Document utilities

great_ai/utilities/parallel_map/simple_parallel_map.py

@@ -15,6 +15,36 @@ def simple_parallel_map(
     chunk_size: Optional[int] = None,
     concurrency: Optional[int] = None,
 ) -> List[V]:
+    """Execute a map operation on an list mimicking the API of the built-in `map()`.
+
+    A thin-wrapper over [parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map].
+    For more options, consult the documentation of
+    [parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map].
+
+    Examples:
+        >>> import math
+        >>> list(simple_parallel_map(math.sqrt, [9, 4, 1]))
+        [3.0, 2.0, 1.0]
+
+    Args:
+        func: The function that should be applied to each element of `input_values`.
+            It can `async`, in that case, a new event loop is started for each chunk.
+        input_values: An iterable of items that `func` is applied to.
+        chunk_size: Tune the number of items processed in each step. Larger numbers
+            result in smaller communication overhead but less parallelism at the start
+            and end. If `chunk_size` has a `__len__` property, the `chunk_size` is
+            calculated automatically if not given.
+        concurrency: Number of new processes to start. Shouldn't be too much more than
+            the number of physical cores.
+
+    Returns:
+        An iterable of results obtained from applying `func` to each input value.
+
+    Raises:
+        WorkerException: If there was an error in the `func` function in a background
+            process.
+    """
+
     input_values = list(input_values)  # in case the input is mistakenly not a sequence
     return list(
         tqdm(