利用Python批量导出mysql数据库表结构的操作实例

SHOW TABLES

SELECT COLUMN_NAME,COLUMN_TYPE,COLUMN_KEY,IS_NULLABLE, COLUMN_COMMENT 
FROM infORMation_schema.`COLUMNS` 
WHERE TABLE_SCHEMA='{dbName}' AND TABLE_NAME='{tableName}'

import pymysql

class MysqlConnection():
    def __init__(self, host, user, passw, port, database, charset="utf8"):
        self.db = pymysql.connect(host=host, user=user, passWord=passw, port=port,
                                  database=database, charset=charset)
        self.cursor = self.db.cursor()

    # 查
    def query(self, sql):
        self.cursor.execute(sql)
        results = self.cursor.fetchall()
        return results

    # 增删改
    def update(self, sql):
        try:
            self.cursor.execute(sql)
            self.db.commit()
            return 1
        except Exception as e:
            print(e)
            self.db.rollback()
            return 0

    # 关闭连接
    def close(self):
        self.cursor.close()
        self.db.close()

# 数据库信息配置
db_config:
  host: 127.0.0.1	# 数据库所在服务IP
  port: 3306		# 数据库服务端口
  username: root	# ~用户名
  password: 12346	# ~密码
  charset: utf8
  # 需要进行处理的数据名称列表 《《 填入数据库名
  db_names: ['db_a','db_b']

# 导出配置
excel_conf:
  # 导出结构Excel表头，长度及顺序不可调整，仅支持更换名称
  column_name: ['字段名', '数据类型', '长度', '主键', '非空', '描述']
  save_dir: ./data

import yaml

class Configure():
    def __init__(self):
        with open("config.yaml", 'r', encoding='utf-8') as f:
            self._conf = yaml.load(f.read(), Loader=yaml.FullLoader)

    def get_db_config(self):
        host = self._conf['db_config']['host']
        port = self._conf['db_config']['port']
        username = self._conf['db_config']['username']
        password = self._conf['db_config']['password']
        charset = self._conf['db_config']['charset']
        db_names = self._conf['db_config']['db_names']
        return host, port, username, password, charset, db_names

    def get_excel_title(self):
        title = self._conf['excel_conf']['column_name']
        save_dir = self._conf['excel_conf']['save_dir']
        return title, save_dir

class ExportMysqlTableStructureInfoToExcel():
	def __init__(self):
	        conf = Configure()	# 获取配置初始化类信息
	        self.__host, self.__port, self.__username, self.__password, self.__charset, self.db_names = conf.get_db_config()
	        self.__excel_title, self.__save_dir = conf.get_excel_title()
	```省略```
	def __connect_to_mysql(self, database):	# 获取数据库连接方法
        connect = MysqlConnection(self.__host,
                                  self.__username,
                                  self.__password,
                                  self.__port, database,
                                  self.__charset)
        return connect
        
	def __get_all_tables(self, con):	# 查询所有表
	        res = con.query("SHOW TABLES")
	        tb_list = []
	        for item in res:
	            tb_list.append(item[0])
	        return tb_list
	``````

class ExportMysqlTableStructureInfoToExcel():
	```省略```
	def __struct_of_table_generator(self, con, db_name):
        tb_list = self.__get_all_tables(con)
        for index, tb_name in enumerate(tb_list):
            sql = "SELECT COLUMN_NAME,COLUMN_TYPE,COLUMN_KEY,IS_NULLABLE, COLUMN_COMMENT " \
              "FROM information_schema.`COLUMNS` WHERE TABLE_SCHEMA='{}' AND TABLE_NAME='{}'".format(db_name, tb_name)
            res = con.query(sql)
            struct_list = []
            for item in res:
                column_name, column_type, column_key, is_nullable, column_comment = item
                length = "0"
                if str(column_type).find('(') > -1:
                    column_type, length = str(column_type).replace(")", '').split('(')
                if column_key == 'PRI':
                    column_key = "是"
                else:
                    column_key = ''
                if is_nullable == 'YES':
                    is_nullable = '是'
                else:
                    is_nullable = '否'
                struct_list.append([column_name, column_type, length, column_key, is_nullable, column_comment])
            yield [struct_list, tb_name]
	```省略```

