Duplicate from posit/shiny-for-python-template

Co-authored-by: Gordon Shotwell <[email protected]>

.gitattributes

@@ -0,0 +1,34 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,4 @@
+
+.venv/
+__pycache__
+.DS_Store

.vscode/settings.json

@@ -0,0 +1,6 @@
+{
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter"
+    },
+    "python.formatting.provider": "none"
+}

Dockerfile

@@ -0,0 +1,13 @@
+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["shiny", "run", "app.py", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -0,0 +1,20 @@
+---
+title: Shiny for Python template
+emoji: 🌍
+colorFrom: yellow
+colorTo: indigo
+sdk: docker
+pinned: false
+license: mit
+---
+
+This is a templated Space for [Shiny for Python](https://shiny.rstudio.com/py/). 
+
+
+To get started with a new app do the following:
+
+1) Install Shiny with `pip install shiny`
+2) Create a new app with `shiny create .`
+3) Then run the app with `shiny run --reload`
+
+To learn more about this framework please see the [Documentation](https://shiny.rstudio.com/py/docs/overview.html).

app.py

@@ -0,0 +1,151 @@
+from pathlib import Path
+from typing import List, Dict, Tuple
+import matplotlib.colors as mpl_colors
+
+import pandas as pd
+import seaborn as sns
+import shinyswatch
+
+from shiny import App, Inputs, Outputs, Session, reactive, render, req, ui
+
+sns.set_theme()
+
+www_dir = Path(__file__).parent.resolve() / "www"
+
+df = pd.read_csv(Path(__file__).parent / "penguins.csv", na_values="NA")
+numeric_cols: List[str] = df.select_dtypes(include=["float64"]).columns.tolist()
+species: List[str] = df["Species"].unique().tolist()
+species.sort()
+
+app_ui = ui.page_fillable(
+    shinyswatch.theme.minty(),
+    ui.layout_sidebar(
+        ui.sidebar(
+            # Artwork by @allison_horst
+            ui.input_selectize(
+                "xvar",
+                "X variable",
+                numeric_cols,
+                selected="Bill Length (mm)",
+            ),
+            ui.input_selectize(
+                "yvar",
+                "Y variable",
+                numeric_cols,
+                selected="Bill Depth (mm)",
+            ),
+            ui.input_checkbox_group(
+                "species", "Filter by species", species, selected=species
+            ),
+            ui.hr(),
+            ui.input_switch("by_species", "Show species", value=True),
+            ui.input_switch("show_margins", "Show marginal plots", value=True),
+        ),
+        ui.output_ui("value_boxes"),
+        ui.output_plot("scatter", fill=True),
+        ui.help_text(
+            "Artwork by ",
+            ui.a("@allison_horst", href="https://twitter.com/allison_horst"),
+            class_="text-end",
+        ),
+    ),
+)
+
+
+def server(input: Inputs, output: Outputs, session: Session):
+    @reactive.Calc
+    def filtered_df() -> pd.DataFrame:
+        """Returns a Pandas data frame that includes only the desired rows"""
+
+        # This calculation "req"uires that at least one species is selected
+        req(len(input.species()) > 0)
+
+        # Filter the rows so we only include the desired species
+        return df[df["Species"].isin(input.species())]
+
+    @output
+    @render.plot
+    def scatter():
+        """Generates a plot for Shiny to display to the user"""
+
+        # The plotting function to use depends on whether margins are desired
+        plotfunc = sns.jointplot if input.show_margins() else sns.scatterplot
+
+        plotfunc(
+            data=filtered_df(),
+            x=input.xvar(),
+            y=input.yvar(),
+            palette=palette,
+            hue="Species" if input.by_species() else None,
+            hue_order=species,
+            legend=False,
+        )
+
+    @output
+    @render.ui
+    def value_boxes():
+        df = filtered_df()
+
+        def penguin_value_box(title: str, count: int, bgcol: str, showcase_img: str):
+            return ui.value_box(
+                title,
+                count,
+                {"class_": "pt-1 pb-0"},
+                showcase=ui.fill.as_fill_item(
+                    ui.tags.img(
+                        {"style": "object-fit:contain;"},
+                        src=showcase_img,
+                    )
+                ),
+                theme_color=None,
+                style=f"background-color: {bgcol};",
+            )
+
+        if not input.by_species():
+            return penguin_value_box(
+                "Penguins",
+                len(df.index),
+                bg_palette["default"],
+                # Artwork by @allison_horst
+                showcase_img="penguins.png",
+            )
+
+        value_boxes = [
+            penguin_value_box(
+                name,
+                len(df[df["Species"] == name]),
+                bg_palette[name],
+                # Artwork by @allison_horst
+                showcase_img=f"{name}.png",
+            )
+            for name in species
+            # Only include boxes for _selected_ species
+            if name in input.species()
+        ]
+
+        return ui.layout_column_wrap(*value_boxes, width = 1 / len(value_boxes))
+
+
+# "darkorange", "purple", "cyan4"
+colors = [[255, 140, 0], [160, 32, 240], [0, 139, 139]]
+colors = [(r / 255.0, g / 255.0, b / 255.0) for r, g, b in colors]
+
+palette: Dict[str, Tuple[float, float, float]] = {
+    "Adelie": colors[0],
+    "Chinstrap": colors[1],
+    "Gentoo": colors[2],
+    "default": sns.color_palette()[0],  # type: ignore
+}
+
+bg_palette = {}
+# Use `sns.set_style("whitegrid")` to help find approx alpha value
+for name, col in palette.items():
+    # Adjusted n_colors until `axe` accessibility did not complain about color contrast
+    bg_palette[name] = mpl_colors.to_hex(sns.light_palette(col, n_colors=7)[1])  # type: ignore
+
+
+app = App(
+    app_ui,
+    server,
+    static_assets=str(www_dir),
+)

