I get: TemplateSyntaxError at /blog/post/test Caught NameError while rendering: global name 'forms' is not defined for this code: forms.py from dojango.forms import widgets from django.contrib.comments.forms import CommentForm from Website.Comments.models import PageComment class PageCommentForm(CommentForm): title = widgets.TextInput() rating = widgets.RatingInput()
我得到： / blog / post / test中的TemplateSyntaxError在呈现时捕获NameError：没有定义全局名称“forms” 对于此代码： forms.py from dojango.forms import widgets from django.contrib.comments.forms import CommentForm from Website.Comments.models import PageComment class PageCommentForm(CommentForm): title = widgets.TextInput() rating = widgets.RatingInput() def get_comment_model(self
Recently i asked a question regarding an error in apache/mod_wsgi recognizing the python script directory. The community kindly answered the question resulting in a successful installation. Now I have a different error, the server daemon (well, technically is a windows service, I say tomato you say...) doesn't find any of the models, here's the full traceback: Environment: Request Me
最近我问了一个关于apache / mod_wsgi中的错误的问题，它可以识别python脚本目录。 社区很好地回答了导致安装成功的问题。 现在我有一个不同的错误，服务器守护进程（嗯，技术上是一个Windows服务，我说番茄你说...）没有找到任何模型，这里是完整的追溯： 环境： Request Method: GET Request URL: `http://localhost/polls/` Django Version: 1.0.2 final Python Version: 2.6.2 Installed Applications: ['django.contrib
I know this question has already been answered on this site, however, none of the solutions I looke up the internet seemed to work. Here's what I tried: Giving all permissions to my python file Changing PATH variable to point to my tesseract folder Running IDLE as administrator and then executing the file from there This error is quite bothering me now and I can't advance any fur
我知道这个问题已经在这个网站上得到了答复，但是，我没有任何解决互联网问题的解决方案似乎工作。 这是我尝试过的： 授予我的Python文件的所有权限 更改PATH变量以指向我的tesseract文件夹 以管理员身份运行IDLE，然后从那里执行文件 现在这个错误让我非常困扰，因为它，我无法进一步发展。 这是我的代码，如果这将有所帮助： import pytesseract import sys import argparse try: import Image except ImportEr
I'm profiling in Python using cProfile . I found a function that takes a lot of CPU time. How do I find out which function is calling this heavy function the most? EDIT: I'll settle for a workaround: Can I write a Python line inside that heavy function that will print the name of the function that called it? That may not answer your question directly, but will definitely help. If
我使用cProfile在Python中进行cProfile 。 我发现一个需要很多CPU时间的功能。 如何找出哪个函数最重要的是调用这个重函数？ 编辑： 我会解决一个解决方法：我可以在这个沉重的函数中写一个Python行，它会打印调用它的函数的名字吗？ 这可能不会直接回答你的问题，但肯定会有所帮助。 如果使用profiler选项--sort累计，它将按累计时间对函数进行排序。 这不仅有助于检测重度功能，而且还可以检测调用它们的功能。 pyth
I use cProfile now but I find it tedious to write pstats code just to query the statistics data. I'm looking for a visual tool that shows me what my Python code is doing in terms of CPU time and memory allocation. Some examples from the Java world are visualvm and JProfiler. Does something like this exist? Is there an IDE that does this? Would dtrace help? I know about KCachegrind
我现在使用cProfile，但是我发现编写pstats代码来查询统计数据非常繁琐。 我正在寻找一个可视化工具，它向我展示了我的Python代码在CPU时间和内存分配方面所做的工作。 来自Java世界的一些例子是visualvm和JProfiler。 有这样的事情存在吗？ 有没有这样做的IDE？ dtrace会有帮助吗？ 我知道KCachegrind for Linux，但我更喜欢可以在Windows / Mac上运行而无需安装KDE的东西。 我和一位朋友编写了一个名为SnakeViz
