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‎marimo-notebook/README.md‎

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# Marimo: A Reactive, Reproducible Notebook
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The materials contained in this download are designed to complement the Real Python tutorial [Marimo: A Reactive, Reproducible Notebook](https://realpython.com/marimo-notebook/).
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## Installation
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Create a [Python virtual environment](https://realpython.com/python-virtual-environments-a-primer/), activate it, and install marimo along with its dependencies into it:
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```sh
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$ python -m venv venv/
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$ source venv/bin/activate
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(venv) $ python -m pip install -r requirements.txt
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```
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## Contents
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Your download bundle contains the following files:
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| Filename | Description |
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|--------------------------------------------|-------------------------------------------------------------------------------------------------|
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| `hypotenuse_calculator.py` | The original `hypotenuse_calculator` code. |
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| `hypotenuse_calculator_before_update.py` | The code before any updating is attempted. The code is out of order but runs cleanly. |
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| `hypotenuse_calculator_duplicate_variable.py` | Shows the effect of redefining a variable. This file produces an error. |
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| `hypotenuse_calculator_after_update.py` | The code after the `adjacent` variable was updated to `10`. Runs cleanly. |
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| `hypotenuse_calculator_after_deletion.py` | The code after the `opposite` variable was deleted. This file produces an error. |
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| `break_even_analysis_chart_code.py` | The basic chart code for a break-even analysis with fixed input data. |
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| `break_even_analysis_ui_elements.py` | Includes four UI interface elements to allow the plot to be adjusted. |
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| `break_even_analysis_solution.py` | A possible solution to the skills test. |
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| `packages.py` | The code used to demonstrate sandboxing. |
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| `quadratic.py` | The marimo notebook version of the quadratic formula example. |
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| `equation.py` | The Python script version of `quadratic.py`. |
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| `simultaneous_equations.py` | The code used to demonstrate marimo's UI elements. |
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| `simultaneous_equations_ui.py` | A possible solution to the challenge skills test. |
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| `hidden_state.ipynb` | This Jupyter Notebook is a starting point for investigating its problems, to be adjusted per tutorial. |

‎marimo-notebook/break_even_analysis_chart_code.py‎

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# flake8: noqa
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import marimo
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__generated_with = "0.13.6"
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app = marimo.App(width="medium")
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@app.cell
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def _():
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import marimo as mo
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import matplotlib.pyplot as plt
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return (plt,)
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@app.cell
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def _():
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fixed_cost = 50000
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unit_cost = 2
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selling_price = 10
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upper_production_quantity = 10000
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return fixed_cost, selling_price, unit_cost, upper_production_quantity
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@app.cell
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def _(fixed_cost, plt, selling_price, unit_cost, upper_production_quantity):
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break_even_quantity = fixed_cost / (selling_price - unit_cost)
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break_even_income = fixed_cost + break_even_quantity * unit_cost
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units = range(0, upper_production_quantity + 1, 1000)
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unit_costs = [(x * unit_cost) + fixed_cost for x in units]
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sales_income = [unit * selling_price for unit in units]
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plt.plot(units, unit_costs, marker="o")
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plt.plot(units, sales_income, marker="x")
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plt.xlabel("Units Produced")
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plt.ylabel("($)")
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plt.legend(["Total Costs", "Total Income"])
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plt.title("Break-Even Analysis")
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plt.vlines(
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break_even_quantity,
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ymin=0,
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ymax=break_even_income,
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linestyles="dashed",
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)
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plt.text(
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x=break_even_quantity + 100,
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y=int(break_even_income / 2),
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s=int(break_even_quantity),
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)
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plt.grid()
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plt.show()
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return
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if __name__ == "__main__":
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app.run()

‎marimo-notebook/break_even_analysis_solution.py‎

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# flake8: noqa
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import marimo
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__generated_with = "0.13.6"
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app = marimo.App(width="medium")
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@app.cell
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def _():
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import marimo as mo
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import matplotlib.pyplot as plt
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return mo, plt
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@app.cell
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def _(ui_fixed_cost, ui_quantity, ui_selling_price, ui_unit_cost):
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fixed_cost = int(ui_fixed_cost.value)
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unit_cost = ui_unit_cost.value
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selling_price = float(ui_selling_price.value)
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upper_production_quantity = ui_quantity.value
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return fixed_cost, selling_price, unit_cost, upper_production_quantity
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@app.cell
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def _(
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fixed_cost,
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plt,
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selling_price,
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ui_break_even,
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ui_plot_color,
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unit_cost,
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upper_production_quantity,
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):
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break_even_quantity = fixed_cost / (selling_price - unit_cost)
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break_even_income = break_even_quantity * selling_price
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units = range(0, upper_production_quantity + 1, 1000)
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total_costs = [(unit * unit_cost) + fixed_cost for unit in units]
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sales_income = [unit * selling_price for unit in units]
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plt.plot(units, total_costs, marker="o", color=ui_plot_color.value)
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plt.plot(units, sales_income, marker="x")
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plt.xlabel("Units Produced")
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plt.ylabel("($)")
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plt.legend(["Total Costs", "Total Income"])
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plt.title("Break-Even Analysis")
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if ui_break_even.value:
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plt.vlines(
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break_even_quantity,
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ymin=100,
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ymax=break_even_income,
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linestyles="dashed",
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)
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plt.text(
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x=break_even_quantity + 100,
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y=int(break_even_income / 2),
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s=int(break_even_quantity),
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)
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plt.grid()
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plt.show()
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return
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@app.cell
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def _(mo):
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ui_fixed_cost = mo.ui.radio(options=["40000", "50000"], value="50000")
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ui_unit_cost = mo.ui.slider(start=2, stop=5, step=1)
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ui_selling_price = mo.ui.text(value="10")
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ui_quantity = mo.ui.dropdown(
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options={"10000": 10000, "12000": 12000, "15000": 15000}, value="10000"
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)
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ui_break_even = mo.ui.switch()
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ui_plot_color = mo.ui.dropdown(
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options={"Red": "red", "Green": "green", "Blue": "blue"}, value="Red"
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)
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mo.md(
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f"""
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Fixed Costs: {ui_fixed_cost}
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Unit Cost Price: {ui_unit_cost}
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Selling Price: {ui_selling_price}
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Maximum Quantity: {ui_quantity}
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Display Break-Even Data: {ui_break_even}
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Total Costs Plot Color: {ui_plot_color}
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"""
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)
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return (
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ui_break_even,
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ui_fixed_cost,
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ui_plot_color,
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ui_quantity,
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ui_selling_price,
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ui_unit_cost,
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)
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if __name__ == "__main__":
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app.run()

