小编Gau*_*pta的帖子

django.db.utils.InternalError：（1050，“表'django_content_type'已经存在”）

我刚刚从我的朋友那里复制了一个项目，当我运行 makemirations 时它运行正常。但对于 -

python3 manage.py migrate 

它给出了这个错误 -

Operations to perform:
  Apply all migrations: admin, auth, balancesheet, contenttypes, dynapp, pandl2, sessions, trialbal2
Running migrations:
  Applying contenttypes.0001_initial...Traceback (most recent call last):
  File "/home/hostbooks/django1/myproject/lib/python3.6/site-packages/django/db/backends/utils.py", line 82, in _execute
    return self.cursor.execute(sql)
  File "/home/hostbooks/django1/myproject/lib/python3.6/site-packages/django/db/backends/mysql/base.py", line 74, in execute
    return self.cursor.execute(query, args)
  File "/home/hostbooks/django1/myproject/lib/python3.6/site-packages/pymysql/cursors.py", line 170, in execute
    result = self._query(query)
  File "/home/hostbooks/django1/myproject/lib/python3.6/site-packages/pymysql/cursors.py", line 328, in _query
    conn.query(q)
  File "/home/hostbooks/django1/myproject/lib/python3.6/site-packages/pymysql/connections.py", line 517, in query
    self._affected_rows = self._read_query_result(unbuffered=unbuffered)
  File "/home/hostbooks/django1/myproject/lib/python3.6/site-packages/pymysql/connections.py", line 732, in _read_query_result …

DRF 中的 request.data 和 DRF 中的 serializers.data 有什么区别。

当我在 DRF 中编写基于函数的视图时，我同时使用它们 -

        elif request.method == 'POST':  

        serializer = datesSerializer(data=request.data)
        if serializer.is_valid():
            serializer.save()   

和，

        startdate = serializer.data['startdate']
        enddate = serializer.data['enddate']

但是找不到它们的区别以及在代码中使用它们的区别。

如何在 Django Rest-API 中使用“serializer.initial_data”。使用request.data和serializer.initial_data有什么区别。

我正在使用 Python 制作一个聊天机器人。代码：

import nltk
import numpy as np
import random
import string 
f=open('/home/hostbooks/ML/stewy/speech/chatbot.txt','r',errors = 'ignore')
raw=f.read()
raw=raw.lower()# converts to lowercase

sent_tokens = nltk.sent_tokenize(raw)# converts to list of sentences 
word_tokens = nltk.word_tokenize(raw)# converts to list of words

lemmer = nltk.stem.WordNetLemmatizer()    

def LemTokens(tokens):
    return [lemmer.lemmatize(token) for token in tokens]

remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation)

def LemNormalize(text):
    return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))

GREETING_INPUTS = ("hello", "hi", "greetings", "sup", "what's up","hey","hii")
GREETING_RESPONSES = ["hi", "hey", "*nods*", "hi there", "hello", "I am glad! You …