I am trying to understand threading in Python. I've looked at the documentation and examples, but quite frankly, many examples are overly sophisticated and I'm having trouble understanding them. How do you clearly show tasks being divided for multi-threading? Since this question was asked in 2010, there has been real simplification in how to do simple multithreading with python with
我想了解Python中的线程。 我已经看过文档和示例，但坦率地说，很多示例都非常复杂，我无法理解它们。 你如何清楚地显示被划分为多线程的任务？ 自从2010年提出这个问题以来，已经真正简化了如何用map和pool进行python简单的多线程处理。 下面的代码来自一篇文章/博客文章，你一定要检查（无从属关系） - 并行性在一行中：日常线程任务的更好模型 。 我将在下面总结 - 它最终只是几行代码： from multiprocessing.dummy
Possible Duplicate: Python: Behaviour of increment and decrement operators I've always laughed to myself when I've looked back at my VB6 days and thought, "What modern language doesn't allow incrementing with double plus signs?": number++ To my surprise, I can't find anything about this in the Python docs. Must I really subject myself to number = number + 1 ? Don
可能重复： Python：增量和减量运算符的行为 当我回顾我的VB6时代，我一直都在笑自己，并且想：“现代语言不允许用双加号递增？”： number++ 令我惊讶的是，在Python文档中我找不到任何关于此的信息。 我真的必须让自己的number = number + 1吗？ 不要使用++/--符号吗？ Python不支持++ ，但你可以这样做： number += 1 简而言之， ++和--运算符在Python中不存在，因为它们不是运算符，它们必须是语句。 为了简单和一
I have already checked many posts such as the one here, but I don't think they have what I look for. I want to create a merging function for the game 2048, and I want it the algorithm to be as general as possible: it should work for the traditional 4x4 2048, as well as the less common 3x3, 5x5 and so on. I also want to use only the most basic functions such as if-else (I am actually coding
我已经在这里检查过很多帖子，但我认为他们没有找到我想要的东西。 我想为游戏2048创建一个合并函数，我希望它的算法尽可能通用：它应该适用于传统的4x4 2048，以及不太常见的3x3，5x5等等。 我也只想使用最基本的功能，例如if-else（我实际上是在使用汇编语言的微处理器中进行编码，所以我不能在python中使用任何奇特的例程或函数）。 有没有高效的优雅解决方案？ 我从较简单的3x3版本开始，为了向右滑动，我开始检查右侧
I'm looking for some kind of "Domino sort" algorithm that sorts a list of two-sided items based on the similarity of "tangent" sides of subsequent items. Suppose the following list where items are represented by 2-tuples: >>> items [(0.72, 0.12), (0.11, 0.67), (0.74, 0.65), (0.32, 0.52), (0.82, 0.43), (0.94, 0.64), (0.39, 0.95), (0.01, 0.72), (0.49, 0.4
我正在寻找某种“Domino排序”算法，它根据后续项目的“相切”边的相似性对双侧项目列表进行排序。 假设以下列表项目由2元组表示： >>> items [(0.72, 0.12), (0.11, 0.67), (0.74, 0.65), (0.32, 0.52), (0.82, 0.43), (0.94, 0.64), (0.39, 0.95), (0.01, 0.72), (0.49, 0.41), (0.27, 0.60)] 目标是对该列表进行排序，使得每两个后续项目（损失）的正切结尾的平方差的总和最小： >>> loss = sum(
I'm trying to classify emotion based on text using naive Bayes. I have the ISEAR dataset and NRC dataset. I felt that ISEAR has lower result compared to NRC. A little explanation for those didn't know the difference between ISEAR and NRC, ISEAR was dataset consist of sentences and NRC was word as a dictionary. The result was far from I expected when inputting manual sentences using IS
我试图用基于朴素贝叶斯的文本来分类情感。 我有ISEAR数据集和NRC数据集。 与NRC相比，我觉得ISEAR的结果较低。 对于那些不了解ISEAR和NRC之间的区别的小解释，ISEAR是由句子组成的数据集，而NRC是词作为词典。 当使用ISEAR输入手动句子时，结果与我的预期相去甚远。 我对机器学习有点新，所以如果我错了，请纠正我。 那么朴素的贝叶斯如何使用每个词的概率显示正确？ 例如，我有一个词“我很高兴”，它在“惊喜”功能上出