本文将带您了解关于ImportError：没有名为twisted.persisted.styles的模块的新内容，同时我们还将为您解释没有命名类型的相关知识，另外，我们还将为您提供关于GDB漂亮打印I

本文将带您了解关于ImportError：没有名为twisted.persisted.styles的模块的新内容，同时我们还将为您解释没有命名类型的相关知识，另外，我们还将为您提供关于GDB漂亮打印ImportError：没有名为“ printers”的模块、ImportError：没有名为 dateutil.parser 的模块、ImportError：没有名为 Image 的模块 [重复] - ImportError: No module named Image [duplicate]、ImportError：没有名为 PIL 的模块的实用信息。

• ImportError：没有名为twisted.persisted.styles的模块（没有命名类型）
• GDB漂亮打印ImportError：没有名为“ printers”的模块
• ImportError：没有名为 dateutil.parser 的模块
• ImportError：没有名为 Image 的模块 [重复] - ImportError: No module named Image [duplicate]
• ImportError：没有名为 PIL 的模块

ImportError：没有名为twisted.persisted.styles的模块（没有命名类型）

从IDLE，我尝试使用新安装的scrapy 1.0.3运行脚本。

我使用的是他所工作的朋友的脚本（但在Windows上，我在Mac上）。

从第一行的scrapy导入中，运行程序时出现此错误： ImportError: No module named twisted.persisted.styles

整个脚本（如果有帮助）指向此：

Traceback (most recent call last):  File "/Users/eliasfong/tutorial/tutorial/spiders/medspider.py", line 1, in <module>    import scrapy  File "/Library/Python/2.7/site-packages/scrapy/__init__.py", line 27, in <module>    from . import _monkeypatches  File "/Library/Python/2.7/site-packages/scrapy/_monkeypatches.py", line 20, in <module>    import twisted.persisted.styles  # NOQAImportError: No module named twisted.persisted.styles

关于如何解决这个问题有什么建议吗？

答案1

只要尝试强制更新：

pip install twisted --upgrade

这对我适用于python3.4和Scrapy == 1.1.0rc1

GDB漂亮打印ImportError：没有名为“ printers”的模块

Traceback (most recent call last):
  File "<string>",line 3,in <module>
  File "/home/jerry/myLib/gdb_stl_support/python/libstdcxx/v6/__init__.py",line 19,in <module>
    from printers import register_libstdcxx_printers
ImportError: No module named 'printers'
/home/jerry/.gdbinit:6: Error in sourced command file:
Error while executing Python code.
Reading symbols from main...done.

ImportError：没有名为 dateutil.parser 的模块

pandas在Python程序中导入时收到以下错误

monas-mbp:book mona$ sudo pip install python-dateutilRequirement already satisfied (use --upgrade to upgrade): python-dateutil in /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/pythonCleaning up...monas-mbp:book mona$ python t1.pyNo module named dateutil.parserTraceback (most recent call last):  File "t1.py", line 4, in <module>    import pandas as pd  File "/Library/Python/2.7/site-packages/pandas/__init__.py", line 6, in <module>    from . import hashtable, tslib, lib  File "tslib.pyx", line 31, in init pandas.tslib (pandas/tslib.c:48782)ImportError: No module named dateutil.parser

