 |
 |
 |
Python Tutorial |  |
 |
 |
|
|
|
Python Tutorial | |
|
|
If you quit from the Python interpreter and enter it again, the definitions you have made (functions and variables) are lost. Therefore, if you want to write a somewhat longer program, you are better off using a text editor to prepare the input for the interpreter and running it with that file as input instead. This is known as creating a script. As your program gets longer, you may want to split it into several files for easier maintenance. You may also want to use a handy function that you've written in several programs without copying its definition into each program.
To support this, Python has a way to put definitions in a file and use them in a script or in an interactive instance of the interpreter. Such a file is called a module; definitions from a module can be imported into other modules or into the main module (the collection of variables that you have access to in a script executed at the top level and in calculator mode).
A module is a file containing Python definitions and statements. The
file name is the module name with the suffix .py appended. Within
a module, the module's name (as a string) is available as the value of
the global variable __name__. For instance, use your favorite text
editor to create a file called fibo.py in the current directory
with the following contents:
# Fibonacci numbers module
def fib(n): # write Fibonacci series up to n
a, b = 0, 1
while b < n:
print b,
a, b = b, a+b
def fib2(n): # return Fibonacci series up to n
result = []
a, b = 0, 1
while b < n:
result.append(b)
a, b = b, a+b
return result
Now enter the Python interpreter and import this module with the following command:
>>> import fibo
This does not enter the names of the functions defined in fibo
directly in the current symbol table; it only enters the module name
fibo there.
Using the module name you can access the functions:
>>> fibo.fib(1000) 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 >>> fibo.fib2(100) [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] >>> fibo.__name__ 'fibo'
If you intend to use a function often you can assign it to a local name:
>>> fib = fibo.fib >>> fib(500) 1 1 2 3 5 8 13 21 34 55 89 144 233 377
A module can contain executable statements as well as function definitions. These statements are intended to initialize the module. They are executed only the first time the module is imported somewhere.6.1
Each module has its own private symbol table, which is used as the
global symbol table by all functions defined in the module.
Thus, the author of a module can use global variables in the module
without worrying about accidental clashes with a user's global
variables.
On the other hand, if you know what you are doing you can touch a
module's global variables with the same notation used to refer to its
functions,
modname.itemname.
Modules can import other modules. It is customary but not required to place all import statements at the beginning of a module (or script, for that matter). The imported module names are placed in the importing module's global symbol table.
There is a variant of the import statement that imports names from a module directly into the importing module's symbol table. For example:
>>> from fibo import fib, fib2 >>> fib(500) 1 1 2 3 5 8 13 21 34 55 89 144 233 377
This does not introduce the module name from which the imports are taken
in the local symbol table (so in the example, fibo is not
defined).
There is even a variant to import all names that a module defines:
>>> from fibo import * >>> fib(500) 1 1 2 3 5 8 13 21 34 55 89 144 233 377
This imports all names except those beginning with an underscore
(_).
When a module named spam is imported, the interpreter searches for a file named spam.py in the current directory, and then in the list of directories specified by the environment variable PYTHONPATH. This has the same syntax as the shell variable PATH, that is, a list of directory names. When PYTHONPATH is not set, or when the file is not found there, the search continues in an installation-dependent default path; on Unix, this is usually .:/usr/local/lib/python.
Actually, modules are searched in the list of directories given by the
variable sys.path which is initialized from the directory
containing the input script (or the current directory),
PYTHONPATH and the installation-dependent default. This allows
Python programs that know what they're doing to modify or replace the
module search path. Note that because the directory containing the
script being run is on the search path, it is important that the
script not have the same name as a standard module, or Python will
attempt to load the script as a module when that module is imported.
This will generally be an error. See section 6.2,
``Standard Modules,'' for more information.
As an important speed-up of the start-up time for short programs that use a lot of standard modules, if a file called spam.pyc exists in the directory where spam.py is found, this is assumed to contain an already-``byte-compiled'' version of the module spam. The modification time of the version of spam.py used to create spam.pyc is recorded in spam.pyc, and the .pyc file is ignored if these don't match.
Normally, you don't need to do anything to create the spam.pyc file. Whenever spam.py is successfully compiled, an attempt is made to write the compiled version to spam.pyc. It is not an error if this attempt fails; if for any reason the file is not written completely, the resulting spam.pyc file will be recognized as invalid and thus ignored later. The contents of the spam.pyc file are platform independent, so a Python module directory can be shared by machines of different architectures.
Some tips for experts:
.pyc files are ignored and .py
files are compiled to optimized bytecode.
__doc__ strings are removed from the
bytecode, resulting in more compact .pyo files. Since some
programs may rely on having these available, you should only use this
option if you know what you're doing.
