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# [`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") |
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- Python文檔內容
- Python 有什么新變化？
- Python 3.7 有什么新變化
- 摘要 - 發布重點
- 新的特性
- 其他語言特性修改
- 新增模塊
- 改進的模塊
- C API 的改變
- 構建的改變
- 性能優化
- 其他 CPython 實現的改變
- 已棄用的 Python 行為
- 已棄用的 Python 模塊、函數和方法
- 已棄用的 C API 函數和類型
- 平臺支持的移除
- API 與特性的移除
- 移除的模塊
- Windows 專屬的改變
- 移植到 Python 3.7
- Python 3.7.1 中的重要變化
- Python 3.7.2 中的重要變化
- Python 3.6 有什么新變化A
- 摘要 - 發布重點
- 新的特性
- 其他語言特性修改
- 新增模塊
- 改進的模塊
- 性能優化
- Build and C API Changes
- 其他改進
- 棄用
- 移除
- 移植到Python 3.6
- Python 3.6.2 中的重要變化
- Python 3.6.4 中的重要變化
- Python 3.6.5 中的重要變化
- Python 3.6.7 中的重要變化
- Python 3.5 有什么新變化
- 摘要 - 發布重點
- 新的特性
- 其他語言特性修改
- 新增模塊
- 改進的模塊
- Other module-level changes
- 性能優化
- Build and C API Changes
- 棄用
- 移除
- Porting to Python 3.5
- Notable changes in Python 3.5.4
- What's New In Python 3.4
- 摘要 - 發布重點
- 新的特性
- 新增模塊
- 改進的模塊
- CPython Implementation Changes
- 棄用
- 移除
- Porting to Python 3.4
- Changed in 3.4.3
- What's New In Python 3.3
- 摘要 - 發布重點
- PEP 405: Virtual Environments
- PEP 420: Implicit Namespace Packages
- PEP 3118: New memoryview implementation and buffer protocol documentation
- PEP 393: Flexible String Representation
- PEP 397: Python Launcher for Windows
- PEP 3151: Reworking the OS and IO exception hierarchy
- PEP 380: Syntax for Delegating to a Subgenerator
- PEP 409: Suppressing exception context
- PEP 414: Explicit Unicode literals
- PEP 3155: Qualified name for classes and functions
- PEP 412: Key-Sharing Dictionary
- PEP 362: Function Signature Object
- PEP 421: Adding sys.implementation
- Using importlib as the Implementation of Import
- 其他語言特性修改
- A Finer-Grained Import Lock
- Builtin functions and types
- 新增模塊
- 改進的模塊
- 性能優化
- Build and C API Changes
- 棄用
- Porting to Python 3.3
- What's New In Python 3.2
- PEP 384: Defining a Stable ABI
- PEP 389: Argparse Command Line Parsing Module
- PEP 391: Dictionary Based Configuration for Logging
- PEP 3148: The concurrent.futures module
- PEP 3147: PYC Repository Directories
- PEP 3149: ABI Version Tagged .so Files
- PEP 3333: Python Web Server Gateway Interface v1.0.1
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- 多線程
- 性能優化
- Unicode
- Codecs
- 文檔
- IDLE
- Code Repository
- Build and C API Changes
- Porting to Python 3.2
- What's New In Python 3.1
- PEP 372: Ordered Dictionaries
- PEP 378: Format Specifier for Thousands Separator
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- 性能優化
- IDLE
- Build and C API Changes
- Porting to Python 3.1
- What's New In Python 3.0
- Common Stumbling Blocks
- Overview Of Syntax Changes
- Changes Already Present In Python 2.6
- Library Changes
- PEP 3101: A New Approach To String Formatting
- Changes To Exceptions
- Miscellaneous Other Changes
- Build and C API Changes
- 性能
- Porting To Python 3.0
- What's New in Python 2.7
- The Future for Python 2.x
- Changes to the Handling of Deprecation Warnings
- Python 3.1 Features
- PEP 372: Adding an Ordered Dictionary to collections
- PEP 378: Format Specifier for Thousands Separator
- PEP 389: The argparse Module for Parsing Command Lines
- PEP 391: Dictionary-Based Configuration For Logging
- PEP 3106: Dictionary Views
- PEP 3137: The memoryview Object
- 其他語言特性修改
- New and Improved Modules
- Build and C API Changes
- Other Changes and Fixes
- Porting to Python 2.7
- New Features Added to Python 2.7 Maintenance Releases
