From f1d37c37452c57b3dbfaa382bdfb03f10fa6b623 Mon Sep 17 00:00:00 2001 From: stephanbreimann Date: Mon, 8 Apr 2024 19:05:16 +0200 Subject: [PATCH] Update badges (remove conda) --- .github/workflows/main.yml | 4 ++++ README.rst | 18 ++++++++---------- 2 files changed, 12 insertions(+), 10 deletions(-) diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index 613daedf..ae55bd0c 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -18,6 +18,7 @@ jobs: steps: - uses: actions/checkout@v4 + - name: Cache Python dependencies uses: actions/cache@v4 with: @@ -41,6 +42,7 @@ jobs: run: pytest tests env: HYPOTHESIS_DEADLINE: None + MPLBACKEND: Agg code-quality: runs-on: ubuntu-latest @@ -63,7 +65,9 @@ jobs: run: | python -m pip install --upgrade pip pip install flake8 mypy pylint + - name: Run flake8 (check style) run: flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics + - name: Run mypy (check static typing) run: mypy aaanalysis/__init__.py --follow-imports=skip diff --git a/README.rst b/README.rst index 4170f844..06a06b57 100644 --- a/README.rst +++ b/README.rst @@ -76,17 +76,17 @@ You can find the official documentation at `Read the Docs `_ or -`conda-forge `_: +**AAanalysis** can be installed from `PyPi `_: .. code-block:: bash pip install -u aaanalysis - or - conda install -c conda-forge aaanalysis -**Note**: Please use Python 3.9 and pip to avoid any dependency issues. Support for Python 3.10 to 3.12 is -planned for the next release. +For extended features, including our explainable AI module, please use the 'professional' version: + +.. code-block:: bash + + pip install -u aaanalysis[pro] Contributing ============ @@ -110,10 +110,8 @@ If you use AAanalysis in your work, please cite the respective publication as fo **CPP**: Breimann and Kamp *et al.* (2024c), - *Interpretable feature engineering by CPP reveals the physicochemical signature of γ-secretase substrates*, - .. # Link if available + *Charting γ-secretase substrates by explainable AI*, .. # Link if available **dPULearn**: Breimann and Kamp *et al.* (2024c), - *Interpretable feature engineering by CPP reveals the physicochemical signature of γ-secretase substrates*, - .. # Link if available + *Charting γ-secretase substrates by explainable AI*, .. # Link if available