Connecting to SQL Server 2012 using sqlalchemy and pyodbc

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Connecting to SQL Server 2012 using sqlalchemy and pyodbc

I’m trying to connect to a SQL Server 2012 database using SQLAlchemy (with pyodbc) on Python 3.3 (Windows 7-64-bit). I am able to connect using straight pyodbc but have been unsuccessful at connecting using SQLAlchemy. I have dsn file setup for the database access.

I successfully connect using straight pyodbc like this:

con = pyodbc.connect('FILEDSN=c:\users\me\mydbserver.dsn')

For sqlalchemy I have tried:

import sqlalchemy as sa
engine = sa.create_engine('mssql+pyodbc://c/users/me/mydbserver.dsn/mydbname')

The create_engine method doesn’t actually set up the connection and succeeds, but
iIf I try something that causes sqlalchemy to actually setup the connection (like engine.table_names()), it takes a while but then returns this error:

DBAPIError: (Error) ('08001', '[08001] [Microsoft][ODBC SQL Server Driver][DBNETLIB]SQL Server does not exist or access denied. (17) (SQLDriverConnect)') None None

I’m not sure where thing are going wrong are how to see what connection string is actually being passed to pyodbc by sqlalchemy. I have successfully using the same sqlalchemy classes with SQLite and MySQL.

Thanks in advance!

Answer #1:

The file-based DSN string is being interpreted by SQLAlchemy as server name = c, database name = users.

I prefer connecting without using DSNs, it’s one less configuration task to deal with during code migrations.

This syntax works using Windows Authentication:

engine = sa.create_engine('mssql+pyodbc://server/database')

Or with SQL Authentication:

engine = sa.create_engine('mssql+pyodbc://user:password@server/database')

SQLAlchemy has a thorough explanation of the different connection string options here.

Answered By: Bryan

Answer #2:

In Python 3 you can use function quote_plus from module urllib.parse to create parameters for connection:

import urllib
params = urllib.parse.quote_plus("DRIVER={SQL Server Native Client 11.0};"

engine = sa.create_engine("mssql+pyodbc:///?odbc_connect={}".format(params))

In order to use Windows Authentication, you want to use Trusted_Connection as parameter:

params = urllib.parse.quote_plus("DRIVER={SQL Server Native Client 11.0};"

In Python 2 you should use function quote_plus from library urllib instead:

params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};"
Answered By: pooja karande

Answer #3:

I have an update info about the connection to MSSQL Server without using DSNs and using Windows Authentication. In my example I have next options:
My local server name is “(localdb)ProjectsV12”. Local server name I see from database properties (I am using Windows 10 / Visual Studio 2015).
My db name is “MainTest1”

engine = create_engine('mssql+pyodbc://(localdb)ProjectsV12/MainTest1?driver=SQL+Server+Native+Client+11.0', echo=True)

It is needed to specify driver in connection.
You may find your client version in:

control panel>Systems and Security>Administrative Tools.>ODBC Data
Sources>System DSN tab>Add

Look on SQL Native client version from the list.

Answered By: Andrew

Answer #4:

Just want to add some latest information here:
If you are connecting using DSN connections:

engine = create_engine("mssql+pyodbc://USERNAME:PASSWORD@SOME_DSN")

If you are connecting using Hostname connections:

engine = create_engine("mssql+pyodbc://USERNAME:PASSWORD@HOST_IP:PORT/DATABASENAME?driver=SQL+Server+Native+Client+11.0")

For more details, please refer to the “Official Document”

Answered By: ssword

Answer #5:

I did different and worked like a charm.

First you import the library:

import pandas as pd
from sqlalchemy import create_engine
import pyodbc

Create a function to create the engine

def mssql_engine(user = os.getenv('user'), password = os.getenv('password')
                 ,host = os.getenv('SERVER_ADDRESS'),db = os.getenv('DATABASE')):
    engine = create_engine(f'mssql+pyodbc://{user}:{password}@{host}/{db}?driver=SQL+Server')
    return engine

Create a variable with your query

query = 'SELECT * FROM [Orders]'

Execute the Pandas command to create a Dataframe from a MSSQL Table

df = pd.read_sql(query, mssql_engine())
Answered By: Hugo Pitta

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