Merge pull request #242 in LCL/wolframclientforpython from bugfix/396642-immutabledict to master

* commit '75e7631324eaea9b9c90471c4289cb48e71c169c':
  Fix bad expected PIL result.
  Update Pandas tests
  adding test for nested assocs
  upgrading isort
  adding immutabledict
  updating aiohttp

Author: crazyeng

wolframclient/cli/commands/refactor.py

@@ -10,7 +10,7 @@ class Command(SimpleCommand):
 
     modules = ["wolframclient"]
 
-    dependencies = (("isort", "4.3.20"), ("autoflake", "1.3"), ("black", "19.3b0"))
+    dependencies = (("isort", "5.3.2"), ("autoflake", "1.3"), ("black", "19.3b0"))
 
     def _module_args(self, *args):
 

wolframclient/cli/commands/test.py

@@ -23,7 +23,7 @@ def dependencies():
         yield ("pandas", "1.0.4")
         yield ("unittest-xml-reporting", None)
     if not six.PY2:
-        yield ("aiohttp", "3.4.4")
+        yield ("aiohttp", "3.6.2")
 
 
 class Command(SimpleCommand):

wolframclient/deserializers/wxf/wxfconsumer.py

@@ -8,6 +8,7 @@
 from wolframclient.serializers.wxfencoder import constants
 from wolframclient.serializers.wxfencoder.utils import array_to_list
 from wolframclient.utils.api import numpy
+from wolframclient.utils.datastructures import immutabledict
 
 __all__ = ["WXFConsumer", "WXFConsumerNumpy"]
 
@@ -112,7 +113,7 @@ def build_function(self, head, arg_list, **kwargs):
         """
         return WLFunction(head, *arg_list)
 
-    def consume_association(self, current_token, tokens, dict_class=dict, **kwargs):
+    def consume_association(self, current_token, tokens, dict_class=immutabledict, **kwargs):
         """Consume a :class:`~wolframclient.deserializers.wxf.wxfparser.WXFToken` of type *association*.
 
         By default, return a :class:`dict` made from the rules.

wolframclient/tests/deserializers/wxf_deserialize.py

@@ -18,9 +18,9 @@
 from wolframclient.tests.configure import skip_for_jython
 from wolframclient.utils import six
 from wolframclient.utils.api import numpy
+from wolframclient.utils.datastructures import immutabledict
 from wolframclient.utils.tests import TestCase as BaseTestCase
 
-
 class TestCase(BaseTestCase):
     def test_token_dimensions(self):
         token = WXFToken(None)
@@ -199,6 +199,13 @@ def test_compressed_input(self):
         res = binary_deserialize(wxf, consumer=WXFConsumer())
         self.assertEqual(expr, res)
 
+    def test_nested_associations(self):
+        expr = immutabledict((('a', 2), ('a', 3)))
+        expr = immutabledict(((expr, expr), (2, 3)))
+        wxf = export(expr, target_format="wxf", compress=True)
+        res = binary_deserialize(wxf, consumer=WXFConsumer())
+        self.assertEqual(expr, res)
+
     # Custom consumers
     class BadGreedyConsumer(WXFConsumer):
         def consume_function(self, current_token, tokens, **kwargs):

wolframclient/tests/serializers/pandas.py

@@ -37,27 +37,19 @@ def sparse_series_dict(self):
         d["b"] = 1
         d["a"] = 0
         d["c"] = 2
-        return pandas.SparseSeries(d)
+        return pandas.Series(d, dtype='Sparse[int]')
 
     def sparse_series_dict_indexed(self):
         constructor_dict = {1: 1.0}
         index = [0, 1, 2]
         # Series with index passed in
-        series = pandas.Series(constructor_dict)
-        return pandas.SparseSeries(series, index=index)
-
-    def sparse_series_list_fill_zero(self):
-        return pandas.SparseArray([1, 0, 3, 0], dtype=numpy.int64, fill_value=0)
-
-    def sparse_series_date(self):
-        arr, index = self.create_numpy_data_nan()
-        date_index = pandas.bdate_range("1/1/2011", periods=len(index))
-        return pandas.SparseSeries(arr, index=date_index, kind="block", name="bseries")
+        series = pandas.Series(constructor_dict, dtype='Sparse[float]')
+        return pandas.Series(series, index=index)
 
     def multiindex_series(self):
         mi = pandas.MultiIndex(
             levels=[["a", "b"], ["x", "y"], [0]],
-            labels=[
+            codes=[
                 [1, 1, 1, 1, 0, 0, 0, 0],
                 [0, 0, 1, 1, 0, 0, 1, 1],
                 [0, -1, 0, -1, 0, -1, 0, -1],
@@ -192,24 +184,6 @@ def test_sparse_from_dict_indexed_as_dataset(self):
             pandas_series_head="dataset",
         )
 
