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Resolve Annotated types (PEP 593) on dataflow visualizations #1276

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merged 4 commits into from
Feb 11, 2025
Merged

Resolve Annotated types (PEP 593) on dataflow visualizations #1276

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578073e
Use first argument of `Annotated` in string representation
cswartzvi Feb 8, 2025
fc5f3c5
Updated and add tests
cswartzvi Feb 8, 2025
d97d145
Use existing `_is_annotated_type`
cswartzvi Feb 8, 2025
023a384
Using `typing_extensions` for `Annotated` backport
cswartzvi Feb 8, 2025
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4 changes: 3 additions & 1 deletion hamilton/htypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -99,7 +99,9 @@ def get_type_as_string(type_: Type) -> Optional[str]:
:return: string representation of the type. An empty string if everything fails.
"""

if getattr(type_, "__name__", None):
if _is_annotated_type(type_):
type_string = get_type_as_string(typing.get_args(type_)[0])
elif getattr(type_, "__name__", None):
type_string = type_.__name__
elif typing_inspect.get_origin(type_):
base_type = typing_inspect.get_origin(type_)
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12 changes: 12 additions & 0 deletions tests/test_type_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,11 @@
from hamilton import htypes
from hamilton.htypes import check_instance

if sys.version_info >= (3, 9):
from typing import Annotated
else:
from typing_extensions import Annotated


class X:
pass
Expand Down Expand Up @@ -178,6 +183,7 @@ def test__safe_subclass(candidate, type_, expected):
(pd.Series),
(htypes.column[pd.Series, int]),
(pd.DataFrame),
(Annotated[int, "metadata"]),
],
)
def test_get_type_as_string(type_):
Expand All @@ -188,6 +194,12 @@ def test_get_type_as_string(type_):
pytest.fail(f"test get_type_as_string raised: {e}")


def test_type_as_string_with_annotated_type():
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If you feel like doing more testing work we should really test the string output of these, not just that they fail. But that's out of scope.

"""Tests the custom_subclass_check"""
type_string = htypes.get_type_as_string(Annotated[int, "metadata"]) # type: ignore
assert type_string == "int"


@pytest.mark.parametrize(
"node_type,input_value",
[
Expand Down