made repo leaner and made app.py more explicit, also increase max output bytes

.gitignore

@@ -0,0 +1 @@
+__pycache__/

.python-version

@@ -0,0 +1 @@
+3.12

Dockerfile

@@ -1,5 +1,5 @@
 FROM python:3.12
-COPY --from=ghcr.io/astral-sh/uv:0.4.20 /uv /bin/uv
+COPY --from=ghcr.io/astral-sh/uv:0.6.11 /uv /uvx /bin/
 
 RUN useradd -m -u 1000 user
 ENV PATH="/home/user/.local/bin:$PATH"
@@ -7,10 +7,10 @@ ENV UV_SYSTEM_PYTHON=1
 
 WORKDIR /app
 
-COPY --chown=user ./requirements.txt requirements.txt
-RUN uv pip install -r requirements.txt
-
 COPY --chown=user . /app
 USER user
 
-CMD ["marimo", "run", "app.py", "--include-code", "--host", "0.0.0.0", "--port", "7860"]
+ENV MARIMO_OUTPUT_MAX_BYTES=20_000_000
+
+CMD ["uvx", "marimo", "run", "--sandbox", "app.py", "--include-code", "--host", "0.0.0.0", "--port", "7860"]
+

app.py

@@ -1,469 +1,103 @@
+# /// script
+# requires-python = ">=3.12"
+# dependencies = [
+#     "ipython==9.0.2",
+#     "ipywidgets==8.1.5",
+#     "marimo",
+#     "numpy==2.1.3",
+#     "pandas==2.2.3",
+#     "scikit-learn==1.6.1",
+#     "setuptools==78.1.0",
+#     "ydata-profiling==4.16.1",
+# ]
+# ///
+
 import marimo
 
-__generated_with = "0.9.2"
-app = marimo.App()
+__generated_with = "0.12.0"
+app = marimo.App(width="medium")
 
 
 @app.cell
-def __():
+def _():
     import marimo as mo
-
-    mo.md("# Welcome to marimo! 🌊🍃")
-    return (mo,)
-
-
-@app.cell
-def __(mo):
-    slider = mo.ui.slider(1, 22)
-    return (slider,)
+    with mo.status.spinner("Importing libraries..."):
+        import numpy as np
+        import pandas as pd
+        from ydata_profiling import ProfileReport 
+        from sklearn import datasets
+    return ProfileReport, datasets, mo, np, pd
 
 
 @app.cell
-def __(mo, slider):
+def _(mo):
     mo.md(
-        f"""
-        marimo is a **reactive** Python notebook.
+        r"""
+        # On-the-fly YData Profiling 
 
-        This means that unlike traditional notebooks, marimo notebooks **run
-        automatically** when you modify them or
-        interact with UI elements, like this slider: {slider}.
-
-        {"##" + "🍃" * slider.value}
-        """
-    )
-    return
+        It is often desirable to have a quick EDA report when you receive a fresh CSV. [YData Profiling](https://docs.profiling.ydata.ai/latest/) is a useful tool to streamline that tool. This small [marimo](https://marimo.io) app enables you to drag-and-drop a CSV and generate an HTML report that you can visualise in your browser or download as an HTML report. 
 
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: disabling automatic execution": mo.md(
-                rf"""
-            marimo lets you disable automatic execution: just go into the
-            notebook settings and set
-
-            "Runtime > On Cell Change" to "lazy".
-
-            When the runtime is lazy, after running a cell, marimo marks its
-            descendants as stale instead of automatically running them. The
-            lazy runtime puts you in control over when cells are run, while
-            still giving guarantees about the notebook state.
-            """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
+        **Note: No data gets stored when you used this service**
         """
-        Tip: This is a tutorial notebook. You can create your own notebooks
-        by entering `marimo edit` at the command line.
-        """
-    ).callout()
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 1. Reactive execution
-
-        A marimo notebook is made up of small blocks of Python code called
-        cells.
-
-        marimo reads your cells and models the dependencies among them: whenever
-        a cell that defines a global variable  is run, marimo
-        **automatically runs** all cells that reference that variable.
-
-        Reactivity keeps your program state and outputs in sync with your code,
-        making for a dynamic programming environment that prevents bugs before they
-        happen.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(changed, mo):
-    (
-        mo.md(
-            f"""
-            **✨ Nice!** The value of `changed` is now {changed}.
-
-            When you updated the value of the variable `changed`, marimo
-            **reacted** by running this cell automatically, because this cell
-            references the global variable `changed`.
-
-            Reactivity ensures that your notebook state is always
-            consistent, which is crucial for doing good science; it's also what
-            enables marimo notebooks to double as tools and  apps.
-            """
-        )
-        if changed
-        else mo.md(
-            """
-            **🌊 See it in action.** In the next cell, change the value of the
-            variable  `changed` to `True`, then click the run button.
-            """
-        )
     )
     return
 
