11.13. sqlite3 — SQLite 数据库 DB-API 2.0 接口模块

2.5 新版功能.

SQLite 是一个C语言库，它可以提供一种轻量级的基于磁盘的数据库，这种数据库不需要独立的服务器进程，也允许需要使用一种非标准的 SQL 查询语言来访问它。一些应用程序可以使用 SQLite 作为内部数据存储。可以用它来创建一个应用程序原型，然后再迁移到更大的数据库，比如 PostgreSQL 或 Oracle。

sqlite3 模块是由 Gerhard Häring 编写。它提供了符合 DB-API 2.0 规范的接口，这个规范是 PEP 249。

要使用这个模块，必须先创建一个 Connection 对象，它代表数据库。下面例子中，数据将存储在 example.db 文件中：

import sqlite3
conn = sqlite3.connect('example.db')

你也可以使用 :memory: 来创建一个内存中的数据库

当有了 Connection 对象后，你可以创建一个 Cursor 游标对象，然后调用它的 execute() 方法来执行 SQL 语句：

c = conn.cursor()

# Create table
c.execute('''CREATE TABLE stocks
             (date text, trans text, symbol text, qty real, price real)''')

# Insert a row of data
c.execute("INSERT INTO stocks VALUES ('2006-01-05','BUY','RHAT',100,35.14)")

# Save (commit) the changes
conn.commit()

# We can also close the connection if we are done with it.
# Just be sure any changes have been committed or they will be lost.
conn.close()

这些数据被持久化保存了，而且可以在之后的会话中使用它们：

import sqlite3
conn = sqlite3.connect('example.db')
c = conn.cursor()

通常你的 SQL 操作需要使用一些 Python 变量的值。你不应该使用 Python 的字符串操作来创建你的查询语句，因为那样做不安全；它会使你的程序容易受到 SQL 注入攻击（在 https://xkcd.com/327/ 上有一个搞笑的例子，看看有什么后果）

推荐另外一种方法：使用 DB-API 的参数替换。在你的 SQL 语句中，使用 ? 占位符来代替值，然后把对应的值组成的元组做为 execute() 方法的第二个参数。（其他数据库可能会使用不同的占位符，比如 %s 或者 :1）例如：

# Never do this -- insecure!
symbol = 'RHAT'
c.execute("SELECT * FROM stocks WHERE symbol = '%s'" % symbol)

# Do this instead
t = ('RHAT',)
c.execute('SELECT * FROM stocks WHERE symbol=?', t)
print c.fetchone()

# Larger example that inserts many records at a time
purchases = [('2006-03-28', 'BUY', 'IBM', 1000, 45.00),
             ('2006-04-05', 'BUY', 'MSFT', 1000, 72.00),
             ('2006-04-06', 'SELL', 'IBM', 500, 53.00),
            ]
c.executemany('INSERT INTO stocks VALUES (?,?,?,?,?)', purchases)

要在执行 SELECT 语句后获取数据，你可以把游标作为 iterator，然后调用它的 fetchone() 方法来获取一条匹配的行，也可以调用 fetchall() 来得到包含多个匹配行的列表。

下面是一个使用迭代器形式的例子：

>>> for row in c.execute('SELECT * FROM stocks ORDER BY price'):
        print row

(u'2006-01-05', u'BUY', u'RHAT', 100, 35.14)
(u'2006-03-28', u'BUY', u'IBM', 1000, 45.0)
(u'2006-04-06', u'SELL', u'IBM', 500, 53.0)
(u'2006-04-05', u'BUY', u'MSFT', 1000, 72.0)

参见

https://github.com/ghaering/pysqlite

pysqlite的主页 – sqlite3 在外部使用 “pysqlite” 名字进行开发。

https://www.sqlite.org

SQLite的主页；它的文档详细描述了它所支持的 SQL 方言的语法和可用的数据类型。

http://www.w3schools.com/sql/

学习 SQL 语法的教程、参考和例子。

PEP 249 - DB-API 2.0 规范

Marc-André Lemburg 写的 PEP。

11.13.1. 模块函数和常量

sqlite3.version

这个模块的版本号，是一个字符串。不是 SQLite 库的版本号。

sqlite3.version_info

这个模块的版本号，是一个由整数组成的元组。不是 SQLite 库的版本号。

sqlite3.sqlite_version

使用中的 SQLite 库的版本号，是一个字符串。

sqlite3.sqlite_version_info

使用中的 SQLite 库的版本号，是一个整数组成的元组。

sqlite3.PARSE_DECLTYPES

这个常量可以作为 connect() 函数的 detect_types 参数。

设置这个参数后，sqlite3 模块将解析它返回的每一列申明的类型。它会申明的类型的第一个单词，比如“integer primary key”，它会解析出“integer”，再比如“number(10)”，它会解析出“number”。然后，它会在转换器字典里查找那个类型注册的转换器函数，并调用它。

