10.1. Operating System Interface

os库

import os

os.getcwd() # Return the current working directory 'C:\Python26'

os.chdir('/server/accesslogs') # Change current working directory

os.system('mkdir today') # Run the command mkdir in the system shell

0

需要注意的是,使用 import os 而不是 from os import * (os.open()将会覆盖掉内建的open())

shutil库

平时可以用其来复制复制文件,移动移动文件,知道有这么个东西就行了

import shutil

shutil.copyfile('data.db', 'archive.db')

shutil.move('/build/executables', 'installdir')

10.2. File Wildcards 通配符

glob库中的函数让你可以使用通配符获取文件列表

import glob

glob.glob('*.py')

['primes.py', 'random.py', 'quote.py']

10.3. Command Line Arguments 命令行参数

有时候,直接在命令行下运行一些脚本文件,同事传递给文件一些参数,那么通过 sys 模块中的 argv 我们就可以获取到一个命令行参数的列表,给出一个栗子:

import sys

print sys.argv

['demo.py', 'one', 'two', 'three']

The getopt module processes sys.argv using the conventions of the Unix getopt() function. More powerful and flexible command line processing is provided by the argparse module.

10.4. Error Output Redirection and Program Termination

The sys module also has attributes for stdin, stdout, and stderr. The latter is useful for emitting warnings and error messages to make them visible even when stdout has been redirected:

sys.stderr.write('Warning, log file not found starting a new one\n')

Warning, log file not found starting a new one

The most direct way to terminate a script is to use sys.exit().

10.5. String Pattern Matching 正则匹配

re 模块提供正则匹配工具用以对字符串进行更高大上的操作.对于复杂的匹配和处理,正 则表达式提供了简洁、优化的解决方案:

import re

re.findall(r'\bf[a-z]*', 'which foot or hand fell fastest')

['foot', 'fell', 'fastest']

re.sub(r'(\b[a-z]+) \1', r'\1', 'cat in the the hat')

'cat in the hat'

有时候,string自带的方法用起来可能更好,因为简单粗暴,容易读写和调试:

'tea for too'.replace('too', 'two')

'tea for two'

10.6. Mathematics 算术表达

math模块提供了一个基于C实现库函数来进行浮点运算:

import math

math.cos(math.pi / 4.0)

0.70710678118654757

math.log(1024, 2)

10.0

random提供了随机数生成器:

import random

random.choice(['apple', 'pear', 'banana'])

'apple'

random.sample(xrange(100), 10) # sampling without replacement

[30, 83, 16, 4, 8, 81, 41, 50, 18, 33]

random.random() # random float

0.17970987693706186

random.randrange(6) # random integer chosen from range(6)

4

10.7. Internet Access

urllib2 和 smtplib 是两个常用的用于web方面的库,前一个用于从网上获取信息,后一个用于发送电子邮件:

import urllib2

for line in urllib2.urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl'):

... if 'EST' in line or 'EDT' in line: # look for Eastern Time

... print line

Nov. 25, 09:43:32 PM EST

import smtplib

server = smtplib.SMTP('localhost')

server.sendmail('soothsayer@example.org', 'jcaesar@example.org',

... """To: jcaesar@example.org

... From: soothsayer@example.org

...

... Beware the Ides of March.

... """)

server.quit()

(Note that the second example needs a mailserver running on localhost.)

10.8. Dates and Times 日期与时间

datetime模块提供了操作日期和时间的方法,不管你是想来简单的还是复杂的.

datetime模块是非常常用的一个模块,关于这个模块的使用,需要熟练掌握.

dates are easily constructed and formatted

from datetime import date

now = date.today()

now

datetime.date(2003, 12, 2)

now.strftime("%m-%d-%y. %d %b %Y is a %A on the %d day of %B.")

'12-02-03. 02 Dec 2003 is a Tuesday on the 02 day of December.'

dates support calendar arithmetic

birthday = date(1964, 7, 31)

age = now - birthday

age.days

14368

10.9. Data Compression 数据压缩

常用是数据压缩相关的模块: zlib, gzip, bz2, zipfile and tarfile.

import zlib

s = 'witch which has which witches wrist watch'

len(s)

41

t = zlib.compress(s)

len(t)

37

zlib.decompress(t)

'witch which has which witches wrist watch'

zlib.crc32(s)

226805979

10.10. Performance Measurement

有时候同一个问题会有多种解法,我们又想要去知道他们的效率上的差别在哪,然后,然后就没有然后了....你想要的,Python里面都有.

我实在是翻译不动了............

For example, it may be tempting to use the tuple packing and unpacking feature instead of the traditional approach to swapping arguments. The timeit module quickly demonstrates a modest performance advantage:

from timeit import Timer

Timer('t=a; a=b; b=t', 'a=1; b=2').timeit()

0.57535828626024577

Timer('a,b = b,a', 'a=1; b=2').timeit()

0.54962537085770791

In contrast to timeit‘s fine level of granularity, the profile and pstats modules provide tools for identifying time critical sections in larger blocks of code.

10.11. Quality Control

One approach for developing high quality software is to write tests for each function as it is developed and to run those tests frequently during the development process.

The doctest module provides a tool for scanning a module and validating tests embedded in a program’s docstrings. Test construction is as simple as cutting-and-pasting a typical call along with its results into the docstring. This improves the documentation by providing the user with an example and it allows the doctest module to make sure the code remains true to the documentation:

def average(values):

"""Computes the arithmetic mean of a list of numbers.

>>> print average([20, 30, 70])
40.0
"""
return sum(values, 0.0) / len(values)

import doctest

doctest.testmod() # automatically validate the embedded tests

The unittest module is not as effortless as the doctest module, but it allows a more comprehensive set of tests to be maintained in a separate file:

import unittest

class TestStatisticalFunctions(unittest.TestCase):

def test_average(self):
self.assertEqual(average([20, 30, 70]), 40.0)
self.assertEqual(round(average([1, 5, 7]), 1), 4.3)
with self.assertRaises(ZeroDivisionError):
average([])
with self.assertRaises(TypeError):
average(20, 30, 70)

unittest.main() # Calling from the command line invokes all tests

10.12. Batteries Included

Python has a “batteries included” philosophy. This is best seen through the sophisticated and robust capabilities of its larger packages. For example:

The xmlrpclib and SimpleXMLRPCServer modules make implementing remote procedure calls into an almost trivial task. Despite the modules names, no direct knowledge or handling of XML is needed.

The email package is a library for managing email messages, including MIME and other RFC 2822-based message documents. Unlike smtplib and poplib which actually send and receive messages, the email package has a complete toolset for building or decoding complex message structures (including attachments) and for implementing internet encoding and header protocols.

The xml.dom and xml.sax packages provide robust support for parsing this popular data interchange format. Likewise, the csv module supports direct reads and writes in a common database format. Together, these modules and packages greatly simplify data interchange between Python applications and other tools.

Internationalization is supported by a number of modules including gettext, locale, and the codecs package.

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