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A Python decorator for converting a function into a module. It also includes tools for combining multiple Python files into one.

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Python Modulization

This project contains three Python tools:

  1. A decorator @modulize which converts a function into a (mock) Python module. This module can then be imported as usual. For example,

    @modulize('my_module')
    def my_dummy_function(__name__):  # the function takes one parameter __name__
        # put module code here
        def my_function(s): 
            print(s, 'bar')
    
        # the function must return locals()
        return locals()
    
    from my_module import my_function
    my_function('foo') # foo bar
  2. A Python script combine_py_files.py which combines a .py file and all the local .py files it imports into one .py file.

    One motivation for this tool is programming contests which require a contestant to submit a single .py file. This makes it is possible to break up a Python project into multiple .py files and combine them automatically in the end.

  3. A Python script sync_combined_py_files.py which runs in the background, keeping track of changes to both the combined file and the source files, syncing changes between them.


@modulize decorator

@modulize(module_name, dependencies=[])

The @modulize decorator (which can be found in modulization.py) works as follows:

# The code defining modulize is short and can be hard
# coded in place of this import line:
from modulization import modulize 

@modulize('a')
def dummy_function_a(__name__):
    """ Doc string for the module """
    def a_function(x, y):
        print(x)
        print(y)

    return locals()

@modulize('a.b.foo', dependencies=['a.b.foo'])
def dummy_function_foo(__name__):
    import a.b.bar as bar # mutually dependent modules

    foo_var = 'foo'

    def foo_func(x):
        return "{} is not {}".format(x, bar.bar_var)

    return locals()

@modulize('a.b.bar')
def the_name_of_this_function_does_not_matter(__name__):
    import a.b.foo as foo # mutually dependent modules

    bar_var = 'bar'

    def bar_func(x):
        return "{} is not {}".format(x, foo.foo_var)

    if __name__ == '__main__': # This will be skipped if __name__ is 
                               # the parameter of the dummy function!
       print(bar_func(bar_var))

    return locals()

if __name__ == '__main__':
    from a import a_function, b
    from b.foo import foo_func
    from b.bar import bar_func

    a_function(foo_func('baz'), bar_func('baz')) # baz is not foo
                                                 # baz is not bar

Here are a few fine points:

  • A module must be imported for it to be used.
  • Modules should be added in the order of their dependencies.
  • For the (rare) case of mutually dependent modules, one can pass a dependencies argument to @modulize. This is only needed when the module being added comes before the module it depends on. (Also, a.b.foo doesn't need to add a.b as a dependency. This is done automatically.)
  • The code in the dummy function is run at the time the dummy function is created, not at that time of import. Be careful, this may effect the desired behavior.
  • Unlike true modules, the code in the mock modules has access to global variables in the main code. However, this is not an issue if one avoids using global variables (or avoids referencing them inside the module code).

Code

import sys
from types import ModuleType

class MockModule(ModuleType):
    def __init__(self, module_name, module_doc=None):
        ModuleType.__init__(self, module_name, module_doc)
        if '.' in module_name:
            package, module = module_name.rsplit('.', 1)
            get_mock_module(package).__path__ = []
            setattr(get_mock_module(package), module, self)

    def _initialize_(self, module_code):
        self.__dict__.update(module_code(self.__name__))
        self.__doc__ = module_code.__doc__

def get_mock_module(module_name):
    if module_name not in sys.modules:
        sys.modules[module_name] = MockModule(module_name)
    return sys.modules[module_name]

def modulize(module_name, dependencies=[]):
    for d in dependencies: get_mock_module(d)
    return get_mock_module(module_name)._initialize_
  • @modulize creates a MockModule object (inheriting from types.ModuleType) which passes all attribute calls to the local variable dictionary returned by the underlying function.
  • This MockModule object is added to sys.modules. It's name is not in the name space until it is imported.
  • If the parameter of the dummy function is named __name__, then if __name__ == '__main__': conditions fail since we pass in the name of the module to the dummy function.
  • If a.b.c is added as a module, then a and a.b are automatically added as well if they are not already in sys.modules. Also a and a.b are marked as packages by setting their __path__ attribute.

