Django
Django ships with unittest-based test tooling out of the box. pytest-django brings the full pytest ecosystem — fixtures, parametrize, plugins, and a cleaner API — to Django projects without rewriting your existing tests. This guide shows you how to set it up, what you gain, and when to reach for
Test Automation
Django's ORM is the heart of most applications — and the source of many bugs. N+1 queries, missing indexes, broken managers, and subtle transaction behaviors are best caught at test time. This guide covers strategies for testing ORM queries, model logic, and test data setup. Setup pip install
Test Automation
Creating test data manually with Model.objects.create(...) doesn't scale. When models have 10+ fields, required foreign keys, and complex relationships, tests become maintenance nightmares. factory_boy and model_bakery solve this with generated test data that respects your model's structure. factory_boy factory_boy generates
Django
Hardcoded fixture files rot. setUpTestData with manual objects.create() calls sprawl. factory_boy solves test data generation in Django by centralizing model construction, providing sensible defaults, and making it easy to override only the fields that matter for a specific test. Installation pip install factory-boy Copy Your First DjangoModelFactory
Django
Django REST Framework provides its own testing tools on top of Django's standard test client. Understanding APIClient, APITestCase, and authentication helpers is essential for writing reliable API tests. This guide covers all the patterns you'll need. APITestCase vs TestCase APITestCase is DRF's equivalent of
Test Automation
Django 3.1+ supports async views, and Django Channels adds WebSocket and long-polling support. Testing async code requires async test runners and clients — but the patterns are familiar once you see them. Setup pip install django channels pytest pytest-django pytest-asyncio Copy # pytest.ini [pytest] DJANGO_SETTINGS_MODULE
Security Testing
Static Application Security Testing (SAST) for Python means scanning your source code for vulnerabilities without running it. Bandit is the go-to Python-specific tool, Semgrep gives you customizable rules, and CodeQL provides deep dataflow analysis. This guide shows you how to configure all three in CI/CD and which
Backend Testing
Saleor is an open-source headless commerce platform built on Django and GraphQL. It powers storefronts for mid-size to enterprise retailers who need full control over their commerce stack. Because Saleor exposes everything through a GraphQL API, testing requires understanding both Django's test tooling and GraphQL-specific
Python
Behave and the Python requests library are a natural pairing for API testing. You write scenarios in plain Gherkin that non-developers can read, while step definitions handle the HTTP calls. This post walks through project setup, reusable context objects, authentication flows, and error-case testing — all with working code.
Robot Framework
Robot Framework has been around since 2005 and remains one of the most widely used test automation frameworks, particularly in enterprises. Its combination of keyword-driven syntax, extensive library ecosystem, and readable test reports makes it a strong choice for teams that need non-developers to participate in test automation.
Coverage.py
Coverage.py measures which Python lines, branches, and functions are executed during tests. Use it with pytest-cov for seamless pytest integration, enforce minimum coverage with --fail-under, and generate XML reports for Codecov, SonarQube, and GitHub Actions integrations. Coverage.py is the standard Python coverage measurement tool. Unlike language-
FPGA
cocotb (Coroutine-Based Co-simulation Testbench) lets you write hardware testbenches in Python instead of VHDL or SystemVerilog. Your Python code drives and monitors HDL signals via a simulator (ModelSim, Questa, Verilator, Icarus, etc.) through a VPI/VHPI interface. The result: familiar Python tooling (pytest, coverage, CI) for hardware verification.