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https://github.com/quant-aq/aeromancy

⚗️ Aeromancy: A framework for performing reproducible AI and ML

https://github.com/quant-aq/aeromancy

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (16.5%) to scientific vocabulary

Keywords

aeromancy data-science machine-learning reproducibility reproducible reproducible-experiments reproducible-research reproducible-science
Last synced: 6 months ago · JSON representation

Repository

⚗️ Aeromancy: A framework for performing reproducible AI and ML

Basic Info
Statistics
  • Stars: 11
  • Watchers: 3
  • Forks: 1
  • Open Issues: 23
  • Releases: 6
Topics
aeromancy data-science machine-learning reproducibility reproducible reproducible-experiments reproducible-research reproducible-science
Created about 2 years ago · Last pushed 9 months ago
Metadata Files
Readme Contributing License Code of conduct

README.md

Aeromancy

Docs Tests Code style: black pdm-managed Ruff pre-commit enabled Apache 2.0 licensed

Aeromancy is an opinionated philosophy and open-sourced framework that closely tracks experimental runtime environments for more reproducible machine learning. In existing experiment trackers, it’s easy to miss important details about how an experiment was run, e.g., which version of a dataset was used as input or the exact versions of library dependencies. Missing these details can make replicability more difficult. Aeromancy aims to make this process smoother by providing both new infrastructure (a more comprehensive versioning scheme including both system runtimes and external datasets) and a corresponding set of best practices to ensure experiments are maximally trackable.

In its current form, Aeromancy requires a fairly specific software stack: (hey, we said it was opinionated)

Aeromancy at SciPy 2024

Check out our abstract and poster:

SciPy 2024 poster

Documentation

  • If you're new to Aeromancy, start here!
  • In the Developer Reference section of the documentation, we include some design docs which provide an architectural overview and a glossary of terms.
  • To see autogenerated docs for code from this repo, you'll need to start a local doc server (pdm doc).
  • Want to get involved? We have starting points in our Contributor Guidelines.

Note: Aeromancy documentation is in a very early state. As this is a pre-release support may be limited.

Common development commands

  • pdm lint: Run pre-commit linters
  • pdm test: Run test suite
  • pdm doc: Start doc server (see also the public version for the latest release)

Owner

  • Name: QuantAQ
  • Login: quant-aq
  • Kind: organization
  • Email: hello@quant-aq.com
  • Location: Boston, MA

GitHub Events

Total
  • Issues event: 13
  • Watch event: 3
  • Issue comment event: 2
  • Create event: 1
Last Year
  • Issues event: 13
  • Watch event: 3
  • Issue comment event: 2
  • Create event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 9
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 1
  • Total pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 9
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 1
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • dmcc (18)
Pull Request Authors
  • dmcc (18)
  • drewp (1)
Top Labels
Issue Labels
enhancement (16) good first issue (4) documentation (2) bug (2)
Pull Request Labels
documentation (9) enhancement (5) bug (5)

Packages

  • Total packages: 1
  • Total downloads: unknown
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 6
proxy.golang.org: github.com/quant-aq/aeromancy
  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.7%
Last synced: 7 months ago

Dependencies

.github/workflows/ci.yml actions
  • actions/checkout v3 composite
  • pdm-project/setup-pdm main composite
.github/workflows/doc.yml actions
  • actions/checkout v2 composite
  • pdm-project/setup-pdm v2 composite
  • peaceiris/actions-gh-pages v3 composite
docker/Dockerfile docker
  • python 3.10.5-bullseye build
pyproject.toml pypi
  • boto3 >=1.28.45
  • doit >=0.36.0
  • giturlparse >=0.12.0
  • humanize >=4.8.0
  • hyperlink >=21.0.0
  • loguru >=0.7.2
  • msgspec >=0.18.2
  • pandas >=2.1.0
  • pyarrow >=13.0.0
  • pydot >=1.4.2
  • rich-click >=1.7.1
  • scipy >=1.9
  • skops >=0.8.0
  • term-image >=0.7.0
  • tomli >=2.0.1
  • wandb >=0.15.10