def h_61_opt(params, variables):
if len(params[0]) == 1 and db._db.has_index(params[0][0]):
bounds = []
for expr in params[1:]:
if len(expr) == 1 \
and isinstance(expr[0], (bytes, str)) \
and expr[0][0] == '$' \
and expr[0][1:] not in variables:
# parameter
bounds.append(expr[0])
else:
bounds.append(evaluate_stack(expr[:], variables))
if all(bounds):
return [params[0][0], ([bounds[0], True], [bounds[1], False])]
def _optimize_conditions(conditions, variables, parent_op=None):
op2 = None
op = conditions[-1]
# list of [[indexed_lookups], [rte conditions]]
optimized = [[[], []]]
# keep a copy of conditions
cp_conditions = conditions[:]
if type(op) == str and op in operators2:
op2 = conditions.pop()
if op == "and":
op1 = _optimize_conditions(conditions, variables, op)
op2 = _optimize_conditions(conditions, variables, op)
# calculate indexed lookups
if op2[0][0]:
optimized[0][0] += op2[0][0]
if op1[0][0]:
# check if the same index is already included
is_optimized = False
if op1[0][0][0][0] in [l[0] for l in optimized[0][0]]:
if type(op1[0][0][0][1]) == tuple:
new_lookup = op1[0][0][0]
lookups = [l for l in optimized[0][0] if l[0] == new_lookup[0]]
for lookup in lookups:
if type(lookup[1]) == tuple:
if lookup[1][0] is None and new_lookup[1][0]:
lookup[1] = (new_lookup[1][0], lookup[1][1])
is_optimized = True
break
elif lookup[1][1] is None and new_lookup[1][1]:
lookup[1] = (lookup[1][0], new_lookup[1][1])
is_optimized = True
break
if not is_optimized:
optimized[0][0] += op1[0][0]
# calculate rte conditions
optimized[0][1] += op2[0][1] + op1[0][1]
if op2[0][1] and op1[0][1]:
optimized[0][1] += ["and"]
elif op == "or":
if parent_op == "and":
# remove operands
_pop_stack(conditions)
_pop_stack(conditions)
optimized[0][1] += cp_conditions[len(conditions) :]
else:
op1 = _optimize_conditions(conditions, variables, op)
op2 = _optimize_conditions(conditions, variables, op)
optimized = op1 + op2
elif op in ["=", "<", ">", "<=", ">="]:
index = conditions[-1]
if type(index) == str:
lookup = None
if index == "_id":
index = "id"
if db._db.has_index(index):
conditions.pop()
if (
isinstance(conditions[-1], (bytes, str))
and conditions[-1][0] == "$"
and conditions[-1][1:] not in variables
):
# query parameter
index_value = conditions.pop()
else:
# try to evaluate index value
index_value = evaluate_stack(conditions, variables)
if index_value is not None:
# we have an immutable value
if op == "=":
lookup = [index, index_value]
elif op in ["<", "<="]:
lookup = [index, (None, [index_value, "=" in op])]
elif op in [">", ">="]:
lookup = [index, ([index_value, "=" in op], None)]
optimized[0][0].append(lookup)
if lookup is None:
# query on an non-indexed attribute
# or on an indexed attribute with mutable value
optimized[0][1] = cp_conditions[len(conditions) :] + optimized[0][1]
else:
# remove operands
_pop_stack(conditions)
_pop_stack(conditions)
optimized[0][1] = cp_conditions[len(conditions) :] + optimized[0][1]
# functions
elif type(op) == list:
lookup = None
cmd_code, params = op
optimizer = globals().get("h_%s_opt" % cmd_code)
if optimizer is not None:
lookup = optimizer(params, variables)
if lookup is None:
optimized[0][1] = [op] + optimized[0][1]
else:
optimized[0][0].append(lookup)
else:
_pop_stack(conditions)
optimized[0][1] = cp_conditions[len(conditions) :] + optimized[0][1]
return optimized
def _optimize_conditions(conditions, variables, parent_op=None):
op2 = None
op = conditions[-1]
# list of [[indexed_lookups], [rte conditions]]
optimized = [[[], []]]
# keep a copy of conditions
cp_conditions = conditions[:]
if type(op) == str and op in operators2:
op2 = conditions.pop()
if op == 'and':
op1 = _optimize_conditions(conditions, variables, op)
op2 = _optimize_conditions(conditions, variables, op)
# calculate indexed lookups
if op2[0][0]:
optimized[0][0] += op2[0][0]
if op1[0][0]:
# check if the same index is already included
is_optimized = False
if op1[0][0][0][0] in [l[0] for l in optimized[0][0]]:
if type(op1[0][0][0][1]) == tuple:
new_lookup = op1[0][0][0]
lookups = [l for l in optimized[0][0]
if l[0] == new_lookup[0]]
for lookup in lookups:
if type(lookup[1]) == tuple:
if lookup[1][0] is None and new_lookup[1][0]:
lookup[1] = (new_lookup[1][0],
lookup[1][1])
is_optimized = True
break
elif lookup[1][1] is None and new_lookup[1][1]:
lookup[1] = (lookup[1][0],
new_lookup[1][1])
is_optimized = True
break
if not is_optimized:
optimized[0][0] += op1[0][0]
# calculate rte conditions
optimized[0][1] += op2[0][1] + op1[0][1]
if op2[0][1] and op1[0][1]:
optimized[0][1] += ['and']
elif op == 'or':
if parent_op == 'and':
# remove operands
_pop_stack(conditions)
_pop_stack(conditions)
optimized[0][1] += cp_conditions[len(conditions):]
else:
op1 = _optimize_conditions(conditions, variables, op)
op2 = _optimize_conditions(conditions, variables, op)
optimized = op1 + op2
elif op in ['=', '<', '>', '<=', '>=']:
index = conditions[-1]
if type(index) == str:
lookup = None
if index == '_id':
index = 'id'
if db._db.has_index(index):
conditions.pop()
if isinstance(conditions[-1], (bytes, str)) \
and conditions[-1][0] == '$' \
and conditions[-1][1:] not in variables:
# query parameter
index_value = conditions.pop()
else:
# try to evaluate index value
index_value = evaluate_stack(conditions, variables)
if index_value is not None:
# we have an immutable value
if op == '=':
lookup = [index, index_value]
elif op in ['<', '<=']:
lookup = [index, (None, [index_value, '=' in op])]
elif op in ['>', '>=']:
lookup = [index, ([index_value, '=' in op], None)]
optimized[0][0].append(lookup)
if lookup is None:
# query on an non-indexed attribute
# or on an indexed attribute with mutable value
optimized[0][1] = cp_conditions[len(conditions):] + \
optimized[0][1]
else:
# remove operands
_pop_stack(conditions)
_pop_stack(conditions)
optimized[0][1] = cp_conditions[len(conditions):] + \
optimized[0][1]
# functions
elif type(op) == list:
lookup = None
cmd_code, params = op
optimizer = globals().get('h_%s_opt' % cmd_code)
if optimizer is not None:
lookup = optimizer(params, variables)
if lookup is None:
optimized[0][1] = [op] + optimized[0][1]
else:
optimized[0][0].append(lookup)
else:
_pop_stack(conditions)
optimized[0][1] = cp_conditions[len(conditions):] + optimized[0][1]
return optimized
