当前位置： 首页 > news >正文

板凳-------Mysql cookbook学习 （十--10）

news 来源：原创 2025/6/26 16:17:18

第9章：获取和使用元数据
9.0 引言
9.1 获取受语句影响的数据行数目

import mysql.connector
from mysql.connector import Errortry:conn = mysql.connector.connect(host='localhost',database='cookbook',user='cbuser',password='cbpass',client_flags=[mysql.connector.constants.ClientFlag.FOUND_ROWS])if conn.is_connected():print('已成功连接到数据库')# 获取数据库信息cursor = conn.cursor()cursor.execute('SELECT VERSION()')version = cursor.fetchone()print(f'MySQL版本: {version[0]}')# 列出所有表cursor.execute('SHOW TABLES')tables = cursor.fetchall()print('数据库中的表:')for table in tables:print(f'- {table[0]}')# 使用实际存在的customers表进行查询stmt = "SELECT * FROM customers LIMIT 5"  # 修改为实际存在的表名cursor.execute(stmt)print(f'查询结果数量: {cursor.rowcount}')# 获取并打印查询结果results = cursor.fetchall()for row in results:print(row)cursor.close()conn.close()print('数据库连接已关闭')except Error as e:
print(f'数据库操作错误: {e}')

已成功连接到数据库
MySQL版本: 8.0.40
数据库中的表:
- actors
- adcount
- al_winner
- app_log
- artist
- book_authors
- book_vendor
- booksales
- catalog_list
- cd
- city
- color
- cow_color
- cow_order
- current_dept_emp
- customers
- date_val
- datetbl
- datetime_val
- department
- dept_emp
- dept_emp_latest_date
- dept_manager
- dialogue
- dialogue_analysis
- die
- doremi
- drawing
- driver_log
- employee
- employees_2023
- event
- expt
- formula1
- goods_characteristics
- goods_shops
- groceries
- groceries_order_items
- hitcount
- hitlog
- hostip
- hostname
- housewares
- housewares2
- housewares3
- housewares4
- httpdlog
- httpdlog2
- hw_category
- image
- ingredient
- insect
- inv_item
- invoice
- item
- kjv
- limbs
- limbs_backup
- limbs_stats
- mail
- mail2
- mail_view
- marathon
- mark_log
- metal
- money
- movies
- movies_actors
- movies_actors_link
- mytable
- name
- news
- newsstaff
- nt_verses
- numbers
- obs
- occasion
- painting
- passtbl
- passwd
- patients
- perl_session
- person
- php_session
- phrase
- player_stats
- player_stats2
- poi
- poll_vote
- profile
- profile_contact
- psalms
- rainfall
- rand_names
- rank
- ranks
- reviews
- roster
- ruby_session
- salary
- sales_region
- sales_tax_rate
- sales_volume
- sibling
- some table
- standings1
- standings2
- states
- str_val
- sundays
- t
- t2
- taxpayer
- tb1
- tbl_name
- temporal_val
- test
- testscore
- testscore_withmisses
- testscore_withmisses2
- time_val
- timestamp_val
- title
- tmp
- tomcat_role
- tomcat_session
- tomcat_user
- top_names
- trip_leg
- trip_log
- trip_summary_view
- ts
- tsdemo
- tsdemo1
- tsdemo2
- tt
- ttt
- weatherdata
- weekday
查询结果数量: 0
('CUST001', 'John', 'Doe', 'john.doe@example.com', '+1-800-123-4567', '123 Main St.', None, 'Springfield', 'IL', '62704', 'USA', datetime.datetime(2025, 5, 18, 11, 42, 53), datetime.datetime(2025, 5, 18, 11, 42, 53))
('CUST002', 'Jane', 'Smith', 'jane.smith@example.com', '+1-800-987-6543', '456 Elm St.', None, 'Shelbyville', 'KY', '40065', 'USA', datetime.datetime(2025, 5, 18, 11, 42, 53), datetime.datetime(2025, 5, 18, 11, 42, 53))
('CUST003', 'Alice', 'Johnson', 'alice.johnson@example.com', '+1-800-555-1212', '789 Oak Ave.', None, 'Capital City', 'TX', '76101', 'USA', datetime.datetime(2025, 5, 18, 11, 42, 53), datetime.datetime(2025, 5, 18, 11, 42, 53))
数据库连接已关闭