sqlite3.PARSE_COLNAMES

这个常量可以作为 connect() 函数的 detect_types 参数。

设置这个参数后，SQLite 接口将解析它返回的每一列的列名。它会在其中查找 [mytype] 这个形式的字符串，然后用‘mytype’来决定那个列的类型。它会尝试在转换器字典中查找‘mytype’键对应的转换器函数，然后用这个转换器函数返回的值来做为列的类型。在 Cursor.description 中找到的列名仅仅是列名的第一个单词，比如你在 SQL 中使用 'as "x [datetime]"'，然后它会解析出第一个空白字符前的所有字符来作为列名：列名就是“x”。

sqlite3.connect(database[, timeout, detect_types, isolation_level, check_same_thread, factory, cached_statements])

Opens a connection to the SQLite database file database. You can use ":memory:" to open a database connection to a database that resides in RAM instead of on disk.

当一个数据库被多个连接访问的时候，如果其中一个进程修改这个数据库，在这个事务提交之前，这个 SQLite 数据库将会被一直锁定。timeout 参数指定了这个连接等待锁释放的超时时间，超时之后会引发一个异常。这个超时时间默认是 5.0（5秒）。

For the isolation_level parameter, please see the Connection.isolation_level property of Connection objects.

SQLite 原生只支持5种类型：TEXT，INTEGER，REAL，BLOB 和 NULL。如果你想用其它类型，你必须自己添加相应的支持。使用 detect_types 参数和模块级别的 register_converter() 函数注册**转换器** 可以简单的实现。

detect_types 默认为0（即关闭，没有类型检测）。你也可以组合 PARSE_DECLTYPES 和 PARSE_COLNAMES 来开启类型检测。

默认情况下，当调用 connect 方法的时候，sqlite3 模块使用了它的 Connection 类。当然，你也可以创建 Connection 类的子类，然后创建提供了 factory 参数的 connect() 方法。

详情请查阅当前手册的 SQLite 与 Python 类型 部分。

sqlite3 模块在内部使用语句缓存来避免 SQL 解析开销。 如果要显式设置当前连接可以缓存的语句数，可以设置 cached_statements 参数。 当前实现的默认值是缓存100条语句。

sqlite3.register_converter(typename, callable)

注册一个回调对象 callable, 用来转换数据库中的字节串为自定的 Python 类型。所有类型为 typename 的数据库的值在转换时，都会调用这个回调对象。通过指定 connect() 函数的 detect-types 参数来设置类型检测的方式。注意，typename 与查询语句中的类型名进行匹配时不区分大小写。

sqlite3.register_adapter(type, callable)

Registers a callable to convert the custom Python type type into one of SQLite’s supported types. The callable callable accepts as single parameter the Python value, and must return a value of the following types: int, long, float, str (UTF-8 encoded), unicode or buffer.

sqlite3.complete_statement(sql)

如果字符串 sql 包含一个或多个完整的 SQL 语句（以分号结束）则返回 True。它不会验证 SQL 语法是否正确，仅会验证字符串字面上是否完整，以及是否以分号结束。

它可以用来构建一个 SQLite shell，下面是一个例子：

# A minimal SQLite shell for experiments

import sqlite3

con = sqlite3.connect(":memory:")
con.isolation_level = None
cur = con.cursor()

buffer = ""

print "Enter your SQL commands to execute in sqlite3."
print "Enter a blank line to exit."

while True:
    line = raw_input()
    if line == "":
        break
    buffer += line
    if sqlite3.complete_statement(buffer):
        try:
            buffer = buffer.strip()
            cur.execute(buffer)

            if buffer.lstrip().upper().startswith("SELECT"):
                print cur.fetchall()
        except sqlite3.Error as e:
            print "An error occurred:", e.args[0]
        buffer = ""

con.close()

sqlite3.enable_callback_tracebacks(flag)

