Basic CRUD Operations Using cx_Oracle, Part 4: Update

In this post, we’re going to take a look at the U in CRUD: Update.  We use the cx_Oracle driver to update some data in the database tables, using the connection object created in the Initial Setup section of the first post in this series.

WARNING: PLEASE REVIEW ALL EXAMPLE CODE AND ONLY RUN IT IF YOU ARE SURE IT WILL NOT CAUSE ANY PROBLEMS WITH YOUR SYSTEM.

We will be using a helper function get_all_rows().  This function encapsulates a select statement used to verify that the updates worked. The select functionality is covered in the R part of this series, so we won’t go into the details here.

Sample :

def get_all_rows(label, data_type='people'):
  # Query all rows
  cur = con.cursor()
  if (data_type == 'pets'):
    statement = 'select id, name, owner, type from cx_pets order by owner, id'
  else:
    statement = 'select id, name, age, notes from cx_people order by id'
  cur.execute(statement)
  res = cur.fetchall()
  print(label + ': ')
  print (res)
  print(' ')
  cur.close()

Add this function to the top of your file.

Resetting the Data

To keep the examples clean and precise, we will reset the data at times.

Create a new file called reset_data.py with the following code and then run it whenever you would like to reset the data. (Notice this version adds pet data not included in other sections.)

import cx_Oracle
import os
connectString = os.getenv('db_connect')
con = cx_Oracle.connect(connectString)
cur = con.cursor()
# Delete rows
statement = 'delete from cx_pets'
cur.execute(statement)
# Reset Identity Coulmn
statement = 'alter table cx_pets modify id generated BY DEFAULT as identity (START WITH 8)'
cur.execute(statement)
# Delete rows
statement = 'delete from cx_people'
cur.execute(statement)
# Reset Identity Coulmn
statement = 'alter table cx_people modify id generated BY DEFAULT as identity (START WITH 3)'
cur.execute(statement)
# Insert default rows
rows = [(1, 'Bob', 35, 'I like dogs'), (2, 'Kim', 27, 'I like birds')]
cur.bindarraysize = 2
cur.setinputsizes(int, 20, int, 100)
cur.executemany("insert into cx_people(id, name, age, notes) values (:1, :2, :3, :4)", rows)
con.commit()
# Insert default rows
rows = [(1, 'Duke', 1, 'dog'),
        (2, 'Pepe', 2, 'bird'),
        (3, 'Princess', 1, 'snake'),
        (4, 'Polly', 1, 'bird'),
        (5, 'Rollo', 1, 'horse'),
        (6, 'Buster', 1, 'dog'),
        (7, 'Fido', 1, 'cat')]
cur.bindarraysize = 2
cur.setinputsizes(int, 20, int, 100)
cur.executemany("insert into cx_pets (id, name, owner, type) values (:1, :2, :3, :4)", rows)
con.commit()
cur.close()

Boilerplate Template

The template we will be using is:

import cx_Oracle
import os
connectString = os.getenv('db_connect')
con = cx_Oracle.connect(connectString)
def get_all_rows(label, data_type='people'):
  # Query all rows
  cur = con.cursor()
  if (data_type == 'pets'):
    statement = 'select id, name, owner, type from cx_pets order by owner, id'
  else:
    statement = 'select id, name, age, notes from cx_people order by id'
  cur.execute(statement)
  res = cur.fetchall()
  print(label + ': ')
  print (res)
  print(' ')
  cur.close()
get_all_rows('Original Data')
# Your code here
get_all_rows('New Data')

For each exercise, replace the “# Your code here” line with your code. 

Simple Update 

We will perform a simple update that modifies a single record in the cx_people table. These are the steps performed in the code snippet below. 

• Get a cursor object from our connection. We will use this cursor to perform our database operations. 
• Prepare a SQL UPDATE statement, changing age to 31 for the record with an id of 1. 
• Execute the statement using bind variables. (See the R part of this series for an explanation of bind variables.) 
• Commit the transaction.

cur = con.cursor()
statement = 'update cx_pets set owner = :1 where id = :2'
cur.execute(statement, (1, 6))
con.commit()
print('Number of rows updated: ' + str(cur.rowcount))
print(' ')

When I run this code in my Python session, I see:

Original Data:
[(3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'), (7, 'Fido', 1, 'cat'),
 (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird'), (6, 'Buster', 2, 'dog')]
Number of rows updated: 1
New Data:
[(3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'), (6, 'Buster', 1, 'dog'),
 (7, 'Fido', 1, 'cat'), (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird')]

Cursor.rowcount will show you the number of rows affected for insert, update and delete statements and the number of rows returned in a select statement. 

