half object/half dictionary
Fernando Pérez
fperez528 at yahoo.com
Mon Dec 9 19:21:19 EST 2002
Manuel M. Garcia wrote:
> I wrote a metaclass(?) for manipulating a class with __slots__ as a
> dictionary. It is to avoid sections of code like this:
In case you are interested, here's my take on the same problem. Feel free to
use any of the code for your purposes. My Struct class mimics as much as
possible a dict but it allows named attribute access.
Cheers,
f.
#########################################################
# File Struct.py
"""Mimic C structs with lots of extra functionality."""
#*****************************************************************************
# Copyright (C) 2001 Fernando Pérez. <fperez at pizero.colorado.edu>
#
# Distributed under the terms of the GNU Lesser General Public License (LGPL)
#
# This code is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# The full text of the LGPL is available at:
#
# http://www.gnu.org/copyleft/lesser.html
#*****************************************************************************
__author__ = 'Fernando Pérez. <fperez at pizero.colorado.edu>'
__version__ = '0.1.0'
__license__ = 'LGPL'
__date__ = 'Tue Dec 11 00:27:58 MST 2001'
__all__ = ['Struct']
import types
from genutils import list2dict2
class Struct:
"""Class to mimic C structs but also provide convenient dictionary-like
functionality.
Instances can be initialized with a dictionary, a list of key=value pairs
or both. If both are present, the dictionary must come first.
Because Python classes provide direct assignment to their members, it's
easy to overwrite normal methods (S.copy = 1 would destroy access to
S.copy()). For this reason, all builtin method names are protected and
can't be assigned to. An attempt to do s.copy=1 or s['copy']=1 will raise
a KeyError exception. If you really want to, you can bypass this
protection by directly assigning to __dict__: s.__dict__['copy']=1 will
still work. Doing this will break functionality, though. As in most of
Python, namespace protection is weakly enforced, so feel free to shoot
yourself if you really want to.
Note that this class uses more memory and is *much* slower than a regular
dictionary, so be careful in situations where memory or performance are
critical. But for day to day use it should behave fine. It is particularly
convenient for storing configuration data in programs.
+,+=,- and -= are implemented. +/+= do merges (non-destructive updates),
-/-= remove keys from the original. See the method descripitions.
This class allows a quick access syntax: both s.key and s['key'] are
valid. This syntax has a limitation: each 'key' has to be explicitly
accessed by its original name. The normal s.key syntax doesn't provide
access to the keys via variables whose values evaluate to the desired
keys. An example should clarify this:
Define a dictionary and initialize both with dict and k=v pairs:
>>> d={'a':1,'b':2}
>>> s=Struct(d,hi=10,ho=20)
The return of __repr__ can be used to create a new instance:
>>> s
Struct({'ho': 20, 'b': 2, 'hi': 10, 'a': 1})
__str__ (called by print) shows it's not quite a regular dictionary:
>>> print s
Struct {a: 1, b: 2, hi: 10, ho: 20}
Access by explicitly named key with dot notation:
>>> s.a
1
Or like a dictionary:
>>> s['a']
1
If you want a variable to hold the key value, only dictionary access
works:
>>> key='hi'
>>> s.key
Traceback (most recent call last):
File "<stdin>", line 1, in ?
AttributeError: Struct instance has no attribute 'key'
>>> s[key]
10
Another limitation of the s.key syntax (and Struct(key=val)
initialization): keys can't be numbers. But numeric keys can be used and
accessed using the dictionary syntax. Again, an example:
This doesn't work:
>>> s=Struct(4='hi')
SyntaxError: keyword can't be an expression
But this does:
>>> s=Struct()
>>> s[4]='hi'
>>> s
Struct({4: 'hi'})
>>> s[4]
'hi'
"""
# Attributes to which __setitem__ and __setattr__ will block access.
# Note: much of this will be moot in Python 2.2 and will be done in a much
# cleaner way.
__protected = ('copy dict dictcopy get has_attr has_key items keys '
'merge popitem setdefault update values '
'__make_dict __dict_invert ').split()
def __init__(self,dict=None,**kw):
"""Initialize with a dictionary, another Struct, or by giving
explicitly the list of attributes.
Both can be used, but the dictionary must come first:
Struct(dict), Struct(k1=v1,k2=v2) or Struct(dict,k1=v1,k2=v2).
