qapytest 0.1.1

A powerful testing framework based on pytest, specifically designed for QA engineers

QaPyTest

QaPyTest — a powerful testing framework based on pytest, specifically designed for QA engineers. Turn your ordinary tests into detailed, structured reports with built-in HTTP, SQL, Redis and GraphQL clients.

🎯 QA made for QA — every feature is designed for real testing and debugging needs.

⚡ Why QaPyTest?

• 🚀 Ready to use: Install → run → get a beautiful report
• 🔧 Built-in clients: HTTP, SQL, Redis, GraphQL — all in one package
• 📊 Professional reports: HTML reports with attachments and logs
• 🎯 Soft assertions: Collect multiple failures in one run instead of stopping at the first
• 📝 Structured steps: Make your tests self-documenting
• 🔍 Debugging friendly: Full traceability of every action in the test

⚙️ Key features

• HTML report generation: simple report at report.html.
• Soft assertions: allow collecting multiple failures in a single run without immediately ending the test.
• Advanced steps: structured logging of test steps for better report readability.
• Attachments: ability to add files, logs and screenshots to test reports.
• HTTP client: client for performing HTTP requests.
• SQL client: client for executing raw SQL queries.
• Redis client: client for working with Redis with automatic JSON (de)serialization.
• GraphQL client: client for executing GraphQL requests.
• JSON Schema validation: function to validate API responses or test artifacts with support for soft-assert and strict mode.

👥 Ideal for

• QA Engineers — automate testing of APIs, databases and web services
• Test Automation specialists — get a ready toolkit for comprehensive testing

🚀 Quick start

1️⃣ Installation

pip install qapytest

2️⃣ Your first powerful test

from qapytest import step, attach, soft_assert, HttpClient, SqlClient

def test_comprehensive_api_validation():
    # Structured steps for readability
    with step('🌐 Testing API endpoint'):
        client = HttpClient(base_url="https://api.example.com")
        response = client.get("/users/1")
        assert response.status_code == 200
    
    # Add artifacts for debugging
    attach(response.text, 'api_response.json')
    
    # Soft assertions - collect all failures
    soft_assert(response.json()['id'] == 1, 'User ID check')
    soft_assert(response.json()['active'], 'User is active')
    
    # Database integration
    with step('🗄️ Validate data in DB'):
        db = SqlClient("postgresql://user:pass@localhost/db")
        user_data = db.fetch_data("SELECT * FROM users WHERE id = 1")
        assert len(user_data) == 1

3️⃣ Run with beautiful reports

pytest --report-html
# Open report.html 🎨

🔌 Built-in clients — everything QA needs

🌐 HttpClient — HTTP testing on steroids

client = HttpClient(base_url="https://api.example.com", timeout=30)
response = client.post("/auth/login", json={"username": "test"})
# Automatic logging of requests/responses + timing + headers

🗄️ SqlClient — Direct DB access

db = SqlClient("postgresql://localhost/testdb")
users = db.fetch_data("SELECT * FROM users WHERE active = true")
db.execute_and_commit("UPDATE users SET last_login = NOW() WHERE id = 1")

📊 GraphQL client — Modern APIs with minimal effort

gql = GraphQLClient("https://api.github.com/graphql", 
                   headers={"Authorization": "Bearer token"})
result = gql.execute("query { viewer { login } }")

🔴 RedisClient — Caching and sessions under control

redis = RedisClient(host="localhost", port=6379)
redis.set_value("session:123", {"user_id": 1, "expires": "2024-01-01"})
session_data = redis.get_value("session:123")  # Automatic JSON serialization!

🎛️ Core testing tools

📝 Structured steps

with step('🔍 Check authorization'):
    with step('Send login request'):
        response = client.post("/login", json=creds)
    with step('Validate token'):
        assert "token" in response.json()

🎯 Soft Assertions — collect all failures

soft_assert(user.id == 1, 'User ID')
soft_assert(user.active, 'Active status')
soft_assert('admin' == user.roles, 'Access rights')
# The test will continue and show all failures together!

📎 Attachments — full context

attach(response.json(), 'server response')
attach(screenshot_bytes, 'error page') 
attach(content, 'application', mime='text/plain')

✅ JSON Schema validation

# Strict validation — stop the test on schema validation error
validate_json(api_response, schema_path="user_schema.json", strict=True)

# Soft mode — collect all schema errors and continue test execution
validate_json(api_response, schema=user_schema, strict=False)

More about the API on the documentation page.

Test markers

QaPyTest also supports custom pytest markers to improve reporting:

• @pytest.mark.title("Custom Test Name") : sets a custom test name in the HTML report
• @pytest.mark.component("API", "Database") : adds component tags to the test

Example usage of markers

import pytest

@pytest.mark.title("User authorization check")
@pytest.mark.component("Auth", "API")
def test_user_login():
    # test code
    pass

⚙️ CLI options

• --env-file : path to an .env file with environment settings (default — ./.env).
• --env-override : if set, values from the .env file will override existing environment variables.
• --report-html [PATH] : create a self-contained HTML report; optionally specify a path (default — report.html).
• --report-title NAME : set the HTML report title.
• --report-theme {light,dark,auto} : choose the report theme: light, dark or auto (default).
• --max-attachment-bytes N : maximum size of an attachment (in bytes) that will be inlined in the HTML; larger files will be truncated.

More about CLI options on the documentation page.

📑 License

This project is distributed under the license.