yy_rms_39zhiyao_duizhao/timing/demo.py

#!/usr/bin/env python
# -*- encoding: utf-8 -*-
'''
@Date:2022/08/26 08:34:30
'''
# import sys
# sys.path.append('.')

# import pymysql


# import pymysql
# conn = pymysql.connect(host='127.0.0.1', port=3306,
#                        user='root', passwd='123456', db='local_rms_db')
# cur = conn.cursor(cursor=pymysql.cursors.DictCursor)


# sql = "select * from rms_user"
# cur.execute(sql)
# data = cur.fetchall()
# print(data)


# import os
# from flask import Flask, jsonify

# app = Flask(__name__)


# def get_file_base():
#     import base64

#     with open(os.getcwd() + "/config/tem_00001.xlsx", "rb") as f:
#         file_str = f.read()
#         file_str = base64.b64encode(file_str).decode()
#     return file_str

# @app.route("/get_file", methods=["GET"])
# def main_file():
#     return jsonify(get_file_base())


# if __name__ == '__main__':
#     app.run("127.0.0.1", 8001)

db_name = "user"
data_list = [
    {"variety_id": "f8442a6e-9950-11ec-a502-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u6613\u5236\u6bd2", "remark4": "", "name": "\u7532\u82ef", "english_name": "", "purity": "AR\uff08\u6caa\u8bd5\uff09\uff0c\u2265 99.5%", "cas_number": "108-88-3", "remark5": "",
        "speci": "500", "speci_unit": "ml", "export_count": "1", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "683", "manufacturer": "\u56fd\u836f", "remark8": "", "remark9": "\u70f7\u57fa\u6c5e", "remark10": ""},
    {"variety_id": "f8442a6f-9950-11ec-9253-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u5371\u5316\u54c1", "remark4": "", "name": "\u82ef\u915a", "english_name": "", "purity": "AR\uff08\u6caa\u8bd5\uff09\uff0c\u2265 99.0%", "cas_number": "108-95-2", "remark5": "",
        "speci": "500", "speci_unit": "ml", "export_count": "1", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "848", "manufacturer": "\u56fd\u836f", "remark8": "", "remark9": "\u6325\u53d1\u915a", "remark10": ""},
    {"variety_id": "f8442a70-9950-11ec-a157-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u5371\u5316\u54c1", "remark4": "", "name": "\u82ef", "english_name": "", "purity": "AR\uff08\u6caa\u8bd5\uff09\uff0c\u2265 99.5%", "cas_number": "71-43-2", "remark5": "",
        "speci": "500", "speci_unit": "ml", "export_count": "1", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "640", "manufacturer": "\u56fd\u836f", "remark8": "", "remark9": "\u6cb9", "remark10": ""},
    {"variety_id": "f8442a71-9950-11ec-9894-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u5371\u5316\u54c1", "remark4": "", "name": "\u4e59\u9178\uff0836%\uff09", "english_name": "", "purity": "AR", "cas_number": "64-19-7", "remark5": "", "speci": "500",
        "speci_unit": "ml", "export_count": "1", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "734", "manufacturer": "\u56fd\u836f", "remark8": "", "remark9": "\u70f7\u57fa\u6c5e", "remark10": ""},
    {"variety_id": "f84451a6-9950-11ec-8925-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u5371\u5316\u54c1", "remark4": "", "name": "\u4e59\u9178\u9150", "english_name": "", "purity": "AR", "cas_number": "106-24-7", "remark5": "", "speci": "500",
        "speci_unit": "ml", "export_count": "1", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "749", "manufacturer": "\u56fd\u836f", "remark8": "", "remark9": "\u70f7\u57fa\u6c5e", "remark10": ""},
    {"variety_id": "f84451a7-9950-11ec-9b4e-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u5371\u5316\u54c1", "remark4": "", "name": "\u56db\u6c2f\u4e59\u70ef", "english_name": "", "purity": "\u73af\u4fdd\u7ea7", "cas_number": "127-18-4", "remark5": "", "speci": "500",
        "speci_unit": "ml", "export_count": "28", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "1207", "manufacturer": "\u5929\u6d25\u50b2\u7136", "remark8": "", "remark9": "\u6cb9", "remark10": ""},
    {"variety_id": "f84451a8-9950-11ec-96ca-e2052a1045e4", "remark1": "", "remark2": "", "remark3": "\u5371\u5316\u54c1", "remark4": "", "name": "\u56db\u6c2f\u5316\u78b3", "english_name": "", "purity": "\u7ea2\u5916\u6d4b\u6cb9\u4eea\u4e13\u7528", "cas_number": "56-23-5", "remark5": "", "speci": "500", "speci_unit": "ml", "export_count": "31", "remark6": "\u74f6", "production_date": "2022-03-01", "shelf_life": 10529, "price": "0", "is_supervise": 0, "remain": "1126", "manufacturer": "\u5b89\u8c31", "remark8": "", "remark9": "\u77ff\u7269\u6cb9", "remark10": ""}]

# sql_header = f"insert into {}"
key_tup = []
value_tup = []
if data_list:
    base_da = data_list[0]
    for k,v in base_da.items():
        key_tup.append(k)
        value_tup.append("%s")

insert_sql = f"insert into {db_name}({','.join(key_tup)}) values({','.join(value_tup)})"
print(insert_sql)
"".join


import pymysql
from dbutils.pooled_db import PooledDB
# from common.db.mysql_config import MysqlConfig