Python comes with a library of standard modules, described in a separate
document, the Python Library Reference
(``Library Reference'' hereafter). Some modules are built into the
interpreter; these provide access to operations that are not part of
the core of the language but are nevertheless built in, either for
efficiency or to provide access to operating system primitives such as
system calls. The set of such modules is a configuration option which
also depends on the underlying platform For example,
the amoeba module is only provided on systems that somehow
support Amoeba primitives. One particular module deserves some
attention: sys, which is built into every
Python interpreter. The variables sys.ps1 and
sys.ps2 define the strings used as primary and secondary
prompts:
>>> import sys >>> sys.ps1 '>>> ' >>> sys.ps2 '... ' >>> sys.ps1 = 'C> ' C> print 'Yuck!' Yuck! C>
These two variables are only defined if the interpreter is in interactive mode.
The variable sys.path is a list of strings that determine the
interpreter's search path for modules. It is initialized to a default
path taken from the environment variable PYTHONPATH, or from
a built-in default if PYTHONPATH is not set. You can modify
it using standard list operations:
>>> import sys
>>> sys.path.append('/ufs/guido/lib/python')
The built-in function dir() is used to find out which names a module defines. It returns a sorted list of strings:
>>> import fibo, sys >>> dir(fibo) ['__name__', 'fib', 'fib2'] >>> dir(sys) ['__displayhook__', '__doc__', '__excepthook__', '__name__', '__stderr__', '__stdin__', '__stdout__', '_getframe', 'api_version', 'argv', 'builtin_module_names', 'byteorder', 'callstats', 'copyright', 'displayhook', 'exc_clear', 'exc_info', 'exc_type', 'excepthook', 'exec_prefix', 'executable', 'exit', 'getdefaultencoding', 'getdlopenflags', 'getrecursionlimit', 'getrefcount', 'hexversion', 'maxint', 'maxunicode', 'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_cache', 'platform', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setdlopenflags', 'setprofile', 'setrecursionlimit', 'settrace', 'stderr', 'stdin', 'stdout', 'version', 'version_info', 'warnoptions']
Without arguments, dir() lists the names you have defined currently:
>>> a = [1, 2, 3, 4, 5] >>> import fibo, sys >>> fib = fibo.fib >>> dir() ['__name__', 'a', 'fib', 'fibo', 'sys']
Note that it lists all types of names: variables, modules, functions, etc.
dir() does not list the names of built-in functions and variables. If you want a list of those, they are defined in the standard module __builtin__:
>>> import __builtin__ >>> dir(__builtin__) ['ArithmeticError', 'AssertionError', 'AttributeError', 'DeprecationWarning', 'EOFError', 'Ellipsis', 'EnvironmentError', 'Exception', 'False', 'FloatingPointError', 'IOError', 'ImportError', 'IndentationError', 'IndexError', 'KeyError', 'KeyboardInterrupt', 'LookupError', 'MemoryError', 'NameError', 'None', 'NotImplemented', 'NotImplementedError', 'OSError', 'OverflowError', 'OverflowWarning', 'PendingDeprecationWarning', 'ReferenceError', 'RuntimeError', 'RuntimeWarning', 'StandardError', 'StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError', 'SystemExit', 'TabError', 'True', 'TypeError', 'UnboundLocalError', 'UnicodeError', 'UserWarning', 'ValueError', 'Warning', 'ZeroDivisionError', '__debug__', '__doc__', '__import__', '__name__', 'abs', 'apply', 'bool', 'buffer', 'callable', 'chr', 'classmethod', 'cmp', 'coerce', 'compile', 'complex', 'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod', 'enumerate', 'eval', 'execfile', 'exit', 'file', 'filter', 'float', 'getattr', 'globals', 'hasattr', 'hash', 'help', 'hex', 'id', 'input', 'int', 'intern', 'isinstance', 'issubclass', 'iter', 'len', 'license', 'list', 'locals', 'long', 'map', 'max', 'min', 'object', 'oct', 'open', 'ord', 'pow', 'property', 'quit', 'range', 'raw_input', 'reduce', 'reload', 'repr', 'round', 'setattr', 'slice', 'staticmethod', 'str', 'string', 'sum', 'super', 'tuple', 'type', 'unichr', 'unicode', 'vars', 'xrange', 'zip']
Packages are a way of structuring Python's module namespace by using ``dotted module names''. For example, the module name A.B designates a submodule named "B" in a package named "A". Just like the use of modules saves the authors of different modules from having to worry about each other's global variable names, the use of dotted module names saves the authors of multi-module packages like NumPy or the Python Imaging Library from having to worry about each other's module names.
Suppose you want to design a collection of modules (a ``package'') for the uniform handling of sound files and sound data. There are many different sound file formats (usually recognized by their extension, for example: .wav, .aiff, .au), so you may need to create and maintain a growing collection of modules for the conversion between the various file formats. There are also many different operations you might want to perform on sound data (such as mixing, adding echo, applying an equalizer function, creating an artificial stereo effect), so in addition you will be writing a never-ending stream of modules to perform these operations. Here's a possible structure for your package (expressed in terms of a hierarchical filesystem):
Sound/ Top-level package
__init__.py Initialize the sound package
Formats/ Subpackage for file format conversions
__init__.py
wavread.py
wavwrite.py
aiffread.py
aiffwrite.py
auread.py
auwrite.py
...
