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A fast, fully typed HTML toolkit for Python, powered by a C-accelerated core.

Project description

turbohtml

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A fast, fully typed HTML toolkit for Python, powered by a C-accelerated core. turbohtml provides spec-correct HTML escaping and unescaping that match the standard library byte for byte, and a WHATWG-conformant streaming tokenizer — all several times faster than their pure-Python counterparts and ready for the free-threaded build.

Install

$ pip install turbohtml

Wheels are published per interpreter for CPython 3.10–3.15 (including free-threading), so there is nothing to compile.

Usage

Escape text before interpolating it into HTML so it cannot break out of its context:

>>> import turbohtml
>>> turbohtml.escape('<a href="?x=1&y=2">Tom & Jerry</a>')
'&lt;a href=&quot;?x=1&amp;y=2&quot;&gt;Tom &amp; Jerry&lt;/a&gt;'

Inside a text node the quotes are safe, so pass quote=False to keep the output smaller:

>>> turbohtml.escape('He said "hi" & left', quote=False)
'He said "hi" &amp; left'

Turn HTML character references back into text, following the full HTML5 rules (named, numeric, and longest-match references that omit the trailing semicolon):

>>> turbohtml.unescape("caf&eacute; &amp; r&eacute;sum&eacute; &#127881;")
'café & résumé 🎉'

escape and unescape reproduce html.escape and html.unescape exactly, so turbohtml is a drop-in replacement on hot paths.

Tokenize markup into a stream of tokens following the WHATWG tokenization algorithm:

>>> for token in turbohtml.tokenize('<p class="x">Tom &amp; Jerry</p>'):
...     print(token.type.name, token.tag or token.data, token.attrs)
START_TAG p [('class', 'x')]
TEXT Tom & Jerry None
END_TAG p []

For incremental input, Tokenizer.feed() returns the tokens completed by each chunk and close() flushes the rest:

>>> tokenizer = turbohtml.Tokenizer()
>>> [token.tag for token in tokenizer.feed("<div><sp")]
['div']
>>> [token.tag for token in tokenizer.feed("an>")]
['span']
>>> list(tokenizer.close())
[]

Performance

Measured with pyperf on CPython 3.14 (release build, Apple M-series) against the standard library's html.escape / html.unescape. The multi-MiB inputs stream well past the CPU caches; the book and spec cases are real documents (Project Gutenberg's War and Peace, the WHATWG HTML spec source) pulled in as git submodules. Reproduce with tox -e bench:

operation input turbohtml stdlib speedup
escape tiny plain (64 B) 0.04 µs 0.11 µs 2.9×
escape medium markup (4 KiB) 2.38 µs 8.09 µs 3.4×
escape no-op prose (4 MiB) 0.12 ms 2.66 ms 22.2×
escape book text (3 MiB) 0.72 ms 2.80 ms 3.9×
escape book HTML (4 MiB) 1.35 ms 4.88 ms 3.6×
escape spec HTML, dense (4 MiB) 5.27 ms 13.3 ms 2.5×
escape UCS-2 plain (4 MiB) 0.74 ms 2.60 ms 3.5×
escape UCS-2 markup (4 MiB) 3.44 ms 11.5 ms 3.3×
escape UCS-4 plain (4 MiB) 0.97 ms 5.58 ms 5.8×
escape UCS-4 markup (4 MiB) 4.08 ms 20.3 ms 5.0×
unescape tiny plain (64 B) 0.02 µs 0.03 µs 1.3×
unescape medium dense refs (4 KiB) 8.57 µs 72.5 µs 8.5×
unescape numeric refs (4 KiB) 5.24 µs 81.1 µs 15.5×
unescape book HTML, real refs (4 MiB) 2.80 ms 8.96 ms 3.2×
unescape escaped book HTML (5 MiB) 2.10 ms 21.2 ms 10.1×
unescape dense refs (4 MiB) 10.4 ms 78.5 ms 7.6×
unescape UCS-2 refs (4 MiB) 2.78 ms 19.4 ms 7.0×

escape gains the most on text that needs little escaping — the SIMD scan classifies sixteen bytes at a time and copies clean stretches wholesale — and unescape gains the most on entity-heavy input, where the standard library pays a Python function call per match. The gap is narrowest on tiny strings, where call overhead dominates, and on special-dense markup, where both sides spend their time writing replacements. Numbers vary with input and hardware; reproduce them with tox -e bench.

tokenize is compared against the standard library's html.parser.HTMLParser (driven with no-op handlers) and html5lib's pure-Python tokenizer, over synthetic cases, html5lib's benchmark corpus of real documents (a slice of the WHATWG spec source plus web-platform-tests pages of varied sizes), and two multi-megabyte specifications:

input turbohtml html.parser speedup html5lib speedup
typical markup 30.3 µs 449 µs 14.8× 840 µs 28×
text-heavy prose 0.55 µs 2.9 µs 5.3× 149 µs 273×
attribute-heavy 24.7 µs 330 µs 13.3× 837 µs 34×
script-heavy 13.0 µs 162 µs 12.5× 526 µs 41×
entity-heavy 22.3 µs 205 µs 9.2× 1246 µs 56×
wpt page (0.6 kB) 1.6 µs 18.2 µs 11.4× 49 µs 31×
wpt page (4 kB) 15.0 µs 176 µs 11.8× 434 µs 29×
wpt page (9.6 kB) 34.9 µs 376 µs 10.8× 1190 µs 34×
wpt page (92 kB) 348 µs 4250 µs 12.2× 9311 µs 27×
wpt page, CJK (124 kB) 626 µs 8926 µs 14.3× 22844 µs 37×
whatwg spec (235 kB) 701 µs 7838 µs 11.2× 20409 µs 29×
ecmascript spec (3 MB) 7.08 ms 57.9 ms 8.2× 192 ms 27×
whatwg spec source (7.9 MB) 37.0 ms 399 ms 10.8× 907 ms 25×

The state machine is stamped per input storage width (the CPython stringlib trick) and, like html5ever, bulk-scans plain text runs instead of dispatching per character, so ASCII documents stay one byte per character end to end. Run scanning uses the same SWAR technique as escape, so even a document that is almost entirely one text node — HTMLParser's best case, a single C regex scan — comes out ahead.

Documentation

Full documentation, including tutorials, how-to guides, the API reference, and the design rationale, lives at turbohtml.readthedocs.io.

License

turbohtml is released under the MIT license.

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Publisher: release.yaml on tox-dev/turbohtml

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