我正在尝试修改优秀书籍编程集体智能提供的朴素贝叶斯分类器的代码，使其适应GAE数据存储区（提供的代码使用pysqlite2）。但试图这样做，我遇到了这一行：
update.count = count + 1
来自这个街区：
def incf(self,f,cat):
count=self.fcount(f,cat)
if count==0:
fc_value = fc(feature = f, category = cat, count = 1)
fc_value.put()
else:
update = db.GqlQuery("SELECT count FROM fc where feature =:feature AND category =:category", feature = f, category = cat).get()
update.count = count + 1
update.put()
# self.con.execute(
# "update fc set count=%d where feature='%s' and category='%s'"
# % (count+1,f,cat))
此错误：
File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 221, in post
sampletrain(nb)
File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 206, in sampletrain
cl.train('Nobody owns the water.','good')
File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 144, in train
self.incf(f,cat)
File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 82, in incf
update.count = count + 1
TypeError: unsupported operand type(s) for +: 'IntegerProperty' and 'int'
我无法理解：为什么我不能用{1}增加count？
为什么update = db.GqlQuery("SELECT count FROM cc where category =:category", category = cat).get()
update.count = count + 1是'IntegerProperty'而不是整数？
我该如何解决？执行此update.count = count + 1操作的正确语法是什么？
这里是整个代码：
import os
import random
import re
import math
from google.appengine.ext import db
import webapp2
import jinja2
from jinja2 import Environment, FileSystemLoader
jinja_environment = jinja2.Environment(autoescape=True,
loader=jinja2.FileSystemLoader(os.path.join(os.path.dirname(__file__), 'templates')))
class fc(db.Model):
feature = db.StringProperty()
category = db.StringProperty()
count = db.IntegerProperty()
class cc(db.Model):
category = db.StringProperty()
count = db.IntegerProperty()
def getfeatures(doc):
splitter=re.compile('\\W*')
# Split the words by non-alpha characters
words=[s.lower() for s in splitter.split(doc)
if len(s)>2 and len(s)<20]
return dict([(w,1) for w in words])
class classifier:
def __init__(self,getfeatures, filename=None):
# Counts of feature/category combinations
self.fc={}
# Counts of documents in each category
self.cc={}
self.getfeatures=getfeatures
# def setdb(self,dbfile):
# self.con=sqlite.connect('db_file')
# self.con=sqlite3.connect(":memory:")
# self.con.execute('create table if not exists fc(feature,category,count)')
# self.con.execute('create table if not exists cc(category,count)')
def incf(self,f,cat):
count=self.fcount(f,cat)
if count==0:
fc_value = fc(feature = f, category = cat, count = 1)
fc_value.put()
else:
update = db.GqlQuery("SELECT count FROM fc where feature =:feature AND category =:category", feature = f, category = cat).get()
update.count = count + 1
update.put()
# self.con.execute(
# "update fc set count=%d where feature='%s' and category='%s'"
# % (count+1,f,cat))
def fcount(self,f,cat):
res = db.GqlQuery("SELECT * FROM fc WHERE feature =:feature AND category =:category", feature = f, category = cat).get()
logging.debug('This is a log message.')
# res=self.con.execute(
# 'select count from fc where feature="%s" and category="%s"'
# %(f,cat)).fetchone()
if res is None: return 0
else:
res = fc.count
return res
# return float(res[0])
def incc(self,cat):
count=self.catcount(cat)
if count==0:
# self.con.execute("insert into cc values ('%s',1)" % (cat))
cc_value = cc(category = cat, count = 1)
cc_value.put()
else:
update = db.GqlQuery("SELECT count FROM cc where category =:category", category = cat).get()
update.count = count + 1
update.put()
# self.con.execute("update cc set count=%d where category='%s'"
# % (count+1,cat))
def catcount(self,cat):
# res=self.con.execute('select count from cc where category="%s"'
# %(cat)).fetchone()
res = db.GqlQuery("SELECT count FROM cc WHERE category =:category", category = cat).get()
if res is None: return 0
# else: return float(res[0])
else: return float(res)
def categories(self):
# cur = self.con.execute('select category from cc');
cur = db.GqlQuery("SELECT category FROM cc").fetch(999)
return [d[0] for d in cur]
def totalcount(self):
# res=self.con.execute('select sum(count) from cc').fetchone();
all_cc = db.GqlQuery("SELECT * FROM cc").fetch(999)
res = 0
for cc in all_cc:
count = cc.count
res+=count
