@task decorator

A key feature of Locust is the @task decorator, which allows you to define the specific actions (or tasks) your simulated users will perform.

n this chapter, we’ll dive into the @task decorator and illustrate its use with an example that prints the current date and time, along with a friendly greeting.

What Is the @task Decorator?

The @task decorator in Locust is used to mark methods in a User class as tasks to be executed during a load test. Each method decorated with @task represents an action that the simulated user will perform.

Locust automatically identifies these tasks and executes them based on the configuration you define, such as the wait time between tasks or their relative weighting.

Example: Printing DateTime and a Greeting

Here’s a simple example of a Locust User class with two tasks: printing the current date and time and printing a greeting message.

from locust import User, task, between
from datetime import datetime

class MyUser(User):
    # Defines the wait time between tasks to be a random value between 1 and 5 seconds.
    wait_time = between(1, 5)

    @task
    def print_datetime(self):
        # This task prints the current date and time.
        print(datetime.now())
    
    @task
    def print_greeting(self):
        # This task prints a greeting message.
        print("Hello!")

Explanation of the Code

1. MyUser Class This class represents the behavior of a simulated user. Every simulated user will execute the tasks defined in this class.

2. wait_time The wait_time attribute determines how long a user will wait before executing the next task.

   • Here, between(1, 5) specifies a random delay between 1 and 5 seconds.

3. Task Methods

   • print_datetime: Prints the current date and time using Python's datetime.now().

   • print_greeting: Prints the message "Hello!".

4. @task Decorator The @task decorator marks the methods print_datetime and print_greeting as tasks for the simulated users.

Fine-Tuning Tasks with Weights

You can adjust the relative frequency of tasks using weights. For instance: