Fast CSS inlining written in Rust

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Project description

css_inline

Blazing-fast CSS inlining for Python implemented with Mozilla's Servo project components.

Features:

Removing style tags after inlining;
Resolving external stylesheets (including local files);
Control if style tags should be processed;
Out-of-document CSS to inline;
Inlining multiple documents in parallel (via Rust-level threads)

The project supports CSS Syntax Level 3.

Installation

To install css_inline via pip run the following command:

pip install css_inline

Pre-compiled wheels for most popular platforms are provided. If your platform is not in the support table below, you will need a Rust compiler to build this package from source. The minimum supported Rust version is 1.54.

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)
# HTML becomes this:
#
# <html>
# <head>
#    <title>Test</title>
#    <style>h1 { color:blue; }</style>
# </head>
# <body>
#     <h1 style="color:blue;">Big Text</h1>
# </body>
# </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(["<...>", "<...>"])

inline_many will use Rust-level threads; thus, you can expect it's running faster than css_inline.inline via Python's multiprocessing or threading modules.

For customization options use the 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 excellent performance characteristics. In comparison with other Python projects, it is ~7-15x faster than the nearest alternative.

For inlining CSS in the html document from the Usage section above there is the following breakdown in the benchmarks:

css_inline 0.8.2 - 21.75 us
premailer 3.10.0 - 329.51 us (x15.14)
toronado 0.1.0 - 1.59 ms (x73.28)
inlinestyler 0.2.5 - 2.37 ms (x109.27)
pynliner 0.8.0 - 2.78 ms (x127.89)

And for a more realistic email:

css_inline 0.8.2 - 443.83 us
premailer 3.10.0 - 3.25 ms (x7.33)
toronado 0.1.0 - 35.35 ms (x79.65)
inlinestyler 0.2.5 - 61.08 ms (x137.62)
pynliner 0.8.0 - 99.52 ms (x224.24)

You can take a look at the benchmarks' code at benches/bench.py file. The results above were measured with stable rustc 1.61.0, Python 3.10.4, Linux x86_64 on i8700K, and 32GB RAM.

Python support

css_inline supports CPython 3.7, 3.8, 3.9, 3.10, and PyPy 3.7 and 3.8.

The following wheels are available:

	manylinux musllinux x86_64	macOS Intel	macOS ARM64	Windows 64bit	Windows 32bit
CPython 3.7	✔	✔️	✔	✔️	✔️
CPython 3.8	✔	✔️	✔️	✔️	✔️
CPython 3.9	✔	✔️	✔️	✔️	✔️
CPython 3.10	✔	✔️	✔️	✔️	✔️
PyPy 3.7 v7.3	✔¹	✔️	N/A	✔️	N/A
PyPy 3.8 v7.3	✔¹	✔️	N/A	✔️	N/A

^{¹ PyPy is only supported for manylinux wheels.}

Extra materials

If you want to know how this library was created & how it works internally, you could take a look at these articles:

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

These details have not been verified by PyPI

Project links

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Release history Release notifications | RSS feed

0.20.0

Feb 7, 2026

0.19.1

Jan 23, 2026

0.19.0

Dec 29, 2025

0.18.0

Nov 1, 2025

0.17.0

Jul 26, 2025

0.16.0

Jul 16, 2025

0.15.0

Jun 17, 2025

0.14.6

Dec 27, 2024

0.14.5

Dec 27, 2024

0.14.3

Nov 14, 2024

0.14.2

Nov 11, 2024

0.14.1

Apr 27, 2024

0.14.0

Apr 1, 2024

0.13.0

Jan 19, 2024

0.12.0

Dec 28, 2023

0.11.2

Dec 9, 2023

0.11.1

Dec 9, 2023

0.11.0

Sep 26, 2023

0.10.5

Aug 30, 2023

0.10.4

Aug 11, 2023

0.10.3

Jul 1, 2023

0.10.2

Jun 25, 2023

0.10.1

Jun 18, 2023

0.10.0

Jun 16, 2023

0.9.0 yanked

Jun 10, 2023

Reason this release was yanked:

