QA Automation with LaVague

Early release

LaVague QA is still a work in progress and may contain bugs. Join our community of amazing contributors to help make this tool more reliable!

Introduction

LaVague QA is a command-line tool that turns Gherkin test specifications into ready-to-use Pytest code for web applications. Built on the LaVague open-source framework, it automates the creation and maintenance of automated tests.

See it in action generating tests on Amazon:

Key Benefits

Faster test creation: generate Pytest code directly from test scenarios by leveraging LaVague Agents.
Reduced maintenance: AI element selection adapts to UI changes, lowering the upkeeping needed when the site changes.

How it works

Write test scenarios in natural language using Gherkin.
Run LaVague QA to automatically generate the corresponding Pytest code.
Execute tests or regenerate them as your website evolves.

LaVague QA diagram

Example

Install LaVague QA

pip install lavague-qa

API keys

LaVague QA uses gpt-4o models by default, as such, you will need to define OPENAI_API_KEY as an environment variable before running LaVague.

Define feature file

In this example, we will use an example feature file that adds test coverage for Cart item removal, a critical component of the Amazon Cart feature.

Feature: Cart

  Scenario: Add and remove a single product from cart
    Given the user is on the homepage
    When the user clicks on "Accepter" to accept cookies
    And the user enters "Zero to One" into the search bar and press Enter
    And the user clicks on the first product in the search results
    And the user clicks on the "Ajouter au panier" button
    And the confirmation message is displayed
    And the user clicks on "Aller au panier" under "Passer la commande"
    And the user clicks on "Supprimer" from the cart page
    Then the cart should be empty

You can view the example file here or download it with following command:

wget https://raw.githubusercontent.com/lavague-ai/LaVague/main/lavague-qa/features/demo_amazon.feature

For guidelines on how to create a Gherkin feature file, see this guide.

Use the CLI

Use lavague-qa with a URL and a .feature file.

lavague-qa --url https://www.amazon.com --feature ./demo_amazon.feature

By default, LaVague QA uses:

Graphical UI for the browser, use --headless or -h to run in headless mode.
GPT4 models, use the --context or -c flag with your custom set of LLMs.

This will generate demo_amazon.py, a Pytest file implementing all steps in your Gherkin scenario.

Example demo_amazon.py

demo_amazon.py

import pytest
from pytest_bdd import scenarios, given, when, then, parsers
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import ElementClickInterceptedException
import time

# Constants
BASE_URL = 'https://www.amazon.fr/'

# Scenarios
scenarios('demo_amazon.feature')

# Fixtures
@pytest.fixture
def browser():
    driver = webdriver.Chrome()
    driver.implicitly_wait(10)
    yield driver
    driver.quit()

# Steps
@given('the user is on the homepage')
def user_on_homepage(browser):
    browser.get(BASE_URL)

@when('the user clicks on "Accepter" to accept cookies')
def accept_cookies(browser):
    accept_button = WebDriverWait(browser, 10).until(
        EC.element_to_be_clickable((By.XPATH, "/html/body/div/span/form/div[2]/span/span/input"))
    )
    accept_button.click()

@when(parsers.parse('the user enter "{search_term}" into the search bar and press Enter'))
def enter_search_term(browser, search_term):
    search_input = WebDriverWait(browser, 10).until(
        EC.presence_of_element_located((By.XPATH, "/html/body/div/header/div/div/div[2]/div/form/div[3]/div/input"))
    )
    search_input.send_keys(search_term)
    search_input.submit()

@when('the user click on the first product in the search results')
def click_first_product(browser):
    first_product_link = WebDriverWait(browser, 10).until(
        EC.element_to_be_clickable((By.XPATH, "/html/body/div/div/div/div/div/span/div/div[2]/div/div/span/div/div/div[2]/div/h2/a"))
    )
    first_product_link.click()

@when('the user click on the "Ajouter au panier" button')
def add_to_cart(browser):
    add_to_cart_button = WebDriverWait(browser, 10).until(
        EC.element_to_be_clickable((By.XPATH, "/html/body/div[2]/div/div[4]/div/div[5]/div[4]/div[4]/div/div/div/div/div/div/div/div/div[2]/div/form/div/div/div[23]/div/span/span/span/input"))
    )
    add_to_cart_button.click()

@when('the user the confirmation message has been displayed')
def confirm_message_displayed(browser):
    time.sleep(3)  # Wait for the confirmation message to be displayed

@when('the user click on "Aller au panier" under "Passer la commande"')
def go_to_cart(browser):
    go_to_cart_button = WebDriverWait(browser, 10).until(
        EC.element_to_be_clickable((By.XPATH, "/html/body/div/div/div/div/div[2]/div/div[3]/div/div/span/span/a"))
    )
    go_to_cart_button.click()

@when('the user click on "Supprimer" from the cart page')
def remove_from_cart(browser):
    remove_button = WebDriverWait(browser, 10).until(
        EC.element_to_be_clickable((By.XPATH, "/html/body/div/div/div[3]/div[5]/div/div[2]/div/div/form/div[2]/div[3]/div[4]/div/div[2]/div/span[2]/span/input"))
    )
    remove_button.click()

@then('the cart should be empty')
def cart_should_be_empty(browser):
    time.sleep(3)  # Wait for the cart update after removal
    empty_cart_message = WebDriverWait(browser, 10).until(
        EC.presence_of_element_located((By.XPATH, "//h1[contains(text(), 'Your amazon Basket is empty.')]"))
    )
    assert 'Your Amazon Cart is empty' in empty_cart_message.text, "Cart is not empty"

Run the generated tests

Use pytest demo_amazon.py to run the test.

pytest demo_amazon.py
=========================== test session starts ===========================
platform darwin -- Python 3.10.14, pytest-8.2.1, pluggy-1.5.0
rootdir: /Users/
configfile: pyproject.toml
plugins: anyio-4.3.0, bdd-7.1.2
collected 1 item                                                                                                                                                                                                                                         

generated_tests/demo_amazon.py .                                                                                                                                                                                                               [100%]

=========================== 1 passed in 16.03s ===========================

LaVague QA eliminates the need for manual selector identification and simplifies test updates when your site changes.

Whether you're adding coverage to a new site or maintaining existing tests, LaVague QA helps you create reliable, comprehensive test suites with minimal technical knowledge.