Skip to main content

One-line, perf-optimized install for the entire Golden Suite — goldenmatch, goldencheck, goldenflow, goldenpipe, GoldenSchema (infermap), goldenanalysis, native acceleration on by default

Project description

golden-suite

One-line, perf-optimized install and single front door for the whole Golden Suite.

pip install golden-suite      # whole suite + native acceleration, defaulted to the fast config
golden-suite doctor           # verify native is actually active

This is a thin meta-package. It pulls in every suite tool plus the native (Rust) acceleration kernels, on by default, and gives you (and your agents) one canonical entry point. It ships no data-processing logic of its own — just a doctor/optimize CLI and introspection helpers.

What you get

Tool Does Import
GoldenPipe Orchestrator — chains the tools as pluggable stages. Start here. import goldenpipe as gp
GoldenMatch Entity resolution: dedupe, match, golden records import goldenmatch as gm
GoldenCheck Data validation (rules discovered from your data) import goldencheck
GoldenFlow Transform / standardize / normalize import goldenflow
GoldenSchema Inference-driven schema mapping (import name: infermap) import infermap
GoldenAnalysis Read-only metrics + reporting import goldenanalysis

goldenpipe is the front door: it adapts every other tool as a stage, so most integrations only ever touch goldenpipe. goldenmatch is a leaf (entity resolution only), not the root.

Install options

Native acceleration is included by default (a hard dependency, not an extra).

You want Install
The whole suite + native pip install golden-suite
Suite + one MCP server pip install "golden-suite[mcp]"
Everything (suite + mcp + serving) pip install "golden-suite[all]"

Native wheels cover Linux x86_64/aarch64, macOS x86_64/arm64, Windows amd64. On an unsupported platform the install fails loudly rather than silently degrading — install the individual pure-Python packages directly there.

Quick start

import goldenpipe as gp

result = gp.run("customers.csv")   # validate -> transform -> match, one call
print(result.status, result.match, result.reasoning)

Verify + repair the perf setup:

golden-suite doctor      # every component + whether native is ACTIVE (non-zero exit if silently slow)
golden-suite optimize    # install any missing native kernels, then re-verify
from golden_suite import installed, native_status
print(installed())       # {"goldenpipe": "1.2.1", "goldenmatch": "1.30.0", ...}
print(native_status())   # per-package native_active / silently_slow / env_mode

For agents

See AGENTS.md and llms.txt — the canonical integration guide, including the anti-patterns that cause most of the "wrong setup" back-and-forth.

License

MIT. Part of the Golden Suite monorepo.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

golden_suite-0.1.0.tar.gz (11.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

golden_suite-0.1.0-py3-none-any.whl (7.5 kB view details)

Uploaded Python 3

File details

Details for the file golden_suite-0.1.0.tar.gz.

File metadata

  • Download URL: golden_suite-0.1.0.tar.gz
  • Upload date:
  • Size: 11.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for golden_suite-0.1.0.tar.gz
Algorithm Hash digest
SHA256 7e6dc2b28beb977e9045644d5548fa95ee3e73a01a130dbf87c5649a893372a7
MD5 4d36ca33a2efe112dbe1049d9020b10d
BLAKE2b-256 ad7cd9d79e3116c0632814c0569253873c802a26b72a71ac994a1f497faa8a65

See more details on using hashes here.

File details

Details for the file golden_suite-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: golden_suite-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 7.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.13

File hashes

Hashes for golden_suite-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 426f45baf71062015bed8369d6b82417b6f4cfb21e0d276f25c5f24187c4965d
MD5 a0d726bffb253a3d97adbd72a62e35c6
BLAKE2b-256 84cb121831e2c662b27ed3cc1514ea946d4f57bbed4b10c4dc2701654ff15c91

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page