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@mnot
mnot / RSS.py
Created October 29, 2009 12:48
RSS.py: work with RSS channels as data structures
#!/usr/bin/env python
"""
RSS.py
Classes for working with RSS channels as arbitrary data structures.
Requires Python 2.2 or newer and PyXML 0.7.1 or newer.
ChannelBase - Base class for RSS Channels.
CollectionChannel - RSS Channel modeled as a URI-per-entry
@karmi
karmi / ElasticSearch.org.Website.Search.FieldNotes.markdown
Created April 8, 2011 17:15
Field notes gathered during installing and configuring ElasticSearch for http://elasticsearch.org

ElasticSearch.org Website Search: Field Notes

These are field notes gathered during installation of website search facility for the ElasticSearch website.

You may re-use it to put a similar system in place.

The following assumes:

@leegao
leegao / Rationale.md
Created July 9, 2011 02:30
JIT for dummies: JIT compiling RPN in python

If you don't care about the explanation, scroll down to find the code, it's 50 some odd lines and written by someone who doesn't know any better. You have been warned.

What it does

This is a very simple proof of concept jitting RPN calculator implemented in python. Basically, it takes the source code, tokenizes it via whitespace, and asks itself one simple question: am I looking at a number or not?

First, let's talk about the underlying program flow. Pretend that you are a shoe connoisseur with a tiny desk. You may only have two individual shoes on that desk at any one time, but should you ever purchase a new one or get harassed by an unruly shoe salesman without realizing that you have the power to say no (or even maybe?), you can always sweep aside one of the two shoes on the desk (the one on the right, because you're a lefty and you feel that the left side is always superior) onto the messy floor, put the other shoe on the right hand side, and then place your newly acquired shoe in

@kiranmeduri
kiranmeduri / about.md
Created August 14, 2011 19:13 — forked from jasonrudolph/about.md
Programming Achievements: How to Level Up as a Developer
@madrobby
madrobby / i18n.coffee
Created November 14, 2011 15:45
Backbone i18n with CoffeeScript
# before this file is loaded, a locale should be set:
#
# In a browser environment, you can use:
# ```<script>__locale='en';</script>```
#
# In a server environment (specifically node.js):
# ```global.__locale = 'en';```
# normalize in-app locale string to "en" or "de-AT"
parts = @__locale.split('-')
@carljm
carljm / runner.py
Created December 9, 2011 04:07
Unittest2 test discovery and real dotted-path named test selection for Django
"""
An alternative Django ``TEST_RUNNER`` which uses unittest2 test discovery from
a base path specified in settings, rather than requiring all tests to be in
``tests`` module of an app.
If you just run ``./manage.py test``, it'll discover and run all tests
underneath the ``TEST_DISCOVERY_ROOT`` setting (a path). If you run
``./manage.py test full.dotted.path.to.test_module``, it'll run the tests in
that module (you can also pass multiple modules).
@datagrok
datagrok / gist:2199506
Last active April 8, 2023 17:36
Virtualenv's `bin/activate` is Doing It Wrong
@kohlmeier
kohlmeier / ka_bnet_numpy.py
Created March 26, 2012 21:59
Bayes net example in Python with Khan Academy data
#!/usr/bin/env python
from numpy import asmatrix, asarray, ones, zeros, mean, sum, arange, prod, dot, loadtxt
from numpy.random import random, randint
import pickle
MISSING_VALUE = -1 # a constant I will use to denote missing integer values
def impute_hidden_node(E, I, theta, sample_hidden):
@kohlmeier
kohlmeier / ka_bnet_pandas.py
Created March 26, 2012 22:32
Bayes net example (Pandas version)
#!/usr/bin/env python
from pandas import DataFrame, Series
import numpy as np
import math
import random
import copy
NaN_Flag = -1 # pandas uses np.nan, but that coerces ints to floats :(
@hellerbarde
hellerbarde / latency.markdown
Created May 31, 2012 13:16 — forked from jboner/latency.txt
Latency numbers every programmer should know

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs