Develop Reference

Accessing SQL data using Google Cloud Postgres for App Engine (python)

I have a google cloud Postgres database and I can query it no problem in a jupyter notebook. I created a connection to the database using psycopg2. However, I am building a web app with flask and it seems that I cannot use psycopg2 in the gcloud run deploy. I've read the documentation on pg8000 but I am very confused. I am very new to this.
What is the simplest function to create a connection to the database so I can query the data?
This is what I was using with psycopg2:
#establishing the connection
conn = psycopg2.connect(
database='postgres', user='postgres', password='password', host='Public IP Address', port='5432')
Then I could fetch data using:
cursor = conn.cursor()
cursor.execute('SELECT STMT')
result = cursor.fetchall()
Any help or direction is much appreciated.

SQL Server connection - Works in pyodbc, but not SQLAlchemy

This is a fairly common question but even using the answers on SO like here but I still can't connect.
When I setup my connection to pyodbc I can connect with the following:
cnxn = pyodbc.connect('DRIVER={SQL Server Native Client 11.0};SERVER=ip,port;DATABASE=db;UID=user;PWD=pass')
cursor = cnxn.cursor()
cursor.execute("some select query")
for row in cursor.fetchall():
print(row)
and it works.
However to do a .read_sql() in pandas I need to connect with sqlalchemy.
I have tried with both hosted connections and pass-through pyodbc connections like the below:
quoted = urllib.parse.quote_plus('DRIVER={SQL Server Native Client 11.0};Server=ip;Database=db;UID=user;PWD=pass;Port=port;')
engine = sqlalchemy.create_engine('mssql+pyodbc:///?odbc_connect={}'.format(quoted))
engine.connect()
I have tried with both SERVER=ip,port format and the separate Port=port parameter like above but still no luck.
The error I'm getting is Login failed for user 'user'. (18456)
Any help is much appreciated.

I assume that you want to create a DataFrame so when you have a cnxn you can pass it to Pandas read_sql_query function.
Example:
cnxn = pyodbc.connect('your connection string')
query = 'some query'
df = pandas.read_sql_query(query, conn)

How to connect to a cluster in Amazon Redshift using SQLAlchemy?

In Amazon Redshift's Getting Started Guide, it's mentioned that you can utilize SQL client tools that are compatible with PostgreSQL to connect to your Amazon Redshift Cluster.
In the tutorial, they utilize SQL Workbench/J client, but I'd like to utilize python (in particular SQLAlchemy). I've found a related question, but the issue is that it does not go into the detail or the python script that connects to the Redshift Cluster.
I've been able to connect to the cluster via SQL Workbench/J, since I have the JDBC URL, as well as my username and password, but I'm not sure how to connect with SQLAlchemy.
Based on this documentation, I've tried the following:
from sqlalchemy import create_engine
engine = create_engine('jdbc:redshift://shippy.cx6x1vnxlk55.us-west-2.redshift.amazonaws.com:5439/shippy')
ERROR:
Could not parse rfc1738 URL from string 'jdbc:redshift://shippy.cx6x1vnxlk55.us-west-2.redshift.amazonaws.com:5439/shippy'

I don't think SQL Alchemy "natively" knows about Redshift. You need to change the JDBC "URL" string to use postgres.
jdbc:postgres://shippy.cx6x1vnxlk55.us-west-2.redshift.amazonaws.com:5439/shippy
Alternatively, you may want to try using sqlalchemy-redshift using the instructions they provide.

I was running into the exact same issue, and then I remembered to include my Redshift credentials:
eng = create_engine('postgresql://[LOGIN]:[PASSWORD]#shippy.cx6x1vnxlk55.us-west-2.redshift.amazonaws.com:5439/shippy')

