build docs with mkdocs

.github/workflows/docs.yml

@@ -0,0 +1,46 @@
+name: Docs Build
+
+on:
+  push:
+    branches:
+      - mkdocs_no_exec
+
+jobs:
+  build_docs:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.10'
+
+      - name: Install dependencies
+        run: |
+          pip install --upgrade pip
+          pip install .
+          pip install -r docs/requirements_docs.txt
+
+      # - name: Convert notebooks to HTML
+      #   # if: ${{ github.event_name == 'push' && contains(github.event.head_commit.modified, 'Tutorial/') && contains(github.event.head_commit.modified, '.ipynb') }}
+      #   run: |
+      #     # jupyter nbconvert --to html --allow-errors --no-input --show-input --template classic --output-dir docs/tutorial Tutorial/*.ipynb
+      #     jupyter nbconvert --to html --allow-errors --template classic --output-dir docs/tutorial Tutorial/*.ipynb
+
+      # - name: Build Tutorial Table of Contents
+      #   run: |
+      #     bash docs/scripts/build_tutorial_toc.sh
+
+      - name: Build Documentation sources
+        run: |
+          bash docs/scripts/build_docs_sources.sh
+
+      - name: Build mkdocs.yml
+        run: |
+          bash docs/scripts/build_mkdocs.sh
+
+      - name: Build and Deploy Docs
+        run: |
+          mkdocs gh-deploy --force --clean --verbose

.github/workflows/publish_package.yml

@@ -29,38 +29,4 @@ jobs:
         TWINE_USERNAME: __token__
         TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
       run: twine upload dist/*
-  build-and-publish-conda:
-    needs: build-and-publish-pypi
-    runs-on: ubuntu-latest
-    steps:
-    - name: Checkout code
-      uses: actions/checkout@v2
-
-    - name: Setup Python
-      uses: actions/setup-python@v2
-      with:
-        python-version: '3.10'
-
-    - name: Install dependencies
-      run: |
-         conda install -c conda-forge grayskull conda-build anaconda-client -y
-
-    - name: Build conda recipe from PYPI
-      run: |
-        $CONDA/bin/grayskull pypi tpot2
-    
-    - name: Update meta.yaml
-      run: |
-        sed -i "/tpot2 --help/d" tpot2/meta.yaml
-        sed -i "/^  license:/ s/.*/  license: LGPLv3/" tpot2/meta.yaml
-        sed -i "/^  license_file:/ s/.*/  license_file: ..\/LICENSE/" tpot2/meta.yaml
-        
-    - name: Build package with conda-forge
-      run: |
-        $CONDA/bin/conda-build tpot2 -c conda-forge
-
-    - name: Upload to conda-forge
-      env:
-        CONDA_API_TOKEN: ${{ secrets.CONDA_API_TOKEN }}
-      run: |
-        $CONDA/bin/anaconda -t $CONDA_API_TOKEN upload -u conda-forge $CONDA/conda-bld/noarch/*.tar.bz2
+

.gitignore

@@ -9,4 +9,6 @@ cache_folder/
 dask-worker-space/
 .tox/
 *.egg-info/
-.coverage
+.coverage
+target/
+.venv/

docs/Tutorial

@@ -0,0 +1 @@
+../Tutorial

docs/cite.md

@@ -0,0 +1 @@
+# Citing TPOT2

docs/contribute.md

@@ -0,0 +1,3 @@
+# Contributing
+
+We welcome you to check the existing issues for bugs or enhancements to work on. If you have an idea for an extension to TPOT, please file a new issue so we can discuss it.

docs/css/extra.css

@@ -0,0 +1,3 @@
+.md-grid {
+    max-width: 100%;
+}

docs/index.md

@@ -0,0 +1,3 @@
+{%
+    include-markdown "../README.md"
+%}

docs/installation.md

@@ -0,0 +1,34 @@
+# Installation
+
+TPOT2 requires a working installation of Python.
+
+### Creating a conda environment (optional)
+
+We recommend using conda environments for installing TPOT2, though it would work equally well if manually installed without it.
+
+[More information on making anaconda environments found here.](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)
+
+```
+conda create --name tpot2env python=3.10
+conda activate tpot2env
+```
+
+### Note for M1 Mac or other Arm-based CPU users
+
+You need to install the lightgbm package directly from conda using the following command before installing TPOT2. 
+
+This is to ensure that you get the version that is compatible with your system.
+
+```
+conda install --yes -c conda-forge 'lightgbm>=3.3.3'
+```
+
+### Developer/Latest Branch Installation
+
+
+```
+pip install -e /path/to/tpot2repo
+```
+
+If you downloaded with git pull, then the repository folder will be named TPOT2. (Note: this folder is the one that includes setup.py inside of it and not the folder of the same name inside it).
+If you downloaded as a zip, the folder may be called tpot2-main. 

