Skip to main content

Autonomous Research Assistant (AutoRA) is a framework for automating steps of the empirical research process.

Project description

Automated Research Assistant

PyPI GitHub Workflow Status PyPI - Downloads

AutoRA (Automated Research Assistant) is an open-source framework for automating multiple stages of the empirical research process, including model discovery, experimental design, data collection, and documentation for open science.

Autonomous Empirical Research Paradigm

Getting Started

Check out the documentation at https://autoresearch.github.io/autora.

About

This project is in active development by the Autonomous Empirical Research Group, led by Sebastian Musslick, in collaboration with the Center for Computation and Visualization at Brown University.

The development of this package is supported by Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM program at Brown University.

Read More

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

autora-3.0.0.tar.gz (609.0 kB view details)

Uploaded Source

Built Distribution

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

autora-3.0.0-py3-none-any.whl (3.7 kB view details)

Uploaded Python 3

File details

Details for the file autora-3.0.0.tar.gz.

File metadata

  • Download URL: autora-3.0.0.tar.gz
  • Upload date:
  • Size: 609.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for autora-3.0.0.tar.gz
Algorithm Hash digest
SHA256 f382df5bf007b94e37ec191de9b8a0a3e4b5a4cbf5f07bc4b49e3fbb13dcb035
MD5 ef13a30c49a1f4daaf64636cbd1edb99
BLAKE2b-256 43da2d9b1b35fd3bf2cdf21b526bab551a26e7e399790bce478f2429b9fc81b7

See more details on using hashes here.

File details

Details for the file autora-3.0.0-py3-none-any.whl.

File metadata

  • Download URL: autora-3.0.0-py3-none-any.whl
  • Upload date:
  • Size: 3.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for autora-3.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 16f6b0a494e3f9f750f88c608c8981a18d79bb3416bde1f0f48c6cdca9ac28cf
MD5 807ce2d2ab7d950b6631093c457fb550
BLAKE2b-256 56bf368777449e08525f4d818ea06c51ed11dcb87bcd99d5d369822cb372146c

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