-    # sparse array with zeros
-    def test_sparse_array_as_numpy(self):
-        sparse_s = self.sparse_series_list_fill_zero()
-        self.export_compare(
-            sparse_s,
-            wl=b'BinaryDeserialize[ByteArray["ODrCAwEEAQAAAAAAAAADAAAAAAAAAA=="]]',
-            wxf=b"8:\xc2\x03\x01\x04\x01\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00",
-        )
-
-    # timeseries
-    def test_timeseries(self):
-        ts = self.sparse_series_date()
-        self.export_compare(
-            ts,
-            wl=b'TimeSeries[{{DateObject[{2011, 1, 3, 0, 0, 0.}, "Instant", "Gregorian", $TimeZone], 0.}, {DateObject[{2011, 1, 4, 0, 0, 0.}, "Instant", "Gregorian", $TimeZone], Indeterminate}, {DateObject[{2011, 1, 5, 0, 0, 0.}, "Instant", "Gregorian", $TimeZone], 2.}, {DateObject[{2011, 1, 6, 0, 0, 0.}, "Instant", "Gregorian", $TimeZone], Indeterminate}, {DateObject[{2011, 1, 7, 0, 0, 0.}, "Instant", "Gregorian", $TimeZone], 4.}}]',
-            wxf=b"8:f\x01s\nTimeSeriesf\x05s\x04Listf\x02s\x04Listf\x04s\nDateObjectf\x06s\x04Listj\xdb\x07C\x01C\x03C\x00C\x00r\x00\x00\x00\x00\x00\x00\x00\x00S\x07InstantS\tGregorians\t$TimeZoner\x00\x00\x00\x00\x00\x00\x00\x00f\x02s\x04Listf\x04s\nDateObjectf\x06s\x04Listj\xdb\x07C\x01C\x04C\x00C\x00r\x00\x00\x00\x00\x00\x00\x00\x00S\x07InstantS\tGregorians\t$TimeZones\rIndeterminatef\x02s\x04Listf\x04s\nDateObjectf\x06s\x04Listj\xdb\x07C\x01C\x05C\x00C\x00r\x00\x00\x00\x00\x00\x00\x00\x00S\x07InstantS\tGregorians\t$TimeZoner\x00\x00\x00\x00\x00\x00\x00@f\x02s\x04Listf\x04s\nDateObjectf\x06s\x04Listj\xdb\x07C\x01C\x06C\x00C\x00r\x00\x00\x00\x00\x00\x00\x00\x00S\x07InstantS\tGregorians\t$TimeZones\rIndeterminatef\x02s\x04Listf\x04s\nDateObjectf\x06s\x04Listj\xdb\x07C\x01C\x07C\x00C\x00r\x00\x00\x00\x00\x00\x00\x00\x00S\x07InstantS\tGregorians\t$TimeZoner\x00\x00\x00\x00\x00\x00\x10@",
-        )
-
     # multi index
     def test_multiindex_as_assoc(self):
         s = self.multiindex_series()

wolframclient/tests/serializers/wl_pil.py

@@ -33,7 +33,7 @@ def test_bool_img(self):
         out = export(img, target_format="wl")
         self.assertTrue(
             out
-            == b'Image[BinaryDeserialize[ByteArray["ODrCEAICAgEAAAA="]], "Bit", Rule[ColorSpace, Automatic], Rule[Interleaving, True]]'
+            == b'Image[BinaryDeserialize[ByteArray["ODrCEAICAgEAAAE="]], "Bit", Rule[ColorSpace, Automatic], Rule[Interleaving, True]]'
             or out
-            == b'Image[BinaryDeserialize[ByteArray["ODrCEAICAgEAAAA="]], "Bit", Rule[Interleaving, True], Rule[ColorSpace, Automatic]]'
+            == b'Image[BinaryDeserialize[ByteArray["ODrCEAICAgEAAAE="]], "Bit", Rule[Interleaving, True], Rule[ColorSpace, Automatic]]'
         )

wolframclient/utils/datastructures.py

@@ -10,6 +10,50 @@ def __repr__(self):
         return dict.__repr__(self)
 
 
+def _fail(self, *args, **opts):
+    raise TypeError("{0} does not support item assignment".format(self.__class__.__name__))
+
+
+class immutabledict(dict):
+    """
+    hashable dict implementation, suitable for use as a key into
+    other dicts.
+
+        >>> h1 = immutabledict({"apples": 1, "bananas":2})
+        >>> h2 = immutabledict({"bananas": 3, "mangoes": 5})
+        >>> h1+h2
+        immutabledict(apples=1, bananas=3, mangoes=5)
+        >>> d1 = {}
+        >>> d1[h1] = "salad"
+        >>> d1[h1]
+        'salad'
+        >>> d1[h2]
+        Traceback (most recent call last):
+        ...
+        KeyError: immutabledict(bananas=3, mangoes=5)
+
+    based on answers from
+       http://stackoverflow.com/questions/1151658/python-hashable-dicts
+
+    """
+
+    def __hash__(self):
+        return hash(tuple(self.items()))
+
+    __setitem__ = _fail
+    __delitem__ = _fail
+    clear = _fail
+    pop = _fail
+    popitem = _fail
+    setdefault = _fail
+    update = _fail
+
+    def __add__(self, right):
+        result = hashdict(self)
+        dict.update(result, right)
+        return result
+
+
 class Settings(dict):
     """
     Dictionary subclass enabling attribute lookup/assignment of keys/values.