sqlite3
--- SQLite 数据库 DB-API 2.0 接口模块P
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 H"aring 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。
- https://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。
模块函数和常量P
-
sqlite3.
version
P 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
P 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
P 使用中的 SQLite 库的版本号,是一个字符串。
-
sqlite3.
sqlite_version_info
P 使用中的 SQLite 库的版本号,是一个整数组成的元组。
-
sqlite3.
PARSE_DECLTYPES
P 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
P 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])P 连接 SQLite 数据库 database。默认返回
Connection
对象,除非使用了自定义的 factory 参数。database 是准备打开的数据库文件的路径(绝对路径或相对于当前目录的相对路径),它是 path-like object。你也可以用
":memory:"
在内存中打开一个数据库。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。
在 3.7 版更改: database 现在可以是一个 path-like object 对象了,不仅仅是字符串。
-
sqlite3.
register_converter
(typename, callable)P 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)P 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)P 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()
连接对象(Connection)P
-
class
sqlite3.
Connection
P SQLite 数据库连接对象有如下的属性和方法:
-
isolation_level
P 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 控制事务。
-
commit
()P 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。
-
execute
(sql[, parameters])P 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])P 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)P 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)P 创建一个可以在 SQL 语句中使用的自定义函数,其中参数 name 为 SQL 语句中使用的函数名,num_params 是这个函数接受的参数个数(如果 num_params 为 -1,那这个函数可以接受任意数量的参数),最后一个参数 func 是作为 SQL 函数调用的一个 Python 可调用对象。
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]) con.close()
-
create_aggregate
(name, num_params, aggregate_class)P 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]) con.close()
-
create_collation
(name, callable)P 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
()P 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。
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)P 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)P 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)P 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) con.close()
-
load_extension
(path)P 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
P 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"]) con.close()
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
P 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" con.close()
-
total_changes
P 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
()P 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) con.close()
-
backup
(target, *, pages=0, progress=None, name="main", sleep=0.250)P 即使在 SQLite 数据库被其他客户端访问时,或者同时由同一连接访问,该方法也会对其进行备份。 该副本将写入强制参数 target,该参数必须是另一个
Connection
实例。默认情况下,或者当 pages 为
0
或负整数时,整个数据库将在一个步骤中复制;否则该方法一次循环复制 pages 规定数量的页面。If progress is specified, it must either be
None
or a callable object that will be executed at each iteration with three integer arguments, respectively the status of the last iteration, the remaining number of pages still to be copied and the total number of pages.The name argument specifies the database name that will be copied: it must be a string containing either
"main"
, the default, to indicate the main database,"temp"
to indicate the temporary database or the name specified after theAS
keyword in anATTACH DATABASE
statement for an attached database.The sleep argument specifies the number of seconds to sleep by between successive attempts to backup remaining pages, can be specified either as an integer or a floating point value.
示例一,将现有数据库复制到另一个数据库中:
import sqlite3 def progress(status, remaining, total): print(f'Copied {total-remaining} of {total} pages...') con = sqlite3.connect('existing_db.db') bck = sqlite3.connect('backup.db') with bck: con.backup(bck, pages=1, progress=progress) bck.close() con.close()
示例二,将现有数据库复制到临时副本中:
import sqlite3 source = sqlite3.connect('existing_db.db') dest = sqlite3.connect(':memory:') source.backup(dest)
可用性:SQLite 3.6.11 或以上版本
3.7 新版功能.
-
Cursor 对象P
-
class
sqlite3.
Cursor
P Cursor
游标实例具有以下属性和方法。-
execute
(sql[, parameters])P 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()) con.close()
execute()
will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise aWarning
. Useexecutescript()
if you want to execute multiple SQL statements with one call.
-
executemany
(sql, seq_of_parameters)P 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()) con.close()
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()) con.close()
-
executescript
(sql_script)P 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 ); """) con.close()
-
fetchone
()P 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)P 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
()P 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
()P 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
P Although the
Cursor
class of thesqlite3
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 intorowcount
.As required by the Python DB API Spec, the
rowcount
attribute "is -1 in case noexecuteXX()
has been performed on the cursor or the rowcount of the last operation is not determinable by the interface". This includesSELECT
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 aDELETE FROM table
without any condition.
-
lastrowid
P This read-only attribute provides the rowid of the last modified row. It is only set if you issued an
INSERT
or aREPLACE
statement using theexecute()
method. For operations other thanINSERT
orREPLACE
or whenexecutemany()
is called,lastrowid
is set toNone
.If the
INSERT
orREPLACE
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
P 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
P 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
P This read-only attribute provides the SQLite database
Connection
used by theCursor
object. ACursor
object created by callingcon.cursor()
will have aconnection
attribute that refers to con:>>> con = sqlite3.connect(":memory:") >>> cur = con.cursor() >>> cur.connection == con True
-
行对象*Row*P
-
class
sqlite3.
Row
P A
Row
instance serves as a highly optimizedrow_factory
forConnection
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
()P 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
异常P
-
exception
sqlite3.
DatabaseError
P Exception raised for errors that are related to the database.
-
exception
sqlite3.
IntegrityError
P 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
P 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
P 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
P 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 ofDatabaseError
.
SQLite 与 Python 类型P
概述P
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 |
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这是SQLite类型默认转换为Python类型的方式:
SQLite 类型 |
Python 类型 |
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取决于 |
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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.
Using adapters to store additional Python types in SQLite databasesP
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.
让对象自行调整P
如果自己编写类,这是一种很好的方法。假设有这样的类::
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])
con.close()
注册可调用的适配器P
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])
con.close()
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])
con.close()
将SQLite 值转换为自定义Python 类型P
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.
输入转换器。
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:
隐式的声明类型
显式的通过列名
Both ways are described in section 模块函数和常量, in the entries
for the constants PARSE_DECLTYPES
and PARSE_COLNAMES
.
下面的示例说明了这两种方法。
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()
默认适配器和转换器P
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.
下面的示例演示了这一点。
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]))
con.close()
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.
控制事务P
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.
有效使用 sqlite3
P
使用快捷方式P
使用 Connection
对象的非标准 execute()
, executemany()
和 executescript()
方法,可以更简洁地编写代码,因为不必显式创建(通常是多余的) Cursor
对象。相反, Cursor
对象是隐式创建的,这些快捷方法返回游标对象。这样,只需对 Connection
对象调用一次,就能直接执行 SELECT
语句并遍历对象。
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")
# close is not a shortcut method and it's not called automatically,
# so the connection object should be closed manually
con.close()
通过名称而不是索引访问索引P
sqlite3
模块的一个有用功能是内置的 sqlite3.Row
类,它被设计用作行对象的工厂。
该类的行装饰器可以用索引(如元组)和不区分大小写的名称访问:
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"]
con.close()
使用连接作为上下文管理器P
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")
# Connection object used as context manager only commits or rollbacks transactions,
# so the connection object should be closed manually
con.close()
常见问题P
多线程P
较老版本的 SQLite 在共享线程之间存在连接问题。这就是Python模块不允许线程之间共享连接和游标的原因。如果仍然尝试这样做,则在运行时会出现异常。
唯一的例外是调用 interrupt()
方法,该方法仅在从其他线程进行调用时才有意义。
备注