On Mon, Nov 6, 2017 at 11:34 AM, Stéfane Fermigier <s...@fermigier.com> wrote:
> [...] > > Now I believe something could be done along the lines: > > a) record runtime type information from test or regular runs > b) massage these information and use them to annotate Python code with > additional type information (up to the developer to then accept or not the > proposed changes) > c) also run a test suite or an app under some magical machinery, and > either raise a TypeError or log warnings when discrepancies are detected > between type annotation and runtime behaviour. > > [...] (a) and (b) would use similar machinery, > I mean, (a) and (c) > and (a), (b) and (c) would be probably a useful way to introduce type > annotations to an existing code base without too much risk. > > (a) and (b) could also provide data for an interesting SE research project. > Similar to "Measuring Polymorphism in Python Programs", by Beatrice Akerblom and Tobias Wrigstad: https://people.dsv.su.se/~beatrice/python/dls15_large_images.pdf S. -- Stefane Fermigier - http://fermigier.com/ - http://twitter.com/sfermigier - http://linkedin.com/in/sfermigier Founder & CEO, Abilian - Enterprise Social Software - http://www.abilian.com/ Chairman, Free&OSS Group / Systematic Cluster - http://www.gt-logiciel-libre.org/ Co-Chairman, National Council for Free & Open Source Software (CNLL) - http://cnll.fr/ Founder & Organiser, PyData Paris - http://pydata.fr/ --- “You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete.” — R. Buckminster Fuller
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