sqlalchemy-redshift is works for me, but after few days of reserch
packages (python3.4):
SQLAlchemy==1.0.14 sqlalchemy-redshift==0.5.0 psycopg2==2.6.2
First of all, I checked, that my query is working workbench (http://www.sql-workbench.net), then I force it work in sqlalchemy (this https://stackoverflow.com/a/33438115/2837890 helps to know that auto_commit or session.commit() must be):
db_credentials = (
'redshift+psycopg2://{p[redshift_user]}:{p[redshift_password]}#{p[redshift_host]}:{p[redshift_port]}/{p[redshift_database]}'
.format(p=config['Amazon_Redshift_parameters']))
engine = create_engine(db_credentials, connect_args={'sslmode': 'prefer'})
connection = engine.connect()
result = connection.execute(text(
"COPY assets FROM 's3://xx/xx/hello.csv' WITH CREDENTIALS "
"'aws_access_key_id=xxx_id;aws_secret_access_key=xxx'"
" FORMAT csv DELIMITER ',' IGNOREHEADER 1 ENCODING UTF8;").execution_options(autocommit=True))
result = connection.execute("select * from assets;")
print(result, type(result))
print(result.rowcount)
connection.close()
And after that, I forced to work sqlalchemy_redshift CopyCommand perhaps bad way, looks little tricky:
import sqlalchemy as sa
tbl2 = sa.Table(TableAssets, sa.MetaData())
copy = dialect_rs.CopyCommand(
assets,
data_location='s3://xx/xx/hello.csv',
access_key_id=access_key_id,
secret_access_key=secret_access_key,
truncate_columns=True,
delimiter=',',
format='CSV',
ignore_header=1,
# empty_as_null=True,
# blanks_as_null=True,
)
print(str(copy.compile(dialect=RedshiftDialect(), compile_kwargs={'literal_binds': True})))
print(dir(copy))
connection = engine.connect()
connection.execute(copy.execution_options(autocommit=True))
connection.close()
We make just that I made with sqlalchemy, excute query, except comine query by CopyCommand. I have not see some profit :(.

The following works for me with Databricks on all kinds of SQLs
import sqlalchemy as SA
import psycopg2
host = 'your_host_url'
username = 'your_user'
password = 'your_passw'
port = 5439
url = "{d}+{driver}://{u}:{p}#{h}:{port}/{db}".\
format(d="redshift",
driver='psycopg2',
u=username,
p=password,
h=host,
port=port,
db=db)
engine = SA.create_engine(url)
cnn = engine.connect()
strSQL = "your_SQL ..."
try:
cnn.execute(strSQL)
except:
raise

import sqlalchemy as db
engine = db.create_engine('postgres://username:password#url:5439/db_name')
This worked for me

How do I connect to SQL Server via sqlalchemy using Windows Authentication?

sqlalchemy, a db connection module for Python, uses SQL Authentication (database-defined user accounts) by default. If you want to use your Windows (domain or local) credentials to authenticate to the SQL Server, the connection string must be changed.
By default, as defined by sqlalchemy, the connection string to connect to the SQL Server is as follows:
sqlalchemy.create_engine('mssql://*username*:*password*#*server_name*/*database_name*')
This, if used using your Windows credentials, would throw an error similar to this:
sqlalchemy.exc.DBAPIError: (Error) ('28000', "[28000] [Microsoft][ODBC SQL Server Driver][SQL Server]Login failed for us
er '***S\\username'. (18456) (SQLDriverConnect); [28000] [Microsoft][ODBC SQL Server Driver][SQL Server]Login failed for us
er '***S\\username'. (18456)") None None
In this error message, the code 18456 identifies the error message thrown by the SQL Server itself. This error signifies that the credentials are incorrect.

In order to use Windows Authentication with sqlalchemy and mssql, the following connection string is required:
ODBC Driver:
engine = sqlalchemy.create_engine('mssql://*server_name*/*database_name*?trusted_connection=yes')
SQL Express Instance:
engine = sqlalchemy.create_engine('mssql://*server_name*\\SQLEXPRESS/*database_name*?trusted_connection=yes')

If you're using a trusted connection/AD and not using username/password, or otherwise see the following:
SAWarning: No driver name specified; this is expected by PyODBC when using >DSN-less connections
"No driver name specified; "
Then this method should work:
from sqlalchemy import create_engine
server = <your_server_name>
database = <your_database_name>
engine = create_engine('mssql+pyodbc://' + server + '/' + database + '?trusted_connection=yes&driver=ODBC+Driver+13+for+SQL+Server')

A more recent response if you want to connect to the MSSQL DB from a different user than the one you're logged with on Windows. It works as well if you are connecting from a Linux machine with FreeTDS installed.
The following worked for me from both Windows 10 and Ubuntu 18.04 using Python 3.6 & 3.7:
import getpass
from sqlalchemy import create_engine
password = getpass.getpass()
eng_str = fr'mssql+pymssql://{domain}\{username}:{password}#{hostip}/{db}'
engine = create_engine(eng_str)
What changed was to add the Windows domain before \username.
You'll need to install the pymssql package.

