{"categories":[{"label":"Viewers","url":"https://skillfed.io/packages/category/multimedia-graphics-viewers"},{"label":"Display","url":"https://skillfed.io/packages/category/multimedia-video-display"}],"enrichment":{"capability":"Mediapy reads, writes, and displays images and videos directly in IPython and Jupyter notebooks, returning them as numpy arrays for further processing.","skillfed_tags":["jupyter-integration","media-io"],"use_cases":["Display images fetched from URLs or local files directly in a notebook cell with optional height and title parameters.","Read video files and play them back in a notebook with correct framerate, or extract individual frames as numpy arrays.","Process video frame-by-frame using VideoReader/VideoWriter to apply transformations and save the result.","Show multiple images side-by-side in a notebook grid for visual comparison of results.","Generate synthetic test images or videos programmatically and display them immediately for inspection."],"what_it_does":"Mediapy is a library that integrates image and video I/O directly into IPython and Jupyter notebook environments. It wraps common operations\u2014reading from URLs or files, displaying with optional sizing and titles, writing to disk\u2014and returns media as numpy arrays so you can manipulate them with standard scientific Python tools. The library handles metadata like video framerate automatically and provides both high-level convenience functions (show_image, read_video) and lower-level streaming interfaces (VideoReader, VideoWriter) for frame-by-frame processing.\n\nThe package depends on matplotlib, numpy, and Pillow for image handling, plus ipython for notebook integration. Video I/O requires ffmpeg to be installed on your system PATH. It targets modern Python versions and is designed specifically for notebook workflows, making it most useful when you're already working interactively in Jupyter rather than in scripts.","worth_installing":"Yes, if you work in Jupyter or IPython notebooks and need to display or manipulate images and videos. The low install friction, active maintenance, permissive license, and tight integration with the notebook environment make it a straightforward choice. The only gotcha is the ffmpeg system dependency for video I/O, which is documented and typically a one-time setup."},"id":"mediapy","links":{"html":"https://skillfed.io/packages/mediapy","md":"https://skillfed.io/packages/mediapy.md","pypi":"https://pypi.org/project/mediapy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-01","license_spdx":null,"license_treatment":"permissive","name":"mediapy","python_support":"supports_current","summary":"Read/write/show images and videos in an IPython notebook"},"popularity":{"monthly_downloads":1143601,"position":4302,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.2.7"}