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37bd4dd 1dda07c 67524d7 37bd4dd 67524d7 37bd4dd 67524d7 37bd4dd 67524d7 37bd4dd 67524d7 37bd4dd 67524d7 37bd4dd 67524d7 37bd4dd 67524d7 37bd4dd 1dda07c 67524d7 1dda07c fd68fcc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 | import psycopg2
import re
import pandas as pd
class DataWrapper:
def __init__(self, data):
if isinstance(data, list):
emptyDict = {dataKey:None for dataKey in data}
self.__dict__.update(emptyDict)
elif isinstance(data, dict):
self.__dict__.update(data)
def addKey(self, key, val=None):
self.__dict__.update({key:val})
def __repr__(self):
return self.__dict__.__repr__()
class MetaDataLayout:
def __init__(self, schemaName, allTablesAndCols):
self.schemaName = schemaName
self.datalayout = {
"schema": self.schemaName,
"selectedTables":{},
"allTables":allTablesAndCols
}
def setSelection(self, tablesAndCols):
"""
tablesAndCols : {"table1":["col1", "col2"], "table1":["cola","colb"]}
"""
datalayout = self.datalayout
for table in tablesAndCols:
if table in datalayout['allTables'].keys():
datalayout['selectedTables'][table] = tablesAndCols[table]
else:
print(f"Table {table} doesn't exists in the schema")
self.datalayout = datalayout
def resetSelection(self):
datalayout = self.datalayout
datalayout['selectedTables'] = {}
self.datalayout = datalayout
def getSelectedTablesAndCols(self):
return self.datalayout['selectedTables']
def getAllTablesCols(self):
return self.datalayout['allTables']
class DbEngine:
def __init__(self, dbCreds):
self.dbCreds = dbCreds
self._connection = None
def connect(self):
dbCreds = self.dbCreds
if self._connection is None or self._connection.closed != 0:
self._connection = psycopg2.connect(database=dbCreds.database, user = dbCreds.user,
password = dbCreds.password, host = dbCreds.host,
port = dbCreds.port)
def getConnection(self):
if self._connection is None or self._connection.closed != 0:
self.connect()
return self._connection
def disconnect(self):
if self._connection is not None and self._connection.closed == 0:
self._connection.close()
def execute_query(self, query):
try:
self.connect()
with self._connection.cursor() as cursor:
cursor.execute(query)
result = cursor.fetchall()
except Exception as e:
raise Exception(e)
return result
def executeQuery(dbEngine, query):
result = dbEngine.execute_query(query)
return result
def executeColumnsQuery(dbEngine, columnQuery):
dbEngine.connect()
with dbEngine._connection.cursor() as cursor:
cursor.execute(columnQuery)
columns = [desc[0] for desc in cursor.description]
return columns
def closeDbEngine(dbEngine):
dbEngine.disconnect()
def getAllTablesInfo(dbEngine, schemaName):
tablesAndCols = {}
allTablesQuery = f"""SELECT table_name FROM information_schema.tables
WHERE table_schema = '{schemaName}'"""
tables = executeQuery(dbEngine, allTablesQuery)
for table in tables:
tableName = table[0]
columnsQuery = f"""Select * FROM {schemaName}.{tableName} LIMIT 0"""
columns = executeColumnsQuery(dbEngine, columnsQuery)
tablesAndCols[tableName] = columns
return tablesAndCols
def getSampleDataForTablesAndCols(dbEngine, schemaName, tablesAndCols, maxRows):
data = {}
dbEngine.connect()
conn = dbEngine.getConnection()
for table in tablesAndCols.keys():
try:
sqlQuery = f"""select * from {schemaName}.{table} limit {maxRows}"""
data[table] = pd.read_sql_query(sqlQuery, con=conn)
except:
print(f"couldn't read table data. Table: {table}")
return data
# Function to test the generated sql query
def isDataQuery(sql_query):
upper_query = sql_query.upper()
dml_keywords = ['INSERT', 'UPDATE', 'DELETE', 'MERGE']
for keyword in dml_keywords:
if re.search(fr'\b{keyword}\b', upper_query):
return False # Found a DML keyword, indicating modification
# If no DML keywords are found, it's likely a data query
return True
def extractSqlFromGptResponse(gptReponse):
sqlPattern = re.compile(r"```sql\n(.*?)```", re.DOTALL)
# Find the match in the text
match = re.search(sqlPattern, gptReponse)
# Extract the SQL query if a match is found
if match:
sqlQuery = match.group(1)
return sqlQuery
else:
return ""
def addSchemaToTableInSQL(sqlQuery, schemaName, tablesList):
for table in tablesList:
pattern = re.compile(rf'(?<!\S){re.escape(table)}(?!\S)', re.IGNORECASE)
replacement = f'{schemaName}.{table}'
sqlQuery = re.sub(pattern, replacement, sqlQuery)
return sqlQuery
def preProcessGptQueryReponse(gptResponse, metadataLayout: MetaDataLayout):
schemaName = metadataLayout.schemaName
tablesList = metadataLayout.getAllTablesCols().keys()
gptResponse = addSchemaToTableInSQL(gptResponse, schemaName=schemaName, tablesList=tablesList)
return gptResponse |