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= Some General references = | |||
See http://www.kitebird.com/articles/pydbapi.html | See http://www.kitebird.com/articles/pydbapi.html | ||
= python-and-mysql = | |||
Check this out in [http://www.performiq.com.au/python-and-mysql.html HTML format] ... | |||
Check this out in [ | |||
<div class="layout"><div id="currentSlide"></div><div id="header"></div><div id="footer"> | <div class="layout"><div id="currentSlide"></div><div id="header"></div><div id="footer"> | ||
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Note use of <code>%</code> operator to insert parameter values. This does <b>not</b> provide proper quoting (escaping of <code>'</code>, <code>NULL</code>/<code>None</code>, or <code> | Note use of <code>%</code> operator to insert parameter values. This does <b>not</b> provide proper quoting (escaping of <code>'</code>, <code>NULL</code>/<code>None</code>, or <code> | ||
[[Category:Python]] | |||
[[Category:MySQL]] |
Latest revision as of 12:02, 25 January 2008
Contents
- 1 Some General references
- 2 python-and-mysql
- 3 MySQL Users Conference 2005, Santa Clara, CA
- 4 Python and MySQL
- 5 Python for the PyCurious
- 6 Types
- 7 Basic type examples
- 8 Strings
- 9 Strings
- 10 Dictionaries
- 11 Sequences
- 12 Iterators
- 13 Common iterator usage
- 14 Exceptions
- 15 Odds and ends
- 16 Odds and ends
- 17 The Python DB-API
- 18 Module Interface
- 19 SQL parameter placeholders
- 20 Exceptions
- 21 Connection Object
- 22 Cursor Object
- 23 Cursor Object
- 24 Cursor Object
- 25 MySQL for Python
- 26 Architecture
- 27 Opening a connection
- 28 Simple query example
- 29 Multi-row query example
- 30 A simple User class
- 31 Multi-row query with User object
- 32 Cursors are iterators
- 33 Dictionaries as parameters
- 34 Multi-row INSERT
- 35 Multi-row INSERT with dictionaries
- 36 Never do this
Some General references
See http://www.kitebird.com/articles/pydbapi.html
python-and-mysql
Check this out in HTML format ...
MySQL Users Conference 2005, Santa Clara, CA
Python and MySQL
Python and MySQL
Andy Dustman
Office of Information Technology
Terry College of Business
University of Georgia
- Andy Dustman
- [1][2]
- Terry College of Business
- http://www.terry.uga.edu/
- University of Georgia
- http://www.uga.edu/
Python for the PyCurious
- interpreted (byte-code compiler)
- interactive (easy to test ideas)
- object-oriented (everything's an object)
- rapid development (5-10x C++, Java)
- fits your brain [Bruce Eckel]
- fits your wallet: free (OSI and GPL)
- fun!
- Introductory Material on Python
- http://www.python.org/doc/Intros.html
Types
Mutable | Immutable | Sequence | list | tuple str, unicode | |
---|---|---|---|---|---|
Number | int, long, float | ||||
Mapping | dict | ||||
Other | object |
Basic type examples
>>> i=1 # an int
>>> j=2**64-1 # a long integer
>>> print j
18446744073709551615
>>> f=3.14 # float (C double)
>>> c=1-1j # complex (1j is imaginary)
>>> print c
(1-1j)
>>> s="welcome to python!"
>>> s.capitalize().split() # returns a list
['Welcome', 'to', 'python!']
>>> [ word.capitalize() for word in s.split() ]
['Welcome', 'To', 'Python!']
>>> a, b = 1, 2
>>> print (a,b) # a tuple
(1, 2)
>>> a, b = b, a
>>> print (a,b)
(2, 1)
Strings
>>> "Normal string literal isn't very interesting."
"Normal string literal isn't very interesting."
>>> 'Single quotes work "same as double".'
'Single quotes work "same as double".'
>>> """Triple-quoted strings are good for long strings
... which span multiple lines."""
'Triple-quoted strings are good for long strings which span multiple lines.'
