我正在尝试修改优秀的书籍Programming Collective Intelligence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).但是试图这样做,我遇到了一个难以调试的错误.错误是这样的：

  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 216, in post
    sampletrain(nb)
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 201, in sampletrain
    cl.train('Nobody owns the water.','good')
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 139, in train
    self.incf(f,cat)
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 71, in incf
    count=self.fcount(f,cat)
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 92, in fcount
    return float(res)
TypeError: float() argument must be a string or a number

错误发生在这个块中：

  def fcount(self,f,cat):
    res = db.GqlQuery("SELECT * FROM fc WHERE feature =:feature AND category =:category", feature = f, category = cat).get()
#    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 float(res)
#        return float(res[0])

如果我将set_trace()放在第91行,如下所示：

def fcount(self,f,cat):
    res = db.GqlQuery("SELECT * FROM fc WHERE feature =:feature AND category =:category", feature = f, category = cat).get()
    set_trace()
#    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
        set_trace()
        return float(res)

我有这个错误跟踪：

File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 224, in post
    sampletrain(nb)
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 209, in sampletrain
    cl.train('Nobody owns the water.','good')
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 147, in train
    self.incf(f,cat)
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 77, in incf
    count=self.fcount(f,cat)
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 95, in fcount
    if res is None: return 0
  File "C:\Users\CG\Desktop\Google Drive\Sci&Tech\projects\naivebayes\main.py", line 95, in fcount
    if res is None: return 0
  File "C:\Python27\lib\bdb.py", line 48, in trace_dispatch
    return self.dispatch_line(frame)
  File "C:\Python27\lib\bdb.py", line 67, in dispatch_line
    if self.quitting: raise BdbQuit
BdbQuit

它与GqlQuery有关.我想在Python IDE中测试代码,逐步打印变量和查询,试图找出问题所在.但是当我尝试在python IDE中执行此操作时,我收到错误消息(例如“ImportError：No module named webapp2”).而且我对成功改变它的程序流程并不熟悉.实际上,我试图这样做却迷路了：我是一名新手程序员,直到最近才开始学习OOP).在这种情况下找到错误的最佳方法是什么？

预期答案应包括此错误标识.

在此先感谢您的帮助！

这里是整个代码：

#!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

# -*- coding: utf-8 -*-
# -*- coding: utf-8 -*-

import os

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')))

import random

from google.appengine.ext import db

import re

import math

def set_trace():
import pdb, sys
debugger = pdb.Pdb(stdin=sys.__stdin__,
    stdout=sys.__stdout__)
debugger.set_trace(sys._getframe().f_back)

class fc(db.Model):
    feature = db.StringProperty(required = True)
    category = db.StringProperty(required = True)
    count = db.IntegerProperty(required = True)

class cc(db.Model):
    category = db.StringProperty(required = True)
    count = db.IntegerProperty(required = True)

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()
#    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 float(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)

解决方法:

您有一个类型错误,应该很容易找到,但您似乎在部署服务器或IDE中运行它之间做出错误的选择.

您可以在本地运行GAE development server,它可以模拟部署环境.

扔掉你的IDE,在开发服务器上运行,*地使用print来确保这些值是你期望它们从错误源中散发出来的.

IDE不能替代理解代码正在做什么,并且依赖于IDE会在您和代码之间放置一层分离,这只会使调试变得更加困难.