[python-hdf5storage] 123/152: Changed the default marshaller for HDF5 Groups to be NumpyScalarArrayMarshaller as opposed to PythonDictMarshaller.

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to annotated tag 0.1
in repository python-hdf5storage.

commit 7e261a82918251435822e00affa3f0913bb57279
Author: Freja Nordsiek <fnordsie at gmail.com>
Date:   Fri Feb 14 17:29:31 2014 -0500

    Changed the default marshaller for HDF5 Groups to be NumpyScalarArrayMarshaller as opposed to PythonDictMarshaller.
---
 hdf5storage/Marshallers.py |  5 +++--
 hdf5storage/lowlevel.py    | 13 +++++--------
 2 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/hdf5storage/Marshallers.py b/hdf5storage/Marshallers.py
index 72e8828..560b476 100644
--- a/hdf5storage/Marshallers.py
+++ b/hdf5storage/Marshallers.py
@@ -1208,8 +1208,9 @@ class PythonDictMarshaller(TypeMarshaller):
         self.types = [dict]
         self.python_type_strings = ['dict']
         self.__MATLAB_classes = {dict: 'struct'}
-        # Set matlab_classes to the supported classes (the values).
-        self.matlab_classes = list(self.__MATLAB_classes.values())
+        # Set matlab_classes to empty since NumpyScalarArrayMarshaller
+        # handles Groups by default now.
+        self.matlab_classes = list()
 
     def write(self, f, grp, name, data, type_string, options):
         # If the group doesn't exist, it needs to be created. If it
diff --git a/hdf5storage/lowlevel.py b/hdf5storage/lowlevel.py
index 379dbfa..487670a 100644
--- a/hdf5storage/lowlevel.py
+++ b/hdf5storage/lowlevel.py
@@ -162,10 +162,10 @@ def read_data(f, grp, name, options):
 
     # If the type_string is present, get the marshaller for it. If it is
     # not, use the one for the matlab class if it is given. Otherwise,
-    # use the fallback (NumpyScalarArrayMarshaller for Datasets and
-    # PythonDictMarshaller for Groups). If calls to the marshaller
-    # collection to get the right marshaller don't return one (return
-    # None), we also go to the default).
+    # use the fallback (NumpyScalarArrayMarshaller for both Datasets and
+    # Groups). If calls to the marshaller collection to get the right
+    # marshaller don't return one (return None), we also go to the
+    # default).
 
     m = None
     mc = options.marshaller_collection
@@ -175,10 +175,7 @@ def read_data(f, grp, name, options):
         m = mc.get_marshaller_for_matlab_class(matlab_class)
 
     if m is None:
-        if isinstance(grp[name], h5py.Dataset):
-            m = mc.get_marshaller_for_type(np.uint8)
-        else:
-            m = mc.get_marshaller_for_type(dict)
+        m = mc.get_marshaller_for_type(np.uint8)
 
     # If a marshaller was found, use it to write the data. Otherwise,
     # return an error.

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