gbdev / gbdev/GBEmulatorShootout
Add more emulators from the "awesome list"
- Dominant language
- Python
- Stars
- 37
- Forks
- 24
- PR merge metrics
- No merged PRs in 30d
Description
https://github.com/gbdev/awesome-gbdev#emulators is a shortlist of truly "awesome" emulators (high-quality, widely-used, stood the test of time), but also maintains a "complete list of open source emulators": https://github.com/gbdev/awesome-gbdev/blob/master/EMULATORS.md Some of those, despite being new or less well-known, could still be worth adding to the shootout.
One criterion I'd personally recommend is "under active development". The EMULATORS.md includes plenty of abandoned projects (just picking an arbitrary one, I hadn't heard of [scimitar](https://github.com/tompko/scimitar) before, and it was only developed for a few months in 2017). On the other hand, more active emulators could benefit from being listed in the shootout, by being motivated to continue and improve.
Two more as examples, which were recently listed:
- [hazelnut-gb-emu](https://github.com/atifcodesalot/hazelnut-gb-emu): "Cross platform, inaccurate and slow performance, but improving and awesome emulator done via pygame! Runs most commercial games." Sounds like the kind of imperfect but enthusiastic project where being in the shootout could help get better.
- [oxGBC](https://github.com/mxmgorin/oxgbc): "Cross-platform, accuracy-focused GB & GBC emulator (passes Blargg, Mooneye, SameSuite & acid2 tests) with save states, rewind, shaders, and a tile viewer". Sounds like a promising candidate for the same goals that vibeEmu (#47) wants to accomplish, and more high-accuracy entries might even help big ones like Emulicious and SameBoy get those last few points.
Contributor guide
Research direction
Start by reviewing the emulators in EMULATORS.md and the linked awesome list, then compare them with the shootout's existing emulator entries. Confirm which candidates are still actively developed and meet the project's testing goals. Done means the selected emulators are included in the shootout and their results can be compared with the existing entries.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- testing-qa
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 45/100