EnzymeML v2 data model

.github/workflows/gen.yml

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+name: MD-Models Pipeline
+
+on:
+  push:
+    paths:
+      - "specifications/*.md"
+  workflow_dispatch:
+
+jobs:
+  generate:
+    name: Generate Pipeline
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+
+      - name: Set up Rust
+        uses: actions-rs/toolchain@v1
+        with:
+          toolchain: stable
+          override: true
+
+      - name: Install MD-Models
+        run: cargo install --git https://github.com/JR-1991/md-models.git
+
+      - name: Run the generation pipeline
+        run: md-models pipeline -i gen.toml
+
+      - name: Format the generated code
+        uses: chartboost/ruff-action@v1
+        with:
+          args: "format"
+
+      - name: "Push generated code/schemes"
+        shell: "bash"
+        run: |
+          if [[ `git status --porcelain` ]]; then
+              git add --all
+              git config --global user.name 'MD-Models Bot'
+              git config --global user.email '[email protected]'
+              git commit -am "Model update"
+              git push
+          else
+            echo "Nothing changed!"
+          fi
+
+      - uses: actions/setup-python@v4
+        with:
+          python-version: 3.x
+      - uses: actions/cache@v2
+        with:
+          path: .cache
+          key: ${{ github.ref }}
+      - run: pip install mkdocs-material jupyter nbconvert mkdocs-jupyter
+      - run: mkdocs gh-deploy --force

docs/index.md

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+# EnzymeML
+
+## Why EnzymeML?
+
+EnzymeML is a data model for catalyzed reaction data.
+
+It sets information on small molecules, proteins, and their reaction in context with reaction conditions and the measured data.
+
+EnzymeML is a standardized data model allowing for exchange of data among colleagues, database providers, and data science tools.
+
+
+## How to use EnzymeML?
+
+Besides the data model, different tools are available to accelerate your processing and analysis of catalyzed reaction data.
+
+- EnzymeML Suite: A desktop application for creating, editing, simulating, and visualizing EnzymeML documents.
+- Chromatopy: A Python tool for processing chromatographic data.
+- MTPHandler: A Python tool for processing plate reader data.
+- NMRpy: A Python tool for processing NMR data.
+