handle Sequence subclasses (list/tuple/...); convert object arrays to strings (like the default for non-array types); convert built-in bools to ints (like numpy boolean arrays)

morioc/pvinfo.py

@@ -1,3 +1,4 @@
+from collections.abc import Sequence
 import numpy as np
 
 
@@ -33,11 +34,15 @@ class PVInfo:
 
 
 
-def infer_type(value, parse_string=True): #TODO lists/tuples/...? char vs. strings?
+def infer_type(value, parse_string=True): #TODO char vs. strings?
+    if isinstance(value, Sequence) and not isinstance(value, str):
+        value = np.array(value) # rely on numpy to figure out a consistent dtype
+
     if isinstance(value, np.ndarray):
         return infer_type_numpy(value) #TODO: also parse strings for np arrays?!
     elif isinstance(value, np.generic): # covers all numpy scalars
         value = value.item()
+
     return infer_type_scalar(value, parse_string=parse_string)
 
 
@@ -74,8 +79,9 @@ def infer_type_scalar(value, parse_string=True):
 
 
 def infer_type_numpy(arr):
+    # cannot infer a single type from object arrays, default to string representation
     if arr.dtype == object:
-        raise NotImplementedError("cannot infer a single type from object arrays")
+        return "string", str(arr.tolist())
 
     # bool -> int
     if arr.dtype == bool:
@@ -83,7 +89,7 @@ def infer_type_numpy(arr):
 
     # epics only allows 1D, and needs conversion to built-in data types
     lst = arr.ravel().tolist()
-    dtype, _ = infer_type_scalar(lst[0])
+    dtype, _ = infer_type_scalar(lst[0]) # TODO: is taking the first element safe? object arrays are ruled out above...
     count = len(lst)
 
     return dtype, lst, count

morioc/test_infer_type.py

@@ -66,11 +66,9 @@ def test_it_None():
     assert it(None) == ("string", "None")
 
 def test_it_True():
-#    assert it(True) == ("string", "True")
     assert it(True) == ("int", 1)
 
 def test_it_False():
-#    assert it(False) == ("string", "False")
     assert it(False) == ("int", 0)
 
 def test_it_nan():
@@ -116,11 +114,9 @@ def test_it_np1D_bool():
 
 def test_it_np1D_object():
     arr = np.array([None]) # gives dtype=object
-    with pytest.raises(NotImplementedError):
+    assert it(arr) == ("string", "[None]")
-        it(arr)
     arr = np.array(["test", 123, 1.23], dtype=object)
-    with pytest.raises(NotImplementedError):
+    assert it(arr) == ("string", "['test', 123, 1.23]")
-        it(arr)
 
 
 def test_it_np_scalar_int():
@@ -137,6 +133,20 @@ def test_it_np_scalar_bool():
     scalar = np.array(True)[()]
     ref = scalar.item()
     assert it(scalar) == ("int", 1)
+    scalar = np.array(False)[()]
+    ref = scalar.item()
+    assert it(scalar) == ("int", 0)
+
+
+def test_it_list():
+    dat = [0, 1, 2]
+    ref = dat
+    assert it(dat) == ("int", ref, len(ref))
+
+def test_it_tuple():
+    dat = (0, 1, 2)
+    ref = list(dat)
+    assert it(dat) == ("int", ref, len(ref))