Recently, an addition to Python 3.12 might be reverted in cpython#105948, where a new json.AttrDict class could enable accessing a dict using dot notation using a json.load hook.
But as pointed out in a related issue thread, this is already possible using the standard library's SimpleNamespace.
This is a short post on how you can publish wheels onto PyPi, using hatchling's custom metadata hook, that seamlessly targets different Python interpreter versions.
Good morning, project!
$ gh pr list
#1626 chore(deps-dev): bump black from 23.1.0 t... dependabot/pip/black-23.3.0 about 7 hours ago
#1625 chore(deps-dev): bump types-requests from... dependabot/pip/types-requests-2.28.11.17 about 7 hours ago
#1624 chore(deps-dev): bump mkdocs-include-mark... dependabot/pip/mkdocs-include-markdown-p... about 7 hours ago
#1623 chore(deps-dev): bump types-redis from 4.... dependabot/pip/types-redis-4.5.3.1 about 7 hours ago
#1622 chore(deps-dev): bump pre-commit from 3.1... dependabot/pip/pre-commit-3.2.1 about 7 hours ago
#1621 chore(deps-dev): bump types-deprecated fr... dependabot/pip/types-deprecated-1.2.9.2 about 7 hours ago
#1620 chore(deps-dev): bump types-python-dateut... dependabot/pip/types-python-dateutil-2.8... about 7 hours ago
#1619 chore(deps-dev): bump types-redis from 4.... dependabot/pip/types-redis-4.5.3.0 about 7 hours ago
#1618 chore(deps-dev): bump moto from 4.1.4 to ... dependabot/pip/moto-4.1.6 about 7 hours ago
-Spits out coffee-
Load an .env file into the environment prior to running something which requires the environment variables:
When using Datadog for monitoring, Datadog will only record a trace if there is an incoming request.
If there is no incoming request, such as if a cronjob is running, then Datadog will not record a trace and you might not be alerted by an error.
To solve this, you can use the ddtrace-py library and create a custom trace/span whenever tag and tag a span with exception information. This will effectively make it possible to track errors in APM error tracking.
In software development, certain software were not designed to run on the ARM-based Apple Silicon. Thankfully, there are workarounds to install and run the Intel version of these applications. Like for the rest of this blog, this post aims to serve as a personal notebook and also for sharing this knowledge.
When I started looking into solutions to my Macbook Pro M1 challenges, a huge chunk was solved when I had read Ekaterina Nikonova's excellent blog post on Python virtual environments with pyenv on Apple Silicon.
This blog post is heavily influenced by her approach of setting up the app and app86 versions for apps which might need both native and emulated treatment.
I recently got some feedback (thank you @simmel, much appreciated!) on a previous post on debugging Poetry. I then realized it was a bit hard to follow if all you wanted to do was to install Poetry globally, with some added control from the default installation method.
This post aims to focus on this and cover the different system-wide installation alternatives that I am aware of.
A guide on how to set up debugging of Poetry in Visual Studio Code, using Pipx and Pyenv.
This was just a fun experiment.
Basically, how to set this up.