Venusian
========

Venusian is a library which allows you to defer the action of
decorators.  Instead of taking actions when a function, method, or
class decorator is executed at import time, you can defer the action
until a separate "scan" phase.

This library is most useful for framework authors.  It is compatible with
CPython versions 2.4, 2.5, 2.6, 2.7, and 3.2.  It also is known to work on
PyPy 1.5 and Jython 2.5.2.

.. note::

   The name "Venusian" is a riff on a library named :term:`Martian`
   (which had its genesis in the :term:`Grok` web framework), from
   which the idea for Venusian was stolen.  Venusian is similar to
   Martian, but it offers less functionality, making it slightly
   simpler to use.

Overview
--------

Offering a decorator that wraps a function, method, or class can be a
convenience to your framework's users.  But the very purpose of a
decorator makes it likely to impede testability of the function or
class it decorates: use of a decorator often prevents the function it
decorates from being called with the originally passed arguments, or a
decorator may modify the return value of the decorated function.  Such
modifications to behavior are "hidden" in the decorator code itself.

For example, let's suppose your framework defines a decorator function
named ``jsonify`` which can wrap a function that returns an arbitrary
Python data structure and renders it to a JSON serialization:

.. code-block:: python
   :linenos:

    import json

    def jsonify(wrapped):
        def json_wrapper(request):
            result = wrapped(request)
            dumped = json.dumps(result)
            return dumped
        return json_wrapper

Let's also suppose a user has written an application using your
framework, and he has imported your jsonify decorator function, and
uses it to decorate an application function:

.. code-block:: python
   :linenos:

    from theframework import jsonify

    @jsonify
    def logged_in(request):
       return {'result':'Logged in'}

As a result of an import of the module containing the ``logged_in``
function, a few things happen:

- The user's ``logged_in`` function is replaced by the
  ``json_wrapper`` function.

- The only reference left to the original ``logged_in`` function is
  inside the frame stack of the call to the ``jsonify`` decorator.

This means, from the perspective of the application developer that the
original ``logged_in`` function has effectively "disappeared" when it
is decorated with your ``jsonify`` decorator.  Without bothersome
hackery, it can no longer be imported or retrieved by its original
author.

More importantly, it also means that if the developer wants to unit
test the ``logged_in`` function, he'll need to do so only indirectly:
he'll need to call the ``json_wrapper`` wrapper decorator function and
test that the json returned by the function contains the expected
values.  This will often imply using the ``json.loads`` function to
turn the result of the function *back* into a Python dictionary from
the JSON representation serialized by the decorator.

If the developer is a stickler for unit testing, however, he'll want
to test *only* the function he has actually defined, not the wrapper
code implied by the decorator your framework has provided.  This is
the very definition of unit testing (testing a "unit" without any
other integration with other code).  In this case, it is also more
convenient for him to be able to test the function without the
decorator: he won't need to use the ``json.loads`` function to turn
the result back into a dictionary to make test assertions against.
It's likely such a developer will try to find ways to get at the
original function for testing purposes.

To do so, he might refactor his code to look like this:

.. code-block:: python
   :linenos:

    from theframework import jsonify

    @jsonify
    def logged_in(request):
       return _logged_in(request)

    def _logged_in(request):
       return {'result':'Logged in'}

Then in test code he might import only the ``_logged_in`` function
instead of the decorated ``logged_in`` function for purposes of unit
testing.  In such a scenario, the concentious unit testing app
developer has to define two functions for each decorated function.  If
you're thinking "that looks pretty tedious", you're right.

To give the intrepid tester an "out", you might be tempted as a
framework author to leave a reference to the original function around
somewhere that the unit tester can import and use only for testing
purposes.  You might modify the ``jsonify`` decorator like so in order
to do that:

.. code-block:: python
   :linenos:

    import json
    def jsonify(wrapped):
        def json_wrapper(request):
            result = wrapped(request)
            dumped = json.dumps(result)
            return dumped
        json_wrapper.original_function = wrapped
        return json_wrapper

The line ``json_wrapper.original_function = wrapped`` is the
interesting one above.  It means that the application developer has a
chance to grab a reference to his original function:

.. code-block:: python
   :linenos:

    from myapp import logged_in
    result = logged_in.original_func(None)
    self.assertEqual(result['result'], 'Logged in')

That works.  But it's just a little weird.  Since the ``jsonify``
decorator function has been imported by the developer from a module in
your framework, the developer probably shouldn't really need to know
how it works.  If he needs to read its code, or understand
documentation about how the decorator functions for testing purposes,
your framework *might* be less valuable to him on some level.  This is
arguable, really.  If you use some consistent pattern like this for
all your decorators, it might be a perfectly reasonable solution.

