Skip to main content

Pluto ML - Machine Learning Operations Framework

Project description

pypi

Pluto is an experiment tracking platform. It provides self-hostable superior experimental tracking capabilities and lifecycle management for training ML models. To take an interactive look, try out our demo environment or get an account with us today!

See it in action

https://github.com/user-attachments/assets/6aff6448-00b6-41f2-adf4-4b7aa853ede6

🚀 Getting Started

Install the pluto-ml sdk

pip install -Uq "pluto-ml[full]"
import pluto

pluto.init(project="hello-world")
pluto.log({"e": 2.718})
pluto.finish()
  • Self-host your very own Pluto instance using the Pluto Server

You may also learn more about Pluto by checking out our documentation.

Migration

Neptune

Want to move your run data from Neptune to Pluto. Checkout the official docs from the Neptune transition hub here.

Before committing to Pluto, you want to see if there's parity between your Neptune and Pluto views? See our compatibility module documented here. Log to both Neptune and Pluto with a single import statement and no code changes.

🛠️ Development Setup

Want to contribute? Here's the quickest way to get the local toolchain (including the linters used in CI) running:

git clone https://github.com/Trainy-ai/pluto.git
cd pluto
python -m venv .venv && source .venv/bin/activate   # or use your preferred environment manager
python -m pip install --upgrade pip
pip install -e ".[full]"

Linting commands (mirrors .github/workflows/lint.yml):

bash format.sh

Run these locally before sending a PR to match the automation that checks on every push and pull request.

🫡 Vision

Pluto is a platform built for and by ML engineers, supported by our community! We were tired of the current state of the art in ML observability tools, and this tool was born to help mitigate the inefficiencies - specifically, we hope to better inform you about your model performance and training runs; and actually save you, instead of charging you, for your precious compute time!

🌟 Be sure to star our repos if they help you ~

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

pluto_ml_nightly-0.0.10.dev20260305110833.tar.gz (87.4 kB view details)

Uploaded Source

Built Distribution

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

File details

Details for the file pluto_ml_nightly-0.0.10.dev20260305110833.tar.gz.

File metadata

File hashes

Hashes for pluto_ml_nightly-0.0.10.dev20260305110833.tar.gz
Algorithm Hash digest
SHA256 16fba390ed44aa51736a2f400e57e071ab6c3a7d8ed140390b6f3109baa5be7a
MD5 3005580466121af1793b40e2116ff1ab
BLAKE2b-256 951b0cc465042b707b5b55c50d03169851107dccf8c8a746e0a813c540bfc9bb

See more details on using hashes here.

File details

Details for the file pluto_ml_nightly-0.0.10.dev20260305110833-py3-none-any.whl.

File metadata

File hashes

Hashes for pluto_ml_nightly-0.0.10.dev20260305110833-py3-none-any.whl
Algorithm Hash digest
SHA256 639b129f72459ccdd54ef76a3b005e232dc8e4d2267923bcd606bf9d4454dc16
MD5 2caaa3d16f75463cab1af83a0ead35da
BLAKE2b-256 4448a170d7f1436f6484c73bb1699a172fdb226f38851675cb42d18b6e1eabdb

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