env-stableretro-turbo 1.0.1.post48

🚀 Blazing-fast Stable Retro fork with native vectorization and preprocessing 🚀

env-StableRetro-turbo is a Python library for reinforcement-learning developers who need faster batched rollouts from classic console games. It keeps Stable Retro's game integrations and single-environment API, and adds RetroVecEnv, a Gymnasium vector environment that steps many libretro emulators and preprocesses observations in native code.

Install the package, import your legally obtained ROMs, and use the upstream-compatible env_stableretro_turbo import. The native path is useful for parallel training workloads that would otherwise spend substantial time crossing between Python wrappers and individual emulator instances.

Install

Release wheels require Python 3.14 and support macOS on Apple Silicon and Linux on x86-64.

uv venv --python 3.14
source .venv/bin/activate
uv pip install env-stableretro-turbo
python -m env_stableretro_turbo.import /path/to/your/roms

ROMs are not included. The importer matches supported ROMs to Stable Retro's game integrations.

Check the games available on your machine, then open one in the interactive player:

env-stableretro-turbo play --list
env-stableretro-turbo play nes
env-stableretro-turbo play SuperMarioBros-Nes-v0 --press START
env-stableretro-turbo play Breakout-Atari2600-v0 --mode 32 --difficulty A

Pass a full game ID such as SuperMarioBros-Nes-v0, or use all to open one imported game per platform. Add --show-obs to display the raw game beside its PPO-style preprocessed observation.

--press BUTTON[:COUNT] applies repeatable startup inputs using the selected game's own button names. Atari games additionally accept --mode N, which pulses the console SELECT switch N times before RESET, and --difficulty A or --difficulty B, which sets both console difficulty switches. For example, Breakout mode values 0, 4, 8, …, 44 select its twelve one-player cartridge variants. Use --state none to launch a game from its power-on state.

Use

import gymnasium as gym
import numpy as np

env = gym.make_vec(
    "env_stableretro_turbo:EnvStableRetroTurbo-v0",
    game="SuperMarioBros-Nes-v0",
    state="Level1-1",
    num_envs=32,
    num_threads=16,
    render_mode="rgb_array",
    obs_crop=(32, 0, 0, 0),
    obs_crop_mode="mask",
    obs_resize=(84, 84),
    obs_resize_algorithm="area",
    obs_grayscale=True,
    obs_layout="chw",
    frame_skip=4,
    frame_stack=4,
    maxpool_last_two=True,
    info_filter="terminal",
)

obs, infos = env.reset(seed=123)
obs, rewards, terminations, truncations, infos = env.step(
    env.action_space.sample()
)

done = terminations | truncations
if done.any():
    obs, reset_infos = env.reset(options={"reset_mask": done})

The module-qualified ID imports the package and registers the factory. This ID is vector-only and requires an explicit game; RetroVecEnv remains available for direct use. Stable Retro's existing scalar env_stableretro_turbo.make() and RetroEnv APIs are unchanged and are not registered under the Turbo ID.

RetroVecEnv uses Gymnasium's disabled-autoreset semantics. A finished lane keeps its terminal observation and cannot be stepped again until it is selected by a masked reset; unselected lanes keep their emulator state, RNG stream, frame stack, and sticky-action history.

Turbo Vector API v2

RetroVecEnv implements the strict Turbo Vector API v2:

• metadata["turbo_api_version"] is 2, metadata["transition_transport"] is "numpy", and metadata["render_modes"] advertises rgb_array.
• Immutable capabilities and signal_schema declarations describe supported features and the dtype, shape, and reset/step availability of every signal.
• buttons, action_mode, action_preset, action_table, action_meanings, and action_table_hash expose the resolved action semantics without provider-specific probing.
• state_catalog is an immutable ordered tuple. Callers select reset states with an int32 state_indices array and inspect the read-only active indices with active_state_indices(); state sampling and lane routing remain caller-owned.
• observation_ownership and observation_buffer_depth declare the exact lifetime of returned observations. Rendering is opt-in: with render_mode="rgb_array", render_lane(index) renders one lane, get_images() renders all lanes, and render() renders lane zero. With the default render_mode=None, the first two methods return None and get_images() returns one None entry per lane.

