zoukankan      html  css  js  c++  java
  • 【转载】Python and Mysql Andy Dustman

    0.

    http://mysql-python.sourceforge.net/

    • Python and MySQL: This is a presentation I did a couple years ago for the 2005 MySQL User Conference. It was a 45-minute talk, so don't expect a lot of detail.

    1.https://web.archive.org/web/20070104043701/http://dustman.net/andy/python/python-and-mysql

    Andy Dustman
    <adustman@terry.uga.edu>
    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

     MutableImmutable
    Sequence list tuple
    str, unicode
    Number   int, long, float
    Mapping dict  
    Other object  
    The basic Python types and their mutability

    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 1"
    '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"u72c2
    u7009".encode('utf-8')
    'xe7x8bx82
    xe7x80x89'
    >>> print u"u72c2
    u7009".encode('utf-8')
    狂
    瀉
    

    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 object
    • iterobj.next() returns the next object
    • StopIteration 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 to NULL)

    Odds and ends

    • Member access with . operator
      • instance.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:
      @g
      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

    paramstyleString 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'
    MySQLdb 1.0 and 1.2 uses format and pyformat; 2.0 may also support qmark.

    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 compression
    • use_unicode=1 returns text-like columns as unicode objects
    • ssl=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 ). Passing them separately (as the second parameter) ensures they are quoted correctly. However, % is necessary if you have to insert arbitrary SQL such as column or table names or WHERE clauses.

    To buffer, or not to buffer...

    mysql_store_result()

    • Stores all rows of result set in client
    • Large result sets can chew up a lot of memory
    • Size of result set known immediately
    • Result set is seekable
    • Can issue another query immediately
    • Used for standard MySQLdb cursor

    mysql_use_result()

    • Sends result set row by row
    • Consumes resources on server
    • Must fetch all rows before issuing any other queries
    • Size of result set unknown until finished
    • Not seekable
    • Can be used with MySQLdb's SSCursor

    Optional cursor classes

    DictCursor causes fetchXXX() methods to return mappings instead of sequences, with column names for keys.

    users = []
    c = db.cursor(MySQLdb.cursors.DictCursor)
    c.execute("""SELECT userid, first_name, last_name, company
    FROM users WHERE status=%s and expire>%s""",
    (status, today))
    
    for row in c:
        u = User(**row)
        print u
        users.append(u)
    

    Note that column names happen to match User member names in this case.

    Type objects and constructors

    • Constructors
      • Date(year,month,day)
      • Time(hour,minute,second)
      • DateFromTicks(ticks)
      • TimeFromTicks(ticks)
      • TimestampFromTicks(ticks)
      • Binary(string)
    • Types
      • STRING
      • BINARY
      • NUMBER
      • DATETIME
      • ROWID

    These are not often used with MySQLdb.

    Embedded server

    1. Build with embedded server support:
      $ export mysqlclient=mysqld
      $ python setup.py build
      # python setup.py install
      
    2. _mysql.server_start()
    3. Use normally
    4. _mysql.server_end()

    Questions?

    • http://sourceforge.net/projects/mysql-python
    • http://www.terry.uga.edu/
    • http://www.uga.edu/
  • 相关阅读:
    Mysql 索引原理《一》索引原理与慢查询2
    Mysql 索引原理《一》索引原理与慢查询1
    Mysql内置功能《六》流程控制
    Mysql内置功能《五》 函数
    Mysql内置功能《四》存储过程
    Mysql pymysql模块
    HDU2020 绝对值排序
    HDU2019 数列有序
    HDU2018 母牛的故事
    HDU2016 数据的交换输出
  • 原文地址:https://www.cnblogs.com/my8100/p/7538004.html
Copyright © 2011-2022 走看看