>>> r"Raw strings are useful for regexs, i.e. w+ or �"
'Raw strings are useful for regexs, i.e. \w+ or \1'
>>> u"Unicode strings work just like regular strings."
u'Unicode strings work just like regular strings.'
>>> u"72c2 7009".encode('utf-8')
'狂 瀉'
>>> print u"72c2 7009".encode('utf-8')
�
�
Strings
Lots of string methods and operators:
>>> "Split words into a list.".split()
['Split', 'words', 'into', 'a', 'list.']
>>> ' '.join(['Join', 'a', 'list', 'of', 'strings'])
'Join a list of strings'
>>> "Concatenate" + " " + "strings"
'Concatenate strings'
>>> "Multiplicity! " * 3
'Multiplicity! Multiplicity! Multiplicity! '
>>> "Parameter %s" % "substitution"
'Parameter substitution'
>>> d = dict(first_name="Vee", last_name="McMillen",
... company="O'Reilly")
>>> "Hello, %(first_name)s. How are things at %(company)s?" % d
"Hello, Vee. How are things at O'Reilly?"
Dictionaries
Python dictionaries are like perl hashes:
>>> d1={}
>>> d1['a']=1
>>> d1['b']=2
>>> d1['c']=3
>>> d1
{'a': 1, 'c': 3, 'b': 2}
>>> d2={'a': 1, 'c': 3, 'b': 2}
>>> d3=dict([('a',1),('b',2),('c',3)])
>>> d4=dict(a=1, b=2, c=3)
>>> d1 == d2 == d3 == d4
True
>>> len(d1)
3
Values can be any type, but keys must be immutable.
Sequences
>>> l = ['a','b','c','d','e']
>>> print l[0]
a
>>> print l[-1]
e
>>> print l[2:4]
['c', 'd']
>>> s='abcde'
>>> print s[2:4]
cd
>>> print s[::2]
ace
>>> print s[::-1]
edcba
>>> l.append(s)
>>> print l
['a', 'b', 'c', 'd', 'e', 'abcde']
Iterators
iter(object)
returns an iterator objectiterobj.next()
returns the next objectStopIteration
is raised when there are no more objects
>>> # no normal person would do this
>>> l = [1, 2, 3]
>>> i = iter(l)
>>> i.next()
1
>>> i.next()
2
>>> i.next()
3
>>> i.next()
Traceback (most recent call last):
File "", line 1, in ?
StopIteration
Common iterator usage
>>> l = [1, 2, 3]
>>> for item in l:
... print item
...
1
2
3
>>> d = dict(a=1, b=2, c=3)
>>> for key in d:
... print key, d[key]
...
a 1
c 3
b 2
Exceptions
f = open("myfile", 'r')
try:
try:
for line in f:
try:
process(line)
except TypeError:
line = mangle(line)
try:
process(line)
except TypeError:
raise FoobarError, line
except IOError, message:
print "Error reading:", message
except FoobarError:
print "This file is totally munged."
except:
print "Something inexplicable happened:"
raise # re-raise original exception
finally:
f.close()
Odds and ends
- Code blocks are delimited by indentation
- You probably do this already
- Space or tabs, your call; just be consistent
- No need for curly braces
- Less cluttered, easier to read
- End-of-line is a statement separator (so is
;
) - No type enforcement
- Argument types are not checked
- Function return types are not checked
- Type checking makes your code less flexible
- If you still want it, you can add it cleanly with decorators
- Operator overloading for user-defined classes
- Everything is a reference (pass by reference)
None
object for null/missing values (equivalent toNULL
)
Odds and ends
- Member access with
.
operatorinstance.method()
instance.attribute
instance.attribute.another
- Functions/methods are not the only things that are callable
- Decorators apply a callable to a function at creation time:
def f(x):
...
is equivalent to: def f(x):
...
f = g(f)
The Python DB-API
- Standard API for database access
- PEP 249: http://www.python.org/peps/pep-0249.html
- By convention, module name ends with "db", i.e. MySQLdb
- Module Interface
- Connection Objects
- Cursor Objects
- DBI Helper Objects
- Type Objects and Constructors
- Implementation Hints
- Major Changes from 1.0 to 2.0
Module Interface
- connect(...)
