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Micha Gorelick
Goodreads Author
Member Since
May 2012
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High Performance Python: Practical Performant Programming for Humans
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published
2013
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22 editions
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High Performance Python
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HIGH PERFORMANCE PYTHON 2/ED
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“Example 11-1. Measuring memory usage of 100,000,000 of the same integer in a list In [1]: %load_ext memory_profiler # load the %memit magic function In [2]: %memit [0]*int(1e8) peak memory: 790.64 MiB, increment: 762.91 MiB”
― High Performance Python: Practical Performant Programming for Humans
― High Performance Python: Practical Performant Programming for Humans
“If you’re working with a large array or matrix of numbers with Cython and you don’t want an external dependency on numpy, be aware that you can store your data in an array and pass it into Cython for processing without any additional memory overhead.”
― High Performance Python: Practical Performant Programming for Humans
― High Performance Python: Practical Performant Programming for Humans
“in computation there are two phases: generating data and transforming data. This function is very clearly performing a transformation on data, while the fibonacci function generates it. This clear demarcation adds extra clarity and extra functionality: we can move a transformative function to work on a new set of data, or perform multiple transformations on existing data. This paradigm has always been important when creating complex programs; however, generators facilitate this clearly by making generators responsible for creating the data, and normal functions responsible for acting on the generated data.”
― High Performance Python: Practical Performant Programming for Humans
― High Performance Python: Practical Performant Programming for Humans
