improvement: showcase loading external data (#1)

.github/workflows/deploy.yml

@@ -37,7 +37,7 @@ jobs:
       - name: 📤 Upload artifact
         uses: actions/upload-pages-artifact@v3
         with:
-          path: public
+          path: _site
 
   deploy:
     needs: build

.gitignore

@@ -1,3 +1,5 @@
+_site/
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

README.md

@@ -6,6 +6,7 @@ This template repository demonstrates how to export [marimo](https://marimo.io)
 
 - `apps/charts.py`: Interactive data visualization with Altair
 - `notebooks/fibonacci.py`: Interactive Fibonacci sequence calculator
+- `notebooks/penguins.py`: Interactive data analysis with Polars and marimo
 
 ## 🚀 Usage
 
@@ -16,3 +17,36 @@ This template repository demonstrates how to export [marimo](https://marimo.io)
 3. Push to main branch
 4. Go to repository **Settings > Pages** and change the "Source" dropdown to "GitHub Actions"
 5. GitHub Actions will automatically build and deploy to Pages
+
+## Including data or assets
+
+To include data or assets in your notebooks, add them to the `public/` directory.
+
+For example, the `apps/charts.py` notebook loads an image asset from the `public/` directory.
+
+```markdown
+<img src="public/logo.png" width="200" />
+```
+
+And the `notebooks/penguins.py` notebook loads a CSV dataset from the `public/` directory.
+
+```python
+import polars as pl
+df = pl.read_csv(mo.notebook_location() / "public" / "penguins.csv")
+```
+
+## 🧪 Testing
+
+To test the export process, run `scripts/build.py` from the root directory.
+
+```bash
+python scripts/build.py
+```
+
+This will export all notebooks in a folder called `_site/` in the root directory. Then to serve the site, run:
+
+```bash
+python -m http.server -d _site
+```
+
+This will serve the site at `http://localhost:8000`.

apps/charts.py

@@ -1,6 +1,6 @@
 import marimo
 
-__generated_with = "0.10.6"
+__generated_with = "0.10.9"
 app = marimo.App(width="medium")
 
 
@@ -19,6 +19,8 @@ def _(mo):
         """
         # Interactive Data Visualization
 
+        <img src="public/logo.png" width="200" />
+
         This notebook demonstrates a simple interactive visualization using Altair.
         Try selecting the points!
         """

notebooks/penguins.py

@@ -0,0 +1,99 @@
+import marimo
+
+__generated_with = "0.10.9"
+app = marimo.App(width="medium")
+
+
+@app.cell
+def _():
+    import polars as pl
+    import marimo as mo
+    import altair as alt
+    return alt, mo, pl
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(
+        """
+        # Palmer Penguins Analysis
+
+        Analyzing the Palmer Penguins dataset using Polars and marimo.
+        """
+    )
+    return
+
+
+@app.cell
+def _(mo, pl):
+    # Read the penguins dataset
+    df = pl.read_csv(mo.notebook_location() / "public" / "penguins.csv")
+    df.head()
+    return (df,)
+
+
+@app.cell
+def _(df, mo):
+    # Basic statistics
+    mo.md(f"""
+    ### Dataset Overview
+
+    - Total records: {df.height}
+    - Columns: {', '.join(df.columns)}
+
+    ### Summary Statistics
+
+    {mo.as_html(df.describe())}
+    """)
+    return
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""### Species Distribution""")
+    return
+
+
+@app.cell
+def _(alt, df, mo):
+    # Create species distribution chart
+    species_chart = mo.ui.altair_chart(
+        alt.Chart(df)
+        .mark_bar()
+        .encode(x="species", y="count()", color="species")
+        .properties(title="Distribution of Penguin Species"),
+        chart_selection=None,
+    )
+
+    species_chart
+    return (species_chart,)
+
+
+@app.cell(hide_code=True)
+def _(mo):
+    mo.md(r"""### Bill Dimensions Analysis""")
+    return
+
+
+@app.cell
+def _(alt, df, mo):
+    # Scatter plot of bill dimensions
+    scatter = mo.ui.altair_chart(
+        alt.Chart(df)
+        .mark_point()
+        .encode(
+            x="bill_length_mm",
+            y="bill_depth_mm",
+            color="species",
+            tooltip=["species", "bill_length_mm", "bill_depth_mm"],
+        )
+        .properties(title="Bill Length vs Depth by Species"),
+        chart_selection=None,
+    )
+
+    scatter
+    return (scatter,)
+
+
+if __name__ == "__main__":
+    app.run()

scripts/build.py

@@ -88,7 +88,7 @@ def generate_index(all_notebooks: List[str], output_dir: str) -> None:
 def main() -> None:
     parser = argparse.ArgumentParser(description="Build marimo notebooks")
     parser.add_argument(
-        "--output-dir", default="public", help="Output directory for built files"
+        "--output-dir", default="_site", help="Output directory for built files"
     )
     args = parser.parse_args()