默认情况下，您不会获得任何用户定义函数中的回溯消息，比如聚合，转换器，授权器回调等。如果要调试它们，可以设置 flag 参数为 True 并调用此函数。 之后，回调中的回溯信息将会输出到 sys.stderr。 再次使用 False 来禁用该功能。

11.13.2. 连接对象（Connection）

class sqlite3.Connection

SQLite 数据库连接对象有如下的属性和方法：

isolation_level

Get or set the current isolation level. None for autocommit mode or one of “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”. See section Controlling Transactions for a more detailed explanation.

cursor(factory=Cursor)

这个方法接受一个可选参数 factory，如果要指定这个参数，它必须是一个可调用对象，而且必须返回 Cursor 类的一个实例或者子类。

commit()

这个方法提交当前事务。如果没有调用这个方法，那么从上一次提交 commit() 以来所有的变化在其他数据库连接上都是不可见的。如果你往数据库里写了数据，但是又查询不到，请检查是否忘记了调用这个方法。

rollback()

这个方法回滚从上一次调用 commit() 以来所有数据库的改变。

close()

关闭数据库连接。注意，它不会自动调用 commit() 方法。如果在关闭数据库连接之前没有调用 commit()，那么你的修改将会丢失！

execute(sql[, parameters])

This is a nonstandard shortcut that creates an intermediate cursor object by calling the cursor method, then calls the cursor’s execute method with the parameters given.

executemany(sql[, parameters])

This is a nonstandard shortcut that creates an intermediate cursor object by calling the cursor method, then calls the cursor’s executemany method with the parameters given.

executescript(sql_script)

This is a nonstandard shortcut that creates an intermediate cursor object by calling the cursor method, then calls the cursor’s executescript method with the parameters given.

create_function(name, num_params, func)

Creates a user-defined function that you can later use from within SQL statements under the function name name. num_params is the number of parameters the function accepts, and func is a Python callable that is called as the SQL function.

The function can return any of the types supported by SQLite: unicode, str, int, long, float, buffer and None.

示例:

import sqlite3
import md5

def md5sum(t):
    return md5.md5(t).hexdigest()

con = sqlite3.connect(":memory:")
con.create_function("md5", 1, md5sum)
cur = con.cursor()
cur.execute("select md5(?)", ("foo",))
print cur.fetchone()[0]

create_aggregate(name, num_params, aggregate_class)

创建一个自定义的聚合函数。

The aggregate class must implement a step method, which accepts the number of parameters num_params, and a finalize method which will return the final result of the aggregate.

The finalize method can return any of the types supported by SQLite: unicode, str, int, long, float, buffer and None.

示例:

import sqlite3

class MySum:
    def __init__(self):
        self.count = 0

    def step(self, value):
        self.count += value

    def finalize(self):
        return self.count

con = sqlite3.connect(":memory:")
con.create_aggregate("mysum", 1, MySum)
cur = con.cursor()
cur.execute("create table test(i)")
cur.execute("insert into test(i) values (1)")
cur.execute("insert into test(i) values (2)")
cur.execute("select mysum(i) from test")
print cur.fetchone()[0]

create_collation(name, callable)

使用 name 和 callable 创建排序规则。这个 callable 接受两个字符串对象，如果第一个小于第二个则返回 -1， 如果两个相等则返回 0，如果第一个大于第二个则返回 1。注意，这是用来控制排序的（SQL 中的 ORDER BY），所以它不会影响其它的 SQL 操作。

注意，这个 callable 可调用对象会把它的参数作为 Python 字节串，通常会以 UTF-8 编码格式对它进行编码。

The following example shows a custom collation that sorts “the wrong way”:

import sqlite3

def collate_reverse(string1, string2):
    return -cmp(string1, string2)

con = sqlite3.connect(":memory:")
con.create_collation("reverse", collate_reverse)

cur = con.cursor()
cur.execute("create table test(x)")
cur.executemany("insert into test(x) values (?)", [("a",), ("b",)])
cur.execute("select x from test order by x collate reverse")
for row in cur:
    print row
con.close()

要移除一个排序规则，需要调用 create_collation 并设置 callable 参数为 None。

con.create_collation("reverse", None)

interrupt()

可以从不同的线程调用这个方法来终止所有查询操作，这些查询操作可能正在连接上执行。此方法调用之后， 查询将会终止，而且查询的调用者会获得一个异常。

set_authorizer(authorizer_callback)

此方法注册一个授权回调对象。每次在访问数据库中某个表的某一列的时候，这个回调对象将会被调用。如果要允许访问，则返回 SQLITE_OK，如果要终止整个 SQL 语句，则返回 SQLITE_DENY，如果这一列需要当做 NULL 值处理，则返回 SQLITE_IGNORE。这些常量可以在 sqlite3 模块中找到。

The first argument to the callback signifies what kind of operation is to be authorized. The second and third argument will be arguments or None depending on the first argument. The 4th argument is the name of the database (“main”, “temp”, etc.) if applicable. The 5th argument is the name of the inner-most trigger or view that is responsible for the access attempt or None if this access attempt is directly from input SQL code.

