Koodihommia

Working with Django in ASGI mode can benefit applications with long requests where the synchronous mode may be a bit wasteful, as you would likely need a ton of workers—especially if those workers are processes (e.g., Gunicorn). Your app may also run some fancy new LLM framework which is often async only. That said, async mode isn't a silver bullet for scaling. In Django 5.1, you still need threads to offload blocking database operations, which remain synchronous by design. Django provides async query wrappers like  aget , acount , and aall , but these are just syntactic sugar for offloading the operation to a worker thread via asgiref.sync_to_async. You can use the asgiref package's  sync_to_async utility to move blocking executions to the worker. By default, that is a ThreadPoolExecutor with one worker. This thread is shared by all sync_to_async calls during the request context, effectively meaning that each request spawns one worker thread for all sync work. So, to summar...

Besides the object geometry information, IFC files may contain properties for the IFC objects. The properties can be, for example, some predefined dimension information such as an object volume or a choice of material. Some of the properties are predefined in the IFC standards, but custom ones can be added. IFC files can be massive and resource-intensive to process, so in some cases, it helps to separate the object properties from the geometry data. IfcOpenShell  is a toolset for processing IFC files. It is written mostly in C++ but also provides a Python interface. To read an IFC file >>> ifc_file = ifcopenshell.open("model.ifc") Fetch all objects of type IfcSlab >>> slab = ifc_file.by_type("IfcSlab")[1] Get the list of properties >>> slab.IsDefinedBy (#145075=IfcRelDefinesByType('2_fok0__fAcBZmMlQcYwie',#1,$,$,(#27,#59),#145074), #145140=IfcRelDefinesByProperties('3U2LyORgXC2f_hWf6I16C1',#1,$,$,(#27,#59),#145141), #145142...