Feb 13, 2018 6:06:00 AM by Brendan Tierney
Is Python the new R?
Maybe, maybe not, but that I'm finding in recent months is more companies are asking me to use Python instead of R for some of my work.
In this blog post I will walk through the steps of setting up the Oracle driver for Python, called cx_Oracle. The documentation for this drive is good and detailed with plenty of examples available on GitHub. Hopefully there isn't anything new in this post, but it is my experiences and what I did.
The Python driver requires Oracle Client software to be installed. Go here, download and install. It's a straightforward install. Make sure the directories are added to the search path.
You can use pip3 to do this.
pip3 install cx_Oracle
Downloading cx_Oracle-6.1.tar.gz (232kB)
100% |████████████████████████████████| 235kB 679kB/s
Building wheels for collected packages: cx-Oracle
Running setup.py bdist_wheel for cx-Oracle ... done
Stored in directory: /Users/brendan.tierney/Library/Caches/pip/wheels/0d/c4/b5/5a4d976432f3b045c3f019cbf6b5ba202b1cc4a36406c6c453
Successfully built cx-Oracle
Installing collected packages: cx-Oracle
Successfully installed cx-Oracle-6.1
Now we can create a connection. When you see some text enclosed in angled brackets <>, you will need to enter your detailed for your schema and database server.
# import the Oracle Python library
# define the login details
p_username = ""
p_password = ""
p_host = ""
p_service = ""
p_port = "1521"
# create the connection
con = cx_Oracle.connect(user=p_username, password=p_password, dsn=p_host+"/"+p_service+":"+p_port)
# an alternative way to create the connection
# con = cx_Oracle.connect('/@/:1521')
# print some details about the connection and the library
print("Database version:", con.version)
print("Oracle Python version:", cx_Oracle.version)
Database version: 22.214.171.124.0
Oracle Python version: 6.1
In this example the query returns the list of tables in the schema.
# define a cursor to use with the connection
cur = con.cursor()
# execute a query returning the results to the cursor
cur.execute('select table_name from user_tables')
# for each row returned to the cursor, print the record
for row in cur:
print("Table: ", row)
Now list the Views available in the schema.
# define a second cursor
cur2 = con.cursor()
# return the list of Views in the schema to the cursor
cur2.execute('select view_name from user_views')
# display the list of Views
for result_name in cur2:
print("View: ", result_name)
Pandas are commonly used for storing, structuring and processing data in Python, using a data frame format. The following returns the results from a query and stores the results in a panda.
# in this example the results of a query are loaded into a Panda
# load the pandas library
import pandas as pd
# execute the query and return results into the panda called df
df = pd.read_sql_query("SELECT * from INSUR_CUST_LTV_SAMPLE", con)
# print the records returned by query and stored in panda
CUSTOMER_ID LAST FIRST STATE REGION SEX PROFESSION
0 CU13388 LEIF ARNOLD MI Midwest M PROF-2
1 CU13386 ALVA VERNON OK Midwest M PROF-18
2 CU6607 HECTOR SUMMERS MI Midwest M Veterinarian
3 CU7331 PATRICK GARRETT CA West M PROF-46
4 CU2624 CAITLYN LOVE NY NorthEast F Clerical
BUY_INSURANCE AGE HAS_CHILDREN ... MONTHLY_CHECKS_WRITTEN
0 No 70 0 ... 0
1 No 24 0 ... 9
2 No 30 1 ... 2
3 No 43 0 ... 4
4 No 27 1 ... 4
MORTGAGE_AMOUNT N_TRANS_ATM N_MORTGAGES N_TRANS_TELLER
0 0 3 0 0
1 3000 4 1 1
2 980 4 1 3
3 0 2 0 1
4 5000 4 1 2
CREDIT_CARD_LIMITS N_TRANS_KIOSK N_TRANS_WEB_BANK LTV LTV_BIN
0 2500 1 0 17621.00 MEDIUM
1 2500 1 450 22183.00 HIGH
2 500 1 250 18805.25 MEDIUM
3 800 1 0 22574.75 HIGH
4 3000 2 1500 17217.25 MEDIUM
[5 rows x 31 columns]
Finally we need to wrap thing up and close our cursors and our connection to the database.
# close the cursors
# close the connection to the database
Watch out for more blog posts on using Python with Oracle, Oracle Data Mining and Oracle R Enterprise.
Written by Brendan Tierney
Brendan Tierney, Oracle ACE Director, is an independent consultant and lectures on Data Mining and Advanced Databases in the Dublin Institute of Technology in Ireland. He has 22+ years of extensive experience working in the areas of Data Mining, Data Warehousing, Data Architecture and Database Design. Brendan has worked on projects in Ireland, UK, Belgium and USA. Brendan is the editor of the UKOUG Oracle Scene magazine and deputy chair of the OUG Ireland BI SIG. Brendan is a regular speaker at conferences across Europe and the USA and has written technical articles for OTN, Oracle Scene, IOUG SELECT Journal and ODTUG Technical Journal.
Brendan has published the following books with Oracle Press book