- Constructor for creating a connection to the database. Returns a Connection Object.
- apilevel
- String constant stating the supported DB API level.
- threadsafety
- Integer constant stating the level of thread safety the interface supports.
SQL parameter placeholders
- paramstyle
- String constant stating the type of parameter marker formatting expected by the interface.
- 'qmark'
- Question mark style, e.g. '...WHERE name=?'
- 'numeric'
- Numeric, positional style, e.g. '...WHERE name=:1'
- 'named'
- Named style, e.g. '...WHERE name=:name'
- 'format'
- ANSI C printf format codes, e.g. '...WHERE name=%s'
- 'pyformat'
- Python extended format codes, e.g. '...WHERE name=%(name)s'
Exceptions
- StandardError
- Warning
- Error
- InterfaceError
- DatabaseError
- DataError
- OperationalError
- IntegrityError
- InternalError
- ProgrammingError
- NotSupportedError
Connection Object
- .close()
- Close the connection now
- .commit()
- Commit any pending transaction to the database. Auto-commit off by default.
- .rollback()
- Rollback any pending transaction.
- .cursor()
- Return a new Cursor Object using the connection.
- exceptions
- The standard exception classes; simplfies error handling in some cases
- .messages
- list of error/warning messages since last method call
Cursor Object
- .description
- A sequence of sequences, each of which describe a column of the result.
- .rowcount
- Number of rows affected by last query.
- .callproc(procname[,parameters])
- Call a stored database procedure with the given name.
- .close()
- Close the cursor now.
- .execute(operation[,parameters])
- Prepare and execute a database operation (query or command). Parameters: sequence or mapping.
- .executemany(operation,seq_of_parameters)
- Prepare a database operation (query or command) and then execute it against a sequence of parameters.
Cursor Object
- .fetchone()
- Fetch the next row of the result set as a sequence, or None if there are no more rows.
- .fetchmany([size=cursor.arraysize])
- Fetch a sequence of up to size rows; may be fewer. Zero length sequence indicates end of result set.
- .fetchall()
- Fetch all remaining rows as a sequence of rows.
- .nextset()
- Skip to the next result set. Returns a true value if there is another result set; None (false) if not.
- .arraysize
- Default number of rows to return with cursor.fetchmany(). Default: 1.
Cursor Object
- .rownumber
- Current index into result set
- .connection
- The Connection object for this cursor
- .scroll(value[,mode='relative'])
- Scroll to a new position in the result set (relative or absolute).
- .messages
- List containing warning/error messages since last method call (except the .fetchXXX() methods).
- .next()
- Fetches one row (like fetchone()) or raises
StopIteration
if no rows left. Iterator protocol - .lastrowid
- Row id of the last affected row (i.e. inserting
AUTO_INCREMENT
columns)
MySQL for Python
- MySQL-python project on SourceForge: http://sourceforge.net/projects/mysql-python
- Current best version: 1.2.0
- Python-2.3 and newer (and maybe 2.2)
- MySQL-3.23, 4.0, and 4.1 (and maybe 5.0)
- Prepared statements not supported yet
- Older version: 1.0.1
- Python-1.5.2 (very old) and newer
- MySQL-3.22, 3.23, and 4.0 (not 4.1 or newer)
- Don't use if you can use 1.2.0
- Vaporware version: 2.0
- Python-2.4 and newer
- MySQL-4.0, 4.1, and 5.0
- Prepared statements will be supported
- Return all text columns as
unicode
by default
Architecture
_mysql
- C extension module
- transliteration of MySQL C API into Python objects
- If you use the C API, this should be very familiar
- Deprecated API calls not implemented
- Not everything (particularly fields) is exposed
- SQL column type to Python type conversions handled by a dictionary
MySQLdb
- Adapts
_mysql
to DB-API - Many non-standard C API calls are exposed
- Relatively light-weight wrapper
- Implements cursors
- Defines default type mappings; easily customizable
Opening a connection
connect()
takes the same options as mysql_real_connect()
, and then some.
