


Solution to the problem that Django templates cannot use perms variables
This article mainly introduces to you the method to solve the problem that Django template cannot use perms variables. The article introduces it in detail through sample code. It has certain reference learning value for everyone's study or work. Friends who need it can follow Let’s learn together with the editor.
Preface
This article mainly introduces to you the solution to the problem that Django template cannot use perms variables, and shares it for your reference and study. Below Not much to say, let’s take a look at the detailed introduction.
Solution:
First of all, when using Django’s built-in permission management system, add
to the settings.py file
INSTALLED_APPS添加: 'django.contrib.auth', MIDDLEWARE添加: 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.context_processors.auth', TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'templates')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.i18n', 'django.template.context_processors.media', 'django.template.context_processors.static', 'django.template.context_processors.tz', 'django.contrib.messages.context_processors.messages', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', ], }, }, ]
How to check permissions in templates?
According to the official website instructions https://docs.djangoproject.com/en/1.11/topics/auth/default/#permissions, the logged in user permissions are saved in the template {{ perms }}
variable is an instance of the permission template agent django.contrib.auth.context_processors.PermWrapper
. For details, you can view the django/contrib/auth/context_processors.py source code
Test case:
During the test, it was found that the {{ perms }}
variable did not exist at all and there was no output; Well, I can only get the source code of Debug Django
def auth(request): """ Returns context variables required by apps that use Django's authentication system. If there is no 'user' attribute in the request, uses AnonymousUser (from django.contrib.auth). """ if hasattr(request, 'user'): user = request.user else: from django.contrib.auth.models import AnonymousUser user = AnonymousUser() print(user, PermWrapper(user), '-----------------------') return { 'user': user, 'perms': PermWrapper(user), }
Test the access interface and find that some interfaces have printing permission information, and some do not, it seems that I suddenly woke up
The interface that can print permission information returns:
return render(request, 'fms/fms_add.html', {'request': request, 'form': form, 'error': error})
The new interface that cannot print permission information returns:
return render_to_response( 'fms/fms.html', data)
The difference between render and render_to_response
render is a more convenient method of rendering templates than render_to_reponse, and will automatically use RequestContext, while the latter requires Manually add:
return render_to_response(request, 'fms/fms_add.html', {'request': request, 'form': form, 'error': error},context_instance=RequestContext(request))
where RequestContext is a subclass of django.template.Context
. Accepts request
and context_processors
, so the problem of rendering context filling to the template has been made clear. Due to the use of the render_to_response
method, the template cannot be used without manually adding context_instance=RequestContext(request)
{{ perms }}Variables
The above is the detailed content of Solution to the problem that Django templates cannot use perms variables. For more information, please follow other related articles on the PHP Chinese website!

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

SublimeText3 Chinese version
Chinese version, very easy to use