Repository: ramonhagenaars/nptyping

Issue:
Nested dtype support
How would you be able to use `nptyping` to define the type of a structured array with the following `dtype`:

```python
dtype = numpy.dtype([('index', numpy.uint64), ('measurements', numpy.float64, (2,))])
```
I tried variations of
```python
NDArray[Shape["*"], Structure["index: UInt64, measurements: Float64"]])
```
but this doesn't work (`assert_isinstance` fails), and I couldn't define anything in the docs that would allow for specifying the shape `(2,)` of the `measurements` sub-array.

Would it be possible to directly use `dtype` objects for type specs?

Discussion:
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Patch:
diff --git a/HISTORY.md b/HISTORY.md
index 40c00c1..5409690 100644
--- a/HISTORY.md
+++ b/HISTORY.md
@@ -1,5 +1,10 @@
 # History
 
+## 2.3.0 (2022-08-28)
+
+- Added support for subarrays with shape expressions inside structure expressions.
+- Added support for wildcards in structure expressions.
+
 ## 2.2.0 (2022-06-26)
 
 - Added support for expressing "at least N dimensions".
diff --git a/README.md b/README.md
index b64c1c4..f9bf3c1 100644
--- a/README.md
+++ b/README.md
@@ -80,6 +80,13 @@ True
 
 ```
 
+Subarrays can be expressed with a shape expression between square brackets:
+```python
+>>> Structure["name: Int[3, 3]"]
+Structure['name: Int[3, 3]']
+
+```
+
 ### Record arrays
 The recarray is a specialization of a structured array. You can use `RecArray`
 to express them.
diff --git a/USERDOCS.md b/USERDOCS.md
index b4b4935..203a8fc 100644
--- a/USERDOCS.md
+++ b/USERDOCS.md
@@ -19,6 +19,7 @@
     * [DTypes](#DTypes)
     * [Structure expressions](#Structure-expressions)
       * [Syntax](#Syntax-structure-expressions)
+      * [Subarrays](#Subarrays)
     * [RecArray](#RecArray)
 * [Examples](#Examples)
 * [Similar projects](#Similar-projects)
@@ -212,8 +213,6 @@ False
 
