# 12.6. `sqlite3` — SQLite 数据库 DB-API 2.0 接口模块

源代码： Lib/sqlite3/

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)

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

## 12.6.1. 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, uri])

  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）。

  isolation_level 参数，请查看 `Connection` 对象的 `isolation_level` 属性。

  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，check_same_thread 为 `True`，只有当前的线程可以使用该连接。 如果设置为 `False`，则多个线程可以共享返回的连接。 当多个线程使用同一个连接的时候，用户应该把写操作进行序列化，以避免数据损坏。

  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。

  如果 uri 为真，则 database 被解释为 URI。 它允许您指定选项。 例如，以只读模式打开数据库：

      db = sqlite3.connect('file:path/to/database?mode=ro', uri=True)

  有关此功能的更多信息，包括已知选项的列表，可以在 ` SQLite URI 文档 <https://www.sqlite.org/uri.html>`_ 中找到。

  在 3.4 版更改: 增加了 uri 参数。

`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)

  注册一个回调对象 callable，用来转换自定义Python类型为一个 SQLite 支持的类型。 这个回调对象 callable 仅接受一个 Python 值作为参数，而且必须返回以下某个类型的值：int，float，str 或 bytes。

`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 = 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。

## 12.6.2. 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`

    获取或设置当前默认的隔离级别。 表示自动提交模式的 `None` 以及 “DEFERRED”, “IMMEDIATE” 或 “EXCLUSIVE” 其中之一。 详细描述请参阅 Controlling Transactions。

  `in_transaction`

    如果是在活动事务中（还没有提交改变），返回 `True`，否则，返回 `False`。它是一个只读属性。

    3.2 新版功能.

  `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])

    这是一个非标准的快捷方法，它会调用 `cursor()` 方法来创建一个游标对象，并使用给定的 parameters 参数来调用游标对象的 `execute()` 方法，最后返回这个游标对象。

  `executemany`(sql[, parameters])

    这是一个非标准的快捷方法，它会调用 `cursor()` 方法来创建一个游标对象，并使用给定的 parameters 参数来调用游标对象的 `executemany()` 方法，最后返回这个游标对象。

  `executescript`(sql_script)

    这是一个非标准的快捷方法，它会调用 `cursor()` 方法来创建一个游标对象，并使用给定的 sql_script 参数来调用游标对象的 `executescript()` 方法，最后返回这个游标对象。

  `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 (if num_params is -1, the function may take any number of arguments), and func is a Python callable that is called as the SQL function.

    此函数可返回任何 SQLite 所支持的类型: bytes, str, int, float 和 `None`。

    示例:

        import sqlite3
        import hashlib

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

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

  `create_aggregate`(name, num_params, aggregate_class)

    创建一个自定义的聚合函数。

    参数中 aggregate_class 类必须实现两个方法：`step` 和 `finalize`。`step` 方法接受 num_params 个参数（如果 num_params 为 -1，那么这个函数可以接受任意数量的参数）；`finalize` 方法返回最终的聚合结果。

    `finalize` 方法可以返回任何 SQLite 支持的类型：bytes，str，int，float 和 `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。

    以下示例显示了使用“错误方式”进行排序的自定义排序规则：

        import sqlite3

        def collate_reverse(string1, string2):
            if string1 == string2:
                return 0
            elif string1 < string2:
                return 1
            else:
                return -1

        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。

    回调的第一个参数表示要授权的操作类型。 第二个和第三个参数将是参数或 `None`，具体取决于第一个参数的值。 第 4 个参数是数据库的名称（“main”，“temp”等），如果需要的话。 第 5 个参数是负责访问尝试的最内层触发器或视图的名称，或者如果此访问尝试直接来自输入 SQL 代码，则为 `None`。

    请参阅 SQLite 文档，了解第一个参数的可能值以及第二个和第三个参数的含义，具体取决于第一个参数。 所有必需的常量都可以在 `sqlite3` 模块中找到。

  `set_progress_handler`(handler, n)

    此例程注册回调。 对SQLite虚拟机的每个多指令调用回调。 如果要在长时间运行的操作期间从SQLite调用（例如更新用户界面），这非常有用。

    如果要清除以前安装的任何进度处理程序，调用该方法时请将 handler 参数设置为 `None`。

    从处理函数返回非零值将终止当前正在执行的查询并导致它引发 `OperationalError` 异常。

  `set_trace_callback`(trace_callback)

