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<title>11. Brief Tour of the Standard Library - Part II
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<A NAME=
"CHILD_LINKS"><STRONG>Subsections
</STRONG></a>
<LI><A href=
"node13.html#SECTION0013100000000000000000">11.1 Output Formatting
</a>
<LI><A href=
"node13.html#SECTION0013200000000000000000">11.2 Templating
</a>
<LI><A href=
"node13.html#SECTION0013300000000000000000">11.3 Working with Binary Data Record Layouts
</a>
<LI><A href=
"node13.html#SECTION0013400000000000000000">11.4 Multi-threading
</a>
<LI><A href=
"node13.html#SECTION0013500000000000000000">11.5 Logging
</a>
<LI><A href=
"node13.html#SECTION0013600000000000000000">11.6 Weak References
</a>
<LI><A href=
"node13.html#SECTION0013700000000000000000">11.7 Tools for Working with Lists
</a>
<LI><A href=
"node13.html#SECTION0013800000000000000000">11.8 Decimal Floating Point Arithmetic
</a>
<!--End of Table of Child-Links-->
<H1><A NAME=
"SECTION0013000000000000000000"></A><A NAME=
"briefTourTwo"></A>
11. Brief Tour of the Standard Library - Part II
This second tour covers more advanced modules that support professional
programming needs. These modules rarely occur in small scripts.
<H1><A NAME=
"SECTION0013100000000000000000"></A><A NAME=
"output-formatting"></A>
The
<a class=
"ulink" href=
"../lib/module-repr.html" ><tt class=
"module">repr
</tt></a> module provides an
version of
<tt class=
"function">repr()
</tt> for abbreviated displays of large or deeply
<div class=
"verbatim"><pre>
>>> repr.repr(set('supercalifragilisticexpialidocious'))
"set(['a', 'c', 'd', 'e', 'f', 'g', ...])"
The
<a class=
"ulink" href=
"../lib/module-pprint.html" ><tt class=
"module">pprint
</tt></a> 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:
<div class=
"verbatim"><pre>
>>> import pprint
>>> t = [[[['black', 'cyan'], 'white', ['green', 'red']], [['magenta',
>>> pprint.pprint(t, width=
30)
The
<a class=
"ulink" href=
"../lib/module-textwrap.html" ><tt class=
"module">textwrap
</tt></a> module
formats paragraphs of text to fit a given screen width:
<div class=
"verbatim"><pre>
>>> 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.
The
<a class=
"ulink" href=
"../lib/module-locale.html" ><tt class=
"module">locale
</tt></a> module accesses
a database of culture specific data formats. The grouping attribute
of locale's format function provides a direct way of formatting numbers
<div class=
"verbatim"><pre>
>>> 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)
>>> locale.format(
"%s%.*f", (conv['currency_symbol'],
... conv['frac_digits'], x), grouping=True)
<H1><A NAME=
"SECTION0013200000000000000000"></A><A NAME=
"templating"></A>
The
<a class=
"ulink" href=
"../lib/module-string.html" ><tt class=
"module">string
</tt></a> module includes a
versatile
<tt class=
"class">Template
</tt> 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
"<tt class="samp
">$</tt>" 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
"<tt class="samp
">$$</tt>" creates a single escaped
"<tt class="samp
">$</tt>":
<div class=
"verbatim"><pre>
>>> from string import Template
>>> t = Template('${village}folk send $$
10 to $cause.')
>>> t.substitute(village='Nottingham', cause='the ditch fund')
'Nottinghamfolk send $
10 to the ditch fund.'
The
<tt class=
"method">substitute
</tt> method raises a
<tt class=
"exception">KeyError
</tt> 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
<tt class=
"method">safe_substitute
</tt> method may be more appropriate -- it will leave
placeholders unchanged if data is missing:
<div class=
"verbatim"><pre>
>>> t = Template('Return the $item to $owner.')
>>> d = dict(item='unladen swallow')
>>> t.substitute(d)
Traceback (most recent call last):
>>> 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:
<div class=
"verbatim"><pre>
>>> import time, os.path
>>> photofiles = ['img_1074.jpg', 'img_1076.jpg', 'img_1077.jpg']
>>> class BatchRename(Template):
>>> 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 '%s --
> %s' % (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.
