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10. Brief Tour of the Standard Library

10.1. Operating System Interface

The

module provides dozens of functions for interacting with the operating system:

>>> 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

Be sure to use the

import os

style instead of

from os import *

. This will keep

os.open()

from shadowing the built-in

open()

function which operates much differently.

The built-in

dir()

and

help()

functions are useful as interactive aids for working with

large modules like

>>> import os

>>> dir(os)

>>> help(os)

For daily file and directory management tasks, the

shutil

module provides a higher level

interface that is easier to use:

>>> import shutil

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

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

10.2. File Wildcards

The

glob

module provides a function for making file lists from directory wildcard

searches:

>>> import glob

>>> glob.glob('*.py')

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

10.3. Command Line Arguments

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Common utility scripts often need to process 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. 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

The

module provides regular expression tools for advanced string processing. For

complex matching and manipulation, regular expressions offer 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'

When only simple capabilities are needed, string methods are preferred because they are

easier to read and debug:

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

'tea for two'

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10.6. Mathematics

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)

10.7. 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 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

<BR>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.)

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10.8. 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 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.")

'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

Common data archiving and compression formats are directly supported by modules

including:

zlib

gzip

bz2

zipfile

and

tarfile

>>> import zlib

>>> s = 'witch which has which witches wrist watch'

>>> len(s)

>>> t = zlib.compress(s)

>>> len(t)

>>> zlib.decompress(t)

'witch which has which witches wrist watch'

>>> zlib.crc32(s)

226805979

10.10. Performance Measurement

Some Python users develop a deep interest in knowing the relative performance of

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 a modest performance advantage:

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>>> 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

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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

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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The Python Software Foundation is a non-profit corporation. Please donate.

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11. Brief Tour of the Standard Library – Part

This second tour covers more advanced modules that support professional programming

needs. These modules rarely occur in small scripts.

11.1. Output Formatting

The

repr

module provides a version of

repr()

customized for abbreviated displays of

large or deeply nested containers:

>>> import repr

>>> repr.repr(set('supercalifragilisticexpialidocious'))

"set(['a', 'c', 'd', 'e', 'f', 'g', ...])"

The

pprint

module offers more sophisticated control over printing both built-in and user

defined objects in a way that is readable by the interpreter. When the result is longer than

one line, the “pretty printer” adds line breaks and indentation to more clearly reveal data

structure:

>>> import pprint

>>> t = [[[['black', 'cyan'], 'white', ['green', 'red']], [['magenta',

... 'yellow'], 'blue']]]

...

>>> pprint.pprint(t, width=30)

[[[['black', 'cyan'],

'white',

['green', 'red']],

[['magenta', 'yellow'],

'blue']]]

The

textwrap

module formats paragraphs of text to fit a given screen width:

>>> import textwrap

>>> doc = """The wrap() method is just like fill() except that it returns

... a list of strings instead of one big string with newlines to separate

... the wrapped lines."""

...

>>> print textwrap.fill(doc, width=40)

The wrap() method is just like fill()

except that it returns a list of strings

instead of one big string with newlines

to separate the wrapped lines.

Python » Python v2.7.6 documentation » The Python Tutorial »

The

locale

module accesses a database of culture specific data formats. The grouping

attribute of locale’s format function provides a direct way of formatting numbers with

group separators:

>>> import locale

>>> locale.setlocale(locale.LC_ALL, 'English_United States.1252')

'English_United States.1252'

>>> conv = locale.localeconv() # get a mapping of conventions

>>> x = 1234567.8

>>> locale.format("%d", x, grouping=True)

'1,234,567'

>>> locale.format_string("%s%.*f", (conv['currency_symbol'],

... conv['frac_digits'], x), grouping=True)

'$1,234,567.80'

11.2. Templating

The

string

module includes a versatile

Template

class with a simplified syntax suitable

for editing by end-users. This allows users to customize their applications without having

to alter the application.

The format uses placeholder names formed by

with valid Python identifiers

(alphanumeric characters and underscores). Surrounding the placeholder with braces

allows it to be followed by more alphanumeric letters with no intervening spaces. Writing

creates a single escaped

>>> from string import Template

>>> t = Template('${village}folk send $$10 to $cause.')

>>> t.substitute(village='Nottingham', cause='the ditch fund')

'Nottinghamfolk send $10 to the ditch fund.'