 ```
 
-
-
 #### Dimension breakdowns
 A dimension can be broken down into more detail. We call this a **dimension breakdown**. This can be useful to clearly
 describe what a dimension means. Example:
@@ -328,7 +327,6 @@ NDArray[Any, Floating]
 
 ```
 
-
 ### Structure expressions
 You can denote the structure of a structured array using what we call a **structure expression**. This expression 
 - again a string - can be put into `Structure` and can then be used in an `NDArray`.
@@ -391,10 +389,12 @@ colons), but this is not included in the schema below.
 ```
 structure-expression  =  <fields>
 fields                =  <field>|<field>","<fields>
-field                 =  <field_name>":"<field_type>|"["<combined_field_names>"]:"<field_type>
-combined_field_names  =  <field_name>","<field_name>|<field_name>","<combined_field_names>
-field_type            =  <word>
-field_name            =  <word>
+field                 =  <field-name>":"<field-type>|"["<combined-field-names>"]:"<field-type>
+combined-field-names  =  <field-name>","<field-name>|<field-name>","<combined-field-names>
+field-type            =  <word>|<word><field-subarray-shape>|<wildcard>
+wildcard              =  "*"
+field-subarray-shape  = "["<shape-expression>"]"
+field-name            =  <word>
 word                  =  <letter>|<word><underscore>|<word><number>
 letter                =  <lletter>|<uletter> 
 uletter               =  "A"|"B"|"C"|"D"|"E"|"F"|"G"|"H"|"I"|"J"|"K"|"L"|"M"|"N"|"O"|"P"|"Q"|"R"|"S"|"T"|"U"|"V"|"W"|"X"|"Y"|"Z" 
@@ -404,6 +404,20 @@ digit                 =  "0"|"1"|"2"|"3"|"4"|"5"|"6"|"7"|"8"|"9"
 underscore            =  "_"
 ```
 
+#### Subarrays
+You can express the shape of a subarray using brackets after a type. You can use the full power of shape expressions.
+
+```python
+>>> from typing import Any
+>>> import numpy as np
+>>> from nptyping import NDArray, Structure
+
+>>> arr = np.array([("x")], np.dtype([("x", "U10", (2, 2))]))
+>>> isinstance(arr, NDArray[Any, Structure["x: Str[2, 2]"]])
+True
+
+```
+
 ### RecArray
 The `RecArray` corresponds to [numpy.recarray](https://numpy.org/doc/stable/reference/generated/numpy.recarray.html).
 It is an extension of `NDArray` and behaves similarly. A key difference is that with `RecArray`, the `Structure` OR 
diff --git a/nptyping/package_info.py b/nptyping/package_info.py
index a2a4f23..4909726 100644
--- a/nptyping/package_info.py
+++ b/nptyping/package_info.py
@@ -22,7 +22,7 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 """
 __title__ = "nptyping"
-__version__ = "2.2.0"
+__version__ = "2.3.0"
 __author__ = "Ramon Hagenaars"
 __author_email__ = "ramon.hagenaars@gmail.com"
 __description__ = "Type hints for NumPy."
diff --git a/nptyping/structure_expression.py b/nptyping/structure_expression.py
index 63f61d1..119726c 100644
--- a/nptyping/structure_expression.py
+++ b/nptyping/structure_expression.py
@@ -30,12 +30,19 @@ from typing import (
     Dict,
     List,
     Mapping,
+    Type,
     Union,
 )
 
 import numpy as np
 
-from nptyping.error import InvalidStructureError
+from nptyping.error import InvalidShapeError, InvalidStructureError
+from nptyping.shape import Shape
+from nptyping.shape_expression import (
+    check_shape,
+    normalize_shape_expression,
+    validate_shape_expression,
+)
 from nptyping.typing_ import StructureExpression
 
 if TYPE_CHECKING:
@@ -59,6 +66,7 @@ def validate_structure_expression(
         _validate_structure_expression_contains_no_multiple_field_names(
             structure_expression
         )
+        _validate_sub_array_expressions(structure_expression)
 
 
 def check_structure(
@@ -77,17 +85,38 @@ def check_structure(
     :return: True if the given dtype is valid with the given target.
     """
     fields: Mapping[str, Any] = structured_dtype.fields or {}  # type: ignore[assignment]
+
+    # Add the wildcard to the lexicon. We want to do this here to keep
+    # knowledge on wildcards in one place (this module).
+    type_per_name_with_wildcard = {**type_per_name, "*": object}  # type: ignore[arg-type]
+
     for name, dtype_tuple in fields.items():
         dtype = dtype_tuple[0]
         target_type_name = target.get_type(name)
-        check_type_name(target_type_name, type_per_name)
-        target_type = type_per_name[target_type_name]
-        if not issubclass(dtype.type, target_type):
+        target_type_shape_match = re.search(_REGEX_FIELD_SHAPE, target_type_name)
+        actual_type = dtype.type
+        if target_type_shape_match:
+            if not dtype.subdtype:
+                # the dtype does not contain a shape.
+                return False
+            actual_type = dtype.subdtype[0].type
+            target_type_shape = target_type_shape_match.group(1)
+            shape_corresponds = check_shape(dtype.shape, Shape[target_type_shape])
