13 New, Improved, and Removed Modules

The standard library received many enhancements and bug fixes in Python 2.5. Here's a partial list of the most notable changes, sorted alphabetically by module name. Consult the Misc/NEWS file in the source tree for a more complete list of changes, or look through the SVN logs for all the details.

• The audioop module now supports the a-LAW encoding, and the code for u-LAW encoding has been improved. (Contributed by Lars Immisch.)

• The codecs module gained support for incremental codecs. The codec.lookup() function now returns a CodecInfo instance instead of a tuple. CodecInfo instances behave like a 4-tuple to preserve backward compatibility but also have the attributes encode, decode, incrementalencoder, incrementaldecoder, streamwriter, and streamreader. Incremental codecs can receive input and produce output in multiple chunks; the output is the same as if the entire input was fed to the non-incremental codec. See the codecs module documentation for details. (Designed and implemented by Walter Dörwald.)

• The collections module gained a new type, defaultdict, that subclasses the standard dict type. The new type mostly behaves like a dictionary but constructs a default value when a key isn't present, automatically adding it to the dictionary for the requested key value.

  The first argument to defaultdict's constructor is a factory function that gets called whenever a key is requested but not found. This factory function receives no arguments, so you can use built-in type constructors such as list() or int(). For example, you can make an index of words based on their initial letter like this:

  words = """Nel mezzo del cammin di nostra vita
  mi ritrovai per una selva oscura
  che la diritta via era smarrita""".lower().split()
  
  index = defaultdict(list)
  
  for w in words:
      init_letter = w[0]
      index[init_letter].append(w)
  

  Printing index results in the following output:

  defaultdict(<type 'list'>, {'c': ['cammin', 'che'], 'e': ['era'], 
          'd': ['del', 'di', 'diritta'], 'm': ['mezzo', 'mi'], 
          'l': ['la'], 'o': ['oscura'], 'n': ['nel', 'nostra'], 
          'p': ['per'], 's': ['selva', 'smarrita'], 
          'r': ['ritrovai'], 'u': ['una'], 'v': ['vita', 'via']}
  

  (Contributed by Guido van Rossum.)

• The deque double-ended queue type supplied by the collections module now has a remove(value) method that removes the first occurrence of value in the queue, raising ValueError if the value isn't found. (Contributed by Raymond Hettinger.)

• New module: The contextlib module contains helper functions for use with the new 'with' statement. See section 8.2 for more about this module.

• New module: The cProfile module is a C implementation of the existing profile module that has much lower overhead. The module's interface is the same as profile: you run cProfile.run('main()') to profile a function, can save profile data to a file, etc. It's not yet known if the Hotshot profiler, which is also written in C but doesn't match the profile module's interface, will continue to be maintained in future versions of Python. (Contributed by Armin Rigo.)

  Also, the pstats module for analyzing the data measured by the profiler now supports directing the output to any file object by supplying a stream argument to the Stats constructor. (Contributed by Skip Montanaro.)

• The csv module, which parses files in comma-separated value format, received several enhancements and a number of bugfixes. You can now set the maximum size in bytes of a field by calling the csv.field_size_limit(new_limit) function; omitting the new_limit argument will return the currently-set limit. The reader class now has a line_num attribute that counts the number of physical lines read from the source; records can span multiple physical lines, so line_num is not the same as the number of records read.

  The CSV parser is now stricter about multi-line quoted fields. Previously, if a line ended within a quoted field without a terminating newline character, a newline would be inserted into the returned field. This behavior caused problems when reading files that contained carriage return characters within fields, so the code was changed to return the field without inserting newlines. As a consequence, if newlines embedded within fields are important, the input should be split into lines in a manner that preserves the newline characters.

  (Contributed by Skip Montanaro and Andrew McNamara.)

• The datetime class in the datetime module now has a strptime(string, format) method for parsing date strings, contributed by Josh Spoerri. It uses the same format characters as time.strptime() and time.strftime():

  from datetime import datetime
  
  ts = datetime.strptime('10:13:15 2006-03-07',
                         '%H:%M:%S %Y-%m-%d')
  

• The SequenceMatcher.get_matching_blocks() method in the difflib module now guarantees to return a minimal list of blocks describing matching subsequences. Previously, the algorithm would occasionally break a block of matching elements into two list entries. (Enhancement by Tim Peters.)

• The doctest module gained a SKIP option that keeps an example from being executed at all. This is intended for code snippets that are usage examples intended for the reader and aren't actually test cases.

  An encoding parameter was added to the testfile() function and the DocFileSuite class to specify the file's encoding. This makes it easier to use non-ASCII characters in tests contained within a docstring. (Contributed by Bjorn Tillenius.)

• The email package has been updated to version 4.0. (Contributed by Barry Warsaw.)

• The fileinput module was made more flexible. Unicode filenames are now supported, and a mode parameter that defaults to "r" was added to the input() function to allow opening files in binary or universal-newline mode. Another new parameter, openhook, lets you use a function other than open() to open the input files. Once you're iterating over the set of files, the FileInput object's new fileno() returns the file descriptor for the currently opened file. (Contributed by Georg Brandl.)

• In the gc module, the new get_count() function returns a 3-tuple containing the current collection counts for the three GC generations. This is accounting information for the garbage collector; when these counts reach a specified threshold, a garbage collection sweep will be made. The existing gc.collect() function now takes an optional generation argument of 0, 1, or 2 to specify which generation to collect. (Contributed by Barry Warsaw.)

• The nsmallest() and nlargest() functions in the heapq module now support a key keyword parameter similar to the one provided by the min()/max() functions and the sort() methods. For example:

  >>> import heapq
  >>> L = ["short", 'medium', 'longest', 'longer still']
  >>> heapq.nsmallest(2, L)  # Return two lowest elements, lexicographically
  ['longer still', 'longest']
  >>> heapq.nsmallest(2, L, key=len)   # Return two shortest elements
  ['short', 'medium']
  

  (Contributed by Raymond Hettinger.)

• The itertools.islice() function now accepts None for the start and step arguments. This makes it more compatible with the attributes of slice objects, so that you can now write the following:

  s = slice(5)     # Create slice object
  itertools.islice(iterable, s.start, s.stop, s.step)
  

  (Contributed by Raymond Hettinger.)

• The format() function in the locale module has been modified and two new functions were added, format_string() and currency().

  The format() function's val parameter could previously be a string as long as no more than one %char specifier appeared; now the parameter must be exactly one %char specifier with no surrounding text. An optional monetary parameter was also added which, if True, will use the locale's rules for formatting currency in placing a separator between groups of three digits.

  To format strings with multiple %char specifiers, use the new format_string() function that works like format() but also supports mixing %char specifiers with arbitrary text.

  A new currency() function was also added that formats a number according to the current locale's settings.

  (Contributed by Georg Brandl.)

• The mailbox module underwent a massive rewrite to add the capability to modify mailboxes in addition to reading them. A new set of classes that include mbox, MH, and Maildir are used to read mailboxes, and have an add(message) method to add messages, remove(key) to remove messages, and lock()/unlock() to lock/unlock the mailbox. The following example converts a maildir-format mailbox into an mbox-format one:

  import mailbox
  
  # 'factory=None' uses email.Message.Message as the class representing
  # individual messages.
  src = mailbox.Maildir('maildir', factory=None)
  dest = mailbox.mbox('/tmp/mbox')
  
  for msg in src:
      dest.add(msg)
  

  (Contributed by Gregory K. Johnson. Funding was provided by Google's 2005 Summer of Code.)

• New module: the msilib module allows creating Microsoft Installer .msi files and CAB files. Some support for reading the .msi database is also included. (Contributed by Martin von Löwis.)

• The nis module now supports accessing domains other than the system default domain by supplying a domain argument to the nis.match() and nis.maps() functions. (Contributed by Ben Bell.)

• The operator module's itemgetter() and attrgetter() functions now support multiple fields. A call such as operator.attrgetter('a', 'b') will return a function that retrieves the a and b attributes. Combining this new feature with the sort() method's key parameter lets you easily sort lists using multiple fields. (Contributed by Raymond Hettinger.)

• The optparse module was updated to version 1.5.1 of the Optik library. The OptionParser class gained an epilog attribute, a string that will be printed after the help message, and a destroy() method to break reference cycles created by the object. (Contributed by Greg Ward.)

• The os module underwent several changes. The stat_float_times variable now defaults to true, meaning that os.stat() will now return time values as floats. (This doesn't necessarily mean that os.stat() will return times that are precise to fractions of a second; not all systems support such precision.)

  Constants named os.SEEK_SET, os.SEEK_CUR, and os.SEEK_END have been added; these are the parameters to the os.lseek() function. Two new constants for locking are os.O_SHLOCK and os.O_EXLOCK.

