[Python-Dev] Tutorial: Brief Introduction to the Standard Libary (original) (raw)

Raymond Hettinger python at rcn.com
Wed Dec 3 01:56:20 EST 2003

Thank you everyone for the ideas on what to include and exclude from the new tutorial section.

Attached is a revised draft. Comments, suggestions, nitpicks, complaints, and accolades are welcome.

Raymond Hettinger

-------------- next part -------------- Brief Tour of some Standard Library Modules

Operating System Interface

The os module provides many functions for interacting with the operating system:

import os os.system('copy /data/mydata.fil /backup/mydata.fil') 0 os.getcwd() 'C:\Python24' os.chdir('/server/accesslogs')

Be sure to use the "import os" style instead of "from os import *". This will keep os.open() from shadowing builtin.open() which operates much differently.

File Wildcards

The glob module provides a function for making file lists from directory wildcard searches:

glob.glob('*.py') ['primes.py', 'random.py', 'quote.py']

Command Line Arguments

Common utility scripts often invoke processing command line arguments. These arguments are stored in the sys module's argv attribute as a list. For instance the following output results from running "python demo.py one two three" at the command line:

import sys print sys.argv[] ['demo.py', 'one', 'two', 'three']

The getopt module processes sys.argv using the conventions of the Unix getopt() function:

import getopt # sys.argv is ['myprog.py', '-a', '-b', '-cfoo', '-d', 'bar', 'a1', 'a2'] optlist, args = getopt.getopt(sys.argv[1:], 'abc:d:') optlist [('-a', ''), ('-b', ''), ('-c', 'foo'), ('-d', 'bar')] args ['a1', 'a2']

More powerful and flexible command line processing is provided by the optparse module.

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') Warning, log file not found starting a new one

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

String Pattern Matching

The re module provides regular expression tools for advanced string processing. When only simple capabilities are needed, string methods are preferred because they are easier to read and debug. For more sophisticated applications, regular expressions can provide succinct, optimized solutions:

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'

Math Library

The math module gives access to the underlying C library functions for floating point math:

import math math.cos(math.pi / 4.0) 0.70710678118654757 math.log(1024, 2) 10.0

The random module provides tools for making random selections:

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

Internet Access

There are a number of modules for accessing the internet and processing internet protocols. Two of the simplest are urllib2 for retrieving data from urls and smtplib for sending mail:

import urllib for line in urllib2.urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl'): ... if 'EST' in line: # look for Eastern Standard Time ... print line


Nov. 25, 09:43:32 PM EST

import smtplib server = smtplib.SMTP('localhost') server.sendmail('soothsayer at tmp.org', 'jceasar at tmp.org', """To: jceasar at tmp.org From: soothsayer at tmp.org

Beware the Ides of March. """)

server.quit()

Dates and Times

The datetime module supplies classes for manipulating dates and times in both simple and complex ways. While date and time arithmetic is supported, the focus of the implementation is on efficient member extraction for output formatting and manipulation. The module also supports objects that are time zone 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 or %d%b %Y is a %A on the %d day of %B") '12-02-03 or 02Dec 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 modules including : zlib, gzip, bz2, zipfile, and tar.

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(t) -1438085031

Performance Measurement

Some Python users develop a deep interest in knowing the relative performance between different approaches to the same problem. Python provides a measurement tool that answers those questions immediately.

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 that the traditional approach is faster:

from timeit import Timer dir(Timer) Timer('t=a; a=b; b=t', 'a=1; b=1').timeit() 0.60864915603680925 Timer('a,b = b,a', 'a=1; b=1').timeit() 0.8625194857439773

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

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)
    self.assertRaises(ZeroDivisionError, average, [])
    self.assertRaises(TypeError, average, 20, 30, 70)

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

Batteries Included

Python has a "batteries included" philosophy. The is best seen through the sophisticated and robust capabilites of its larger packages:

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