chiaki-py
PS4/PS5 Remote Play from Python, built on chiaki-ng: discover consoles, pair, stream video and audio, and send controller input.
Install
pip install chiaki-py
Python 3.11–3.14. Wheels for Windows, Ubuntu, macOS 15+ (Apple Silicon) and 64-bit Raspberry Pi OS; elsewhere, build from source.
On Linux, the Qt windows (StreamDisplay, PSNLoginQt) also need sudo apt install libxcb-cursor0.
On macOS, PySDL3's prebuilt SDL3_ttf links against Homebrew's libraries, so run brew install harfbuzz freetype. Without them, chiaki-py falls back to loading only the core SDL3 library, which is all controller input needs.
Quickstart
from chiaki_py import Session, discover_hosts, register_host, Serializer, AudioSink
from chiaki_py.psn import PSNLoginQt
host = discover_hosts(timeout=3.0)[0]
psn_account = PSNLoginQt.login()
registration = register_host(
host=host.host_addr,
psn_id=psn_account.user_rpid, # or .online_id for a PS4
pin="12345678", # shown on the console's Link Device screen
target=host.target,
)
Serializer.save(registration, "registration.json") # reload later with Serializer.load(HostRegistration, path)
with Session(registration) as session:
audio_sink = AudioSink(session) # plays audio on the default output device
for frame in session.frames(max_fps=60):
... # frame is an (H, W, 3) uint8 numpy array
Frame handlers
The third argument to Session picks what session.frames() yields:
| Handler | Yields | Notes |
|---|---|---|
CpuFrameHandler (default) |
(H, W, 3) uint8 numpy array | Works everywhere |
CudaFrameHandler |
(H, W, 3) uint8 CuPy array on the GPU | NVIDIA only; settings.set_hardware_decoder("cuda"). Pass out= to write into your own tensor (see CudaFrameHandler.empty_frame) |
VulkanFrameHandler |
VulkanFrame with raw GPU handles (NV12/P010) |
Any hardware decoder; release frames promptly |
from chiaki_py.lib import CudaFrameHandler
settings.set_hardware_decoder("cuda")
with Session(registration, CudaFrameHandler) as session:
for frame in session.frames():
...
Logging
chiaki-py logs through Python's logging under chiaki_py.*, including the native libraries (chiaki_py.lib, chiaki_py.lib.ffmpeg, chiaki_py.lib.placebo):
import logging
logging.basicConfig(level=logging.INFO)
logging.getLogger("chiaki_py.lib.ffmpeg").setLevel(logging.CRITICAL) # e.g. hide decoder errors
For noisy streams, filter at the source instead: settings.set_log_level(LogLevel.WARNING), and CHIAKI_PY_PLACEBO_LOG=warning for libplacebo.
Examples
Run from the repo root; the scripts share a ./cache directory for the PSN account and console registration.
| Script | What it does | Extra packages |
|---|---|---|
1.1_login.py |
PSN login, saved to cache/ |
|
1.2_discover_hosts.py |
List consoles on the network | |
1.3_register_console.py <host> <pin> [--ps4] |
Pair with a console | |
1.4.1_stream_cpu_qt.py |
Stream in a Qt window (CPU) | |
1.4.2_stream_cuda_qt.py |
Same, via CUDA + OpenGL (NVIDIA) | cupy-cuda12x cuda-python PyOpenGL |
1.4.3_stream_vulkan_qt.py |
Same, via Vulkan + libplacebo, zero-copy (Windows, Linux X11; XWayland on Wayland) | |
2_discover_and_stream_opencv.py |
Discover, log in, pair and stream in one script | opencv-python typer |
3_simple_stream.py |
Minimal OpenCV viewer; good starting point | opencv-python |
4_stream_cuda_glfw.py |
CUDA stream in a GLFW window (NVIDIA) | cupy-cuda12x glfw opencv-python typer |
5_stream_tensor_opengl.py |
Frames as PyTorch GPU tensors, e.g. for YOLO (NVIDIA) | CUDA PyTorch, glfw opencv-python typer |
All examples also need pip install miniaudio.
Building from source
CMake fetches chiaki-ng automatically (and on Windows, FFmpeg and libplacebo — the first build is slow). The CI workflows in .github/workflows/ are the reference recipes for each platform, including exact dependency versions.
git clone https://github.com/Rothen/chiaki-py && cd chiaki-py
pip install "protobuf==7.36.2" "grpcio-tools==1.84.0"
cmake --fresh -S . -B build -G Ninja -DCMAKE_BUILD_TYPE=Release -DCMAKE_POLICY_VERSION_MINIMUM=3.5 <platform flags>
cmake --build build --target chiaki-py
pip install -e .
- Windows: Visual Studio 2022+ C++ tools, LLVM, CMake, Ninja, Meson and vcpkg. Run from a VS dev shell with
-DCMAKE_TOOLCHAIN_FILE=$env:VCPKG_ROOT/scripts/buildsystems/vcpkg.cmake -DCMAKE_C_COMPILER=clang-cl -DCMAKE_CXX_COMPILER=clang-cl. - Ubuntu: native deps from apt; see build-ubuntu.yml for the package list.
VulkanRendererneedslibplacebo-dev(6.338+) andlibx11-dev, plus FFmpeg 6.1+ (Ubuntu 24.04); without them it is built as a stub that raises. - macOS: deps from Homebrew, plus SDL2 built from source (Homebrew's
sdl2is an SDL3 shim that can't be bundled); see build-macos.yml.
After C++ changes, re-run only the cmake --build step.
Python bindings
The pybind11 bindings in pybind/bindings/ and the type stubs in chiaki_py/lib/chiaki_py/ are generated from the C++ headers with litgen: a function is exposed to Python, and the comment above it (or at the end of its line) becomes its docstring. After changing a bound header, regenerate them and commit the result:
pip install litgen==0.22.0
python pybind/bindings/generate_bindings.py # or: cmake --build build --target chiaki-py-generate-bindings
generate_bindings.py lists which headers go into which pydef_*.cpp file and what each one excludes or adds by hand; pydef_chiaki.cpp and pydef_event_source.cpp (chiaki's C types and the event sources) are written by hand.
Known limitations
settings.set_audio_volume()has no effect yet.- Rumble/haptics and microphone aren't forwarded yet.
- PS4 pairing is far less tested than PS5.
License
AGPL-3.0-only (see LICENSE), since the extension statically links chiaki-ng's AGPL-3.0 chiaki-lib.
Metadata
Release files for chiaki-py 0.3.3
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Transparency logRelease files / chiaki_py-0.3.3-cp311-cp311-macosx_15_0_arm64.whl
| Download URL | chiaki_py-0.3.3-cp311-cp311-macosx_15_0_arm64.whl |
|---|---|
| Size | 20.5 MB |
| Tags | CPython 3.11 macOS 15.0+ ARM64 |
|
SHA-256 checksum How to use checksums |
fb64e3cac95eed39f58d23944640435ebe4c611f0f89b0dcd497d554815ffcb4
|
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BLAKE2b-256 checksum How to use checksums |
d290a69c2fb0f3c307e8329fcd8672dc2b390a6a6529c831c6c23aeb52bb7ae7
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
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Signed by GitHub Actions, verified by PyPI on Sep 28, 2026.
Transparency log