  Two new functions, wait3() and wait4(), were added. They're similar the waitpid() function which waits for a child process to exit and returns a tuple of the process ID and its exit status, but wait3() and wait4() return additional information. wait3() doesn't take a process ID as input, so it waits for any child process to exit and returns a 3-tuple of process-id, exit-status, resource-usage as returned from the resource.getrusage() function. wait4(pid) does take a process ID. (Contributed by Chad J. Schroeder.)

  On FreeBSD, the os.stat() function now returns times with nanosecond resolution, and the returned object now has st_gen and st_birthtime. The st_flags member is also available, if the platform supports it. (Contributed by Antti Louko and Diego Pettenò.)

• The Python debugger provided by the pdb module can now store lists of commands to execute when a breakpoint is reached and execution stops. Once breakpoint #1 has been created, enter "commands 1" and enter a series of commands to be executed, finishing the list with "end". The command list can include commands that resume execution, such as "continue" or "next". (Contributed by Grégoire Dooms.)

• The pickle and cPickle modules no longer accept a return value of None from the __reduce__() method; the method must return a tuple of arguments instead. The ability to return None was deprecated in Python 2.4, so this completes the removal of the feature.

• The pkgutil module, containing various utility functions for finding packages, was enhanced to support PEP 302's import hooks and now also works for packages stored in ZIP-format archives. (Contributed by Phillip J. Eby.)

• The pybench benchmark suite by Marc-André Lemburg is now included in the Tools/pybench directory. The pybench suite is an improvement on the commonly used pystone.py program because pybench provides a more detailed measurement of the interpreter's speed. It times particular operations such as function calls, tuple slicing, method lookups, and numeric operations, instead of performing many different operations and reducing the result to a single number as pystone.py does.

• The pyexpat module now uses version 2.0 of the Expat parser. (Contributed by Trent Mick.)

• The old regex and regsub modules, which have been deprecated ever since Python 2.0, have finally been deleted. Other deleted modules: statcache, tzparse, whrandom.

• Also deleted: the lib-old directory, which includes ancient modules such as dircmp and ni, was removed. lib-old wasn't on the default sys.path, so unless your programs explicitly added the directory to sys.path, this removal shouldn't affect your code.

• The rlcompleter module is no longer dependent on importing the readline module and therefore now works on non-Unix platforms. (Patch from Robert Kiendl.)

• The SimpleXMLRPCServer and DocXMLRPCServer classes now have a rpc_paths attribute that constrains XML-RPC operations to a limited set of URL paths; the default is to allow only '/' and '/RPC2'. Setting rpc_paths to None or an empty tuple disables this path checking.

• The socket module now supports AF_NETLINK sockets on Linux, thanks to a patch from Philippe Biondi. Netlink sockets are a Linux-specific mechanism for communications between a user-space process and kernel code; an introductory article about them is at http://www.linuxjournal.com/article/7356. In Python code, netlink addresses are represented as a tuple of 2 integers, (pid, group_mask).

  Two new methods on socket objects, recv_buf(buffer) and recvfrom_buf(buffer), store the received data in an object that supports the buffer protocol instead of returning the data as a string. This means you can put the data directly into an array or a memory-mapped file.

  Socket objects also gained getfamily(), gettype(), and getproto() accessor methods to retrieve the family, type, and protocol values for the socket.

• New module: the spwd module provides functions for accessing the shadow password database on systems that support shadow passwords.

• The struct is now faster because it compiles format strings into Struct objects with pack() and unpack() methods. This is similar to how the re module lets you create compiled regular expression objects. You can still use the module-level pack() and unpack() functions; they'll create Struct objects and cache them. Or you can use Struct instances directly:

  s = struct.Struct('ih3s')
  
  data = s.pack(1972, 187, 'abc')
  year, number, name = s.unpack(data)
  

  You can also pack and unpack data to and from buffer objects directly using the pack_into(buffer, offset, v1, v2, ...) and unpack_from(buffer, offset) methods. This lets you store data directly into an array or a memory-mapped file.

  (Struct objects were implemented by Bob Ippolito at the NeedForSpeed sprint. Support for buffer objects was added by Martin Blais, also at the NeedForSpeed sprint.)

• The Python developers switched from CVS to Subversion during the 2.5 development process. Information about the exact build version is available as the sys.subversion variable, a 3-tuple of (interpreter-name, branch-name, revision-range). For example, at the time of writing my copy of 2.5 was reporting ('CPython', 'trunk', '45313:45315').

