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{ "category": "EuroPython 2011", "language": "English", "slug": "data-plumbing-with-python", "speakers": [ "Pavlos Christoforou" ], "tags": [ "community", "deployment", "framework", "processing" ], "id": 1073, "state": 1, "title": "Data Plumbing with Python", "summary": "[EuroPython 2011] Pavlos Christoforou - 21 June 2011 in \"Track Ravioli\"\n\n", "description": "Point Nine provides operations outsourcing and support to large and complex\nfinancial institutions.\n\nAs part of our day to day responsibilities we are required to process our\nclient's trading activity which generally involves receiving data in various\nformats and through various protocols, apply transformations, validations and\nenrichment processes and distribute the resulting data to various third\nparties, in short Data Plumbing.\n\nThe goal of this talk is to introduce the audience to the (vast) field of\nfinancial data processing which we believe presents a tremendous opportunity\nfor python and it's community and provide a brief overview of Point Nine's\ndeployment of Python as the main framework for all data plumbing activities.\n\n", "quality_notes": "", "copyright_text": "Standard YouTube License", "embed": "<object width=\"640\" height=\"390\"><param name=\"movie\" value=\";hl=en_US\"></param><param name=\"allowFullScreen\" value=\"true\"></param><param name=\"allowscriptaccess\" value=\"always\"></param><embed src=\";hl=en_US\" type=\"application/x-shockwave-flash\" width=\"640\" height=\"390\" allowscriptaccess=\"always\" allowfullscreen=\"true\"></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": "2011-07-18", "added": "2012-08-30T21:02:23", "updated": "2014-04-08T20:28:27.773" }