CODEWITHSUNDEEP
pythonsql-serversqlalchemypyodbc
vftw
vftw

Reputation: 1677

Create table and Insert to SQL Server using Python

I have a huge table (147 columns) and I would like to know if it is possible to create the table in SQL server from my pandas dataframe so I don't have to CREATE TABLE for 147 columns.

I am trying to follow what is answered in most of related questions:

params = urllib.parse.quote_plus("DRIVER={ODBC Driver 17 for SQL Server};SERVER=DESKTOP-LFOSSEF;DATABASE=test;UID=xxxx;PWD=xxx")
engine = create_engine("mssql+pyodbc:///?odbc_connect=%s" % params)
connection = engine.raw_connection()
df.to_sql("table_name", connection,index=False)

The user and password work because that's what I am using to sign in into sqlserver.

When I run this, I get:

Execution failed on sql 'SELECT name FROM sqlite_master WHERE type='table' AND name=?;': ('42S02', "[42S02] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Invalid object name 'sqlite_master'. (208) (SQLExecDirectW); [42S02] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Statement(s) could not be prepared. (8180)")

If I remove the connection = engine.raw_connection() and use engine directly, I get:

AttributeError: 'Engine' object has no attribute 'cursor'

Any idea what is wrong? Do I need to create an empty table first? I've been troubleshooting for hours and can't find any reason why this isnt working.

Upvotes: 1

Views: 1357

Answers (1)

ASH
ASH

Reputation: 20322

Do it like this.

import pyodbc

engine = "mssql+pyodbc://Your_Server_Name/Your_DB_Name?driver=SQL Server Native Client 11.0?trusted_connection=yes"

df.to_sql(x, engine, if_exists='append', index=True)

df = name of your dataframe & x = name of your table in SQL Server

Upvotes: 1

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