import MySQLdb
# These are all equivalent, for the most part
db = MySQLdb.connect("myhost", "myuser", "mysecret", "mydb")
db = MySQLdb.connect(host="myhost", user="myuser",
passwd="mysecret", db="mydb")
auth = dict(user="myuser", passwd="mysecret")
db = MySQLdb.connect("myhost", db="mydb", **auth)
db = MySQLdb.connect(read_default_file="/etc/mysql/myapp.cnf")
compress=1
enables gzip compressionuse_unicode=1
returns text-like columns asunicode
objectsssl=dict(...)
negotiates SSL/TLS
Simple query example
import MySQLdb
db = MySQLdb.connect(read_default_file="/etc/mysql/myapp.cnf")
c = db.cursor()
c.execute("""SELECT * FROM users WHERE userid=%s""", ('monty',))
print c.fetchone()
Notes
('monty',)
is a 1-tuple; comma required to distinquish from algebraic grouping- Good reasons not to use
*
- How many columns are being returned?
- What is the order of the columns?
- Good reasons to use
*
- Table/database browser
- Lazy
Multi-row query example
c = db.cursor()
c.execute("""SELECT userid, first_name, last_name, company
FROM users WHERE status=%s and expire>%s""",
(status, today))
users = c.fetchall()
Notes
- We know what the columns are
- Could use some object abstraction
A simple User class
class User(object):
"""A simple User class"""
def __init__(self, userid,
first_name=None, last_name=None,
company=None):
self.userid = userid
self.first_name = first_name
self.last_name = last_name
self.company = company
def announce(self):
"""Announce User to the world."""
name = "%s %s" % (self.first_name, self.last_name)
if self.company:
return "%s of %s" % (name, self.company)
else:
return name
def __str__(self):
return self.announce()
Multi-row query with User object
users = []
c = db.cursor()
c.execute("""SELECT userid, first_name, last_name, company
FROM users WHERE status=%s and expire>%s""",
(status, today))
for userid, first_name, last_name, company in c.fetchall():
u = User(userid, first_name, last_name, company)
print u
users.append(u)
might produce output like:
Tim O'Reilly of O'Reilly Media, Inc.
Monty Widenius of MySQL AB
Carleton Fiorina
Guido van Rossum of Elemental Security
Cursors are iterators
Not necessary to use c.fetchall()
users = []
c = db.cursor()
c.execute("""SELECT userid, first_name, last_name, company
FROM users WHERE status=%s and expire>%s""",
(status, today))
for userid, first_name, last_name, company in c:
u = User(userid, first_name, last_name, company)
print u
users.append(u)
Under certain conditions, this is more efficient than fetchall()
, and no worse.
Dictionaries as parameters
Python classes typically store attributes in __dict__
, so you can get away with this:
u = User(...)
c = db.cursor()
c.execute("""INSERT INTO users
(userid, first_name, last_name, company)
VALUES (%(userid)s, %(first_name)s,
%(last_name)s, %(company)s)""", u.__dict__)
db.commit()
Multi-row INSERT
# users is a list of (userid, first_name, last_name, company)
c = db.cursor()
c.executemany("""INSERT INTO users
(userid, first_name, last_name, company)
VALUES (%s, %s, %s, %s)""", users)
db.commit()
In MySQLdb, this is converted internally to a multi-row INSERT, which is reported to be 2-3 orders of magnitude faster. Also works for REPLACE.
Multi-row INSERT with dictionaries
# users is a list of Users
c = db.cursor()
c.executemany("""INSERT INTO users
(userid, first_name, last_name, company)
VALUES (%(userid)s, %(first_name)s,
%(last_names, %(company)s)""",
[ u.__dict__ for u in users ])
db.commit()
This builds the parameter list with a list comprehension.
Never do this
Biggest MySQLdb newbie mistake of all time: Seeing %s
and thinking, "I should use the %
operator here."
users = []
c = db.cursor()
c.execute("""SELECT userid, first_name, last_name, company
FROM users WHERE status='%s' and expire>'%s'""" %
(status, today))
for userid, first_name, last_name, company in c:
u = User(userid, first_name, last_name, company)
print u
users.append(u)
Note use of %
operator to insert parameter values. This does not provide proper quoting (escaping of '
, NULL
/None
, or