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holoviz
GitHub Repository: holoviz/panel
Path: blob/main/doc/how_to/test/loadtests.md
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Test operating capacity

This guide addresses how to test performance by simulating multiple users accessing an app concurrently.


Load testing means testing the performance of the entire Panel application and the server(s) running it.

This kind of testing is really useful if you want to

  • develop fast and snappy applications and/ or

  • develop applications that scale to many users

Before you get started ensure you have installed the required dependencies:

pip install panel pytest locust pytest-playwright pytest-asyncio loadwright

and ensure playwright sets up the browsers it will use to display the applications:

playwright install

Create the app

Lets create a simple data app for testing. The app sleeps 0.5 seconds (default) when loaded and when the button is clicked.

app.py

Create the file app.py and add the code below:

:::{card} app.py

import time import panel as pn import param class App(pn.viewable.Viewer): run = param.Event(doc="Runs for click_delay seconds when clicked") runs = param.Integer(doc="The number of runs") status = param.String(default="No runs yet") load_delay = param.Number(default=0.5) run_delay = param.Number(default=0.5) def __init__(self, **params): super().__init__(**params) result = self._load() self._time = time.time() self._status_pane = pn.pane.Markdown(self.status, height=40, align="start", margin=(0,5,10,5)) self._result_pane = pn.Column(result) self._view = pn.Column( pn.Row(pn.widgets.Button.from_param(self.param.run, sizing_mode="fixed"), self._status_pane), self._result_pane ) def __panel__(self): return self._view def _start_run(self): self.status = f"Running ..." self._time = time.time() def _stop_run(self): now = time.time() duration = round(now-self._time,3) self._time = now self.runs+=1 self.status=f"Finished run {self.runs} in {duration}sec" @param.depends("run", watch=True) def _run_with_status_update(self): self._start_run() self._result_pane[:] = [self._run()] self._stop_run() @param.depends("status", watch=True) def _update_status_pane(self): self._status_pane.object = self.status def _load(self): time.sleep(self.load_delay) return "Loaded" def _run(self): time.sleep(self.run_delay) return f"Result {self.runs+1}" if pn.state.served: pn.extension(sizing_mode="stretch_width") App().servable()

:::

Serve the app via panel serve app.py and open http://localhost:5006/app in your browser.

Create a conftest.py

The conftest.py file should be placed alongside your tests and will be loaded automatically by pytest. It is often used to declare fixtures that allow you declare reusable components. It will:

  • provide us with an available port.

  • clean up the Panel state after each test.

Create the file conftest.py and add the code below.

:::{card} conftest.py

"""Shared configuration and fixtures for testing Panel""" import panel as pn import pytest PORT = [6000] @pytest.fixture def port(): PORT[0] += 1 return PORT[0] @pytest.fixture(autouse=True) def server_cleanup(): """ Clean up server state after each test. """ try: yield finally: pn.state.reset()

:::

For more inspiration see the Panel conftest.py file

Test the initial load with Locust

Locust can help you test the behaviour of users that load (i.e. request) your Panel app. Locust provides many useful performance related statistics and charts.

Create the file locustfile.py and add the code below.

:::{card} locustfile.py

from locust import HttpUser, task class RequestOnlyUser(HttpUser): @task def goto(self): self.client.get("/app")

:::

Start the Panel server:

panel serve app.py

Start the Locust server

locust --host http://localhost:5006

Open http://localhost:8089. Keep the default settings and click the Start swarming button. This should look like the below:

panel-locust.gif

The median response time is ~530ms when one user requests the page every second. If you try to increase to 10 simultaneous users you will see a median response time of ~5300ms. If this is a likely scenario, you will have to look into how to improve the performance of your app.

Test advanced interactions with Loadwright

Loadwright is a young load testing framework built on top of Playwright and Panel.

Lets replicate a user that:

  • Opens the app in the browser

  • Clicks the Run button n_clicks times.

Create the file test_loadwright.py and add the code below:

:::{card} test_loadwright.py

import param import pytest from loadwright import LoadTestRunner, LoadTestViewer, User import panel as pn from app import App HEADLESS = False class LoadAndClickUser(User): """A custom User that loads a page and clicks a button n_clicks times""" n_clicks = param.Integer( default=1, bounds=(0, None), doc="The number of times to click the button" ) async def run(self): with self.event(name="load", user=self.name): await self.page.goto(self.url) await self.page.get_by_role("button", name="Run").wait_for() await self.sleep() for click_index in range(self.n_clicks): with self.event(name="interact", user=self.name): await self.page.get_by_role("button", name="Run").first.click() await self.page.get_by_text(f"Finished run {click_index+1}").wait_for() await self.sleep() @pytest.mark.asyncio async def test_component_2(port=6001): """We can run the LoadTestRunner with 5 users each clicking 5 times""" async with LoadTestRunner.serve(App, port=port) as host: runner = LoadTestRunner(host=host, headless=HEADLESS, user=LoadAndClickUser(n_clicks=5), n_users=5) await runner.run() # You can access the data of the run via runner.logger.data assert runner.logger.data.duration.mean()<=10 if pn.state.served: import panel as pn pn.extension(sizing_mode="stretch_width") viewer = LoadTestViewer(data="test_results/loadwright.csv") pn.template.FastListTemplate( site="LoadWright", title="Load Testing with Playwright and Panel", main=[viewer] ).servable()

:::

Run the tests with pytest

pytest test_loadwright.py

View the results with Panel

$ panel serve test_loadwright.py ... 2023-01-01 15:53:03,396 Bokeh app running at: http://localhost:5006/test_loadwright

Loadwright Demo.

You will find an archive of test results in the tests_results/archive folder.