Develop Reference

PyODBC: how to replicate behavior of batch separator (GO) in a transaction?

Background
I maintain a Python application that automatically applies SQL schema migrations (adding/removing tables and columns, adjusting the data, etc) to our database (SQL2016). Each migration is executed via PyODBC within a transaction so that it can be rolled back if something goes wrong. Sometimes a migration requires one or more batch statements (GO) to execute correctly. Since GO is not actually a T-SQL command but rather a special keyword in SSMS, I've been splitting each SQL migration on GO and executing each SQL fragment separately within the same transaction.
import pyodbc
import re
conn_args = {
'driver': '{ODBC Driver 17 for SQL Server}',
'hostname': 'MyServer',
'port': 1298,
'server': r'MyServer\MyInstance',
'database': 'MyDatabase',
'user': 'MyUser',
'password': '********',
'autocommit': False,
}
connection = pyodbc.connect(**conn_args)
cursor = connection.cursor()
sql = '''
ALTER TABLE MyTable ADD NewForeignKeyID INT NULL FOREIGN KEY REFERENCES MyParentTable(ID)
GO
UPDATE MyTable
SET NewForeignKeyID = 1
'''
sql_fragments = re.split(r'^\s*GO;?\s*$', sql, flags=re.IGNORECASE|re.MULTILINE)
for sql_frag in sql_fragments:
cursor.execute(sql_frag)
# Wait for the command to complete. This is necessary for some database system commands
# (backup, restore, etc). Probably not necessary for schema migrations, but included
# for completeness.
while cursor.nextset():
pass
connection.commit()
Problem
SQL statement batches aren't being executed like I expected. When the above schema migration is executed in SSMS, it succeeds. When executed in Python, the first batch (adding the foreign key) executes just fine, but the second batch (setting the foreign key value) fails because it isn't aware of the new foreign key.
('42S22', "[42S22] [FreeTDS][SQL Server]Invalid column name 'NewForeignKeyID'. (207) (SQLExecDirectW)")
Goal
Execute a hierarchy of SQL statement batches (i.e. where each statement batch depends upon the previous batch) within a single transaction in PyODBC.
What I've Tried
Searching the PyODBC documentation for information on how PyODBC supports or doesn't support batch statements / the GO command. No references found.
Searching StackOverflow & Google for how to batch statements within PyODBC.
Introducing a small sleep between SQL fragment executions just in case there's some sort of race condition. Seemed unlikely to be a solution, and didn't change the behavior.
I've considered separating each batch of statements out into a separate transaction that is committed before the next batch is executed, but that would reduce/eliminate our ability to automatically roll back a schema migration that fails.
EDIT: I just found this question, which is pretty much exactly what I want to do. However, upon testing (in SSMS) the answer that recommends using EXEC I discovered that the second EXEC command (setting the value) fails because it isn't aware of the new foreign key. I'm bad at testing and it actually does succeed. This solution might work but isn't ideal since EXEC isn't compatible with parameters. Also, this won't work if variables are used across fragments.
BEGIN TRAN
EXEC('ALTER TABLE MyTable ADD NewForeignKeyID INT NULL FOREIGN KEY REFERENCES MyParentTable(ID)')
EXEC('UPDATE MyTable SET NewForeignKeyID = 1')
ROLLBACK TRAN
Invalid column name 'FK_TestID'.

If you are reading the SQL statements from a text file (such as one produced by scripting objects in SSMS) then you could just use Python's subprocess module to run the sqlcmd utility with that file as the input (-i). In its simplest form that would look like
server = "localhost"
port = 49242
uid = "scott"
pwd = "tiger^5HHH"
database = "myDb"
script_file = r"C:\__tmp\batch_test.sql"
"""contents of the above file:
DROP TABLE IF EXISTS so69020084;
CREATE TABLE so69020084 (src varchar(10), var_value varchar(10));
INSERT INTO so69020084 (src, var_value) VALUES ('1st batch', 'foo');
GO
INSERT INTO so69020084 (src, var_value) VALUES ('2nd batch', 'bar');
GO
"""
import subprocess
cmd = [
"sqlcmd",
"-S", f"{server},{port}",
"-U", uid,
"-P", pwd,
"-d", database,
"-i", script_file,
]
subprocess.run(cmd)

why the stored procedure called from sqlalchemy is not working but calling from workbench is working?