The

substitute()

method raises a

KeyError

when a placeholder is not supplied in a

dictionary or a keyword argument. For mail-merge style applications, user supplied data

may be incomplete and the

safe_substitute()

method may be more appropriate — it

will leave placeholders unchanged if data is missing:

>>> t = Template('Return the $item to $owner.')

>>> d = dict(item='unladen swallow')

>>> t.substitute(d)

Traceback (most recent call last):

...

KeyError: 'owner'

>>> t.safe_substitute(d)

'Return the unladen swallow to $owner.'

Template subclasses can specify a custom delimiter. For example, a batch renaming

utility for a photo browser may elect to use percent signs for placeholders such as the

current date, image sequence number, or file format:

>>> import time, os.path

>>> photofiles = ['img_1074.jpg', 'img_1076.jpg', 'img_1077.jpg']

>>> class BatchRename(Template):

... delimiter = '%'

>>> fmt = raw_input('Enter rename style (%d-date %n-seqnum %f-format): ')

Enter rename style (%d-date %n-seqnum %f-format): Ashley_%n%f

>>> t = BatchRename(fmt)

>>> date = time.strftime('%d%b%y')

>>> for i, filename in enumerate(photofiles):

... base, ext = os.path.splitext(filename)

... newname = t.substitute(d=date, n=i, f=ext)

... print '{0} --> {1}'.format(filename, newname)

img_1074.jpg --> Ashley_0.jpg

img_1076.jpg --> Ashley_1.jpg

img_1077.jpg --> Ashley_2.jpg

Another application for templating is separating program logic from the details of multiple

output formats. This makes it possible to substitute custom templates for XML files, plain

text reports, and HTML web reports.

11.3. Working with Binary Data Record Layouts

The

struct

module provides

pack()

and

unpack()

functions for working with variable

length binary record formats. The following example shows how to loop through header

information in a ZIP file without using the

zipfile

module. Pack codes

"H"

and

"I"

represent two and four byte unsigned numbers respectively. The

"<"

indicates that they

are standard size and in little-endian byte order:

import struct

data = open('myfile.zip', 'rb').read()

start = 0

for i in range(3): # show the first 3 file headers

start += 14

fields = struct.unpack('<IIIHH', data[start:start+16])

crc32, comp_size, uncomp_size, filenamesize, extra_size = fields

start += 16

filename = data[start:start+filenamesize]

start += filenamesize

extra = data[start:start+extra_size]

print filename, hex(crc32), comp_size, uncomp_size

start += extra_size + comp_size # skip to the next header

11.4. Multi-threading

Threading is a technique for decoupling tasks which are not sequentially dependent.

Threads can be used to improve the responsiveness of applications that accept user

input while other tasks run in the background. A related use case is running I/O in parallel

with computations in another thread.

The following code shows how the high level

threading

module can run tasks in

background while the main program continues to run:

import threading, zipfile

class AsyncZip(threading.Thread):

def __init__(self, infile, outfile):

threading.Thread.__init__(self)

self.infile = infile

self.outfile = outfile

def run(self):

f = zipfile.ZipFile(self.outfile, 'w', zipfile.ZIP_DEFLATED)

f.write(self.infile)

f.close()

print 'Finished background zip of: ', self.infile

background = AsyncZip('mydata.txt', 'myarchive.zip')

background.start()

print 'The main program continues to run in foreground.'

background.join() # Wait for the background task to finish

print 'Main program waited until background was done.'

The principal challenge of multi-threaded applications is coordinating threads that share

data or other resources. To that end, the threading module provides a number of

synchronization primitives including locks, events, condition variables, and semaphores.

While those tools are powerful, minor design errors can result in problems that are

difficult to reproduce. So, the preferred approach to task coordination is to concentrate all

access to a resource in a single thread and then use the

Queue

module to feed that

thread with requests from other threads. Applications using

Queue.Queue

objects for inter-

thread communication and coordination are easier to design, more readable, and more

reliable.

11.5. Logging

The

logging

module offers a full featured and flexible logging system. At its simplest, log

messages are sent to a file or to

sys.stderr

import logging

logging.debug('Debugging information')

logging.info('Informational message')

logging.warning('Warning:config file %s not found', 'server.conf')

logging.error('Error occurred')

logging.critical('Critical error -- shutting down')

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