    为每个 SQLite 后端实际执行的 SQL 语句注册要调用的 trace_callback。

    传递给回调的唯一参数是正在执行的语句（作为字符串）。 回调的返回值将被忽略。 请注意，后端不仅运行传递给 `Cursor.execute()` 方法的语句。 其他来源包括 Python 模块的事务管理和当前数据库中定义的触发器的执行。

    将传入的 trace_callback 设为 `None` 将禁用跟踪回调。

    3.3 新版功能.

  `enable_load_extension`(enabled)

    此例程允许/禁止SQLite引擎从共享库加载SQLite扩展。 SQLite扩展可以定义新功能，聚合或全新的虚拟表实现。 一个众所周知的扩展是与SQLite一起分发的全文搜索扩展。

    默认情况下禁用可加载扩展。 见 1.

    3.2 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)

    此例程从共享库加载SQLite扩展。 在使用此例程之前，必须使用 `enable_load_extension()` 启用扩展加载。

    默认情况下禁用可加载扩展。 见 1.

    3.2 新版功能.

  `row_factory`

    您可以将此属性更改为可接受游标和原始行作为元组的可调用对象，并将返回实际结果行。 这样，您可以实现更高级的返回结果的方法，例如返回一个可以按名称访问列的对象。

    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"])

    如果返回一个元组是不够的，并且你想要对列进行基于名称的访问，你应该考虑将 `row_factory` 设置为高度优化的 `sqlite3.Row` 类型。 `Row` 提供基于索引和不区分大小写的基于名称的访问，几乎没有内存开销。 它可能比您自己的基于字典的自定义方法甚至基于 db_row 的解决方案更好。

  `text_factory`

    使用此属性可以控制为 `TEXT` 数据类型返回的对象。 默认情况下，此属性设置为 `str` 和 `sqlite3` 模块将返回 `TEXT` 的 Unicode 对象。 如果要返回字节串，可以将其设置为 `bytes`。

    您还可以将其设置为接受单个 bytestring 参数的任何其他可调用对象，并返回结果对象。

    请参阅以下示例代码以进行说明：

        import sqlite3

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

        AUSTRIA = "\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 = bytes
        cur.execute("select ?", (AUSTRIA,))
        row = cur.fetchone()
        assert type(row[0]) is bytes
        # 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 appends "foo" to all strings
        con.text_factory = lambda x: x.decode("utf-8") + "foo"
        cur.execute("select ?", ("bar",))
        row = cur.fetchone()
        assert row[0] == "barfoo"

  `total_changes`

    返回自打开数据库连接以来已修改，插入或删除的数据库行的总数。

  `iterdump`()

    返回以SQL文本格式转储数据库的迭代器。 保存内存数据库以便以后恢复时很有用。 此函数提供与 sqlite3 shell 中的 `.dump` 命令相同的功能。

    示例:

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

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

## 12.6.3. Cursor 对象

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 seq_of_parameters. 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.ascii_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 an instance of `str`.

    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.

  `close`()

    Close the cursor now (rather than whenever `__del__` is called).

    The cursor will be unusable from this point forward; a `ProgrammingError` exception will be raised if any operation is attempted with the cursor.

  `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` or a `REPLACE` statement using the `execute()` method. For operations other than `INSERT` or `REPLACE` or when `executemany()` is called, `lastrowid` is set to `None`.

    If the `INSERT` or `REPLACE` statement failed to insert the previous successful rowid is returned.

    在 3.6 版更改: 增加了 `REPLACE` 语句的支持。

  `arraysize`

    Read/write attribute that controls the number of rows returned by `fetchmany()`. The default value is 1 which means a single row would be fetched per call.

  `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

## 12.6.4. 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.

  `keys`()

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

  在 3.5 版更改: Added support of slicing.

