Replace average with statistics.fmean

The `average` function is just a mean function and Python already offers
a function to calculate a mean, so we use that instead.

We also wrap `fmean` to match the `ResamplingFunction` signature inline
so it is clear in the documentation what the default resampling function
does.

Signed-off-by: Leandro Lucarella <[email protected]>

Author: llucax

src/frequenz/sdk/timeseries/_resampling/_config.py

@@ -6,6 +6,7 @@
 from __future__ import annotations
 
 import logging
+import statistics
 from collections.abc import Sequence
 from dataclasses import dataclass
 from datetime import datetime, timedelta
@@ -79,27 +80,6 @@ def __call__(
         ...  # pylint: disable=unnecessary-ellipsis
 
 
-def average(
-    samples: Sequence[tuple[datetime, float]],
-    resampler_config: ResamplerConfig,  # pylint: disable=unused-argument
-    source_properties: SourceProperties,  # pylint: disable=unused-argument
-) -> float:
-    """Calculate average of all the provided values.
-
-    Args:
-        samples: The samples to apply the average to. It must be non-empty.
-        resampler_config: The configuration of the resampler calling this
-            function.
-        source_properties: The properties of the source being resampled.
-
-    Returns:
-        The average of all `samples` values.
-    """
-    assert len(samples) > 0, "Average cannot be given an empty list of samples"
-    values = list(sample[1] for sample in samples)
-    return sum(values) / len(values)
-
-
 @dataclass(frozen=True)
 class ResamplerConfig:
     """Resampler configuration."""
@@ -134,7 +114,9 @@ class ResamplerConfig:
         passed to the resampling function.
     """
 
-    resampling_function: ResamplingFunction = average
+    resampling_function: ResamplingFunction = lambda samples, _, __: statistics.fmean(
+        s[1] for s in samples
+    )
     """The resampling function.
 
     This function will be applied to the sequence of relevant samples at