Incremental Testing, Build Tools, Cacheing, Logging
This article explores Python testing methods, logging best practices, and error handling techniques. It also introduces alternative libraries, such as enum class, pytest caching, Redis LRU cache for decorators, build tools, type checking, code static analysis, automation tools like pydoit, SCons, and Rake. The article aims to provide insights into various Python tools and their applications for effective development and maintenance.
how to log error emitted from better-exceptions?
logging tutorial at betterstack & official
other logging libraries: loguru structlog (able to show locals/globals around error)
to ensure the consistency of tests, you need to collect input/output pairs (and compare with expected/actual output), if it is deterministic.
monkeytype, pytype (by google), runtype (Dispatch)
better assertion
enum class in python
use cache in pytest
use redis lru_cache, put decorators to json serializable functions
use build tools, forcing program to read and write files in the process
type checking using mypy
code static analysis
code formatter like black
tools:
pydoit with “up to date” signals for non-file objectives
ruby rake