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Hi, I'm seriously considering adding aiologic as a dependency for the package I created 'async-kernel' (fairly new and largely unknown), you can see the PR here that I'm currently working on. I'd like to provide some feedback on Event & REvent based on my recent experience:
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There are times where it its helpful and you don't really want to write a wrapper every time. I guess for that matter I think it could be. async def wait_async(self):
if not self:
await self |
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Greetings to everyone reading this. It has been 8 months since the last release. In a sense, this is quite a long time, and a lot has been done during this period: the number of commits has more than doubled, and the list of recent changes is now so long that it takes up more than half of the entire page on Read the Docs. However, the goal of 0.15.0, that is, upgrading to the beta development stage, still remains unachieved.
By upgrading to the beta development stage in the context of this project, I mean the following:
sphinx.ext.autodoc) and manually. This is actually more complicated than it seems, and just to support typing on the Sphinx side, a lot of effort had to be put into changing the entire code (sincesphinx.ext.autodocdoes not support stub files for pure Python modules, and existing third-party extensions just do not work). At the moment, only one section is well written — "Libraries" — and even that does not cover all questions: in particular, it should also include explanations about monkey patching support (quick answer: aiologic supports it, but the required dependencies do not, so import aiologic before monkey patching) and support for native threads (quick answer: most of aiologic's features are independent of thread type, but for some features you may need to import the greenlet module). The situation has improved somewhat with DeepWiki, but it lies a lot and cannot explain what it does not know itself.So, it is becoming clear that 0.15.0 may not be released even before the new year. This is influenced by many factors, including those beyond my control, and as the only active developer, I can only do what is within my power (even though I do have some kind of superpowers). The reason why I am not releasing an update until the main goal is achieved, as yet another alpha release, is that for all the public use cases I have seen, 0.14.0 is sufficient (which is usually a fairly simple use of0.15.0 is out (and it is still alpha)!aiologic.Event/aiologic.Lockand threading + asyncio). For cases where you need more features and relevant fixes, you can use the latest version (from GitHub), but I recommend updating at least one hour after the last commit (because during that time I may find some mistakes and quickly fix them via force-push, since separate commits are redundant for this, and there is no one else to do reviews besides me).As for the popularity of the project, I will be honest and say that I actively use GitHub and Read the Docs tools to get traffic statistics, as well as search engines to find at least some mentions. Currently, based on the low repository view statistics, near-zero documentation view statistics, almost complete lack of mentions other than my own, and low number of unique uses (discoverable via GitHub), aiologic looks like an almost unknown and most likely misunderstood project (indeed, the topic is very unusual, and the approaches I use are even more unusual, and are the result of work done years before the first release of aiologic). However, you may find that the package is frequently downloaded according to PyPI statistics, but here you should interpret the results correctly: these statistics reflect any attempt to install or download the package, regardless of the package manager used, regardless of how (whether manually, automatically via CI/CD, or as a dependency of another package). Apache Airflow made the main contribution to the PyPI statistics, from 3.0.0rc2 to 3.0.3 (not inclusive). This is also reflected in the aiologic's dependents — almost all dependents since the appearance of aiologic as a dependency of apache-airflow-task-sdk are somehow related to Apache Airflow and only list aiologic in requirements.txt or lock files as its dependency. Thus, there is no information about how many people actually use aiologic directly.
Okay, why did I write all this? Since mid-October, I have been recording unusually high activity in viewing documentation (about a dozen per day) combined with strange spikes in the number of clones, up to two thousand in the middle of last week (however, I have been observing such unusual activity with clones for a long time, and I suspect deployment mechanisms are involved, but I do not have any related details). This led me to wonder how useful the library is at the moment and what priorities should be set to make the latest version as accessible as possible here and now. Unfortunately, I cannot do this without feedback, so I ask everyone interested to express their opinion by voting (or separate comment/discussion/whatever else).
It is okay if no one votes — I will just continue to move forward on my intuition.
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