faststat

fast online statistics collection

Requires Python 3.9 or newer. The library works with Python 3.9 through 3.13. Building the optional Rust extension uses PyO3 0.22 and maturin, so maturin 1.4 or newer is recommended when compiling from source.

very simple API:

>>> import faststat
>>> stats = faststat.Stats()
>>> stats.add(point)
>>> stats.add(point)
...

For lower overhead you can use StatsLite which keeps only the core moments:

>>> lite = faststat.StatsLite()
>>> lite.add(point)

The following properties are accessible on a Stats object: n, min, max, variance, skewness and kurtosis. It also tracks percentiles and other optional features.

StatsLite exposes the same basic properties without the percentile or window-tracking overhead.

Performance is pretty good: 0.63 microseconds per point on my machine. (Provided the C module is available.)

In pure Python mode, performance is about 9 microseconds per point.

0.615999937057 microseconds per point
mean (should be 1) 0.998333953189
kurtosis / reference kurtosis -0.0021881144433 -0.00220621681959
variance / reference variance 0.999219190297 0.999219190297
skewness (should be 0) -0.0071960817771
max, min 5.83625092886 -3.4749002526
m2, m3, m4 999218.191078 -7187.64448532 2993126.28574
9.00099992752 microseconds per point
mean (should be 1) 0.998333953189
kurtosis / reference kurtosis -0.0021881144433 -0.00220621681959
variance / reference variance 0.999219190297 0.999219190297
skewness (should be 0) -0.0071960817771
max, min 5.83625092886 -3.4749002526
m2, m3, m4 999218.191078 -7187.64448532 2993126.28574

Rust Usage

A standalone Rust crate faststat-core provides the same streaming statistics. Example:

use faststat_core::Stats;

let mut s = Stats::new();
s.add(1.0);
s.add(2.0);
println!("mean {}", s.mean());

Profiler

The :mod:faststat.profiler module can attach using the standard sys.setprofile and sys.settrace hooks to collect per-function or per-line timing information. Run a script under the profiler using::

python -m faststat.profiler myscript.py

This prints timing statistics for the executed code.