Arignir

HoleyBeep

This is an exploit for HoleyBeep.

To use it, place any command you want root to execute in /tmp/x.

$ cat /tmp/x
echo PWNED $(whoami)

stepps00

#!/usr/bin/env python

# run original SHP file thru MapShaper to add label position (mps_y, mps_x) columns
#
# first add label position via mapshaper:
# mapshaper input.shp encoding=utf8 -each 'mps_x=$.innerX, mps_y=$.innerY' -o import_via_mapshaper.shp
# full example:
# mapshaper /usr/local/mapzen/countries/Chile/Admin_2/Chile_admin2.shp encoding=utf8 -each 'mps_x=$.innerX, mps_y=$.innerY' -o chile_adm2_via_mapshaper.shp
#
# now convert that SHP to GeoJSON format, which is easier to load into Python

patpohler

Big List of Real Estate APIs

Listings / Property Data

####Rets Rabbit http://www.retsrabbit.com

Rets Rabbit removes the nightmare of importing thousands of real estate listings and photos from RETS or ListHub and gives you an easy to use import and Web API server so you can focus on building your listing search powered website or app.

ctokheim

Cython

Cython has two major benefits:

1. Making python code faster, particularly things that can't be done in scipy/numpy
2. Wrapping/interfacing with C/C++ code

Cython gains most of it's benefit from statically typing arguments. However, statically typing is not required, in fact, regular python code is valid cython (but don't expect much of a speed up). By incrementally adding more type information, the code can speed up by several factors. This gist just provides a very basic usage of cython.

irazasyed

<?PHP

/**
 * Spintax - A helper class to process Spintax strings.
 */
class Spintax
{
    /**
     * Set seed to make the spinner predictable. 
     */

pnorman

(select way, religion,
coalesce (aeroway, amenity, landuse, leisure, military, "natural", power, tourism, highway) as feature from (
select way,
('aeroway_' || (case when aeroway in ('apron', 'aerodrome') then aeroway else null end)) as aeroway,
('amenity_' || (case when amenity in ('parking', 'university', 'college', 'school', 'hospital', 'kindergarten', 'grave_yard') then amenity else null end)) as amenity,
('landuse_' || (case when landuse in ('quarry', 'vineyard', 'orchard', 'cemetery', 'grave_yard', 'residential', 'garages', 'field', 'meadow', 'grass', 'allotments', 'forest', 'farmyard', 'farm', 'farmland', 'recreation_ground', 'conservation', 'village_green', 'retail', 'industrial', 'railway', 'commercial', 'brownfield', 'landfill', 'greenfield', 'construction') then landuse else null end)) as landuse,
('leisure_' || (case when leisure in ('swimming_pool', 'playground', 'park', 'recreation_ground', 'common', 'garden', 'golf_course') then leisure else null end)) as leisure,
('military_' || (case when mil

sloria

import math
from text.blob import TextBlob as tb

def tf(word, blob):
    return blob.words.count(word) / len(blob.words)

def n_containing(word, bloblist):
    return sum(1 for blob in bloblist if word in blob)

def idf(word, bloblist):

sgillies

Author: Sean Gillies Version: 1.0

Abstract

This document describes a GeoJSON-like protocol for geo-spatial (GIS) vector data.

Introduction