def validateUnique(database, table, value, index):
records = jsonMode.extractTable(database, table)
if records == []:
return
for record in records:
if value == record[index]:
lstErr.append("El Valor " + str(value) +
" ya existe dentro de la tabla")
syntaxPostgreErrors.append("Error: 23505: El valor " + str(value) +
" ya existe dentro de la tabla")
break
def validatePrimary(database, table, values, index):
records = jsonMode.extractTable(database, table)
if records == []:
return
for record in records:
lst1 = []
lst2 = []
for j in index:
lst1.append(record[j])
lst2.append(values[j].value)
if lst1 == lst2:
lstErr.append("Llaves primarias existentes dentro de la tabla")
syntaxPostgreErrors.append(
"Error: 23505: llaves primarias duplicadas ")
break
def validateForeign(database, values, value):
# values = [references,column]
references = values[0]
column = values[1]
records = jsonMode.extractTable(database, references)
if records == []:
syntaxPostgreErrors.append("Error: 23503: El valor " + str(value) +
" no es una llave foranea ")
lstErr.append("El Valor " + str(value) + " no es una llave foranea")
return
index = S.getIndex(database, references, column)
for record in records:
if value == record[index]:
return
lstErr.append("El Valor " + str(value) + " no es una llave primaria")
syntaxPostgreErrors.append("Error: 23505: El valor " + str(value) +
" no es una llave primaria ")
def execute(self, environment):
result = jsonMode.extractTable(instruction.dbtemp, self.name)
if result == None:
instruction.semanticErrors.append([
"La tabla " + str(self.name) +
" no pertenece a la base de datos " + instruction.dbtemp,
self.row,
])
instruction.syntaxPostgreSQL.append("Error: 42P01: la relacion " +
instruction.dbtemp + "." +
str(self.name) + " no existe")
return "FATAL ERROR TABLE ID"
# Almacena una lista con con el nombre y tipo de cada columna
lst = Struct.extractColumns(instruction.dbtemp, self.name)
columns = [l.name for l in lst]
newColumns = [self.name + "." + col for col in columns]
df = pd.DataFrame(result, columns=newColumns)
environment.addTable(self.name)
tempTypes = {}
for i in range(len(newColumns)):
tempTypes[newColumns[i]] = lst[i].type
return [df, tempTypes]