Relational data structure in python

So long as you don't have any duplicates on (a,b,c) you could sub-class dict, enter your objects indexed by the tuple(a,b,c), and define your filter method (probably a generator) to return all entries that match your criteria.

class mydict(dict):
    def filter(self,a=None, b=None, c=None):
        for key,obj in enumerate(self):
            if (a and (key[0] == a)) or not a:
                if (b and (key[1] == b)) or not b:
                    if (c and (key[2] == c)) or not c:
                        yield obj

that is an ugly and very inefficient example, but you get the idea. I'm sure there is a better implementation method in itertools, or something.

edit:

I kept thinking about this. I toyed around with it some last night and came up with storing the objects in a list and storing dictionaries of the indexes by the desired keyfields. Retrieve objects by taking the intersection of the indexes for all specified criteria. Like this:

objs = []
aindex = {}
bindex = {}
cindex = {}

def insertobj(a,b,c,obj):
    idx = len(objs)
    objs.append(obj)
    if a in aindex:
        aindex[a].append(idx)
    else:
        aindex[a] = [idx]

    if b in bindex: 
        bindex[b].append(idx)
    else:
        bindex[b] = [idx]

    if c in cindex:
        cindex[c].append(idx)
    else :
        cindex[c] = [idx]

def filterobjs(a=None,b=None,c=None):
    if a : aset = set(aindex[a])
    if b : bset = set(bindex[b])
    if c : cset = set(cindex[c])
    result = set(range(len(objs)))
    if a and aset : result = result.intersection(aset)
    if b and bset : result = result.intersection(bset)
    if c and cset : result = result.intersection(cset)
    for idx in result:
        yield objs[idx]

class testobj(object):
    def __init__(self,a,b,c):
        self.a = a
        self.b = b
        self.c = c

    def show(self):
        print ('a=%i\tb=%i\tc=%s'%(self.a,self.b,self.c))

if __name__ == '__main__':
    for a in range(20):
        for b in range(5):
            for c in ['one','two','three','four']:
                insertobj(a,b,c,testobj(a,b,c))

    for obj in filterobjs(a=5):
        obj.show()
    print()
    for obj in filterobjs(b=3):
        obj.show()
    print()
    for obj in filterobjs(a=8,c='one'):
        obj.show()

it should be reasonably quick, although the objects are in a list, they are accessed directly by index. The "searching" is done on a hashed dict.