"""
    pymysql封装总结
    https://blog.csdn.net/zhj_1121/article/details/121070412
    
    python操作mysql之只看这篇就够了
    https://www.jianshu.com/p/4e72faebd27f
    
    关于PooledDB使用autocommit的方法
    https://blog.51cto.com/abyss/1736844
"""


class MysqlPool:
    """
    MySQL 数据库连接池类 配置变量
    """

    '''
        :param
        reset: how connections should be reset when returned to the pool
            (False or None to rollback transcations started with begin(),
            True to always issue a rollback for safety's sake)

        :param 
        setsession: optional list of SQL commands that may serve to prepare
            the session, e.g. ["set datestyle to ...", "set time zone ..."]
    '''

    '''
        https://blog.51cto.com/abyss/1736844
        其中的
        setsession=['SET AUTOCOMMIT = 1']
        就是用来设置线程池是否打开自动更新的配置，0为False，1为True
    '''

    # 初始化数据库连接池变量
    __pool = None

    # 创建连接池的最大数量
    __MAX_CONNECTIONS = 20
    # 连接池中空闲连接的初始数量
    __MIN_CACHED = 5
    # 连接池中空闲连接的最大数量
    __MAX_CACHED = 5
    # 共享连接的最大数量
    __MAX_SHARED = 0

    # 超过最大连接数量时候的表现，为True等待连接数量下降，为false直接报错处理
    __BLOCK = True
    # 单个连接的最大重复使用次数
    __MAX_USAGE = 1

    # 当返回到池时，连接应该如何重置
    # (False或None回滚以begin()开始的事务，为了安全起见，总是发出回滚)
    __RESET = True
    # 设置自动提交
    __SET_SESSION = []

    # 不能是 UTF-8
    __CHARSET = 'UTF8'

    def __init__(self, host, port, user, password, database):
        """
        :param host: 数据库主机地址
        :param port: 端口号
        :param user: 用户名
        :param password: 密码
        :param database: 数据库名
        """
        if not self.__pool:
            # self代表当前类的实例，即为 MysqlPool（） 带小括号，执行后的数据。
            # __class__，魔法函数，代表从当前类的实例中，获取当前类，即为 MysqlPool 不带小括号的类。
            # __pool，这个代表的事类的变量，即为在类下面创建的初始化连接池，__pool
            self.__class__.__pool = PooledDB(
                creator=pymysql,
                host=host,
                port=port,
                user=user,
                password=password,
                database=database,
                maxconnections=self.__MAX_CONNECTIONS,
                mincached=self.__MIN_CACHED,
                maxcached=self.__MAX_CACHED,
                maxshared=self.__MAX_SHARED,
                blocking=self.__BLOCK,
                maxusage=self.__MAX_USAGE,
                setsession=self.__SET_SESSION,
                charset=self.__CHARSET
            )

    def get_connect(self):
        return self.__pool.connection()


class MysqlCursor:
    """
    从数据库配置环境，取出数据库配置参数
    这里的参数，可以不从外部导入，直接手动写入也可以。
    """

    def __init__(self, host=host, port=port, user=user, password=password, database=database) -> None:
        """
        :param host: 数据库主机地址
        :param port: 端口号
        :param user: 用户名
        :param password: 密码
        :param database: 数据库名
        """
        self.__host = host
        self.__port = port
        self.__user = user
        self.__password = password
        self.__database = database

        # 初始化数据库连接池
        self.connects_pool = MysqlPool(
            host=self.__host,
            port=self.__port,
            user=self.__user,
            password=self.__password,
            database=self.__database
        )

    def __enter__(self):
        """
        # with 上下文管理，魔法函数，进入with时调用
        :return: 当前类
        """
        # 从数据库链接池，获取一个数据库链接
        connect = self.connects_pool.get_connect()
        # 从获取的数据库链接，获取一个光标
        cursor = connect.cursor(pymysql.cursors.DictCursor)

        '''
        # https://blog.51cto.com/abyss/1736844
        # 如果使用连接池 则不能在取出后设置 而应该在创建线程池时设置
        # connect.autocommit = False 
        '''
        # 将数据库链接，赋值给当前类，方便__exit__函数调用
        self._connect = connect
        # 将数据库光标，赋值给当前类，方便__exit__函数调用
        self._cursor = cursor

        # __enter__函数，必须返回当前类
        return self

    def __exit__(self, *exc_info):
        """
        # with 上下文管理，魔法函数，退出with时调用
        :param exc_info: 异常信息，元祖
        :return: None
        """
        # 退出with上下文时，使用当前类链接，提交数据库语句
        self._connect.commit()
        # 关闭光标
        self._cursor.close()
        # 关闭链接
        self._connect.close()

    @property
    def cursor(self):
        """
        数据库连接池，取出链接，取出光标，转换为光标属性
        :return: 数据库连接池的光标
        """
        return self._cursor


if __name__ == "__main__":

    with MysqlCursor() as db:
        # 获取数据库的方法
        sql = 'select count(id) as total from people'
        db.cursor.execute("select count(id) as total from people")
        data = db.cursor.fetchone()
        print('--------统计数据条数', data)