This presentation covers the basic idea of connecting postgresql database with python and psycopg2 module. Covered Topics: 1. Psycopg2 Installation 2. Connecting to PostgreSQL Database 3. Connection Parameters 4. Create and Drop Table 5. Adaptation of Python Values to SQL Types 6. SQL Transactions 7. DML

1. A presentation on
psycopg2 python
module
by Dinesh Neupane [@neupanedinesh_] | Kathmandu
University

2. Psycopg2
A python driver for PostGreSQL
PostgreSQL
Python
Script

3. Background
 PostGreSQL database adapter for Python
Programming language
 Version 2 : original code completely rewritten for
better styling of classes for connection and cursor
 Postgres is type sensitive so we have to declare
types on each of our columns.
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4. Background
● Robust engine that is implemented as a server
rather than a single file. As a server, Postgres
accepts connections from clients who can request a
SELECT, INSERT, or any other type of SQL query.
● This type of a design is called a client-server model,
where clients can interact with the server.
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5. Requirements
 PostGreSQL 9.3 or higher
 Python 2.0 or higher
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6. Installation
● Install python package installer (pip)
● For windows machine (to install package with all it’s
dependencies)
pip install psycopg2
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7. Classes and Methods
● Connect()
Create a new database connection and returns a new
connection instance
connect("dbname=‘test_database’user=‘postgres'host='localhost'
password=‘italy'")
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8. Connection Parameters
The basic connection parameters are:
● dbname – the database name (database is a
deprecated alias) user – user name used to
authenticate
● password – password used to authenticate
● host – database host address
● port – connection port number
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9. Connection Example
Example:
import psycopg2
try:
conn = psycopg2.connect("dbname='test_database'
user='postgres' host='localhost' password='italy’”)
print "Connection Sucessful !! "
except:
print "unable to connect to the database"
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10. Cursor()
Cursors are created by the connection.cursor()
method: they are bound to the connection for the
entire lifetime and all the commands are executed in
the context of the database session wrapped by the
connection.
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11. Cursor()
The class cursor allows interaction with the database:
● Send commands to the database using using
methods like execute() and executemany()
● Retrieve data from the database by iteration or
using methods such as fetchone(), fetchmany() or
fetchall()
● cursor.description to get the metadata
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12. Cursor()
● mogrify() - Return a query string after arguments
binding. The string returned is exactly the one that
would be sent to the database running the execute()
method or similar. Example:
>>> cur.mogrify("INSERT INTO table_one VALUES(6, 'Sarad
Chaudhary', 'Banke Nepalgunj’)”)
"INSERT INTO table_one VALUES(6, 'Sarad Chaudhary', 'Banke
Nepalgunj’)”
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13. Create and Drop table
CREATE TABLE student (
student_id INTEGER UNIQUE,
student_name VARCHAR(50),
phone CHAR(10),
birth_date DATE,
);
This creates a new table costumers with different
attribute fields.
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14. Adaptation of Python Values to
SQL Types
Python PostgreSQL
None Null
Bool Bool
Float Real, Double
Int, Long Smallint, integer, bigint
Decimal Numeric
Str Varchar
List Array
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15. Closing a database session
Make the changes to the database persistent
● Conn.commit()
Close the communication with database
● Cur.close()
● Conn.close()
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16. Create and Drop table
The student table is created in the database that you
are connected to. [first schema in search path]
If you want the table to be created in some other
schema, you can prefix the table name with the
schema qualifier, for example:
CREATE TABLE another_schema.student( ... );
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17. Create and Drop table
Dropping a table is much easier than creating a table.
The syntax for the DROP TABLE command is:
DROP TABLE student;
The rentals table existed in some schema other than your current
schema, you would qualify the table name:
DROP TABLE other_schema.student;
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18. SQL Transactions
● If you check the postgres
database now you would
notice that there actually
isn't a users table inside it.
● This isn't a bug – it's
because of a concept
called SQL transactions.
16import psycopg2
conn=psycopg2.connect("host=loca
lhost dbname=postgres
user=postgres") cur =
conn.cursor()
cur.execute(""“
CREATE TABLE users(
id integer PRIMARY KEY,
email text,
name text,
address text )
""")

19. SQL Transactions
● With Postgres, we're dealing
with multiple users who could
be changing the database at
the same time.
● Let's imagine a simple
scenario where we're keeping
track of accounts for different
customers of a bank.
17import psycopg2
conn=psycopg2.connect("host=loca
lhost dbname=postgres
user=postgres") cur =
conn.cursor()
cur.execute("""
CREATE TABLE accounts(
id integer PRIMARY KEY,
name text,
balance float )
""")

20. SQL Transactions
● Our table looks like this:
● Let’s say Madhav gave 100 rupees to Sanjib. We could model this with
two queries:
UPDATE accounts SET balance=200 WHERE name=“Sanjib";
UPDATE accounts SET balance=100 WHERE name=“Madhav";
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id name balance
1 Sanjib 100
2 Madhav 200

21. SQL Transactions
● We remove 100 rupees from Madhav, and add 100 rupees to Sanjib.
What if the second UPDATE statement has an error in it, the database
fails, or another user has a conflicting query?
● The first query would run properly, but the second would fail. That
would result in the following:
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id name balance
1 Sanjib 200
2 Madhav 200

22. SQL Transactions
● Sanjib would be credited 100 rupees, but 100 rupees would not be
deducted from Madhav. This would cause the bank to lose money.
● Transactions prevent this type of behaviour by ensuring that all the
queries in a transaction block are executed at the same time. If any of
the transactions fail, the whole group fails, and no changes are made
to the database at all.
● When commit() is called, the PostgreSQL engine will run all the
queries at once.
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23. DML: Insert
● Pass data to fill a query placeholders and let
Psycopg perform the correct conversion
● No more SQL injections!
>> "INSERT INTO table_one VALUES(6, 'Sarad Chaudhary', 'Banke
Nepalgunj’)”
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24. DML: Insert
Example:
cur = conn.cursor()
insert_query="INSERT INTO table_one VALUES(6, 'Sarad
Chaudhary', 'Banke Nepalgunj’)”
cur.execute(insert_query)
conn.commit()
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25. DML: Insert (copy_from() method)
● Method to load a file like .csv into the table of running
database
● Like the execute() method, it is attached to the Cursor object
but it contains different parameters.
● Arguments:
copy_from(f, ‘table_name’, sep=‘,’)
f=file to load(without header), table_name=table name, it should
load into, sep=delimeter
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26. copy_from() method
Example:
import psycopg2
conn = psycopg2.connect("dbname='test_database' user='postgres'
host='localhost' password='italy’”)
cur = conn.cursor()
with open('name_list.csv', 'r') as f:
# no need to any other module to load csv
next(f)
# Skip the header row
cur.copy_from(f, 'table_one', sep=',’)
conn.commit()
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27. DML: Delete
If you want to pass values to the DELETE statement, you use the
placeholders ( %s) in the DELETE statement and pass input
values to the second parameter of the execute() method.
The DELETE statement with a placeholder for the value of the id
field is as follows:
DELETE FROM test_table WHERE id = %s;
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28. DML: Update
Execute the UPDATE statement with the input values
by calling the execute() method of the cursor object.
cur.execute(update_sql, (value1,value2))
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29. Thank You