<ruby id="bdb3f"></ruby>

    <p id="bdb3f"><cite id="bdb3f"></cite></p>

      <p id="bdb3f"><cite id="bdb3f"><th id="bdb3f"></th></cite></p><p id="bdb3f"></p>
        <p id="bdb3f"><cite id="bdb3f"></cite></p>

          <pre id="bdb3f"></pre>
          <pre id="bdb3f"><del id="bdb3f"><thead id="bdb3f"></thead></del></pre>

          <ruby id="bdb3f"><mark id="bdb3f"></mark></ruby><ruby id="bdb3f"></ruby>
          <pre id="bdb3f"><pre id="bdb3f"><mark id="bdb3f"></mark></pre></pre><output id="bdb3f"></output><p id="bdb3f"></p><p id="bdb3f"></p>

          <pre id="bdb3f"><del id="bdb3f"><progress id="bdb3f"></progress></del></pre>

                <ruby id="bdb3f"></ruby>

                ThinkChat2.0新版上線,更智能更精彩,支持會話、畫圖、視頻、閱讀、搜索等,送10W Token,即刻開啟你的AI之旅 廣告
                ### 導航 - [索引](../genindex.xhtml "總目錄") - [模塊](../py-modindex.xhtml "Python 模塊索引") | - [下一頁](archiving.xhtml "數據壓縮和存檔") | - [上一頁](dbm.xhtml "dbm --- Interfaces to Unix "databases"") | - ![](https://box.kancloud.cn/a721fc7ec672275e257bbbfde49a4d4e_16x16.png) - [Python](https://www.python.org/) ? - zh\_CN 3.7.3 [文檔](../index.xhtml) ? - [Python 標準庫](index.xhtml) ? - [數據持久化](persistence.xhtml) ? - $('.inline-search').show(0); | # [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") --- SQLite 數據庫 DB-API 2.0 接口模塊 **源代碼:** [Lib/sqlite3/](https://github.com/python/cpython/tree/3.7/Lib/sqlite3/) \[https://github.com/python/cpython/tree/3.7/Lib/sqlite3/\] - - - - - - SQLite 是一個C語言庫,它可以提供一種輕量級的基于磁盤的數據庫,這種數據庫不需要獨立的服務器進程,也允許需要使用一種非標準的 SQL 查詢語言來訪問它。一些應用程序可以使用 SQLite 作為內部數據存儲。可以用它來創建一個應用程序原型,然后再遷移到更大的數據庫,比如 PostgreSQL 或 Oracle。 sqlite3 模塊是由 Gerhard H?ring 編寫。它提供了符合 DB-API 2.0 規范的接口,這個規范是 [**PEP 249**](https://www.python.org/dev/peps/pep-0249) \[https://www.python.org/dev/peps/pep-0249\]。 要使用這個模塊,必須先創建一個 [`Connection`](#sqlite3.Connection "sqlite3.Connection") 對象,它代表數據庫。下面例子中,數據將存儲在 `example.db` 文件中: ``` import sqlite3 conn = sqlite3.connect('example.db') ``` 你也可以使用 `:memory:` 來創建一個內存中的數據庫 當有了 [`Connection`](#sqlite3.Connection "sqlite3.Connection") 對象后,你可以創建一個 [`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") 游標對象,然后調用它的 [`execute()`](#sqlite3.Cursor.execute "sqlite3.Cursor.execute") 方法來執行 SQL 語句: ``` 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() ``` 這些數據被持久化保存了,而且可以在之后的會話中使用它們: ``` import sqlite3 conn = sqlite3.connect('example.db') c = conn.cursor() ``` 通常你的 SQL 操作需要使用一些 Python 變量的值。你不應該使用 Python 的字符串操作來創建你的查詢語句,因為那樣做不安全;它會使你的程序容易受到 SQL 注入攻擊(在 <https://xkcd.com/327/> 上有一個搞笑的例子,看看有什么后果) 推薦另外一種方法:使用 DB-API 的參數替換。在你的 SQL 語句中,使用 `?` 占位符來代替值,然后把對應的值組成的元組做為 [`execute()`](#sqlite3.Cursor.execute "sqlite3.Cursor.execute") 方法的第二個參數。(其他數據庫可能會使用不同的占位符,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) ``` 要在執行 SELECT 語句后獲取數據,你可以把游標作為 [iterator](../glossary.xhtml#term-iterator),然后調用它的 [`fetchone()`](#sqlite3.Cursor.fetchone "sqlite3.Cursor.fetchone") 方法來獲取一條匹配的行,也可以調用 [`fetchall()`](#sqlite3.Cursor.fetchall "sqlite3.Cursor.fetchall") 來得到包含多個匹配行的列表。 下面是一個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) ``` 參見 <https://github.com/ghaering/pysqlite>pysqlite的主頁 -- sqlite3 在外部使用 “pysqlite” 名字進行開發。 <https://www.sqlite.org>SQLite的主頁;它的文檔詳細描述了它所支持的 SQL 方言的語法和可用的數據類型。 <https://www.w3schools.com/sql/>學習 SQL 語法的教程、參考和例子。 [**PEP 249**](https://www.python.org/dev/peps/pep-0249) \[https://www.python.org/dev/peps/pep-0249\] - DB-API 2.0 規范Marc-André Lemburg 寫的 PEP。 ## 模塊函數和常量 `sqlite3.``version`這個模塊的版本號,是一個字符串。不是 SQLite 庫的版本號。 `sqlite3.``version_info`這個模塊的版本號,是一個由整數組成的元組。不是 SQLite 庫的版本號。 `sqlite3.``sqlite_version`使用中的 SQLite 庫的版本號,是一個字符串。 `sqlite3.``sqlite_version_info`使用中的 SQLite 庫的版本號,是一個整數組成的元組。 `sqlite3.``PARSE_DECLTYPES`這個常量可以作為 [`connect()`](#sqlite3.connect "sqlite3.connect") 函數的 *detect\_types* 參數。 設置這個參數后,[`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 模塊將解析它返回的每一列申明的類型。它會申明的類型的第一個單詞,比如“integer primary key”,它會解析出“integer”,再比如“number(10)”,它會解析出“number”。然后,它會在轉換器字典里查找那個類型注冊的轉換器函數,并調用它。 `sqlite3.``PARSE_COLNAMES`這個常量可以作為 [`connect()`](#sqlite3.connect "sqlite3.connect") 函數的 *detect\_types* 參數。 設置這個參數后,SQLite 接口將解析它返回的每一列的列名。它會在其中查找 \[mytype\] 這個形式的字符串,然后用‘mytype’來決定那個列的類型。它會嘗試在轉換器字典中查找‘mytype’鍵對應的轉換器函數,然后用這個轉換器函數返回的值來做為列的類型。在 [`Cursor.description`](#sqlite3.Cursor.description "sqlite3.Cursor.description") 中找到的列名僅僅是列名的第一個單詞,比如你在 SQL 中使用 `'as "x [datetime]"'`,然后它會解析出第一個空白字符前的所有字符來作為列名:列名就是“x”。 `sqlite3.``connect`(*database*\[, *timeout*, *detect\_types*, *isolation\_level*, *check\_same\_thread*, *factory*, *cached\_statements*, *uri*\])連接 SQLite 數據庫 *database*。默認返回 [`Connection`](#sqlite3.Connection "sqlite3.Connection") 對象,除非使用了自定義的 *factory* 參數。 *database* 是準備打開的數據庫文件的路徑(絕對路徑或相對于當前目錄的相對路徑),它是 [path-like object](../glossary.xhtml#term-path-like-object)。你也可以用 `":memory:"` 在內存中打開一個數據庫。 當一個數據庫被多個連接訪問的時候,如果其中一個進程修改這個數據庫,在這個事務提交之前,這個 SQLite 數據庫將會被一直鎖定。*timeout* 參數指定了這個連接等待鎖釋放的超時時間,超時之后會引發一個異常。這個超時時間默認是 5.0(5秒)。 *isolation\_level* 參數,請查看 [`Connection`](#sqlite3.Connection "sqlite3.Connection") 對象的 [`isolation_level`](#sqlite3.Connection.isolation_level "sqlite3.Connection.isolation_level") 屬性。 SQLite 原生只支持5種類型:TEXT,INTEGER,REAL,BLOB 和 NULL。如果你想用其它類型,你必須自己添加相應的支持。使用 *detect\_types* 參數和模塊級別的 [`register_converter()`](#sqlite3.register_converter "sqlite3.register_converter") 函數注冊\*\*轉換器\*\* 可以簡單的實現。 *detect\_types* 默認為0(即關閉,沒有類型檢測)。你也可以組合 [`PARSE_DECLTYPES`](#sqlite3.PARSE_DECLTYPES "sqlite3.PARSE_DECLTYPES") 和 [`PARSE_COLNAMES`](#sqlite3.PARSE_COLNAMES "sqlite3.PARSE_COLNAMES") 來開啟類型檢測。 默認情況下,*check\_same\_thread* 為 [`True`](constants.xhtml#True "True"),只有當前的線程可以使用該連接。 如果設置為 [`False`](constants.xhtml#False "False"),則多個線程可以共享返回的連接。 當多個線程使用同一個連接的時候,用戶應該把寫操作進行序列化,以避免數據損壞。 默認情況下,當調用 connect 方法的時候,[`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 模塊使用了它的 [`Connection`](#sqlite3.Connection "sqlite3.Connection") 類。當然,你也可以創建 [`Connection`](#sqlite3.Connection "sqlite3.Connection") 類的子類,然后創建提供了 *factory* 參數的 [`connect()`](#sqlite3.connect "sqlite3.connect") 方法。 詳情請查閱當前手冊的 [SQLite 與 Python 類型](#sqlite3-types) 部分。 [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 模塊在內部使用語句緩存來避免 SQL 解析開銷。 如果要顯式設置當前連接可以緩存的語句數,可以設置 *cached\_statements* 參數。 當前實現的默認值是緩存100條語句。 如果 *uri* 為真,則 *database* 被解釋為 URI。 它允許您指定選項。 例如,以只讀模式打開數據庫: ``` db = sqlite3.connect('file:path/to/database?mode=ro', uri=True) ``` 有關此功能的更多信息,包括已知選項的列表,可以在 ` SQLite URI 文檔 <<https://www.sqlite.org/uri.html>>`\_ 中找到。 在 3.4 版更改: 增加了 *uri* 參數。 在 3.7 版更改: *database* 現在可以是一個 [path-like object](../glossary.xhtml#term-path-like-object) 對象了,不僅僅是字符串。 `sqlite3.``register_converter`(*typename*, *callable*)注冊一個回調對象 *callable*, 用來轉換數據庫中的字節串為自定的 Python 類型。所有類型為 *typename* 的數據庫的值在轉換時,都會調用這個回調對象。通過指定 [`connect()`](#sqlite3.connect "sqlite3.connect") 函數的 *detect-types* 參數來設置類型檢測的方式。注意,*typename* 與查詢語句中的類型名進行匹配時不區分大小寫。 `sqlite3.``register_adapter`(*type*, *callable*)注冊一個回調對象 *callable*,用來轉換自定義Python類型為一個 SQLite 支持的類型。 這個回調對象 *callable* 僅接受一個 Python 值作為參數,而且必須返回以下某個類型的值:int,float,str 或 bytes。 `sqlite3.``complete_statement`(*sql*)如果字符串 *sql* 包含一個或多個完整的 SQL 語句(以分號結束)則返回 [`True`](constants.xhtml#True "True")。它不會驗證 SQL 語法是否正確,僅會驗證字符串字面上是否完整,以及是否以分號結束。 