By: Joshua O’Donoghue

Operating System Interface In order to interact with the operating system in python you will want to become familiar with the OS module This module can be used with the command “import os” Useful functions to aid in using this module are dir(os) which returns a list of all module functions and help(os) which returns a manual page created from the module’s docstrings

Operating Systems Interface Daily file and directory management tasks can be performed with the shutil module >>> import shutil >>> shutil.copyfile('data.db', 'archive.db') >>> shutil.move('/build/executables', 'installdir')

File Wildcards The glob module is a function used for making lists from directory wildcard searches: >>> import glob >>> glob.glob('*.py') ['primes.py', 'random.py', 'quote.py']

Error Output Redirection and Program Termination The attributes stdin, stdout, and stderr are also part of the “sys” module These are useful for outputting warnings and error messages The most direct way to terminate a script is to use sys.exit() >>> sys.stderr.write('Warning, log file not found starting a new one\n') Warning, log file not found starting a new one

String Pattern Matching The re module provides regular expression tools for string processing. >>> 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' String methods are easier to read and debug, therefore are preferred when only simple capabilities are needed >>> 'tea for too'.replace('too', 'two') 'tea for two'

Command Line Arguments Common utility scripts often need to process command line arguments which are stored in the “sys” module’s “argv” attribute These attributes are stored as a list >>> import sys >>> print sys.argv ['demo.py', 'one', 'two', 'three']

Mathematics The math module gives access to C library functions for floating point math >>> import math >>> math.cos(math.pi / 4.0) >>> math.log(1024, 2) 10.0

Mathematics Random Numbers can be created using the random module >>> 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 >>> random.randrange(6) # random integer chosen from range(6) 4

Internet Access Two of the simplest modules for accessing the internet are urllib2 and smtplib. Urllib2 is used for retrieving data >>> import urllib2 >>> for line in urllib2.urlopen(' if 'EST' in line or 'EDT' in line: # look for Eastern Time... print line Nov. 25, 09:43:32 PM EST

Internet Access Smtplib is used for sending mail >>> import smtplib >>> server = smtplib.SMTP('localhost') >>> """To: From: Beware the Ides of March.... """) >>> server.quit()

Dates and Times The datetime module supplies classes for manipulating dates and times. This module supports objects that are timezone aware >>> # 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.") ' 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

Data Compression Common data archiving and compression formats are directly supported by the modules: 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)

Performance Measurement Many users wish to know the performance of different approaches to the same problem The timeit module quickly can demonstrate performance advantages >>> from timeit import Timer >>> Timer('t=a; a=b; b=t', 'a=1; b=2').timeit() >>> Timer('a,b = b,a', 'a=1; b=2').timeit()

Quality Control In order to develop high quality software, you should write tests for each function and run them frequently during the developmental process The module that provides a tool for scanning and validating tests embedded in the docstrings is “doctest” 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

Quality Control The unitest module is not as effortless as the doctest module, but it does allow for 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) self.assertRaises(ZeroDivisionError, average, []) self.assertRaises(TypeError, average, 20, 30, 70) unittest.main() # Calling from the command line invokes all tests

Batteries Included The xmlrpclib and simpleXMLRPCServer modules make implementing remote procedure calls into an almost trivial task, and works needing no knowledge or handling of XML despite their names The package is a library for managing messages and contains a complete toolset for building or decoding complex message structures.

Batteries Included The xml.dom and xml.sax packages provide support for parsing popular data interchange format. The csv module supports direct reads and writes in a common database format. These modules are extremely useful in simpifying data interchange between python applications and other tools.

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