However, what if the decorators offered by your framework were passive
until activated explicitly?  This is the promise of using Venusian
within your decorator implementations.  You may use Venusian within
your decorators to associate a wrapped function, class, or method with
a callback.  Then you can return the originally wrapped function.
Instead of your decorators being "active", the callback associated
with the decorator is passive until a "scan" is initiated.

Using Venusian
--------------

The most basic use of Venusian within a decorator implementation is
demonstrated below.

.. code-block:: python
   :linenos:

   import venusian

   def jsonify(wrapped):
       def callback(scanner, name, ob):
           print 'jsonified'
       venusian.attach(wrapped, callback)
       return wrapped

As you can see, this decorator actually calls into venusian, but then
simply returns the wrapped object.  Effectively this means that this
decorator is "passive" when the module is imported.

Usage of the decorator:

.. code-block:: python
   :linenos:

   from theframework import jsonify

   @jsonify
   def logged_in(request):
       return {'result':'Logged in'}

Note that when we import and use the function, the fact that it is
decorated with the ``jsonify`` decorator is immaterial.  Our decorator
doesn't actually change its behavior.

.. code-block:: python
   :linenos:

   >>> from theapp import logged_in
   >>> logged_in()
   {'result':'Logged in'}
   >>>

This is the intended result.  During unit testing, the original
function can be imported and tested despite the fact that it has been
wrapped with a decorator.

However, we can cause something to happen when we invoke a :term:`scan`.

.. code-block:: python
   :linenos:

   import venusian
   import theapp

   scanner = venusian.Scanner()
   scanner.scan(theapp)

Above we've imported a module named ``theapp``. The ``logged_in``
function which we decorated with our ``jsonify`` decorator lives in
this module.  We've also imported the :mod:`venusian` module, and
we've created an instance of the :class:`venusian.Scanner` class.
Once we've created the instance of :class:`venusian.Scanner`, we
invoke its :meth:`venusian.Scanner.scan` method, passing the
``theapp`` module as an argument to the method.

Here's what happens as a result of invoking the
:meth:`venusian.Scanner.scan` method:

#. Every object defined at module scope within the ``theapp`` Python
   module will be inspected to see if it has had a Venusian callback
   attached to it.

#. For every object that *does* have an Venusian callback attached to
   it, the callback is called.

We could have also passed the ``scan`` method a Python *package*
instead of a module.  This would recursively import each module in the
package (as well as any modules in subpackages), looking for
callbacks.

.. note:: During scan, the only Python files that are processed are
   Python *source* (``.py``) files.  Compiled Python files (``.pyc``,
   ``.pyo`` files) without a corresponding source file are ignored.

In our case, because the callback we defined within the ``jsonify``
decorator function prints ``jsonified`` when it is invoked, which
means that the word ``jsonified`` will be printed to the console when
we cause :meth:`venusian.Scanner.scan` to be invoked.  How is this
useful?  It's not!  At least not yet.  Let's create a more realistic
example.

Let's change our ``jsonify`` decorator to perform a more useful action
when a scan is invoked by changing the body of its callback.

.. code-block:: python
   :linenos:

   import venusian

   def jsonify(wrapped):
       def callback(scanner, name, ob):
           def jsonified(request):
               result = wrapped(request)
               return json.dumps(result)
           scanner.registry.add(name, jsonified)
       venusian.attach(wrapped, callback)
       return wrapped

Now if we invoke a scan, we'll get an error:

.. code-block:: python
   :linenos:

   import venusian
   import theapp

   scanner = venusian.Scanner()
   scanner.scan(theapp)

   AttributeError: Scanner has no attribute 'registry'.

The :class:`venusian.Scanner` class constructor accepts any key-value
pairs; for each key/value pair passed to the scanner's constructor, an
attribute named after the key which points at the value is added to
the scanner instance.  So when you do:

.. code-block:: python
   :linenos:

   import venusian
   scanner = venusian.Scanner(a=1)

Thereafter, ``scanner.a`` will equal the integer 1.

