4. SQL Relational Database Access
SELECT * FROM ip2country;
"ipfrom";"ipto";"registry";"assigned";"countrycode2";"countrycode3";"countryname"
1729522688;1729523711;"apnic";"2011-08-05";"CN";"CHN";"China"
1729523712;1729524735;"apnic";"2011-08-05";"CN";"CHN";"China”
...
SELECT * FROM ip2country
WHERE date_part('year', assigned) = 2012
AND countrycode2 = 'SG';
"ipfrom";"ipto";"registry";"assigned";"countrycode2";"countrycode3";"countryname"
1729580032;1729581055;"apnic";"2012-01-16";"SG";"SGP";"Singapore"
1729941504;1729942527;"apnic";"2012-01-10";"SG";"SGP";"Singapore”
...
SELECT ipfrom FROM ip2country
WHERE date_part('year', assigned) = 2012
AND countrycode2 = 'SG';
"ipfrom"
1729580032
1729941504
...
5. Python + SQL == Python DB-API 2.0
• The Python standard for a consistent
interface to relational databases is the
Python DB-API (PEP 249)
• The majority of Python database interfaces
adhere to this standard
7. Python DB-API Connection Object
Access the database via the connection object
• Use connect constructor to create a
connection with database
conn = psycopg2.connect(parameters…)
• Create cursor via the connection
cur = conn.cursor()
• Transaction management (implicit begin)
conn.commit()
conn.rollback()
• Close connection (will rollback current
transaction)
conn.close()
• Check module capabilities by globals
psycopg2.apilevel psycopg2.threadsafety psycopg2.paramstyle
8. Python DB-API Cursor Object
A cursor object is used to represent a database
cursor, which is used to manage the context of
fetch operations.
• Cursors created from the same connection
are not isolated
cur = conn.cursor()
cur2 = conn.cursor()
• Cursor methods
cur.execute(operation, parameters)
cur.executemany(op,seq_of_parameters)
cur.fetchone()
cur.fetchmany([size=cursor.arraysize])
cur.fetchall()
cur.close()
9. Python DB-API Cursor Object
• Optional cursor methods
cur.scroll(value[,mode='relative']) cur.next()
cur.callproc(procname[,parameters])
cur.__iter__()
• Results of an operation
cur.description
cur.rowcount
cur.lastrowid
• DB adaptor specific “proprietary” cursor
methods
10. Python DB-API Parameter Styles
Allows you to keep SQL separate from parameters
Improves performance & security
Warning Never, never, NEVER use Python string
concatenation (+) or string parameters
interpolation (%) to pass variables to a SQL query
string. Not even at gunpoint.
From http://initd.org/psycopg/docs/usage.html#query-parameters
11. Python DB-API Parameter Styles
Global paramstyle gives supported style for the
adaptor
qmark Question mark style
WHERE countrycode2 = ?
numeric Numeric positional style
WHERE countrycode2 = :1
named Named style
WHERE countrycode2 = :code
format ANSI C printf format style
WHERE countrycode2 = %s
pyformat Python format style
WHERE countrycode2 = %(name)s
12. Python + SQL: INSERT
import csv, datetime, psycopg2
conn = psycopg2.connect("dbname=ip2country user=ip2country_rw password=secret”)
cur = conn.cursor()
with open("IpToCountry.csv", "rb") as f:
reader = csv.reader(f)
try:
for row in reader:
print row
if row[0][0] != "#":
row[3] = datetime.datetime.utcfromtimestamp(float(row[3]))
cur.execute("""INSERT INTO ip2country(
ipfrom, ipto, registry, assigned,
countrycode2, countrycode3, countryname)
VALUES (%s, %s, %s, %s, %s, %s, %s)""", row)
except:
conn.rollback()
else:
conn.commit()
finally:
cur.close()
conn.close()
13. Python + SQL: SELECT
# Find ipv4 address ranges assigned to Singapore
import psycopg2, socket, struct
def num_to_dotted_quad(n):
"""convert long int to dotted quad string
http://code.activestate.com/recipes/66517/"""
return socket.inet_ntoa(struct.pack('!L',n))