- Acknowledgements
- Python 2.6 有什么新變化
- Python 3.0
- Changes to the Development Process
- PEP 343: The 'with' statement
- PEP 366: Explicit Relative Imports From a Main Module
- PEP 370: Per-user site-packages Directory
- PEP 371: The multiprocessing Package
- PEP 3101: Advanced String Formatting
- PEP 3105: print As a Function
- PEP 3110: Exception-Handling Changes
- PEP 3112: Byte Literals
- PEP 3116: New I/O Library
- PEP 3118: Revised Buffer Protocol
- PEP 3119: Abstract Base Classes
- PEP 3127: Integer Literal Support and Syntax
- PEP 3129: Class Decorators
- PEP 3141: A Type Hierarchy for Numbers
- 其他語言特性修改
- New and Improved Modules
- Deprecations and Removals
- Build and C API Changes
- Porting to Python 2.6
- Acknowledgements
- What's New in Python 2.5
- PEP 308: Conditional Expressions
- PEP 309: Partial Function Application
- PEP 314: Metadata for Python Software Packages v1.1
- PEP 328: Absolute and Relative Imports
- PEP 338: Executing Modules as Scripts
- PEP 341: Unified try/except/finally
- PEP 342: New Generator Features
- PEP 343: The 'with' statement
- PEP 352: Exceptions as New-Style Classes
- PEP 353: Using ssize_t as the index type
- PEP 357: The 'index' method
- 其他語言特性修改
- New, Improved, and Removed Modules
- Build and C API Changes
- Porting to Python 2.5
- Acknowledgements
- What's New in Python 2.4
- PEP 218: Built-In Set Objects
- PEP 237: Unifying Long Integers and Integers
- PEP 289: Generator Expressions
- PEP 292: Simpler String Substitutions
- PEP 318: Decorators for Functions and Methods
- PEP 322: Reverse Iteration
- PEP 324: New subprocess Module
- PEP 327: Decimal Data Type
- PEP 328: Multi-line Imports
- PEP 331: Locale-Independent Float/String Conversions
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- Build and C API Changes
- Porting to Python 2.4
- Acknowledgements
- What's New in Python 2.3
- PEP 218: A Standard Set Datatype
- PEP 255: Simple Generators
- PEP 263: Source Code Encodings
- PEP 273: Importing Modules from ZIP Archives
- PEP 277: Unicode file name support for Windows NT
- PEP 278: Universal Newline Support
- PEP 279: enumerate()
- PEP 282: The logging Package
- PEP 285: A Boolean Type
- PEP 293: Codec Error Handling Callbacks
- PEP 301: Package Index and Metadata for Distutils
- PEP 302: New Import Hooks
- PEP 305: Comma-separated Files
- PEP 307: Pickle Enhancements
- Extended Slices
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- Pymalloc: A Specialized Object Allocator
- Build and C API Changes
- Other Changes and Fixes
- Porting to Python 2.3
- Acknowledgements
- What's New in Python 2.2
- 概述
- PEPs 252 and 253: Type and Class Changes
- PEP 234: Iterators
- PEP 255: Simple Generators
- PEP 237: Unifying Long Integers and Integers
- PEP 238: Changing the Division Operator
- Unicode Changes
- PEP 227: Nested Scopes
- New and Improved Modules
- Interpreter Changes and Fixes
- Other Changes and Fixes
- Acknowledgements
- What's New in Python 2.1
- 概述
- PEP 227: Nested Scopes
- PEP 236: future Directives
- PEP 207: Rich Comparisons
- PEP 230: Warning Framework
- PEP 229: New Build System
- PEP 205: Weak References
- PEP 232: Function Attributes
- PEP 235: Importing Modules on Case-Insensitive Platforms
- PEP 217: Interactive Display Hook
- PEP 208: New Coercion Model
- PEP 241: Metadata in Python Packages
- New and Improved Modules
- Other Changes and Fixes
- Acknowledgements
- What's New in Python 2.0
- 概述
- What About Python 1.6?
