This document provides an overview of connecting to PostgreSQL databases using Python, particularly through the psycopg2 adapter and pygresql module. It includes instructions on installation, creating connections, executing SQL commands, handling transactions, and using different types of cursors for data retrieval. The document also elaborates on various functionalities and methods available in the psycopg2 library for database interactions.

1. CONNECT TO POSTGRESQL
With python script

2.  psycopg is a PostgreSQL database adapter for
the Python_ programming language. This is
version 2, a complete rewrite of the original
code to provide new-style classes for
connection and cursor objects and other sweet
candies.
 Homepage:
http://initd.org/projects/psycopg2

3. PyGreSQL – PostgreSQL module for Python
PyGreSQL is an open-source Python module
that interfaces to a PostgreSQL database. It
embeds the PostgreSQL query library to allow
easy use of the powerful PostgreSQL features
from a Python script.

4. Python version 2.5 or 2.6 or 2.7
PostGreSQL 9.1 or higher

5. Linux
Look for a package such as python-psycopg2
sudo apt-get install python-psycopg2 - to install
the package with all its dependencies.
Windows
 http://www.stickpeople.com/projects/python/win-psycopg/
 http://initd.org/psycopg/

6.  Binary(...) Binary(buffer) -> new binary object
Build an object capable to hold a binary string value.
 Date(...) - Date(year, month, day) -> new date
Build an object holding a date value.
 Time(...) - Time(hour, minutes, seconds, tzinfo=None) –> new time
Build an object holding a time value.
 Timestamp(...) -
Timestamp(year, month, day, hour, minutes, seconds, tzinfo=None) -
> new timestamp
Build an object holding a timestamp value

7.  Create a new database connection and returns a new connection instance.

connect(dsn=None, database=None, user=None, password=None, host=No
ne, port=None, connection_factory=None, cursor_factory=None, async=Fal
se).
 Parameters:
 Using the *connection_factory* parameter a different class or connections
factory can be specified. It should be a callable object taking a dsn
argument.
 Using the *cursor_factory* parameter, a new default cursor factory will be
used by cursor().
 Using *async*=True an asynchronous connection will be created.

8.  It allows to:
 create new cursors using the cursor() method to execute
database commands and queries,
 commit() - The changes are committed to the database.
 rollback() In case of an error, we roll back any possible
changes to our database table.

9.  The class cursor allows interaction with the database:
 send commands to the database using methods such as execute() and
executemany(),
 retrieve data from the database by iteration or using methods such as
fetchone(), fetchmany(), fetchall().
 cur.description – to get metadata
 copy-to – to copy db tables to a file
 copy-from – to copy files to a db
 scrollable()
 mogrify()

10. import psycopg2
Connect to an existing database
 conn=psycopg2.connect("dbname=test user=postgres")
- as a libpq connection string
 conn=psycopg2.connect(database=“test” user=“postgres")
- as a set of keyword arguments
Open a cursor to perform database operations
cur = conn.cursor()

11.  Psycopg cursor usually fetches all the record from database
during a query, usually which is a large dataset to be handled
in the client side, hence to do controlled transfer of data to the
client,we use server side cursors.
 Psycopg wraps the database server side cursor in named
cursors. A named cursor is created using the cursor() method
specifying the name parameter.
 To move in the dataset we use scroll() method and scrollable()
method to move backward as well

12. Make the changes to the database persistent
conn.commit()
Close communication with the database
cur.close()
conn.close()

13. connect_test.py
check_version.py
Form.py

14. CRUD

15.  cur.execute("DROP TABLE IF EXISTS tablename")
 cur.execute("CREATE TABLE tablename (id serial
PRIMARY KEY, num integer, data varchar)“)
 cur.executemany() ???????
Create and drop table

16. cur.execute("SELECT * FROM tablename")
cur.execute("INSERT INTO tablename
(num, data) VALUES (%s, %s)", ...
(100, “apple"))
insert
insertmany

17. Obtain data as Python objects
cur.fetchone(),cur.fetchall(),cur.fetchmany(5)
fetchone
fetchall

18.  Always be a %s, even if a different placeholder (such as a %d for
integers or %f for floats) may look more appropriate:
cur.execute("INSERT INTO tablename VALUES (%d)", (42,)) # WRONG
cur.execute("INSERT INTO tablenameVALUES (%s)", (42,)) # correct
 Named arguments are supported too using %(name)s placeholders.
cur.execute( """INSERT INTO tablename (an_int, a_date,
another_date, a_string) VALUES (%(int)s, %(date)s, %(date)s,
%(str)s);""", {'int': 10, 'str': "O'Reilly", 'date': datetime.date(2005,
11, 18)})

19.  The Python string operator % is not used: the execute() method accepts a
tuple or dictionary of values as second parameter.
 For positional variables binding, the second argument must always be a
sequence, even if it contains a single variable:
 cur.execute("INSERT INTO foo VALUES (%s)", "bar") # WRONG
 cur.execute("INSERT INTO foo VALUES (%s)", ("bar")) # WRONG
 cur.execute("INSERT INTO foo VALUES (%s)", ("bar",)) # correct
 cur.execute("INSERT INTO foo VALUES (%s)", ["bar"]) # correct

20. Python PostgreSQL
None NULL
Bool Bool
Float Real,double
Int,long Smallint,integer,bigint
Decimal Numeric
Str Varchar
Date Date
Datetime Timestamp
List array
Many standard Python types are adapted into SQL and returned as Python objects
when a query is executed.
Psycopg casts Python variables to SQL literals by type.

21. cur.execute("UPDATE tablename SET
price=50000 WHERE id1")
update
delete

22. cur.execute("UPDATE tablename SET
price=%s WHERE id=%s", (60000, 1))
cur.execute("SELECT * FROM tablename
WHERE id=%(id)s", {'id': 4 } )

23. Python Filescopy_from_db.py
Python Filescopy_to_db.py

24. Matadata.py
Information on db

25. autocommit

26. Writing image to db
Reading image from db

27. Python Filesdictionary_cursor.py