NeoProphet
Prophet forecasting that is easier to use, clearer to read and faster at scale.
NeoProphet is a drop-in fork of Facebook Prophet with a one-call API, self-explaining charts, built-in tuning and an experimental Apple Silicon GPU backend for fitting many series at once.
Install
pip install neoprophet # or: uv add neoprophet
pip install "neoprophet[mlx]" # adds the MLX backend on Apple Silicon
NeoProphet installs the prophet import package, so it replaces upstream Prophet: uninstall prophet first and do not install both in one environment. Wheels include the compiled Stan model for macOS (Intel and Apple Silicon), Linux (x86-64 and ARM64) and Windows.
Quick start
import pandas as pd
from prophet import forecast
df = pd.read_csv("https://raw.githubusercontent.com/CodeWithBehnam/NeoProphet/main/examples/example_wp_log_peyton_manning.csv")
result = forecast(df, horizon="12 months", country_holidays="US")
result.forecast # ds, yhat, yhat_lower, yhat_upper for the future
result.plot() # the chart above
result.plot_components() # trend, holidays, weekly and yearly patterns
forecast(..., tune=True)chooses the prior scales and seasonality mode by parallel cross-validation.prophet.mlx_backend.fit_many(dfs)fits many series in one batch on an Apple Silicon GPU (experimental; linear and flat growth, MAP only).- The classic API is unchanged:
from prophet import Prophetworks as before.
Links
- Source, benchmarks and notebooks: https://github.com/CodeWithBehnam/NeoProphet
- Issues: https://github.com/CodeWithBehnam/NeoProphet/issues
- Upstream Prophet documentation: https://facebook.github.io/prophet/
- Paper: Taylor and Letham (2018), Forecasting at Scale, The American Statistician 72(1):37-45.
Released under the MIT licence. Prophet was created by Sean J. Taylor and Ben Letham at Facebook.
1 maintainer
Metadata
1 maintainer
Release files for neoprophet 1.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| neoprophet-1.4.0.tar.gz | 129.7 kB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| neoprophet-1.4.0-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details |
| neoprophet-1.4.0-py3-none-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl | Python 3 | none | Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 | Details |
| neoprophet-1.4.0-py3-none-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl | Python 3 | none | Linux glibc 2.26+ ARM64, Linux glibc 2.28+ ARM64 | Details |
| neoprophet-1.4.0-py3-none-macosx_11_0_arm64.whl | Python 3 | none | macOS 11.0+ ARM64 | Details |
| neoprophet-1.4.0-py3-none-macosx_10_11_x86_64.whl | Python 3 | none | macOS 10.11+ x86-64 | Details |
Total release size: 60.9 MB
Release files / neoprophet-1.4.0.tar.gz
| Download URL | neoprophet-1.4.0.tar.gz |
|---|---|
| Size | 129.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6414108ce16dcd7f3a0d1d11f0e4cca27fee9e932f7446a66c37ebd34fc52512
|
|
BLAKE2b-256 checksum How to use checksums |
a148df910218500190111f078cb30749180bd253c3b3469dd202b48880e358db
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency logRelease files / neoprophet-1.4.0-py3-none-win_amd64.whl
| Download URL | neoprophet-1.4.0-py3-none-win_amd64.whl |
|---|---|
| Size | 12.2 MB |
| Tags | Python 3 Windows x86-64 |
|
SHA-256 checksum How to use checksums |
973c3b63c8be154534c6d9132a9b8f37cec50e8c78e8cdcbc02de60c1718e3e5
|
|
BLAKE2b-256 checksum How to use checksums |
56cae6507a4c5da90000ae157520dbd6784d5e97ee5d2fdd58806dbcc20d6899
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency logRelease files / neoprophet-1.4.0-py3-none-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
| Download URL | neoprophet-1.4.0-py3-none-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl |
|---|---|
| Size | 11.9 MB |
| Tags | Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 Python 3 |
|
SHA-256 checksum How to use checksums |
3f83a7b6b429f689d6d1437b900d9833cce71ec97ce335b684f994797cdca845
|
|
BLAKE2b-256 checksum How to use checksums |
f5b1b3319e90e5a8075c4e458ce1106490e08510088ca6e045481732366bf2f2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency logRelease files / neoprophet-1.4.0-py3-none-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl
| Download URL | neoprophet-1.4.0-py3-none-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl |
|---|---|
| Size | 11.9 MB |
| Tags | Linux glibc 2.26+ ARM64 Linux glibc 2.28+ ARM64 Python 3 |
|
SHA-256 checksum How to use checksums |
821f6cd9c1732de24e9506ffb98e11094853ad92e1029a38cb671646226cdbba
|
|
BLAKE2b-256 checksum How to use checksums |
b3830c69791b76d10185c580bfc39844ccc050afbc8de903f3c4374832b28d96
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency logRelease files / neoprophet-1.4.0-py3-none-macosx_11_0_arm64.whl
| Download URL | neoprophet-1.4.0-py3-none-macosx_11_0_arm64.whl |
|---|---|
| Size | 12.1 MB |
| Tags | Python 3 macOS 11.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
47c065d41b902337d338ad3393d32fb4bfeb2f62db1e3f752c15e17db1312d37
|
|
BLAKE2b-256 checksum How to use checksums |
f5f08cf9ddab7bdfba6098eee85b4ee788a06f8850ef0c4eba83e280e834c265
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency logRelease files / neoprophet-1.4.0-py3-none-macosx_10_11_x86_64.whl
| Download URL | neoprophet-1.4.0-py3-none-macosx_10_11_x86_64.whl |
|---|---|
| Size | 12.6 MB |
| Tags | Python 3 macOS 10.11+ x86-64 |
|
SHA-256 checksum How to use checksums |
3a56c725ef95fdfd07cb7aa1327157a4b4a713028c3687d7a6078983b9df6a33
|
|
BLAKE2b-256 checksum How to use checksums |
b50a19d79500ce9b32b72b0edda1f2655f2ddab27c6856444990f7da2de3cd58
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 10, 2026.
Transparency log
