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ORPA-pyOpenRPA/Resources/WPy64-3720/python-3.7.2.amd64/Lib/site-packages/jedi/evaluate/cache.py

78 lines
2.4 KiB

"""
- the popular ``_memoize_default`` works like a typical memoize and returns the
default otherwise.
- ``CachedMetaClass`` uses ``_memoize_default`` to do the same with classes.
"""
_NO_DEFAULT = object()
def _memoize_default(default=_NO_DEFAULT, evaluator_is_first_arg=False, second_arg_is_evaluator=False):
""" This is a typical memoization decorator, BUT there is one difference:
To prevent recursion it sets defaults.
Preventing recursion is in this case the much bigger use than speed. I
don't think, that there is a big speed difference, but there are many cases
where recursion could happen (think about a = b; b = a).
"""
def func(function):
def wrapper(obj, *args, **kwargs):
# TODO These checks are kind of ugly and slow.
if evaluator_is_first_arg:
cache = obj.memoize_cache
elif second_arg_is_evaluator:
cache = args[0].memoize_cache # needed for meta classes
else:
cache = obj.evaluator.memoize_cache
try:
memo = cache[function]
except KeyError:
memo = {}
cache[function] = memo
key = (obj, args, frozenset(kwargs.items()))
if key in memo:
return memo[key]
else:
if default is not _NO_DEFAULT:
memo[key] = default
rv = function(obj, *args, **kwargs)
memo[key] = rv
return rv
return wrapper
return func
def evaluator_function_cache(default=_NO_DEFAULT):
def decorator(func):
return _memoize_default(default=default, evaluator_is_first_arg=True)(func)
return decorator
def evaluator_method_cache(default=_NO_DEFAULT):
def decorator(func):
return _memoize_default(default=default)(func)
return decorator
def evaluator_as_method_param_cache():
def decorator(call):
return _memoize_default(second_arg_is_evaluator=True)(call)
return decorator
class CachedMetaClass(type):
"""
This is basically almost the same than the decorator above, it just caches
class initializations. Either you do it this way or with decorators, but
with decorators you lose class access (isinstance, etc).
"""
@evaluator_as_method_param_cache()
def __call__(self, *args, **kwargs):
return super(CachedMetaClass, self).__call__(*args, **kwargs)