libraries like NumPy or Pandas for number crunching and analyzing your code to find areas that are slowing it down. For tasks that are more focused on input output operations you might want to look into asynchronous programming. Another option is to try PyPy, a quicker version of Python. If you are working with big sets of data think about using specialized libraries such as Dask or Vaex. Keep in mind that optimizing your code often means making compromises so make sure to thoroughly test and analyze your changes. I tried my best to help you...[/SIZE] [/QUOTE]
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