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)
    <class 'sqlite3.Row'>
    >>> tuple(r)
    ('2006-01-05', 'BUY', 'RHAT', 100.0, 35.14)
    >>> len(r)
    5
    >>> r[2]
    '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

## 12.6.5. 异常

exception `sqlite3.``Warning`

  `Exception` 的一个子类。

exception `sqlite3.``Error`

  此模块中其他异常的基类。 它是 `Exception` 的一个子类。

exception `sqlite3.``DatabaseError`

  Exception raised for errors that are related to the database.

exception `sqlite3.``IntegrityError`

  Exception raised when the relational integrity of the database is affected, e.g. a foreign key check fails. It is a subclass of `DatabaseError`.

exception `sqlite3.``ProgrammingError`

  Exception raised for programming errors, e.g. table not found or already exists, syntax error in the SQL statement, wrong number of parameters specified, etc. It is a subclass of `DatabaseError`.

exception `sqlite3.``OperationalError`

  Exception raised for errors that are related to the database’s operation and not necessarily under the control of the programmer, e.g. an unexpected disconnect occurs, the data source name is not found, a transaction could not be processed, etc. It is a subclass of `DatabaseError`.

exception `sqlite3.``NotSupportedError`

  Exception raised in case a method or database API was used which is not supported by the database, e.g. calling the `rollback()` method on a connection that does not support transaction or has transactions turned off. It is a subclass of `DatabaseError`.

## 12.6.6. SQLite 与 Python 类型

### 12.6.6.1. 概述

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

因此可以将以下Python类型发送到SQLite而不会出现任何问题：

Python 类型 | SQLite 类型
--- | ---
`None` | `NULL`
`int` | `INTEGER`
`float` | `REAL`
`str` | `TEXT`
`bytes` | `BLOB`

这是SQLite类型默认转换为Python类型的方式：

SQLite 类型 | Python 类型
--- | ---
`NULL` | `None`
`INTEGER` | `int`
`REAL` | `float`
`TEXT` | 取决于 `text_factory` , 默认为 `str`
`BLOB` | `bytes`

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.

### 12.6.6.2. 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, float, str, bytes.

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

#### 12.6.6.2.1. 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:
        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:
        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])

#### 12.6.6.2.2. 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()`.

    import sqlite3

    class Point:
        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
    import 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])

### 12.6.6.3. 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 `bytes` object, no matter under which data type you sent the value to SQLite.

    def convert_point(s):
        x, y = map(float, s.split(b";"))
        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:
        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)).encode('ascii')

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

### 12.6.6.4. 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.

## 12.6.7. Controlling Transactions

The underlying `sqlite3` library operates in `autocommit` mode by default, but the Python `sqlite3` module by default does not.

`autocommit` mode means that statements that modify the database take effect immediately. A `BEGIN` or `SAVEPOINT` statement disables `autocommit` mode, and a `COMMIT`, a `ROLLBACK`, or a `RELEASE` that ends the outermost transaction, turns `autocommit` mode back on.

The Python `sqlite3` module by default issues a `BEGIN` statement implicitly before a Data Modification Language (DML) statement (i.e. `INSERT`/`UPDATE`/`DELETE`/`REPLACE`).

You can control which kind of `BEGIN` statements `sqlite3` implicitly executes via the isolation_level parameter to the `connect()` call, or via the `isolation_level` property of connections. If you specify no isolation_level, a plain `BEGIN` is used, which is equivalent to specifying `DEFERRED`. Other possible values are `IMMEDIATE` and `EXCLUSIVE`.

You can disable the `sqlite3` module’s implicit transaction management by setting `isolation_level` to `None`. This will leave the underlying `sqlite3` library operating in `autocommit` mode. You can then completely control the transaction state by explicitly issuing `BEGIN`, `ROLLBACK`, `SAVEPOINT`, and `RELEASE` statements in your code.

在 3.6 版更改: `sqlite3` used to implicitly commit an open transaction before DDL statements. This is no longer the case.

## 12.6.8. Using `sqlite3` efficiently

### 12.6.8.1. 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")

### 12.6.8.2. 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"]

### 12.6.8.3. 使用连接作为上下文管理器

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")

## 12.6.9. 常见问题

### 12.6.9.1. 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)

  sqlite3 模块默认没有构建可加载扩展支持，因为有一些平台带有不支持这个特性的 SQLite 库（特别是 Mac OS X）。要获得可加载扩展的支持，那么在编译配置的时候必须指定 –enable-loadable-sqlite-extensions 选项。