Add NumpyToNativeEncoder with a test

NumpyToNativeEncoder is a custom JSON encoder that encodes numpy types
into native types so it can be saved in JSON.

There is no corresponding decoder, since the JSON just contains native
types and does not need special decoding.

Signed-off-by: Patrick Avery <[email protected]>

hexrd/utils/json.py

@@ -7,6 +7,17 @@
 ndarray_key = '!__hexrd_ndarray__'
 
 
+class NumpyToNativeEncoder(json.JSONEncoder):
+    # Change all Numpy arrays to native types during JSON encoding
+    def default(self, obj):
+        if isinstance(obj, np.ndarray):
+            return obj.tolist()
+        elif isinstance(obj, (np.generic, np.number)):
+            return obj.item()
+
+        return super().default(obj)
+
+
 class NumpyEncoder(json.JSONEncoder):
     def default(self, obj):
         if isinstance(obj, np.ndarray):
@@ -20,7 +31,6 @@ def default(self, obj):
                 ndarray_key: base64.b64encode(data).decode('ascii')
             }
 
-        # Let the base class default method raise the TypeError
         return super().default(obj)
 
 

tests/test_utils_json.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from hexrd.utils.json import NumpyDecoder, NumpyEncoder
+from hexrd.utils.json import NumpyDecoder, NumpyEncoder, NumpyToNativeEncoder
 
 
 def test_decode_encode():
@@ -29,6 +29,36 @@ def test_decode_encode():
     assert _json_equal(to_test, converted_back)
 
 
+def test_numpy_to_native():
+    to_test = {
+        'inside': np.arange(27, dtype=np.int8).reshape((3, 3, 3)),
+        'nested': {
+            'float': np.arange(4, dtype=np.float32).reshape((2, 2)),
+        },
+        'float': np.float64(8.3),
+    }
+
+    inside_to_list = to_test['inside'].tolist()
+    nested_float_to_value = to_test['nested']['float'].tolist()
+    float_to_value = to_test['float'].item()
+
+    encoded = json.dumps(to_test, cls=NumpyToNativeEncoder)
+    output = json.loads(encoded)
+
+    assert (
+        isinstance(output['inside'], list) and
+        output['inside'] == to_test['inside'].tolist()
+    )
+    assert (
+        isinstance(output['float'], float) and
+        output['float'] == to_test['float'].item()
+    )
+    assert (
+        isinstance(output['nested']['float'], list) and
+        output['nested']['float'] == to_test['nested']['float'].tolist()
+    )
+
+
 def _json_equal(a, b):
     if isinstance(a, np.ndarray):
         return np.array_equal(a, b) and a.dtype == b.dtype