CI/CD
Dagger Python SDK: Writing Testable CI Pipelines with Python
The Dagger Python SDK lets you write CI pipelines as ordinary Python functions. No YAML, no DSL — just Python.
Python
Latest
Testing
Running pytest Tests in Parallel with pytest-xdist
pytest-xdist lets you run tests across multiple CPUs — or even multiple machines — without changing a single test.
Testing
Python Localization Testing: Babel, gettext, and pytest-i18n
Python's localization stack — gettext, Babel, and framework-specific layers like Flask-Babel or Django's i18n — has plenty of failure modes: missing translations, broken .mo files, incorrect plural forms, and format differences across locales. This guide covers how to test each layer systematically with pytest. Testing Message
MLOps
Testing ML Experiments with Weights & Biases: Assertions, Alerts, and CI Checks
Weights & Biases (W&B) tracks ML experiments — but it also provides the infrastructure to assert training quality, detect regressions, and gate deployments on metric thresholds. This post covers how to use W&B as a testing tool, not just a logging tool. W&B as a
MLOps
Testing ML Models with Evidently AI: Data Drift and Model Quality Reports
Evidently AI is an open-source framework for evaluating and monitoring machine learning models.
MLOps
Testing ML Model Services with BentoML: Unit, Integration, and Load Tests
BentoML packages machine learning models as production-ready API services.
Testing
Testcontainers Advanced: Multi-Container Setups, Compose Modules, and Parallel Tests
Testcontainers starts real Docker containers in tests, replacing mocks and in-memory fakes.
Python
hypothesis-django: Property-Based Testing for Django Models and Views
Hypothesis is a property-based testing library for Python. Instead of writing specific test cases, you describe the shape of your input and Hypothesis generates hundreds of examples automatically — including edge cases you wouldn't think to write manually. hypothesis-django is the Django integration that handles database transactions,
Python
factory_boy Advanced: Traits, Sub-Factories, Batch Creation, and Django Integration
factory_boy is Python's most widely used test object factory library. The basics — factory.Factory and factory.django.DjangoModelFactory — are well documented, but the advanced features are what make large test suites maintainable. This guide covers traits, sub-factories, batch creation, lazy attributes, and the patterns that keep
Test Automation
Atheris: Python Fuzzing with libFuzzer for Automated Vulnerability Discovery
Python's dynamic type system and exception handling make it easier to write code that handles invalid input gracefully — in theory.
Test Automation
Celery Testing with pytest: Unit and Integration Tests for Async Tasks
Celery is Python's most popular distributed task queue. Testing Celery tasks well means covering task logic in isolation, testing how tasks interact with the broker and result backend, and verifying retry behaviour. This guide shows how to do all three with pytest. Setup pip install celery redis pytest
AI Testing
Testing CrewAI Tools, Task Context, and Crew Output: A Practical Guide
CrewAI's abstraction is clean: you define agents with roles and tools, wire them into tasks, and the crew handles delegation. What's less clean is testing it.