Allow num_regression to accept array-like inputs

CHANGELOG.rst

@@ -1,3 +1,8 @@
+2.2.0 (UNRELEASED)
+------------------
+
+* `#45 <https://github.com/ESSS/pytest-regressions/pull/45>`__: ``num_regression.check`` now accepts any object that can be coerced to a 1d ``numpy`` array with numeric ``dtype`` (e.g. list, tuple, etc).
+
 2.1.1 (2020-12-7)
 ------------------
 

src/pytest_regressions/num_regression.py

@@ -19,7 +19,7 @@ def check(
     ):
         """
         Checks the given dict against a previously recorded version, or generate a new file.
-        The dict must map from user-defined keys to 1d numpy arrays.
+        The dict must map from user-defined keys to 1d numpy arrays or array-like values.
 
         Example::
 
@@ -31,7 +31,8 @@ def check(
                 'P': Pa_to_bar(P)[positions],
             })
 
-        :param dict data_dict: dict mapping keys to numpy arrays.
+        :param dict data_dict: dict mapping keys to numpy arrays, or objects that can be
+            coerced to 1d numpy arrays with a numeric dtype (e.g. list, tuple, etc).
 
         :param str basename: basename of the file to test/record. If not given the name
             of the test is used.
@@ -73,11 +74,17 @@ def check(
 
         __tracebackhide__ = True
 
+        for k, obj in data_dict.items():
+            if not isinstance(obj, np.ndarray):
+                arr = np.atleast_1d(np.asarray(obj))
+                if np.issubdtype(arr.dtype, np.number):
+                    data_dict[k] = arr
+
         data_shapes = []
         for obj in data_dict.values():
             assert type(obj) in [
                 np.ndarray
-            ], "Only numpy arrays are valid for numeric_data_regression fixture.\n"
+            ], "Only objects that can be coerced to numpy arrays are valid for numeric_data_regression fixture.\n"
             shape = obj.shape
 
             assert len(shape) == 1, (

tests/test_num_regression.py

@@ -257,3 +257,39 @@ def test_arrays_of_same_size(num_regression):
         "world": np.zeros((1,), dtype=np.int),
     }
     num_regression.check(same_size_int_arrays)
+
+
+def test_simple_numbers(num_regression, data_regression):
+    data1 = 1.1
+    data2 = 2
+    num_regression.check({"data1": data1, "data2": data2})
+    data_regression.check({"data1": data1, "data2": data2})
+    data1 += 0.00000001
+    num_regression.check({"data1": data1, "data2": data2})  # passes, within tol
+    with pytest.raises(
+        AssertionError,
+        match="FILES DIFFER.*",
+    ):
+        data_regression.check({"data1": data1, "data2": data2})  # fails, must be exact
+
+
+def test_simple_list_of_numbers(num_regression):
+    data1 = [1.1, 1.1, 1.1]
+    data2 = [2, 2, 2]
+    num_regression.check({"data1": data1, "data2": data2})
+
+
+def test_simple_tuple_of_numbers(num_regression):
+    data1 = (1.1, 1.1, 1.1)
+    data2 = (2, 2, 2)
+    num_regression.check({"data1": data1, "data2": data2})
+
+
+def test_simple_list_of_mostly_numbers(num_regression):
+    data1 = [1.1, "not a number", 1.1]
+    data2 = [2, 2, 2]
+    with pytest.raises(
+        AssertionError,
+        match="Only objects that can be coerced to numpy arrays are valid for numeric_data_regression fixture.",
+    ):
+        num_regression.check({"data1": data1, "data2": data2})

tests/test_num_regression/test_simple_floats.csv

@@ -0,0 +1,2 @@
+,data1,data2
+0,1.1000000000000001,2.2000000000000002

tests/test_num_regression/test_simple_list_of_numbers.csv

@@ -0,0 +1,4 @@
+,data1,data2
+0,1.1000000000000001,2
+1,1.1000000000000001,2
+2,1.1000000000000001,2

tests/test_num_regression/test_simple_numbers.csv

@@ -0,0 +1,2 @@
+,data1,data2
+0,1.1000000000000001,2

tests/test_num_regression/test_simple_numbers.yml

@@ -0,0 +1,2 @@
+data1: 1.1
+data2: 2

tests/test_num_regression/test_simple_tuple_of_numbers.csv

@@ -0,0 +1,4 @@
+,data1,data2
+0,1.1000000000000001,2
+1,1.1000000000000001,2
+2,1.1000000000000001,2