def getPaperByWords(words, docNumber = 10):
'''Get a list of articles for a given request.
:param words: list of words for the query.
:param docNumber: count of max nomber of results to get.
:returns: a dictionnary of [nameArticle=>table count[,]]. example of use: data["Article"] = [42, 2]'''
article = Article.all()
data = collections.defaultdict(list)
for oneArticle in article:
nbWord = 0
nbOccur = []
for strWord in words:
mapReduce = MapReduce.all()
mapReduce.filter('keyArticle = ', oneArticle)
mapReduce.filter('keyWord =', strWord)
if mapReduce.count() > 0:
mR = mapReduce.get()
nbWord += mR.count
nbOccur.append(mR.count)
else :
nbOccur.append(0)
if nbWord != 0 :
data[oneArticle.name] = nbOccur
# Sort the results based on the sum of each word's occurences
sortedList = data.items()
sortedList.sort(key=lambda x: sum(x[1]), reverse=True)
return OrderedDict(sortedList)
def getWordsMostFreqByAuthor(authorName, wordNumber = 10):
''' Get the keyword's stats for a given author.
:param authorName: The asked author's name.
:param wordNumber: the max number of results.
:returns: a dictionnary of [word=>count]. example of use: data["lol"] = 42'''
author = Author.all()
author.filter('name = ', authorName)
artiAuths = ArtiAuth.all()
artiAuths.filter('keyAuthor = ', author.get())
data = collections.defaultdict(list)
for article in artiAuths :
mapReduces = MapReduce.all()
mapReduces.filter('keyArticle = ', article.keyArticle)
for mR in mapReduces:
try:
if data[mR.keyWord]:
data[mR.keyWord] += mR.count
else:
data[mR.keyWord] = mR.count
except ReferencePropertyResolveError :
print 'Pas de reference word'
# Sort the results based on the sum of each word's occurences
sortedList = data.items()
sortedList.sort(key=lambda x: x[1], reverse=True)
return OrderedDict(sortedList[0:wordNumber-1])
def saveMapReduce(namefic):
"""
Converted the pdf file in text
Do the mapper and reduce in the text
Get the references cited in the article
Save data Author, Article, ArtCitedBib, MapReduce, Master
:param namefic : the name file
"""
# save_pdf(namefic)
fic = convert_pdf_to_txt(namefic)
dataDict = mapper(fic)
dataDict = reducer(dataDict)
lines = re.split(r"\n", fic)
authorStr = re.sub(r"[^a-zA-Z\s]", " ", lines[4])
author = Author(name=authorStr)
author.put()
titre = re.sub(r"[^a-zA-Z\s]", " ", lines[0] + lines[1])
titre = titre.strip()
article = Article(name=titre, fileName=namefic)
article.put()
getReferences(fic, article)
artiAuth = ArtiAuth(keyAuthor=author, keyArticle=article)
artiAuth.put()
for cle in dataDict.keys():
mapReduce = MapReduce(keyWord=cle, keyArticle=article, count=dataDict[cle])
mapReduce.put()
checkMaster = Master.all()
checkMaster.filter("keyWord =", cle)
if checkMaster.count() > 0:
master = checkMaster.get()
master.count = master.count + dataDict[cle]
else:
master = Master(keyWord=cle, count=dataDict[cle])
master.put()
def deleteData():
"""
Delete all the data
"""
masters = Master.all()
for master in masters:
Master.delete(master)
mapReduces = MapReduce.all()
for mapReduce in mapReduces:
MapReduce.delete(mapReduce)
articles = Article.all()
for article in articles:
Article.delete(article)
authors = Author.all()
for author in authors:
Author.delete(author)
artCitedBibs = ArtCitedBib.all()
for artCitedBib in artCitedBibs:
ArtCitedBib.delete(artCitedBib)