还有这里的程序：

import codecs from math import sqrtimport numpy as npimport pandas as pdusers = {"Angelica": {"Blues Traveler": 3.5, "Broken Bells": 2.0,                      "Norah Jones": 4.5, "Phoenix": 5.0,                      "Slightly Stoopid": 1.5,                      "The Strokes": 2.5, "Vampire Weekend": 2.0},         "Bill":{"Blues Traveler": 2.0, "Broken Bells": 3.5,                 "Deadmau5": 4.0, "Phoenix": 2.0,                 "Slightly Stoopid": 3.5, "Vampire Weekend": 3.0},         "Chan": {"Blues Traveler": 5.0, "Broken Bells": 1.0,                  "Deadmau5": 1.0, "Norah Jones": 3.0, "Phoenix": 5,                  "Slightly Stoopid": 1.0},         "Dan": {"Blues Traveler": 3.0, "Broken Bells": 4.0,                 "Deadmau5": 4.5, "Phoenix": 3.0,                 "Slightly Stoopid": 4.5, "The Strokes": 4.0,                 "Vampire Weekend": 2.0},         "Hailey": {"Broken Bells": 4.0, "Deadmau5": 1.0,                    "Norah Jones": 4.0, "The Strokes": 4.0,                    "Vampire Weekend": 1.0},         "Jordyn":  {"Broken Bells": 4.5, "Deadmau5": 4.0,                     "Norah Jones": 5.0, "Phoenix": 5.0,                     "Slightly Stoopid": 4.5, "The Strokes": 4.0,                     "Vampire Weekend": 4.0},         "Sam": {"Blues Traveler": 5.0, "Broken Bells": 2.0,                 "Norah Jones": 3.0, "Phoenix": 5.0,                 "Slightly Stoopid": 4.0, "The Strokes": 5.0},         "Veronica": {"Blues Traveler": 3.0, "Norah Jones": 5.0,                      "Phoenix": 4.0, "Slightly Stoopid": 2.5,                      "The Strokes": 3.0}        }class recommender:    def __init__(self, data, k=1, metric=''pearson'', n=5):        """ initialize recommender        currently, if data is dictionary the recommender is initialized        to it.        For all other data types of data, no initialization occurs        k is the k value for k nearest neighbor        metric is which distance formula to use        n is the maximum number of recommendations to make"""        self.k = k        self.n = n        self.username2id = {}        self.userid2name = {}        self.productid2name = {}        # for some reason I want to save the name of the metric        self.metric = metric        if self.metric == ''pearson'':            self.fn = self.pearson        #        # if data is dictionary set recommender data to it        #        if type(data).__name__ == ''dict'':            self.data = data    def convertProductID2name(self, id):        """Given product id number return product name"""        if id in self.productid2name:            return self.productid2name[id]        else:            return id    def userRatings(self, id, n):        """Return n top ratings for user with id"""        print ("Ratings for " + self.userid2name[id])        ratings = self.data[id]        print(len(ratings))        ratings = list(ratings.items())        ratings = [(self.convertProductID2name(k), v)                   for (k, v) in ratings]        # finally sort and return        ratings.sort(key=lambda artistTuple: artistTuple[1],                     reverse = True)        ratings = ratings[:n]        for rating in ratings:            print("%s\t%i" % (rating[0], rating[1]))    def loadBookDB(self, path=''''):        """loads the BX book dataset. Path is where the BX files are        located"""        self.data = {}        i = 0        #        # First load book ratings into self.data        #        f = codecs.open(path + "BX-Book-Ratings.csv", ''r'', ''utf8'')        for line in f:            i += 1            #separate line into fields            fields = line.split('';'')            user = fields[0].strip(''"'')            book = fields[1].strip(''"'')            rating = int(fields[2].strip().strip(''"''))            if user in self.data:                currentRatings = self.data[user]            else:                currentRatings = {}            currentRatings[book] = rating            self.data[user] = currentRatings        f.close()        #        # Now load books into self.productid2name        # Books contains isbn, title, and author among other fields        #        f = codecs.open(path + "BX-Books.csv", ''r'', ''utf8'')        for line in f:            i += 1            #separate line into fields            fields = line.split('';'')            isbn = fields[0].strip(''"'')            title = fields[1].strip(''"'')            author = fields[2].strip().strip(''"'')            title = title + '' by '' + author            self.productid2name[isbn] = title        f.close()        #        #  Now load user info into both self.userid2name and        #  self.username2id        #        f = codecs.open(path + "BX-Users.csv", ''r'', ''utf8'')        for line in f:            i += 1            #print(line)            #separate line into fields            fields = line.split('';'')            userid = fields[0].strip(''"'')            location = fields[1].strip(''"'')            if len(fields) > 3:                age = fields[2].strip().strip(''"'')            else:                age = ''NULL''            if age != ''NULL'':                value = location + ''  (age: '' + age + '')''            else:                value = location            self.userid2name[userid] = value            self.username2id[location] = userid        f.close()        print(i)    def pearson(self, rating1, rating2):        sum_xy = 0        sum_x = 0        sum_y = 0        sum_x2 = 0        sum_y2 = 0        n = 0        for key in rating1:            if key in rating2:                n += 1                x = rating1[key]                y = rating2[key]                sum_xy += x * y                sum_x += x                sum_y += y                sum_x2 += pow(x, 2)                sum_y2 += pow(y, 2)        if n == 0:            return 0        # now compute denominator        denominator = (sqrt(sum_x2 - pow(sum_x, 2) / n)                       * sqrt(sum_y2 - pow(sum_y, 2) / n))        if denominator == 0:            return 0        else:            return (sum_xy - (sum_x * sum_y) / n) / denominator    def computeNearestNeighbor(self, username):        """creates a sorted list of users based on their distance to        username"""        distances = []        for instance in self.data:            if instance != username:                distance = self.fn(self.data[username],                                   self.data[instance])                distances.append((instance, distance))        # sort based on distance -- closest first        distances.sort(key=lambda artistTuple: artistTuple[1],                       reverse=True)        return distances    def recommend(self, user):       """Give list of recommendations"""       recommendations = {}       # first get list of users  ordered by nearness       nearest = self.computeNearestNeighbor(user)       #       # now get the ratings for the user       #       userRatings = self.data[user]       #       # determine the total distance       totalDistance = 0.0       for i in range(self.k):          totalDistance += nearest[i][1]       # now iterate through the k nearest neighbors       # accumulating their ratings       for i in range(self.k):          # compute slice of pie           weight = nearest[i][1] / totalDistance          # get the name of the person          name = nearest[i][0]          # get the ratings for this person          neighborRatings = self.data[name]          # get the name of the person          # now find bands neighbor rated that user didn''t          for artist in neighborRatings:             if not artist in userRatings:                if artist not in recommendations:                   recommendations[artist] = (neighborRatings[artist]                                              * weight)                else:                   recommendations[artist] = (recommendations[artist]                                              + neighborRatings[artist]                                              * weight)       # now make list from dictionary       recommendations = list(recommendations.items())       recommendations = [(self.convertProductID2name(k), v)                          for (k, v) in recommendations]       # finally sort and return       recommendations.sort(key=lambda artistTuple: artistTuple[1],                            reverse = True)       # Return the first n items       return recommendations[:self.n]r = recommender(users)# The author implementationr.loadBookDB(''/Users/mona/Downloads/BX-Dump/'')ratings = pd.read_csv(''/Users/danialt/BX-CSV-Dump/BX-Book-Ratings.csv'', sep=";", quotechar="\"", escapechar="\\")books = pd.read_csv(''/Users/danialt/BX-CSV-Dump/BX-Books.csv'', sep=";", quotechar="\"", escapechar="\\")users = pd.read_csv(''/Users/danialt/BX-CSV-Dump/BX-Users.csv'', sep=";", quotechar="\"", escapechar="\\")pivot_rating = ratings.pivot(index=''User-ID'', columns=''ISBN'', values=''Book-Rating'')