  This information is also available to C extensions via the Py_GetBuildInfo() function that returns a string of build information like this: "trunk:45355:45356M, Apr 13 2006, 07:42:19". (Contributed by Barry Warsaw.)

• Another new function, sys._current_frames(), returns the current stack frames for all running threads as a dictionary mapping thread identifiers to the topmost stack frame currently active in that thread at the time the function is called. (Contributed by Tim Peters.)

• The TarFile class in the tarfile module now has an extractall() method that extracts all members from the archive into the current working directory. It's also possible to set a different directory as the extraction target, and to unpack only a subset of the archive's members.

  The compression used for a tarfile opened in stream mode can now be autodetected using the mode 'r|*'. (Contributed by Lars Gustäbel.)

• The threading module now lets you set the stack size used when new threads are created. The stack_size([size]) function returns the currently configured stack size, and supplying the optional size parameter sets a new value. Not all platforms support changing the stack size, but Windows, POSIX threading, and OS/2 all do. (Contributed by Andrew MacIntyre.)

• The unicodedata module has been updated to use version 4.1.0 of the Unicode character database. Version 3.2.0 is required by some specifications, so it's still available as unicodedata.ucd_3_2_0.

• New module: the uuid module generates universally unique identifiers (UUIDs) according to RFC 4122. The RFC defines several different UUID versions that are generated from a starting string, from system properties, or purely randomly. This module contains a UUID class and functions named uuid1(), uuid3(), uuid4(), and uuid5() to generate different versions of UUID. (Version 2 UUIDs are not specified in RFC 4122 and are not supported by this module.)

  >>> import uuid
  >>> # make a UUID based on the host ID and current time
  >>> uuid.uuid1()
  UUID('a8098c1a-f86e-11da-bd1a-00112444be1e')
  
  >>> # make a UUID using an MD5 hash of a namespace UUID and a name
  >>> uuid.uuid3(uuid.NAMESPACE_DNS, 'python.org')
  UUID('6fa459ea-ee8a-3ca4-894e-db77e160355e')
  
  >>> # make a random UUID
  >>> uuid.uuid4()
  UUID('16fd2706-8baf-433b-82eb-8c7fada847da')
  
  >>> # make a UUID using a SHA-1 hash of a namespace UUID and a name
  >>> uuid.uuid5(uuid.NAMESPACE_DNS, 'python.org')
  UUID('886313e1-3b8a-5372-9b90-0c9aee199e5d')
  

  (Contributed by Ka-Ping Yee.)

• The weakref module's WeakKeyDictionary and WeakValueDictionary types gained new methods for iterating over the weak references contained in the dictionary. iterkeyrefs() and keyrefs() methods were added to WeakKeyDictionary, and itervaluerefs() and valuerefs() were added to WeakValueDictionary. (Contributed by Fred L. Drake, Jr.)

• The webbrowser module received a number of enhancements. It's now usable as a script with python -m webbrowser, taking a URL as the argument; there are a number of switches to control the behaviour (-n for a new browser window, -t for a new tab). New module-level functions, open_new() and open_new_tab(), were added to support this. The module's open() function supports an additional feature, an autoraise parameter that signals whether to raise the open window when possible. A number of additional browsers were added to the supported list such as Firefox, Opera, Konqueror, and elinks. (Contributed by Oleg Broytmann and Georg Brandl.)

• The xmlrpclib module now supports returning datetime objects for the XML-RPC date type. Supply use_datetime=True to the loads() function or the Unmarshaller class to enable this feature. (Contributed by Skip Montanaro.)

• The zipfile module now supports the ZIP64 version of the format, meaning that a .zip archive can now be larger than 4 GiB and can contain individual files larger than 4 GiB. (Contributed by Ronald Oussoren.)

• The zlib module's Compress and Decompress objects now support a copy() method that makes a copy of the object's internal state and returns a new Compress or Decompress object. (Contributed by Chris AtLee.)

13.1 The ctypes package

The ctypes package, written by Thomas Heller, has been added to the standard library. ctypes lets you call arbitrary functions in shared libraries or DLLs. Long-time users may remember the dl module, which provides functions for loading shared libraries and calling functions in them. The ctypes package is much fancier.