它可以用來構建一個 SQLite shell,下面是一個例子: ``` # 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*)默認情況下,您不會獲得任何用戶定義函數中的回溯消息,比如聚合,轉換器,授權器回調等。如果要調試它們,可以設置 *flag* 參數為 `True` 并調用此函數。 之后,回調中的回溯信息將會輸出到 `sys.stderr`。 再次使用 [`False`](constants.xhtml#False "False") 來禁用該功能。 ## 連接對象(Connection) *class* `sqlite3.``Connection`SQLite 數據庫連接對象有如下的屬性和方法: `isolation_level`獲取或設置當前默認的隔離級別。 表示自動提交模式的 [`None`](constants.xhtml#None "None") 以及 "DEFERRED", "IMMEDIATE" 或 "EXCLUSIVE" 其中之一。 詳細描述請參閱 [Controlling Transactions](#sqlite3-controlling-transactions)。 `in_transaction`如果是在活動事務中(還沒有提交改變),返回 [`True`](constants.xhtml#True "True"),否則,返回 [`False`](constants.xhtml#False "False")。它是一個只讀屬性。 3\.2 新版功能. `cursor`(*factory=Cursor*)這個方法接受一個可選參數 *factory*,如果要指定這個參數,它必須是一個可調用對象,而且必須返回 [`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") 類的一個實例或者子類。 `commit`()這個方法提交當前事務。如果沒有調用這個方法,那么從上一次提交 `commit()` 以來所有的變化在其他數據庫連接上都是不可見的。如果你往數據庫里寫了數據,但是又查詢不到,請檢查是否忘記了調用這個方法。 `rollback`()這個方法回滾從上一次調用 [`commit()`](#sqlite3.Connection.commit "sqlite3.Connection.commit") 以來所有數據庫的改變。 `close`()關閉數據庫連接。注意,它不會自動調用 [`commit()`](#sqlite3.Connection.commit "sqlite3.Connection.commit") 方法。如果在關閉數據庫連接之前沒有調用 [`commit()`](#sqlite3.Connection.commit "sqlite3.Connection.commit"),那么你的修改將會丟失! `execute`(*sql*\[, *parameters*\])這是一個非標準的快捷方法,它會調用 [`cursor()`](#sqlite3.Connection.cursor "sqlite3.Connection.cursor") 方法來創建一個游標對象,并使用給定的 *parameters* 參數來調用游標對象的 [`execute()`](#sqlite3.Cursor.execute "sqlite3.Cursor.execute") 方法,最后返回這個游標對象。 `executemany`(*sql*\[, *parameters*\])這是一個非標準的快捷方法,它會調用 [`cursor()`](#sqlite3.Connection.cursor "sqlite3.Connection.cursor") 方法來創建一個游標對象,并使用給定的 *parameters* 參數來調用游標對象的 [`executemany()`](#sqlite3.Cursor.executemany "sqlite3.Cursor.executemany") 方法,最后返回這個游標對象。 `executescript`(*sql\_script*)這是一個非標準的快捷方法,它會調用 [`cursor()`](#sqlite3.Connection.cursor "sqlite3.Connection.cursor") 方法來創建一個游標對象,并使用給定的 *sql\_script* 參數來調用游標對象的 [`executescript()`](#sqlite3.Cursor.executescript "sqlite3.Cursor.executescript") 方法,最后返回這個游標對象。 `create_function`(*name*, *num\_params*, *func*)創建一個可以在 SQL 語句中使用的自定義函數,其中參數 *name* 為 SQL 語句中使用的函數名,*num\_params* 是這個函數接受的參數個數(如果 *num\_params* 為 -1,那這個函數可以接受任意數量的參數),最后一個參數 *func* 是作為 SQL 函數調用的一個 Python 可調用對象。 此函數可返回任何 SQLite 所支持的類型: 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*)創建一個自定義的聚合函數。 參數中 *aggregate\_class* 類必須實現兩個方法:`step` 和 `finalize`。`step` 方法接受 *num\_params* 個參數(如果 *num\_params* 為 -1,那么這個函數可以接受任意數量的參數);`finalize` 方法返回最終的聚合結果。 `finalize` 方法可以返回任何 SQLite 支持的類型: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*)使用 *name* 和 *callable* 創建排序規則。這個 *callable* 接受兩個字符串對象,如果第一個小于第二個則返回 -1, 如果兩個相等則返回 0,如果第一個大于第二個則返回 1。注意,這是用來控制排序的(SQL 中的 ORDER BY),所以它不會影響其它的 SQL 操作。 注意,這個 *callable* 可調用對象會把它的參數作為 Python 字節串,通常會以 UTF-8 編碼格式對它進行編碼。 The following example shows a custom collation that sorts "the wrong way": ``` 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() ``` 要移除一個排序規則,需要調用 `create_collation` 并設置 callable 參數為 `None`。 ``` con.create_collation("reverse", None) ``` `interrupt`()可以從不同的線程調用這個方法來終止所有查詢操作,這些查詢操作可能正在連接上執行。此方法調用之后, 查詢將會終止,而且查詢的調用者會獲得一個異常。 `set_authorizer`(*authorizer\_callback*)此方法注冊一個授權回調對象。每次在訪問數據庫中某個表的某一列的時候,這個回調對象將會被調用。如果要允許訪問,則返回 `SQLITE_OK`,如果要終止整個 SQL 語句,則返回 `SQLITE_DENY`,如果這一列需要當做 NULL 值處理,則返回 `SQLITE_IGNORE`。這些常量可以在 [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 模塊中找到。 