CODEWITHSUNDEEP
logic-programming
kerblogglobel
kerblogglobel

Reputation: 148

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

I am trying to use pyDatalog to determine if the dependencies for various features are satisfied. Some library (lA,lB,...) provides outputs (1,2,...) which are needed by features (fX,fY,...).

For example:

+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

Using the pyDatalog graph tutorials I can find libraries that provide at least one of the outputs required for a feature:

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

This returns: [('lA',), ('lB',)] because it is merely finding any library with at least one path to the feature.

Is there a good way to return only the libraries that meet all the needs of that feature using pyDatalog?

Upvotes: 0

Views: 138

Answers (2)

chris elgoog
chris elgoog

Reputation: 145

You can count the number of supported_and_needed features and compare them with the number of needed features. If they are equal all feature needs are meet.

(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])

Upvotes: 1

Pierre Carbonnelle
Pierre Carbonnelle

Reputation: 2625

You need to use a double negation :

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))

Upvotes: 1

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