Extra Fun 1 

Update Bob’s notes to ‘I like cats’ . Your results should be:

Original Data:
[(1, 'Bob', 31, 'I like dogs'), (2, 'Kim', 27, 'I like birds')]
New Data:
[(1, 'Bob', 31, 'I like cats'), (2, 'Kim', 27, 'I like birds')]

Answer

cur = con.cursor()
statement = 'update cx_people set notes = :1 where id = :2'
cur.execute(statement, ("I like cats", 1))
con.commit()

Reset the data 

Now is a good time to run reset_data.py. 

Boilerplate Change 

Change the boilerplate get_all_rows statements to get pet data.

get_all_rows('Original Data', 'pets')
# Your code here
get_all_rows('New Data', 'pets')

Make Sure Your Where Clause is Specific 

In the above example, notice that we used the id column in our where clause. For our data set, id is the primary key. You do not always have to use a primary key, but you should make sure you only update the rows you intend to. 

Next, let’s look at updating multiple rows. We’ll have Bob give his dog Duke to Kim. 

• Get a cursor object from our connection. We will use this cursor to perform our database operations. 
• Prepare a SQL UPDATE statement, changing owner to 2 (Kim) for the records with an owner of 1 (Bob) and a type of ‘dog’. 
• Execute the statement using bind variables. (See the R part of this series for an explanation of bind variables.) 
• Commit the transaction.

cur = con.cursor()
statement = 'update cx_pets set owner = :1 where owner = :2 and type = :3'
cur.execute(statement, (2, 1, 'dog'))
con.commit()

When I run this code in my Python session, I see:

Original Data:
[(1, 'Duke', 1, 'dog'), (3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'),
 (6, 'Buster', 1, 'dog'), (7, 'Fido', 1, 'cat'), (2, 'Pepe', 2, 'bird')]
New Data:
[(3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'), (7, 'Fido', 1, 'cat'),
 (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird'), (6, 'Buster', 2, 'dog')]

In our example we only used owner and type; assuming that Bob only had one dog, Duke, as it is in our original data. With the new reset data function, we added a second dog, Buster. This example is intended to demonstrate what may happen when multiple users are working with the same data set. 

In our data, the only unique identifier for cx_pets is id. Bob may have two dogs, or even two dogs named Duke. Make sure if you intend to change a specific row you use a unique identifier. 

It also helps to… 

Verify the Number of Affected Rows 

Now let's give Buster back to Bob. This time, we will use the unique id column and we will print out the number of rows affected using Cursor.rowcount. 

• Get a cursor object from our connection. We will use this cursor to perform our database operations. 
• Prepare a SQL UPDATE statement, changing owner to 1 (Bob) for the records with an id of 6 (Buster). 
• Execute the statement using bind variables. (See the R part of this series for an explanation of bind variables.) 
• Commit the transaction.

cur = con.cursor()
statement = 'update cx_pets set owner = :1 where id = :2'
cur.execute(statement, (1, 6))
con.commit()
print('Number of rows updated: ' + str(cur.rowcount))
print(' ')

When I run this code in my Python session, I see:

Original Data:
[(3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'), (7, 'Fido', 1, 'cat'),
 (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird'), (6, 'Buster', 2, 'dog')]
Number of rows updated: 1
New Data:
[(3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'), (6, 'Buster', 1, 'dog'),
 (7, 'Fido', 1, 'cat'), (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird')]

Cursor.rowcount will show you the number of rows affected for insert, update and delete statements and the number of rows returned in a select statement. 

Extra Fun 2 

Give all birds to Kim that she doesn’t already have and print the number of affected rows . Your results should be:

Original Data:
[(3, 'Princess', 1, 'snake'), (4, 'Polly', 1, 'bird'), (5, 'Rollo', 1, 'horse'), (6, 'Buster', 1, 'dog'),
 (7, 'Fido', 1, 'cat'), (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird')]
Number of rows updated: 1
New Data:
[(3, 'Princess', 1, 'snake'), (5, 'Rollo', 1, 'horse'), (6, 'Buster', 1, 'dog'), (7, 'Fido', 1, 'cat'),
 (1, 'Duke', 2, 'dog'), (2, 'Pepe', 2, 'bird'), (4, 'Polly', 2, 'bird')]

Answer

cur = con.cursor()
statement = 'update cx_pets set owner = :1 where type = :2 and owner != :3'
cur.execute(statement, (2, 'bird', 2))
con.commit()
print('Number of rows updated: ' + str(cur.rowcount))
print(' ')

Some other things you could try 

• Change multiple column values. 
• Perform an update that changes all rows, if the row count is greater than 2, rollback the change.