ixtel’s gists

ixtel / gbs.py

Created October 19, 2015 12:59 — forked from bbengfort/gbs.py

Google Book Service

	from urllib import urlencode
	from datetime import date, datetime
	from httplib import HTTPSConnection, HTTPException

	try:
	from django.utils import simplejson as json
	except ImportError:
	import json

	def capitalize(word):

ixtel / aws.py

Created October 19, 2015 12:58 — forked from bbengfort/aws.py

Lookup books on Amazon's API.

	from django.conf import settings
	from datetime import datetime
	from urllib import urlencode
	from httplib import HTTPConnection
	from xml.dom.minidom import parse
	import hmac, hashlib, base64

	ACCESS_ID = getattr(settings, 'AWS')['ID']
	ACCESS_SECRET = getattr(settings, 'AWS')['SECRET']

ixtel / summarize.py

Created October 19, 2015 12:58 — forked from bbengfort/summarize.py

Uses TFIDF to extract relevant sentences from text. Based off of Charlie Greenbacker's example from "A smattering of NLP with Python" presentation he gave a while ago.

	# summarize
	# Uses TFIDF to extract relevent sentences from text.
	#
	# Author: Benjamin Bengfort <[email protected]>
	# Created: Sun Oct 26 16:06:36 2014 -0400
	#
	# ID: summarize.py [] [email protected] $

	"""
	Uses TFIDF to extract relevent sentences from text.

ixtel / tokens.py

Created October 19, 2015 12:58 — forked from bbengfort/tokens.py

Getting a normalized FreqDist

	import nltk
	import string

	def tokenize(text):
	stopwords = set(nltk.corpus.stopwords.words('english'))
	for token in nltk.word_tokenize(text):
	if token in stopwords or token in string.punctuation:
	continue
	yield token.lower()

ixtel / rss.json

Created October 19, 2015 12:58 — forked from bbengfort/rss.json

A summary of the fields for many RSS feeds downloaded using Python feedparser

	{
	"fields": {
	"dc_source": 7,
	"media_credit": 71,
	"updated_parsed": 277,
	"links": 2130,
	"twitter": 20,
	"media_text": 31,
	"summary_detail": 1993,
	"href": 386,

ixtel / nba.py

Created October 19, 2015 12:58 — forked from bbengfort/nba.py

Computing Statistics of NBA salaries.

	# nba
	# Analyzes the NBA Salary to PER data set
	#
	# Author: Benjamin Bengfort <[email protected]>
	# Created: Sat Sep 20 09:35:11 2014 -0400
	#
	# Copyright (C) 2014 Bengfort.com
	# For license information, see LICENSE.txt
	#
	# ID: nba.py [] [email protected] $

ixtel / big_tweet_import.py

Created October 19, 2015 12:58 — forked from bbengfort/big_tweet_import.py

Import and wrangling of the Big Tweet Dump from @murphsp1.

	#!/usr/bin/env python
	# big_tweet_import
	# Imports the tweet-dump into MongoDB
	#
	# Author: Benjamin Bengfort <[email protected]>
	# Created: Thu Aug 28 07:37:41 2014 -0400
	#
	# Copyright (C) 2014 Bengfort.com
	# For license information, see LICENSE.txt
	#

ixtel / avg.py

Created October 19, 2015 12:58 — forked from bbengfort/avg.py

Keeping a running average with Python, see: http://invisibleblocks.com/2008/07/30/long-running-averages-without-the-sum-of-preceding-values/ for more information.

	#!/usr/bin/env python

	from __future__ import division

	import sys
	import time
	import random


	class Averager(object):

ixtel / mgen.py

Created October 19, 2015 12:58 — forked from bbengfort/mgen.py

Get a random matrix with elements between 0 and 9.

	#!/usr/bin/env python

	##########################################################################
	## Imports
	##########################################################################

	import sys
	import argparse
	import traceback
	import numpy as np

ixtel / report.py

Created October 19, 2015 12:58 — forked from bbengfort/report.py

Plotting ingestion from CSVs

	#!/usr/bin/env python

	import os
	import numpy as np
	import matplotlib.pyplot as plt
	import matplotlib.dates as mdates

	from datetime import datetime

	PATH = os.path.abspath(os.path.dirname(__file__))

Igor Lukashin ixtel