mdalp

:neo4j-version: 2.2
:author: Marcello Dalponte
:twitter: @m_dalp

## Contact networks

A contact network is one of the typologies of dynamic networks described in the famous paper of Holme and Saramäki[1]. 
A dynamic network is a mathematical representation of the evolution of the relationships between entities through graphs. 
It's interesting to catch this dynamicity because describes the transitivity of the order of the interactions: if A meets B and after B meets C then A can transmit something to C but not the opposite; this is useful to study the spreading of informations or infections.
An interesting project that aims to collect this kind of data is Sociopatterns[2], where Cattuto and others developed a framework to collect contacts data from RFID sensors [3]. 

mdalp

# The story of rebels economical system began

## Introduction

Here I tell you a story to present a solution to an everyday problem.
How many times it happens that you go for a travel in the hyperspace
with other rebels, you go on a mission with a couple of Jedi or,
in general, you do something together with other people with which
you have to share expenses?

mdalp

import re

class DaveType(type):
    not_allowed_attr_names = re.compile('^__\w+__$')
    
    @classmethod
    def _is_allowed_attr_name(cls, name):
        return not cls.not_allowed_attr_names.match(name)
    
    @classmethod

mdalp

def PoweredRelatedFactory(related_factory_class, related_name, pre_save=None):
    """Improvement of factory.RelatedFactory.

    :param related_factory_class:   (class) factory class of the related field
    :param related_name:    (str)  string defining the name of the attribute
        of the related factory
    :param pre_save:        (function) function called just before calling
        the related factory class. Takes:
            - `related_kwargs`  (dict) ATTR__SUBATTR dict of the related object to create
            - `related_n`       (int) index of the list of related objects, if

mdalp

from __future__ import division
def binary_digits(n):
    if n == 0:
        return '0'

    res = ''
    while n > 0:
        mod_n = n % 2
        res = str(mod_n) + res
        n = int(n / 2)

mdalp

from __future__ import absolute_import, division, unicode_literals, print_function
import atexit
import cPickle
import logging
import multiprocessing
import sys
import time
import traceback
from datetime import datetime