- New Development Process
- Unicode
- 列表推導式
- Augmented Assignment
- 字符串的方法
- Garbage Collection of Cycles
- Other Core Changes
- Porting to 2.0
- Extending/Embedding Changes
- Distutils: Making Modules Easy to Install
- XML Modules
- Module changes
- New modules
- IDLE Improvements
- Deleted and Deprecated Modules
- Acknowledgements
- 更新日志
- Python 下一版
- Python 3.7.3 最終版
- Python 3.7.3 發布候選版 1
- Python 3.7.2 最終版
- Python 3.7.2 發布候選版 1
- Python 3.7.1 最終版
- Python 3.7.1 RC 2版本
- Python 3.7.1 發布候選版 1
- Python 3.7.0 正式版
- Python 3.7.0 release candidate 1
- Python 3.7.0 beta 5
- Python 3.7.0 beta 4
- Python 3.7.0 beta 3
- Python 3.7.0 beta 2
- Python 3.7.0 beta 1
- Python 3.7.0 alpha 4
- Python 3.7.0 alpha 3
- Python 3.7.0 alpha 2
- Python 3.7.0 alpha 1
- Python 3.6.6 final
- Python 3.6.6 RC 1
- Python 3.6.5 final
- Python 3.6.5 release candidate 1
- Python 3.6.4 final
- Python 3.6.4 release candidate 1
- Python 3.6.3 final
- Python 3.6.3 release candidate 1
- Python 3.6.2 final
- Python 3.6.2 release candidate 2
- Python 3.6.2 release candidate 1
- Python 3.6.1 final
- Python 3.6.1 release candidate 1
- Python 3.6.0 final
- Python 3.6.0 release candidate 2
- Python 3.6.0 release candidate 1
- Python 3.6.0 beta 4
- Python 3.6.0 beta 3
- Python 3.6.0 beta 2
- Python 3.6.0 beta 1
- Python 3.6.0 alpha 4
- Python 3.6.0 alpha 3
- Python 3.6.0 alpha 2
- Python 3.6.0 alpha 1
- Python 3.5.5 final
- Python 3.5.5 release candidate 1
- Python 3.5.4 final
- Python 3.5.4 release candidate 1
- Python 3.5.3 final
- Python 3.5.3 release candidate 1
- Python 3.5.2 final
- Python 3.5.2 release candidate 1
- Python 3.5.1 final
- Python 3.5.1 release candidate 1
- Python 3.5.0 final
- Python 3.5.0 release candidate 4
- Python 3.5.0 release candidate 3
- Python 3.5.0 release candidate 2
- Python 3.5.0 release candidate 1
- Python 3.5.0 beta 4
- Python 3.5.0 beta 3
- Python 3.5.0 beta 2
- Python 3.5.0 beta 1
- Python 3.5.0 alpha 4
- Python 3.5.0 alpha 3
- Python 3.5.0 alpha 2
- Python 3.5.0 alpha 1
- Python 教程
- 課前甜點
- 使用 Python 解釋器
- 調用解釋器
- 解釋器的運行環境
- Python 的非正式介紹
- Python 作為計算器使用
- 走向編程的第一步
- 其他流程控制工具
- if 語句
- for 語句
- range() 函數
- break 和 continue 語句，以及循環中的 else 子句
- pass 語句
- 定義函數
- 函數定義的更多形式
- 小插曲：編碼風格
- 數據結構
- 列表的更多特性
- del 語句
- 元組和序列
- 集合
- 字典
- 循環的技巧
- 深入條件控制
- 序列和其它類型的比較
- 模塊
- 有關模塊的更多信息
- 標準模塊
- dir() 函數
- 包
- 輸入輸出
- 更漂亮的輸出格式
- 讀寫文件
- 錯誤和異常
- 語法錯誤
- 異常
- 處理異常
- 拋出異常
- 用戶自定義異常
- 定義清理操作
- 預定義的清理操作
- 類
- 名稱和對象
- Python 作用域和命名空間
- 初探類
- 補充說明
- 繼承
- 私有變量
- 雜項說明
- 迭代器
- 生成器
- 生成器表達式
- 標準庫簡介
- 操作系統接口
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- 字符串模式匹配
- 數學
- 互聯網訪問
- 日期和時間
- 數據壓縮
- 性能測量
- 質量控制
- 自帶電池
- 標準庫簡介 —— 第二部分
- 格式化輸出
- 模板
- 使用二進制數據記錄格式
- 多線程
- 日志
- 弱引用
- 用于操作列表的工具
- 十進制浮點運算
- 虛擬環境和包
- 概述
- 創建虛擬環境
- 使用pip管理包
- 接下來？
- 交互式編輯和編輯歷史
- Tab 補全和編輯歷史
- 默認交互式解釋器的替代品
- 浮點算術：爭議和限制
- 表示性錯誤
- 附錄
- 交互模式
- 安裝和使用 Python
- 命令行與環境
- 命令行
- 環境變量
- 在Unix平臺中使用Python
- 獲取最新版本的Python
- 構建Python
- 與Python相關的路徑和文件
- 雜項
- 編輯器和集成開發環境
- 在Windows上使用 Python
- 完整安裝程序
- Microsoft Store包
- nuget.org 安裝包
- 可嵌入的包
- 替代捆綁包
- 配置Python
- 適用于Windows的Python啟動器
- 查找模塊
- 附加模塊
- 在Windows上編譯Python
- 其他平臺
- 在蘋果系統上使用 Python
- 獲取和安裝 MacPython
- IDE
- 安裝額外的 Python 包
- Mac 上的圖形界面編程
- 在 Mac 上分發 Python 應用程序
- 其他資源
- Python 語言參考
- 概述
- 其他實現
- 標注
- 詞法分析
- 行結構
- 其他形符
- 標識符和關鍵字
- 字面值
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- 數據模型
- 對象、值與類型
- 標準類型層級結構
- 特殊方法名稱
- 協程
- 執行模型
- 程序的結構
- 命名與綁定
- 異常
- 導入系統
- importlib
- 包
- 搜索
- 加載
- 基于路徑的查找器
- 替換標準導入系統
- Package Relative Imports
- 有關 main 的特殊事項
- 開放問題項
- 參考文獻
- 表達式
- 算術轉換
- 原子
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- await 表達式
- 冪運算符
- 一元算術和位運算
- 二元算術運算符
- 移位運算
- 二元位運算
- 比較運算
- 布爾運算
- 條件表達式
- lambda 表達式
- 表達式列表
- 求值順序
- 運算符優先級
- 簡單語句
- 表達式語句
- 賦值語句
- assert 語句
- pass 語句
- del 語句
- return 語句
