Skip to main content

hgraph-analytics

C++-first numerical analytics for hgraph. The package owns the numerical analytical family migrated from core—diff, count, clip, ewma, and pct_change—plus quantile, shaped-array array_std, shaped-array rolling_window, window_values, array_get_item, cumulative_sum, correlation, generic std/var, trailing rolling_mean, scheduled resample, and the EWMA parameter conversion helpers.

For installation, semantics, and Python/C++ usage patterns, see the analytics user guide. Runnable examples covering scalar pipelines, rolling windows, and shaped-array analytics are in python/examples.

import hgraph as hg
import hgraph_analytics as hga

change = hga.pct_change(
    value,
    period=12,
    divide_by_zero=hg.DivideByZero.NAN,
)

bounded = hga.clip(change, -0.25, 0.25)
smoothed = hga.ewma(bounded, alpha=0.2)
median = hga.quantile(observations, 0.5)
volatility = hga.array_std(observations, ddof=1)
recent = hga.rolling_window(value, period=20, min_window_period=5)
window = hga.window_values(hg.to_window(value, 20))
running = hga.cumulative_sum(observations, axis=0)
correlation = hga.correlation(observations, rowvar=False)
sample_volatility = hga.std(hg.to_window(change, 20, 20), ddof=1)
moving_average = hga.rolling_mean(value, period=20)

The result is fractional: 0.05 denotes five percent. period counts valid source observations and must be positive. The operator does not infer dataframe ordering, elapsed-time sampling, market sessions, or financial price adjustment.

Native consumers link hgraph::analytics, call hgraph::analytics::register_analytics_operators(), and wire the markers in hgraph::analytics, including diff, count, clip, ewma, pct_change, window_values, array_get_item, cumulative_sum, correlation, quantile, array_std, rolling_window, std_, var_, rolling_mean, and resample.

See the hgraph user-guide migration note for the complete Python and C++ name mapping from the former core API.

Metadata

Release files for hgraph-analytics 0.8.23

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for hgraph-analytics 0.8.23
File Size Uploaded Provenance
hgraph_analytics-0.8.23.tar.gz 41.6 kB With provenance Details

Built distributions (wheels)

Table of built distributions (wheels) for hgraph-analytics 0.8.23
File Interpreter ABI Platform
hgraph_analytics-0.8.23-cp312-abi3-win_amd64.whl CPython 3.12 abi3 Windows x86-64 Details
hgraph_analytics-0.8.23-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 abi3 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
hgraph_analytics-0.8.23-cp312-abi3-macosx_15_0_arm64.whl CPython 3.12 abi3 macOS 15.0+ ARM64 Details

Total release size: 10.2 MB

Release files / hgraph_analytics-0.8.23.tar.gz

Download URL hgraph_analytics-0.8.23.tar.gz
Size 41.6 kB
Tags Source
SHA-256 checksum
How to use checksums
0032565d2570ccdfdb01c33615ca01ac2f3fa715f8757b639d898abe405528ed
BLAKE2b-256 checksum
How to use checksums
a01f3a9f9f8e07faa61414bf94c5cb5bcc5b3426ddf0b25a492f90b076326fb1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

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 Sep 7, 2026.

Transparency log

Release files / hgraph_analytics-0.8.23-cp312-abi3-win_amd64.whl

Download URL hgraph_analytics-0.8.23-cp312-abi3-win_amd64.whl
Size 6.2 MB
Tags CPython 3.12 Windows x86-64 abi3
SHA-256 checksum
How to use checksums
d11976b5946e118654c323d1bee1cd9c0769837e57fc52d895b9261bc2aece46
BLAKE2b-256 checksum
How to use checksums
25081a6db01ed1d0ac406475701d1d61e3ca44f8bd87182cfd64bd9c3d7a6cf9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

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 Sep 7, 2026.

Transparency log

Release files / hgraph_analytics-0.8.23-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl

Download URL hgraph_analytics-0.8.23-cp312-abi3-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Size 2.2 MB
Tags CPython 3.12 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64 abi3
SHA-256 checksum
How to use checksums
378d91c1f3beeed5a28286322593fa78eb8d25a6476a230e247ad821c9133c8b
BLAKE2b-256 checksum
How to use checksums
1a1df7e18f276022ca7fbecd3e62adefd623651662a679ee652ea286f133883c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

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 Sep 7, 2026.

Transparency log

Release files / hgraph_analytics-0.8.23-cp312-abi3-macosx_15_0_arm64.whl

Download URL hgraph_analytics-0.8.23-cp312-abi3-macosx_15_0_arm64.whl
Size 1.7 MB
Tags CPython 3.12 abi3 macOS 15.0+ ARM64
SHA-256 checksum
How to use checksums
67bb792a1c770e9b73cf6577417fa77ed1e21307dc90ef1534c7763c550bed64
BLAKE2b-256 checksum
How to use checksums
b1c751a5028c43bfd168afe366e8bd89ab00d91af2e48bfac26539e868d2236f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

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 Sep 7, 2026.

Transparency log

Security for hgraph-analytics 0.8.23

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.

Full provenance

All 4 files in this release have been uploaded with provenance metadata.

Select from 4 files

Attestation for hgraph_analytics-0.8.23.tar.gz

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 Sep 7, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release

0.8.23 This release

4 release files Full provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page