是否可以使用 pyDatalog 检查是否满足所有数据依赖性？

Question

我正在尝试使用 pyDatalog 来确定是否满足各种功能的依赖性。某些库 (lA,lB,...) 提供功能 (fX,fY,...) 所需的输出 (1,2,...)。

例如：

+has("lA", 1)   #Library A has output 1
+has("lA", 2)   #Library A has output 2
+has("lB", 2)   #Library B has output 2
+needs("fX", 1) #Feature X needs output 1
+needs("fX", 2) #Feature X needs output 2
+needs("fY", 2) #Feature Y needs output 2

使用 pyDatalog 图形教程，我可以找到至少提供功能所需输出之一的库：

lib_supports_feature(X, Z) <= has(X, Y) & needs(Z, Y)
lib_supports_feature(X,"fX")

这个 returns: [('lA',), ('lB',)] 因为它只是在寻找至少有一个特征路径的任何库。

是否有一种好方法 return 仅使用 pyDatalog 满足所有该功能需求的库？

Answer 1

你需要使用双重否定:

missing(X,Y,Z) <= ( # Y is a missing output of X, and is needed by Z
               needs(Z, Y) 
               & has(X, Y1) # needed only if X is not bound
               & ~ has(X, Y))

lib_full_supports_feature(X,Z) <= ( # like supports, but there is no missing output
               has(X,Y) 
               & needs(Z,Y) 
               & ~ missing(X, Y1, Z))

Answer 2

您可以计算 supported_and_needed 个功能的数量，并将它们与所需功能的数量进行比较。如果它们相等，则满足所有功能需求。

(lib_num_supported_and_needed_features[X, Z] == len_(Y)) <= (has(X, Y) & needs(Z, Y))
(num_needed_features[Z] == len_(Y)) <= (needs(Z, Y))
lib_full_supports_features(X, Z) <= (num_needed_features[Z] == lib_num_supported_and_needed_features[X, Z])

是否可以使用 pyDatalog 检查是否满足所有数据依赖性？

Can pyDatalog be used to check if all data dependencies are satisfied?

logic-programming