"""
if dict is None:
dict = {}
if isinstance(dict,Struct):
dict = dict.dict()
elif dict and type(dict) is not types.DictType:
raise TypeError,\
'Initialize with a dictionary or key=val pairs.'
dict.update(kw)
# do the updating by hand to guarantee that we go through the
# safety-checked __setitem__
for k,v in dict.items():
self[k] = v
def __setitem__(self,key,value):
"""Used when struct[key] = val calls are made."""
if key in Struct.__protected:
raise KeyError,'Key '+`key`+' is a protected key of class Struct.'
self.__dict__[key] = value
def __setattr__(self, key, value):
"""Used when struct.key = val calls are made."""
self.__setitem__(key,value)
def __str__(self):
"""Gets called by print."""
return 'Struct('+str(self.__dict__)+')'
def __repr__(self):
"""Gets called by repr.
A Struct can be recreated with S_new=eval(repr(S_old))."""
return 'Struct('+str(self.__dict__)+')'
def __getitem__(self,key):
"""Allows struct[key] access."""
return self.__dict__[key]
def __contains__(self,key):
"""Allows use of the 'in' operator."""
return self.__dict__.has_key(key)
def __iadd__(self,other):
"""S += S2 is a shorthand for S.merge(S2)."""
self.merge(other)
return self
def __add__(self,other):
"""S + S2 -> New Struct made form S and S.merge(S2)"""
Sout = self.copy()
Sout.merge(other)
return Sout
def __sub__(self,other):
"""Return S1-S2, where all keys in S2 have been deleted (if present)
from S1."""
Sout = self.copy()
Sout -= other
return Sout
def __isub__(self,other):
"""Do in place S = S - S2, meaning all keys in S2 have been deleted
(if present) from S1."""
for k in other.keys():
if self.has_key(k):
del self.__dict__[k]
def __make_dict(self,__loc_data__,**kw):
"Helper function for update and merge. Return a dict from data."
if __loc_data__ == None:
dict = {}
elif type(__loc_data__) is types.DictType:
dict = __loc_data__
elif isinstance(__loc_data__,Struct):
dict = __loc_data__.__dict__
else:
raise TypeError, 'Update with a dict, a Struct or key=val pairs.'
if kw:
dict.update(kw)
return dict
def __dict_invert(self,dict):
"""Helper function for merge. Takes a dictionary whose values are
lists and returns a dict. with the elements of each list as keys and
the original keys as values."""
outdict = {}
for k,lst in dict.items():
if type(lst) is types.StringType:
lst = lst.split()
for entry in lst:
outdict[entry] = k
return outdict
def clear(self):
"""Clear all attributes."""
self.__dict__.clear()
def copy(self):
"""Return a (shallow) copy of a Struct."""
return Struct(self.__dict__.copy())
def dict(self):
"""Return the Struct's dictionary."""
return self.__dict__
def dictcopy(self):
"""Return a (shallow) copy of the Struct's dictionary."""
return self.__dict__.copy()
def popitem(self):
"""S.popitem() -> (k, v), remove and return some (key, value) pair as
a 2-tuple; but raise KeyError if S is empty."""
return self.__dict__.popitem()
def update(self,__loc_data__=None,**kw):
"""Update (merge) with data from another Struct or from a dictionary.
Optionally, one or more key=value pairs can be given at the end for
direct update."""
# The funny name __loc_data__ is to prevent a common variable name
which
# could be a fieled of a Struct to collide with this parameter. The
problem
# would arise if the function is called with a keyword with this same
name
# that a user means to add as a Struct field.
newdict = Struct.__make_dict(self,__loc_data__,**kw)
for k,v in newdict.items():
self[k] = v
def merge(self,__loc_data__=None,__conflict_solve=None,**kw):
"""S.merge(data,conflict,k=v1,k=v2,...) -> merge data and k=v into S.
This is similar to update(), but much more flexible. First, a dict is
made from data+key=value pairs. When merging this dict with the Struct
S, the optional dictionary 'conflict' is used to decide what to do.
If conflict is not given, the default behavior is to preserve any keys
with their current value (the opposite of the update method's
behavior).
conflict is a dictionary of binary functions which will be used to
solve key conflicts. It must have the following structure:
conflict == { fn1 : [Skey1,Skey2,...], fn2 : [Skey3], etc }
Values must be lists or whitespace separated strings which are
automatically converted to lists of strings by calling string.split().