Please consult the SQLite documentation about the possible values for the first argument and the meaning of the second and third argument depending on the first one. All necessary constants are available in the sqlite3 module.

set_progress_handler(handler, n)

This routine registers a callback. The callback is invoked for every n instructions of the SQLite virtual machine. This is useful if you want to get called from SQLite during long-running operations, for example to update a GUI.

If you want to clear any previously installed progress handler, call the method with None for handler.

2.6 新版功能.

enable_load_extension(enabled)

This routine allows/disallows the SQLite engine to load SQLite extensions from shared libraries. SQLite extensions can define new functions, aggregates or whole new virtual table implementations. One well-known extension is the fulltext-search extension distributed with SQLite.

Loadable extensions are disabled by default. See [1].

2.7 新版功能.

import sqlite3

con = sqlite3.connect(":memory:")

# enable extension loading
con.enable_load_extension(True)

# Load the fulltext search extension
con.execute("select load_extension('./fts3.so')")

# alternatively you can load the extension using an API call:
# con.load_extension("./fts3.so")

# disable extension loading again
con.enable_load_extension(False)

# example from SQLite wiki
con.execute("create virtual table recipe using fts3(name, ingredients)")
con.executescript("""
    insert into recipe (name, ingredients) values ('broccoli stew', 'broccoli peppers cheese tomatoes');
    insert into recipe (name, ingredients) values ('pumpkin stew', 'pumpkin onions garlic celery');
    insert into recipe (name, ingredients) values ('broccoli pie', 'broccoli cheese onions flour');
    insert into recipe (name, ingredients) values ('pumpkin pie', 'pumpkin sugar flour butter');
    """)
for row in con.execute("select rowid, name, ingredients from recipe where name match 'pie'"):
    print row

load_extension(path)

This routine loads a SQLite extension from a shared library. You have to enable extension loading with enable_load_extension() before you can use this routine.

Loadable extensions are disabled by default. See [1].

2.7 新版功能.

row_factory

You can change this attribute to a callable that accepts the cursor and the original row as a tuple and will return the real result row. This way, you can implement more advanced ways of returning results, such as returning an object that can also access columns by name.

示例:

import sqlite3

def dict_factory(cursor, row):
    d = {}
    for idx, col in enumerate(cursor.description):
        d[col[0]] = row[idx]
    return d

con = sqlite3.connect(":memory:")
con.row_factory = dict_factory
cur = con.cursor()
cur.execute("select 1 as a")
print cur.fetchone()["a"]

If returning a tuple doesn’t suffice and you want name-based access to columns, you should consider setting row_factory to the highly-optimized sqlite3.Row type. Row provides both index-based and case-insensitive name-based access to columns with almost no memory overhead. It will probably be better than your own custom dictionary-based approach or even a db_row based solution.

text_factory

Using this attribute you can control what objects are returned for the TEXT data type. By default, this attribute is set to unicode and the sqlite3 module will return Unicode objects for TEXT. If you want to return bytestrings instead, you can set it to str.

For efficiency reasons, there’s also a way to return Unicode objects only for non-ASCII data, and bytestrings otherwise. To activate it, set this attribute to sqlite3.OptimizedUnicode.

You can also set it to any other callable that accepts a single bytestring parameter and returns the resulting object.