 
 @app.cell
-def __():
-    changed = False
-    return (changed,)
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: execution order": (
-                """
-                The order of cells on the page has no bearing on
-                the order in which cells are executed: marimo knows that a cell
-                reading a variable must run after the cell that  defines it. This
-                frees you to organize your code in the way that makes the most
-                sense for you.
-                """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        **Global names must be unique.** To enable reactivity, marimo imposes a
-        constraint on how names appear in cells: no two cells may define the same
-        variable.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: encapsulation": (
-                """
-                By encapsulating logic in functions, classes, or Python modules,
-                you can minimize the number of global variables in your notebook.
-                """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.accordion(
-        {
-            "Tip: private variables": (
-                """
-                Variables prefixed with an underscore are "private" to a cell, so
-                they can be defined by multiple cells.
-                """
-            )
-        }
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 2. UI elements
-
-        Cells can output interactive UI elements. Interacting with a UI
-        element **automatically triggers notebook execution**: when
-        you interact with a UI element, its value is sent back to Python, and
-        every cell that references that element is re-run.
-
-        marimo provides a library of UI elements to choose from under
-        `marimo.ui`.
-        """
-    )
-    return
+def _(mo, try_default_df):
+    uploaded_file = mo.ui.file(
+        filetypes=[".csv"], 
+        kind='area', 
+        label = "Drag and drop a CSV file here, or click to open file browser"
+    ) if not try_default_df.value else None
+    uploaded_file
+    return (uploaded_file,)
 
 
 @app.cell
-def __(mo):
-    mo.md("""**🌊 Some UI elements.** Try interacting with the below elements.""")
-    return
+def _(mo):
+    try_default_df = mo.ui.switch(label="Try default dataset (`diabetes` from scikit-learn)")
+    try_default_df
+    return (try_default_df,)
 
 
 @app.cell
-def __(mo):
-    icon = mo.ui.dropdown(["🍃", "🌊", "✨"], value="🍃")
-    return (icon,)
+def _(mo):
+    minimal = mo.ui.checkbox(True, label="Minimal profiling")
+    minimal
+    return (minimal,)
 
 
 @app.cell
-def __(icon, mo):
-    repetitions = mo.ui.slider(1, 16, label=f"number of {icon.value}: ")
-    return (repetitions,)
+def _(datasets, mo, pd, try_default_df, uploaded_file):
+    should_stop = not try_default_df.value and len(uploaded_file.value) == 0
+    mo.stop(should_stop , mo.callout("⬆️ Please choose a source dataframe above!"))
 
-
-@app.cell
-def __(icon, repetitions):
-    icon, repetitions
-    return
+    if try_default_df.value:
+        diabetes = datasets.load_diabetes()
+        df = pd.DataFrame(diabetes.data, columns=diabetes.feature_names)
+    else:
+        df = pd.read_csv(uploaded_file.value[0].contents)
+    return df, diabetes, should_stop
 
 
 @app.cell
-def __(icon, mo, repetitions):
-    mo.md("# " + icon.value * repetitions.value)
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 3. marimo is just Python
-
-        marimo cells parse Python (and only Python), and marimo notebooks are
-        stored as pure Python files — outputs are _not_ included. There's no
-        magical syntax.
-
-        The Python files generated by marimo are:
-
-        - easily versioned with git, yielding minimal diffs
-        - legible for both humans and machines
-        - formattable using your tool of choice,
-        - usable as Python  scripts, with UI  elements taking their default
-        values, and
-        - importable by other modules (more on that in the future).
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 4. Running notebooks as apps
-
-        marimo notebooks can double as apps. Click the app window icon in the
-        bottom-right to see this notebook in "app view."
-
-        Serve a notebook as an app with `marimo run` at the command-line.
-        Of course, you can use marimo just to level-up your
-        notebooking, without ever making apps.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 5. The `marimo` command-line tool
-
-        **Creating and editing notebooks.** Use
-
-        ```
-        marimo edit
-        ```
-
-        in a terminal to start the marimo notebook server. From here
-        you can create a new notebook or edit existing ones.
-
-
-        **Running as apps.** Use
-
-        ```
-        marimo run notebook.py
-        ```
-
-        to start a webserver that serves your notebook as an app in read-only mode,
-        with code cells hidden.
-
-        **Convert a Jupyter notebook.** Convert a Jupyter notebook to a marimo
-        notebook using `marimo convert`:
-
-        ```
-        marimo convert your_notebook.ipynb > your_app.py
-        ```
-
-        **Tutorials.** marimo comes packaged with tutorials:
-
-        - `dataflow`: more on marimo's automatic execution
-        - `ui`: how to use UI elements
-        - `markdown`: how to write markdown, with interpolated values and
-           LaTeX
-        - `plots`: how plotting works in marimo
-        - `sql`: how to use SQL
-        - `layout`: layout elements in marimo
-        - `fileformat`: how marimo's file format works
-        - `markdown-format`: for using `.md` files in marimo
-        - `for-jupyter-users`: if you are coming from Jupyter
-
-        Start a tutorial with `marimo tutorial`; for example,
-
-        ```
-        marimo tutorial dataflow
-        ```
-
-        In addition to tutorials, we have examples in our
-        [our GitHub repo](https://www.github.com/marimo-team/marimo/tree/main/examples).
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        ## 6. The marimo editor
-
-        Here are some tips to help you get started with the marimo editor.
-        """
+def _(mo, profile):
+    mo.download(
+        data=profile.html,
+        filename="ydata.html",
+        mimetype="text/html",
+        label = "Download YData Profile"
     )
     return
 
