python.AccumulatorCache Namespace Reference

Classes
class	DataHandle
class	NotHashable
class	AccumulatorCachable
class	AccumulatorDecorator

Functions
	make_hashable (obj)
	AccumulatorCache (func=None, maxSize=128, verifyResult=AccumulatorDecorator.VERIFY_NOTHING, deepCopy=True)

Variables
	_msg = logging.getLogger('AccumulatorCache')

Function Documentation

AccumulatorCache()

AccumulatorCache	(		func = None,
			maxSize = 128,
			verifyResult = AccumulatorDecorator.VERIFY_NOTHING,
			deepCopy = True )

Function decorator, implements memoization.

Keyword arguments:
    maxSize: maximum size for the cache associated with the function (default 128)
    verifyResult:   takes two possible values
                    
                    AccumulatorDecorator.VERIFY_NOTHING -   default, the cached function result is returned with no verification
                    AccumulatorDecorator.VERIFY_HASH -      before returning the cached function value, the hash of the
                                                            result is checked to verify if this object was not modified
                                                            between function calls
    deepCopy:   if True (default) a deep copy of the function result will be stored in the cache.

Returns:
    An instance of AccumulatorDecorator.

Definition at line 247 of file AccumulatorCache.py.

                     verifyResult = AccumulatorDecorator.VERIFY_NOTHING, deepCopy = True):
    """Function decorator, implements memoization.
 
    Keyword arguments:
        maxSize: maximum size for the cache associated with the function (default 128)
        verifyResult:   takes two possible values
                        
                        AccumulatorDecorator.VERIFY_NOTHING -   default, the cached function result is returned with no verification
                        AccumulatorDecorator.VERIFY_HASH -      before returning the cached function value, the hash of the
                                                                result is checked to verify if this object was not modified
                                                                between function calls
        deepCopy:   if True (default) a deep copy of the function result will be stored in the cache.
    
    Returns:
        An instance of AccumulatorDecorator.
    """
 
    def wrapper_accumulator(func):
        return AccumulatorDecorator(func, maxSize, verifyResult, deepCopy)
 
    return wrapper_accumulator(func) if func else wrapper_accumulator

make_hashable()

make_hashable

(

obj

)

Make obj hashable by turning mutable lists into non-mutable tuples.
This is e.g. useful when kwargs is passed to a cached Cfg function and
contains non-hashable lists.
This transformation is usually safe because list-valued properties can
be set from a tuple or list.

Example:  myCfg(**make_hashable(kwargs))

Definition at line 22 of file AccumulatorCache.py.

def make_hashable(obj):
    """Make obj hashable by turning mutable lists into non-mutable tuples.
    This is e.g. useful when kwargs is passed to a cached Cfg function and
    contains non-hashable lists.
    This transformation is usually safe because list-valued properties can
    be set from a tuple or list.
 
    Example:  myCfg(**make_hashable(kwargs))
    """
    if isinstance(obj, list):
        return tuple(make_hashable(item) for item in obj)
    elif isinstance(obj, dict):
        return {key: make_hashable(value) for key, value in obj.items()}
    elif isinstance(obj, set):
        return {make_hashable(item) for item in obj}
    return obj
 
 

Variable Documentation

_msg

python.AccumulatorCache._msg = logging.getLogger('AccumulatorCache')

protected

Definition at line 6 of file AccumulatorCache.py.