To load a shared library or DLL, you must create an instance of the CDLL class and provide the name or path of the shared library or DLL. Once that's done, you can call arbitrary functions by accessing them as attributes of the CDLL object.

import ctypes

libc = ctypes.CDLL('libc.so.6')
result = libc.printf("Line of output\n")

Type constructors for the various C types are provided: c_int, c_float, c_double, c_char_p (equivalent to char *), and so forth. Unlike Python's types, the C versions are all mutable; you can assign to their value attribute to change the wrapped value. Python integers and strings will be automatically converted to the corresponding C types, but for other types you must call the correct type constructor. (And I mean must; getting it wrong will often result in the interpreter crashing with a segmentation fault.)

You shouldn't use c_char_p with a Python string when the C function will be modifying the memory area, because Python strings are supposed to be immutable; breaking this rule will cause puzzling bugs. When you need a modifiable memory area, use create_string_buffer():

s = "this is a string"
buf = ctypes.create_string_buffer(s)
libc.strfry(buf)

C functions are assumed to return integers, but you can set the restype attribute of the function object to change this:

>>> libc.atof('2.71828')
-1783957616
>>> libc.atof.restype = ctypes.c_double
>>> libc.atof('2.71828')
2.71828

ctypes also provides a wrapper for Python's C API as the ctypes.pythonapi object. This object does not release the global interpreter lock before calling a function, because the lock must be held when calling into the interpreter's code. There's a py_object() type constructor that will create a PyObject * pointer. A simple usage:

import ctypes

d = {}
ctypes.pythonapi.PyObject_SetItem(ctypes.py_object(d),
          ctypes.py_object("abc"),  ctypes.py_object(1))
# d is now {'abc', 1}.

Don't forget to use py_object(); if it's omitted you end up with a segmentation fault.

ctypes has been around for a while, but people still write and distribution hand-coded extension modules because you can't rely on ctypes being present. Perhaps developers will begin to write Python wrappers atop a library accessed through ctypes instead of extension modules, now that ctypes is included with core Python.

13.2 The ElementTree package

A subset of Fredrik Lundh's ElementTree library for processing XML has been added to the standard library as xml.etree. The available modules are ElementTree, ElementPath, and ElementInclude from ElementTree 1.2.6. The cElementTree accelerator module is also included.

The rest of this section will provide a brief overview of using ElementTree. Full documentation for ElementTree is available at http://effbot.org/zone/element-index.htm.

ElementTree represents an XML document as a tree of element nodes. The text content of the document is stored as the .text and .tail attributes of (This is one of the major differences between ElementTree and the Document Object Model; in the DOM there are many different types of node, including TextNode.)

The most commonly used parsing function is parse(), that takes either a string (assumed to contain a filename) or a file-like object and returns an ElementTree instance:

from xml.etree import ElementTree as ET

tree = ET.parse('ex-1.xml')

feed = urllib.urlopen(
          'http://planet.python.org/rss10.xml')
tree = ET.parse(feed)

Once you have an ElementTree instance, you can call its getroot() method to get the root Element node.

There's also an XML() function that takes a string literal and returns an Element node (not an ElementTree). This function provides a tidy way to incorporate XML fragments, approaching the convenience of an XML literal:

svg = ET.XML("""<svg width="10px" version="1.0">
             </svg>""")
svg.set('height', '320px')
svg.append(elem1)

Each XML element supports some dictionary-like and some list-like access methods. Dictionary-like operations are used to access attribute values, and list-like operations are used to access child nodes.

Comments and processing instructions are also represented as Element nodes. To check if a node is a comment or processing instructions:

if elem.tag is ET.Comment:
    ...
elif elem.tag is ET.ProcessingInstruction:
    ...

To generate XML output, you should call the ElementTree.write() method. Like parse(), it can take either a string or a file-like object:

# Encoding is US-ASCII
tree.write('output.xml')

# Encoding is UTF-8
f = open('output.xml', 'w')
tree.write(f, encoding='utf-8')

(Caution: the default encoding used for output is ASCII. For general XML work, where an element's name may contain arbitrary Unicode characters, ASCII isn't a very useful encoding because it will raise an exception if an element's name contains any characters with values greater than 127. Therefore, it's best to specify a different encoding such as UTF-8 that can handle any Unicode character.)

This section is only a partial description of the ElementTree interfaces. Please read the package's official documentation for more details.

13.3 The hashlib package

A new hashlib module, written by Gregory P. Smith, has been added to replace the md5 and sha modules. hashlib adds support for additional secure hashes (SHA-224, SHA-256, SHA-384, and SHA-512). When available, the module uses OpenSSL for fast platform optimized implementations of algorithms.