See the following example code for illustration:

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()

AUSTRIA = u"\xd6sterreich"

# by default, rows are returned as Unicode
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert row[0] == AUSTRIA

# but we can make sqlite3 always return bytestrings ...
con.text_factory = str
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert type(row[0]) is str
# the bytestrings will be encoded in UTF-8, unless you stored garbage in the
# database ...
assert row[0] == AUSTRIA.encode("utf-8")

# we can also implement a custom text_factory ...
# here we implement one that will ignore Unicode characters that cannot be
# decoded from UTF-8
con.text_factory = lambda x: unicode(x, "utf-8", "ignore")
cur.execute("select ?", ("this is latin1 and would normally create errors" +
                         u"\xe4\xf6\xfc".encode("latin1"),))
row = cur.fetchone()
assert type(row[0]) is unicode

# sqlite3 offers a built-in optimized text_factory that will return bytestring
# objects, if the data is in ASCII only, and otherwise return unicode objects
con.text_factory = sqlite3.OptimizedUnicode
cur.execute("select ?", (AUSTRIA,))
row = cur.fetchone()
assert type(row[0]) is unicode

cur.execute("select ?", ("Germany",))
row = cur.fetchone()
assert type(row[0]) is str

total_changes

Returns the total number of database rows that have been modified, inserted, or deleted since the database connection was opened.

iterdump

Returns an iterator to dump the database in an SQL text format. Useful when saving an in-memory database for later restoration. This function provides the same capabilities as the .dump command in the sqlite3 shell.

2.6 新版功能.

示例:

# Convert file existing_db.db to SQL dump file dump.sql
import sqlite3, os

con = sqlite3.connect('existing_db.db')
with open('dump.sql', 'w') as f:
    for line in con.iterdump():
        f.write('%s\n' % line)

11.13.3. 游标对象*Cursor*

class sqlite3.Cursor

Cursor 游标实例具有以下属性和方法。

execute(sql[, parameters])

执行SQL语句。 可以是参数化 SQL 语句（即，在 SQL 语句中使用占位符）。sqlite3 模块支持两种占位符：问号（qmark风格）和命名占位符（命名风格）。

以下是两种风格的示例：

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.execute("create table people (name_last, age)")

who = "Yeltsin"
age = 72

# This is the qmark style:
cur.execute("insert into people values (?, ?)", (who, age))

# And this is the named style:
cur.execute("select * from people where name_last=:who and age=:age", {"who": who, "age": age})

print cur.fetchone()

execute() will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise a Warning. Use executescript() if you want to execute multiple SQL statements with one call.

executemany(sql, seq_of_parameters)

Executes an SQL command against all parameter sequences or mappings found in the sequence sql. The sqlite3 module also allows using an iterator yielding parameters instead of a sequence.

import sqlite3

class IterChars:
    def __init__(self):
        self.count = ord('a')

    def __iter__(self):
        return self

    def next(self):
        if self.count > ord('z'):
            raise StopIteration
        self.count += 1
        return (chr(self.count - 1),) # this is a 1-tuple

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.execute("create table characters(c)")

theIter = IterChars()
cur.executemany("insert into characters(c) values (?)", theIter)

cur.execute("select c from characters")
print cur.fetchall()

这是一个使用生成器 generator 的简短示例：

import sqlite3
import string

def char_generator():
    for c in string.lowercase:
        yield (c,)

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.execute("create table characters(c)")

cur.executemany("insert into characters(c) values (?)", char_generator())

cur.execute("select c from characters")
print cur.fetchall()

executescript(sql_script)

This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a COMMIT statement first, then executes the SQL script it gets as a parameter.

sql_script can be a bytestring or a Unicode string.

示例:

import sqlite3

con = sqlite3.connect(":memory:")
cur = con.cursor()
cur.executescript("""
    create table person(
        firstname,
        lastname,
        age
    );

    create table book(
        title,
        author,
        published
    );

    insert into book(title, author, published)
    values (
        'Dirk Gently''s Holistic Detective Agency',
        'Douglas Adams',
        1987
    );
    """)

fetchone()

Fetches the next row of a query result set, returning a single sequence, or None when no more data is available.

fetchmany([size=cursor.arraysize])

Fetches the next set of rows of a query result, returning a list. An empty list is returned when no more rows are available.

The number of rows to fetch per call is specified by the size parameter. If it is not given, the cursor’s arraysize determines the number of rows to be fetched. The method should try to fetch as many rows as indicated by the size parameter. If this is not possible due to the specified number of rows not being available, fewer rows may be returned.

Note there are performance considerations involved with the size parameter. For optimal performance, it is usually best to use the arraysize attribute. If the size parameter is used, then it is best for it to retain the same value from one fetchmany() call to the next.

fetchall()

Fetches all (remaining) rows of a query result, returning a list. Note that the cursor’s arraysize attribute can affect the performance of this operation. An empty list is returned when no rows are available.

rowcount

Although the Cursor class of the sqlite3 module implements this attribute, the database engine’s own support for the determination of “rows affected”/”rows selected” is quirky.

