def process(self, instruction):
#Obteniendo tabla de la cual voy a hacer el update
database_id = SymbolTable().useDatabase
table_tp = TypeChecker().searchTable(database_id, self.table)
table_cont = DataController().extractTable(self.table,0,0)
headers = TypeChecker().searchColumnHeadings(table_tp)
table_update = pd.DataFrame(table_cont)
table_update.columns = headers
tuplas = [] #t[0] = nombre columna, t[1] = valor a cambiar
for column in self.arr_columns_vals:
tuplas.append(column.process(instruction))
d = {}
for t in tuplas:
if not t[0] in headers:
print("Columna no existe --- ERROR")
break
else:
d[ headers.index(t[0]) ] = t[1].value
print("DICTIONARY")
print(d)
return None
if self.params == None: #CAMBIAR TODOS LOS REGISTROS DE LA TABLA
pk_col_name = TypeChecker().searchColPrimaryKey(table_tp).name
pk_list = table_update[[pk_col_name]].to_numpy()
print(pk_list)
for pk in pk_list:
DataController().update(self.table.value, d, pk, 0 , 0)
else:
for option in self.params:
if isinstance(option, Where):
table_update.query(option.condition.alias)
break
def process(self, instruction):
# Obteniendo tabla de la cual voy a hacer el update
database_id = SymbolTable().useDatabase
table_tp = TypeChecker().searchTable(database_id, self.table)
table_cont = DataController().extractTable(self.table, self.line, self.column)
headers = TypeChecker().searchColumnHeadings(table_tp)
table_update = pd.DataFrame(table_cont)
tuplas = [] # t[0] = nombre columna, t[1] = valor a cambiar
for column in self.arr_columns_vals:
tuplas.append(column.process(instruction))
d = {}
d_col_names = {}
# validando nombres de columnas ingresados
for t in tuplas:
if not t[0] in headers:
desc = f'Nombre de columna invalido, {t[0]}'
ErrorController().add(26, 'Execution', desc, self.line, self.column)
return None
else:
d[headers.index(t[0])] = t[1].value
d_col_names[t[0]] = t[1].value
# validando tipo de valores para las columnas
print(d_col_names)
checker = CreateTB(None, None, None, None)
for key in list(d_col_names.keys()):
column = TypeChecker().searchColumn(table_tp, key).__dict__
is_correct = checker.validateType(
column['_dataType'], d_col_names.get(key), False)
if not is_correct:
desc = f'Valor no valido para la columna {key}'
ErrorController().add(9, 'Execution', desc, self.line, self.column)
return None
if not realizeCheck(column, d_col_names, self.line, self.column):
return None
# CAMBIAR TODOS LOS REGISTROS DE LA TABLA
if self.params == None:
pk_col_name = TypeChecker().searchColPrimaryKey(table_tp)
if pk_col_name == []: # NO HAY LLAVE PRIMARIA
pk_list = range(len(table_update.index))
print(pk_list)
for pk in pk_list:
DataController().update(self.table, d, [
pk], self.line, self.column)
else:
list_pks = []
for col in pk_col_name:
list_pks.append(col.name)
table_update.columns = headers
pk_list = table_update[list_pks].values.tolist()
print(pk_list)
for pk in pk_list:
DataController().update(self.table, d, [
pk], self.line, self.column)
else:
if self.params is not list:
self.params = [self.params]
for option in self.params:
if isinstance(option, Where):
table_update.columns = headers
storage_columns(table_cont, headers,
self.line, self.column)
storage_table(table_cont, headers, self.table,
self.line, self.column)
table_result = option.process(
instruction, table_update, self.table)
pk_col_name = TypeChecker().searchColPrimaryKey(table_tp)
if pk_col_name == []: # NO HAY LLAVE PRIMARIA
pk_list = table_result.index.to_list()
print(pk_list)
for pk in pk_list:
if type(pk) is list:
DataController().update(self.table, d, pk, self.line, self.column)
else:
DataController().update(self.table, d, [pk], self.line, self.column)
else:
table_result.columns = headers
list_pks = []
for col in pk_col_name:
list_pks.append(col.name)
pk_list = table_result[list_pks].values.tolist()
print(pk_list)
for pk in pk_list:
if type(pk) is list:
DataController().update(self.table, d, pk, self.line, self.column)
else:
DataController().update(self.table, d, [pk], self.line, self.column)
return None
