From 621a8f2467ea43ce23bb8061ad14fa5e796f2508 Mon Sep 17 00:00:00 2001
From: Tom White <tom.e.white@gmail.com>
Date: Thu, 11 Apr 2024 16:10:52 +0100
Subject: [PATCH] Deprecate misspelled `aggegrate_func` in favour of
 `aggregate_func`

---
 cubed/array_api/statistical_functions.py |  2 +-
 cubed/core/ops.py                        | 25 ++++++++++++++++--------
 cubed/nan_functions.py                   |  2 +-
 3 files changed, 19 insertions(+), 10 deletions(-)

diff --git a/cubed/array_api/statistical_functions.py b/cubed/array_api/statistical_functions.py
index a7d7d9ae..78ff6ae2 100644
--- a/cubed/array_api/statistical_functions.py
+++ b/cubed/array_api/statistical_functions.py
@@ -47,7 +47,7 @@ def mean(x, /, *, axis=None, keepdims=False, use_new_impl=True, split_every=None
         x,
         _mean_func,
         combine_func=_mean_combine,
-        aggegrate_func=_mean_aggregate,
+        aggregate_func=_mean_aggregate,
         axis=axis,
         intermediate_dtype=intermediate_dtype,
         dtype=dtype,
diff --git a/cubed/core/ops.py b/cubed/core/ops.py
index deba169c..a8fa6acb 100644
--- a/cubed/core/ops.py
+++ b/cubed/core/ops.py
@@ -6,6 +6,7 @@
 from numbers import Integral, Number
 from operator import add
 from typing import TYPE_CHECKING, Any, Sequence, Union
+from warnings import warn
 
 import numpy as np
 import zarr
@@ -886,7 +887,8 @@ def reduction(
     x: "Array",
     func,
     combine_func=None,
-    aggegrate_func=None,
+    aggegrate_func=None,  # typo, will removed in next release
+    aggregate_func=None,
     axis=None,
     intermediate_dtype=None,
     dtype=None,
@@ -896,12 +898,19 @@ def reduction(
     extra_func_kwargs=None,
 ) -> "Array":
     """Apply a function to reduce an array along one or more axes."""
+    if aggegrate_func is not None and aggregate_func is None:
+        warn(
+            "`aggegrate_func` is deprecated, please use `aggregate_func` instead",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+        aggregate_func = aggegrate_func
     if use_new_impl:
         return reduction_new(
             x,
             func,
             combine_func,
-            aggegrate_func,
+            aggregate_func,
             axis,
             intermediate_dtype,
             dtype,
@@ -983,8 +992,8 @@ def reduction(
                 extra_func_kwargs=extra_func_kwargs,
             )
 
-    if aggegrate_func is not None:
-        result = map_blocks(aggegrate_func, result, dtype=dtype)
+    if aggregate_func is not None:
+        result = map_blocks(aggregate_func, result, dtype=dtype)
 
     if not keepdims:
         axis_to_squeeze = tuple(i for i in axis if result.shape[i] == 1)
@@ -1002,7 +1011,7 @@ def reduction_new(
     x: "Array",
     func,
     combine_func=None,
-    aggegrate_func=None,
+    aggregate_func=None,
     axis=None,
     intermediate_dtype=None,
     dtype=None,
@@ -1043,8 +1052,8 @@ def reduction_new(
     )
 
     # aggregate final chunks
-    if aggegrate_func is not None:
-        result = map_blocks(aggegrate_func, result, dtype=dtype)
+    if aggregate_func is not None:
+        result = map_blocks(aggregate_func, result, dtype=dtype)
 
     if not keepdims:
         axis_to_squeeze = tuple(i for i in axis if result.shape[i] == 1)
@@ -1213,7 +1222,7 @@ def arg_reduction(
         out,
         _arg_func,
         combine_func=partial(_arg_combine, arg_func=arg_func),
-        aggegrate_func=_arg_aggregate,
+        aggregate_func=_arg_aggregate,
         axis=axis,
         intermediate_dtype=intermediate_dtype,
         dtype=dtype,
diff --git a/cubed/nan_functions.py b/cubed/nan_functions.py
index 13ccfdc2..2acd308b 100644
--- a/cubed/nan_functions.py
+++ b/cubed/nan_functions.py
@@ -26,7 +26,7 @@ def nanmean(x, /, *, axis=None, keepdims=False, use_new_impl=True, split_every=N
         x,
         _nanmean_func,
         combine_func=_nanmean_combine,
-        aggegrate_func=_nanmean_aggregate,
+        aggregate_func=_nanmean_aggregate,
         axis=axis,
         intermediate_dtype=intermediate_dtype,
         dtype=dtype,