July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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B.4
IPython
での生産的コード開発に向けたヒント
543
Function: call_function at line 8
Total time: 0.121016 s
Line # Hits Time Per Hit % Time Line Contents
==============================================================
8 def call_function():
9 1 57169 57169.0 47.2 x = randn(1000, 1000)
10 1 58304 58304.0 48.2
y = randn(1000, 1000)
11 1 5543 5543.0 4.6 return add_and_sum(x, y)
著者の経験からは、
%prun(cProfile)
で目的とするのはいわば「マクロ」のプロファイリングで、一方
%lprun(line_profiler)
では「ミクロ」のプロファイリングを目的とします。この
2
つのツールを使いこ
なし、効率的な開発に役立ててください。
なぜ
%lprun
で
はプロファイルしたい関数名を明示的に指定する必要があるのでしょうか。こ
れは、実際に関数内の各行をトレースする実行時間オーバーヘッドが馬鹿にならないためで
す。興味のない関数内までもトレースしていると、プロファイリング結果を大幅に変動させ
てしまうのです。
B.4
IPython
での生産的コード開発に向けたヒント
コ
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