6. Modules
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:
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
6.1 More on Modules
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 (_).
6.1.1 The Module Search Path
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:
- When the Python interpreter is invoked with the -O flag,
optimized code is generated and stored in .pyo files. The
optimizer currently doesn't help much; it only removes assert
statements. When -O is used, all bytecode is
optimized;
.pyc files are ignored and .py files are compiled
to optimized bytecode.
- Passing two -O flags to the Python interpreter (-OO) will cause the bytecode compiler to perform optimizations
that could in some rare cases result in malfunctioning programs. Currently only
__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.
- A program doesn't run any faster when it is read from a .pyc
or .pyo file than when it is read from a .py
file; the only thing that's faster about .pyc or .pyo files is the speed with which they are loaded.
- When a script is run by giving its name on the command line, the bytecode for the
script is never written to a .pyc or .pyo
file. Thus, the startup time of a script may be reduced by moving most of its code to
a module and having a small bootstrap script that imports that module. It is also
possible to name a .pyc or .pyo
file directly on the command line.
- It is possible to have a file called spam.pyc (or spam.pyo when -O is used) without a file
spam.py for the same module. This can be used to distribute
a library of Python code in a form that is moderately hard to reverse engineer.
- The module compileall
can create .pyc files (or .pyo
files when -O is used) for all modules in a directory.
6.2 Standard Modules
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')
6.3 The dir() Function
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']
6.4 Packages
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.
6.4.1 Importing * From a Package
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.
Footnotes
- ... somewhere.6.1
- In fact function definitions are also `statements' that are `executed'; the
execution enters the function name in the module's global symbol table.
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