+            if not shape_corresponds:
+                return False
+            target_type_name = target_type_name.replace(
+                target_type_shape_match.group(0), ""
+            )
+        check_type_name(target_type_name, type_per_name_with_wildcard)
+        target_type = type_per_name_with_wildcard[target_type_name]
+        if not issubclass(actual_type, target_type):
             return False
     return True
 
 
-def check_type_names(structure: "Structure", type_per_name: Dict[str, type]) -> None:
+def check_type_names(
+    structure: "Structure", type_per_name: Dict[str, Type[object]]
+) -> None:
     """
     Check the given structure for any invalid type names in the given context
     of type_per_name. Raises an InvalidStructureError if a type name is
@@ -100,7 +129,7 @@ def check_type_names(structure: "Structure", type_per_name: Dict[str, type]) ->
         check_type_name(type_, type_per_name)
 
 
-def check_type_name(type_name: str, type_per_name: Dict[str, type]) -> None:
+def check_type_name(type_name: str, type_per_name: Dict[str, Type[object]]) -> None:
     """
     Check if the given type_name is in type_per_name and raise a meaningful
     error if not.
@@ -108,6 +137,8 @@ def check_type_name(type_name: str, type_per_name: Dict[str, type]) -> None:
     :param type_per_name: a dict that is looked in for type_name.
     :return: None.
     """
+    # Remove any subarray stuff here.
+    type_name = type_name.split("[")[0]
     if type_name not in type_per_name:
         close_matches = get_close_matches(
             type_name, type_per_name.keys(), 3, cutoff=0.4
@@ -135,7 +166,7 @@ def normalize_structure_expression(
     structure_expression = re.sub(r"\s*", "", structure_expression)
     type_to_names_dict = _create_type_to_names_dict(structure_expression)
     normalized_structure_expression = _type_to_names_dict_to_str(type_to_names_dict)
-    return normalized_structure_expression.replace(",", ", ")
+    return normalized_structure_expression.replace(",", ", ").replace("  ", " ")
 
 
 def create_name_to_type_dict(
@@ -188,6 +219,23 @@ def _validate_structure_expression_contains_no_multiple_field_names(
         )
 
 
+def _validate_sub_array_expressions(structure_expression: str) -> None:
+    # Validate that the given structure expression does not contain any shape
+    # expressions for sub arrays that are invalid.
+    for field_match in re.findall(_REGEX_FIELD, structure_expression):
+        field_type = field_match[0].split(_FIELD_TYPE_POINTER)[1]
+        type_shape_match = re.search(_REGEX_FIELD_SHAPE, field_type)
+        if type_shape_match:
+            type_shape = type_shape_match[1]
+            try:
+                validate_shape_expression(type_shape)
+            except InvalidShapeError as err:
+                raise InvalidStructureError(
+                    f"'{structure_expression}' is not a valid structure"
+                    f" expression; {str(err)}"
+                ) from err
+
+
 def _create_type_to_names_dict(
     structure_expression: StructureExpression,
 ) -> Dict[str, List[str]]:
@@ -199,10 +247,17 @@ def _create_type_to_names_dict(
         field_name_combination_match = re.match(
             _REGEX_FIELD_NAMES_COMBINATION, field_name_combination
         )
+        field_type_shape_match = re.search(_REGEX_FIELD_SHAPE, field_type)
         if field_name_combination_match:
             field_names = field_name_combination_match.group(2).split(_SEPARATOR)
         else:
             field_names = [field_name_combination]
+        if field_type_shape_match:
+            type_shape = field_type_shape_match.group(1)
+            normalized_type_shape = normalize_shape_expression(type_shape)
+            field_type = field_type.replace(
+                field_type_shape_match.group(0), f"[{normalized_type_shape}]"
+            )
         names_per_type[field_type] += field_names
     return {
         field_type: sorted(names_per_type[field_type])
@@ -230,7 +285,11 @@ _REGEX_FIELD_NAMES_COMBINATION = rf"(\s*\[{_REGEX_FIELD_NAMES}\]\s*)"
 _REGEX_FIELD_LEFT = rf"({_REGEX_FIELD_NAME}|{_REGEX_FIELD_NAMES_COMBINATION})"
 _REGEX_FIELD_TYPE = r"(\s*[a-zA-Z]\w*\s*)"
 _REGEX_FIELD_TYPE_WILDCARD = r"(\s*\*\s*)"
-_REGEX_FIELD_RIGHT = rf"({_REGEX_FIELD_TYPE}|{_REGEX_FIELD_TYPE_WILDCARD})"
+_REGEX_FIELD_SHAPE = r"\[([^\]]+)\]"
+_REGEX_FIELD_SHAPE_MAYBE = rf"\s*({_REGEX_FIELD_SHAPE})?\s*"
+_REGEX_FIELD_RIGHT = (
+    rf"({_REGEX_FIELD_TYPE}|{_REGEX_FIELD_TYPE_WILDCARD}){_REGEX_FIELD_SHAPE_MAYBE}"
+)
 _REGEX_FIELD_TYPE_POINTER = rf"(\s*{_FIELD_TYPE_POINTER}\s*)"
 _REGEX_FIELD = (
     rf"(\s*{_REGEX_FIELD_LEFT}{_REGEX_FIELD_TYPE_POINTER}{_REGEX_FIELD_RIGHT}\s*)"


Test patch:
diff --git a/tests/test_ndarray.py b/tests/test_ndarray.py
index e4929b4..f4f7676 100644
--- a/tests/test_ndarray.py