 
 @app.cell
-def __(mo, tips):
-    mo.accordion(tips)
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md("""## Finally, a fun fact""")
-    return
-
-
-@app.cell(hide_code=True)
-def __(mo):
-    mo.md(
-        """
-        The name "marimo" is a reference to a type of algae that, under
-        the right conditions, clumps together to form a small sphere
-        called a "marimo moss ball". Made of just strands of algae, these
-        beloved assemblages are greater than the sum of their parts.
-        """
-    )
-    return
-
-
-@app.cell(hide_code=True)
-def __():
-    tips = {
-        "Saving": (
-            """
-            **Saving**
-
-            - _Name_ your app using the box at the top of the screen, or
-              with `Ctrl/Cmd+s`. You can also create a named app at the
-              command line, e.g., `marimo edit app_name.py`.
-
-            - _Save_ by clicking the save icon on the bottom right, or by
-              inputting `Ctrl/Cmd+s`. By default marimo is configured
-              to autosave.
-            """
-        ),
-        "Running": (
-            """
-            1. _Run a cell_ by clicking the play ( ▷ ) button on the top
-            right of a cell, or by inputting `Ctrl/Cmd+Enter`.
-
-            2. _Run a stale cell_  by clicking the yellow run button on the
-            right of the cell, or by inputting `Ctrl/Cmd+Enter`. A cell is
-            stale when its code has been modified but not run.
-
-            3. _Run all stale cells_ by clicking the play ( ▷ ) button on
-            the bottom right of the screen, or input `Ctrl/Cmd+Shift+r`.
-            """
-        ),
-        "Console Output": (
-            """
-            Console output (e.g., `print()` statements) is shown below a
-            cell.
-            """
-        ),
-        "Creating, Moving, and Deleting Cells": (
-            """
-            1. _Create_ a new cell above or below a given one by clicking
-                the plus button to the left of the cell, which appears on
-                mouse hover.
-
-            2. _Move_ a cell up or down by dragging on the handle to the 
-                right of the cell, which appears on mouse hover.
-
-            3. _Delete_ a cell by clicking the trash bin icon. Bring it
-                back by clicking the undo button on the bottom right of the
-                screen, or with `Ctrl/Cmd+Shift+z`.
-            """
-        ),
-        "Disabling Automatic Execution": (
-            """
-            Via the notebook settings (gear icon) or footer panel, you
-            can disable automatic execution. This is helpful when
-            working with expensive notebooks or notebooks that have
-            side-effects like database transactions.
-            """
-        ),
-        "Disabling Cells": (
-            """
-            You can disable a cell via the cell context menu.
-            marimo will never run a disabled cell or any cells that depend on it.
-            This can help prevent accidental execution of expensive computations
-            when editing a notebook.
-            """
-        ),
-        "Code Folding": (
-            """
-            You can collapse or fold the code in a cell by clicking the arrow
-            icons in the line number column to the left, or by using keyboard
-            shortcuts.
-
-            Use the command palette (`Ctrl/Cmd+k`) or a keyboard shortcut to
-            quickly fold or unfold all cells.
-            """
-        ),
-        "Code Formatting": (
-            """
-            If you have [ruff](https://github.com/astral-sh/ruff) installed,
-            you can format a cell with the keyboard shortcut `Ctrl/Cmd+b`.
-            """
-        ),
-        "Command Palette": (
-            """
-            Use `Ctrl/Cmd+k` to open the command palette.
-            """
-        ),
-        "Keyboard Shortcuts": (
-            """
-            Open the notebook menu (top-right) or input `Ctrl/Cmd+Shift+h` to
-            view a list of all keyboard shortcuts.
-            """
-        ),
-        "Configuration": (
-            """
-           Configure the editor by clicking the gears icon near the top-right
-           of the screen.
-           """
-        ),
-    }
-    return (tips,)
+def _(ProfileReport, df, minimal, mo):
+    with mo.status.spinner("Generating YData Profile report..."):
+        profile = ProfileReport(df,minimal = minimal.value, title="YData Profiling Report")
+        profile.to_notebook_iframe()
+    return (profile,)
 
 
 if __name__ == "__main__":

makefile

@@ -0,0 +1,3 @@
+local-run:
+	docker build -t marimo-app .
+	docker run -it --rm -p 7860:7860 marimo-app

requirements.txt

@@ -1,5 +0,0 @@
-marimo
-# Or a specific version
-# marimo>=0.9.0
-
-# Add other dependencies as needed