I have a stored procedure.
calling it via MySQL workbench as follows working;
CALL `lobdcapi`.`escalatelobalarm`('A0001');
But not from the python program. (means it is not throwing any exception, process finish execution silently) if I make any error in column names, then at python I get an error. So it calls my stored procedure but not working as expected. (it is an update query .it needs SAFE update )
Why through the python sqlalchemy this update didn't update any records?
CREATE DEFINER=`lob`#`%` PROCEDURE `escalatelobalarm`(IN client_id varchar(50))
BEGIN
SET SQL_SAFE_UPDATES = 0;
update lobdcapi.alarms
set lobalarmescalated=1
where id in (
SELECT al.id
from (select id,alarmoccurredhistoryid from lobdcapi.alarms where lobalarmpriorityid=1 and lobalarmescalated=0 and clientid=client_id
and alarmstatenumber='02' ) as al
inner join lobdcapi.`alarmhistory` as hi on hi.id=al.alarmoccurredhistoryid
and hi.datetimestamp<= current_timestamp() )
);
SET SQL_SAFE_UPDATES = 1;
END
I call it like;
from sqlalchemy import and_, func,text
db.session.execute(text("CALL escalatelobalarm(:param)"), {'param': clientid})
I suspect the param I pass via code didn't get bind properly?

I haven't called stored procs from SQLAlchemy, but it seems possible that this could be within a transaction because you're using the session. Perhaps calling db.session.commit() at the end would help?
If that fails, SQLAlchemy calls out calling stored procs here. Perhaps try their method of using callproc. Adapting to your use-case, something like:
connection = db.session.connection()
try:
cursor = connection.cursor()
cursor.callproc("escalatelobalarm", [clientid])
results = list(cursor.fetchall())
cursor.close()
connection.commit()
finally:
connection.close()

Python Pycharm and SQL Server connection

I would like to use data from SQL server in Pycharm using python. I have my database connection set up in Pycharm, but not sure how to access this data within my python code. I would like to query the data within the python code (similar to what I would do in R using the RODBC package).
Any suggestions on what to do or where to look would be much appreciated.

I have been having issues with this over learning this the last few days. (database / python) For me I am working in flask but it doesn't really seem to matter.
I did get this to work though not exactly what you ask but might get you a start
import MySQLdb
def database():
db = MySQLdb.connect(host="localhost", port=3306, user="root", passwd="admin", db="echo")
cursor = db.cursor()
cursor.execute( "INSERT INTO `post` (`hello`) VALUES (null), ('hello_world')" )
db.commit()
db.close()
I had to just set up my database from the command line. Its not pretty or intuitive but should get you started.

If you want to work with Python objects rather than SQL, I'd use SqlAlchemy and reflection.
from sqlalchemy import MetaData, create_engine
from sqlalchemy.orm import Session
from sqlalchemy.ext.automap import automap_base
engine = create_engine('mysql+mysqldb://...', pool_recycle=3600)
metadata = MetaData()
metadata.reflect(bind=engine)
session = Session(engine)
Base = automap_base(metadata=metadata)
Base.prepare()
# assuming I have a table named 'users'
Users = Base.classes.users
someUsers = Users.query.filter(Users.name.in_(['Jack', 'Bob', 'YakMan')).all()

import mysql.connector
connection=mysql.connector.connect(user='root', password='daniela', host='localhost', database='girrafe')
mycursor=connection.cursor()

