Use low level interface for read_n_rows

src/lgdo/lh5/_serializers/read/utils.py

@@ -1,10 +1,16 @@
 from __future__ import annotations
 
+import logging
+
 import h5py
 import numpy as np
 
+from .... import types
+from ... import datatype
 from ...exceptions import LH5DecodeError
 
+log = logging.getLogger(__name__)
+
 
 def check_obj_buf_attrs(attrs, new_attrs, fname, oname):
     if set(attrs.keys()) != set(new_attrs.keys()):
@@ -23,7 +29,7 @@ def read_attrs(h5o, fname, oname):
         h5a = h5py.h5a.open(h5o, index=i_attr)
         name = h5a.get_name().decode()
         if h5a.shape != ():
-            msg = f"attribute {name} is not a string or scalar"
+            msg = f"attribute {oname} is not a string or scalar"
             raise LH5DecodeError(msg, fname, oname)
         val = np.empty((), h5a.dtype)
         h5a.read(val)
@@ -33,3 +39,58 @@ def read_attrs(h5o, fname, oname):
             attrs[name] = val.item()
         h5a.close()
     return attrs
+
+
+def read_n_rows(h5o, fname, oname):
+    """Read number of rows in LH5 object"""
+    if not h5py.h5a.exists(h5o, b"datatype"):
+        msg = "missing 'datatype' attribute"
+        raise LH5DecodeError(msg, fname, oname)
+
+    h5a = h5py.h5a.open(h5o, b"datatype")
+    type_attr = np.empty((), h5a.dtype)
+    h5a.read(type_attr)
+    type_attr = type_attr.item().decode()
+    lgdotype = datatype.datatype(type_attr)
+
+    # scalars are dim-0 datasets
+    if lgdotype is types.Scalar:
+        return None
+
+    # structs don't have rows
+    if lgdotype is types.Struct:
+        return None
+
+    # tables should have elements with all the same length
+    if lgdotype is types.Table:
+        # read out each of the fields
+        rows_read = None
+        for field in datatype.get_struct_fields(type_attr):
+            n_rows_read = read_n_rows(h5py.h5o.open(h5o, field.encode()), fname, field)
+            if not rows_read:
+                rows_read = n_rows_read
+            elif rows_read != n_rows_read:
+                log.warning(
+                    f"'{field}' field in table '{oname}' has {rows_read} rows, "
+                    f"{n_rows_read} was expected"
+                )
+
+        return rows_read
+
+    # length of vector of vectors is the length of its cumulative_length
+    if lgdotype is types.VectorOfVectors:
+        return read_n_rows(
+            h5py.h5o.open(h5o, b"cumulative_length"), fname, "cumulative_length"
+        )
+
+    # length of vector of encoded vectors is the length of its decoded_size
+    if lgdotype in (types.VectorOfEncodedVectors, types.ArrayOfEncodedEqualSizedArrays):
+        return read_n_rows(h5py.h5o.open(h5o, b"encoded_data"), fname, "encoded_data")
+
+    # return array length (without reading the array!)
+    if issubclass(lgdotype, types.Array):
+        # compute the number of rows to read
+        return h5o.get_space().shape[0]
+
+    msg = f"don't know how to read rows of LGDO {lgdotype.__name__}"
+    raise LH5DecodeError(msg, fname, oname)

src/lgdo/lh5/utils.py

@@ -12,7 +12,7 @@
 import h5py
 
 from .. import types
-from . import _serializers, datatype
+from . import _serializers
 from .exceptions import LH5DecodeError
 
 log = logging.getLogger(__name__)
@@ -47,54 +47,12 @@ def read_n_rows(name: str, h5f: str | h5py.File) -> int | None:
         h5f = h5py.File(h5f, "r")
 
     try:
-        attrs = h5f[name].attrs
+        h5o = h5f[name].id
     except KeyError as e:
         msg = "not found"
         raise LH5DecodeError(msg, h5f, name) from e
-    except AttributeError as e:
-        msg = "missing 'datatype' attribute"
-        raise LH5DecodeError(msg, h5f, name) from e
-
-    lgdotype = datatype.datatype(attrs["datatype"])
-
-    # scalars are dim-0 datasets
-    if lgdotype is types.Scalar:
-        return None
-
-    # structs don't have rows
-    if lgdotype is types.Struct:
-        return None
-
-    # tables should have elements with all the same length
-    if lgdotype is types.Table:
-        # read out each of the fields
-        rows_read = None
-        for field in datatype.get_struct_fields(attrs["datatype"]):
-            n_rows_read = read_n_rows(name + "/" + field, h5f)
-            if not rows_read:
-                rows_read = n_rows_read
-            elif rows_read != n_rows_read:
-                log.warning(
-                    f"'{field}' field in table '{name}' has {rows_read} rows, "
-                    f"{n_rows_read} was expected"
-                )
-        return rows_read
-
-    # length of vector of vectors is the length of its cumulative_length
-    if lgdotype is types.VectorOfVectors:
-        return read_n_rows(f"{name}/cumulative_length", h5f)
-
-    # length of vector of encoded vectors is the length of its decoded_size
-    if lgdotype in (types.VectorOfEncodedVectors, types.ArrayOfEncodedEqualSizedArrays):
-        return read_n_rows(f"{name}/encoded_data", h5f)
-
-    # return array length (without reading the array!)
-    if issubclass(lgdotype, types.Array):
-        # compute the number of rows to read
-        return h5f[name].shape[0]
 
-    msg = f"don't know how to read rows of LGDO {lgdotype.__name__}"
-    raise LH5DecodeError(msg, h5f, name)
+    return _serializers.read.utils.read_n_rows(h5o, h5f.name, name)
 
 
 def get_h5_group(