- yield 語句
- raise 語句
- break 語句
- continue 語句
- import 語句
- global 語句
- nonlocal 語句
- 復合語句
- if 語句
- while 語句
- for 語句
- try 語句
- with 語句
- 函數定義
- 類定義
- 協程
- 最高層級組件
- 完整的 Python 程序
- 文件輸入
- 交互式輸入
- 表達式輸入
- 完整的語法規范
- Python 標準庫
- 概述
- 可用性注釋
- 內置函數
- 內置常量
- 由 site 模塊添加的常量
- 內置類型
- 邏輯值檢測
- 布爾運算 — and, or, not
- 比較
- 數字類型 — int, float, complex
- 迭代器類型
- 序列類型 — list, tuple, range
- 文本序列類型 — str
- 二進制序列類型 — bytes, bytearray, memoryview
- 集合類型 — set, frozenset
- 映射類型 — dict
- 上下文管理器類型
- 其他內置類型
- 特殊屬性
- 內置異常
- 基類
- 具體異常
- 警告
- 異常層次結構
- 文本處理服務
- string — 常見的字符串操作
- re — 正則表達式操作
- 模塊 difflib 是一個計算差異的助手
- textwrap — Text wrapping and filling
- unicodedata — Unicode 數據庫
- stringprep — Internet String Preparation
- readline — GNU readline interface
- rlcompleter — GNU readline的完成函數
- 二進制數據服務
- struct — Interpret bytes as packed binary data
- codecs — Codec registry and base classes
- 數據類型
- datetime — 基礎日期/時間數據類型
- calendar — General calendar-related functions
- collections — 容器數據類型
- collections.abc — 容器的抽象基類
- heapq — 堆隊列算法
- bisect — Array bisection algorithm
- array — Efficient arrays of numeric values
- weakref — 弱引用
- types — Dynamic type creation and names for built-in types
- copy — 淺層 (shallow) 和深層 (deep) 復制操作
- pprint — 數據美化輸出
- reprlib — Alternate repr() implementation
- enum — Support for enumerations
- 數字和數學模塊
- numbers — 數字的抽象基類
- math — 數學函數
- cmath — Mathematical functions for complex numbers
- decimal — 十進制定點和浮點運算
- fractions — 分數
- random — 生成偽隨機數
- statistics — Mathematical statistics functions
- 函數式編程模塊
- itertools — 為高效循環而創建迭代器的函數
- functools — 高階函數和可調用對象上的操作
- operator — 標準運算符替代函數
- 文件和目錄訪問
- pathlib — 面向對象的文件系統路徑
- os.path — 常見路徑操作
- fileinput — Iterate over lines from multiple input streams
- stat — Interpreting stat() results
- filecmp — File and Directory Comparisons
- tempfile — Generate temporary files and directories
- glob — Unix style pathname pattern expansion
- fnmatch — Unix filename pattern matching
- linecache — Random access to text lines
- shutil — High-level file operations
- macpath — Mac OS 9 路徑操作函數
- 數據持久化
- pickle —— Python 對象序列化
- copyreg — Register pickle support functions
- shelve — Python object persistence
- marshal — Internal Python object serialization
- dbm — Interfaces to Unix “databases”
- sqlite3 — SQLite 數據庫 DB-API 2.0 接口模塊
- 數據壓縮和存檔
- zlib — 與 gzip 兼容的壓縮
- gzip — 對 gzip 格式的支持
- bz2 — 對 bzip2 壓縮算法的支持
- lzma — 用 LZMA 算法壓縮
- zipfile — 在 ZIP 歸檔中工作
- tarfile — Read and write tar archive files
- 文件格式
- csv — CSV 文件讀寫
- configparser — Configuration file parser
- netrc — netrc file processing
- xdrlib — Encode and decode XDR data
- plistlib — Generate and parse Mac OS X .plist files
- 加密服務
- hashlib — 安全哈希與消息摘要
- hmac — 基于密鑰的消息驗證
- secrets — Generate secure random numbers for managing secrets
- 通用操作系統服務
- os — 操作系統接口模塊
- io — 處理流的核心工具
- time — 時間的訪問和轉換
- argparse — 命令行選項、參數和子命令解析器
- getopt — C-style parser for command line options
- 模塊 logging — Python 的日志記錄工具
- logging.config — 日志記錄配置
- logging.handlers — Logging handlers
- getpass — 便攜式密碼輸入工具
- curses — 終端字符單元顯示的處理
- curses.textpad — Text input widget for curses programs
- curses.ascii — Utilities for ASCII characters
- curses.panel — A panel stack extension for curses
- platform — Access to underlying platform's identifying data
- errno — Standard errno system symbols
- ctypes — Python 的外部函數庫
- 并發執行
- threading — 基于線程的并行
- multiprocessing — 基于進程的并行
- concurrent 包
- concurrent.futures — 啟動并行任務
- subprocess — 子進程管理
- sched — 事件調度器
- queue — 一個同步的隊列類
- _thread — 底層多線程 API
- _dummy_thread — _thread 的替代模塊
- dummy_threading — 可直接替代 threading 模塊。
- contextvars — Context Variables
- Context Variables
- Manual Context Management
- asyncio support
- 網絡和進程間通信
- asyncio — 異步 I/O
- socket — 底層網絡接口
- ssl — TLS/SSL wrapper for socket objects
