statistics.kde has inconsistent and counterintuitive caching behaviour
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@rhettinger is already working on this.
Since Aug 6, 2026.
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Description
Bug report
Bug description:
The author appears to be trying to support this pattern:
data = [1, 2, 3]
f = kde(data, h=1)
data.append(4) # length changed
f(2)
In that case len(data) != n becomes true and the sorted sample is rebuilt.
However, this pattern is implemented inconsistently, and does not check value changes, only length changes.
import statistics
data = [1, 2, 3]
f = statistics.kde(data, h=1.0, kernel='triangular')
z = f(1.5)
print(z)
data[0] = 5
print(f(1.5))
data.pop()
print(f(1.5))
data = [1, 2, 3]
f = statistics.kde(data, h=1.0, kernel='normal')
z = f(1.5)
print(z)
data[0] = 5
print(f(1.5))
data.pop()
print(f(1.5))
output:
0.3333333333333333
0.3333333333333333
0.25
vs.
0.2778827497314969
0.16081853504174567
0.17646900472967264
CPython versions tested on:
3.13
Operating systems tested on:
Other
Linked PRs
- gh-155034
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