For executemany() statements, the number of modifications are summed up into rowcount.

As required by the Python DB API Spec, the rowcount attribute “is -1 in case no executeXX() has been performed on the cursor or the rowcount of the last operation is not determinable by the interface”. This includes SELECT statements because we cannot determine the number of rows a query produced until all rows were fetched.

With SQLite versions before 3.6.5, rowcount is set to 0 if you make a DELETE FROM table without any condition.

lastrowid

This read-only attribute provides the rowid of the last modified row. It is only set if you issued an INSERT statement using the execute() method. For operations other than INSERT or when executemany() is called, lastrowid is set to None.

description

This read-only attribute provides the column names of the last query. To remain compatible with the Python DB API, it returns a 7-tuple for each column where the last six items of each tuple are None.

It is set for SELECT statements without any matching rows as well.

connection

This read-only attribute provides the SQLite database Connection used by the Cursor object. A Cursor object created by calling con.cursor() will have a connection attribute that refers to con:

>>> con = sqlite3.connect(":memory:")
>>> cur = con.cursor()
>>> cur.connection == con
True

11.13.4. 行对象*Row*

class sqlite3.Row

A Row instance serves as a highly optimized row_factory for Connection objects. It tries to mimic a tuple in most of its features.

It supports mapping access by column name and index, iteration, representation, equality testing and len().

If two Row objects have exactly the same columns and their members are equal, they compare equal.

在 2.6 版更改: Added iteration and equality (hashability).

keys()

This method returns a list of column names. Immediately after a query, it is the first member of each tuple in Cursor.description.

2.6 新版功能.

Let’s assume we initialize a table as in the example given above:

conn = sqlite3.connect(":memory:")
c = conn.cursor()
c.execute('''create table stocks
(date text, trans text, symbol text,
 qty real, price real)''')
c.execute("""insert into stocks
          values ('2006-01-05','BUY','RHAT',100,35.14)""")
conn.commit()
c.close()

Now we plug Row in:

>>> conn.row_factory = sqlite3.Row
>>> c = conn.cursor()
>>> c.execute('select * from stocks')
<sqlite3.Cursor object at 0x7f4e7dd8fa80>
>>> r = c.fetchone()
>>> type(r)
<type 'sqlite3.Row'>
>>> r
(u'2006-01-05', u'BUY', u'RHAT', 100.0, 35.14)
>>> len(r)
5
>>> r[2]
u'RHAT'
>>> r.keys()
['date', 'trans', 'symbol', 'qty', 'price']
>>> r['qty']
100.0
>>> for member in r:
...     print member
...
2006-01-05
BUY
RHAT
100.0
35.14

11.13.5. SQLite 与 Python 类型

11.13.5.1. 概述

SQLite 原生支持如下的类型： NULL，INTEGER，REAL，TEXT，BLOB。

The following Python types can thus be sent to SQLite without any problem:

Python 类型	SQLite 类型
None	NULL
int	INTEGER
long	INTEGER
float	REAL
str (UTF8-encoded)	TEXT
unicode	TEXT
buffer	BLOB

This is how SQLite types are converted to Python types by default:

SQLite 类型	Python 类型
NULL	None
INTEGER	int or long, depending on size
REAL	float
TEXT	depends on text_factory, unicode by default
BLOB	buffer

The type system of the sqlite3 module is extensible in two ways: you can store additional Python types in a SQLite database via object adaptation, and you can let the sqlite3 module convert SQLite types to different Python types via converters.

11.13.5.2. Using adapters to store additional Python types in SQLite databases

As described before, SQLite supports only a limited set of types natively. To use other Python types with SQLite, you must adapt them to one of the sqlite3 module’s supported types for SQLite: one of NoneType, int, long, float, str, unicode, buffer.

There are two ways to enable the sqlite3 module to adapt a custom Python type to one of the supported ones.

