December 2018
Intermediate to advanced
374 pages
11h 39m
English
Content preview from Hands-On Enterprise Application Development with Python
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Dealing with Concurrency
As we saw in the previous chapter, when working on any large-scale enterprise application, we deal with a lot of data. This data is processed in a synchronous manner and the results are sent only after the data processing for a particular process is complete. This kind of model is absolutely fine when the data being processed in individual requests is not large. But consider a situation where a lot of data needs to be processed before a response is generated. What happens then? The answer is, slow application response times.
We need a better solution. A solution that will allow us to process data in parallel, resulting in faster application responses. But how do we achieve this? The answer to the question is concurrency ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.