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Fast CSS inlining written in Rust

Project description

Build Version Python versions License

Fast CSS inlining for Python implemented in Rust.

Features:

  • Removing style tags after inlining;

  • Resolving external stylesheets (including local files);

  • Control if style tags should be processed;

  • Additional CSS to inline;

Installation

To install css_inline via pip run the following command:

pip install css_inline

Usage

To inline CSS in a HTML document:

import css_inline

HTML = """<html>
<head>
    <title>Test</title>
    <style>h1 { color:blue; }</style>
</head>
<body>
    <h1>Big Text</h1>
</body>
</html>"""

inlined = css_inline.inline(HTML)

If you want to inline many HTML documents, you can utilize inline_many that processes the input in parallel.

import css_inline

css_inline.inline_many(["...", "..."])

For customization options use CSSInliner class:

import css_inline

inliner = css_inline.CSSInliner(remove_style_tags=True)
inliner.inline("...")

Performance

Due to the usage of efficient tooling from Mozilla’s Servo project (html5ever, rust-cssparser and others) this library has good performance characteristics. In comparison with other Python projects, it is ~7-15x faster than the nearest competitor.

For inlining CSS in the html document from the Usage section above we have the following breakdown in our benchmarks:

  • css_inline 0.6.0 - 23.01 us

  • premailer 3.7.0 - 340.89 us (x14.81)

  • inlinestyler 0.2.4 - 2.44 ms (x106.35)

  • pynliner 0.8.0 - 2.78 ms (x121.04)

And for a more realistic email:

  • css_inline 0.6.0 - 483.3 us

  • premailer 3.7.0 - 3.38 ms (x7)

  • inlinestyler 0.2.4 - 64.41 ms (x133.28)

  • pynliner 0.8.0 - 93.11 ms (x192.65)

You can take a look at the benchmarks’ code at benches/bench.py file. The results above were measured with stable rustc 1.47.0, Python 3.8.6 on i8700K, and 32GB RAM.

Python support

css_inline supports Python 3.5, 3.6, 3.7, 3.8, and 3.9.

License

The code in this project is licensed under MIT license. By contributing to css_inline, you agree that your contributions will be licensed under its MIT license.

Project details


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