Create Your SqlAlchemy Connection URL      From Your pyodbc Connection String      OR Your Known Connection Parameters
I found all the other answers to be educational, and I found the SqlAlchemy Docs on connection strings helpful too, but I kept failing to connect to MS SQL Server Express 19 where I was using no username or password and trusted_connection='yes' (just doing development at this point).
Then I found THIS method in the SqlAlchemy Docs on Connection URLs built from a pyodbc connection string (or just a connection string), which is also built from known connection parameters (i.e. this can simply be thought of as a connection string that is not necessarily used in pyodbc). Since I knew my pyodbc connection string was working, this seemed like it would work for me, and it did!
This method takes the guesswork out of creating the correct format for what you feed to the SqlAlchemy create_engine method. If you know your connection parameters, you put those into a simple string per the documentation exemplified by the code below, and the create method in the URL class of the sqlalchemy.engine module does the correct formatting for you.
The example code below runs as is and assumes a database named master and an existing table named table_one with the schema shown below. Also, I am using pandas to import my table data. Otherwise, we'd want to use a context manager to manage connecting to the database and then closing the connection like HERE in the SqlAlchemy docs.
import pandas as pd
import sqlalchemy
from sqlalchemy.engine import URL
# table_one dictionary:
table_one = {'name': 'table_one',
'columns': ['ident int IDENTITY(1,1) PRIMARY KEY',
'value_1 int NOT NULL',
'value_2 int NOT NULL']}
# pyodbc stuff for MS SQL Server Express
driver='{SQL Server}'
server='localhost\SQLEXPRESS'
database='master'
trusted_connection='yes'
# pyodbc connection string
connection_string = f'DRIVER={driver};SERVER={server};'
connection_string += f'DATABASE={database};'
connection_string += f'TRUSTED_CONNECTION={trusted_connection}'
# create sqlalchemy engine connection URL
connection_url = URL.create(
"mssql+pyodbc", query={"odbc_connect": connection_string})
""" more code not shown that uses pyodbc without sqlalchemy """
engine = sqlalchemy.create_engine(connection_url)
d = {'value_1': [1, 2], 'value_2': [3, 4]}
df = pd.DataFrame(data=d)
df.to_sql('table_one', engine, if_exists="append", index=False)
Update
Let's say you've installed SQL Server Express on your linux machine. You can use the following commands to make sure you're using the correct strings for the following:
For the driver: odbcinst -q -d
For the server: sqlcmd -S localhost -U <username> -P <password> -Q 'select ##SERVERNAME'

pyodbc
I think that you need to put:
"+pyodbc" after mssql
try this:
from sqlalchemy import create_engine
engine = create_engine("mssql+pyodbc://user:password#host:port/databasename?driver=ODBC+Driver+17+for+SQL+Server")
cnxn = engine.connect()
It works for me
Luck!

If you are attempting to connect:
DNS-less
Windows Authentication for a server not locally hosted.
Without using ODBC connections.
Try the following:
import sqlalchemy
engine = sqlalchemy.create_engine('mssql+pyodbc://' + server + '/' + database + '?trusted_connection=yes&driver=SQL+Server')
This avoids using ODBC connections and thus avoids pyobdc interface errors from DPAPI2 vs DBAPI3 conflicts.
I would recommend using the URL creation tool instead of creating the url from scratch.
connection_url = sqlalchemy.engine.URL.create("mssql+pyodbc",database=databasename, host=servername, query = {'driver':'SQL Server'})
engine = sqlalchemy.create_engine(connection_url)
See this link for creating a connection string with SQL Server Authentication (non-domain, uses username and password)

How to create a new database using SQLAlchemy?

Using SQLAlchemy, an Engine object is created like this:
from sqlalchemy import create_engine
engine = create_engine("postgresql://localhost/mydb")
Accessing engine fails if the database specified in the argument to create_engine (in this case, mydb) does not exist. Is it possible to tell SQLAlchemy to create a new database if the specified database doesn't exist?

