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Merge pull request #81 from daisybio/fixing_vis
Fixing vis
2 parents c16fd66 + 43cec75 commit 7e4bba4

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-3028
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.github/workflows/run_tests.yml

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fail-fast: false
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matrix:
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include:
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- { python-version: "3.11", os: ubuntu-latest, session: "pre-commit" }
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- { python-version: "3.11", os: ubuntu-latest, session: "safety" }
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- { python-version: "3.11", os: ubuntu-latest, session: "mypy" }
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- { python-version: "3.11", os: ubuntu-latest, session: "tests" }
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- { python-version: "3.11", os: windows-latest, session: "tests" }
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- { python-version: "3.11", os: ubuntu-latest, session: "typeguard" }
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- { python-version: "3.11", os: ubuntu-latest, session: "xdoctest" }
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- { python-version: "3.11", os: ubuntu-latest, session: "docs-build" }
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- { python-version: "3.12", os: ubuntu-latest, session: "pre-commit" }
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- { python-version: "3.12", os: ubuntu-latest, session: "mypy" }
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- { python-version: "3.12", os: ubuntu-latest, session: "tests" }
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- { python-version: "3.12", os: windows-latest, session: "tests" }
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- { python-version: "3.12", os: ubuntu-latest, session: "typeguard" }
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- { python-version: "3.12", os: ubuntu-latest, session: "xdoctest" }
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- { python-version: "3.12", os: ubuntu-latest, session: "docs-build" }
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env:
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NOXSESSION: ${{ matrix.session }}

.github/workflows/safety_scan.yml

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name: Safety Action
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on:
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push: # Run on every push to any branch
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pull_request: # Run on new pull requests
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jobs:
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security:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@main
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- name: Run Safety CLI to check for vulnerabilities
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uses: pyupio/safety-action@v1
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with:
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api-key: ${{ secrets.SAFETY_API_KEY }}

README.rst

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:target: https://github.com/psf/black
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:alt: Black
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Origin story
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*Long ago, the people of science lived in harmony. Researchers collaborated, data flowed freely, and models were tested with integrity.
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But then, the H-Index Nation attacked.
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Suddenly, impact factors ruled all, flashy results overshadowed rigorous testing, and biased benchmarks spread like wildfire. Science, once a beacon of knowledge, became clouded by competition and questionable practices.
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Only a fair and unbiased framework could restore balance.
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And when the field needed it most—drevalpy was born.
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A framework designed to test drug response prediction models with fairness and transparency, cutting through bias and restoring the integrity of scientific evaluation.
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Though the fight against bad practices is long, with drevalpy, balance may yet be restored.*
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Focus on Innovating Your Models — DrEval Handles the Rest!
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- DrEval is a toolkit that ensures drug response prediction evaluations are statistically sound, biologically meaningful, and reproducible.
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- Focus on model innovation while using our automated standardized evaluation protocols and preprocessing workflows.

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