polars-tldextract 0.2.1

Vectorized, tldextract-compatible URL domain parsing for Polars.

polars-tldextract

Accurate URL domain parsing for Polars, as a native Rust expression plugin.

Splitting a hostname into subdomain / domain / public suffix is not a string operation. www.bbc.co.uk and blog.cloudflare.com look identical to a regex, but the registrable domain is bbc.co.uk in one and cloudflare.com in the other — "last two labels" is wrong half the time. Getting it right requires the Public Suffix List, and in Python that means tldextract — an excellent library, but a Python function. Inside Polars it can only be driven through Expr.map_elements, one interpreter round-trip per row.

This package implements the same algorithm in Rust and exposes it as ordinary Polars expressions. It is built to produce identical output to tldextract, not merely similar output — see Correctness.

import polars as pl
import polars_tldextract as tld

df = pl.DataFrame({
    "url": [
        "https://www.bbc.co.uk/news/technology",
        "github.com",
        "https://blog.cloudflare.com:443/page/2/",
        "127.0.0.1",
        None,
    ]
})

df.with_columns(
    tld.fqdn("url").alias("fqdn"),
    tld.registrable_domain("url").alias("registrable_domain"),
    tld.suffix("url").alias("suffix"),
)

┌─────────────────────────────────────────┬─────────────────────┬────────────────────┬────────┐
│ url                                     ┆ fqdn                ┆ registrable_domain ┆ suffix │
╞═════════════════════════════════════════╪═════════════════════╪════════════════════╪════════╡
│ https://www.bbc.co.uk/news/technology   ┆ www.bbc.co.uk       ┆ bbc.co.uk          ┆ co.uk  │
│ github.com                              ┆ github.com          ┆ github.com         ┆ com    │
│ https://blog.cloudflare.com:443/page/2/ ┆ blog.cloudflare.com ┆ cloudflare.com     ┆ com    │
│ 127.0.0.1                               ┆ 127.0.0.1           ┆ null               ┆ null   │
│ null                                    ┆ null                ┆ null               ┆ null   │
└─────────────────────────────────────────┴─────────────────────┴────────────────────┴────────┘

Install

pip install polars-tldextract
# or
uv add polars-tldextract

Prebuilt wheels cover Linux (glibc and musl, x86_64 and aarch64), macOS (Intel and Apple Silicon), and Windows (x64 and arm64). There is one wheel per platform rather than one per Python version, because the extension is built against the stable ABI. An sdist is published too, so anything else builds from source given a Rust toolchain — see CONTRIBUTING.md.

Usage

Six expressions, all taking a string column of URLs or bare hostnames:

	https://www.bbc.co.uk/news
tld.extract	{"www", "bbc", "co.uk", false}	struct: subdomain, domain, suffix, is_private
tld.fqdn	www.bbc.co.uk	the whole hostname
tld.registrable_domain	bbc.co.uk	what you register — domain.suffix
tld.subdomain	www
tld.domain	bbc	the registrable label, tldextract's domain field
tld.suffix	co.uk	the public suffix

Nulls, and the one exception

The five single-value expressions return null for a part that does not exist. That matters in a DataFrame: an empty string is a value, so two rows that both failed to parse would compare equal and join to each other.

tld.extract is the exception, and deliberately so — it reproduces tldextract.ExtractResult verbatim, empty strings and all. Reach for it when porting existing tldextract code and you want the behavior unchanged; reach for anything else when the result is going into a join, a group-by, or a comparison.

fqdn vs. registrable_domain

The two differ on hosts that have no registrable domain. registrable_domain is strict — no recognized suffix means null, so an IP or a .local name drops out. fqdn just gives you the hostname:

tld.fqdn("url")  # "127.0.0.1", "localhost", "printer.local"
tld.registrable_domain("url")  # null,        null,        null

fqdn is also the normalized netloc — scheme, userinfo, port, path, query and fragment stripped, trailing root labels dropped, and the non-ASCII IDNA separators folded to . — so ftp://user:[e-mail]:2121/pub becomes ftp.gnu.org. Casing and punycode spelling are preserved, exactly like tldextract.

Expression namespace

Importing the package registers a .tld namespace:

df.with_columns(pl.col("url").tld.registrable_domain())
df.filter(pl.col("url").tld.suffix() == "org")

Scalars

For code that isn't holding a DataFrame — the same Rust core, no Polars round-trip:

tld.extract_scalar("https://www.bbc.co.uk/news")
# ('bbc.co.uk', 'bbc', 'co.uk')         (registrable_domain, domain, suffix), nulls for absences

tld.extract_scalar_full("https://www.bbc.co.uk/news")
# ('www', 'bbc', 'co.uk', False)        (subdomain, domain, suffix, is_private), tldextract-faithful

Private suffixes

The Public Suffix List has an ICANN section and a private section. Like tldextract, the private section is off by default:

tld.extract_scalar("pola-rs.github.io")
# ('github.io', 'github', 'io')

tld.extract_scalar("pola-rs.github.io", include_private=True)
# ('pola-rs.github.io', 'pola-rs', 'github.io')

Every expression takes the same include_private keyword.

