def parse_query(string):
pattern = re.compile("\[[A-Za-z_,0-9]*\]:[A-Za-z_,\(\)\[\]\*0-9]*$")
if pattern.match(string):
try:
free_var_body, query_body = string.split(":")
free_var_body = free_var_body[1:-1]
free_vars = parse_atoms_values(free_var_body)
q = ConjunctiveQuery()
for atom, fd_set, is_key, is_consistent in parse_atoms(query_body):
q = q.add_atom(atom, fd_set, is_key, is_consistent)
for value in free_vars:
if value.var:
q = q.release_variable(value)
return q
except MalformedQuery:
raise
else:
raise MalformedQuery(string, "ConjunctiveQuery")
atom_s = Atom("S", [y, z])
# Initialize functional dependencies
# First parameter : Left side of the FD (List of variables)
# Second parameter : Right side of the FD (must be a single variable)
fd1 = FunctionalDependencySet()
fd1.add(FunctionalDependency([x], y))
fd2 = FunctionalDependencySet()
fd2.add(FunctionalDependency([y], z))
# Initialize the conjunctive query
q = ConjunctiveQuery()
# Add atoms to q
# First parameter : The atom to be added
# Second parameter : The set of FD (must be a frozenset as in the example)
# Third parameter : A List of booleans describing the "key positions" of the atom
# Fourth Parameter : A boolean that must be True if the atom is consistent, False if not
q = q.add_atom(atom_r, fd1, [True, True, False], False)
q = q.add_atom(atom_s, fd2, [True, False], False)
# Choose free variables (creates a new instance)
q = q.release_variable(x)
q = q.release_variable(y)
# Launch rewriting
program = rewrite(q)
# You can print the Datalog program
print(program)