pandas to sql index
resultDf.to_sql('table_name', engine, schema="schema_name", if_exists="append", index=False)pandas to sql index
resultDf.to_sql('table_name', engine, schema="schema_name", if_exists="append", index=False)df to sql pandas sql achemy
from sqlalchemy import create_engine
engine = create_engine('sqlite://', echo=False)
df.to_sql('users', con=engine)
engine.execute("SELECT * FROM users").fetchall()convert sql to python
# credit to Stack Overflow user in the source link
# NOTE: this is ust an example, you have to adapt the query and other stuff to your needs
import sqlite3
import json
query = """
{
"ID": "4",
"Name": "David",
"Transformation": "SELECT ID || Name AS NewField FROM inputdata"
}"""
query_dict = json.loads(query)
db = sqlite3.Connection('mydb')
db.execute('create table inputdata ({} VARCHAR(100));'.format(' VARCHAR(100), '.join(query_dict.keys())))
db.execute('insert into inputdata ({}) values ("{}")'.format(','.join(query_dict.keys()),'","'.join(query_dict.values())))
r = db.execute(query_dict['Transformation'])
response = {}
response[r.description[0][0]] = r.fetchone()[0]
print(response)
>>> {'NewField': '4David'}
db.execute('drop table inputdata;')
db.close()Copyright © 2021 Codeinu
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