title: How do you stop numpy from multithreading?
body: <p>I have to run jobs on a regular basis on compute servers that I share with others in the department and when I start 10 jobs, I really would like it to just take 10 cores and not more; I don't care if it takes a bit longer with a single core per run: I just don't want it to encroach on the others' territory, which would require me to renice the jobs and so on. I just want to have 10 solid cores and that's all.</p>
  <p>I am using Enthought 7.3-1 on Redhat, which is based on Python 2.7.3 and numpy 1.6.1, but the question is more general.</p>