docs/related.md

@@ -0,0 +1,112 @@
+Other Automated Machine Learning (AutoML) tools and related projects:
+
+<table>
+<tr>
+<th width="20%">Name</th>
+<th width="15%">Language</th>
+<th width="15%">License</th>
+<th>Description</th>
+</tr>
+<tr>
+<td><a target="_blank" href="http://www.cs.ubc.ca/labs/beta/Projects/autoweka/">Auto-WEKA</a></td>
+<td>Java</td>
+<td>GPL-v3</td>
+<td>Automated model selection and hyper-parameter tuning for Weka models.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/automl/auto-sklearn">auto-sklearn</a></td>
+<td>Python</td>
+<td>BSD-3-Clause</td>
+<td>An automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/ClimbsRocks/auto_ml">auto_ml</a></td>
+<td>Python</td>
+<td>MIT</td>
+<td>Automated machine learning for analytics & production. Supports manual feature type declarations.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="http://docs.h2o.ai/h2o/latest-stable/h2o-docs/automl.html">H2O AutoML</a></td>
+<td>Java with Python, Scala & R APIs and web GUI</td>
+<td>Apache 2.0</td>
+<td>Automated: data prep, hyperparameter tuning, random grid search and stacked ensembles in a distributed ML platform.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/joeddav/devol">devol</a></td>
+<td>Python</td>
+<td>MIT</td>
+<td>Automated deep neural network design via genetic programming.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/AxeldeRomblay/MLBox">MLBox</a></td>
+<td>Python</td>
+<td>BSD-3-Clause</td>
+<td>Accurate hyper-parameter optimization in high-dimensional space with support for distributed computing.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/RecipeML/Recipe">Recipe</a></td>
+<td>C</td>
+<td>GPL-v3</td>
+<td>Machine-learning pipeline optimization through genetic programming. Uses grammars to define pipeline structure.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/reiinakano/xcessiv">Xcessiv</a></td>
+<td>Python</td>
+<td>Apache 2.0</td>
+<td>A web-based application for quick, scalable, and automated hyper-parameter tuning and stacked ensembling in Python.</td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/PGijsbers/gama">GAMA</a></td>
+<td>Python</td>
+<td>Apache 2.0</td>
+<td>Machine-learning pipeline optimization through asynchronous evaluation based genetic programming. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://pymoo.org">PyMoo</a></td>
+<td>Python</td>
+<td>Apache 2.0</td>
+<td>Multi-objective optimization in Python. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/kstaats/karoo_gp">Karoo GP</a></td>
+<td>Python</td>
+<td>MIT</td>
+<td>A Python based genetic programming application suite with support for symbolic regression and classification. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/Hintzelab/MABE/wiki">MABE</a></td>
+<td>C++</td>
+<td><a target="_blank" href="https://github.com/Hintzelab/MABE/wiki/license">See here</a></td>
+<td>A Python based genetic programming application suite with support for symbolic regression and classification. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/jpbonson/SBBFramework">SBBFramework</a></td>
+<td>Python</td>
+<td>BSD-2-Clause</td>
+<td>Python implementation of Symbiotic Bid-Based (SBB) framework for problem decomposition using Genetic Programming (GP). </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/moshesipper/tiny_gp">Tiny GP</a></td>
+<td>Python</td>
+<td>GPL-v3</td>
+<td>A minimalistic program implementing Koza-style (tree-based) genetic programming to solve a symbolic regression problem. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/alegonz/baikal">Baikal</a></td>
+<td>Python</td>
+<td>BSD-3-Clause</td>
+<td>A graph-based functional API for building complex scikit-learn pipelines. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/scikit-learn-contrib/skdag">skdag</a></td>
+<td>Python</td>
+<td>MIT</td>
+<td>A more flexible alternative to scikit-learn Pipelines. </td>
+</tr>
+<tr>
+<td><a target="_blank" href="https://github.com/d6t/d6tflow">d6tflow</a></td>
+<td>Python</td>
+<td>MIT</td>
+<td>A python library which makes building complex data science workflows easy, fast and intuitive. </td>
+</tr>
+</table>

docs/requirements_docs.txt

@@ -0,0 +1,7 @@
+mkdocs==1.4.2
+mkdocs-material==9.1.6
+mkdocs-include-markdown-plugin==4.0.4
+nbconvert==7.4.0
+mkdocs-jupyter==0.24.1
+mkdocstrings==0.21.2
+mkdocstrings-python==0.10.1

docs/scripts/build_docs_sources.sh

@@ -0,0 +1,25 @@
+#!/bin/bash
+
+function iterate_files() {
+    local directory="$1"
+    base_dir="docs/documentation"
+
+    for file in "$directory"/*; do
+        if [ -f "$file" ] && [[ "$file" == *.py ]] && [ "$(basename "$file")" != "__init__.py" ] && \
+            ! echo "$file" | grep -q "test" && [ "$(basename "$file")" != "graph_utils.py" ]; then
+            directories=$base_dir/$(dirname "$file")
+            file_name=$(basename "$file")
+            md_file=$directories/"${file_name%.*}".md
+
+            mkdir -p $directories && touch $md_file
+            include_line=$(dirname "$file")
+            include_line="${include_line//\//.}"."${file_name%.*}"
+            echo "::: $include_line" > $md_file
+
+        elif [ -d "$file" ]; then
+            iterate_files "$file"
+        fi
+    done
+}
+
+iterate_files "tpot2"