I'm trying to connect to a database with python.
I'm not an expert in SQL, So I will put the parameters of my db
Driver = Sybase jConnect 6.0 (com.sybase.jdbc4.SybDriver)
URL = jdbc:sybase:Tds:slpdfrsiqq3401.fr.intranet:20301
Usename = myusername
Password = mypassword
Database = databasename
Since I don't have the right to install the package sybase-python, I'm trying to do the job with available packages. This is my code :
import pandas as pd
import pyodbc
from sqlalchemy import create_engine
engine=create_engine("jdbc+sybase://myusername:mypassword#slpdfrsiqq3401.fr.intranet:20301/databasename")
#Trying to creating engine to use then pd.read_sql_query()
My code doesn't work and I have this error :
"Can't load plugin: sqlalchemy.dialects:jdbc.sybase"
Could anyone help me to fix the problem?
I think you need to try other drivers as suggested in the docs here
Example
sybase+pyodbc://<username>:<password>#<dsnname>[/<database>]
Related
I need an R script that allows me to connect to an Oracle DB without having to install anything needing admin powers, and preferrably nothing at all apart from package downloads. In python the following code works, I believe because it uses the cx_Oracle module as a portable driver. What would be a good R alternative?
import pandas as pd
import sqlalchemy
import sys
host = "xxx.intra"
database = "mydb"
user = "usr"
password = "pw"
def get_oracle_engine(host, database, user, password):
return sqlalchemy.create_engine("oracle+cx_oracle://{user}:{password}#{host}:1521/?service_name={database}".format(host=host, database=database, user=user, password=password))
engine=get_oracle_engine(host, database, user, password)
pd.read_sql_table("mytable", engine, schema= mydb,index.cols="id1")
I managed to install ROracle using the CRAN instructions but I keep getting the ORA-12154 TNS: cound not resolve the connect identifier specified when using:
library(ROracle)
con= DBI::dbconnect(dbDriver("Oracle"), user= user, password=password, host=host, dbname=database, port="1521")
By the way dbDriver("Oracle") returns
Driver name : Oracle (OCI)
Driver version: 1.3-1
Client version: 12.1.0.2.0
Try code like:
library(DBI)
library(ROracle)
drv <- Oracle()
con <- dbConnect(drv, 'cj', 'welcome', 'localhost:1521/orclpdb1')
dbGetQuery(con,"select count(*) from dual")
The connect string components are related to the {host}:1521/?service_name values you used with SQLAlchemy. Use a TNS alias or Easy Connect String, the same as other C based Oracle drivers, e.g. https://cx-oracle.readthedocs.io/en/latest/user_guide/connection_handling.html#connection-strings
The current ROracle code is at https://www.oracle.com/database/technologies/roracle-downloads.html There are some packaging glitches with uploading to CRAN and the CRAN maintainers haven't been responsive about resolving them.
ROracle still needs Oracle Client libraries such as from Oracle Instant Client.
I am trying to connect to Netezza using SQLalchemy.create_engine(). The reason I want to use SQLAlchmey is because I want to be able to read and write through pandas dataframe.
What works is as follow:
import pandas as pd
import pyodbc
conn = pyodbc.connect('DSN=NZDWW')
df2 = pd.read_sql(Query,conn)
Above code runs fine. But in order to write df dataframe to the Netezza, I need to use the function to_sql(), which needs SQLAlchemy. This is what my code looks like:
from sqlalchemy import create_engine
username = os.getenv('REDSHIFT_USER')
password = os.getenv('REDSHIFT_PASS')
DATABASE = "SHP_TARGET"
HOST = "Netezza1"
PORT = 5480
conn_str = "postgresql://"+username+":"+password+"#"+HOST+':'+str(PORT)+'/'+DATABASE
engine3 = create_engine(conn_str)
df = pd.read_sql(Query, engine3)
When I execute this, I get the following error:
OperationalError: (psycopg2.OperationalError) Invalid - opcode
Invalid - opcodeInvalid packet length (Background on this error at: http://sqlalche.me/e/e3q8)
Any leads will be much appreciated. thanks.