When env.supports_live_snapshots is true, live positions can be captured without advancing emulation and restored into any lane of the same environment:

capture_mask = np.zeros(env.num_envs, dtype=np.bool_)
capture_mask[0] = True
captured = env.capture_snapshots(capture_mask)

restore_mask = np.zeros(env.num_envs, dtype=np.bool_)
restore_mask[3] = True
starts = [None] * env.num_envs
starts[3] = captured[0]
obs, infos = env.reset(
    options={"reset_mask": restore_mask, "snapshots": starts},
)
env.close()

Handles are reusable, session-local, and intentionally not pickleable. A single masked reset can mix snapshot starts with ordinary state_indices; infos["start_source"] is int8: 0 means an environment state and 1 means a snapshot. Scripted scenarios and cores that cannot serialize exact state report the capability as unavailable.

The fast path also supports:

• native crop, mask, resize, grayscale, layout conversion, frame skip, frame stack, and two-frame max-pooling;
• ordered reset-state catalogs (including power-on as index zero when no saved state exists) with explicit per-lane state_indices; state sampling and curriculum routing stay with the caller;
• copy-safe, safe-view, and benchmark-only unsafe-view observation ownership;
• sticky actions, random no-op starts, reward clipping, and native info filtering;
• Atari through the packaged Stella core, using the same RetroEnv and RetroVecEnv APIs.

The inherited RetroEnv API remains available for single-environment use. RetroVecEnv supports one player, image observations, and no movie recording.

Develop

git clone https://github.com/tsilva/env-StableRetro-turbo.git
cd env-StableRetro-turbo
uv sync --frozen

Source builds require Python 3.14, CMake, a C/C++ compiler, and the platform dependencies needed by the selected emulator cores.

Commands

Run these commands from the repository root:

uv run --frozen env-stableretro-turbo play --list                                      # list imported games by platform
uv run --frozen --with pytest pytest tests/test_python/test_cli.py                   # run quick tests
uv run --frozen --with build python -m build                                        # build source and wheel artifacts

Core and semantic changes additionally use pinned TurboBench parity profiles against original Stable Retro for Super Mario Bros. and Breakout. The compared fields, reproducible commands, and release receipt gate are documented in docs/parity.md.

Benchmark

In an official correctness-gated TurboBench 1.0.0 comparison on the matched supermario/canonical-v1 workload, env-stableretro-turbo==1.0.1.post37 measured 2.1248x to 2.2465x the throughput of original stable-retro==1.0.1 at 1, 16, and 32 environments. This is a workload-specific result, not a claim across all games or emulator cores. See BENCHMARKS.md for exact SPS, paired confidence intervals, protocol, host details, provenance, and the reproduction command. Install the benchmark CLI with:

uv tool install \
  --exclude-newer-package turbobench-cli=2026-08-12T00:00:00Z \
  turbobench-cli==1.0.0

Notes

• The distribution is env-stableretro-turbo; the Python package is env_stableretro_turbo. The upstream-compatible retro import remains available for scalar integrations, while new code should import env_stableretro_turbo.
• RetroVecEnv implements Gymnasium's vector API directly. It is not a Stable-Baselines3 VecEnv, and Stable-Baselines3 is not a runtime dependency.
• A scalar reset seed expands to seed + lane_index. Seed sequences must contain one integer or None per lane.
• state_catalog preloads an ordered saved-state catalog. Select reset lanes with reset_mask and their exact catalog entries with state_indices; Turbo does not sample states.
• capture_snapshots(mask) returns lane-aligned live handles for exact same-instance continuation. The caller owns archive selection, eviction, and curriculum policy; handle.nbytes exposes approximate payload size.
• active_state_indices() returns a read-only NumPy view. Copy it when you need a stable snapshot.
• Stable Retro remains the source for inherited game, integration, and emulator documentation.
• Bundled emulator cores have their own licenses; see LICENSES.md.

Local credentials

Private local values declared in .keyenv.toml live in macOS Keychain. Run keyenv doctor to verify them and launch credential-dependent commands with keyenv run -- <command>. Python, Node, and their child processes receive the values through their normal environment APIs. Keep only public or non-secret configuration in dotenv files.

Architecture

License

MIT