E.g., I have:
def readDb():
    # Fetch a lot of data from db, spends a lot time
    ...
    return aList
def calculation():
    x = readdb()
    # Process          
        Write a simple decorator:
class memo(object):
    def __init__(self, fun):
        self.fun = fun
        self.res = None
    def __call__(self):
        if self.res is None:
            self.res = self.fun()
        return self.res
@memo
def readDb():
    # ... etc
    return aList
For more general solutions, look here: http://code.activestate.com/recipes/498245-lru-and-lfu-cache-decorators/.
def readDb():
    ... #Fetch a lot of data from db, spends a lot time
    return aList
def calculation(data):
    x=data
    ...process x...
    return y
data = readDb()
calculation(data)
calculation(data)
calculation(data)
This will only hit the database once.
Basically, you want to save the results of readDb() to a seperate variable which you can then pass to calculation().
Updated answer for modern Python
For anyone still searching for how to do this, the standard library functools includes a decorator function @functools.lru_cache to do this. 
For example (from the docs):
@lru_cache(maxsize=32)
def get_pep(num):
    'Retrieve text of a Python Enhancement Proposal'
    resource = 'http://www.python.org/dev/peps/pep-%04d/' % num
    try:
        with urllib.request.urlopen(resource) as s:
            return s.read()
    except urllib.error.HTTPError:
        return 'Not Found'
This would store the last 32 calls to get_pep and when it is called with the same argument, the cached value will be returned.