from sqlglot import exp from sqlglot.helper import while_changing from sqlglot.optimizer.simplify import flatten, simplify, uniq_sort def normalize(expression, dnf=False, max_distance=128): """ Rewrite sqlglot AST into conjunctive normal form. Example: >>> import sqlglot >>> expression = sqlglot.parse_one("(x AND y) OR z") >>> normalize(expression).sql() '(x OR z) AND (y OR z)' Args: expression (sqlglot.Expression): expression to normalize dnf (bool): rewrite in disjunctive normal form instead max_distance (int): the maximal estimated distance from cnf to attempt conversion Returns: sqlglot.Expression: normalized expression """ expression = simplify(expression) expression = while_changing( expression, lambda e: distributive_law(e, dnf, max_distance) ) return simplify(expression) def normalized(expression, dnf=False): ancestor, root = (exp.And, exp.Or) if dnf else (exp.Or, exp.And) return not any( connector.find_ancestor(ancestor) for connector in expression.find_all(root) ) def normalization_distance(expression, dnf=False): """ The difference in the number of predicates between the current expression and the normalized form. This is used as an estimate of the cost of the conversion which is exponential in complexity. Example: >>> import sqlglot >>> expression = sqlglot.parse_one("(a AND b) OR (c AND d)") >>> normalization_distance(expression) 4 Args: expression (sqlglot.Expression): expression to compute distance dnf (bool): compute to dnf distance instead Returns: int: difference """ return sum(_predicate_lengths(expression, dnf)) - ( len(list(expression.find_all(exp.Connector))) + 1 ) def _predicate_lengths(expression, dnf): """ Returns a list of predicate lengths when expanded to normalized form. (A AND B) OR C -> [2, 2] because len(A OR C), len(B OR C). """ expression = expression.unnest() if not isinstance(expression, exp.Connector): return [1] left, right = expression.args.values() if isinstance(expression, exp.And if dnf else exp.Or): x = [ a + b for a in _predicate_lengths(left, dnf) for b in _predicate_lengths(right, dnf) ] return x return _predicate_lengths(left, dnf) + _predicate_lengths(right, dnf) def distributive_law(expression, dnf, max_distance): """ x OR (y AND z) -> (x OR y) AND (x OR z) (x AND y) OR (y AND z) -> (x OR y) AND (x OR z) AND (y OR y) AND (y OR z) """ if isinstance(expression.unnest(), exp.Connector): if normalization_distance(expression, dnf) > max_distance: return expression to_exp, from_exp = (exp.Or, exp.And) if dnf else (exp.And, exp.Or) exp.replace_children(expression, lambda e: distributive_law(e, dnf, max_distance)) if isinstance(expression, from_exp): a, b = expression.unnest_operands() from_func = exp.and_ if from_exp == exp.And else exp.or_ to_func = exp.and_ if to_exp == exp.And else exp.or_ if isinstance(a, to_exp) and isinstance(b, to_exp): if len(tuple(a.find_all(exp.Connector))) > len( tuple(b.find_all(exp.Connector)) ): return _distribute(a, b, from_func, to_func) return _distribute(b, a, from_func, to_func) if isinstance(a, to_exp): return _distribute(b, a, from_func, to_func) if isinstance(b, to_exp): return _distribute(a, b, from_func, to_func) return expression def _distribute(a, b, from_func, to_func): if isinstance(a, exp.Connector): exp.replace_children( a, lambda c: to_func( exp.paren(from_func(c, b.left)), exp.paren(from_func(c, b.right)), ), ) else: a = to_func(from_func(a, b.left), from_func(a, b.right)) return _simplify(a) def _simplify(node): node = uniq_sort(flatten(node)) exp.replace_children(node, _simplify) return node