Each key of conflict is a function which defines a policy for
resolving conflicts when merging with the input data. Each fn must be
a binary function which returns the desired outcome for a key
conflict. These functions will be called as fn(old,new).
An example is probably in order. Suppose you are merging the struct S
with a dict D and the following conflict policy dict:
S.merge(D,{fn1:['a','b',4], fn2:'key_c key_d'})
If the key 'a' is found in both S and D, the merge method will call:
S['a'] = fn1(S['a'],D['a'])
As a convenience, merge() provides five (the most commonly needed)
pre-defined policies: preserve, update, add, add_flip and add_s. The
easiest explanation is their implementation:
preserve = lambda old,new: old
update = lambda old,new: new
add = lambda old,new: old + new
add_flip = lambda old,new: new + old # note change of order!
add_s = lambda old,new: old + ' ' + new # only works for
strings!
You can use those four words (as strings) as keys in conflict instead
of defining them as functions, and the merge method will substitute
the appropriate functions for you. That is, the call
S.merge(D,{'preserve':'a b c','add':[4,5,'d'],my_function:[6]})
will automatically substitute the functions preserve and add for the
names 'preserve' and 'add' before making any function calls.
For more complicated conflict resolution policies, you still need to
construct your own functions. """
data_dict = Struct.__make_dict(self,__loc_data__,**kw)
# policies for conflict resolution: two argument functions which
return
# the value that will go in the new struct
preserve = lambda old,new: old
update = lambda old,new: new
add = lambda old,new: old + new
add_flip = lambda old,new: new + old # note change of order!
add_s = lambda old,new: old + ' ' + new
# default policy is to keep current keys when there's a conflict
conflict_solve = list2dict2(self.keys(),default = preserve)
# the conflict_solve dictionary is given by the user 'inverted': we
# need a name-function mapping, it comes as a function -> names
# dict. Make a local copy (b/c we'll make changes), replace user
# strings for the three builtin policies and invert it.
if __conflict_solve:
inv_conflict_solve_user = __conflict_solve.copy()
for name, func in [('preserve',preserve), ('update',update),
('add',add), ('add_flip',add_flip),
('add_s',add_s)]:
if name in inv_conflict_solve_user.keys():
inv_conflict_solve_user[func] =
inv_conflict_solve_user[name]
del inv_conflict_solve_user[name]
conflict_solve.update(Struct.__dict_invert(self,inv_conflict_solve_user))
#print 'merge. conflict_solve: '; pprint(conflict_solve) # dbg
# after Python 2.2, use iterators: for key in data_dict will then work
#print '*'*50,'in merger. conflict_solver:'; pprint(conflict_solve)
for key in data_dict.keys():
if key not in self:
self[key] = data_dict[key]
else:
self[key] = conflict_solve[key](self[key],data_dict[key])
def has_key(self,key):
"""Like has_key() dictionary method."""
return self.__dict__.has_key(key)
def hasattr(self,key):
"""hasattr function available as a method.
Implemented like has_key, to make sure that all available keys in the
internal dictionary of the Struct appear also as attributes (even
numeric keys)."""
return self.__dict__.has_key(key)
def items(self):
"""Return the items in the Struct's dictionary, in the same format
as a call to {}.items()."""
return self.__dict__.items()
def keys(self):
"""Return the keys in the Struct's dictionary, in the same format
as a call to {}.keys()."""
return self.__dict__.keys()
def values(self,keys=None):
"""Return the values in the Struct's dictionary, in the same format
as a call to {}.values().
Can be called with an optional argument keys, which must be a list or
tuple of keys. In this case it returns only the values corresponding
to those keys (allowing a form of 'slicing' for Structs)."""
if not keys:
return self.__dict__.values()
else:
ret=[]
for k in keys:
ret.append(self[k])
return ret
def get(self,attr,val=None):
"""S.get(k[,d]) -> S[k] if S.has_key(k), else d. d defaults to
None."""
try:
return self[attr]
except KeyError:
return val
def setdefault(self,attr,val=None):
"""S.setdefault(k[,d]) -> S.get(k,d), also set S[k]=d if not
S.has_key(k)"""
if not self.has_key(attr):
self[attr] = val
return self.get(attr,val)
# end class Struct
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