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توضیحات

Memoization utilities with fading memory.

ویژگی	مقدار
سیستم عامل	-
نام فایل	Elephants-1.0.0
نام	Elephants
نسخه کتابخانه	1.0.0
نگهدارنده	[]
ایمیل نگهدارنده	[]
نویسنده	Marc Schwarzschild
ایمیل نویسنده	ms@TheBrookhavenGroup.com
آدرس صفحه اصلی	http://github.com/Schwarzschild/Elephants
آدرس اینترنتی	https://pypi.org/project/Elephants/
مجوز	MIT

========= Elephants ========= This is a memoize package using StrongDict a class introduced in this package. StrongDict described in detail in the following section uses a linked list of strong references in combination with a weak reference dictionary to enable fading memory storage by either restricting the number of items in the store or imposing a time limit on items stored. About the name -------------- This package is named Elephants because they are the symbol of remembering, or in a modern Python world, memoizing. Examples -------- Simple memoize ^^^^^^^^^^^^^^ :: from elephants import memo @memo def fib(n): if n<2: return 1 return fib(n-1) + fib(n-2) Memoize with time limit ^^^^^^^^^^^^^^^^^^^^^^^ The following pattern demonstrates the @memo_until decorator to cache data object instances for a given length of time. :: from elephants import memo_until class MyDataObject(object): def __init__(self, x): self.x = x def __str__(self): return str(self.x) @memo_until(tlimit=3600) # seconds def get_my_data_obj_instance(x): print 'Getting a new instance for x =', x return MyDataObject(x) y = get_my_data_obj_instance(1) y = get_my_data_obj_instance(2) y = get_my_data_obj_instance(1) y = get_my_data_obj_instance(3) y = get_my_data_obj_instance(1) print 'The final value of y should be 1. It is', y Memoize with length limit ^^^^^^^^^^^^^^^^^^^^^^^^^ The following pattern demonstrates the @memo_until decorator to cache data object instances for a given length of time. :: from elephants import nmemo class MyDataObject(object): def __init__(self, x): self.x = x def __str__(self): return str(self.x) @nmemo(limit=2) # Limit the cache to only two items. def get_my_data_obj_instance(x): print 'Getting a new instance for x =', x return MyDataObject(x) y = get_my_data_obj_instance(1) y = get_my_data_obj_instance(2) y = get_my_data_obj_instance(3) y = get_my_data_obj_instance(1) print 'At this point the cache should only have 1 and 3.' StrongDict ^^^^^^^^^^ A dictionary using strong and weak references. Items are stored in a WeakValueDictionary. They are also stored in a the linked list, the strong cache, holding strong references. Retreival is a fast WeakValueDictionary lookup. Items most recently used are moved to the top of the strong cache list. Options are provided to fade from the strong linked list defined by either a time limit or a list quantity limit. The default is to keep everything in strong linked list forever. If an item is removed from the strong cache and later queried and found in the WeakValuedictionary it will be added back to the strong cache. This can only happen if an reference to the removed item exists outside the cache. As long as items have a strong reference they will stay in the WeakValueDictionary. However, if an item no longer has a strong reference it is not guaranteed to be in the WeakValueDictionary. The WeakValueDictionary will "forget" about objects not also referenced elsewhere, in this case the StrongDict() strong reference linked list. The weakref.WeakValueDictionary() cannot hold native types like int or str. But it can hold a python object that has native types. This StrongDict class uses a Link object defined above to hold all values stored in the cache. Therefore the user of StrongDict() does not need to be concerned with this limitation of the weakref package. CAVEAT EMPTOR: If a class instance is used as key in the dictionary then the __hash__() method may need to be implmented. StrongDict Example ^^^^^^^^^^^^^^^^^^ :: from elephants import StrongDict w = StrongDict(limit=3) # populate with test cases for i in range(10): w[i] = i * i # demonstrate limit is imposed and len() works for StrongDict assert(len(w) == 3) assert(6 not in w) # demonstrate that del works on StrongDict instances del w[8] assert(len(w) == 2) # demonstrate that KeyError is thrown when item is not in the dictionary. try: del w[6] assert(False) except KeyError: 'It cannot delete w[7] since it is not there.' assert(True) # demonstrate for negation on inclusion test. del w[9] assert(9 not in w) # demonstrate equals operator x = {} for i in range(4): w[i] = x[i]= i * i del x[0] assert(w == x) # demonstrate conversion to dict x = dict(w) print x print type(x) Special Note ^^^^^^^^^^^^ @memo, @nmemo, and @memo_until have two special arguments. If a decorated method is called with 'size_elephant_cache' as the argument it will return the number of items in the cache. If it is called with 'clear_elephant_cache' as the argument it will clear the cache as shown in the following example. Example ^^^^^^^ :: from elephants import memo @memo def f(x): return x * x for i in range(10): f(i) print 'There are', f('size_elephant_cache'), 'items in the cache.' f('clear_elephant_cache') print 'There are', f('size_elephant_cache'), 'items in the cache.' Thank you ========= A special thank you to Jonathan Arrender Smith for his guidance and education.

نحوه نصب

نصب پکیج whl Elephants-1.0.0:

pip install Elephants-1.0.0.whl

نصب پکیج tar.gz Elephants-1.0.0:

pip install Elephants-1.0.0.tar.gz