- select — Waiting for I/O completion
- selectors — 高級 I/O 復用庫
- asyncore — 異步socket處理器
- asynchat — 異步 socket 指令/響應 處理器
- signal — Set handlers for asynchronous events
- mmap — Memory-mapped file support
- 互聯網數據處理
- email — 電子郵件與 MIME 處理包
- json — JSON 編碼和解碼器
- mailcap — Mailcap file handling
- mailbox — Manipulate mailboxes in various formats
- mimetypes — Map filenames to MIME types
- base64 — Base16, Base32, Base64, Base85 數據編碼
- binhex — 對binhex4文件進行編碼和解碼
- binascii — 二進制和 ASCII 碼互轉
- quopri — Encode and decode MIME quoted-printable data
- uu — Encode and decode uuencode files
- 結構化標記處理工具
- html — 超文本標記語言支持
- html.parser — 簡單的 HTML 和 XHTML 解析器
- html.entities — HTML 一般實體的定義
- XML處理模塊
- xml.etree.ElementTree — The ElementTree XML API
- xml.dom — The Document Object Model API
- xml.dom.minidom — Minimal DOM implementation
- xml.dom.pulldom — Support for building partial DOM trees
- xml.sax — Support for SAX2 parsers
- xml.sax.handler — Base classes for SAX handlers
- xml.sax.saxutils — SAX Utilities
- xml.sax.xmlreader — Interface for XML parsers
- xml.parsers.expat — Fast XML parsing using Expat
- 互聯網協議和支持
- webbrowser — 方便的Web瀏覽器控制器
- cgi — Common Gateway Interface support
- cgitb — Traceback manager for CGI scripts
- wsgiref — WSGI Utilities and Reference Implementation
- urllib — URL 處理模塊
- urllib.request — 用于打開 URL 的可擴展庫
- urllib.response — Response classes used by urllib
- urllib.parse — Parse URLs into components
- urllib.error — Exception classes raised by urllib.request
- urllib.robotparser — Parser for robots.txt
- http — HTTP 模塊
- http.client — HTTP協議客戶端
- ftplib — FTP protocol client
- poplib — POP3 protocol client
- imaplib — IMAP4 protocol client
- nntplib — NNTP protocol client
- smtplib —SMTP協議客戶端
- smtpd — SMTP Server
- telnetlib — Telnet client
- uuid — UUID objects according to RFC 4122
- socketserver — A framework for network servers
- http.server — HTTP 服務器
- http.cookies — HTTP state management
- http.cookiejar — Cookie handling for HTTP clients
- xmlrpc — XMLRPC 服務端與客戶端模塊
- xmlrpc.client — XML-RPC client access
- xmlrpc.server — Basic XML-RPC servers
- ipaddress — IPv4/IPv6 manipulation library
- 多媒體服務
- audioop — Manipulate raw audio data
- aifc — Read and write AIFF and AIFC files
- sunau — 讀寫 Sun AU 文件
- wave — 讀寫WAV格式文件
- chunk — Read IFF chunked data
- colorsys — Conversions between color systems
- imghdr — 推測圖像類型
- sndhdr — 推測聲音文件的類型
- ossaudiodev — Access to OSS-compatible audio devices
- 國際化
- gettext — 多語種國際化服務
- locale — 國際化服務
- 程序框架
- turtle — 海龜繪圖
- cmd — 支持面向行的命令解釋器
- shlex — Simple lexical analysis
- Tk圖形用戶界面(GUI)
- tkinter — Tcl/Tk的Python接口
- tkinter.ttk — Tk themed widgets
- tkinter.tix — Extension widgets for Tk
- tkinter.scrolledtext — 滾動文字控件
- IDLE
- 其他圖形用戶界面（GUI）包
- 開發工具
- typing — 類型標注支持
- pydoc — Documentation generator and online help system
- doctest — Test interactive Python examples
- unittest — 單元測試框架
- unittest.mock — mock object library
- unittest.mock 上手指南
- 2to3 - 自動將 Python 2 代碼轉為 Python 3 代碼
- test — Regression tests package for Python
- test.support — Utilities for the Python test suite
- test.support.script_helper — Utilities for the Python execution tests
- 調試和分析
- bdb — Debugger framework
- faulthandler — Dump the Python traceback
- pdb — The Python Debugger
- The Python Profilers
- timeit — 測量小代碼片段的執行時間
- trace — Trace or track Python statement execution
- tracemalloc — Trace memory allocations
- 軟件打包和分發
- distutils — 構建和安裝 Python 模塊
- ensurepip — Bootstrapping the pip installer
- venv — 創建虛擬環境
- zipapp — Manage executable Python zip archives
- Python運行時服務
- sys — 系統相關的參數和函數
- sysconfig — Provide access to Python's configuration information
- builtins — 內建對象
- main — 頂層腳本環境
- warnings — Warning control
- dataclasses — 數據類