conn = psycopg2.connect("dbname=ip2country user=ip2country_rw password=secret")
cur = conn.cursor()
cur.execute("""SELECT * FROM ip2country
WHERE countrycode2 = 'SG'
ORDER BY ipfrom""")
for row in cur:
print "%s - %s" % (num_to_dotted_quad(int(row[0])),
num_to_dotted_quad(int(row[1])))
14. SQLite
• sqlite3
• CPython 2.5 & 3
• DB-API 2.0
• Part of CPython distribution since 2.5
15. PostgreSQL
• psycopg
• CPython 2 & 3
• DB-API 2.0, level 2 thread safe
• Appears to be most popular
• http://initd.org/psycopg/
• py-postgresql
• CPython 3
• DB-API 2.0
• Written in Python with optional C
optimizations
• pg_python - console
• http://python.projects.postgresql.org/
20. ODBC
• mxODBC
• CPython 2.3+
• DB-API 2.0 interfaces
• http://www.egenix.com/products/pytho
n/mxODBC/doc
• Commercial product
• PyODBC
• CPython 2 & 3
• DB-API 2.0 interfaces with extensions
• http://code.google.com/p/pyodbc/
• ODBC interfaces not limited to Windows
thanks to iODBC and unixODBC
21. Jython + SQL
• zxJDBC
• DB-API 2.0 Written in Java using JDBC API
so can utilize JDBC drivers
• Support for connection pools and JNDI
lookup
• Included with standard Jython
installation http://www.jython.org/
• jyjdbc
• DB-API 2.0 compliant
• Written in Python/Jython so can utilize
JDBC drivers
• Decimal data type support
• http://code.google.com/p/jyjdbc/
22. IronPython + SQL
• adodbapi
• IronPython 2+
• Also works with CPython 2.3+ with
pywin32
• http://adodbapi.sourceforge.net/
23. Gerald, the half a schema
• Database schema toolkit
• via DB-API currently supports
• PostgreSQL
• MySQL
• Oracle
• http://halfcooked.com/code/gerald/
import gerald
s1 = gerald.PostgresSchema(’public',
'postgres://ip2country_rw:secret@localhost/ip2country')
s2 = gerald.PostgresSchema(’public',
'postgres://ip2country_rw:secret@localhost/ip2countryv4')
print s1.schema['ip2country'].compare(s2.schema['ip2country'])
DIFF: Definition of assigned is different
DIFF: Column countryname not in ip2country
DIFF: Definition of registry is different
DIFF: Column countrycode3 not in ip2country
DIFF: Definition of countrycode2 is different
24. SQLPython
• A command-line interface to relational
databases
• via DB-API currently supports
• PostgreSQL
• MySQL
• Oracle
• http://packages.python.org/sqlpython/
$ sqlpython --postgresql ip2country ip2country_rw
Password:
0:ip2country_rw@ip2country> select * from ip2country where countrycode2='SG';
...
1728830464.0 1728830719.0 apnic 2011-11-02 SG SGP Singapore
551 rows selected.
0:ip2country_rw@ip2country> select * from ip2country where countrycode2='SG'j
[...
{"ipfrom": 1728830464.0, "ipto": 1728830719.0, "registry": "apnic”,"assigned": "2011-11-02",
"countrycode2": "SG", "countrycode3": "SGP", "countryname": "Singapore"}]
25. SQLPython, batteries included
0:ip2country_rw@ip2country> select * from ip2country where countrycode2 ='SG’;
...
1728830464.0 1728830719.0 apnic 2011-11-02 SG SGP Singapore
551 rows selected.
0:ip2country_rw@ip2country> py
Python 2.6.6 (r266:84292, May 20 2011, 16:42:25)
[GCC 4.4.5 20110214 (Red Hat 4.4.5-6)] on linux2
py <command>: Executes a Python command.
py: Enters interactive Python mode.
End with `Ctrl-D` (Unix) / `Ctrl-Z` (Windows), `quit()`, 'exit()`.
Past SELECT results are exposed as list `r`;
most recent resultset is `r[-1]`.
SQL bind, substitution variables are exposed as `binds`, `substs`.
Run python code from external files with ``run("filename.py")``
>>> r[-1][-1]
(1728830464.0, 1728830719.0, 'apnic', datetime.date(2011, 11, 2), 'SG', 'SGP', 'Singapore')
>>> import socket, struct
>>> def num_to_dotted_quad(n):
... return socket.inet_ntoa(struct.pack('!L',n))
...