Database: Netezza
Python version: 3.6
OS: Windows
The sqlalchemy dialect for Postges isn't compatible with Netezza.
The error you're receiving is the psycopg2 module, which facilitates the connection, complaining that it can't make sense of what the server is "saying", basically.
There appears to be a dialect for Netezza though. You may want to try that out.
Here's the formal dialect for Netezza has been released.
It can be used as documented here - https://github.com/IBM/nzalchemy#prerequisites
Example
from sqlalchemy import create_engine
from urllib import parse_quote_plus
# assumes NZ_HOST, NZ_USER, NZ_PASSWORD are set
import os
params = parse_quote_plus(f"DRIVER=NetezzaSQL;SERVER={os['NZ_HOST']};"
f"DATABASE={os['NZ_DATABASE']};USER={os['NZ_USER'};"
f"PASSWORD={os['NZ_PASSWORD']}")
engine = create_engine(f"netezza+pyodbc:///?odbc_connect={params}",
echo=True)
I have a python code through which I am getting a pandas dataframe "df". I am trying to write this dataframe to Microsoft SQL server. I am trying to connect through the following code by I am getting an error
import pyodbc
from sqlalchemy import create_engine
engine = create_engine('mssql+pyodbc:///?odbc_connect=DRIVER={SQL Server};SERVER=bidept;DATABASE=BIDB;UID=sdcc\neils;PWD=neil!pass')
engine.connect()
df.to_sql(name='[BIDB].[dbo].[Test]',con=engine, if_exists='append')
However at the engine.connect() line I am getting the following error
sqlalchemy.exc.DBAPIError: (pyodbc.Error) ('08001', '[08001] [Microsoft][ODBC SQL Server Driver]Neither DSN nor SERVER keyword supplied (0) (SQLDriverConnect)')
Can anyone tell me what I am missing. I am using Microsoft SQL Server Management Studio - 14.0.17177.0
I connect to the SQL server through the following
Server type: Database Engine
Server name: bidept
Authentication: Windows Authentication
for which I log into my windows using username : sdcc\neils
and password : neil!pass
I am new to databases and python. Kindly let me know if you need any additional details. Any help will be greatly appreciated. Thank you in advance.
I was finally able to make it run.
import pyodbc
from sqlalchemy import create_engine
import urllib
params = urllib.quote_plus(r'DRIVER={SQL Server};SERVER=bidept;DATABASE=BIDB;Trusted_Connection=yes')
### For python 3.5: urllib.parse.quote_plus
conn_str = 'mssql+pyodbc:///?odbc_connect={}'.format(params)
engine = create_engine(conn_str)
reload(sys)
sys.setdefaultencoding('utf8')
df.to_sql(name='Test',con=engine, if_exists='append',index=False)
Thanks to #gord-thompson who answered Here
Although my in my sql server, all the tables are under the 'dbo' schema (i.e. dbo.Test1, dbo.Other_Tables) and this query puts my table in 'sdcc\neils' schema (i.e. sdcc\neils.Test1, sdcc\neils.Other_Tables) any solution to this?
