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{ "category": "PyCon US 2012", "language": "English", "slug": "high-performance-python-ii", "speakers": [ "Travis Oliphant" ], "tags": [], "id": 620, "state": 1, "title": "High Performance Python II", "summary": "In this tutorial, I will cover how to write very fast Python code for data\nanalysis. I will briefly introduce NumPy and illustrate how fast code for\nPython is written in SciPy using tools like Fwrap / F2py and Cython. I will\nalso describe interesting new approaches to creating fast code that is leading\nchanges to NumPy on a fundamental level.\n\n", "description": "", "quality_notes": "", "copyright_text": "", "embed": "<object width=\"425\" height=\"344\"><param name=\"movie\" value=\";f=videos&amp;app=youtube_gdata\"><param name=\"allowFullScreen\" value=\"true\"><param name=\"allowscriptaccess\" value=\"always\"><embed src=\";f=videos&amp;app=youtube_gdata\" allowscriptaccess=\"always\" height=\"344\" width=\"425\" allowfullscreen=\"true\" type=\"application/x-shockwave-flash\"></embed></object>", "thumbnail_url": "", "duration": null, "video_ogv_length": null, "video_ogv_url": null, "video_ogv_download_only": false, "video_mp4_length": null, "video_mp4_url": null, "video_mp4_download_only": false, "video_webm_length": null, "video_webm_url": null, "video_webm_download_only": false, "video_flv_length": null, "video_flv_url": null, "video_flv_download_only": false, "source_url": "", "whiteboard": "", "recorded": "2012-03-08", "added": "2012-03-12T20:00:06", "updated": "2014-04-08T20:28:27.626" }