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Python数据处理
book

Python数据处理

by Jacqueline Kazil, Katharine Jarmul
July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Posts & Telecom Press
Content preview from Python数据处理
自动化和规模化
303
器。你希望能够非常简单地管理和更新脚本和任务,并且可以定期运行脚本以完成任务。
最后,你还希望可以轻松地配置和文档化它们。在下面的几节中,我们会介绍所有这些主
题,从可以让你的脚本更加自动友好的
Python
工具开始。
14.5
 自动化的特殊工具
Python
提供了许多用于自动化的特殊工具。我们会查看一些使用
Python
管理自动化程序
的方法,同时也会使用其他的机器和服务器完成任务。我们还会讨论怎样使用一些内置的
Python
工具管理脚本的输入,自动化看起来需要人工输入的事情。
14.5.1
 使用本地文件
参数及配置文件
根据脚本的工作情况,你可能需要存储在数据库或
API
之外的参数或输入。当有一个简单
的输入或输出时,你可以使用本地文件和参数来传递数据。
1.
本地文件
使用本地文件作为输入和输出时,你需要确保脚本可以每天运行在相同的机器上,或者可
以简单地与输入和输出文件一起迁移。随着脚本的开发,很可能需要同时移动并改变脚本
和所用文件。
我们之前使用过本地文件,但是让我们看一下如何从更加函数式的代码的角度来使用它。
这段代码给了你使用标准数据类型打开和写文件的能力,并且根据脚本的需求,其复用性
和扩展性很好。
from
csv
import
reader, writer
def
read_local_file(file_name):
if
'.csv' in file_name:
rdr = reader(open(file_name, 'rb'))
return
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Publisher Resources

ISBN: 9787115459190