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Quick Overview
Django Pipeline is a web development framework for Django that provides a set of tools for managing and optimizing static assets, such as CSS, JavaScript, and images. It aims to simplify the process of bundling, compressing, and caching these assets, improving the performance and efficiency of web applications.
Pros
- Asset Optimization: Django Pipeline offers a range of optimization features, including CSS and JavaScript minification, image optimization, and cache busting, which can significantly improve the loading speed of web pages.
- Flexibility: The framework supports a variety of asset types, including CSS, JavaScript, images, and fonts, and can be easily integrated with various asset compilers and preprocessors, such as Sass, Less, and CoffeeScript.
- Caching and Versioning: Django Pipeline provides built-in support for caching and versioning of assets, which can help reduce the number of HTTP requests and improve the overall user experience.
- Modular Design: The framework is designed to be modular, allowing developers to easily customize and extend its functionality to meet their specific needs.
Cons
- Complexity: While Django Pipeline offers a lot of features, the setup and configuration process can be somewhat complex, especially for developers who are new to the framework.
- Dependency Management: The framework relies on several external libraries and tools, which can make it more challenging to manage dependencies and ensure compatibility across different environments.
- Limited Documentation: The project's documentation, while generally good, could be more comprehensive and provide more detailed examples and use cases.
- Maintenance: As with any open-source project, the long-term maintenance and support of Django Pipeline may be a concern, especially if the project's development activity slows down.
Code Examples
Configuring Django Pipeline
# settings.py
PIPELINE = {
'STYLESHEETS': {
'main': {
'source_filenames': (
'css/bootstrap.css',
'css/app.css',
),
'output_filename': 'css/main.css',
}
},
'JAVASCRIPT': {
'main': {
'source_filenames': (
'js/jquery.js',
'js/bootstrap.js',
'js/app.js',
),
'output_filename': 'js/main.js',
}
}
}
Using Django Pipeline in Templates
{% load pipeline %}
<link href="{% stylesheet 'main' %}" rel="stylesheet" type="text/css" />
<script src="{% javascript 'main' %}"></script>
Compiling Assets with Django Pipeline
python manage.py pipeline_compile
Getting Started
To get started with Django Pipeline, follow these steps:
-
Install the package using pip:
pip install django-pipeline
-
Add
'pipeline'
to yourINSTALLED_APPS
in your Django project'ssettings.py
file:INSTALLED_APPS = [ # ... 'pipeline', ]
-
Configure your static asset bundles in the
PIPELINE
setting insettings.py
. For example:PIPELINE = { 'STYLESHEETS': { 'main': { 'source_filenames': ( 'css/bootstrap.css', 'css/app.css', ), 'output_filename': 'css/main.css', } }, 'JAVASCRIPT': { 'main': { 'source_filenames': ( 'js/jquery.js', 'js/bootstrap.js', 'js/app.js', ), 'output_filename': 'js/main.js', } } }
-
Load the Django Pipeline templates tags in your HTML templates and use them to reference your asset bundles:
{% load pipeline %} <link href="{% stylesheet 'main' %}" rel="stylesheet" type="text/css" /> <script src="{% javascript 'main' %}"></script>
-
Compile your assets using the Django management command:
Competitor Comparisons
Compresses linked and inline javascript or CSS into a single cached file.
Pros of django-compressor/django-compressor
- Flexibility: django-compressor offers more flexibility in terms of supported file types and compression methods, allowing you to customize the build process to your specific needs.
- Caching: django-compressor provides efficient caching mechanisms to improve performance by reducing the number of file compilations.
- Integration: django-compressor integrates well with popular front-end frameworks like Bootstrap and Foundation, making it easier to manage your project's assets.
Cons of django-compressor/django-compressor
- Complexity: django-compressor can be more complex to set up and configure compared to django-pipeline, especially for projects with more complex asset management requirements.
- Dependency Management: django-compressor may have more dependencies and external libraries to manage, which can increase the overall complexity of your project.
Code Comparison
django-pipeline:
PIPELINE = {
'STYLESHEETS': {
'main': {
'source_filenames': (
'css/bootstrap.css',
'css/style.css',
),
'output_filename': 'css/main.css',
}
},
'JAVASCRIPT': {
'main': {
'source_filenames': (
'js/jquery.js',
'js/bootstrap.js',
'js/script.js',
),
'output_filename': 'js/main.js',
}
}
}
django-compressor:
COMPRESS_PRECOMPILERS = (
('text/x-scss', 'django_libsass.SassCompiler'),
('text/stylus', 'compressor.filters.stylus.StylusCompiler'),
('text/less', 'compressor.filters.less.LessCompiler'),
)
COMPRESS_CSS_FILTERS = [
'compressor.filters.css_default.CssAbsoluteFilter',
'compressor.filters.cssmin.CSSMinFilter',
]
COMPRESS_JS_FILTERS = [
'compressor.filters.jsmin.JSMinFilter',
]
Transparently use webpack with django
Pros of django-webpack/django-webpack-loader
- Webpack Integration: django-webpack-loader seamlessly integrates Webpack into the Django development and deployment workflow, making it easier to manage and optimize front-end assets.
