If you want to use your existing FFmpeg/Libav, the C-source version of PyAV is on PyPI too: pip install av -no-binary avĪnother way of installing PyAV is via conda-forge: conda install av -c conda-forge You can install these wheels by running: pip install av Since release 8.0.0 binary wheels are provided on PyPI for Linux, Mac and Windows linked against a modern FFmpeg. Installationĭue to the complexity of the dependencies, PyAV is not always the easiest Python package to install from source. If the ffmpeg command does the job without you bending over backwards, PyAV is likely going to be more of a hindrance than a help.īut where you can't work without it, PyAV is a critical tool. This power does come with some responsibility as working with media is horrendously complicated and PyAV can't abstract it away or make all the best decisions for you. It exposes a few transformations of that data, and helps you get your data to/from other packages (e.g. PyAV is for direct and precise access to your media via containers, streams, packets, codecs, and frames. We aim to provide all of the power and control of the underlying library, but manage the gritty details as much as possible. General questions are always welcome on the mailing list.PyAV is a Pythonic binding for the FFmpeg libraries. There's an O'Reilly book, Python and HDF5, written by the lead author of h5py, Andrew Collette. The h5py user manual is a great place to start you may also want to check out the FAQ. Request, please ping the mailing list at Google Groups. Stable DownloadsĪll downloads are now available at the Python Package Index (PyPI).Īll development for h5py takes place on GitHub. Almost anything you can do from C in HDF5, you can doīest of all, the files you create are in a widely-used standard binary format, which you can exchange with other people, including those who use programs like IDL and MATLAB. In addition to the easy-to-use high level interface, h5py rests on a object-orientedĬython wrapping of the HDF5 C API. You don't need to know anything special about HDF5 to get started. For example, you can iterate over datasets in a file, or check out the. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. Thousands of datasets can be stored in a single file, categorized and tagged however you want. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. The h5py package is a Pythonic interface to the HDF5 binary data format.
0 kommentar(er)