+++ b/tests/test_ndarray.py
@@ -187,6 +187,10 @@ class NDArrayTest(TestCase):
             NDArray[Any, Structure["[name, age]: Str"]],
         )
 
+    def test_isinstance_succeeds_if_structure_subarray_matches(self):
+        arr = np.array([("x")], np.dtype([("x", "U10", (2, 2))]))
+        self.assertIsInstance(arr, NDArray[Any, Structure["x: Str[2, 2]"]])
+
     def test_isinstance_fails_if_structure_contains_invalid_types(self):
         with self.assertRaises(InvalidStructureError) as err:
             NDArray[Any, Structure["name: Str, age: Float, address: Address"]]
diff --git a/tests/test_structure_expression.py b/tests/test_structure_expression.py
index 3c77c9d..fc52930 100644
--- a/tests/test_structure_expression.py
+++ b/tests/test_structure_expression.py
@@ -23,6 +23,44 @@ class StructureExpressionTest(TestCase):
         structure2 = Structure["[a, b, c]: Integer"]
         self.assertTrue(check_structure(dtype2, structure2, dtype_per_name))
 
+        dtype3 = np.dtype([("name", "U10")])
+        structure3 = Structure["name: *"]
+        self.assertTrue(check_structure(dtype3, structure3, dtype_per_name))
+
+    def test_check_structure_with_sub_array(self):
+        dtype = np.dtype([("x", "U10", (2, 2))])
+        structure = Structure["x: Str[2, 2]"]
+        self.assertTrue(check_structure(dtype, structure, dtype_per_name))
+
+        dtype2 = np.dtype([("x", "U10", (2, 2))])
+        structure2 = Structure["x: Int[2, 2]"]
+        self.assertFalse(
+            check_structure(dtype2, structure2, dtype_per_name),
+            "It should fail because of the type.",
+        )
+
+        dtype3 = np.dtype([("x", "U10", (3, 3))])
+        structure3 = Structure["x: Str[2, 2]"]
+        self.assertFalse(
+            check_structure(dtype3, structure3, dtype_per_name),
+            "It should fail because of the shape.",
+        )
+
+        dtype4 = np.dtype([("x", "U10", (2, 2)), ("y", "U10", (2, 2))])
+        structure4 = Structure["x: Str[2, 2], y: Str[2, 2]"]
+        self.assertTrue(check_structure(dtype4, structure4, dtype_per_name))
+
+        dtype5 = np.dtype([("x", "U10", (2, 2)), ("y", "U10", (2, 2))])
+        structure5 = Structure["[x, y]: Str[2, 2]"]
+        self.assertTrue(check_structure(dtype5, structure5, dtype_per_name))
+
+        dtype6 = np.dtype([("x", "U10")])
+        structure6 = Structure["x: Str[2, 2]"]
+        self.assertFalse(
+            check_structure(dtype6, structure6, dtype_per_name),
+            "It should fail because it doesn't contain a sub array at all.",
+        )
+
     def test_check_structure_false(self):
         dtype = np.dtype([("name", "U10"), ("age", "i4")])
         structure = Structure["name: Str, age: UInt"]
@@ -66,8 +104,12 @@ class StructureExpressionTest(TestCase):
         validate_structure_expression("a_123: t")
         validate_structure_expression("abc: type")
         validate_structure_expression("abc: *")
+        validate_structure_expression("abc: type[2, 2]")
+        validate_structure_expression("abc: type [*, ...]")
         validate_structure_expression("abc: type, def: type")
+        validate_structure_expression("abc: type[*, 2, ...], def: type[2 ]")
         validate_structure_expression("[abc, def]: type")
+        validate_structure_expression("[abc, def]: type[*, ...]")
         validate_structure_expression("[abc, def]: type1, ghi: type2")
         validate_structure_expression("[abc, def]: type1, [ghi, jkl]: type2")
         validate_structure_expression(
@@ -104,6 +146,15 @@ class StructureExpressionTest(TestCase):
             validate_structure_expression("[a,b,]: type")
         with self.assertRaises(InvalidStructureError):
             validate_structure_expression("[,a,b]: type")
+        with self.assertRaises(InvalidStructureError):
+            validate_structure_expression("abc: type []")
+        with self.assertRaises(InvalidStructureError):
+            validate_structure_expression("a: t[]")
+        with self.assertRaises(InvalidStructureError) as err:
+            validate_structure_expression(
+                "a: t[*, 2, ...], b: t[not-a-valid-shape-expression]"
+            )
+        self.assertIn("not-a-valid-shape-expression", str(err.exception))
         with self.assertRaises(InvalidStructureError) as err:
             validate_structure_expression("a: t1, b: t2, c: t3, a: t4")
         self.assertEqual(
@@ -138,6 +189,9 @@ class StructureExpressionTest(TestCase):
             "[a, b, d, e]: t1, c: t2",
             normalize_structure_expression("[b, a]: t1, c: t2, [d, e]: t1"),
         )
+        self.assertEqual(
+            "a: t[*, ...]", normalize_structure_expression("  a  :  t  [ * , ... ]")
+        )
 
     def test_create_name_to_type_dict(self):
         output = create_name_to_type_dict("a: t1, b: t2, c: t1")