Skip to content
CI

Adopt deepcell-auth for model/data downloads #54

Sign in to view logs

Adopt deepcell-auth for model/data downloads

Adopt deepcell-auth for model/data downloads #54

Workflow file for this run

.github/workflows/ci.yml at 5e0981b
name: CI
on:
push:
branches: [master]
pull_request:
branches: [master]
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
jobs:
inference-only:
# Guards the inference / [train] dep boundary. The whole point of the
# [train] extra is that ``pip install deepcell-types`` (no extras)
# pulls only the runtime deps needed to call ``predict()``. The
# ``tests/test_inference_deps.py`` subprocess probe asserts no
# training-only module ends up in sys.modules after the inference
# imports; if it ever does, this job goes red.
name: inference-only / py${{ matrix.python }}
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python: ["3.11", "3.12"]
steps:
- uses: actions/checkout@v4
with:
submodules: false
- uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python }}
cache: pip
- name: Install (inference-only) + dev tools
run: |
python -m pip install --upgrade pip
pip install -e .
pip install pytest ruff
- name: Pytest (inference-only — train-only tests skip via conftest)
run: pytest -q
full:
# Full suite with the [train] extra installed. Catches drift between
# training-side code and the tests that exercise it.
name: full / py${{ matrix.python }}
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
python: ["3.11", "3.12"]
steps:
- uses: actions/checkout@v4
with:
submodules: false
- uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python }}
cache: pip
- name: Install [train] + dev tools
run: |
python -m pip install --upgrade pip
pip install -e ".[train]"
pip install pytest ruff
- name: Pytest (full)
# Data-gated tests (TissueNet archive, gold-standard CSVs) skip
# cleanly when DATA_DIR is not set on a hosted runner.
run: pytest -q
lint:
name: ruff
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
submodules: false
- uses: actions/setup-python@v5
with:
python-version: "3.12"
cache: pip
- name: Install ruff
run: pip install ruff
- name: ruff check
run: ruff check deepcell_types scripts tests
wheel:
# Builds the wheel and installs it into a clean env, then imports the
# public API and touches package data (vocab.json, channel_mapping.yaml).
# An editable install (-e .) hides missing package-data globs; this job
# catches a wheel that ships without the YAML/JSON the runtime needs.
name: wheel build + install smoke
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
submodules: false
- uses: actions/setup-python@v5
with:
python-version: "3.12"
cache: pip
- name: Build wheel
run: |
python -m pip install --upgrade pip build
python -m build --wheel
- name: Install wheel into a clean venv and import
run: |
python -m venv /tmp/wheelenv
/tmp/wheelenv/bin/pip install --upgrade pip
/tmp/wheelenv/bin/pip install dist/*.whl
/tmp/wheelenv/bin/python -c "import deepcell_types; from deepcell_types import predict, make_preprocessor, DCTConfig; from deepcell_types.utils import download_model, list_model_versions; DCTConfig().marker2idx; print('wheel OK', deepcell_types.__version__)"
baselines-smoke:
# Installs the FULL [all] extra (train + every baseline, incl. the
# nimbus-inference==0.0.5 pin) and imports each baseline package. Pinned to
# Python 3.11 ONLY: nimbus-inference==0.0.5 requires Python <3.12, so the
# `python_version < '3.12'` markers in [baseline-nimbus] keep [all]
# resolvable on 3.12 (nimbus dropped there) but the runnable Nimbus stack is
# only exercised here on 3.11. Without this job the [baselines]/[all] Docker
# profiles ship untested.
name: baselines [all] import smoke / py3.11
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
submodules: false
- uses: actions/setup-python@v5
with:
python-version: "3.11"
cache: pip
- name: Install [all] (train + baselines, incl. nimbus on py3.11)
run: |
python -m pip install --upgrade pip
pip install -e ".[all]"
- name: Import baseline packages
run: |
python -c "import xgboost, optuna, nimbus_inference; import deepcell_types.baselines.xgb, deepcell_types.baselines.nimbus, deepcell_types.baselines.maps, deepcell_types.baselines.cellsighter; print('baselines import OK')"