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`](constants.xhtml#None "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`](constants.xhtml#None "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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 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`](constants.xhtml#None "None") for *handler*. Returning a non-zero value from the handler function will terminate the currently executing query and cause it to raise an [`OperationalError`](#sqlite3.OperationalError "sqlite3.OperationalError")exception. `set_trace_callback`(*trace\_callback*)Registers *trace\_callback* to be called for each SQL statement that is actually executed by the SQLite backend. The only argument passed to the callback is the statement (as string) that is being executed. The return value of the callback is ignored. Note that the backend does not only run statements passed to the [`Cursor.execute()`](#sqlite3.Cursor.execute "sqlite3.Cursor.execute")methods. Other sources include the transaction management of the Python module and the execution of triggers defined in the current database. Passing [`None`](constants.xhtml#None "None") as *trace\_callback* will disable the trace callback. 3\.3 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](#f1). 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*)This routine loads a SQLite extension from a shared library. You have to enable extension loading with [`enable_load_extension()`](#sqlite3.Connection.enable_load_extension "sqlite3.Connection.enable_load_extension") before you can use this routine. Loadable extensions are disabled by default. See [1](#f1). 3\.2 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"]) con.close() ``` If returning a tuple doesn't suffice and you want name-based access to columns, you should consider setting [`row_factory`](#sqlite3.Connection.row_factory "sqlite3.Connection.row_factory") to the highly-optimized [`sqlite3.Row`](#sqlite3.Row "sqlite3.Row") type. [`Row`](#sqlite3.Row "sqlite3.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 [`str`](stdtypes.xhtml#str "str") and the [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module will return Unicode objects for `TEXT`. If you want to return bytestrings instead, you can set it to [`bytes`](stdtypes.xhtml#bytes "bytes"). 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 = "\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`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. 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*)This method makes a backup of a SQLite database even while it's being accessed by other clients, or concurrently by the same connection. The copy will be written into the mandatory argument *target*, that must be another [`Connection`](#sqlite3.Connection "sqlite3.Connection") instance. By default, or when *pages* is either `0` or a negative integer, the entire database is copied in a single step; otherwise the method performs a loop copying up to *pages* pages at a time. 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 the `AS` keyword in an `ATTACH 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,將現有數據庫復制到另一個數據庫中: ``` 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,將現有數據庫復制到臨時副本中: ``` 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. ## 游標對象\*Cursor\* *class* `sqlite3.``Cursor`[`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") 游標實例具有以下屬性和方法。 `execute`(*sql*\[, *parameters*\])執行SQL語句。 可以是參數化 SQL 語句(即,在 SQL 語句中使用占位符)。[`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 模塊支持兩種占位符:問號(qmark風格)和命名占位符(命名風格)。 以下是兩種風格的示例: ``` 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()`](#sqlite3.Cursor.execute "sqlite3.Cursor.execute") will only execute a single SQL statement. If you try to execute more than one statement with it, it will raise a [`Warning`](#sqlite3.Warning "sqlite3.Warning"). Use [`executescript()`](#sqlite3.Cursor.executescript "sqlite3.Cursor.