August 2015
Intermediate to advanced
384 pages
7h 42m
Chinese
Content preview from 高效能PYTHON程式設計
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我們的結果顯示，呼叫
calc_pure_python
的總成本為 13.1 秒（最好的情況），而先前以
@timefn
裝飾器量測到單一的
calculate_z_serial_purepython
呼叫花費 12.2 秒，主要的
差異是建立
zs
與
cs
串列所花費的時間。
在 IPython 裡，我們能夠以相同的方式使用神奇的
%timeit
。假如你正在 IPython 裡以互
動的方式開發你的程式碼，而函式位在區域的名稱空間中（可能因為你在使用
%run
），
那麼，你就可以使用︰
%timeit calc_pure_python(desired_width=1000, max_iterations=300)
值得考量一般電腦上的負載變異，許多在背景執行的任務（例如，Dropbox、backups）
都會隨機地影響 CPU 與磁碟資源。網頁裡的指令稿也會引起無可預測的資源耗用。圖
2-4 顯示單一 CPU 因為我們所執行的某些計時步驟而達到 100% 的使用率；而此機器上
的其他核心則各自輕鬆地處理其他任務。
圖 2-4 Ubuntu 上的 System Monitor 顯示在計時我們的函式時的 CPU 使用率變化
偶爾，System Monitor 顯示出機器上的活動尖峰，最好觀察你的 System Monitor，確認
沒有其他東西在干擾你的重要資源（CPU，磁碟，網路）。
使用 Unix 的 time 指令做簡單的計時
我們可以暫時離開 Python，使用類 Unix 系統上的標準系統工具。下面內容將針對程式 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.