- contextlib — Utilities for with-statement contexts
- abc — 抽象基類
- atexit — 退出處理器
- traceback — Print or retrieve a stack traceback
- future — Future 語句定義
- gc — 垃圾回收器接口
- inspect — 檢查對象
- site — Site-specific configuration hook
- 自定義 Python 解釋器
- code — Interpreter base classes
- codeop — Compile Python code
- 導入模塊
- zipimport — Import modules from Zip archives
- pkgutil — Package extension utility
- modulefinder — 查找腳本使用的模塊
- runpy — Locating and executing Python modules
- importlib — The implementation of import
- Python 語言服務
- parser — Access Python parse trees
- ast — 抽象語法樹
- symtable — Access to the compiler's symbol tables
- symbol — 與 Python 解析樹一起使用的常量
- token — 與Python解析樹一起使用的常量
- keyword — 檢驗Python關鍵字
- tokenize — Tokenizer for Python source
- tabnanny — 模糊縮進檢測
- pyclbr — Python class browser support
- py_compile — Compile Python source files
- compileall — Byte-compile Python libraries
- dis — Python 字節碼反匯編器
- pickletools — Tools for pickle developers
- 雜項服務
- formatter — Generic output formatting
- Windows系統相關模塊
- msilib — Read and write Microsoft Installer files
- msvcrt — Useful routines from the MS VC++ runtime
- winreg — Windows 注冊表訪問
- winsound — Sound-playing interface for Windows
- Unix 專有服務
- posix — The most common POSIX system calls
- pwd — 用戶密碼數據庫
- spwd — The shadow password database
- grp — The group database
- crypt — Function to check Unix passwords
- termios — POSIX style tty control
- tty — 終端控制功能
- pty — Pseudo-terminal utilities
- fcntl — The fcntl and ioctl system calls
- pipes — Interface to shell pipelines
- resource — Resource usage information
- nis — Interface to Sun's NIS (Yellow Pages)
- Unix syslog 庫例程
- 被取代的模塊
- optparse — Parser for command line options
- imp — Access the import internals
- 未創建文檔的模塊
- 平臺特定模塊
- 擴展和嵌入 Python 解釋器
- 推薦的第三方工具
- 不使用第三方工具創建擴展
- 使用 C 或 C++ 擴展 Python
- 自定義擴展類型：教程
- 定義擴展類型：已分類主題
- 構建C/C++擴展
- 在Windows平臺編譯C和C++擴展
- 在更大的應用程序中嵌入 CPython 運行時
- Embedding Python in Another Application
- Python/C API 參考手冊
- 概述
- 代碼標準
- 包含文件
- 有用的宏
- 對象、類型和引用計數
- 異常
- 嵌入Python
- 調試構建
- 穩定的應用程序二進制接口
- The Very High Level Layer
- Reference Counting
- 異常處理
- Printing and clearing
- 拋出異常
- Issuing warnings
- Querying the error indicator
- Signal Handling
- Exception Classes
- Exception Objects
- Unicode Exception Objects
- Recursion Control
- 標準異常
- 標準警告類別
- 工具
- 操作系統實用程序
- 系統功能
- 過程控制
- 導入模塊
- Data marshalling support
- 語句解釋及變量編譯
- 字符串轉換與格式化
- 反射
- 編解碼器注冊與支持功能
- 抽象對象層
- Object Protocol
- 數字協議
- Sequence Protocol
- Mapping Protocol
- 迭代器協議
- 緩沖協議
- Old Buffer Protocol
- 具體的對象層
- 基本對象
- 數值對象
- 序列對象
- 容器對象
- 函數對象
- 其他對象
- Initialization, Finalization, and Threads
- 在Python初始化之前
- 全局配置變量
- Initializing and finalizing the interpreter
- Process-wide parameters
- Thread State and the Global Interpreter Lock
- Sub-interpreter support
- Asynchronous Notifications
- Profiling and Tracing
- Advanced Debugger Support
- Thread Local Storage Support
- 內存管理
- 概述
- 原始內存接口
- Memory Interface
- 對象分配器
- 默認內存分配器
- Customize Memory Allocators
- The pymalloc allocator
- tracemalloc C API
- 示例
- 對象實現支持
- 在堆中分配對象
- Common Object Structures
- Type 對象
- Number Object Structures
- Mapping Object Structures
- Sequence Object Structures
- Buffer Object Structures
- Async Object Structures
- 使對象類型支持循環垃圾回收
- API 和 ABI 版本管理
- 分發 Python 模塊
- 關鍵術語
- 開源許可與協作
- 安裝工具
- 閱讀指南
- 我該如何...？
- ...為我的項目選擇一個名字？
- ...創建和分發二進制擴展？
- 安裝 Python 模塊
- 關鍵術語
- 基本使用
- 我應如何 ...？
- ... 在 Python 3.4 之前的 Python 版本中安裝 pip ？
- ... 只為當前用戶安裝軟件包？
- ... 安裝科學計算類 Python 軟件包？
- ... 使用并行安裝的多個 Python 版本？
- 常見的安裝問題
- 在 Linux 的系統 Python 版本上安裝
- 未安裝 pip
- 安裝二進制編譯擴展
- Python 常用指引
- 將 Python 2 代碼遷移到 Python 3
- 簡要說明
- 詳情
- 將擴展模塊移植到 Python 3
- 條件編譯
- 對象API的更改
- 模塊初始化和狀態
- CObject 替換為 Capsule
- 其他選項
- Curses Programming with Python
- What is curses?
