Pinboard: bookmarks for nico.ash tagged 'python'

movieos

The links to the personal projects of one of the author of flame. Including "Shelf":
Shelf is an app for MacOS that looks at the current foreground application, and tries to figure out if what you’re looking at corresponds to a person in your Address Book. Then it’ll tell you things about them.

python ruby cool flame java bonjour rendezvous osx ios flickr
january 2012 by nico.ash

copy to mine

Bill Katz

Simple Full Text Search for App Engine

Revised 2009-07-12 to include addition of stemming, multi-word exact matching, multiple search entities, and stowing of designated parent titles in index entity keys.

algorithms appengine article code cs datastore development django engine foss library googleappengine google gae fulltext search model programming text web python resource indexing google_app_engine searchablemodel
november 2010 by nico.ash

copy to mine

asynctools - Project Hosting on Google Code

asynctools is a library allowing you to execute Google App Engine API calls in parallel. API calls can be mixed together and queued up and then all are kicked off in parallel. Callbacks can be used to operate over completed calls immediately, if desired.

Currently, wrappers for Query and UrlFetch API calls are available. More will come over time.

api app appengine async asynchronous code database dev gae google library python performance parallel opensource running software tools asynctools datastore engine queries query
november 2010 by nico.ash

copy to mine

Damn Cool Algorithms: Levenshtein Automata - Nick's Blog

The basic insight behind Levenshtein automata is that it's possible to construct a Finite state automaton that recognizes exactly the set of strings within a given Levenshtein distance of a target word. We can then feed in any word, and the automaton will accept or reject it based on whether the Levenshtein distance to the target word is at most the distance specified when we constructed the automaton. Further, due to the nature of FSAs, it will do so in O(n) time with the length of the string being tested. Compare this to the standard Dynamic Programming Levenshtein algorithm, which takes O(mn) time, where m and n are the lengths of the two input words! It's thus immediately apparrent that Levenshtein automaton provide, at a minimum, a faster way for us to check many words against a single target word and maximum distance - not a bad improvement to start with!

algorithms algorithm search python levenshtein distance toread programming article fuzzy automata
july 2010 by nico.ash

copy to mine

python-on-a-chip - Project Hosting on Google Code

This project's goals are to develop the PyMite virtual machine, device drivers, high-level libraries and other tools to run a significant subset of the Python language on microcontrollers without an OS. Please join the python-on-a-chip google group to discuss this project

python embedded programming hardware avr mobile vm electronics microcontrollers
june 2010 by nico.ash

copy to mine