Hey Andrew, Congratulations on the release! Re. thread-safety, I thought code like: data = dset[0:100] was already thread-safe since the GIL lock wouldn't be released until the call returns. Is that not the case? John
On Wednesday, November 5, 2014 9:20:37 AM UTC-8, Andrew Collette wrote: > > Hi Ray, > > > Great news! Many thanks to the h5py team! > > > > What exactly does it mean for the API to be thread-safe? Can we now > > read/write datasets in parallel without using MPI? > > It means that you can use h5py objects in a threaded program without > manually locking everything. For example, this code: > > data = dset[0:100] > > is now an atomic operation; other threads can't interfere with the > reading of data. Previously, it was required that such operations be > surrounded by threading locks, or bad things might happen while h5py > was reading & returning the data. For example, another thread might > change the size of the dataset mid-read, with undefined results. > > MPI is still necessary if you want multiple processes to interact with > the file. But other programs (e.g. web servers) which only > occasionally talk to HDF5 should have an easier time. > > Andrew >
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