Performance

200,000 URLs, measured with just bench:

	throughput	vs. map_elements
tldextract via Expr.map_elements	94k rows/s	—
polars_tldextract, parallel=False	2.05M rows/s	21.7×
polars_tldextract, parallel=True	21.9M rows/s	232.8×

_{AMD Ryzen 9 3950X (16 cores / 32 threads), 32 GB RAM, Linux 6.18 (WSL2), Python 3.12.13, Polars 1.43.}

Measure a release build. just bench builds one; a plain maturin develop is unoptimized and roughly 15× slower on this workload, which measures the profile rather than the code.

Columns of 100k rows or more are split across rayon threads; pass parallel=False to force single-threaded. The threshold sits above the streaming engine's morsel size, so when Polars is already calling the plugin from several of its own worker threads each call stays single-threaded rather than nesting a fan-out inside it.

The parallel figure scales with core count — 233× reflects 32 threads, and a 4-core laptop will land far below it. It is also by far the noisiest of the three, swinging ~20% run to run with thread scheduling while the single-threaded number holds within a couple of percent. The single-threaded number is the one to reason about when Polars is already saturating your cores.

A caveat worth stating plainly: if your column has far fewer distinct URLs than rows, a dict built over Series.unique() plus replace_strict can still beat any per-row approach, including this one. This package wins on columns with high cardinality, and on code you would rather not write.

Correctness

The point of this package is not "fast domain parsing" — it is "fast domain parsing you can swap in without your results moving". tests/test_parity.py asserts (subdomain, domain, suffix) equals tldextract's answer, for both settings of include_private, over four corpora:

1. Hand-written edge cases: schemes, userinfo, ports, IPv4, bracketed IPv6, trailing root labels, the three non-ASCII IDNA dot characters, IDN in Unicode and punycode spellings, mixed case, and degenerate input.
2. Every rule in the Public Suffix List — each of ~9,750 rules turned into three concrete hosts, ~29,000 cases. Wildcard rules (*.ck) get a concrete label and exception rules (!www.ck) have their marker stripped so the exception path is genuinely taken. This is the check that catches divergence no hand-written suite would find.
3. 200,000 randomly assembled URLs.
4. A fixture set drawn from a production pipeline.

Both sides are pointed at the same list file, so a disagreement can only be an algorithm difference — never two different snapshots.

If you find an input where this package and tldextract disagree, that is a bug here. Please open an issue with the input.

The suffix list

A snapshot of the Public Suffix List is compiled into the binary, so there is no network access, no cache directory, and no first-call latency spike. tld.psl_version() reports which snapshot is in use.

To supply your own list at startup, point POLARS_TLDEXTRACT_PSL at a .dat file:

export POLARS_TLDEXTRACT_PSL=/path/to/public_suffix_list.dat

It is read once, on first use, so set it before the first extraction.

Refreshing without a restart

The list changes several times a week. A long-lived process — a notebook, a cluster, a service — would otherwise be stuck with whatever list it read when it parsed its first URL, so two functions replace it in place:

# Download the current list and load it into this process.
tld.refresh_psl()

# ...and keep a copy, so the next run need not go back to the network.
tld.refresh_psl(save_to="psl.dat")

# Or load one you already have: a path, a Path, or the list text itself.
tld.load_psl("psl.dat")

Both return the new VERSION: stamp, and take effect for every extraction that starts after they return. A query already in flight keeps the list it began with, so no single column is ever parsed against two different lists.

refresh_psl is the only function here that touches the network, and only when you call it — importing the package still does nothing. Point it at an internal mirror with tld.refresh_psl(url=...) if outbound access is restricted.

An unreadable file, an unparseable list, or one missing the ===BEGIN ICANN DOMAINS=== / ===BEGIN PRIVATE DOMAINS=== markers raises ValueError and leaves the working list untouched. The marker check matters more than it looks: a list without them parses as one undifferentiated section, and every private suffix would quietly start counting as an ICANN one — wrong output, no signal.

Compatibility

Python	3.10+ — one abi3 wheel covers all versions
Polars	1.37+ — the plugin FFI ABI is (0, 1) and unchanged across that range
Linux	manylinux2014 and musllinux_1_2, x86_64 and aarch64
macOS	x86_64 (10.12+) and arm64 (11.0+)
Windows	x64 and arm64

If a future Polars release bumps the plugin ABI, this package fails loudly at load rather than miscomputing.

Contributing

Contributions are welcome — see CONTRIBUTING.md for the development loop, the parity requirement, and how to refresh the suffix list. docs/architecture/overview.md explains how this implementation maps onto tldextract's, which is worth reading before changing the algorithm.

License

Licensed under either of Apache License, Version 2.0 or MIT license at your option.

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this work, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

Two third-party works are included or drawn upon and keep their own terms — the Public Suffix List (MPL-2.0) and the tldextract algorithm (BSD-3-Clause). See NOTICE.