摘要：是一個純實現的客戶端操作庫，支持事務存儲過程批量執行等。插入數據元組或列表插入數據字典批量插入參考資料中操作的模塊詳解之的使用原文地址更多文章請訪問我的個人博客

PyMySQL 是一個純 Python 實現的 MySQL 客戶端操作庫，支持事務、存儲過程、批量執行等。

PyMySQL 遵循 Python 數據庫 API v2.0 規范，并包含了 pure-Python MySQL 客戶端庫。

pip install PyMySQL

import pymysql

connection = pymysql.connect(host="localhost",
                             port=3306,
                             user="root",
                             password="root",
                             db="demo",
                             charset="utf8")

參數列表：

cursor.execute(sql, args) 執行單條 SQL

# 獲取游標
cursor = connection.cursor()

# 創建數據表
effect_row = cursor.execute("""
CREATE TABLE `users` (
  `name` varchar(32) NOT NULL,
  `age` int(10) unsigned NOT NULL DEFAULT "0",
  PRIMARY KEY (`name`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8
""")

# 插入數據(元組或列表)
effect_row = cursor.execute("INSERT INTO `users` (`name`, `age`) VALUES (%s, %s)", ("mary", 18))

# 插入數據(字典)
info = {"name": "fake", "age": 15}
effect_row = cursor.execute("INSERT INTO `users` (`name`, `age`) VALUES (%(name)s, %(age)s)", info)

connection.commit()

executemany(sql, args) 批量執行 SQL

# 獲取游標
cursor = connection.cursor()

# 批量插入
effect_row = cursor.executemany(
    "INSERT INTO `users` (`name`, `age`) VALUES (%s, %s) ON DUPLICATE KEY UPDATE age=VALUES(age)", [
        ("hello", 13),
        ("fake", 28),
    ])

connection.commit()

注意：INSERT、UPDATE、DELETE 等修改數據的語句需手動執行connection.commit()完成對數據修改的提交。

cursor.lastrowid

# 執行查詢 SQL
cursor.execute("SELECT * FROM `users`")

# 獲取單條數據
cursor.fetchone()

# 獲取前N條數據
cursor.fetchmany(3)

# 獲取所有數據
cursor.fetchall()

所有的數據查詢操作均基于游標，我們可以通過cursor.scroll(num, mode)控制游標的位置。

cursor.scroll(1, mode="relative") # 相對當前位置移動
cursor.scroll(2, mode="absolute") # 相對絕對位置移動

查詢時，默認返回的數據類型為元組，可以自定義設置返回類型。支持5種游標類型：

Cursor: 默認，元組類型

DictCursor: 字典類型

DictCursorMixin: 支持自定義的游標類型，需先自定義才可使用

SSCursor: 無緩沖元組類型

SSDictCursor: 無緩沖字典類型

無緩沖游標類型，適用于數據量很大，一次性返回太慢，或者服務端帶寬較小時。源碼注釋：

Unbuffered Cursor, mainly useful for queries that return a lot of data, or for connections to remote servers over a slow network.
Instead of copying every row of data into a buffer, this will fetch rows as needed. The upside of this is the client uses much less memory, and rows are returned much faster when traveling over a slow network
or if the result set is very big.
There are limitations, though. The MySQL protocol doesn"t support returning the total number of rows, so the only way to tell how many rows there are is to iterate over every row returned. Also, it currently isn"t possible to scroll backwards, as only the current row is held in memory.

創建連接時，通過 cursorclass 參數指定類型：

connection = pymysql.connect(host="localhost",
                             user="root",
                             password="root",
                             db="demo",
                             charset="utf8",
                             cursorclass=pymysql.cursors.DictCursor)

也可以在創建游標時指定類型：

cursor = connection.cursor(cursor=pymysql.cursors.DictCursor)

開啟事務

connection.begin()

提交修改

connection.commit()

回滾事務

connection.rollback()

轉義特殊字符
connection.escape_string(str)

參數化語句
支持傳入參數進行自動轉義、格式化 SQL 語句，以避免 SQL 注入等安全問題。

# 插入數據(元組或列表)
effect_row = cursor.execute("INSERT INTO `users` (`name`, `age`) VALUES (%s, %s)", ("mary", 18))

# 插入數據(字典)
info = {"name": "fake", "age": 15}
effect_row = cursor.execute("INSERT INTO `users` (`name`, `age`) VALUES (%(name)s, %(age)s)", info)

# 批量插入
effect_row = cursor.executemany(
    "INSERT INTO `users` (`name`, `age`) VALUES (%s, %s) ON DUPLICATE KEY UPDATE age=VALUES(age)", [
        ("hello", 13),
        ("fake", 28),
    ])

Python中操作mysql的pymysql模塊詳解

Python之pymysql的使用

原文地址: https://shockerli.net/post/py...
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