
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 name is encountered
in an import statement. [1] (They are also run if the file is executed
as a script.)

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 first searches
for a built-in module with that name. If not found, it then searches
for a file named "spam.py" in a list of directories given by the
variable "sys.path".  "sys.path" is initialized from these locations:

* the directory containing the input script (or the current
  directory).

* "PYTHONPATH" (a list of directory names, with the same syntax as
  the shell variable "PATH").

* the installation-dependent default.

After initialization, Python programs can modify "sys.path".  The
directory containing the script being run is placed at the beginning
of the search path, ahead of the standard library path. This means
that scripts in that directory will be loaded instead of modules of
the same name in the library directory. This is an error unless the
replacement is intended.  See section *Standard Modules* for more
information.


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

To speed up loading modules, Python caches the compiled version of
each module in the "__pycache__" directory under the name
"module.*version*.pyc", where the version encodes the format of the
compiled file; it generally contains the Python version number.  For
example, in CPython release 3.3 the compiled version of spam.py would
be cached as "__pycache__/spam.cpython-33.pyc".  This naming
convention allows compiled modules from different releases and
different versions of Python to coexist.

Python checks the modification date of the source against the compiled
version to see if it's out of date and needs to be recompiled.  This
is a completely automatic process.  Also, the compiled modules are
platform-independent, so the same library can be shared among systems
with different architectures.

Python does not check the cache in two circumstances.  First, it
always recompiles and does not store the result for the module that's
loaded directly from the command line.  Second, it does not check the
cache if there is no source module.  To support a non-source (compiled
only) distribution, the compiled module must be in the source
directory, and there must not be a source module.

Some tips for experts:

* You can use the *-O* or *-OO* switches on the Python command to
  reduce the size of a compiled module.  The "-O" switch removes
  assert statements, the "-OO" switch removes both assert statements
  and __doc__ strings.  Since some programs may rely on having these
  available, you should only use this option if you know what you're
  doing.  "Optimized" modules have a .pyo rather than a .pyc suffix
  and are usually smaller.  Future releases may change the effects of
  optimization.

* 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.

* The module "compileall" can create .pyc files (or .pyo files when
  *-O* is used) for all modules in a directory.

* There is more detail on this process, including a flow chart of
  the decisions, in PEP 3147.


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)  # doctest: +NORMALIZE_WHITESPACE
   ['__displayhook__', '__doc__', '__egginsert', '__excepthook__',
    '__loader__', '__name__', '__package__', '__plen', '__stderr__',
    '__stdin__', '__stdout__', '_clear_type_cache', '_current_frames',
    '_debugmallocstats', '_getframe', '_home', '_mercurial', '_xoptions',
    'abiflags', 'api_version', 'argv', 'base_exec_prefix', 'base_prefix',
    'builtin_module_names', 'byteorder', 'call_tracing', 'callstats',
    'copyright', 'displayhook', 'dont_write_bytecode', 'exc_info',
    'excepthook', 'exec_prefix', 'executable', 'exit', 'flags', 'float_info',
    'float_repr_style', 'getcheckinterval', 'getdefaultencoding',
    'getdlopenflags', 'getfilesystemencoding', 'getobjects', 'getprofile',
    'getrecursionlimit', 'getrefcount', 'getsizeof', 'getswitchinterval',
    'gettotalrefcount', 'gettrace', 'hash_info', 'hexversion',
    'implementation', 'int_info', 'intern', 'maxsize', 'maxunicode',
    'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_cache',
    'platform', 'prefix', 'ps1', 'setcheckinterval', 'setdlopenflags',
    'setprofile', 'setrecursionlimit', 'setswitchinterval', 'settrace',
    'stderr', 'stdin', 'stdout', 'thread_info', '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__', '__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)  # doctest: +NORMALIZE_WHITESPACE
   ['ArithmeticError', 'AssertionError', 'AttributeError', 'BaseException',
    'BlockingIOError', 'BrokenPipeError', 'BufferError', 'BytesWarning',
    'ChildProcessError', 'ConnectionAbortedError', 'ConnectionError',
    'ConnectionRefusedError', 'ConnectionResetError', 'DeprecationWarning',
    'EOFError', 'Ellipsis', 'EnvironmentError', 'Exception', 'False',
    'FileExistsError', 'FileNotFoundError', 'FloatingPointError',
    'FutureWarning', 'GeneratorExit', 'IOError', 'ImportError',
    'ImportWarning', 'IndentationError', 'IndexError', 'InterruptedError',
    'IsADirectoryError', 'KeyError', 'KeyboardInterrupt', 'LookupError',
    'MemoryError', 'NameError', 'None', 'NotADirectoryError', 'NotImplemented',
    'NotImplementedError', 'OSError', 'OverflowError',
    'PendingDeprecationWarning', 'PermissionError', 'ProcessLookupError',
    'ReferenceError', 'ResourceWarning', 'RuntimeError', 'RuntimeWarning',
    'StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError',
    'SystemExit', 'TabError', 'TimeoutError', 'True', 'TypeError',
    'UnboundLocalError', 'UnicodeDecodeError', 'UnicodeEncodeError',
    'UnicodeError', 'UnicodeTranslateError', 'UnicodeWarning', 'UserWarning',
    'ValueError', 'Warning', 'ZeroDivisionError', '_', '__build_class__',
    '__debug__', '__doc__', '__import__', '__name__', '__package__', 'abs',
    'all', 'any', 'ascii', 'bin', 'bool', 'bytearray', 'bytes', 'callable',
    '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', 'memoryview',
    'min', 'next', 'object', 'oct', 'open', 'ord', 'pow', 'print', 'property',
    'quit', 'range', 'repr', 'reversed', 'round', 'set', 'setattr', 'slice',
    'sorted', '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 "sound/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 definition
    enters the function name in the module's global symbol table.
