Using __*attr__ with __*item__

me at home.com me at home.com
Fri Aug 9 03:28:18 CEST 2002


Bengt,

     Thanks for the information.  What I am doing is accessing data
that is packed into a raw data buffer (i.e., packed below the word
level as in MIL-STD-1553 or ARINC-429 avionics busses).  I was able to
successfully get the arrays to work by using some of your ideas.

     I am passing the buffer from the top-level class into the array
class.  This is one instance where the fact that python assigns
references to lists, rather than duplicating them, actually worked in
my favor.  The rop-level class is also instantiating the array
instances with enough additional information to do their jobs (i.e., in
addition to the buffer I am also passing the (un)packing information
for each element in the list.

     I was able to successfully insert booleans, enumerations, and
scaled integers into the raw data block and send it to the proper
destination (even things like Foo.my_list = [1,2,3,4]).  What I wound
up with is considerably more clean that I was expecting.

Thanks again!

Jonathan polley

In article <aisv0p$5br$0 at 216.39.172.122>, Bengt Richter <bokr at oz.net>
wrote:

> On Thu, 08 Aug 2002 02:45:13 GMT, <me at home.com> wrote:
> 
> >     I will be providing a data structure-like interface to some raw
> >data, so using __getattr__ and __setattr__ are just what I need to use. 
> >The problem comes when I need to operate as if I have an array of
> >elements in this data.
> >
> >     Each class that is instantiated has an instance of a data block
> >that is operates on via __getattr__ and __setattr__.  This works well
> >because the attribute name helps to determine where the data is
> >located, and how it is to be accessed.  When I have an array of related
> >data in the block, I would like to use __getitem__ and __setitem__. 
> 
> (Warning. I haven't tested any of this ;-)
> 
> Do you want to write source like this ?
> 
>    item_value = raw_data_container.data_block_name[index_within_data_block]
> 
> I am assuming you want to operate on your raw data in place. But you should be
> able to update the buffer reference in an instance and still proceed. Just
> don't
> keep a stale instance of IndexableClass around (which you normally wouldn't).
> 
> If so, have __getattr__ return an instance of a class for datablocks that has
> the required references to the appropriate raw data inside, and __getitem__
> defined to do the indexed selection from that. __getattr__ could also return
> named unindexed values like
> 
>    item_value = raw_data_container.item_name
> 
> You'd just get an error if you tried to index it (unless it was a string or
> something
> that supports indexing).
> 
> >The problem is that __*item__ does not get the attribute name passed to
> >it, just the index range and potential values.  Because of this, I have
> >no way to know how to access the buffer.  The class is defined
> >something like:
> >
> >
> >class foo:
>  class Foo:
> >    def __init__ ():
>      def __init__(self, datasource=None_or_some_default):
> >        self.data = get the data buffer
> Normally you don't want to initialize from a global source, and you have to
> put self
> in the arg list before you can use it. If this data buffer is to be accessed
> first by
> an element name, and then optionally by index within the element, you can
> start with
>          self._data = datasource # just a reference to the raw stuff
> then
>     foo_instance = Foo(my_raw_data)
> will make it so
>     foo_instance._data
> is the raw data. You may want to hide it a little as self._data so you can
> avoid it
> easily when you process __getattr__
> >
> >    def __setattr__ (self, attr, value):
>          if attr == '_data': raise AttributeError, 'Raw data may not be
> accessed directly'
> >        load 'value' into self.data per 'attr'
>          # maybe something like
> 
>          where_att, kind_of_att =
> find_att_in_raw_data(self.__dict__['_data'], attr)
>          if kind_of_att == SCALAR_KIND:
>              # pretend global raw data access routines exist ;-) (You could
> put them in the class).
>              set_scalar_from_raw(self.__dict__['_data'], where_att)
>          else:
>              raise AttributeError, '%s must be accessed item-wise by index'%
> attr
> 
>          # i.e., but note that this should be considered to operate on a
> single named item,
>          # and you probably need to look in the raw data to see that it's not
> indexable,
>          # since indexable stuff gets set by first __getattr__ to find the
> indexable thing
>          # and then __setitem__ on what's found.
>              
> >
> >    def __getattr__ (self, attr):
>          if attr == '_data': raise AttributeError, 'Raw data may not be
