Derek_yuli的专栏

json.load:Deserialize fp (a .read()-supporting file-like object containing a JSON document) to a Python object using this conversion table.json.loads:Deserialize s (a str or unicode instance

Single-Source shortest PathsInput directed graph G = (V,E)  (m = |E|, n = |V|)    ---each edge has nonnegative length     ---source vertex soutput: for each v, compute L(v) = length of a sho

import operatorresult = sorted(dict.iteritems(), key = operator.itemgetter(1))The type of result is "list" and is sorted by the values of dict in ascending order.

Graph Search and Connectivity    Generic Graph Search    Goals 1. find everything findable              2. don't explore anything twice    Generic Algorithm (given graph G, vertex S)

在Python中,无论你把对象做为参数传递,做为函数返回值,都是引用传递的。标准库中的copy模块提供了两个方法来实现拷贝.一个方法是copy(shallow copy),它返回和参数包含内容一样的对象。浅拷贝是指拷贝的只是原对象元素的引用，换句话说，浅拷贝产生的对象本身是新的，但是它的内容不是新的，只是对原对象的一个引用。这里有个例子>>> a=[[1, 2], 3, 4

Merge Sort is a good introduction to divide & conquer.The Big O of Merge Sort Algorithm is O(nlog(n)).The divide & conquer Paradigm1. Divide into small subproblems2. Conquer via recursive

如果不知道dict中是否有key的值，那么最好用dict.get(key)如果用dict[key]这个读取会报KeyError异常d = {'a': 1, 'b': 2}'a' in dTrueor:d = {'a': 1, 'b': 2}d.has_key('a')TrueIn fact has_key() was removed in Pytho

1. Simple expression3e-10 #10的－10次10//3 #10/3的整数部分10%3 #余数2.Setsx = {} #dictionary not setx = set() #setsum({1,2,3})sum({1,2,3}, 3)num = {1,2,3}2 in num #return True2 not

def choosePivot(number, l, r): #choose the first element as the Pivot p = l return pdef partition(number, l, r, p): number[l], number[p] = number[p], number[l] #swap the lth number a

Graphs     Two ingredients     1. vertices (nodes) v     2. edges(undirected or directed)Examples: road networks, the web, social networksThe minimum Cut problem    Input: undirected g

count = 0def function(): count = count + 1 print(count)Then we get: UnboundLocalError: local variable 'count' referenced before assignmentThe reason this happens is because as so

首先讲一下写这篇文章的动机，之前已经写过一段时间的python代码了，但是基本上仅限于基本的算法和机器学习方面的算法，对Linux、Mac OS下的环境也不是很熟悉。    不过最近开始研究Deep Learning，准备捣鼓下Montreal 大学Yoshua Bengio等人搞的python的包Theano(论文地址：http://www.iro.umontreal.ca/~lisa/po