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-0.0.6.dev20260215105543.tar.gz (77.0 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-0.0.6.dev20260215105543.tar.gz.

File metadata

File hashes

Hashes for pluto_ml_nightly-0.0.6.dev20260215105543.tar.gz
Algorithm Hash digest
SHA256 531c2566762b89f3db10f685d09664fe37ea0ec9ffc36d021c06e48df3564479
MD5 d31eb127c5ab83f1f8c668d637ad5fd8
BLAKE2b-256 0fc8bb65c90965404ef78cdb973abb7c8bca1414586f745a8bc1343dae0eac20

See more details on using hashes here.

File details

Details for the file pluto_ml_nightly-0.0.6.dev20260215105543-py3-none-any.whl.

File metadata

File hashes

Hashes for pluto_ml_nightly-0.0.6.dev20260215105543-py3-none-any.whl
Algorithm Hash digest
SHA256 427c43578e498230d3a286e3c22b1363672dfea15ad330edb29537fee7730a86
MD5 14b06f8f93db19e77a0fa51588b2dcbe
BLAKE2b-256 87c498c87875026caff2f6028ce418246cc29827b57785574db3233f3fcb81f5

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