PyPI · #3294 most downloaded on PyPI

coreforecast

0.0.181.5M downloads/moNixtla/coreforecast ↗New releases in your daily digest, changelog included.

Fast implementations of common forecasting routines

Last release 2 months ago
09 Jul 2026
Release timing varies
gaps range from 1 weeks to 11 months
Nearly every release is documented
notes for 19 of 19 stable releases
Nothing withdrawn
no release was ever pulled
3 years old
20 releases · first in 2023

Release timeline

20 releases since 2023

2023202420252026

20232026

One column per quarter.

Releases

0.0.189 Jul 2026
[CHORE] Updating packages settings Saul (@nasaul)
Changes

[CHORE] Updating packages settings Saul (@nasaul) (#137)
Open source →
0.0.1724 Feb 2026
[FEAT] Implements NaN handling Saul (@nasaul)
Changes

[FEAT] Implements NaN handling Saul (@nasaul) (#111)

[FIX] Box-Cox lambda when using Guerrero's method Mariana Menchero García (@MMenchero) (#97)

[CHORE] Update Python support: Adds 3.14 and drops 3.9 Saul (@nasaul) (#112)

Docs

[DOCS] Update title Deven Mistry (@deven367) (#124)

[DOCS] Documentation improvement for new release Saul (@nasaul) (#113)

[DOCS] migrate to docs.json Deven Mistry (@deven367) (#108)

[DOCS]Removes Deployment from build-docs for Community based PR Saul (@nasaul) (#110)

[DOCS] lazydocs to mkdocstrings Deven Mistry (@deven367) (#104)

[DOCS] Fix table render Deven Mistry (@deven367) (#107)

[DOCS] Third party licenses Deven Mistry (@deven367) (#106)

[DOCS] Doc enhancements Deven Mistry (@deven367) (#101)

0.0.17.dev024 Feb 2026pre-release

Bumps to dev version in order to test release

Open source →

0.0.163 Apr 2025

fix: remove _greatest_autocovariance by José Morales (@jmoralez) in #65

What's Changed

fix: remove _greatest_autocovariance by José Morales (@jmoralez) in #65
use eigen by José Morales (@jmoralez) in #70
fix(exponentially_weighted_mean): add non-contiguous array support by Christopher Titchen (@christophertitchen) in #79
fix lag update by José Morales (@jmoralez) in #86

New Contributors

Christopher Titchen (@christophertitchen) made their first contribution in #79

Full Changelog: v0.0.15...v0.0.16

Open source →

0.0.1515 Nov 2024

fix(rolling): return NaN when n < min_samples by José Morales (@jmoralez) in #62

What's Changed

fix(rolling): return NaN when n < min_samples by José Morales (@jmoralez) in #62

Full Changelog: v0.0.14...v0.0.15

Open source →

0.0.145 Nov 2024

feat: add GroupedArray._greatest_autocovariance to estimate season length by José Morales (@jmoralez) in #59

What's Changed

feat: add GroupedArray._greatest_autocovariance to estimate season length by José Morales (@jmoralez) in #59

Full Changelog: v0.0.13.1...v0.0.14

Open source →

0.0.13.116 Oct 2024

fix: do not edit library output path by José Morales (@jmoralez) in #56

What's Changed

fix: do not edit library output path by José Morales (@jmoralez) in #56

Full Changelog: v0.0.13...v0.0.13.1

Open source →

0.0.1314 Oct 2024

add ruff formatting, pre-commit and codspeed by José Morales (@jmoralez) in #43

What's Changed

add ruff formatting, pre-commit and codspeed by José Morales (@jmoralez) in #43
migrate to pybind11 by José Morales (@jmoralez) in #48
migration fixes by José Morales (@jmoralez) in #54

Full Changelog: v0.0.12...v0.0.13

Open source →

0.0.1217 Jul 2024

return NaN for empty series in reduce by José Morales (@jmoralez) in #41

What's Changed

return NaN for empty series in reduce by José Morales (@jmoralez) in #41

Full Changelog: v0.0.11...v0.0.12

Open source →

0.0.1117 Jul 2024

use standard thread instead of openmp by @jmoralez in https://github.com/Nixtla/coreforecast/pull/37

What's Changed

use standard thread instead of openmp by @jmoralez in https://github.com/Nixtla/coreforecast/pull/37
define lambda captures by @jmoralez in https://github.com/Nixtla/coreforecast/pull/40

