Do the JVM-based pythons solve any threading issues? Plain parallel java
seems indispensable.
Bill
--
Phobrain.com
On 2025-07-03 05:05, Nathan via NumPy-Discussion wrote:
> If a NumPy array is shared between two threads, NumPy doesn't do anything to
> synchronize array access. This is true
If a NumPy array is shared between two threads, NumPy doesn’t do anything
to synchronize array access. This is true in all Python versions and build
configurations - since NumPy releases the GIL during most array operations
whether or not you’re using free-threaded Python doesn’t change much except
On a related note, does numpy's gufunc mechanism provide any thread safety,
or is the responsibility on the extension writer to do that? For simple
numpy array inputs, I would think that I don't have to worry about
free-threaded python messing things up (unless I have a global state), I'm
wondering