9.2 获取设置元数据的结果

import mysql.connector
from mysql.connector import Error
from mysql.connector import constants  # 导入constants模块try:conn = mysql.connector.connect(host='localhost',database='cookbook',user='cbuser',password='cbpass',client_flags=[constants.ClientFlag.FOUND_ROWS])if conn.is_connected():print('已成功连接到数据库')stmt = "SELECT name, foods from profile"print("Statement: ", stmt)cursor = conn.cursor()cursor.execute(stmt)print(f'查询结果数量: {cursor.rowcount}')if cursor.description is None:ncols = 0else:ncols = len(cursor.description)print("Number of columns: ", ncols)if ncols == 0:print("Note: statement has no result set")# 打印列信息 - 使用修正后的类型获取方式for i in range(ncols):col_info = cursor.description[i]col_name = col_info[0]col_type_code = col_info[1]# 通过类型代码获取类型名称col_type_name = constants.FieldType.get_info(col_type_code)print(f"Column {i+1}: {col_name} ({col_type_name})")# 获取并打印查询结果results = cursor.fetchall()for row in results:print(row)cursor.close()conn.close()print('数据库连接已关闭')except Error as e:
print(f'数据库操作错误: {e}')已成功连接到数据库
Statement:  SELECT name, foods from profile
查询结果数量: 0
Number of columns:  2
Column 1: name (STRING)
Column 2: foods (STRING)
('Fred', {'lutefisk', 'fadge', 'pizza'})
('Mort', {'curry', 'eggroll', 'burrito'})
('Brit', {'curry', 'pizza', 'burrito'})
('Carl', {'eggroll', 'pizza'})
('Sean', {'curry', 'burrito'})
('Alan', {'curry', 'fadge'})
('Mara', {'lutefisk', 'fadge'})
('Shepard', {'curry', 'pizza'})
('Dick', {'lutefisk', 'fadge'})
('Tony', {'pizza', 'burrito'})
('Alison', {'eggroll'})
("De'Mont", {'eggroll'})
("De'Mont", {'eggroll'})
("De'Mont", {'eggroll'})
("De'Mont", {'eggroll'})
("De'Mont", {'eggroll'})
('Amabel', None)
("De'Mont", {'eggroll'})
('Juan', None)
("De'Mont", {'eggroll'})
数据库连接已关闭import mysql.connector
from mysql.connector import Error
from mysql.connector import constantstry:conn = mysql.connector.connect(host='localhost',database='cookbook',user='cbuser',password='cbpass',client_flags=[constants.ClientFlag.FOUND_ROWS])if conn.is_connected():print('已成功连接到数据库')stmt = "SELECT name, foods FROM profile"print("执行查询:", stmt)cursor = conn.cursor(dictionary=True)cursor.execute(stmt)# 获取所有结果results = cursor.fetchall()total_records = len(results)print(f"查询返回 {total_records} 条记录")if cursor.description:print(f"列信息:")for i, col in enumerate(cursor.description):col_type = constants.FieldType.get_info(col[1])print(f"  {i+1}. {col[0]} ({col_type})")if total_records > 0:print("\n格式化显示结果:")print("=" * 40)print(f"{'Name':<15} | {'Foods':<30}")print("-" * 40)unique_names = set()empty_foods_count = 0for row in results:name = row['name']foods = row['foods']if foods is None:foods_display = "None"empty_foods_count += 1else:if isinstance(foods, set):foods_display = ", ".join(sorted(foods))else:foods_display = str(foods)if name in unique_names:name_display = f"{name} (重复)"else:name_display = nameunique_names.add(name)print(f"{name_display:<15} | {foods_display:<30}")print("=" * 40)print(f"统计:")print(f"  - 不重复姓名数量: {len(unique_names)}")print(f"  - 总记录数: {total_records}")print(f"  - 无食物偏好记录数: {empty_foods_count}")else:print("查询结果为空")cursor.close()conn.close()print('\n数据库连接已关闭')except Error as e:print(f'数据库操作错误: {e}')

已成功连接到数据库
执行查询: SELECT name, foods FROM profile
查询返回 20 条记录
列信息:1. name (STRING)2. foods (STRING)格式化显示结果:
========================================
Name            | Foods                         
----------------------------------------
Fred            | fadge, lutefisk, pizza        
Mort            | burrito, curry, eggroll       
Brit            | burrito, curry, pizza         
Carl            | eggroll, pizza                
Sean            | burrito, curry                
Alan            | curry, fadge                  
Mara            | fadge, lutefisk               
Shepard         | curry, pizza                  
Dick            | fadge, lutefisk               
Tony            | burrito, pizza                
Alison          | eggroll                       
De'Mont         | eggroll                       
De'Mont (重复)    | eggroll                       
De'Mont (重复)    | eggroll                       
De'Mont (重复)    | eggroll                       
De'Mont (重复)    | eggroll                       
Amabel          | None                          
De'Mont (重复)    | eggroll                       
Juan            | None                          
De'Mont (重复)    | eggroll                       
========================================
统计:- 不重复姓名数量: 14- 总记录数: 20- 无食物偏好记录数: 2数据库连接已关闭

相关文章：

  • 做外包任务网站如何推广网站方法
  • unity3d可以做网站吗怎么把产品推广到各大平台
  • 福州做网站互联网公司seo搜索引擎优化薪资水平
  • 广州外贸网站建设公司价格品牌推广活动策划案例
  • 动态网站开发用的什么语言全国疫情突然又严重了
  • wordpress 外贸站主题鸡西网站seo
  • Java期末复习题（二）
  • Linux 内存管理之page cache
  • LOOP如何让长周期交互LLM代理在复杂环境中实现突破？
  • JSON框架转化isSuccess()为sucess字段
  • DataX（3）—— 核心流程源码
  • 计算机网络 网络层：数据平面（二）
  • 北斗导航 ｜ 基于改进奇偶矢量法的CAT I精密进近RAIM算法
  • 若依框架配置+相关报错
  • [日志收集]
  • [ linux-系统 ] 基础IO
  • 区间求最值问题高效解决方法
  • 仿Apple官网设计风格
  • 基于STM32的智能节能风扇的设计
  • IT运维效率提升: 当IT监控遇上3D可视化
  • Python 爬虫入门：从数据爬取到转存 MySQL 数据库
  • 深度学习入门--（二）感知机
  • VBA技术资料MF329：获得屏幕分辨率
  • 数据库1.0
  • 【请关注】实操mongodb集群部署
  • 迁移学习—基于猫狗数据集