<H1><A NAME=
"SECTION0013300000000000000000"></A><A NAME=
"binary-formats"></A>
11.3 Working with Binary Data Record Layouts
The
<a class=
"ulink" href=
"../lib/module-struct.html" ><tt class=
"module">struct
</tt></a> module provides
<tt class=
"function">pack()
</tt> and
<tt class=
"function">unpack()
</tt> functions for working with
variable length binary record formats. The following example shows how
to loop through header information in a ZIP file (with pack codes
<code>"H"</code> and
<code>"L"</code> representing two and four byte unsigned
<div class=
"verbatim"><pre>
data = open('myfile.zip', 'rb').read()
for i in range(
3): # show the first
3 file headers
fields = struct.unpack('LLLHH', data[start:start+
16])
crc32, comp_size, uncomp_size, filenamesize, extra_size = fields
filename = data[start: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
<H1><A NAME=
"SECTION0013400000000000000000"></A><A NAME=
"multi-threading"></A>
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
<a class=
"ulink" href=
"../lib/module-threading.html"
><tt class=
"module">threading
</tt></a> module can run
tasks in background while the main program continues to run:
<div class=
"verbatim"><pre>
import threading, zipfile
class AsyncZip(threading.Thread):
def __init__(self, infile, outfile):
threading.Thread.__init__(self)
f = zipfile.ZipFile(self.outfile, 'w', zipfile.ZIP_DEFLATED)
print 'Finished background zip of: ', self.infile
background = AsyncZip('mydata.txt', 'myarchive.zip')
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
<a class=
"ulink" href=
"../lib/module-Queue.html"
><tt class=
"module">Queue
</tt></a> module to feed that
thread with requests from other threads. Applications using
<tt class=
"class">Queue
</tt> objects for inter-thread communication and coordination
are easier to design, more readable, and more reliable.
<H1><A NAME=
"SECTION0013500000000000000000"></A><A NAME=
"logging"></A>
The
<a class=
"ulink" href=
"../lib/module-logging.html" ><tt class=
"module">logging
</tt></a> module offers
a full featured and flexible logging system. At its simplest, log
messages are sent to a file or to
<code>sys.stderr
</code>:
<div class=
"verbatim"><pre>
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')
This produces the following output:
<div class=
"verbatim"><pre>
WARNING:root:Warning:config file server.conf not found
ERROR:root:Error occurred
CRITICAL:root:Critical error -- shutting down
By default, informational and debugging messages are suppressed and the
output is sent to standard error. Other output options include routing
messages through email, datagrams, sockets, or to an HTTP Server. New
filters can select different routing based on message priority:
<tt class=
"constant">DEBUG
</tt>,
<tt class=
"constant">INFO
</tt>,
<tt class=
"constant">WARNING
</tt>,
<tt class=
"constant">ERROR
</tt>,
and
<tt class=
"constant">CRITICAL
</tt>.
The logging system can be configured directly from Python or can be
loaded from a user editable configuration file for customized logging
without altering the application.
<H1><A NAME=
"SECTION0013600000000000000000"></A><A NAME=
"weak-references"></A>
Python does automatic memory management (reference counting for most
objects and garbage collection to eliminate cycles). The memory is
freed shortly after the last reference to it has been eliminated.
This approach works fine for most applications but occasionally there
is a need to track objects only as long as they are being used by
something else. Unfortunately, just tracking them creates a reference
that makes them permanent. The
<a class=
"ulink" href=
"../lib/module-weakref.html"
><tt class=
"module">weakref
</tt></a> module provides
tools for tracking objects without creating a reference. When the
object is no longer needed, it is automatically removed from a weakref
table and a callback is triggered for weakref objects. Typical
applications include caching objects that are expensive to create:
<div class=
"verbatim"><pre>
>>> import weakref, gc
... def __init__(self, value):
... return str(self.value)
>>> a = A(
10) # create a reference
>>> d = weakref.WeakValueDictionary()
>>> d['primary'] = a # does not create a reference
>>> d['primary'] # fetch the object if it is still alive
>>> del a # remove the one reference
>>> gc.collect() # run garbage collection right away
>>> d['primary'] # entry was automatically removed
Traceback (most recent call last):
File
"<pyshell#108>", line
1, in -toplevel-
d['primary'] # entry was automatically removed
File
"C:/PY24/lib/weakref.py", line
46, in __getitem__
<H1><A NAME=
"SECTION0013700000000000000000"></A><A NAME=
"list-tools"></A>
11.7 Tools for Working with Lists
Many data structure needs can be met with the built-in list type.