Effects/ Subpackage for sound effects
__init__.py
echo.py
surround.py
reverse.py
...
Filters/ Subpackage for filters
__init__.py
equalizer.py
vocoder.py
karaoke.py
...
When importing the package, Python searches through the directories
on sys.path looking for the package subdirectory.
The __init__.py files are required to make Python treat the
directories as containing packages; this is done to prevent
directories with a common name, such as "string", from
unintentionally hiding valid modules that occur later on the module
search path. In the simplest case, __init__.py can just be an
empty file, but it can also execute initialization code for the
package or set the __all__ variable, described later.
Users of the package can import individual modules from the package, for example:
import Sound.Effects.echo
This loads the submodule Sound.Effects.echo. It must be referenced with its full name.
Sound.Effects.echo.echofilter(input, output, delay=0.7, atten=4)
An alternative way of importing the submodule is:
from Sound.Effects import echo
This also loads the submodule echo, and makes it available without its package prefix, so it can be used as follows:
echo.echofilter(input, output, delay=0.7, atten=4)
Yet another variation is to import the desired function or variable directly:
from Sound.Effects.echo import echofilter
Again, this loads the submodule echo, but this makes its function echofilter() directly available:
echofilter(input, output, delay=0.7, atten=4)
Note that when using from package import item, the
item can be either a submodule (or subpackage) of the package, or some
other name defined in the package, like a function, class or
variable. The import statement first tests whether the item is
defined in the package; if not, it assumes it is a module and attempts
to load it. If it fails to find it, an
ImportError exception is raised.
Contrarily, when using syntax like import
item.subitem.subsubitem, each item except for the last must be
a package; the last item can be a module or a package but can't be a
class or function or variable defined in the previous item.
Now what happens when the user writes from Sound.Effects import
*? Ideally, one would hope that this somehow goes out to the
filesystem, finds which submodules are present in the package, and
imports them all. Unfortunately, this operation does not work very
well on Mac and Windows platforms, where the filesystem does not
always have accurate information about the case of a filename! On
these platforms, there is no guaranteed way to know whether a file
ECHO.PY should be imported as a module echo,
Echo or ECHO. (For example, Windows 95 has the
annoying practice of showing all file names with a capitalized first
letter.) The DOS 8+3 filename restriction adds another interesting
problem for long module names.
The only solution is for the package author to provide an explicit
index of the package. The import statement uses the following
convention: if a package's __init__.py code defines a list
named __all__, it is taken to be the list of module names that
should be imported when from package import * is
encountered. It is up to the package author to keep this list
up-to-date when a new version of the package is released. Package
authors may also decide not to support it, if they don't see a use for
importing * from their package. For example, the file
Sounds/Effects/__init__.py could contain the following code:
__all__ = ["echo", "surround", "reverse"]
This would mean that from Sound.Effects import * would
import the three named submodules of the Sound package.
If __all__ is not defined, the statement from Sound.Effects
import * does not import all submodules from the package
Sound.Effects into the current namespace; it only ensures that the
package Sound.Effects has been imported (possibly running its
initialization code, __init__.py) and then imports whatever names are
defined in the package. This includes any names defined (and
submodules explicitly loaded) by __init__.py. It also includes any
submodules of the package that were explicitly loaded by previous
import statements. Consider this code:
import Sound.Effects.echo import Sound.Effects.surround from Sound.Effects import *
In this example, the echo and surround modules are imported in the
current namespace because they are defined in the
Sound.Effects package when the from...import statement
is executed. (This also works when __all__ is defined.)
Note that in general the practice of importing * from a module or
package is frowned upon, since it often causes poorly readable code.
However, it is okay to use it to save typing in interactive sessions,
and certain modules are designed to export only names that follow
certain patterns.
Remember, there is nothing wrong with using from Package
import specific_submodule! In fact, this is the
recommended notation unless the importing module needs to use
submodules with the same name from different packages.
The submodules often need to refer to each other. For example, the
surround module might use the echo module. In fact,
such references
are so common that the import statement first looks in the
containing package before looking in the standard module search path.
Thus, the surround module can simply use import echo or
from echo import echofilter. If the imported module is not
found in the current package (the package of which the current module
is a submodule), the import statement looks for a top-level
module with the given name.
When packages are structured into subpackages (as with the
Sound package in the example), there's no shortcut to refer
to submodules of sibling packages - the full name of the subpackage
must be used. For example, if the module
Sound.Filters.vocoder needs to use the echo module
in the Sound.Effects package, it can use from
Sound.Effects import echo.
Packages support one more special attribute, __path__. This is initialized to be a list containing the name of the directory holding the package's __init__.py before the code in that file is executed. This variable can be modified; doing so affects future searches for modules and subpackages contained in the package.
While this feature is not often needed, it can be used to extend the set of modules found in a package.
|
|
|
Python Tutorial | |
|
|