背景
知识点
拓展
库
流程
实现代码
解释
背景由于不同乙方对服务商业务接口字段理解不一致,导致线上上千万数据量数据存在问题,为了修复数据,通过 Python 脚本进行修改
知识点Python3、线程池、pymysql、CSV 文件操作、requests
拓展当我们程序在使用到线程、进程或协程的时候,以下三个知识点可以先做个基本认知
CPU 密集型、IO 密集型、GIL 全局解释器锁
库流程 实现代码pip3 install requests
pip3 install pymysql
# -*- coding:utf-8 -*-
# @FileName:grade_update.py
# @Desc :在一台超级计算机上运行过的牛逼Python代码
import time
from concurrent.futures import ThreadPoolExecutor,FIRST_COMPLETED,wait
import requests
import pymysql
from projectPath import path
gradeId = [4303, 4304, 1000926, 1000927]
def writ_mysql():
"""
数据库连接
"""
return pymysql.connect(host="localhost",
port=3306,
user="admin",
password="admin",
database="test"
)
def oprationdb(grade_id, member_id):
"""
操作数据库
"""
db = writ_mysql()
try:
cursor = db.cursor()
sql = f"UPDATE `t_m_member_grade` SET `current_grade_id`={grade_id}, `modified` =now() WHERE `member_id`={member_id};"
cursor.execute(sql)
db.commit()
print(f"提交的SQL->{sql}")
except pymysql.Error as e:
db.rollback()
print("DB数据库异常:", e)
db.close()
return True
def interface(rows, thead):
"""
调用第三方接口
"""
print(f"处理数据行数--->{thead}----数据--->{rows}")
try:
url = "http://xxxx/api/xxx-data/Tmall/bindQuery"
body = {
"nickname": str(rows[0]),
"seller_name": "test",
"mobile": "111"
}
heade={"Content-Type": "application/x-www-form-urlencoded"}
res = requests.post(url=url, data=body,headers=heade)
result = res.json()
if result["data"]["status"] in [1, 2]:
grade = result["data"]["member"]["level"]
grade_id = gradeId[grade]
oprationdb(grade_id=grade_id, member_id=rows[1])
return True
return True
except Exception as e:
print(f"调用异常:{e}")
def read_csv():
import csv
# db = writ_mysql()
#线程数
MAX_WORKERS=5
with ThreadPoolExecutor(MAX_WORKERS) as pool:
with open(path + '/file/result2_colu.csv', 'r', newline='', encoding='utf-8') as f:
#set() 函数创建无序不重复元素集
seq_notdone = set()
seq_done = set()
# 使用csv的reader()方法,创建一个reader对象
reader = csv.reader(f)
n = 0
for row in reader:
n += 1
# 遍历reader对象的每一行
try:
seq_notdone.add(pool.submit(interface, rows=row, thead=n))
if len(seq_notdone) >= MAX_WORKERS:
#FIRST_COMPLETED文档说明 -- Return when any future finishes or is cancelled.
done, seq_notdone = wait(seq_notdone,return_when=FIRST_COMPLETED)
seq_done.update(done)
except Exception as e:
print(f"解析结果出错:{e}")
# db.close()
return "完成"
if __name__ == '__main__':
read_csv()
解释
引入线程池库
from concurrent.futures import ThreadPoolExecutor,FIRST_COMPLETED,wait
pool.submit(interface, rows=row, thead=n)
提交任务,interface 调用的函数,rows、thead 为 interface() 函数的入参
任务持续提交,线程池通过 MAX_WORKERS 定义的线程数持续消费
说明像这种 I/O 密集型的操作脚本适合使用多线程,如果是 CPU 密集型建议使用进行,根据机器核数进行配置
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