Right now I'm running 50 PHP (in CLI mode) individual workers (processes) per machine that are waiting to receive their workload (job). For example, the job of resizing an image. In workload they receive the image (binary data) and the desired size. The worker does it's work and returns the resized image back. Then it waits for more jobs (it loops in a smart way). I'm presuming that I have the same executable, libraries and classes loaded and instantiated 50 times. Am I correct? Because this does not sound very effective.
What I'd like to have now is one process that handles all this work and being able to use all available CPU cores while having everything loaded only once (to be more efficient). I presume a new thread would be started for each job and after it finishes, the thread would stop. More jobs would be accepted if there are less than 50 threads doing the work. If all 50 threads are busy, no additional jobs are accepted.
I am using a lot of libraries (for Memcached, Redis, MogileFS, ...) to have access to all the various components that the system uses and Python is pretty much the only language apart from PHP that has support for all of them.
Can Python do what I want and will it be faster and more efficient that the current PHP solution?
If you are on a sane operating system then shared libraries should only be loaded once and shared among all processes using them.  Memory for data structures and connection handles will obviously be duplicated, but the overhead of stopping and starting the systems may be greater than keeping things up while idle.  If you are using something like gearman it might make sense to let several workers stay up even if idle and then have a persistent monitoring process that will start new workers if all the current workers are busy up until a threshold such as the number of available CPUs.  That process could then kill workers in a LIFO manner after they have been idle for some period of time.
From PHP workers to Python threads