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FrontEngine

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About

FrontEngine is a lightweight and flexible framework designed to simplify automation and visualization tasks.
It provides an intuitive interface and supports multiple media formats for interactive demonstrations.

FrontEngine UI


Features

  • GIFs & Animations
    (GIFs may take time to load)
    GIF
    WEBP

  • Video
    Video

  • Website
    Website

  • YouTube Showcase
    Watch on YouTube


Desktop pet

Spawn an animated sprite that lives on your desktop, from the Pet tab.

  • Sprites — pick a single GIF/WebP/PNG, or a pet pack folder whose file names map to states: walk, idle, sleep, climb, fall, drag (missing states fall back to walk).
  • Behaviour — walk on the floor with gravity (throw it and it bounces), wander freely, or chase the cursor. Floor pets can climb screen edges and stand on the top edge of other windows.
  • Life — mood, fullness and an affection level that persist between runs; the pet grows as it levels up, chats in speech bubbles, naps while you are away, and warns you about a low battery.
  • Interaction — drag it around, right-click to clone/feed/set a reminder, and drop a file onto it: an image or pet pack becomes its new look, anything else is eaten. What it eats matters — an archive is a feast, music cheers it up more than it fills, a document is a modest meal, and a binary is too hard to chew.
  • Tag — with two or more pets on screen, tick Play tag with each other and one becomes "it": it walks toward its nearest neighbour while the others run the other way, and catching someone passes the tag on.
  • React to audio — the pet pulses to your speakers' output level. It reads only the Windows output meter (WASAPI IAudioMeterInformation); no audio is captured or recorded. Peaks are smoothed with an RMS window and a fast-attack/slow-decay envelope so the pulse breathes instead of flickering. On multi-monitor setups each pet follows the audio endpoint that matches its own screen, falling back to the default output device.

Audio features are Windows-only and degrade to "no pulse" elsewhere.


Install

  • System Requirements

    • Python 3.10+
    • Windows 10/11 is the primary target; macOS and Linux are supported but may need extra OS dependencies.
  • From PyPI

    pip install frontengine
    
  • Pre-built binaries


Development

  • Requires Python 3.10+.
  • Install the dev toolchain:
    pip install -r dev_requirements.txt
    pip install -e .
    
  • Run the unit smoke tests:
    python ./tests/unit_test/start/start_front_engine.py
    python ./tests/unit_test/start/extend_front_engine.py
    
  • Contributions and pull requests are welcome!

Continuous Integration & Release

This repository ships two GitHub Actions workflows:

Workflow Trigger Purpose
CI (.github/workflows/ci.yml) Push / PR to main or dev, daily cron Matrix smoke test across Python 3.10 / 3.11 / 3.12 on Windows
Release (.github/workflows/release.yml) A pull request is merged into main (or manual dispatch) Auto-bumps the version in stable.toml/pyproject.toml, commits the bump back to main, swaps stable.tomlpyproject.toml, builds sdist + wheel, uploads to PyPI as frontengine via twine, creates a GitHub release tagged v<version>

Publishing only happens on merge to main — pushing to dev runs CI but never publishes. On merge, the workflow automatically bumps the patch segment of the version (configurable via manual dispatch: patch / minor / major), commits the bump back to main with [skip ci], then builds, uploads, and releases under the new version. Both the PyPI upload and the GitHub release see the bumped version, not the previous one.

Cutting a new release

  1. Merge a pull request into main — the patch version bumps automatically.
  2. That's it. PyPI publish and GitHub release happen in one workflow run.

For a minor or major bump, trigger the workflow manually via Actions → Release → Run workflow and pick the bump segment. That path also works when you need to re-run a failed publish without a new merge.

Required repository secrets

Secret Used by Contents
PYPI_API_TOKEN release.yml A PyPI API token scoped to the frontengine project

The workflow uses __token__ as the twine username, so only the token itself needs to be stored.

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