This package supports FFmpeg asynchronously invoke with async / await pattern wrapping ffmpeg.run_async() of ffmpeg-python and returned subprocess.Popen.

import asyncio from ffmpeg import Progress from ffmpeg.asyncio import FFmpeg async def main(): ffmpeg = ( FFmpeg() .option("y") .input("input.mov") .output( "output.mp4", codec="copy", ) ) @ffmpeg.on("progress") async def on_progress(progress: Progress): await asyncio.sleep(1) print(progress) @ffmpeg.on("completed") def on_completed(): print("Completed") await ffmpeg.execute() if __name__ == "__main__": asyncio.run(main())

process = ( ffmpeg .input('pipe:', format='rawvideo', pix_fmt='rgb24', s='{}x{}'.format(width, height)) .output(out_filename, pix_fmt='yuv420p') .overwrite_output() .run_async(pipe_stdin=True) ) process.communicate(input=input_data)

import asyncio from ffmpeg.asyncio import FFmpeg async def main(): ffmpeg = ( FFmpeg() .option("y") .input("input.mp4") .output( "output.mp4", {"codec:v": "libx264"}, vf="scale=1280:-1", preset="veryslow", crf=24, ) ) await ffmpeg.execute() ...

May 18, 2024 - import asyncio from ffmpeg_asyncio import FFmpeg, Progress async def main(): ffmpeg = ( FFmpeg() .input("input.mp4") .output("output.mp4") ) @ffmpeg.on("progress") def on_progress(progress: Progress): print(progress) @ffmpeg.on("completed") def completed(): print("Finished!") @ffmpeg.on("terminated") def exited(return_code: int): print("Oh no!") await ffmpeg.execute() if __name__ == "__main__": asyncio.run(main())

from ffmpeg import FFmpeg, Progress def main(): ffmpeg = ( FFmpeg() .option("y") .input( "rtsp://username:password@127.0.0.1/cam", rtsp_transport="tcp", rtsp_flags="prefer_tcp", ) .output("output.mp4", vcodec="copy") ) @ffmpeg.on("progress") def time_to_terminate(progress: Progress): if progress.frame > 200: ffmpeg.terminate() ffmpeg.execute() if __name__ == "__main__": main() import asyncio from ffmpeg import Progress from ffmpeg.asyncio import FFmpeg async def main(): ffmpeg = ( FFmpeg() .option("y") .input( "rtsp://username:password@127.0.0.1/cam", rtsp_transport="tcp", rtsp_flags="prefer_tcp", ) .output("output.mp4", vcodec="copy") ) @ffmpeg.on("progress") def time_to_terminate(progress: Progress): if progress.frame > 200: ffmpeg.terminate() await ffmpeg.execute() if __name__ == "__main__": asyncio.run(main())

import asyncio from ffmpeg import Progress from ffmpeg.asyncio import FFmpeg async def main(): ffmpeg = ( FFmpeg() .option("y") .input("input.mov") .output( "output.mp4", codec="copy", ) ) @ffmpeg.on("progress") async def on_progress(progress: Progress): await asyncio.sleep(1) print(progress) @ffmpeg.on("completed") def on_completed(): print("Completed") await ffmpeg.execute() if __name__ == "__main__": asyncio.run(main())

In this example, and most examples using process.terminate() and process.kill(), the process ends abruptly without letting ffmpeg do a clean exit. Attempting to add await to process throws an error since it cannot be awaited. ... process = await asyncio.create_subprocess_shell( command, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE )

from ffmpeg import FFmpeg, Progress def main(): ffmpeg = ( FFmpeg() .option("y") .input( "rtsp://username:password@127.0.0.1/cam", rtsp_transport="tcp", rtsp_flags="prefer_tcp", ) .output("output.mp4", vcodec="copy") ) @ffmpeg.on("progress") def time_to_terminate(progress: Progress): if progress.frame > 200: ffmpeg.terminate() ffmpeg.execute() if __name__ == "__main__": main() import asyncio from ffmpeg import Progress from ffmpeg.asyncio import FFmpeg async def main(): ffmpeg = ( FFmpeg() .option("y") .input( "rtsp://username:password@127.0.0.1/cam", rtsp_transport="tcp", rtsp_flags="prefer_tcp", ) .output("output.mp4", vcodec="copy") ) @ffmpeg.on("progress") def time_to_terminate(progress: Progress): if progress.frame > 200: ffmpeg.terminate() await ffmpeg.execute() if __name__ == "__main__": asyncio.run(main())

November 7, 2025 - Welcome to my special sauce fork of ffmpeg-python, with asyncio support.