I am trying to use 'pandas.read_sql_query' to copy data from MS SQL Server into a pandas DataFrame. I need to do multiple joins in my SQL query. The tables being joined are on the same server but in different databases. The query I am passing to pandas works fine inside MS SQL Server Management Studio. In a Jupyter Notebook I tried to query data like so (to make things readable the query itself is simplified to just 2 joins and generic names are used):
import pandas as pd
import sqlalchemy as sql
import pyodbc
server = '100.10.10.10'
driver = 'SQL+Server+Native+Client+11.0'
myQuery = '''SELECT first.Field1, second.Field2
FROM db1.schema.Table1 AS first
JOIN db2.schema.Table2 AS second
ON first.Id = second.FirstId
'''
engine = sql.create_engine('mssql+pyodbc://{}?driver={}'.format(server, driver))
df = pd.read_sql_query(myQuery, engine)
This does not work and returns an error:
DBAPIError: (pyodbc.Error) ('IM010', '[IM010] [Microsoft][��������� ��������� ODBC] ������� ������� ��� ��������� ������ (0) (SQLDriverConnect)')
It seems that the problem is in the engine which does not include information about the database, because everything works fine with the next kind of code, where I include database in the engine:
myQuery = 'select Field1 from schema.Table1'
db = 'db1'
engine = sql.create_engine('mssql+pyodbc://{}/{}?driver={}'.format(server, db, driver))
df = pd.read_sql_query(myQuery, engine)
but breaks like the code with joins above if I don't include database in the engine, but add it to the query like so:
myQuery = 'select Field1 from db1.schema.Table1'
engine = sql.create_engine('mssql+pyodbc://{}?driver={}'.format(server,
driver))
df = pd.read_sql_query(myQuery, engine)
So how should I specify the pandas.read_sql_query 'sql' and 'con' parameters in
this case when I need to join tables from different databases but the same server?
P.S. I only have read access to this server I am connecting to. I can not create new tables or views or anything like that.
Update:
The MS SQL Server version is 2008 R2.
Update 2: I am using Python 3.6 and Windows 10.
So I have found a workaround: use pymssql instead of pyodbc (both in the import statement and in the engine). It lets you build your joins using database names and without specifying them in the engine. And there is no need to specify a driver in this case.
There might be a problem if you are using Python 3.6 which is not supported by pymssql oficially yet, but you can find unofficial wheels for your Python 3.6 here. It works as is supposed to with my queries.
Here is the original code with joins, rebuilt to work with pymssql:
import pandas as pd
import sqlalchemy as sql
import pymssql
server = '100.10.10.10'
myQuery = '''SELECT first.Field1, second.Field2
FROM db1.schema.Table1 AS first
JOIN db2.schema.Table2 AS second
ON first.Id = second.FirstId'''
engine = sql.create_engine('mssql+pymssql://{}'.format(server))
df = pd.read_sql_query(myQuery, engine)
As for the unofficial wheels, you need to download the file for Python 3.6 from the link I gave above, then cd to the download folder and run pip install wheels where 'wheels' is the name of the wheels file.
UPDATE:
Actually, it is possible to use pyodbc too. I am not sure if this should work for any SQL Server setup, but everything worked for me after I had set 'master' as my database in the engine. The resulting code would look like this:
import pandas as pd
import sqlalchemy as sql
import pyodbc
server = '100.10.10.10'
driver = 'SQL+Server'
db = 'master'
myQuery = '''SELECT first.Field1, second.Field2
FROM db1.schema.Table1 AS first
JOIN db2.schema.Table2 AS second
ON first.Id = second.FirstId'''
engine = sql.create_engine('mssql+pyodbc://{}/{}?driver={}'.format(server, db, driver))
df = pd.read_sql_query(myQuery, engine)
The following code is working for me. I am using SQL server with SQLAlchemy
import pyodbc
import pandas as pd
cnxn = pyodbc.connect('DRIVER=ODBC Driver 17 for SQL Server;SERVER=your_db_server_id,your_db_server_port;DATABASE=pangard;UID=your_db_username;PWD=your_db_password')
query = "SELECT * FROM database.tablename;"
df = pd.read_sql(query, cnxn)
print(df)
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.
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.
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};"
"SERVER=dagger;"
"DATABASE=test;"
"UID=user;"
"PWD=password")
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};"
"SERVER=dagger;"
"DATABASE=test;"
"Trusted_Connection=yes")
In Python 2 you should use function quote_plus from library urllib instead:
params = urllib.quote_plus("DRIVER={SQL Server Native Client 11.0};"
"SERVER=dagger;"
"DATABASE=test;"
"UID=user;"
"PWD=password")
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.
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"
import pyodbc
import sqlalchemy as sa
engine = sa.create_engine('mssql+pyodbc://ServerName/DatabaseName?driver=SQL+Server+Native+Client+11.0',echo = True)
This works with Windows Authentication.
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())