- Automatic Asset Handling: The loader automatically handles the inclusion of Webpack-generated assets in your Django templates, reducing boilerplate code.
- Flexible Configuration: The loader provides a flexible configuration system, allowing you to customize the Webpack setup to fit your project's needs.
Cons of django-webpack/django-webpack-loader
- Complexity: Integrating Webpack into a Django project can add a layer of complexity, especially for developers unfamiliar with Webpack.
- Dependency Management: Keeping the Webpack and Django dependencies in sync can be challenging, especially when upgrading to newer versions.
- Learning Curve: Developers may need to invest time in learning Webpack and its integration with Django, which can be a barrier for some teams.
Code Comparison
django-pipeline:
PIPELINE = {
'STYLESHEETS': {
'styles': {
'source_filenames': (
'css/bootstrap.css',
'css/app.css',
),
'output_filename': 'css/styles.css',
}
},
'JAVASCRIPT': {
'scripts': {
'source_filenames': (
'js/jquery.js',
'js/bootstrap.js',
'js/app.js',
),
'output_filename': 'js/scripts.js',
}
}
}
django-webpack-loader:
WEBPACK_LOADER = {
'DEFAULT': {
'BUNDLE_DIR_NAME': 'bundles/',
'STATS_FILE': os.path.join(BASE_DIR, 'webpack-stats.json'),
}
}
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Pipeline
.. image:: https://jazzband.co/static/img/badge.svg :alt: Jazzband :target: https://jazzband.co/
.. image:: https://github.com/jazzband/django-pipeline/workflows/Test/badge.svg :target: https://github.com/jazzband/django-pipeline/actions :alt: GitHub Actions
.. image:: https://codecov.io/gh/jazzband/django-pipeline/branch/master/graph/badge.svg :target: https://codecov.io/gh/jazzband/django-pipeline :alt: Coverage
.. image:: https://readthedocs.org/projects/django-pipeline/badge/?version=latest :alt: Documentation Status :target: https://django-pipeline.readthedocs.io/en/latest/?badge=latest
Pipeline is an asset packaging library for Django, providing both CSS and JavaScript concatenation and compression, built-in JavaScript template support, and optional data-URI image and font embedding.
.. image:: https://github.com/jazzband/django-pipeline/raw/master/img/django-pipeline.svg :alt: Django Pipeline Overview
Installation
To install it, simply:
.. code-block:: bash
pip install django-pipeline
Quickstart
Pipeline compiles and compress your assets files from
STATICFILES_DIRS
to your STATIC_ROOT
when you run Django's
collectstatic
command.
These simple steps add Pipeline to your project to compile multiple .js
and
.css
file into one and compress them.
Add Pipeline to your installed apps:
.. code-block:: python
# settings.py
INSTALLED_APPS = [
...
'pipeline',
]
Use Pipeline specified classes for STATICFILES_FINDERS
and STATICFILES_STORAGE
:
.. code-block:: python
STATICFILES_STORAGE = 'pipeline.storage.PipelineManifestStorage'
STATICFILES_FINDERS = (
'django.contrib.staticfiles.finders.FileSystemFinder',
'django.contrib.staticfiles.finders.AppDirectoriesFinder',
'pipeline.finders.PipelineFinder',
)
Configure Pipeline:
.. code-block:: python
# The folowing config merges CSS files(main.css, normalize.css)
# and JavaScript files(app.js, script.js) and compress them using
# `yuglify` into `css/styles.css` and `js/main.js`
# NOTE: Pipeline only works when DEBUG is False
PIPELINE = {
'STYLESHEETS': {
'css_files': {
'source_filenames': (
'css/main.css',
'css/normalize.css',
),
'output_filename': 'css/styles.css',
'extra_context': {
'media': 'screen,projection',
},
},
},
'JAVASCRIPT': {
'js_files': {
'source_filenames': (
'js/app.js',
'js/script.js',
),
'output_filename': 'js/main.js',
}
}
}
Then, you have to install compilers and compressors binary manually.
For example, you can install them using NPM <https://www.npmjs.com/>
_
and address them from node_modules
directory in your project path:
.. code-block:: python
PIPELINE.update({
'YUGLIFY_BINARY': path.join(BASE_DIR, 'node_modules/.bin/yuglify'),
})
# For a list of all supported compilers and compressors see documentation
Load static files in your template:
.. code-block::
{% load pipeline %}
{% stylesheet 'css_files' %}
{% javascript 'js_files' %}
Documentation
For documentation, usage, and examples, see: https://django-pipeline.readthedocs.io
Issues
You can report bugs and discuss features on the issues page <https://github.com/jazzband/django-pipeline/issues>
_.
Changelog
See HISTORY.rst <https://github.com/jazzband/django-pipeline/blob/master/HISTORY.rst>
_.
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Convert designs to code with AI
Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.
Try Visual Copilot