security vulnerability in HTML serialization

0.8.7

Jan 30, 2023

0.8.6

Nov 10, 2022

0.8.5

Nov 2, 2022

This version

0.8.4

Oct 21, 2022

0.8.3

Jul 21, 2022

0.8.2

Apr 1, 2022

0.8.1

Jan 11, 2022

0.8.0

Jan 10, 2022

0.7.8

Jan 8, 2022

0.7.7

Jan 7, 2022

0.7.6

Aug 6, 2021

0.7.5

Jul 24, 2021

0.7.4

Jul 6, 2021

0.7.3

Jun 24, 2021

0.7.2

Jun 22, 2021

0.7.1

Jun 10, 2021

0.7.0

Jun 9, 2021

0.6.2

Jan 28, 2021

0.6.1

Dec 7, 2020

0.6.0

Nov 2, 2020

0.5.0

Aug 7, 2020

0.4.0

Jul 13, 2020

0.3.2

Jul 9, 2020

0.3.1

Jul 7, 2020

0.3.0

Jun 27, 2020

0.2.0

Jun 25, 2020

0.1.0

Jun 24, 2020

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css-inline 0.8.4

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Algorithm	Hash digest
SHA256	`a85ac91cd2ec49f53ae7dd9bda458b0de66fc530a6fc92dd4d23102d3d993b93`
MD5	`33cf5619f690bf30ad00a5d7046eb4ec`
BLAKE2b-256	`35ac8d081c15d0e473f8a31405fbfd48bdc276337e80c0d003a40ea0f61d039a`

Algorithm	Hash digest
SHA256	`204819378218e5d790f720e2576d17c7e0ba02cf06b26f4aa3fc0ddc3ed738f6`
MD5	`f9b3e47d0c80c91d4a3ccdb81119e067`
BLAKE2b-256	`7bfe3172beff7b7a224ca680175d2747d77bec9a72dbf7554d1cce91365d9cb8`

Algorithm	Hash digest
SHA256	`d27bcf486703f647b3754dfcbeca829246f8290a5be1713a4ae69128ca8513c1`
MD5	`37b4ae139852e4da645287a125a34dcf`
BLAKE2b-256	`9d618f02a095f9ce171940b14a76a59d4d5f26a1075778a0adcdc2035e29bbce`

Algorithm	Hash digest
SHA256	`278cfe84d56ad21aa07c8f25c24141ac1a0e9c72f08d8f73a9b82ff5c32795a7`
MD5	`b288919f3df7c750ba6db8d20b967424`
BLAKE2b-256	`dac324bbc931af55458c0e50365fb0b559b24b06e09f9e433be20a956660aaff`

Algorithm	Hash digest
SHA256	`64bd985c1680b6f5da38a729d8c72bc92bea8852ab4f8f04496f4ab418f44b7a`
MD5	`d3ca42b0a9450aeb6c86459ff691d74c`
BLAKE2b-256	`94013b90797a63ad465897fa1d0cbc3b87e05c7dc95de41b9bfad6a6c58f11a6`

Algorithm	Hash digest
SHA256	`f05fb24b108c5d74345f22f814f5b6360663b68aa699c5c1eb615261fc57f9c2`
MD5	`a12ffe9710f165db0b3209a0791fe48f`
BLAKE2b-256	`ef012530131606c12f496d4a0173246294054b08fb1bfec83854e1a8371e6fac`

Algorithm	Hash digest
SHA256	`f4955e1bc5f26403e5bd85219a58a959461e93866b91a31f26cc7a08595f43dd`
MD5	`b362c421bae7fcb6101616f29ba1be2f`
BLAKE2b-256	`8cb5a72caaec1d69dfe09de43a17d175089a0d207845f823fb9428240b64d783`

Algorithm	Hash digest
SHA256	`383d0d907ad53ae0aa4589a4a89e5fd11d6cbc9a4cb6eb4ea7a72940383079c9`
MD5	`6f593338014d4c9bd655a7e4a377937a`
BLAKE2b-256	`ea5eed93bf5a95c184daadefd34fd236bf85bb062239ed40df1c6c5992c927aa`