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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第十二章
Python 在 Smesh 的角色
我們廣泛地使用 Python —平台與服務的大部分都是以 Python 打造的，Python 所提供的
各種程式庫、工具，和框架讓我們全面地將它運用在工作上。
那種多樣性讓我們能夠（希望）為我們的工作挑選合適的工具。例如，我們已經使用
Django、Flask 與 Pyramid 建立 app，每個工具都有它的優點，我們能夠針對手頭上的
工作挑選正確的工具。我們使用 Celery 處理任務；使用 Boto 與 AWS 互動；並且使用
PyMongo、MongoEngine、redis-py、Psycopg 等來處理我們的各種資料需求。種種例
子，不勝枚舉。
平台
我們的主要平台包含為資料輸入、過濾、聚集、及處理提供掛鉤（hook）的中央 Python
模組，以及各種其他的核心功能。專案特定的程式碼從該核心匯入功能性，然後實作更
具體的資料處理與視圖邏輯，根據每個應用程式的需要而客製化。
目前為止，這個平台運作得相當順利，讓我們無需重複花費很多功夫，就能夠建造從各
種來源擷取及處理資料的複雜應用程式，然而，它也不是沒缺點—每個應用程式皆倚賴
共用的核心模組，使得更新該模組的程式碼以及讓使用它的應用程式維持在最新狀態，
變成是一項最主要的任務。
我們目前正在執行專案，重新設計該核心軟體，並且將它改變成服務導向的架構
（service-oriented architecture，SoA）。隨著平台成長，尋找正確時機進行這種架構更
動，似乎是大多數軟體團隊會面臨的巨大挑戰之一。將元件打造成個別服務有它的成本 ...
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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.