答案1

在 Ubuntu 上，您可能需要先安装包管理器pip：

sudo apt-get install python-pip

然后python-dateutil使用以下命令安装软件包：

sudo pip install python-dateutil

ImportError：没有名为 Image 的模块 [重复] - ImportError: No module named Image [duplicate]

问题：

I have also tried 我也尝试过

from PIL import Image

but it gives me ImportError: No module named PIL. 但是它给了我 ImportError：没有名为 PIL 的模块。

I have installed PIL successfully using 我已经成功使用安装了 PIL

pip install pil

and I''ve also installed xcode command line tools. 并且我还安装了 xcode 命令行工具。 Nothing seem to work. 似乎没有任何作用。

Details : 详细资料 ：

Mac OS X 10.9 Mac OS X 10.9

Python 2.7.6 Python 2.7.6

python is /Library/Frameworks/Python.framework/Versions/2.7/bin/python python 是 / Library/Frameworks/Python.framework/Versions/2.7/bin/python

python is /usr/bin/python python 是 /usr/bin /python

python is /usr/local/bin/python python 是 /usr/local /bin/python

Name: PIL 名称：PIL

Version: 1.1.7 版本：1.1.7

Location: /usr/local/lib/python2.7/site-packages/PIL 位置：/usr/local/lib/python2.7/site-packages/PIL

解决方案：

ImportError：没有名为 PIL 的模块

easy_install PIL

Traceback (most recent call last):
  File "<console>",line 1,in <module>
ImportError: No module named PIL

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