- Starting and ending a curses application
- Windows and Pads
- Displaying Text
- User Input
- For More Information
- 實現描述器
- 摘要
- 定義和簡介
- 描述器協議
- 發起調用描述符
- 描述符示例
- Properties
- 函數和方法
- Static Methods and Class Methods
- 函數式編程指引
- 概述
- 迭代器
- 生成器表達式和列表推導式
- 生成器
- 內置函數
- itertools 模塊
- The functools module
- Small functions and the lambda expression
- Revision History and Acknowledgements
- 引用文獻
- 日志 HOWTO
- 日志基礎教程
- 進階日志教程
- 日志級別
- 有用的處理程序
- 記錄日志中引發的異常
- 使用任意對象作為消息
- 優化
- 日志操作手冊
- 在多個模塊中使用日志
- 在多線程中使用日志
- 使用多個日志處理器和多種格式化
- 在多個地方記錄日志
- 日志服務器配置示例
- 處理日志處理器的阻塞
- Sending and receiving logging events across a network
- Adding contextual information to your logging output
- Logging to a single file from multiple processes
- Using file rotation
- Use of alternative formatting styles
- Customizing LogRecord
- Subclassing QueueHandler - a ZeroMQ example
- Subclassing QueueListener - a ZeroMQ example
- An example dictionary-based configuration
- Using a rotator and namer to customize log rotation processing
- A more elaborate multiprocessing example
- Inserting a BOM into messages sent to a SysLogHandler
- Implementing structured logging
- Customizing handlers with dictConfig()
- Using particular formatting styles throughout your application
- Configuring filters with dictConfig()
- Customized exception formatting
- Speaking logging messages
- Buffering logging messages and outputting them conditionally
- Formatting times using UTC (GMT) via configuration
- Using a context manager for selective logging
- 正則表達式HOWTO
- 概述
- 簡單模式
- 使用正則表達式
- 更多模式能力
- 修改字符串
- 常見問題
- 反饋
- 套接字編程指南
- 套接字
- 創建套接字
- 使用一個套接字
- 斷開連接
- 非阻塞的套接字
- 排序指南
- 基本排序
- 關鍵函數
- Operator 模塊函數
- 升序和降序
- 排序穩定性和排序復雜度
- 使用裝飾-排序-去裝飾的舊方法
- 使用 cmp 參數的舊方法
- 其它
- Unicode 指南
- Unicode 概述
- Python's Unicode Support
- Reading and Writing Unicode Data
- Acknowledgements
- 如何使用urllib包獲取網絡資源
- 概述
- Fetching URLs
- 處理異常
- info and geturl
- Openers and Handlers
- Basic Authentication
- Proxies
- Sockets and Layers
- 腳注
- Argparse 教程
- 概念
- 基礎
- 位置參數介紹
- Introducing Optional arguments
- Combining Positional and Optional arguments
- Getting a little more advanced
- Conclusion
- ipaddress模塊介紹
- 創建 Address/Network/Interface 對象
- 審查 Address/Network/Interface 對象
- Network 作為 Address 列表
- 比較
- 將IP地址與其他模塊一起使用
- 實例創建失敗時獲取更多詳細信息
- Argument Clinic How-To
- The Goals Of Argument Clinic
- Basic Concepts And Usage
- Converting Your First Function
- Advanced Topics