penguins.csv

@@ -0,0 +1,345 @@
+Species,Island,Bill Length (mm),Bill Depth (mm),Flipper Length (mm),Body Mass (g),Sex,Year
+Adelie,Torgersen,39.1,18.7,181,3750,male,2007
+Adelie,Torgersen,39.5,17.4,186,3800,female,2007
+Adelie,Torgersen,40.3,18,195,3250,female,2007
+Adelie,Torgersen,NA,NA,NA,NA,NA,2007
+Adelie,Torgersen,36.7,19.3,193,3450,female,2007
+Adelie,Torgersen,39.3,20.6,190,3650,male,2007
+Adelie,Torgersen,38.9,17.8,181,3625,female,2007
+Adelie,Torgersen,39.2,19.6,195,4675,male,2007
+Adelie,Torgersen,34.1,18.1,193,3475,NA,2007
+Adelie,Torgersen,42,20.2,190,4250,NA,2007
+Adelie,Torgersen,37.8,17.1,186,3300,NA,2007
+Adelie,Torgersen,37.8,17.3,180,3700,NA,2007
+Adelie,Torgersen,41.1,17.6,182,3200,female,2007
+Adelie,Torgersen,38.6,21.2,191,3800,male,2007
+Adelie,Torgersen,34.6,21.1,198,4400,male,2007
+Adelie,Torgersen,36.6,17.8,185,3700,female,2007
+Adelie,Torgersen,38.7,19,195,3450,female,2007
+Adelie,Torgersen,42.5,20.7,197,4500,male,2007
+Adelie,Torgersen,34.4,18.4,184,3325,female,2007
+Adelie,Torgersen,46,21.5,194,4200,male,2007
+Adelie,Biscoe,37.8,18.3,174,3400,female,2007
+Adelie,Biscoe,37.7,18.7,180,3600,male,2007
+Adelie,Biscoe,35.9,19.2,189,3800,female,2007
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+Adelie,Dream,39.5,16.7,178,3250,female,2007
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+Adelie,Dream,37.5,18.9,179,2975,NA,2007
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requirements.txt

@@ -0,0 +1,4 @@
+shiny==0.6.0
+shinyswatch==0.4.1
+seaborn==0.12.2
+matplotlib==3.7.1