swayson

from pymongo.connection import Connection

m = Connection()
db = m.reddit
votes = db.votes

cursor = votes.find().skip(0).limit(50000)

print "Setup cursor: %s" % cursor

swayson

"""Kernel K-means"""

# Author: Mathieu Blondel <[email protected]>
# License: BSD 3 clause

import numpy as np

from sklearn.base import BaseEstimator, ClusterMixin
from sklearn.metrics.pairwise import pairwise_kernels
from sklearn.utils import check_random_state

swayson

(\b((https?://|www\.)|[a-z0-9\.-]+?\.(com|co\.uk|org|net|info|ca)(?=[/ \W\b]))[^ \t\r\n<>]*?(?=(([\'\xe2\x80\x9c".?!,:;]|&(amp|lt|gt|quot);)+?)?(\.\.+|[<>]|\s|$)))

swayson

# script stolen from http://goo.gl/YbQyAQ

# install.packages("tm")
# install.packages("ggplot2")
# install.packages("lsa")
# install.packages("scatterplot3d")
#install.packages("SnowballC")
#if !(require('SnowballC')) then install.packages("SnowballC")
library(tm)
library(ggplot2)

swayson

# Create a virtual environment using conda
conda create -n edx_downloader python=2.7 pip
activate edx_downloader

# Install dependencies:
pip install youtube-dl
pip install beautifulsoup4

# Get the script
git clone https://github.com/dmitrime/edx-downloader.git

swayson

# Create a virtual environment using conda
conda create -n coursera_dl python=2.7 pip

# Get the code
git clone https://github.com/coursera-dl/coursera.git
cd coursera\

# Install the dependencies (using virtual environment)
activate coursera_dl
pip install -r requirements.txt