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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module also allows using an [iterator](../glossary.xhtml#term-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() ``` 這是一個使用生成器 [generator](../glossary.xhtml#term-generator) 的簡短示例: ``` 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*)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`](stdtypes.xhtml#str "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`()Fetches the next row of a query result set, returning a single sequence, or [`None`](constants.xhtml#None "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()`](#sqlite3.Cursor.fetchmany "sqlite3.Cursor.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`](#sqlite3.ProgrammingError "sqlite3.ProgrammingError")exception will be raised if any operation is attempted with the cursor. `rowcount`Although the [`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") class of the [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module implements this attribute, the database engine's own support for the determination of "rows affected"/"rows selected" is quirky. For [`executemany()`](#sqlite3.Cursor.executemany "sqlite3.Cursor.executemany") statements, the number of modifications are summed up into [`rowcount`](#sqlite3.Cursor.rowcount "sqlite3.Cursor.rowcount"). As required by the Python DB API Spec, the [`rowcount`](#sqlite3.Cursor.rowcount "sqlite3.Cursor.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`](#sqlite3.Cursor.rowcount "sqlite3.Cursor.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()`](#sqlite3.Cursor.execute "sqlite3.Cursor.execute") method. For operations other than `INSERT` or `REPLACE` or when [`executemany()`](#sqlite3.Cursor.executemany "sqlite3.Cursor.executemany") is called, [`lastrowid`](#sqlite3.Cursor.lastrowid "sqlite3.Cursor.lastrowid") is set to [`None`](constants.xhtml#None "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` 語句的支持。 `arraysize`Read/write attribute that controls the number of rows returned by [`fetchmany()`](#sqlite3.Cursor.fetchmany "sqlite3.Cursor.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`](constants.xhtml#None "None"). It is set for `SELECT` statements without any matching rows as well. `connection`This read-only attribute provides the SQLite database [`Connection`](#sqlite3.Connection "sqlite3.Connection")used by the [`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") object. A [`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") object created by calling [`con.cursor()`](#sqlite3.Connection.cursor "sqlite3.Connection.cursor") will have a [`connection`](#sqlite3.Cursor.connection "sqlite3.Cursor.connection") attribute that refers to *con*: ``` >>> con = sqlite3.connect(":memory:") >>> cur = con.cursor() >>> cur.connection == con True ``` ## 行對象\*Row\* *class* `sqlite3.``Row`A [`Row`](#sqlite3.Row "sqlite3.Row") instance serves as a highly optimized [`row_factory`](#sqlite3.Connection.row_factory "sqlite3.Connection.row_factory") for [`Connection`](#sqlite3.Connection "sqlite3.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()`](functions.xhtml#len "len"). If two [`Row`](#sqlite3.Row "sqlite3.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`](#sqlite3.Cursor.description "sqlite3.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`](#sqlite3.Row "sqlite3.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 ``` ## 異常 *exception* `sqlite3.