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@onyxfish
onyxfish / example1.py
Created March 5, 2010 16:51
Basic example of using NLTK for name entity extraction.
import nltk
with open('sample.txt', 'r') as f:
sample = f.read()
sentences = nltk.sent_tokenize(sample)
tokenized_sentences = [nltk.word_tokenize(sentence) for sentence in sentences]
tagged_sentences = [nltk.pos_tag(sentence) for sentence in tokenized_sentences]
chunked_sentences = nltk.batch_ne_chunk(tagged_sentences, binary=True)
@didip
didip / tornado-nginx-example.conf
Created January 30, 2011 05:19
Nginx config example for Tornado
worker_processes 2;
error_log /var/log/nginx/error.log;
pid /var/run/nginx.pid;
events {
worker_connections 1024;
use epoll;
}
@alexbowe
alexbowe / nltk-intro.py
Created March 21, 2011 12:59
Demonstration of extracting key phrases with NLTK in Python
import nltk
text = """The Buddha, the Godhead, resides quite as comfortably in the circuits of a digital
computer or the gears of a cycle transmission as he does at the top of a mountain
or in the petals of a flower. To think otherwise is to demean the Buddha...which is
to demean oneself."""
# Used when tokenizing words
sentence_re = r'''(?x) # set flag to allow verbose regexps
([A-Z])(\.[A-Z])+\.? # abbreviations, e.g. U.S.A.
@whitequark
whitequark / gist:2622705
Created May 6, 2012 14:48
a piece of modern art
(3995:lookup-switch 3523 [3307, 3307, 3307, 3337, 3337, 3337, 3337, 3337, 3491, 3491, 3491, 3491, 3491, 3491, 3491, 3523]
(ternary
(3560:===
(3558:bit-or
(3555:lshift
(3551:integer 46)
(3553:integer 16))
(3556:integer 14))
(3559:get-local 3))
(3564:integer 0)
@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

@jeje
jeje / gist:3027236
Created July 1, 2012 06:58
Arduino Sketch recording raw IR signal and sending it through an infrared LED again every 2 seconds
#include <IRremote.h>
int RECV_PIN = 11;
IRrecv irrecv(RECV_PIN);
IRsend irsend;
boolean recording = true;
decode_results results;
@marcelom
marcelom / pysyslog.py
Created December 5, 2012 18:06
Tiny Python Syslog Server
#!/usr/bin/env python
## Tiny Syslog Server in Python.
##
## This is a tiny syslog server that is able to receive UDP based syslog
## entries on a specified port and save them to a file.
## That's it... it does nothing else...
## There are a few configuration parameters.
LOG_FILE = 'youlogfile.log'
@dergachev
dergachev / GIF-Screencast-OSX.md
Last active November 5, 2024 18:44
OS X Screencast to animated GIF

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Screencapture GIF

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application:

@abhinav-upadhyay
abhinav-upadhyay / DateTimeDecoder.py
Last active September 10, 2024 19:58
A JSON decoder/encoder implementation for parsing dates as datetime objects in Python
#!/usr/bin/env python
# An example of decoding/encoding datetime values in JSON data in Python.
# Code adapted from: http://broadcast.oreilly.com/2009/05/pymotw-json.html
# Copyright (c) 2023, Abhinav Upadhyay
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# coding=UTF-8
import nltk
from nltk.corpus import brown
# This is a fast and simple noun phrase extractor (based on NLTK)
# Feel free to use it, just keep a link back to this post
# http://thetokenizer.com/2013/05/09/efficient-way-to-extract-the-main-topics-of-a-sentence/
# Create by Shlomi Babluki
# May, 2013