However, sometimes there is a need for alternative implementations
with different performance trade-offs.
The
<a class=
"ulink" href=
"../lib/module-array.html" ><tt class=
"module">array
</tt></a> module provides an
<tt class=
"class">array()
</tt> object that is like a list that stores only homogenous
data but stores it more compactly. The following example shows an array
of numbers stored as two byte unsigned binary numbers (typecode
<code>"H"</code>) rather than the usual
16 bytes per entry for regular lists
<div class=
"verbatim"><pre>
>>> from array import array
>>> a = array('H', [
4000,
10,
700,
22222])
The
<a class=
"ulink" href=
"../lib/module-collections.html" ><tt class=
"module">collections
</tt></a> module
provides a
<tt class=
"class">deque()
</tt> object that is like a list with faster
appends and pops from the left side but slower lookups in the middle.
These objects are well suited for implementing queues and breadth first
<div class=
"verbatim"><pre>
>>> from collections import deque
>>> d = deque([
"task1",
"task2",
"task3"])
>>> d.append(
"task4")
>>> print
"Handling", d.popleft()
unsearched = deque([starting_node])
def breadth_first_search(unsearched):
node = unsearched.popleft()
for m in gen_moves(node):
In addition to alternative list implementations, the library also offers
other tools such as the
<a class=
"ulink" href=
"../lib/module-bisect.html" ><tt class=
"module">bisect
</tt></a>
module with functions for manipulating sorted lists:
<div class=
"verbatim"><pre>
>>> import bisect
>>> scores = [(
100, 'perl'), (
200, 'tcl'), (
400, 'lua'), (
500, 'python')]
>>> bisect.insort(scores, (
300, 'ruby'))
[(
100, 'perl'), (
200, 'tcl'), (
300, 'ruby'), (
400, 'lua'), (
500, 'python')]
The
<a class=
"ulink" href=
"../lib/module-heapq.html" ><tt class=
"module">heapq
</tt></a> module provides
functions for implementing heaps based on regular lists. The lowest
valued entry is always kept at position zero. This is useful for
applications which repeatedly access the smallest element but do not
want to run a full list sort:
<div class=
"verbatim"><pre>
>>> from heapq import heapify, heappop, heappush
>>> data = [
1,
3,
5,
7,
9,
2,
4,
6,
8,
0]
>>> heapify(data) # rearrange the list into heap order
>>> heappush(data, -
5) # add a new entry
>>> [heappop(data) for i in range(
3)] # fetch the three smallest entries
<H1><A NAME=
"SECTION0013800000000000000000"></A><A NAME=
"decimal-fp"></A>
11.8 Decimal Floating Point Arithmetic
The
<a class=
"ulink" href=
"../lib/module-decimal.html" ><tt class=
"module">decimal
</tt></a> module offers a
<tt class=
"class">Decimal
</tt> datatype for decimal floating point arithmetic. Compared to
the built-in
<tt class=
"class">float
</tt> implementation of binary floating point, the new
class is especially helpful for financial applications and other uses which
require exact decimal representation, control over precision, control over
rounding to meet legal or regulatory requirements, tracking of significant
decimal places, or for applications where the user expects the results to
match calculations done by hand.
For example, calculating a
5% tax on a
70 cent phone charge gives
different results in decimal floating point and binary floating point.
The difference becomes significant if the results are rounded to the
<div class=
"verbatim"><pre>
>>> from decimal import *
>>> Decimal('
0.70') * Decimal('
1.05')
The
<tt class=
"class">Decimal
</tt> result keeps a trailing zero, automatically inferring four
place significance from multiplicands with two place significance. Decimal reproduces
mathematics as done by hand and avoids issues that can arise when binary
floating point cannot exactly represent decimal quantities.
Exact representation enables the
<tt class=
"class">Decimal
</tt> class to perform
modulo calculations and equality tests that are unsuitable for binary
<div class=
"verbatim"><pre>
>>> Decimal('
1.00') % Decimal('
.10')
>>> sum([Decimal('
0.1')]*
10) == Decimal('
1.0')
>>> sum([
0.1]*
10) ==
1.0
The
<tt class=
"module">decimal
</tt> module provides arithmetic with as much precision as
<div class=
"verbatim"><pre>
>>> getcontext().prec =
36
>>> Decimal(
1) / Decimal(
7)
Decimal(
"0.142857142857142857142857142857142857")
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<span class=
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2.4.2, documentation updated on
28 September
2005.
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