Template system in Django framework
Django is a commonly used web development framework, and its template system is an important part of developing web applications. In this article, we will take a deep dive into the template system in the Django framework.
The template system is a modular tool for generating HTML pages. Its goal is to enable developers to separate the logic of the application from the HTML pages returned from the server to the client. This separation makes applications easier to maintain and develop, while also improving code readability.
Django’s template system uses a template language called Django Template Language (DTL). DTL is very similar to other common template languages (such as Jinja2, Twig, etc.).
In Django, a template is usually located in a separate file, which can contain HTML code as well as tags and filters using DTL. Tags and filters are important parts of DTL. They are responsible for generating HTML pages, controlling processes and formatting data.
The following is a simple DTL template example, which shows the basic structure and syntax in Django templates:
<!DOCTYPE html>
<html>
<head>
<title>{{ page_title }}</title>
</head>
<body>
{% if user.is_authenticated %}
<p>Welcome back, {{ user.username }}!</p>
{% else %}
<a href="{% url 'login' %}">Log in</a>
{% endif %}
<ul>
{% for item in items %}
<li>{{ item }}</li>
{% endfor %}
</ul>
</body>
</html>In this example, we can see that the template contains HTML code and the use DTL tags and filter statements. In this template, {{page_title}}, {{user.username}} and {{item}} are all DTL variables, which will be It is dynamically replaced with the corresponding value when the template is rendered.
In addition, the template also contains {% if %} and {% else %} conditional statements, which can generate different HTML codes based on conditions. There is also a {% for %} loop statement, which can be used to traverse a list or query result set and repeatedly generate the same HTML code.
In Django, templates can be obtained from a variety of sources, including files, databases, strings, and other data sources. The template system also supports template inheritance and inclusion, making it easier for developers to reuse and organize template code.
In addition to tags and filters, the Django template system also supports the use of custom tags and filters in templates. Custom tags and filters can be written in Python, and they allow developers to extend the functionality of the template language to suit different application needs.
Summary:
Django’s template system is an important part of developing web applications. It uses DTL as the template language and provides a wealth of tags, filters and functions, allowing developers to It is easier to generate and maintain HTML pages. The template system also supports the development of templates and custom tags and filters from multiple sources, providing greater flexibility for application needs.
The above is the detailed content of Template system in Django framework. For more information, please follow other related articles on the PHP Chinese website!
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
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1653
14
1413
52
1305
25
1251
29
1224
24
Python vs. C : Applications and Use Cases Compared
Apr 12, 2025 am 12:01 AM
Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.
How Much Python Can You Learn in 2 Hours?
Apr 09, 2025 pm 04:33 PM
You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.
Python: Games, GUIs, and More
Apr 13, 2025 am 12:14 AM
Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.
The 2-Hour Python Plan: A Realistic Approach
Apr 11, 2025 am 12:04 AM
You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.
Python vs. C : Learning Curves and Ease of Use
Apr 19, 2025 am 12:20 AM
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: Exploring Its Primary Applications
Apr 10, 2025 am 09:41 AM
Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.
Python and Time: Making the Most of Your Study Time
Apr 14, 2025 am 12:02 AM
To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.
Python: Automation, Scripting, and Task Management
Apr 16, 2025 am 12:14 AM
Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