‎marimo-notebook/break_even_analysis_ui_elements.py‎

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# flake8: noqa
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import marimo
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__generated_with = "0.13.6"
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app = marimo.App(width="medium")
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@app.cell
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def _():
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import marimo as mo
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import matplotlib.pyplot as plt
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return mo, plt
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@app.cell
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def _(ui_fixed_cost, ui_quantity, ui_selling_price, ui_unit_cost):
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fixed_cost = int(ui_fixed_cost.value)
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unit_cost = ui_unit_cost.value
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selling_price = float(ui_selling_price.value)
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upper_production_quantity = ui_quantity.value
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return fixed_cost, selling_price, unit_cost, upper_production_quantity
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@app.cell
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def _(
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fixed_cost,
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plt,
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selling_price,
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ui_color_costs,
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unit_cost,
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upper_production_quantity,
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):
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break_even_quantity = fixed_cost / (selling_price - unit_cost)
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break_even_income = break_even_quantity * selling_price
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units = range(0, upper_production_quantity + 1, 1000)
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unit_costs = [(unit * unit_cost) + fixed_cost for unit in units]
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sales_income = [unit * selling_price for unit in units]
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plt.plot(units, unit_costs, marker="o", color=ui_color_costs.value)
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plt.plot(units, sales_income, marker="x")
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plt.xlabel("Units Produced")
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plt.ylabel("($)")
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plt.legend(["Total Costs", "Total Income"])
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plt.title("Break-Even Analysis")
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plt.vlines(
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break_even_quantity,
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ymin=0,
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ymax=break_even_income,
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linestyles="dashed",
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)
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plt.text(
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x=break_even_quantity + 100,
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y=int(break_even_income / 2),
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s=int(break_even_quantity),
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)
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plt.grid()
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plt.show()
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return
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@app.cell
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def _(mo):
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ui_fixed_cost = mo.ui.radio(options=["40000", "50000"], value="50000")
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ui_unit_cost = mo.ui.slider(start=2, stop=5, step=1)
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ui_selling_price = mo.ui.text(value="10")
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ui_quantity = mo.ui.dropdown(
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options={"10000": 10000, "12000": 12000, "15000": 15000},
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value="10000",
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)
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ui_disply_break_even = mo.ui.switch()
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ui_color_costs = mo.ui.dropdown(
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options={"Red": "red", "Green": "green", "Blue": "blue"}, value="Red"
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)
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mo.md(
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f"""
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Fixed Costs: {ui_fixed_cost}
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Unit Cost Price: {ui_unit_cost}
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Selling Price: {ui_selling_price}
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Maximum Quantity: {ui_quantity}
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Display Break-Even Data: {ui_disply_break_even}
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Total Costs Plot Color: {ui_color_costs}
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"""
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)
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return (
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ui_color_costs,
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ui_fixed_cost,
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ui_quantity,
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ui_selling_price,
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ui_unit_cost,
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)
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if __name__ == "__main__":
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app.run()

‎marimo-notebook/equation.py‎

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# flake8: noqa
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__generated_with = "0.13.6"
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# %%
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import marimo as mo
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# %%
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mo.md(
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r"""
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A quadratic equation is one of the form **$ax^2 + bx + c = 0$**, where a, b and c are constants, and a $\neq$ 0.
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You can solve it using the *quadratic formula*:
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$$x = \frac {-b \pm \sqrt{b^2 -4ac}} {2a}$$
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For example, suppose you wanted to solve: **$2x^2 - 3x - 2 = 0$**
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"""
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)
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# %%
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a = 2
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# %%
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import math
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# %%
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b = -3
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# %%
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c = -2
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# %%
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x1 = (-b + math.sqrt(b**2 - 4 * a * c)) / (2 * a)
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# %%
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x2 = (-b - math.sqrt(b**2 - 4 * a * c)) / (2 * a)
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# %%
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print(f"x = {x1} and {x2}.")

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