# res = db.GqlQuery("SELECT sum(count) FROM cc").get()
# if res==None: return 0
if res == 0: return 0
# return res[0]
return res
def train(self,item,cat):
features=self.getfeatures(item)
# Increment the count for every feature with this category
for f in features.keys():
## for f in features:
self.incf(f,cat)
# Increment the count for this category
self.incc(cat)
# self.con.commit()
def fprob(self,f,cat):
if self.catcount(cat)==0: return 0
# The total number of times this feature appeared in this
# category divided by the total number of items in this category
return self.fcount(f,cat)/self.catcount(cat)
def weightedprob(self,f,cat,prf,weight=1.0,ap=0.5):
# Calculate current probability
basicprob=prf(f,cat)
# Count the number of times this feature has appeared in
# all categories
totals=sum([self.fcount(f,c) for c in self.categories()])
# Calculate the weighted average
bp=((weight*ap)+(totals*basicprob))/(weight+totals)
return bp
class naivebayes(classifier):
def __init__(self,getfeatures):
classifier.__init__(self, getfeatures)
self.thresholds={}
def docprob(self,item,cat):
features=self.getfeatures(item)
# Multiply the probabilities of all the features together
p=1
for f in features: p*=self.weightedprob(f,cat,self.fprob)
return p
def prob(self,item,cat):
catprob=self.catcount(cat)/self.totalcount()
docprob=self.docprob(item,cat)
return docprob*catprob
def setthreshold(self,cat,t):
self.thresholds[cat]=t
def getthreshold(self,cat):
if cat not in self.thresholds: return 1.0
return self.thresholds[cat]
def classify(self,item,default=None):
probs={}
# Find the category with the highest probability
max=0.0
for cat in self.categories():
probs[cat]=self.prob(item,cat)
if probs[cat]>max:
max=probs[cat]
best=cat
# Make sure the probability exceeds threshold*next best
for cat in probs:
if cat==best: continue
if probs[cat]*self.getthreshold(best)>probs[best]: return default
return best
def sampletrain(cl):
cl.train('Nobody owns the water.','good')
cl.train('the quick rabbit jumps fences','good')
cl.train('buy pharmaceuticals now','bad')
cl.train('make quick money at the online casino','bad')
cl.train('the quick brown fox jumps','good')
class MainHandler(webapp2.RequestHandler):
def get(self):
template_values = {"given_sentence":'put a name here'}
template = jinja_environment.get_template('index.html')
self.response.out.write(template.render(template_values))
def post(self):
nb = naivebayes(getfeatures)
sampletrain(nb)
given_sentence = self.request.get("given_sentence")
spam_result = nb.classify(given_sentence)
submit_button = self.request.get("submit_button")
if submit_button:
self.redirect('/test_result?spam_result=%s&given_sentence=%s' % (spam_result, given_sentence))
class test_resultHandler(webapp2.RequestHandler):
def get(self):
spam_result = self.request.get("spam_result")
given_sentence = self.request.get("given_sentence")
test_result_values = {"spam_result": spam_result,
"given_sentence": given_sentence}
template = jinja_environment.get_template('test_result.html')
self.response.out.write(template.render(test_result_values))
app = webapp2.WSGIApplication([('/', MainHandler), ('/test_result', test_resultHandler)],
debug=True)
答案 0 :(得分：3)
“属性”通常意味着在对象实例上访问，而不是在类上访问。尝试更改：
class fc(db.Model):
feature = db.StringProperty()
category = db.StringProperty()
count = db.IntegerProperty()
类似于：
class fc_class(db.Model):
feature = db.StringProperty()
category = db.StringProperty()
count = db.IntegerProperty()
fc = fc_class()
（并不是说这是一个很棒的设计，但我认为它会解决你遇到的问题 - 即属性对象只有在通过类isntance访问时才会获得特殊行为，而不是通过类本身。）
答案 1 :(得分：2)
查看您的代码，似乎问题可能出在res任务中：
def fcount(self,f,cat):
res = db.GqlQuery("SELECT * FROM fc WHERE feature =:feature AND category =:category", feature = f, category = cat).get()
logging.debug('This is a log message.')
if res is None: return 0
else:
res = fc.count
return res
据我所知，您正在为class fc分配一个未绑定的res方法，正如@Hamish所指出的那样，确实是IntegerProperty()。相反（又一次，不是专业人士），你可能想要返回一个这样的值：
def fcount(self,f,cat):
res = db.GqlQuery("SELECT * FROM fc WHERE feature =:feature AND category =:category", feature = f, category = cat).get()
logging.debug('This is a log message.')
if res is None: return 0
else:
return res.count
我相信res已经是一个Query实例（这就是你想要的），然后你可以拉count属性来获得你想要的值。