The old md5 and sha modules still exist as wrappers around hashlib to preserve backwards compatibility. The new module's interface is very close to that of the old modules, but not identical. The most significant difference is that the constructor functions for creating new hashing objects are named differently.

# Old versions
h = md5.md5()   
h = md5.new()   

# New version 
h = hashlib.md5()

# Old versions
h = sha.sha()   
h = sha.new()   

# New version 
h = hashlib.sha1()

# Hash that weren't previously available
h = hashlib.sha224()
h = hashlib.sha256()
h = hashlib.sha384()
h = hashlib.sha512()

# Alternative form
h = hashlib.new('md5')          # Provide algorithm as a string

Once a hash object has been created, its methods are the same as before: update(string) hashes the specified string into the current digest state, digest() and hexdigest() return the digest value as a binary string or a string of hex digits, and copy() returns a new hashing object with the same digest state.

13.4 The sqlite3 package

The pysqlite module (http://www.pysqlite.org), a wrapper for the SQLite embedded database, has been added to the standard library under the package name sqlite3.

SQLite is a C library that provides a SQL-language database that stores data in disk files without requiring a separate server process. pysqlite was written by Gerhard Häring and provides a SQL interface compliant with the DB-API 2.0 specification described by PEP 249. This means that it should be possible to write the first version of your applications using SQLite for data storage. If switching to a larger database such as PostgreSQL or Oracle is later necessary, the switch should be relatively easy.

If you're compiling the Python source yourself, note that the source tree doesn't include the SQLite code, only the wrapper module. You'll need to have the SQLite libraries and headers installed before compiling Python, and the build process will compile the module when the necessary headers are available.

To use the module, you must first create a Connection object that represents the database. Here the data will be stored in the /tmp/example file:

conn = sqlite3.connect('/tmp/example')

You can also supply the special name ":memory:" to create a database in RAM.

Once you have a Connection, you can create a Cursor object and call its execute() method to perform SQL commands:

c = conn.cursor()

# Create table
c.execute('''create table stocks
(date timestamp, trans varchar, symbol varchar,
 qty decimal, price decimal)''')

# Insert a row of data
c.execute("""insert into stocks
          values ('2006-01-05','BUY','RHAT',100,35.14)""")

Usually your SQL operations will need to use values from Python variables. You shouldn't assemble your query using Python's string operations because doing so is insecure; it makes your program vulnerable to an SQL injection attack.

Instead, use the DB-API's parameter substitution. Put "?" as a placeholder wherever you want to use a value, and then provide a tuple of values as the second argument to the cursor's execute() method. (Other database modules may use a different placeholder, such as "%s" or ":1".) For example:

    
# Never do this -- insecure!
symbol = 'IBM'
c.execute("... where symbol = '%s'" % symbol)

# Do this instead
t = (symbol,)
c.execute('select * from stocks where symbol=?', t)

# Larger example
for t in (('2006-03-28', 'BUY', 'IBM', 1000, 45.00),
          ('2006-04-05', 'BUY', 'MSOFT', 1000, 72.00),
          ('2006-04-06', 'SELL', 'IBM', 500, 53.00),
         ):
    c.execute('insert into stocks values (?,?,?,?,?)', t)

To retrieve data after executing a SELECT statement, you can either treat the cursor as an iterator, call the cursor's fetchone() method to retrieve a single matching row, or call fetchall() to get a list of the matching rows.

This example uses the iterator form:

>>> c = conn.cursor()
>>> c.execute('select * from stocks order by price')
>>> for row in c:
...    print row
...
(u'2006-01-05', u'BUY', u'RHAT', 100, 35.140000000000001)
(u'2006-03-28', u'BUY', u'IBM', 1000, 45.0)
(u'2006-04-06', u'SELL', u'IBM', 500, 53.0)
(u'2006-04-05', u'BUY', u'MSOFT', 1000, 72.0)
>>>

For more information about the SQL dialect supported by SQLite, see http://www.sqlite.org.

13.5 The wsgiref package

The Web Server Gateway Interface (WSGI) v1.0 defines a standard interface between web servers and Python web applications and is described in PEP 333. The wsgiref package is a reference implementation of the WSGI specification.

The package includes a basic HTTP server that will run a WSGI application; this server is useful for debugging but isn't intended for production use. Setting up a server takes only a few lines of code:

from wsgiref import simple_server

wsgi_app = ...

host = ''
port = 8000
httpd = simple_server.make_server(host, port, wsgi_app)
httpd.serve_forever()

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What's New in Python 2.5

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