SQLAlchemy-Utils provides custom data types and various utility functions for SQLAlchemy. You can install the most recent official version using pip:
pip install sqlalchemy-utils
The database helpers include a create_database function:
from sqlalchemy import create_engine
from sqlalchemy_utils import database_exists, create_database
engine = create_engine("postgres://localhost/mydb")
if not database_exists(engine.url):
create_database(engine.url)
print(database_exists(engine.url))

On postgres, three databases are normally present by default. If you are able to connect as a superuser (eg, the postgres role), then you can connect to the postgres or template1 databases. The default pg_hba.conf permits only the unix user named postgres to use the postgres role, so the simplest thing is to just become that user. At any rate, create an engine as usual with a user that has the permissions to create a database:
>>> engine = sqlalchemy.create_engine("postgres://postgres#/postgres")
You cannot use engine.execute() however, because postgres does not allow you to create databases inside transactions, and sqlalchemy always tries to run queries in a transaction. To get around this, get the underlying connection from the engine:
>>> conn = engine.connect()
But the connection will still be inside a transaction, so you have to end the open transaction with a commit:
>>> conn.execute("commit")
And you can then proceed to create the database using the proper PostgreSQL command for it.
>>> conn.execute("create database test")
>>> conn.close()

It's possible to avoid manual transaction management while creating database by providing isolation_level='AUTOCOMMIT' to create_engine function:
import sqlalchemy
with sqlalchemy.create_engine(
'postgresql:///postgres',
isolation_level='AUTOCOMMIT'
).connect() as connection:
connection.execute('CREATE DATABASE my_database')
Also if you are not sure that database doesn't exist there is a way to ignore database creation error due to existence by suppressing sqlalchemy.exc.ProgrammingError exception:
import contextlib
import sqlalchemy.exc
with contextlib.suppress(sqlalchemy.exc.ProgrammingError):
# creating database as above

Extending the accepted answer using with yields:
from sqlalchemy import create_engine
engine = create_engine("postgresql://localhost")
NEW_DB_NAME = 'database_name'
with engine.connect() as conn:
conn.execute("commit")
# Do not substitute user-supplied database names here.
conn.execute(f"CREATE DATABASE {NEW_DB_NAME}")

Please note that I couldn't get the above suggestions with database_exists because whenever I check if the database exists using if not database_exists(engine.url): I get this error:
InterfaceError('(pyodbc.InterfaceError) (\'28000\', u\'[28000]
[Microsoft][SQL Server Native Client 11.0][SQL Server]Login failed for
user \\'myUser\\'. (18456) (SQLDriverConnect); [28000]
[Microsoft][SQL Server Native Client 11.0][SQL Server]Cannot open
database "MY_DATABASE" requested by the login. The login failed.
(4060); [28000] [Microsoft][SQL Server Native Client 11.0][SQL
Server]Login failed for user \\'myUser\\'. (18456); [28000]
[Microsoft][SQL Server Native Client 11.0][SQL Server]Cannot open
database "MY_DATABASE" requested by the login. The login failed.
(4060)\')',)
Also contextlib/suppress was not working and I'm not using postgres so I ended up doing this to ignore the exception if the database happens to already exist with SQL Server:
import logging
import sqlalchemy
logging.basicConfig(filename='app.log', format='%(asctime)s-%(levelname)s-%(message)s', level=logging.DEBUG)
engine = create_engine('mssql+pyodbc://myUser:mypwd#localhost:1234/MY_DATABASE?driver=SQL+Server+Native+Client+11.0?trusted_connection=yes', isolation_level = "AUTOCOMMIT")
try:
engine.execute('CREATE DATABASE ' + a_database_name)
except Exception as db_exc:
logging.exception("Exception creating database: " + str(db_exc))

If someone like me don't want to take whole sqlalchemy_utils to your project just for database creation, you can use script like this. I've come with it, based on SingleNegationElimination's answer. I'm using pydantic here (it's FastAPI project) and my imported settings for reference, but you can easily change this:
from sqlalchemy import create_engine
from sqlalchemy.exc import OperationalError
from pydantic import PostgresDsn
from src.conf import settings
def build_db_connection_url(custom_db: Optional[str] = None):
db_name = f"/{settings.POSTGRES_DB or ''}" if custom_db is None else "/" + custom_db
return PostgresDsn.build(
scheme='postgresql+psycopg2',
user=settings.POSTGRES_USER,
password=settings.POSTGRES_PASSWORD,
host=settings.POSTGRES_HOST,
path=db_name,
)
def create_database(db_name: str):
try:
eng = create_engine(build_db_connection_url(custom_db=db_name))
conn = eng.connect()
conn.close()
except OperationalError as exc:
if "does not exist" in exc.__str__():
eng = create_engine(build_db_connection_url(custom_db="postgres"))
conn = eng.connect()
conn.execute("commit")
conn.execute(f"create database {db_name}")
conn.close()
print(f"Database {db_name} created")
else:
raise exc
eng.dispose()
create_database("test_database")