class ExportMysqlTableStructureInfoToExcel():
	```省略```
	def export(self):
        if len(self.db_names) == 0:
            print("请配置数据库列表")
        for i, db_name in enumerate(self.db_names):		# 对多个数据库进行处理
            connect = self.__connect_to_mysql(db_name)	# 获取数据库连接
            if not os.path.exists(self.__save_dir):		# 判断数据导出保存路径是否存在
                os.mkdir(self.__save_dir)

            file_name = os.path.join(self.__save_dir,'{}.xlsx'.format(db_name))	# 用数据库名命名导出Excel文件
            if not os.path.exists(file_name):  # 文件不存在时自动创建文件 excel
                wrokb = openpyxl.Workbook()
                wrokb.save(file_name)
                wrokb.close()
            wb = openpyxl.load_workbook(file_name)
            writer = pd.ExcelWriter(file_name, engine='openpyxl')
            writer.book = wb

            struct_generator = self.__struct_of_table_generator(connect, db_name)	# 获取表结构信息的生成器

            for tb_info in tqdm(struct_generator, desc=db_name):	# 从生成器中获取表结构并利用pandas进行格式化保存，写入Excel文件
                s_list, tb_name = tb_info
                data = pd.DataFrame(s_list, columns=self.__excel_title)
                data.to_excel(writer, sheet_name=tb_name)
            writer.close()

            connect.close()
	```省略```

pip install pymysql
pip install document

# -*- coding: utf-8 -*-
import pymysql
from docx import Document
from docx.shared import Pt
from docx.oXML.ns import qn

db = pymysql.connect(host='127.0.0.1', #数据库服务器IP
                         port=3306,
                         user='root',
                         passwd='123456',
                         db='test_db') #数据库名称)
#根据表名查询对应的字段相关信息
def query(tableName):
    #打开数据库连接
    cur = db.cursor()
    sql = "select b.COLUMN_NAME,b.COLUMN_TYPE,b.COLUMN_COMMENT from (select * from information_schema.`TABLES`  where TABLE_SCHEMA='test_db') a right join(select * from information_schema.`COLUMNS` where TABLE_SCHEMA='test_db_test') b on a.TABLE_NAME = b.TABLE_NAME where a.TABLE_NAME='" + tableName+"'"
    cur.execute(sql)
    data = cur.fetchall()
    cur.close
    return data
#查询当前库下面所有的表名，表名：tableName；表名+注释(用于填充至word文档)：concat(TABLE_NAME,'(',TABLE_COMMENT,')')
def queryTableName():
    cur = db.cursor()
    sql = "select TABLE_NAME,concat(TABLE_NAME,'(',TABLE_COMMENT,')') from information_schema.`TABLES`  where TABLE_SCHEMA='test_db_test'"
    cur.execute(sql)
    data = cur.fetchall()
    return data
#将每个表生成word结构，输出到word文档
def generateWord(singleTableData,document,tableName):
    p=document.add_paragraph()
    p.paragraph_format.line_spacing=1.5 #设置该段落 行间距为 1.5倍
    p.paragraph_format.space_after=Pt(0) #设置段落 段后 0 磅
    #document.add_paragraph(tableName,style='ListBullet')
    r=p.add_run('\n'+tableName)
    r.font.name=u'宋体'
    r.font.size=Pt(12)
    table = document.add_table(rows=len(singleTableData)+1, cols=3,style='Table Grid')
    table.style.font.size=Pt(11)
    table.style.font.name=u'Calibri'
    #设置表头样式
    #这里只生成了三个表头，可通过实际需求进行修改
    for i in ((0,'NAME'),(1,'TYPE'),(2,'COMMENT')):
        run = table.cell(0,i[0]).paragraphs[0].add_run(i[1])
        run.font.name = 'Calibri'
        run.font.size = Pt(11)
        r = run._element
        r.rPr.rFonts.set(qn('w:eastAsia'), '宋体')
    
    for i in range(len(singleTableData)):
        #设置表格内数据的样式
        for j in range(len(singleTableData[i])):
            run = table.cell(i+1,j).paragraphs[0].add_run(singleTableData[i][j])
            run.font.name = 'Calibri'
            run.font.size = Pt(11)
            r = run._element
            r.rPr.rFonts.set(qn('w:eastAsia'), '宋体')
        #table.cell(i+1, 0).text=singleTableData[i][1]
        #table.cell(i+1, 1).text=singleTableData[i][2]
        #table.cell(i+1, 2).text=singleTableData[i][3]
    

if __name__ == '__main__':
    #定义一个document
    document = Document()
    #设置字体默认样式
    document.styles['Normal'].font.name = u'宋体'
    document.styles['Normal']._element.rPr.rFonts.set(qn('w:eastAsia'), u'宋体')
    #获取当前库下所有的表名信息和表注释信息
    tableList = queryTableName()
    #循环查询数据库，获取表字段详细信息，并调用generateWord，生成word数据
    #由于时间匆忙，我这边选择的是直接查询数据库，执行了100多次查询，可以进行优化，查询出所有的表结构，在代码里面将每个表结构进行拆分
    for singleTableName in tableList:
        data = query(singleTableName[0])
        generateWord(data,document,singleTableName[1])
    #保存至文档
    document.save('数据库设计.docx')