``Warning`[`Exception`](exceptions.xhtml#Exception "Exception") 的一個子類。 *exception* `sqlite3.``Error`此模塊中其他異常的基類。 它是 [`Exception`](exceptions.xhtml#Exception "Exception") 的一個子類。 *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`](#sqlite3.DatabaseError "sqlite3.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`](#sqlite3.DatabaseError "sqlite3.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`](#sqlite3.DatabaseError "sqlite3.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()`](#sqlite3.Connection.rollback "sqlite3.Connection.rollback")method on a connection that does not support transaction or has transactions turned off. It is a subclass of [`DatabaseError`](#sqlite3.DatabaseError "sqlite3.DatabaseError"). ## SQLite 與 Python 類型 ### 概述 SQLite 原生支持如下的類型: `NULL`,`INTEGER`,`REAL`,`TEXT`,`BLOB`。 The following Python types can thus be sent to SQLite without any problem: Python 類型 SQLite 類型 [`None`](constants.xhtml#None "None") `NULL` [`int`](functions.xhtml#int "int") `INTEGER` [`float`](functions.xhtml#float "float") `REAL` [`str`](stdtypes.xhtml#str "str") `TEXT` [`bytes`](stdtypes.xhtml#bytes "bytes") `BLOB` This is how SQLite types are converted to Python types by default: SQLite 類型 Python 類型 `NULL` [`None`](constants.xhtml#None "None") `INTEGER` [`int`](functions.xhtml#int "int") `REAL` [`float`](functions.xhtml#float "float") `TEXT` depends on [`text_factory`](#sqlite3.Connection.text_factory "sqlite3.Connection.text_factory"), [`str`](stdtypes.xhtml#str "str") by default `BLOB` [`bytes`](stdtypes.xhtml#bytes "bytes") The type system of the [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module convert SQLite types to different Python types via converters. ### 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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module to adapt a custom Python type to one of the supported ones. #### 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]) con.close() ``` #### 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()`](#sqlite3.register_adapter "sqlite3.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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module has two default adapters for Python's built-in [`datetime.date`](datetime.xhtml#datetime.date "datetime.date") and [`datetime.datetime`](datetime.xhtml#datetime.datetime "datetime.datetime") types. Now let's suppose we want to store [`datetime.datetime`](datetime.xhtml#datetime.datetime "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() ``` ### 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`](stdtypes.xhtml#bytes "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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 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 [模塊函數和常量](#sqlite3-module-contents), in the entries for the constants [`PARSE_DECLTYPES`](#sqlite3.PARSE_DECLTYPES "sqlite3.PARSE_DECLTYPES") and [`PARSE_COLNAMES`](#sqlite3.PARSE_COLNAMES "sqlite3.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() ``` ### 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`](datetime.xhtml#datetime.date "datetime.date") and under the name "timestamp" for [`datetime.datetime`](datetime.xhtml#datetime.datetime "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])) 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. ## Controlling Transactions The underlying `sqlite3` library operates in `autocommit` mode by default, but the Python [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 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`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") implicitly executes via the *isolation\_level* parameter to the [`connect()`](#sqlite3.connect "sqlite3.