For example, you can prefix any Python statement with %px to automatically parallelize it. Joblib has two major goals: run jobs in parallel, and don’t recompute results if nothing has changed.

Most of the time this isn’t a significant bottleneck, but it becomes one when you want to run many jobs in parallel. Python provides two ways to work around this issue: threading and ...

So, I have this little web application I've written in Django. The final step in it's functionality is talking to a REST API, the service on the other side does all of the heavy lifting.

In this video from EuroPython 2019, Pierre Glaser from INRIA presents: Parallel computing in Python: Current state and recent advances. Modern hardware is multi-core. It is crucial for Python to ...

My preferred Python package for retrieving data from the web is ... Again, if the threads don't really need to execute in a truly parallel fashion, you're fine. But, what if your system receives a ...

So, it's something of a dilemma: do you launch easy-to-use threads, even though they don't really run in parallel? Or, do you launch new processes, over which you have little control? The answer is ...

Israeli researchers have developed a new software "platform" to turn easily readable Python instructions into low-level machine code and execute it in RAM without going through the CPU.