11.13.5.2.1. Letting your object adapt itself

This is a good approach if you write the class yourself. Let’s suppose you have a class like this:

class Point(object):
    def __init__(self, x, y):
        self.x, self.y = x, y

Now you want to store the point in a single SQLite column. First you’ll have to choose one of the supported types first to be used for representing the point. Let’s just use str and separate the coordinates using a semicolon. Then you need to give your class a method __conform__(self, protocol) which must return the converted value. The parameter protocol will be PrepareProtocol.

import sqlite3

class Point(object):
    def __init__(self, x, y):
        self.x, self.y = x, y

    def __conform__(self, protocol):
        if protocol is sqlite3.PrepareProtocol:
            return "%f;%f" % (self.x, self.y)

con = sqlite3.connect(":memory:")
cur = con.cursor()

p = Point(4.0, -3.2)
cur.execute("select ?", (p,))
print cur.fetchone()[0]

11.13.5.2.2. Registering an adapter callable

The other possibility is to create a function that converts the type to the string representation and register the function with register_adapter().

注解

The type/class to adapt must be a new-style class, i. e. it must have object as one of its bases.

import sqlite3

class Point(object):
    def __init__(self, x, y):
        self.x, self.y = x, y

def adapt_point(point):
    return "%f;%f" % (point.x, point.y)

sqlite3.register_adapter(Point, adapt_point)

con = sqlite3.connect(":memory:")
cur = con.cursor()

p = Point(4.0, -3.2)
cur.execute("select ?", (p,))
print cur.fetchone()[0]

The sqlite3 module has two default adapters for Python’s built-in datetime.date and datetime.datetime types. Now let’s suppose we want to store datetime.datetime objects not in ISO representation, but as a Unix timestamp.

import sqlite3
import datetime, time

def adapt_datetime(ts):
    return time.mktime(ts.timetuple())

sqlite3.register_adapter(datetime.datetime, adapt_datetime)

con = sqlite3.connect(":memory:")
cur = con.cursor()

now = datetime.datetime.now()
cur.execute("select ?", (now,))
print cur.fetchone()[0]

11.13.5.3. Converting SQLite values to custom Python types

Writing an adapter lets you send custom Python types to SQLite. But to make it really useful we need to make the Python to SQLite to Python roundtrip work.

Enter converters.

Let’s go back to the Point class. We stored the x and y coordinates separated via semicolons as strings in SQLite.

First, we’ll define a converter function that accepts the string as a parameter and constructs a Point object from it.

注解

Converter functions always get called with a string, no matter under which data type you sent the value to SQLite.

def convert_point(s):
    x, y = map(float, s.split(";"))
    return Point(x, y)

Now you need to make the sqlite3 module know that what you select from the database is actually a point. There are two ways of doing this:

• Implicitly via the declared type
• Explicitly via the column name

Both ways are described in section 模块函数和常量, in the entries for the constants PARSE_DECLTYPES and PARSE_COLNAMES.

The following example illustrates both approaches.

import sqlite3

class Point(object):
    def __init__(self, x, y):
        self.x, self.y = x, y

    def __repr__(self):
        return "(%f;%f)" % (self.x, self.y)

def adapt_point(point):
    return "%f;%f" % (point.x, point.y)

def convert_point(s):
    x, y = map(float, s.split(";"))
    return Point(x, y)

# Register the adapter
sqlite3.register_adapter(Point, adapt_point)

# Register the converter
sqlite3.register_converter("point", convert_point)

p = Point(4.0, -3.2)

#########################
# 1) Using declared types
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
cur = con.cursor()
cur.execute("create table test(p point)")

cur.execute("insert into test(p) values (?)", (p,))
cur.execute("select p from test")
print "with declared types:", cur.fetchone()[0]
cur.close()
con.close()

#######################
# 1) Using column names
con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(p)")

cur.execute("insert into test(p) values (?)", (p,))
cur.execute('select p as "p [point]" from test')
print "with column names:", cur.fetchone()[0]
cur.close()
con.close()

11.13.5.4. Default adapters and converters

There are default adapters for the date and datetime types in the datetime module. They will be sent as ISO dates/ISO timestamps to SQLite.

The default converters are registered under the name “date” for datetime.date and under the name “timestamp” for datetime.datetime.

This way, you can use date/timestamps from Python without any additional fiddling in most cases. The format of the adapters is also compatible with the experimental SQLite date/time functions.