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-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") 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`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") used to implicitly commit an open transaction before DDL statements. This is no longer the case. ## Using [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") efficiently ### Using shortcut methods Using the nonstandard `execute()`, `executemany()` and `executescript()` methods of the [`Connection`](#sqlite3.Connection "sqlite3.Connection") object, your code can be written more concisely because you don't have to create the (often superfluous) [`Cursor`](#sqlite3.Cursor "sqlite3.Cursor") objects explicitly. Instead, the [`Cursor`](#sqlite3.Cursor "sqlite3.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`](#sqlite3.Connection "sqlite3.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") # close is not a shortcut method and it's not called automatically, # so the connection object should be closed manually con.close() ``` ### Accessing columns by name instead of by index One useful feature of the [`sqlite3`](#module-sqlite3 "sqlite3: A DB-API 2.0 implementation using SQLite 3.x.") module is the built-in [`sqlite3.Row`](#sqlite3.Row "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"] con.close() ``` ### 使用連接作為上下文管理器 連接對象可以用來作為上下文管理器,它可以自動提交或者回滾事務。如果出現異常,事務會被回滾;否則,事務會被提交。 ``` 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() ``` ## 常見問題 ### 多線程 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()`](#sqlite3.Connection.interrupt "sqlite3.Connection.interrupt") method, which only makes sense to call from a different thread. 腳注 1([1](#id1),[2](#id2))sqlite3 模塊默認沒有構建可加載擴展支持,因為有一些平臺帶有不支持這個特性的 SQLite 庫(特別是 Mac OS X)。要獲得可加載擴展的支持,那么在編譯配置的時候必須指定 --enable-loadable-sqlite-extensions 選項。 ### 導航 - [索引](../genindex.xhtml "總目錄") - [模塊](../py-modindex.xhtml "Python 模塊索引") | - [下一頁](archiving.xhtml "數據壓縮和存檔") | - [上一頁](dbm.xhtml "dbm --- Interfaces to Unix "databases"") | - ![](https://box.kancloud.cn/a721fc7ec672275e257bbbfde49a4d4e_16x16.png) - [Python](https://www.python.org/) ? - zh\_CN 3.7.3 [文檔](../index.xhtml) ? - [Python 標準庫](index.xhtml) ? - [數據持久化](persistence.xhtml) ? - $('.inline-search').show(0); | ? [版權所有](../copyright.xhtml) 2001-2019, Python Software Foundation. Python 軟件基金會是一個非盈利組織。 [請捐助。](https://www.python.org/psf/donations/) 最后更新于 5月 21, 2019. [發現了問題](../bugs.xhtml)? 使用[Sphinx](http://sphinx.pocoo.org/)1.8.4 創建。
                  <ruby id="bdb3f"></ruby>

                  <p id="bdb3f"><cite id="bdb3f"></cite></p>

                    <p id="bdb3f"><cite id="bdb3f"><th id="bdb3f"></th></cite></p><p id="bdb3f"></p>
                      <p id="bdb3f"><cite id="bdb3f"></cite></p>

                        <pre id="bdb3f"></pre>
                        <pre id="bdb3f"><del id="bdb3f"><thead id="bdb3f"></thead></del></pre>

                        <ruby id="bdb3f"><mark id="bdb3f"></mark></ruby><ruby id="bdb3f"></ruby>
                        <pre id="bdb3f"><pre id="bdb3f"><mark id="bdb3f"></mark></pre></pre><output id="bdb3f"></output><p id="bdb3f"></p><p id="bdb3f"></p>

                        <pre id="bdb3f"><del id="bdb3f"><progress id="bdb3f"></progress></del></pre>

                              <ruby id="bdb3f"></ruby>

                              哎呀哎呀视频在线观看