- 使用 DTrace 和 SystemTap 檢測CPython
- Enabling the static markers
- Static DTrace probes
- Static SystemTap markers
- Available static markers
- SystemTap Tapsets
- 示例
- Python 常見問題
- Python常見問題
- 一般信息
- 現實世界中的 Python
- 編程常見問題
- 一般問題
- 核心語言
- 數字和字符串
- 性能
- 序列（元組/列表）
- 對象
- 模塊
- 設計和歷史常見問題
- 為什么Python使用縮進來分組語句？
- 為什么簡單的算術運算得到奇怪的結果？
- 為什么浮點計算不準確？
- 為什么Python字符串是不可變的？
- 為什么必須在方法定義和調用中顯式使用“self”？
- 為什么不能在表達式中賦值？
- 為什么Python對某些功能（例如list.index()）使用方法來實現，而其他功能（例如len(List)）使用函數實現？
- 為什么 join()是一個字符串方法而不是列表或元組方法？
- 異常有多快？
- 為什么Python中沒有switch或case語句？
- 難道不能在解釋器中模擬線程，而非得依賴特定于操作系統的線程實現嗎？
- 為什么lambda表達式不能包含語句？
- 可以將Python編譯為機器代碼，C或其他語言嗎？
- Python如何管理內存？
- 為什么CPython不使用更傳統的垃圾回收方案？
- CPython退出時為什么不釋放所有內存？
- 為什么有單獨的元組和列表數據類型？
- 列表是如何在CPython中實現的？
- 字典是如何在CPython中實現的？
- 為什么字典key必須是不可變的？
- 為什么 list.sort() 沒有返回排序列表？
- 如何在Python中指定和實施接口規范？
- 為什么沒有goto？
- 為什么原始字符串（r-strings）不能以反斜杠結尾？
- 為什么Python沒有屬性賦值的“with”語句？
- 為什么 if/while/def/class語句需要冒號？
- 為什么Python在列表和元組的末尾允許使用逗號？
- 代碼庫和插件 FAQ
- 通用的代碼庫問題
- 通用任務
- 線程相關
- 輸入輸出
- 網絡 / Internet 編程
- 數據庫
- 數學和數字
- 擴展/嵌入常見問題
- 可以使用C語言中創建自己的函數嗎？
- 可以使用C++語言中創建自己的函數嗎？
- C很難寫，有沒有其他選擇？
- 如何從C執行任意Python語句？
- 如何從C中評估任意Python表達式？
- 如何從Python對象中提取C的值？
- 如何使用Py_BuildValue()創建任意長度的元組？
- 如何從C調用對象的方法？
- 如何捕獲PyErr_Print()（或打印到stdout / stderr的任何內容）的輸出？
- 如何從C訪問用Python編寫的模塊？
- 如何從Python接口到C ++對象？
- 我使用Setup文件添加了一個模塊，為什么make失敗了？
- 如何調試擴展？
- 我想在Linux系統上編譯一個Python模塊，但是缺少一些文件。為什么?
- 如何區分“輸入不完整”和“輸入無效”？
- 如何找到未定義的g++符號__builtin_new或__pure_virtual？
- 能否創建一個對象類，其中部分方法在C中實現，而其他方法在Python中實現（例如通過繼承）？
- Python在Windows上的常見問題
- 我怎樣在Windows下運行一個Python程序？
- 我怎么讓 Python 腳本可執行？
- 為什么有時候 Python 程序會啟動緩慢？
- 我怎樣使用Python腳本制作可執行文件？
- *.pyd 文件和DLL文件相同嗎？
- 我怎樣將Python嵌入一個Windows程序？
- 如何讓編輯器不要在我的 Python 源代碼中插入 tab ？
- 如何在不阻塞的情況下檢查按鍵？
- 圖形用戶界面（GUI）常見問題
- 圖形界面常見問題
- Python 是否有平臺無關的圖形界面工具包？
- 有哪些Python的GUI工具是某個平臺專用的？
- 有關Tkinter的問題
- “為什么我的電腦上安裝了 Python ？”
- 什么是Python？
- 為什么我的電腦上安裝了 Python ？
- 我能刪除 Python 嗎？
- 術語對照表
- 文檔說明
- Python 文檔貢獻者
- 解決 Bug
- 文檔錯誤
- 使用 Python 的錯誤追蹤系統
- 開始為 Python 貢獻您的知識
- 版權
- 歷史和許可證
- 軟件歷史
- 訪問Python或以其他方式使用Python的條款和條件
- Python 3.7.3 的 PSF 許可協議
- Python 2.0 的 BeOpen.com 許可協議
- Python 1.6.1 的 CNRI 許可協議
- Python 0.9.0 至 1.2 的 CWI 許可協議
- 集成軟件的許可和認可
- Mersenne Twister
- 套接字
- Asynchronous socket services
- Cookie management
- Execution tracing
- UUencode and UUdecode functions
- XML Remote Procedure Calls
- test_epoll
- Select kqueue
- SipHash24
- strtod and dtoa
- OpenSSL
- expat
- libffi
- zlib
- cfuhash
- libmpdec