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We need maybe more hardcoded floats. I mean a "cache" of current 
float. Example of pseudocode:
def cache_float(value):
 return abs(value) in (0.0, 1.0, 2.0)
def create_float(value):
 try:
 return cache[value]
 except KeyError:
 obj = float(value)
 if cache_value(value):
 cache[value] = obj
 return obj
Since some (most?) programs don't use float, the cache is created on 
demand and not at startup.
Since the goal is speed, only a benchmark can answer to my question 
(is Python faster using such cache) ;-) Instead of cache_float(), an 
RCU cache might me used.