December 18, 2024 - import httpx client = httpx.AsyncClient() async def write_input( client: httpx.AsyncClient, video_link: str, process: asyncio.subprocess.Process ) -> None: async with client.stream("GET", video_link) as response: async for chunk in ...

Source code in ffmpeg/ffmpeg.py · Bases: AsyncIOEventEmitter · Source code in ffmpeg/asyncio/ffmpeg.py · Initialize an FFmpeg instance using asyncio · Parameters: Source code in ffmpeg/asyncio/ffmpeg.py · Return a list of arguments to be used when executing FFmpeg.

May 4, 2019 - Now I'm working on Asynchronous application. And using asyncio library which is built in python3. And uses async/await syntax. Good to have possibility to return ffmpeg process as a coroutine and use it in a asyncio way. For example: pro...

We use src/ Python layout to demonstrate general good packaging practice, so to use the scripts: ... Hint the location of FFMPEG executable if necessary by setting the location in environment variable FFMPEG_ROOT. All examples are under the examples/ directory. For computationally bound programs, multiple processes is often a good choice. Try: ... Both synchronous (traditional for loop) and asynchronous pipeline are demonstrated.

import asyncio from ffmpeg_asyncio import FFmpeg, Progress async def main(): ffmpeg = ( FFmpeg() .input("input.mp4") .output("output.mp4") ) @ffmpeg.on("progress") def on_progress(progress: Progress): print(progress) @ffmpeg.on("completed") def completed(): print("Finished!") @ffmpeg.on("terminated") def exited(return_code: int): print("Oh no!") await ffmpeg.execute() if __name__ == "__main__": asyncio.run(main())

""" if isinstance(cmd, ... quiet=False, overwrite_output=False, cwd=None, ): """Asynchronously invoke ffmpeg for the supplied node graph....

packet_size = 4096 process = ( ffmpeg .input('rtsp://%s:8554/default') .output('-', format='h264') .run_async(pipe_stdout=True) ) while process.poll() is None: packet = process.stdout.read(packet_size) try: tcp_socket.send(packet) except socket.error: process.stdout.close() process.wait() break

>>> ff = ffmpy3.FFmpeg( ... inputs={'input.mp4': None}, ... outputs={'output.avi': None} ... ) >>> ff.run_async() >>> await ff.wait()

Then, make an HTTP request in your Python code to call the Bannerbear API and trigger the video generation process. You will get the URL of the resulting video in the response and here’s a screenshot of the video: ... You can refer to this tutorial and the API Reference to learn how to do it in detail. The ffmpeg-library enables you to use FFmpeg in Python to manipulate various media files for different purposes like building comprehensive multimedia applications, preprocessing media files for machine learning projects, etc.

from ffmpeg import FFmpeg, Progress def main(): ffmpeg = ( FFmpeg() .option("y") .input( "rtsp://username:password@127.0.0.1/cam", rtsp_transport="tcp", rtsp_flags="prefer_tcp", ) .output("output.mp4", vcodec="copy") ) @ffmpeg.on("progress") def time_to_terminate(progress: Progress): # If you have recorded more than 200 frames, stop recording if progress.frame > 200: ffmpeg.terminate() ffmpeg.execute() if __name__ == "__main__": main() import asyncio from ffmpeg import Progress from ffmpeg.asyncio import FFmpeg async def main(): ffmpeg = ( FFmpeg() .option("y") .input( "rtsp://username:passwor