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omegalib: v6.2

Authors: Alessandro Febretti; Cai Shanli; Arthur Nishimoto; Victor Mateevitsi; ioflowstudios; Shi Yin; J Markus Maunus;

omegalib: v6.2

Abstract

This version adds python multithreading support and some other minor fixes and improvements. A note on python multithreading You can execute custom code from other python threads but you should avoid calling into omegalib functions as much as possible. Some things may work but there are no guarantees. You should limit using multiple python threads to execute long blocking operations (i.e. reading data from a file, web IO stuff). Also note that the python interpreter itself is not designed to support multithread. In other words, only a single thread will execute bytecode at any given time. Python functions going out of the interpreter (like the aforementioned IO operations, hashing code, etc) will let the interpreter run other threads. Also since omegalib now releases the python interpreter after the update and event callbacks, if you have threads in your python script they will keep running while the application does rendering or performs other operations. Since rendering & other updates are usually the most expensive steps in an omegalib application, letting other python threads run concurrently could give you a good performance boost in some scenario. again avoid calling omegalib from those threads, since there is no way to know what the omegalib runtime is doing at the time (rendering, updating other stuff, baking bread, etc.)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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9