The following example demonstrates this.

import sqlite3
import datetime

con = sqlite3.connect(":memory:", detect_types=sqlite3.PARSE_DECLTYPES|sqlite3.PARSE_COLNAMES)
cur = con.cursor()
cur.execute("create table test(d date, ts timestamp)")

today = datetime.date.today()
now = datetime.datetime.now()

cur.execute("insert into test(d, ts) values (?, ?)", (today, now))
cur.execute("select d, ts from test")
row = cur.fetchone()
print today, "=>", row[0], type(row[0])
print now, "=>", row[1], type(row[1])

cur.execute('select current_date as "d [date]", current_timestamp as "ts [timestamp]"')
row = cur.fetchone()
print "current_date", row[0], type(row[0])
print "current_timestamp", row[1], type(row[1])

If a timestamp stored in SQLite has a fractional part longer than 6 numbers, its value will be truncated to microsecond precision by the timestamp converter.

11.13.6. Controlling Transactions

By default, the sqlite3 module opens transactions implicitly before a Data Modification Language (DML) statement (i.e. INSERT/UPDATE/DELETE/REPLACE), and commits transactions implicitly before a non-DML, non-query statement (i. e. anything other than SELECT or the aforementioned).

So if you are within a transaction and issue a command like CREATE TABLE ..., VACUUM, PRAGMA, the sqlite3 module will commit implicitly before executing that command. There are two reasons for doing that. The first is that some of these commands don’t work within transactions. The other reason is that sqlite3 needs to keep track of the transaction state (if a transaction is active or not).

You can control which kind of BEGIN statements sqlite3 implicitly executes (or none at all) via the isolation_level parameter to the connect() call, or via the isolation_level property of connections.

If you want autocommit mode, then set isolation_level to None.

Otherwise leave it at its default, which will result in a plain “BEGIN” statement, or set it to one of SQLite’s supported isolation levels: “DEFERRED”, “IMMEDIATE” or “EXCLUSIVE”.

11.13.7. Using sqlite3 efficiently

11.13.7.1. Using shortcut methods

Using the nonstandard execute(), executemany() and executescript() methods of the Connection object, your code can be written more concisely because you don’t have to create the (often superfluous) Cursor objects explicitly. Instead, the Cursor objects are created implicitly and these shortcut methods return the cursor objects. This way, you can execute a SELECT statement and iterate over it directly using only a single call on the Connection object.

import sqlite3

persons = [
    ("Hugo", "Boss"),
    ("Calvin", "Klein")
    ]

con = sqlite3.connect(":memory:")

# Create the table
con.execute("create table person(firstname, lastname)")

# Fill the table
con.executemany("insert into person(firstname, lastname) values (?, ?)", persons)

# Print the table contents
for row in con.execute("select firstname, lastname from person"):
    print row

print "I just deleted", con.execute("delete from person").rowcount, "rows"

11.13.7.2. Accessing columns by name instead of by index

One useful feature of the sqlite3 module is the built-in sqlite3.Row class designed to be used as a row factory.

Rows wrapped with this class can be accessed both by index (like tuples) and case-insensitively by name:

import sqlite3

con = sqlite3.connect(":memory:")
con.row_factory = sqlite3.Row

cur = con.cursor()
cur.execute("select 'John' as name, 42 as age")
for row in cur:
    assert row[0] == row["name"]
    assert row["name"] == row["nAmE"]
    assert row[1] == row["age"]
    assert row[1] == row["AgE"]

11.13.7.3. 使用连接作为上下文管理器

2.6 新版功能.

连接对象可以用来作为上下文管理器，它可以自动提交或者回滚事务。如果出现异常，事务会被回滚；否则，事务会被提交。

import sqlite3

con = sqlite3.connect(":memory:")
con.execute("create table person (id integer primary key, firstname varchar unique)")

# Successful, con.commit() is called automatically afterwards
with con:
    con.execute("insert into person(firstname) values (?)", ("Joe",))

# con.rollback() is called after the with block finishes with an exception, the
# exception is still raised and must be caught
try:
    with con:
        con.execute("insert into person(firstname) values (?)", ("Joe",))
except sqlite3.IntegrityError:
    print "couldn't add Joe twice"

11.13.8. 常见问题

11.13.8.1. 多线程

Older SQLite versions had issues with sharing connections between threads. That’s why the Python module disallows sharing connections and cursors between threads. If you still try to do so, you will get an exception at runtime.

The only exception is calling the interrupt() method, which only makes sense to call from a different thread.

脚注

[1]

(1, 2) The sqlite3 module is not built with loadable extension support by default, because some platforms (notably Mac OS X) have SQLite libraries which are compiled without this feature. To get loadable extension support, you must modify setup.py and remove the line that sets SQLITE_OMIT_LOAD_EXTENSION.