Any number of key-value pairs can be passed to a scanner.  The purpose
of being able to pass arbitrary key/value pairs to a scanner is to
allow cooperating decorator callbacks to access these values: each
callback is passed the ``scanner`` constructed when a scan is invoked.

Let's fix our example by creating an object named ``registry`` that
we'll pass to our scanner's constructor:

.. code-block:: python
   :linenos:

   import venusian
   import theapp

   class Registry(object):
       def __init__(self):
          self.registered = []

       def add(self, name, ob):
          self.registered.append((name, ob))

   register = Register()
   scanner = venusian.Scanner(registry=registry)
   scanner.scan(theapp)

At this point, we have a system which, during a scan, for each object
that is wrapped with a Venusian-aware decorator, a tuple will be
appended to the ``registered`` attribute of a ``Registry`` object.
The first element of the tuple will be the decorated object's name,
the second element of the tuple will be a "truly" decorated object.
In our case, this will be a jsonify-decorated callable.

Our framework can then use the information in the registry to decide
which view function to call when a request comes in.

Venusian callbacks must accept three arguments:

``scanner``

  This will be the instance of the scanner that has had its ``scan``
  method invoked.

``name``

  This is the module-level name of the object being decorated.

``ob``

  This is the object being decorated if it's a function or an
  instance; if the object being decorated is a *method*, however, this
  value will be the *class*.

If you consider that the decorator and the scanner can cooperate, and
can perform arbitrary actions together, you can probably imagine a
system where a registry will be populated that informs some
higher-level system (such as a web framework) about the available
decorated functions.

Scan Categories
---------------

Because an application may use two separate Venusian-using frameworks,
Venusian allows for the concept of "scan categories".

The :func:`venusian.attach` function accepts an additional argument
named ``category``.

For example:

.. code-block:: python
   :linenos:

   import venusian

   def jsonify(wrapped):
       def callback(scanner, name, ob):
           def jsonified(request):
               result = wrapped(request)
               return json.dumps(result)
           scanner.registry.add(name, jsonified)
       venusian.attach(wrapped, callback, category='myframework')
       return wrapped

Note the ``category='myframework'`` argument in the call to
:func:`venusian.attach`.  This tells Venusian to attach the callback
to the wrapped object under the specific scan category
``myframework``.  The default scan category is ``None``.

Later, during :meth:`venusian.Scanner.scan`, a user can choose to
activate all the decorators associated only with a particular set of
scan categories by passing a ``categories`` argument.  For example:

.. code-block:: python
   :linenos:

   import venusian
   scanner = venusian.Scanner(a=1)
   scanner.scan(theapp, categories=('myframework',))

The default ``categories`` argument is ``None``, which means activate
all Venusian callbacks during a scan regardless of their category.

``onerror`` Scan Callback
-------------------------

By default, when Venusian scans a package, it will propagate all exceptions
raised while attempting to import code.  You can use an ``onerror`` callback
argument to :meth:`venusian.Scanner.scan` to change this behavior.

The ``onerror`` argument should either be ``None`` or a callback function
which behaves the same way as the ``onerror`` callback function described in
http://docs.python.org/library/pkgutil.html#pkgutil.walk_packages .

Here's an example ``onerror`` callback that ignores all :exc:`ImportError`
exceptions:

.. code-block:: python
   :linenos:

     import sys
     def onerror(name):
         if not issubclass(sys.exc_info()[0], ImportError):
             raise # reraise the last exception

Here's how we'd use this callback:

.. code-block:: python
   :linenos:

   import venusian
   scanner = venusian.Scanner()
   scanner.scan(theapp, onerror=onerror)

The ``onerror`` callback should execute ``raise`` at some point if any
exception is to be propagated, otherwise it can simply return.  The ``name``
passed to ``onerror`` is the module or package dotted name that could not be
imported due to an exception.

.. note:: the ``onerror`` callback is new as of Venusian 1.0.

``ignore`` Scan Argument
------------------------

The ``ignore`` to ``scan`` allows you to ignore certain modules, packages, or
global objects during a scan.  It should be a sequence containing strings
and/or callables that will be used to match against the full dotted name of
each object encountered during the scanning process.  If the ignore value you
provide matches a package name, global objects contained by that package as
well any submodules and subpackages of the package (and any global objects
contained by them) will be ignored.  If the ignore value you provide matches
a module name, any global objects in that module will be ignored.  If the
ignore value you provide matches a global object that lives in a package or
module, only that particular global object will be ignored.