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.10...v0.0.11

Open source →

0.0.1014 Jun 2024

stack allocate GroupedArray by @jmoralez in https://github.com/Nixtla/coreforecast/pull/35

What's Changed

stack allocate GroupedArray by @jmoralez in https://github.com/Nixtla/coreforecast/pull/35

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.9...v0.0.10

Open source →

0.0.97 May 2024

Create CODE_OF_CONDUCT.md by @tracykteal in https://github.com/Nixtla/coreforecast/pull/29

What's Changed

Create CODE_OF_CONDUCT.md by @tracykteal in https://github.com/Nixtla/coreforecast/pull/29
define C API by @jmoralez in https://github.com/Nixtla/coreforecast/pull/30
build wheels for linux arm by @jmoralez in https://github.com/Nixtla/coreforecast/pull/31
add single array transformations by @jmoralez in https://github.com/Nixtla/coreforecast/pull/32
speedup rolling min and max by @jmoralez in https://github.com/Nixtla/coreforecast/pull/33

New Contributors

@tracykteal made their first contribution in https://github.com/Nixtla/coreforecast/pull/29

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.8...v0.0.9

Open source →

0.0.810 Apr 2024

ensure dtypes match in scalers by @jmoralez in https://github.com/Nixtla/coreforecast/pull/28

What's Changed

ensure dtypes match in scalers by @jmoralez in https://github.com/Nixtla/coreforecast/pull/28

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.7...v0.0.8

Open source →

0.0.728 Feb 2024

fix boxcox inequality check by @jmoralez in https://github.com/Nixtla/coreforecast/pull/25

What's Changed

fix boxcox inequality check by @jmoralez in https://github.com/Nixtla/coreforecast/pull/25
fix take method for differences by @jmoralez in https://github.com/Nixtla/coreforecast/pull/26

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.6...v0.0.7

Open source →

0.0.620 Feb 2024

add loglik method to boxcox by @jmoralez in https://github.com/Nixtla/coreforecast/pull/23

What's Changed

add loglik method to boxcox by @jmoralez in https://github.com/Nixtla/coreforecast/pull/23
add stack method by @jmoralez in https://github.com/Nixtla/coreforecast/pull/24

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.5...v0.0.6

Open source →

0.0.515 Feb 2024

add take method to scalers and lag_transforms by @jmoralez in https://github.com/Nixtla/coreforecast/pull/21

What's Changed

add take method to scalers and lag_transforms by @jmoralez in https://github.com/Nixtla/coreforecast/pull/21
add Difference scaler by @jmoralez in https://github.com/Nixtla/coreforecast/pull/22

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.4...v0.0.5

Open source →

0.0.412 Feb 2024

add docs by @jmoralez in https://github.com/Nixtla/coreforecast/pull/11

What's Changed

add docs by @jmoralez in https://github.com/Nixtla/coreforecast/pull/11
add boxcox by @jmoralez in https://github.com/Nixtla/coreforecast/pull/15
add differences by @jmoralez in https://github.com/Nixtla/coreforecast/pull/16
add auto seasonality by @jmoralez in https://github.com/Nixtla/coreforecast/pull/18
add update method to differences by @jmoralez in https://github.com/Nixtla/coreforecast/pull/19

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.3...v0.0.4

Open source →

0.0.329 Nov 2023

add quantiles by @jmoralez in https://github.com/Nixtla/coreforecast/pull/8

What's Changed

add quantiles by @jmoralez in https://github.com/Nixtla/coreforecast/pull/8
allocate empty arrays by @jmoralez in https://github.com/Nixtla/coreforecast/pull/9

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.2...v0.0.3

Open source →

0.0.23 Nov 2023

add templates to support float64 by @jmoralez in https://github.com/Nixtla/coreforecast/pull/4

What's Changed

add templates to support float64 by @jmoralez in https://github.com/Nixtla/coreforecast/pull/4
lag transforms by @jmoralez in https://github.com/Nixtla/coreforecast/pull/6

Full Changelog: https://github.com/Nixtla/coreforecast/compare/v0.0.1...v0.0.2

Open source →

0.0.111 Oct 2023

initial packaging by @jmoralez in https://github.com/Nixtla/coreforecast/pull/1

Changes

Add scalers
initial packaging by @jmoralez in https://github.com/Nixtla/coreforecast/pull/1

Full Changelog: https://github.com/Nixtla/coreforecast/commits/v0.0.1

Open source →

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coreforecast

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