>>> num_to_dotted_quad(int(r[-1][-1].ipfrom))
'103.11.220.0'
26. SpringPython – Database Templates
# Find ipv4 address ranges assigned to Singapore
# using SpringPython DatabaseTemplate & DictionaryRowMapper
from springpython.database.core import *
from springpython.database.factory import *
conn_factory = PgdbConnectionFactory(
user="ip2country_rw", password="secret",
host="localhost", database="ip2country")
dt = DatabaseTemplate(conn_factory)
results = dt.query(
"SELECT * FROM ip2country WHERE countrycode2=%s",
("SG",), DictionaryRowMapper())
for row in results:
print "%s - %s" % (num_to_dotted_quad(int(row['ipfrom'])),
num_to_dotted_quad(int(row['ipto'])))
27. Attributions
DB-API 2.0 PEP
http://www.python.org/dev/peps/pep-0249/
Travis Spencer‟s DB-API UML Diagram
http://travisspencer.com/
Andrew Kuchling's introduction to the DB-API
http://www.amk.ca/python/writing/DB-API.html
28. Attributions
Andy Todd‟s OSDC paper
http://halfcooked.com/presentations/osdc2006/p
ython_databases.html
Source of csv data used in examples from
WebNet77 licensed under GPLv3
http://software77.net/geo-ip/
29. Contact Details
Mark Rees
mark at centurysoftware dot com dot my
+Mark Rees
@hexdump42
hex-dump.blogspot.com
Notas del editor
For some Python programmers, their only exposure to accessing relational data is via a object relational mapper (ORM). As powerful is the concept of mapping objects to data, sometimes it is much simpler to manipulate your relational data using SQL. This talk will be about using the DB-API, Python’s standard mechanism for accessing relational databases.
Or maybe you prefer sqlalchemy to abstract away the database. This talk will be about using the DB-API, Python’s standard mechanism for accessing relational databases.
SQL (Structured Query Language) is a DSL and we can achieve the same results as the previous two slides. This what DBA’s program in.
This diagram no longer seems toexist on Travis’s site
Always use parameter binding. Why? * you normally get better performance from some database engines due to to SQL query caching * reduce the chance of SQL injection
Always use parameter binding. Why? * you normally get better performance from some database engines due to to SQL query caching * reduce the chance of SQL injection
Gerald is a general purpose database schema toolkit written in Python. It can be used for cataloguing, managing and deploying database schemas. It is designed to allow you to easily identify the differences between databases.
SQLPython is a command-line interface to relational databases written in Python. It was created as an alternative to Oracle’s SQL\\*Plus, and can likewise be used instead of postgres’ psql or mysql’smysql text clients. In addition, it offers several extra features inspired by other command-line clients: Neatened output, smart prompt, tab completion, history, scripting, output to file, paste buffer & os command, unix like commands – ls cat grep, data dictionary exploration. Another feature is special output formats. By replacing the ; that terminates a SELECT statement with a backslash-character sequence, you can get output in a number of useful formats like xml, json, csvetc
One of the most powerful features is the py command. The py command allows the user to execute Python commands, either one-at-a-time (with py {command}) or in an interactive environment (beginning with a bare py statement, and continuing until Ctrl-D, quit(), or exit() is entered). A history of result sets from each query is exposed to the python session as the list r; the most recent result set is r[-1]. Each row can be references as a tuple, or as an object with an attribute for each column.
Spring Python takes the concepts of the Spring Framework and Spring Security, and brings them to the world of Python. It isn't a simple line-by-line port of the code. Instead, it takes some powerful ideas that were discovered in the realm of Java, and pragmatically applies them in the world of Python.One of these paradigms is a Portable Service Abstraction called DatabaseTemplate. * It is portable because it uses Python's standardized API, not tying us to any database vendor. Instead, in our example, we injected in an instance of Sqlite3ConnectionFactory* It provides the useful service of easily accessing information stored in a relational database, but letting us focus on the query, not the plumbing code* It offers a nice abstraction over Python's low level database API with reduced code noise. This allows us to avoid the cost and risk of writing code to manage cursors and exception handlingDatabaseTemplate handles exceptions by catching and holding them, then properly closing the cursor. It then raises it wrapped inside a Spring Python DataAccessException. This way, database resources are properly disposed of without losing the exception stack trace.The Database Template can be used in isolation from the SpringPython framework.