Testing
Most Python database test suites share the same set of mistakes. Tests that mock Session.query(). Fixtures that share state between tests. Integration tests that take 20 minutes because developers tried to be too thorough. This guide identifies the most damaging anti-patterns and shows how to replace them with patterns
Testing
asyncpg is the fastest PostgreSQL driver for Python—but testing async database code correctly requires more setup than the synchronous equivalent. This guide covers the full testing stack: spinning up real PostgreSQL via Testcontainers, managing async connection pools in tests, and isolating tests without sacrificing speed. Why asyncpg Testing Is
Testing
OneSignal abstracts the complexity of FCM and APNS behind a unified REST API, but that means your integration is only as reliable as your HTTP layer. This guide covers testing OneSignal notification delivery, segment targeting, A/B test setup, and delivery reporting using Python with requests-mock and httpretty — all without
Testing
Web Push notifications rely on three moving parts: VAPID authentication, encrypted payloads using the Web Cryptography API, and browser subscription endpoints from push services like FCM or Mozilla's autopush. Testing all three layers without a real browser is entirely possible — this guide shows how using pywebpush in Python
Testing
Apple Push Notification Service (APNS) has stricter requirements than FCM: a 4096-byte payload limit, two distinct environments (sandbox and production), and a choice between certificate-based and JWT token-based authentication. This guide walks through testing APNS integrations in Python using httpx-based clients, mocked HTTP/2 connections, and payload size assertions — without
Testing
Firebase Cloud Messaging (FCM) is the backbone of push notifications for Android, iOS, and web apps, but testing it without hitting real devices is a challenge most teams skip. This guide shows how to write reliable unit tests for FCM payloads, multicast sends, and topic subscriptions using unittest.mock in
Testing
S3 multipart upload is a three-phase protocol: initiate (get an upload ID), upload parts (minimum 5MB each), and complete (assemble the parts). Testing it requires verifying each phase independently, handling aborts, and testing resumable upload state management. moto supports multipart upload end-to-end. Key Takeaways Multipart upload is a three-phase transaction.
Testing
Azure Blob Storage has two testing paths: Azurite for integration tests against a real local emulator, and azure-storage-blob mocks for fast unit tests. Both have sharp edges — Azurite doesn't support all Blob Storage features, and the official SDK's mock story is weaker than AWS's
Testing
DuckDB is an in-process analytical database that starts in milliseconds, runs SQL against Parquet/CSV files natively, and integrates seamlessly with pandas and polars. It makes an ideal test fixture for data pipelines — replace your BigQuery or Redshift dependency with DuckDB in tests, keep your production SQL mostly unchanged, and
Testing
MinIO is an S3-compatible object storage server you can run locally or in production. Testing it properly means running a real MinIO instance — TestContainers makes this easy in both Java and Python by spinning up a MinIO Docker container per test suite and tearing it down automatically. Key Takeaways TestContainers
Testing
Testing AWS S3 without hitting real buckets is straightforward with moto, a Python library that intercepts boto3 calls and simulates S3 in memory. This guide covers unit testing bucket operations, presigned URL generation, versioning, and lifecycle policies with runnable examples. Key Takeaways moto replaces real AWS calls in tests. Decorate
Testing
moto is great for unit tests but stops at service boundaries. When you need SQS triggering Lambda, SNS fan-out to multiple SQS queues, or Lambda updating DynamoDB — you need LocalStack. This guide sets up a full LocalStack integration test environment with Docker Compose, pytest fixtures, and reusable infrastructure helpers. Key