Riuchando

from nltk.corpus import wordnet as wn
from sets import Set

def wordlist(word):
  t=Set([])
  for word in wn.synsets(word):
    for syn in word.lemma_names():
      t.add(syn.lower())
    for hypo in word.hyponyms() :
      #t.append(hypo.lemmas_name())

Riuchando

import random
def randomchunk(lst,chunknum):
  total=len(lst)
  #take the even chunksize and given a normal distribution
  #it seems that a normal coeffecient of variation would be 0.47,
  #so with the random choices let it be the "mean" + or - 0.47* mean, if the - is <1, let it be one
  chunkVariaton=0.47*(float(total)/chunknum)
  high=int((float(total)/chunknum)+  chunkVariaton)
  low=int((float(total)/chunknum)-  chunkVariaton)
  if  low < 1:

Riuchando

import random
def randomchunk(lst,chunknum):
  total=len(lst)
  #take the even chunksize and given a normal distribution
  #it seems that a normal coeffecient of variation would be 0.47,
  #so with the random choices let it be the "mean" + or - 0.47* mean, if the - is <1, let it be one
  chunkVariaton=0.47*(float(total)/chunknum)
  high=int((float(total)/chunknum)+  chunkVariaton)
  low=int((float(total)/chunknum)-  chunkVariaton)
  if  low < 1:

Riuchando

#include <iostream>
int minus(int lhs, int rhs);
int main(){
std::cout<<minus(-4,1)<<'\n';
std::cout<<minus(4,1)<<'\n';
std::cout<<minus(4,-1)<<'\n';
 std::cout<<minus(-4,-1)<<'\n';
 
return 0;
}