手把手教你实现Python连接数据库并快速取数的工具

pd.read_sql_query(sql, con, index_col=None,coerce_float=True, params=None, parse_dates=None,chunksize=None)

import pandas as pd
​​​​​​​pd.read_sql_table(table_name, con, schema=None,index_col=None, coerce_float=True, parse_dates=None, columns=None,chunksize=None)

import pandas as pd
pd.read_sql(sql, con, index_col=None,coerce_float=True, params=None, parse_dates=None, columns=None, chunksize=None)

import cx_Oracle
# Pandas读写操作Oracle数据库
import pandas as pd

# 避免编码问题带来的乱码
import os
os.environ['NLS_LANG'] = 'SIMPLIFIED CHINESE_CHINA.UTF8'


class Oracle_DB(object):
    def __init__(self):
        try:
            # 连接oracle
            # 方法1：sqlalchemy 提供的create_engine()
            # from sqlalchemy import create_engine
            # engine = create_engine('oracle+cx_oracle://username:passWord@ip:1521/ORCL')
            # #方法2：cx_Oracle.connect()
            self.engine = cx_Oracle.connect('username', 'password', 'ip:1521/database')

        except cx_Oracle.Error as e:
            print("Error %d：%s" % (e.args[0], e.args[1]))
            exit()
            
    # 查询部分信息
    def search_one(self, sql,sparm):
        try:
            # #查询获取数据用sql语句
            # 代传参数：sparm--查询指定字段参数
            df = pd.read_sql_query(sql, self.engine,params=sparm)

            self.engine.close()

        except Exception as e:
            return "Error " + e.args[0]

        return df

    # 查询全部信息
    def search_all(self, sql):
        try:

            # #查询获取数据用sql语句

            df = pd.read_sql_query(sql, self.engine)

            self.engine.close()

        except Exception as e:
            return "Error " + e.args[0]

        return df

#建立ID——编号字典
def buildid():
    sqlid = """select * from b_build_info"""
    db = Oracle_DB()  # 实例化一个对象
    b_build_info = db.search_all(sqlid)
    ID_bUILDCODE = b_build_info.set_index("BUILDCODE")["ID"].to_dict()
    return ID_bUILDCODE
    
#通过文本传入待导出数据清单
def read_task_list():
    build_code=buildid()
    tasklist=[]
    is_first_line=True
    with open("./b_lst.txt") as lst:
        for line in lst:
            if is_first_line:
                is_first_line=False
                continue
            tasklist.append(build_code.get(line.strip('\n')))  #键值对转换
    return tasklist

def sql_d(lst):
    # 逐月数据
    sql_d_energy_item_month = """select * from d_energy_item_month
           where recorddate >= to_date(:Start_time, 'yyyy-MM-dd')
           and recorddate < to_date(:End_time, 'yyyy-MM-dd')
           and  buildid  in {0}
           order by recorddate asc""".fORMat(lst)

    # 逐月数据
    sql_d_energy_month = """select d.*,t.name from d_energy_month d join t_device_info t on d.branchid = t.id
           where d.recorddate >= to_date(:Start_time, 'yyyy-MM-dd')
           and d.recorddate < to_date(:End_time, 'yyyy-MM-dd')
           and d.buildid = '{0}'
           order by d.recorddate asc""".format(lst)

    # 查询当日数据
    sql_energy_item_hour_cheak = """select * from d_energy_item_hour
            where trunc(sysdate)=trunc(recorddate)
            order by recorddate asc""".format(lst)

    sql_collection = [sql_d_energy_item_month, sql_d_energy_item_day, sql_d_energy_item_hour, sql_d_energy_month,
                      sql_d_energy_day, sql_d_energy_hour, sql_energy_hour_cheak]
                      #此处省略部分sql语句
    return sql_collection

def db_extranction(lst,sparm,sql_type):   
    """sql_type--输入需要操作的sql业务序号"""
    sql_=sql_d(lst)[sql_type]  #输出sql语句
    db = Oracle_DB()  # 实例化一个对象
    res=db.search_one(sql_,sparm)
    # 数据处理加工
    RES=Data_item_factory(res)  #此处省略
    # res = db.search_all(sql_d_energy_item_month)
    print(RES)
    return RES

import threading
# Pandas读写操作Oracle数据库
from tools.Data_Update_oracle import Oracle_DB
import pandas as pd
from concurrent import futures  

if __name__ == '__main__':
    #外部传入
    tasklist= read_task_list()
    print(tasklist)
    # 输入时间查找范围参数，可手动修改
    sparm = {'Start_time':'2021-04-01','End_time':'2021-05-01'}
    lst = tuple(list(tasklist))
    
    #业务类型序号，可手动修改
    sql_type=0
    
    #全部提取
    db_extranction(lst,sparm,sql_type)  

    #多线程按字段分批提取
    方法一：使用threading模块的Thread类的构造器创建线程
    #threads=[threading.Thread(target=db_extranction,args=(lst,sparm,sql_type)) for lst in tasklist]
    # [threads[i].start() for i in range(len(threads))]
    
    方法二：使用python的concurrent库，这是官方基于 threading 封装，先安装该库
    # with futures.ThreadPoolExecutor(len(tasklist)) as executor:
    #     executor.map([db_extranction(lst,sparm,sql_type) for lst in tasklist],tasklist)