
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, end=' ')
           a, b = b, a+b
       print()

   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


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. [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
(``_``). In most cases Python programmers do not use this facility
since it introduces an unknown set of names into the interpreter,
possibly hiding some things you have already 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.

Note: For efficiency reasons, each module is only imported once per
  interpreter session.  Therefore, if you change your modules, you
  must restart the interpreter -- or, if it's just one module you want
  to test interactively, use ``imp.reload()``, e.g. ``import imp;
  imp.reload(modulename)``.


Executing modules as scripts
----------------------------

When you run a Python module with

   python fibo.py <arguments>

the code in the module will be executed, just as if you imported it,
but with the ``__name__`` set to ``"__main__"``.  That means that by
adding this code at the end of your module:

   if __name__ == "__main__":
       import sys
       fib(int(sys.argv[1]))

you can make the file usable as a script as well as an importable
module, because the code that parses the command line only runs if the
module is executed as the "main" file:

   $ python fibo.py 50
   1 1 2 3 5 8 13 21 34

If the module is imported, the code is not run:

   >>> import fibo
   >>>

This is often used either to provide a convenient user interface to a
module, or for testing purposes (running the module as a script
executes a test suite).


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 *Standard Modules* for more information.


"Compiled" Python files
-----------------------

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.


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 ``winreg`` module is only
provided on Windows systems. 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 determines 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 ``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_info', '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
   >>> fib = fibo.fib
   >>> dir()
   ['__builtins__', '__doc__', '__file__', '__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
``builtins``:

   >>> import builtins
   >>> dir(builtins)

   ['ArithmeticError', 'AssertionError', 'AttributeError', 'BaseException', 'Buffer
   Error', 'BytesWarning', 'DeprecationWarning', 'EOFError', 'Ellipsis', 'Environme
   ntError', 'Exception', 'False', 'FloatingPointError', 'FutureWarning', 'Generato
   rExit', 'IOError', 'ImportError', 'ImportWarning', 'IndentationError', 'IndexErr
   or', 'KeyError', 'KeyboardInterrupt', 'LookupError', 'MemoryError', 'NameError',
    'None', 'NotImplemented', 'NotImplementedError', 'OSError', 'OverflowError', 'P
   endingDeprecationWarning', 'ReferenceError', 'RuntimeError', 'RuntimeWarning', '
   StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError', 'SystemExit', 'Ta
   bError', 'True', 'TypeError', 'UnboundLocalError', 'UnicodeDecodeError', 'Unicod
   eEncodeError', 'UnicodeError', 'UnicodeTranslateError', 'UnicodeWarning', 'UserW
   arning', 'ValueError', 'Warning', 'ZeroDivisionError', '__build_class__', '__deb
   ug__', '__doc__', '__import__', '__name__', '__package__', 'abs', 'all', 'any',
   'ascii', 'bin', 'bool', 'bytearray', 'bytes', 'chr', 'classmethod', 'compile', '
   complex', 'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod', 'enumerate
   ', 'eval', 'exec', 'exit', 'filter', 'float', 'format', 'frozenset', 'getattr',
   'globals', 'hasattr', 'hash', 'help', 'hex', 'id', 'input', 'int', 'isinstance',
    'issubclass', 'iter', 'len', 'license', 'list', 'locals', 'map', 'max', 'memory
   view', 'min', 'next', 'object', 'oct', 'open', 'ord', 'pow', 'print', 'property'
   , 'quit', 'range', 'repr', 'reversed', 'round', 'set', 'setattr', 'slice', 'sort
   ed', 'staticmethod', 'str', 'sum', 'super', 'tuple', 'type', 'vars', 'zip']


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.


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.  This could take a long time and importing sub-modules might have
unwanted side-effects that should only happen when the sub-module is
explicitly imported.

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 any
initialization code in ``__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.)

Although certain modules are designed to export only names that follow
certain patterns when you use ``import *``, it is still considered bad
practise in production code.

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.


Intra-package References
------------------------

When packages are structured into subpackages (as with the ``sound``
package in the example), you can use absolute imports to refer to
submodules of siblings packages.  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``.

You can also write relative imports, with the ``from module import
name`` form of import statement.  These imports use leading dots to
indicate the current and parent packages involved in the relative
import.  From the ``surround`` module for example, you might use:

   from . import echo
   from .. import formats
   from ..filters import equalizer

Note that relative imports are based on the name of the current
module.  Since the name of the main module is always ``"__main__"``,
modules intended for use as the main module of a Python application
must always use absolute imports.


Packages in Multiple Directories
--------------------------------

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 ]-

[1] In fact function definitions are also 'statements' that are
    'executed'; the execution of a module-level function enters the
    function name in the module's global symbol table.