There is a concept called OR(Object Relational) Mapping in python, which can be used for database connections. One of the modules that you need to import for the purpose is SQLAlchemy.
First, you will need to install sqlalchemy by:
pip install sqlalchemy
Now, for database connection, we have an Engine class in the sqlalchemy, which is responsible for the database connectivity. We create an object of the Engine class for establishing connection.
from sqlalchemy import create_engine,MetaData,select
engine=create_engine("mysql://user:pwd#localhost/dbname", echo=True)
connection=engine.connect()
The process of reading the database and creating metadata is called Reflection.
metadata=MetaData()
query=select([Student]) #Assuming that my database already has a table named Student
result=connection.execute(query)
row=result.fetchall() #This works similar to the select* query
In this way, you can manipulate data through other queries too, using sqlalchemy!

stored proc not committing with sqlalchemy/pyodbc

I am using sqlalchemy/pyodbc to connect to a MS SQL 2012 server. I chose sqlalchemy because of the direct integration with pandas dataframes using .read_sql and .to_sql.
At a high level, my code is:
df = dataframe.read_sql("EXEC sp_getsomedata")
<do some stuff here>
finaldf.to_sql("loader_table", engine,...)
This part works great, very easy to read, etc. The problem is that I have to run a final stored proc to insert the data from the loader table into the live table. Normally, sqlalchemy knows to commit after INSERT/UPDATE/DELETE, but doesn't want to do the commit for me when I run this final stored proc.
After having tried multiple approaches, I see the transaction in the db sitting uncommitted. I know sqlalchemy is very flexible and I am using about 3% of its functionality, what is the simplest way to get this working? I think I need to be using sqlalchemy core and not ORM. I saw examples using sessionmaker, but I think that monopolizes the engine object and doesn't let pandas access it.
connection = engine.connect()
transaction = connection.begin()
connection.execute("EXEC sp_doLoaderStuff")
transaction.commit()
connection.close()
I have tried calling .execute from the connection level, from a cursor level, and even using the .raw_connection() method without success.
connection = engine.raw_connection()
connection.autocommit = True
cursor = connection.cursor()
cursor.execute("EXEC sp_doLoaderStuff")
connection.commit()
connection.close()
Any ideas what I am missing here?

Completely self-inflicted. The correct working code using the raw_connection() method that is working fine is:
connection = engine.raw_connection()
cursor = connection.cursor()
cursor.execute("EXEC sp_doLoaderStuff")
connection.commit()
connection.close()

Accessing test PostgreSQL database from python

I can't seem to correctly connect and pull from a test postgreSQL database in python. I installed PostgreSQL using Homebrew. Here's how I have been accessing the database table and value from the terminal:
xxx-macbook:~ xxx$ psql
psql (9.4.0)
Type "help" for help.
xxx=# \dn
List of schemas
Name | Owner
--------+---------
public | xxx
(1 row)
xxx=# \connect postgres
You are now connected to database "postgres" as user "xxx".
postgres=# SELECT * from test.test;
coltest
-----------
It works!
(1 row)
But when trying to access it from python, using the code below, it doesn't work. Any suggestions?
########################################################################################
# Importing variables from PostgreSQL database via SQL commands
db_conn = psycopg2.connect(database='postgres',
user='xxx')
cursor = db_conn.cursor()
#querying the database
result = cursor.execute("""
Select * From test.test
""")
print "Result: ", result
>>> Result: None
It should say: Result: It works!

You need to fetch the results.
From the docs:
The [execute()-]method returns None. If a query was executed, the returned values can be retrieved using fetch*() methods.
Example:
result = cursor.fetchall()
For reference:
http://initd.org/psycopg/docs/cursor.html#execute
http://initd.org/psycopg/docs/cursor.html#fetch
Note that (unlike psql) psycopg2 wraps anything in transactions. So if you intend to issue persistent changes to the database (INSERT, UPDATE, DELETE, ...) you need to commit them explicitly. Otherwise changes will be rolled back automatically when the connection object is destroyed. Read more on that topic here:
http://initd.org/psycopg/docs/usage.html
http://initd.org/psycopg/docs/usage.html#transactions-control