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Version: Nightly

Mojo quickstart

This page quickly teaches you Mojo's syntax by focusing on code.

For more explanation of the language features, see the Mojo get started tutorial or Mojo language basics.

Project setup​

You can install Mojo using any Python or Conda package manager, but we recommend either pixi or uv.

  1. If needed, install uv:

    curl -LsSf https://astral.sh/uv/install.sh | sh

  2. Create a project and install Mojo:

    uv init temperature-analyzer && cd temperature-analyzer
    uv venv && source .venv/bin/activate
    uv pip install mojo --extra-index-url https://modular.gateway.scarf.sh/simple/

Try Mojo agent skills​

Use Mojo agent skills with your AI tools to generate more accurate Mojo code while learning Mojo:

npx skills add modular/skills

Hello Mojo​

Create analyzer.mojo in your favorite IDE or editor.

Add this to analyzer.mojo:

def main():
    print("Temperature Analyzer")

Run it:

mojo analyzer.mojo

Insights:

  • If you see "Temperature Analyzer", your setup works.
  • All Mojo executables use main() as their entry point.

Variables and data​

Update your file to add temperature data:

def main():
    print("Temperature Analyzer")

    # Square brackets tell Mojo the `List` type at compile time
    var temps: List[Float64] = [20.5, 22.3, 19.8, 25.1]

    print("Recorded", len(temps), "temperatures")

Loops​

Print each temperature. Add to main() under the print statement:

def main():
    # ... existing code ...

    for index in range(len(temps)):  # The range is [0, len(temps))
        print("  Day {}: {}°C".format(index + 1, temps[index]))

Insights:

  • The day is offset by 1 because the range uses zero-based indexing.

Functions​

Add this function above main() to calculate the average temperature:

def calculate_average(temps: List[Float64]) -> Float64:
    var total: Float64 = 0.0
    for index in range(len(temps)):
        total += temps[index]
    return total / Float64(len(temps))

def main():
    # ... existing code ...

Add to the end of main() to call the function:

    var avg = calculate_average(temps)
    print("Average: {}°C".format(avg))

Conditionals​

Classify the average temperature. Add to the end of main():

    if avg > 25.0:
        print("Status: Hot week")
    elif avg > 20.0:
        print("Status: Comfortable week")
    else:
        print("Status: Cool week")

Raise errors​

Handle empty data by updating calculate_average. Now the function can raise an error.

def calculate_average(temps: List[Float64]) raises -> Float64:
    if len(temps) == 0:  # Empty list of temperatures
        raise Error("No temperature data")

    var total: Float64 = 0.0
    for index in range(len(temps)):
        total += temps[index]
    return total / Float64(len(temps))

What changed:

  • You add raises before the return arrow.
  • You add the check for an empty list.
  • You raise an Error if it's empty.

Handle errors​

In main(), wrap your code in try-except for error handling:

    try:
        var avg = calculate_average(temps)
        print("Average: {}°C".format(avg))

        if avg > 25.0:
            print("Status: Hot week")
        elif avg > 20.0:
            print("Status: Comfortable week")
        else:
            print("Status: Cool week")
    except e:
        print("Error:", e)

To test the error, replace temps with List[Float64](). Confirm that your app errors with "No temperature data".

Python integration​

Add statistics with Python's numpy. First, install it:

uv pip install numpy

Then, add the following imports at the top of your file:

from std.python import Python, PythonObject

Now, calculate Python stats at the end of the try block in main():

        var np = Python.import_module("numpy")
        var pytemps: PythonObject = [20.5, 22.3, 19.8, 25.1]
        print("Temperature standard deviation:", np.std(pytemps))

Final code​

Your complete analyzer.mojo:

from std.python import Python, PythonObject

def calculate_average(temps: List[Float64]) raises -> Float64:
    if len(temps) == 0:
        raise Error("No temperature data")

    var total: Float64 = 0.0
    for index in range(len(temps)):
        total += temps[index]
    return total / Float64(len(temps))

def main():
    print("Temperature Analyzer")
    var temps: List[Float64] = [20.5, 22.3, 19.8, 25.1]
    print("Recorded", len(temps), "temperatures")

    for index in range(len(temps)):
        print("  Day {}: {}°C".format(index + 1, temps[index]))

    try:
        var avg = calculate_average(temps)
        print("Average: {}°C".format(avg))

        if avg > 25.0:
            print("Status: Hot week")
        elif avg > 20.0:
            print("Status: Comfortable week")
        else:
            print("Status: Cool week")

        var np = Python.import_module("numpy")
        var pytemps: PythonObject = [20.5, 22.3, 19.8, 25.1]
        print("Temperature standard deviation:", np.std(pytemps))
        _ = pytemps^ # Allow the Python object to deallocate
    except e:
        print("Error:", e)

What you touched​

Mojo variables, lists, loops, functions, conditionals, error handling, and Python integration, all in one working program.

Build something bigger: Tutorial: Game of Life Language guide: Mojo Manual API docs: Standard Library

Read about learning Mojo with AI Agent skills.

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