Spa Selections 86257 Chlorinating Granules Shock Treatment for S

Spa Selections 86257 Chlorinating Granules Shock Treatment for S

23円

Spa Selections 86257 Chlorinating Granules Shock Treatment for S

Spa Selections 86257 Chlorinating Granules Shock Treatment for S:お客様の期待を超えるという私たちの長期的な取り組みは、私たちの成功の背後にある原動力です。 ☆国内最安値に挑戦☆,【96%off!】,毎日がバーゲンセールSpa Selections 86257 Chlorinating Granules Shock Treatment for S

I'm impressed not more people talk about locust (http://locust.io/). The thing is awesome :) Shoutout too the guys from ESN :)

Armin Ronacher Author of Flask, Jinja2 & more

Spa Selections 86257 Chlorinating Granules Shock Treatment for S

Alex Gaynor Django & PyPy core developer
locustfile.py
from locust import HttpUser, between, task


class WebsiteUser(HttpUser):
    wait_time = between(5, 15)
    
    def on_start(self):
        self.client.post("/login", {
            "username": "test_user",
            "password": ""
        })
    
    @task
    def index(self):
        self.client.get("/")
        self.client.get("/static/assets.js")
        
    @task
    def about(self):
        self.client.get("/about/")
# This locust test script example will simulate a user 
# browsing the Locust documentation on https://docs.locust.io

import random
from locust import HttpUser, between, task
from pyquery import PyQuery


class AwesomeUser(HttpUser):
    host = "https://docs.locust.io/en/latest/"
    
    # we assume someone who is browsing the Locust docs, 
    # generally has a quite long waiting time (between 
    # 10 and 600 seconds), since there's a bunch of text 
    # on each page
    wait_time = between(10, 600)
    
    def on_start(self):
        # start by waiting so that the simulated users 
        # won't all arrive at the same time
        self.wait()
        # assume all users arrive at the index page
        self.index_page()
        self.urls_on_current_page = self.toc_urls
    
    @task(10)
    def index_page(self):
        r = self.client.get("")
        pq = PyQuery(r.content)
        link_elements = pq(".toctree-wrapper a.internal")
        self.toc_urls = [
            l.attrib["href"] for l in link_elements
        ]
    
    @task(50)
    def load_page(self):
        url = random.choice(self.toc_urls)
        r = self.client.get(url)
        pq = PyQuery(r.content)
        link_elements = pq("a.internal")
        self.urls_on_current_page = [
            l.attrib["href"] for l in link_elements
        ]
    
    @task(30)
    def load_sub_page(self):
        url = random.choice(self.urls_on_current_page)
        r = self.client.get(url)
# An example on how to use and nest TaskSets

from locust import HttpUser, TaskSet, task, between

class ForumThread(TaskSet):
    pass

class ForumPage(TaskSet):
    # wait_time can be overridden for individual TaskSets
    wait_time = between(10, 300)
    
    # TaskSets can be nested multiple levels
    tasks = {
        ForumThread:3
    }
    
    @task(3)
    def forum_index(self):
        pass
    
    @task(1)
    def stop(self):
        self.interrupt()

class AboutPage(TaskSet):
    pass

class WebsiteUser(HttpUser):
    wait_time = between(5, 15)
    
    # We can specify sub TaskSets using the tasks dict
    tasks = {
        ForumPage: 20,
        AboutPage: 10,
    }
    
    # We can use the @task decorator as well as the  
    # tasks dict in the same Locust/TaskSet
    @task(10)
    def index(self):
        pass
$ locust -f locustfile.py

Example code

A fundamental feature of Locust is that you describe all your test in Python code. No need for clunky UIs or bloated XML, just plain code.

Select example


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Item specifics

Condition:
New: A brand-new, unused, unopened, undamaged item in its original packaging (where packaging is ...
Brand:
Unknown
Item model number:
86257
ISBN:
Does not apply
EAN:
0744759422637
MPN:
Does not apply
UPC:
744759422637
Item Weight:
117 pounds
Color:
Does not apply
Model:
86257
Type:
Does not apply
Product Dimensions:
28 x 28 x 7 inches
Manufacturer:
Innovative Water Care







Installation

The easiest way to install Locust is from PyPI, using pip:

> pip install locust

Read more detailed installations instructions in the documentation.

Get the source code at Github.

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Spa Selections 86257 Chlorinating Granules Shock Treatment for S

Spa Selections 86257 Chlorinating Granules Shock Treatment for S:お客様の期待を超えるという私たちの長期的な取り組みは、私たちの成功の背後にある原動力です。 ☆国内最安値に挑戦☆,【96%off!】,毎日がバーゲンセールSpa Selections 86257 Chlorinating Granules Shock Treatment for S