> accessed directly'
> >        read value from sefl.data per 'attr' and return it
>          here you want to look at the raw data per attr and decide if what
> you find
>          is indexable. If it is, then you don't return an item, you make a
> class instance
>          initialized with a reference to the part of the raw data you found
> with attr,
>   and you return that. So when you write
>      foo_instance.attr
>          you well get that IndexableClass instance. Its class will have
> __[gs]etitem__ defined, so when
>          you write
>      foo_instance.attr[an_index]
>          It's __getitem__ will be called, and when you write
>      foo_instance.attr[an_index] = new_value
>          its __setitem__ will be called. Note that here .attr still caused
> __getattr__ so be called,
>          not __setattr__, because we're not targeting the attribute itself,
> but something indexed within.
> 
>          So, you need something like
>      def __getattr__ (self, attr):
>          where_att, kind_of_att =
> find_att_in_raw_data(self.__dict__['_data'], attr)
>          if kind_of_att == SCALAR_KIND:
>              return get_scalar_from_raw(self.__dict__['_data'], where_att)
>          else:
>              return IndexingClass(self.__dict__['_data'], where_att)
> 
>          # ( the .__dict__['_data'] is to avoid a recursive __getattr__ call )
> ># end class foo
> 
> And then don't put the following in class Foo. Make it the separate
> IndexingClass, e.g.,
> 
>  class IndexingClass:
>      def __init__(self, raw_data_ref, where_att):
>          self.raw_data_ref = raw_data_ref
>          self.where_att = where_att    # place where data was located for
> particular attr
> >
> >    def __setitem__ (self, item, values):
> >        ### Can't determine which of the possible arrays are being
> >        ### referenced
>          # now you can
>          set_indexed_item_in_raw_data( self.raw_data_ref, self.where_att,
> values)
> 
> >
> >    def __getitem__ (self, item):
> >        ### Can't determine which of the possible arrays are being
> >        ### referenced
>          # now you can
>          return get_indexed_item_in_raw_data(self.raw_data_ref,
> self.where_att)
> 
>      # if you implement this, you should be able to write
>      # for item in foo_instance.attr: do_something(item)
>      # it will also be needed if you want __getitem__ to support slices like
>      # foo_instance.attr[3:-4]
>      def __len__(self):
>          return get_max_valid_index_plus_one(self.raw_data_ref,
> self.where_att)
> >
> ># end class IndexingClass
> >
> >
> >     If I move the __*item__ routines into their own package, then all
> >visibility to self.data is lost.
>       Not if you do it as above.
> >
> >     I have a work around, but it bothers me because it looks too much
> >like a bad hack.  The solution I will be trying is to move the
> >__*item__ routines into their own class.  Then define EACH element of
> >the array as a unique attribute.  Once this is done, instantiate the
> Sorry, I don't want to dig through it ;-) No more time.
> 
> >array class with these elements and pass them BACK INTO the structure
> >class.  Something like this:
> >
> >class foo:
> >    def __init__ (self, other_params):
> >        self.data = get the data buffer
> >
> >    def __setattr__ (self, attr, value):
> >        load 'value' into self.data per 'attr'
> >
> >    def __getattr__ (self, attr):
> >        read value from sefl.data per 'attr' and return it
> >
> >    def set_array (self, array_attribute, the_array):
> >        self.__dict__[array_attribute] = the_array
> >
> ># end class foo
> >
> >
> >class bar:
> >    def __init__ (self, array_element_list):
> >        self.the_array = array_element_list
> >
> >    def __setitem__ (self, item, values):
> >        for index in range (item.start, item.stop):
> >            # this should trap to the proper __setattr__ in class foo
> >            self.the_array [index] = values [index - item.start]
> >
> >    def __getitem__ (self, item):
> >        the_answer = []
> >        for index in range (item.start, item.stop):
> >            # this should trap to the proper __getattr__ in class foo
> >            the_answer.append (self.the_array [index])
> >
> ># end class bar
> >
> >FOO = foo()
> >the_array = bar([FOO.array_element_1, FOO.array_element_2, ...])
> >FOO.set_array ("array_name", the_array)
> >
> >     Because of how I am creating FOO, I can hide the instantiation of
> >bar, but it still bothers me.
> >
> >     Any thoughts as to a better way to do this?
> >
> First, use capitals on class names and lower case for instances, or you'll
> confuse a lot of people ;-)
> 
> Regards,
> Bengt Richter



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