fast-scrape
8x faster HTML parsing than BeautifulSoup4. Rust-powered with 3000x faster CSS selector queries.
Installation
pip install fast-scrape
Alternative package managers
# uv (recommended - 10-100x faster)
uv pip install fast-scrape
# Poetry
poetry add fast-scrape
# Pipenv
pipenv install fast-scrape
Quick start
from scrape_rs import Soup
soup = Soup("<html><body><div class='content'>Hello, World!</div></body></html>")
div = soup.find("div")
print(div.text) # Hello, World!
Usage
Find elements
from scrape_rs import Soup
soup = Soup(html)
# Find first element by tag
div = soup.find("div")
# Find all elements
divs = soup.find_all("div")
# CSS selectors
for el in soup.select("div.content > p"):
print(el.text)
Element properties
element = soup.find("a")
text = element.text # Get text content
html = element.inner_html # Get inner HTML
href = element.get("href") # Get attribute
Batch processing
from scrape_rs import parse_batch
# Process multiple documents in parallel
documents = [html1, html2, html3]
soups = parse_batch(documents)
for soup in soups:
print(soup.find("title").text)
Type hints
Full IDE support with type stubs:
from scrape_rs import Soup, Tag
def extract_links(soup: Soup) -> list[str]:
return [a.get("href") for a in soup.select("a[href]")]
Performance
Massive performance improvements across all operations:
Parse speed comparison
| File size | fast-scrape | BeautifulSoup4 | lxml | Speedup |
|---|---|---|---|---|
| 1 KB | 11 µs | 0.23 ms | 0.31 ms | 20-28x faster |
| 100 KB | 2.96 ms | 31.4 ms | 28.2 ms | 9.5-10.6x faster |
| 1 MB | 15.5 ms | 1247 ms | 1032 ms | 66-80x faster |
Throughput: 64 MB/s on 1MB files — handles large documents efficiently.
Query performance
| Operation | fast-scrape | BeautifulSoup4 | Speedup |
|---|---|---|---|
find("div") |
208 ns | 16 µs | 77x |
find(".class") |
20 ns | 797 µs | 40,000x |
find("#id") |
20 ns | 799 µs | 40,000x |
select("div > p") |
24.7 µs | 4.361 ms | 176x |
CSS selectors dominate: Class and ID selectors run in nanoseconds vs microseconds.
Memory efficiency (100MB HTML)
| Library | Memory | Efficiency |
|---|---|---|
| fast-scrape | 145 MB | 1x baseline |
| lxml | 2,100 MB | 14.5x larger |
| BeautifulSoup4 | 3,200 MB | 22x larger |
Result: 14-22x more memory-efficient than Python competitors.
Architecture optimizations:
- SIMD-accelerated class matching — 2-10x faster selector execution
- Zero-copy serialization — 50-70% memory reduction in HTML output
- Batch processing — Parallel parsing uses all CPU cores automatically
Parsing & Selection (Servo browser engine):
Streaming Parser (Cloudflare):
- lol_html — High-performance streaming HTML parser with constant-memory event-driven API
Related packages
| Platform | Package |
|---|---|
| Rust | scrape-core |
| Node.js | @fast-scrape/node |
| WASM | @fast-scrape/wasm |
License
MIT OR Apache-2.0
1 maintainer
Metadata
1 maintainer
Release files for fast-scrape 0.2.13
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fast_scrape-0.2.13.tar.gz | 130.4 kB | Details |
Built distributions (wheels)
Total release size: 17.4 MB
Release files / fast_scrape-0.2.13.tar.gz
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| Size | 130.4 kB |
| Tags | Source |
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