Remove add_keys_iter

pangeo_forge_recipes/transforms.py

@@ -5,14 +5,14 @@
 import random
 import sys
 from dataclasses import dataclass, field
-from typing import Callable, Dict, Iterable, Iterator, List, Optional, Tuple, TypeVar, Union
+from typing import Callable, Dict, List, Optional, Tuple, TypeVar, Union
 
 # PEP612 Concatenate & ParamSpec are useful for annotating decorators, but their import
 # differs between Python versions 3.9 & 3.10. See: https://stackoverflow.com/a/71990006
 if sys.version_info < (3, 10):
-    from typing_extensions import Concatenate, ParamSpec
+    from typing_extensions import ParamSpec
 else:
-    from typing import Concatenate, ParamSpec
+    from typing import ParamSpec
 
 import apache_beam as beam
 import fsspec
@@ -90,28 +90,6 @@ class RequiredAtRuntimeDefault:
     pass
 
 
-def _add_keys_iter(
-    func: Callable[Concatenate[T, P], R],
-) -> Callable[Concatenate[Iterable[IndexedArg], P], Iterator[IndexedReturn]]:
-    """Convenience decorator to iteratively remove and re-add keys to items in a FlatMap"""
-    annotations = func.__annotations__.copy()
-    arg_name, annotation = next(iter(annotations.items()))
-    return_annotation = annotations["return"]
-
-    # mypy doesn't view `annotation` and `return_annotation` as valid types, so ignore
-    annotations[arg_name] = Iterable[Tuple[Index, annotation]]  # type: ignore
-    annotations["return"] = Iterator[Tuple[Index, return_annotation]]  # type: ignore
-
-    def iterable_wrapper(arg, *args: P.args, **kwargs: P.kwargs):
-        for inner_item in arg:
-            key, item = inner_item
-            result = func(item, *args, **kwargs)
-            yield key, result
-
-    iterable_wrapper.__annotations__ = annotations
-    return iterable_wrapper
-
-
 def _assign_concurrency_group(elem, max_concurrency: int):
     return (random.randint(0, max_concurrency - 1), elem)
 
@@ -144,11 +122,16 @@ def expand(self, pcoll):
             if not self.max_concurrency
             else (
                 pcoll
-                | beam.Map(_assign_concurrency_group, self.max_concurrency)
-                | beam.GroupByKey()
-                | beam.Values()
+                | "Assign concurrency key"
+                >> beam.Map(_assign_concurrency_group, self.max_concurrency)
+                | "Group together by concurrency key" >> beam.GroupByKey()
+                | "Drop concurrency key" >> beam.Values()
                 | f"{self.fn.__name__} (max_concurrency={self.max_concurrency})"
-                >> beam.FlatMap(_add_keys_iter(self.fn), *self.args, **self.kwargs)
+                >> beam.FlatMap(
+                    lambda kvlist: [
+                        (kv[0], self.fn(kv[1], *self.args, **self.kwargs)) for kv in kvlist
+                    ]
+                )
             )
         )