workingjubilee

/*              INFO LIST CHUNKS (from the Multimedia Programmer's Reference
                                        plus new ones)
*/
#define RIFFINFO_IARL      mmioFOURCC ('I', 'A', 'R', 'L')     /*Archival location  */
#define RIFFINFO_IART      mmioFOURCC ('I', 'A', 'R', 'T')     /*Artist  */
#define RIFFINFO_ICMS      mmioFOURCC ('I', 'C', 'M', 'S')     /*Commissioned  */
#define RIFFINFO_ICMT      mmioFOURCC ('I', 'C', 'M', 'T')     /*Comments  */
#define RIFFINFO_ICOP      mmioFOURCC ('I', 'C', 'O', 'P')     /*Copyright  */
#define RIFFINFO_ICRD      mmioFOURCC ('I', 'C', 'R', 'D')     /*Creation date of subject  */
#define RIFFINFO_ICRP      mmioFOURCC ('I', 'C', 'R', 'P')     /*Cropped  */

workingjubilee

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

workingjubilee

Python2 is about to die...

But a lot of modern Python code still depends on it. This is a problem because as the years drag on, we will begin to forget the differences. The data for conversions can become lost. It is important to update now while we still remember. While it'd be nice to just tell everyone to update their modules, transitions are not always simple (I should know). So the only way to resolve Python2 dependencies is to send PRs to projects. Then maintainers will become free to shed their Python2 support, or at least Python3 code can be completely forked if legacy support becomes a concern, and Python3 code can depend on Python3 code either way, which can be kept up to date and maintained by new developers who have never read a line of Python2 before.

This list focuses on Python modules that continue to support or are directly enmeshed with the Python3 ecosystem in some way. Excellent examples are RPython and Twisted: RPython uses 2.7 Python, but is critical to PyPy, which supports 3.x Pythons