Known issues

  • Relative imports, e.g. from . import foo are not supported.
  • Code inside the underlying function will be run at the time of creation, not the time of import.
  • The mock module code has access to global variables unlike in true modules.
  • Nonstandard behavior might be observed if a variable has the same name as a submodule (for example. a.b.foo = 5 as well as a module a.b.foo.)
  • The imp and importlib modules have not been tested.
  • This is ultimately a hack of the import system and one should not hope for an exact replica. Nonetheless, I tried to make it close!

combine_py_files.py script

Usage: python combine_py_files.py entry_point output_file

  • entry_point is the file or directory to start (as if one was running python entry_point). If it is a directory, it will start at the file __main__.py in that directory.
  • output_file is the name of the combined Python file.

Example

Directory structure and .py files:

my_dir/
    __main__.py

        import foo.bar
        fb = foo.bar.bar_func(foo.foo_var)
        print(fb) # foo bar

    foo/
        __init__.py

            foo_var = 'foo'

        bar.py
    
            def bar_func(x):
                return x + ' bar'

Running the script:

$ python combine_py_files.py my_dir/ combined.py
... foo/__init__.py
... foo/bar.py
... __main__.py
Successfully combined files.

combined.py:

import sys
from types import ModuleType

class MockModule(ModuleType):
    def __init__(self, module_name, module_doc=None):
        ModuleType.__init__(self, module_name, module_doc)
        if '.' in module_name:
            package, module = module_name.rsplit('.', 1)
            get_mock_module(package).__path__ = []
            setattr(get_mock_module(package), module, self)

    def _initialize_(self, module_code):
        self.__dict__.update(module_code(self.__name__))
        self.__doc__ = module_code.__doc__

def get_mock_module(module_name):
    if module_name not in sys.modules:
        sys.modules[module_name] = MockModule(module_name)
    return sys.modules[module_name]

def modulize(module_name, dependencies=[]):
    for d in dependencies: get_mock_module(d)
    return get_mock_module(module_name)._initialize_

##===========================================================================##

@modulize('foo')
def _foo(__name__):
    ##----- Begin foo/__init__.py ------------------------------------------------##
    foo_var = 'foo'
    ##----- End foo/__init__.py --------------------------------------------------##
    return locals()

@modulize('foo.bar')
def _bar(__name__):
    ##----- Begin foo/bar.py -----------------------------------------------------##
    def bar_func(x):
        return x + ' bar'
    ##----- End foo/bar.py -------------------------------------------------------##
    return locals()


def __main__():
    ##----- Begin __main__.py ----------------------------------------------------##
    import foo.bar
    fb = foo.bar.bar_func(foo.foo_var)
    print(fb) # foo bar
    ##----- End __main__.py ------------------------------------------------------##

__main__()

Notes

  • This script has a very basic logic to find the module files and to determine the order to load them.

    • First it looks for lines containing import ... or from ... import. These statements must be on their own line (possibly indented). The script ignores all of the surrounding code including whether or not the import statement is inside an if block.
    • Then it looks for the desired Python file and repeats the process.

    This usually works in practice, but their are no guarantees.

  • All the modules are run at the beginning of the combined script, not during their import. If the modules run code (and not just define functions and variables), then the behavior of the single combined Python script may be different from the original collection of scripts.

  • The entry point .py file code is put inside a function at the end (with the same name as the entry point file). This is to organize the code and to prevent global variables in the entry point code from being accessible to the mock modules.


sync_combined_py_files.py script

Usage: python sync_combined_py_files.py entry_point output_file

After creating the combined file one can run the sync_combined_py_files.py script to keep the files synced. For example,

$ python sync_combined_py_files.py my_dir/ combined.py
Running...

If one, say, makes and saves changes to foo/bar.py, then one will see the following message.

Syncing combined.py to match foo/bar.py

Conversely, if one makes and saves changes to the foo/bar.py copy in combined.py file, then one will see the following message.

Syncing foo/bar.py to match combined.py

The syncing process can be stopped with a keyboard interrupt (for example, control-C).

^C
GOOD BYE!
$

Important Note: The syncing process is fairly simple. Any changes to the module/import structure of the project (for example, adding/removing a module or changing a dependency) will require running combine_py_files.py again.

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A Python decorator for converting a function into a module. It also includes tools for combining multiple Python files into one.

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