itemloaders
Base library for scrapy's ItemLoader
Decision gist · record as of 2026-08-14
Yes. Itemloaders is actively maintained, has no known vulnerabilities, requires only lightweight dependencies, and solves a real problem in web data extraction. It's production-stable and well-suited for any project that needs to extract and normalize data from HTML or XML at scale. Install it if you're doing web scraping or structured data collection.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Low friction: pure Python wheel with only three runtime dependencies (itemadapter, jmespath, parsel).
- Actively maintained with recent commits and production-stable status.
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause permissive license allows commercial and private use with minimal restrictions.
last release 2026-01-29 (197 days) · last repo commit 2026-08-12 · 49 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,903,410 downloads/mo, #2,828 on PyPI
Alternatives
Verify before relying
pip install itemloaders
from itemloaders import ItemLoader
from parsel import Selector
html = '<div class="name">Product</div><span id="price">$10</span>'
loader = ItemLoader(selector=Selector(html))
loader.add_css('name', '.name::text')
loader.add_css('price', '#price::text')
item = loader.load_item()
print(item) # {'name': ['Product'], 'price': ['$10']}- Whether the package handles malformed HTML gracefully or requires well-formed input
- Performance characteristics when processing large documents or high-volume extraction tasks
What it is and what it does
Itemloaders is a data extraction library that wraps HTML and XML parsing to collect fields from web pages using CSS and XPath selectors. It sits between raw HTML/XML and your application, providing a consistent interface for extracting multiple values per field, applying transformations, and normalizing data across different sources.
The library is designed for web scraping workflows where you need to extract the same logical fields from many different page structures. Instead of writing extraction logic inline, you define your selectors and parsing rules once in a loader, then apply it repeatedly. It handles multiple selector paths per field (useful when data appears in different locations), supports literal values, and returns results as lists by default to accommodate multi-valued fields.
Use it for
- Extract product names, prices, and descriptions from e-commerce pages using CSS/XPath rules
- Standardize contact information scraped from multiple website formats into consistent fields
- Collect article metadata (title, author, date, body) from news sites with varying HTML structures
- Parse structured data from XML feeds or APIs that return XML responses
- Build a data pipeline that applies the same extraction rules across hundreds of similar pages
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Itemloaders is actively maintained, has no known vulnerabilities, requires only lightweight dependencies, and solves a real problem in web data extraction. It's production-stable and well-suited for any project that needs to extract and normalize data from HTML or XML at scale. Install it if you're doing web scraping or structured data collection.
Install
itemloaders on PyPI
Before you install
Low friction: pure Python wheel with only three runtime dependencies (itemadapter, jmespath, parsel). Actively maintained with recent commits and production-stable status.
Requires Python 3.10 or later.
License in practice
BSD-3-Clause permissive license allows commercial and private use with minimal restrictions.
Quickstart
pip install itemloaders
from itemloaders import ItemLoader
from parsel import Selector
html = '<div class="name">Product</div><span id="price">$10</span>'
loader = ItemLoader(selector=Selector(html))
loader.add_css('name', '.name::text')
loader.add_css('price', '#price::text')
item = loader.load_item()
print(item) # {'name': ['Product'], 'price': ['$10']}Verify before relying
- Whether the package handles malformed HTML gracefully or requires well-formed input
- Performance characteristics when processing large documents or high-volume extraction tasks
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesitemadapterjmespathparsel |
| Maintenance | Actively maintained 197 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,903,410 / month, #2,828 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableFramework :: ScrapyIntended Audience :: DevelopersOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyTopic :: Internet :: WWW/HTTPTopic :: Software Development :: Libraries :: Python Modules |
Evidence: itemloaders-1.4.0-py3-none-any.whl
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See also itemadapter · parsel · requests-html · cssselect · elementpath · selectolax · cssselect2 · Scrapy · soupsieve · python-didl-lite