The sequence can contain any of these three types of objects:

- A string representing a full dotted name.  To name an object by dotted
  name, use a string representing the full dotted name.  For example, if you
  want to ignore the ``my.package`` package and any of its subobjects during
  the scan, pass ``ignore=['my.package']``.  If the string matches a global
  object (e.g. ``ignore=['my.package.MyClass']``), only that object will be
  ignored and the rest of the objects in the module or package that contains
  the object will be processed.

- A string representing a relative dotted name.  To name an object relative
  to the ``package`` passed to this method, use a string beginning with a
  dot.  For example, if the ``package`` you've passed is imported as
  ``my.package``, and you pass ``ignore=['.mymodule']``, the
  ``my.package.mymodule`` module and any of its subobjects will be omitted
  during scan processing.  If the string matches a global object
  (e.g. ``ignore=['my.package.MyClass']``), only that object will be ignored
  and the rest of the objects in the module or package that contains the
  object will be processed.

- A callable that accepts a full dotted name string of an object as its
  single positional argument and returns ``True`` or ``False``.  If the
  callable returns ``True`` or anything else truthy, the module, package, or
  global object is ignored, if it returns ``False`` or anything else falsy,
  it is not ignored.  If the callable matches a package name, the package as
  well as any of that package's submodules and subpackages (recursively) will
  be ignored.  If the callable matches a module name, that module and any of
  its contained global objects will be ignored.  If the callable mactches a
  global object name, only that object name will be ignored.  For example, if
  you want to skip all packages, modules, and global objects that have a full
  dotted name that ends with the word "tests", you can use
  ``ignore=[re.compile('tests$').search]``.

Here's an example of how we might use the ``ignore`` argument to ``scan`` to
ignore an entire package (and any of its submodules and subpackages) by
absolute dotted name:

.. code-block:: python
   :linenos:

   import venusian
   scanner = venusian.Scanner()
   scanner.scan(theapp, ignore=['theapp.package'])

Here's an example of how we might use the ``ignore`` argument to ``scan`` to
ignore an entire package (and any of its submodules and subpackages) by
relative dotted name (``theapp.package``):

.. code-block:: python
   :linenos:

   import venusian
   scanner = venusian.Scanner()
   scanner.scan(theapp, ignore=['.package'])

Here's an example of how we might use the ``ignore`` argument to ``scan`` to
ignore a particular class object:

.. code-block:: python
   :linenos:

   import venusian
   scanner = venusian.Scanner()
   scanner.scan(theapp, ignore=['theapp.package.MyClass'])

Here's an example of how we might use the ``ignore`` argument to ``scan`` to
ignore any module, package, or global object that has a name which ends
with the string ``tests``:

.. code-block:: python
   :linenos:

   import re
   import venusian
   scanner = venusian.Scanner()
   scanner.scan(theapp, ignore=[re.compile('tests$').search])

You can mix and match the three types in the list.  For example,
``scanner.scan(my, ignore=['my.package', '.someothermodule',
re.compile('tests$').search])`` would cause ``my.package`` (and all its
submodules and subobjects) to be ignored, ``my.someothermodule`` to be
ignored, and any modules, packages, or global objects found during the scan
that have a full dotted path that ends with the word ``tests`` to be ignored
beneath the ``my`` package.

Packages and modules matched by any ignore in the list will not be imported,
and their top-level code will not be run as a result.

.. note:: the ``ignore`` argument is new as of Venusian 1.0a3.


Limitations and Audience
------------------------

Venusian is not really a tool that is maximally useful to an
application developer.  It would be a little silly to use it every
time you needed a decorator.  Instead, it's most useful for framework
authors, in order to be able to say to their users "the frobozz
decorator doesn't change the output of your function at all" in
documentation.  This is a lot easier than telling them how to test
methods/functions/classes decorated by each individual decorator
offered by your frameworks.

API Documentation / Glossary
----------------------------

.. toctree::
   :maxdepth: 2

   api.rst
   glossary.rst

Indices and tables
------------------

* :ref:`glossary`
* :ref:`modindex`
* :ref:`search`