- IPython Interactive Computing and Visualization Cookbook（Second Edition）
- Cyrille Rossant
- 133字
- 2021-07-02 16:23:35
Introduction
Although Python is not generally considered one of the fastest language (which is somewhat unfair), it is possible to achieve excellent performance with the appropriate methods. This is the objective of this chapter and the next. This chapter describes how to evaluate (profile) what makes a program slow, and how this information can be used to optimize the code and make it more efficient. The next chapter will deal with more advanced high-performance computing methods that should only be tackled when the methods described here are not sufficient.
The recipes of this chapter are organized into three parts:
- Time and memory profiling: Evaluating the performance of your code
- NumPy optimization: Using NumPy more efficiently, particularly with large arrays
- Memory mapping with arrays: Implementing memory mapping techniques for out-of-core computations on huge arrays
推薦閱讀
- 在你身邊為你設(shè)計Ⅲ：騰訊服務(wù)設(shè)計思維與實戰(zhàn)
- Spark快速大數(shù)據(jù)分析（第2版）
- 分布式數(shù)據(jù)庫系統(tǒng)：大數(shù)據(jù)時代新型數(shù)據(jù)庫技術(shù)（第3版）
- 大數(shù)據(jù)導(dǎo)論
- Learn Unity ML-Agents：Fundamentals of Unity Machine Learning
- 數(shù)字媒體交互設(shè)計（初級）：Web產(chǎn)品交互設(shè)計方法與案例
- Spark大數(shù)據(jù)分析實戰(zhàn)
- 圖數(shù)據(jù)實戰(zhàn)：用圖思維和圖技術(shù)解決復(fù)雜問題
- 重復(fù)數(shù)據(jù)刪除技術(shù)：面向大數(shù)據(jù)管理的縮減技術(shù)
- 數(shù)據(jù)庫應(yīng)用系統(tǒng)開發(fā)實例
- 一本書講透Elasticsearch：原理、進階與工程實踐
- 數(shù)字IC設(shè)計入門（微課視頻版）
- The Natural Language Processing Workshop
- Microsoft Dynamics NAV 2015 Professional Reporting
- AndEngine for Android Game Development Cookbook