fix: preserve the source Zarr dtype in from_array

[d-v-b]

This AI-authored PR ensures that from_array uses the Zarr data type object, when available, instead of the numpy-like data type exposed by array.dtype, which ensures that data types like vlen-bytes have their data type preserved via from_array.

🤖 AI text below 🤖

zarr.from_array({}, data=source) fails when source is a variable-length bytes array. It passes the source's NumPy object dtype to array creation, losing the complete Zarr dtype already available in the source metadata. Inferring a storage type from object then raises ValueError because it is ambiguous.

Preserve the source's explicit Zarr dtype when creating the copy. Array-like inputs continue to use their native dtype.

A parametrized test covers all 22 registered dtype examples in formats 2 and 3, checking dtype preservation and data when copying and reopening. Before the fix, both variable-length bytes cases failed.

Validation: 1,152 from_array tests passed, 720 unsupported format-2 sharding combinations skipped. All repository commit checks passed.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 94.34%. Comparing base (3203018) to head (eded2e6).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #4335      +/-   ##
==========================================
+ Coverage   94.31%   94.34%   +0.02%     
==========================================
  Files          92       92              
  Lines       12935    12935              
==========================================
+ Hits        12200    12203       +3     
+ Misses        735      732       -3     

Files with missing lines	Coverage Δ
src/zarr/core/array.py	98.08% <ø> (ø)

... and 1 file with indirect coverage changes

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[d-v-b]

simple bugfix, so i'm self-merging