背景

在我们测试工作中,性能测试也是避免不了的,因此在性能测试前期准备工作中,需要 mock 足够批量的数据进行压测。那么怎么能在短时间内快速 mock 出想要的格式数据和足够量的数据进行压测?那么往下看。

安装相关类包

举例说明:快速 mock kafka 批量测试数据

# -* coding:utf8 *-

from pykafka import KafkaClient
import uuid
import time
import threading
from appmetrics import metrics
from faker import Faker
import os

fake = Faker("zh-cn")
PATH = lambda p: os.path.abspath(
    os.path.join(os.path.dirname(__file__), p)
)
meter = metrics.new_meter("meter_test")
host_producer = 'host地址'


def data_info():
    uid = str(uuid.uuid4())
    suid = ''.join(uid.split('-'))
    return suid


def data_result():
    #数据格式可自行定义
    data = f"{data_info()},{fake.phone_number()},111111111111,LOL-UZI"
    return data


def mock_request():
    client_producer = KafkaClient(hosts=host_producer)
    topicdocu = client_producer.topics['XXXXXXX-TOPIC']
    producer = topicdocu.get_producer(sync=False) # sync=False  关闭同步,使用异步
    while True:
        data_uni = data_result()
        producer.produce(bytes(data_uni, encoding='utf-8'))
        meter.notify(1) # 请求一次 记录器打点一次
        # i = i - 1
    producer.stop()


def print_meter():
    while True:
        print(meter.get())
        time.sleep(1)


def thread_request(nums):
    t1 = []
    for i in range(nums):
        if i == 0:
            #该线程是为了记录每秒打点作用
            t = threading.Thread(target=print_meter, name="T" + str(i))
        else:
            t = threading.Thread(target=mock_request, name="T" + str(i))
        t.setDaemon(True)
        t1.append(t)
    for t in t1:
        t.start()
    for t in t1:
        t.join()


#
#
if __name__ == '__main__':
    thread_request(101)

appmetrics 使用方法

Meters

Meters,度量一系列事件发生的速率 (rate),例如 TPS。Meters 会统计最近 1 分钟,5 分钟,15 分钟,还有全部时间的速率。
meter = metrics.new_meter(“meter_test”)
meter.notify(1)
meter.notify(1)
meter.notify(3)
meter.get()
返回结果:

{'count': 5, 'kind': 'meter', 'five': 0.0066114184713530035, 'mean': 0.27743058841197027, 'fifteen': 0.0022160607980413085, 'day': 2.3147478365093123e-05, 'one': 0.031982234148270686}


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