Merge dev branch to main branch

.github/workflows/build.yml

@@ -0,0 +1,36 @@
+name: Build Python Package
+
+on:
+  workflow_call: # Allows this workflow to be called by others
+
+permissions:
+  contents: read
+
+jobs:
+  build_package:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install build tools
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install build twine
+
+      - name: Build sdist and wheel
+        run: python -m build
+
+      - name: Validate metadata
+        run: python -m twine check dist/*
+
+      - name: Save build artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: python-package-distributions
+          path: dist/
+          retention-days: 1

.github/workflows/test-ci.yml

@@ -0,0 +1,15 @@
+name: Test Python Package Build
+
+on:
+  push:
+    branches: [ main, dev ]
+  pull_request:
+    branches: [ main, dev ]
+  workflow_dispatch: # Manual test button
+
+permissions:
+  contents: read
+
+jobs:
+  run-build:
+    uses: ./.github/workflows/build.yml

README.md

@@ -1,48 +1,41 @@
-# Rawk: Metabolic reaction network local enrichment analysis
+# Rawk
 
-Rawk is a python package to identify and visualize locally enriched metabolic pathways in metabolic reaction networks.
+A python package for metabolic pathway local enrichment analysis via random
+walks on metabolic reaction network.
 
 ## Install
 
-**Note** that Rawk currently can only be installed from local source files.
+**Note** that Rawk currently can only be installed from the source files in
+this repository.
 
-Following is an example procedure for installing Rawk on a Linux computer using command line tools:
+Rawk will be available on PyPI soon.
 
-```bash
-# Download rawk-0.0.5.tar.gz
-
-tar -xvf rawk-0.0.5.tar.gz
-
-cd rawk-0.0.5
-
-pip install .
-```
-
-## Tutorials
-
-The tutorials of Rawk are the python scripts in the `docs/tutorials` folder contained in `rawk-0.0.5.tar.gz`. The `docs/tutorials` folder contains the following tutorials:
-
-- `construct_recon3d_met_net.py`: Construct a metabolic reaction network from a genome scale metabolic model.
-- `example_mouse_data_analysis.py`: Run Rawk standard analysis workflow on an example mouse dataset.
-- `example_human_data_analysis.py`: Run Rawk standard analysis workflow on an example human dataset.
-
-Following is an example procedure for running the tutorials on a Linux computer using command line tools:
+## Documentation
 
-```bash
-python construct_recon3d_met_net.py
+### Tutorials
 
-python example_mouse_data_analysis.py
+The tutorials of Rawk are in the `docs/tutorials` folder,
+which contains the following tutorials:
 
-python example_human_data_analysis.py
-```
+- `construct_recon3d_mrn.md`: Construct a metabolic reaction network from a
+  genome scale metabolic model.
+- `example_mouse_data_analysis.md`: Run Rawk standard analysis workflow on an
+  example mouse dataset.
+- `example_human_data_analysis.md`: Run Rawk standard analysis workflow on an
+  example human dataset.
 
-## Documentation
+### API reference
 
-Rawk package documentation can be accessed using `help` in python interpreter. For example, `help(rawk.Rawk)` shows the documentation of the `Rawk` class.
+The API reference files of Rawk are in
+`docs/api_reference`. The API reference files were
+generated from the package docstrings. The docstrings can also be accessed
+using `help` in python interpreter. For example, `help(rawk.Rawk)` shows the
+documentation of the `Rawk` class.
 
 ## Troubleshooting
 
-If you encounter any error related to `tkinter` multi-threading, try rerunning with `workers=1` or removing `tkinter` from the environment.
+If you encounter any error related to `tkinter` multi-threading, try rerunning
+with parameters set to use only one CPU core.
 
 ## Notice about license