Mock API of np.empty. Extend raw_data and return view to the new area.

A single axis is indexed by either - a list[int] whose elements can be negative, non-unique, and not in order, or - a list[bool] All oth

Auxiliary function to convert bytes to a more readable human format.

Define the selection of each chunk through IndexChunkMappers. Parameters ---------- mappers: List of IndexChunkMa

Traverse all versions of a dataset, writing to a brand new hash table. Parameters ---------- f : File File for wh

Retrieve all of the registered h5py filters. Returns ------- Iterator[int] Filter ID numbers; each filter has a dedicated ID - se

Yield location of loaded dynamic libraries (plus spurious open files)

Hash the slab and return a new hash table

Print out which .so file is actually loaded at runtime for libhdf5

Return a NumPy array with the given shape and layout, full of random float64 data

Hypothesis draw to slice src and dst arrays along the same axis dst[idx_dst] = src[idx_src] Returns tuples of idx_src, idx_dst where src[

Return True if there are any filters that are explicitly set and differ between self and other; False otherwise.

Delete and rebuild *all* existing hashtables for the raw datasets.

Needed to qualify as an ArrayLike and to be accepted as the RHS of numpy.ndarray.__setitem__.

Delete a version If the version is the current version, the new current version will be set to the previous version.

Get a slice of data from the array. This reads from the staged slabs in memory when available and from either the base slab or the fill_value

Read a slice from the HDF5 dataset given by the index. Takes slices and recarray-style field names (more than one is allowed!) in any

Generate instructions to execute StagedChangesArray.__getitem__ Parameters ---------- idx: Arbitrary numpy fancy

Generate instructions to execute StagedChangesArray.__setitem__. Parameters ---------- idx: Arbitrary numpy fancy

Generate instructions to execute StagedChangesArray.changes(). All parameters are the matching attributes of StagedChangesArray.

Generate instructions to execute StagedChangesArray.resize(). Parameters ---------- old_shape: StagedChangesArray

Return number of slices that will be transferred