Shipping the Accelerated Project
Package, verify, and report the speedup.
Shipping the Accelerated Project is a free Mojo Academy lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Mojo Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Time to Ship
The kernel is fast and correct. Now package it, prove the win, and hand off a project others can actually use. 🚀
Organize Into Modules
Split the code into clear files. One module for the kernel, one for I/O, keeps the project readable as it grows.
from kernel import sum_squares
from io_utils import load_dataDefine a Public API
Decide what users call and what stays internal. A small, clear API means people use your code without reading every line.
Build a Package
Bundle the modules into a single shareable file. A .mojopkg lets others import your accelerated code with one line.
mojo package myproj -o myproj.mojopkgKeep Python Where It Fits
The app can stay mostly Python and call your Mojo kernel through interop. You accelerate the hot path without rewriting everything.
Run the Final Benchmark
Time the shipped pipeline end to end. This final benchmark is what you compare to the original Python baseline.
Compute the Speedup
Divide the old time by the new time to get the speedup. A clean ratio tells the whole story in a single honest number.
speedup = baseline_time / mojo_timeVerify Once More
Run the full app on real input and check the output against the reference. Final correctness matters as much as the speed gain.
Report Honestly
State the input size, hardware, and method with the result. An honest report lets others trust and reproduce your numbers.
Document the Project
Write a short note on how to install, run, and benchmark it. Good docs turn a fast experiment into something people can adopt.
Reflect on the Journey
You profiled, ported the hot path, vectorized, parallelized, tuned, and shipped. That full workflow is how real Mojo acceleration happens.
Quick Check
Pick the right way to report your capstone result.
Recap
You packaged the kernel, ran a final benchmark, verified correctness, and reported an honest speedup. Your accelerated project is ready to ship. 🎯
Frequently asked questions
Is the “Shipping the Accelerated Project” lesson free?
Yes — the full text of “Shipping the Accelerated Project” is free to read here on the web, and the Mojo Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Mojo Academy course, upgrade to CoddyKit PRO.
What will I learn in “Shipping the Accelerated Project”?
Package, verify, and report the speedup. You practise Mojo Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start Mojo Academy?
No prior experience is required. Mojo Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Shipping the Accelerated Project” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this Mojo Academy lesson?
Yes. Every Mojo Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Profiling the Python Baseline
- Rewriting the Hot Path in Mojo
- Parallelizing and Tuning the Core
- Shipping the Accelerated Project