What it is

recipe-scrapers is an open-source Python package for extracting recipe data from cooking websites. It lives in the Python data-extraction ecosystem and focuses on HTML parsing rather than network access. The library reads recipe pages through a consistent API, so developers can obtain ingredients, instructions, cooking times, and other metadata without writing a separate parser for every site.

The concrete problem it solves is the variation in how recipe websites publish structured information. Some pages expose standard HTML, while others include Schema markup in JSON-LD, Microdata, or RDFa, or provide OpenGraph metadata. recipe-scrapers normalizes these sources into Python methods and JSON output. The package does not circumvent or bypass bot protection measures, and users must supply or fetch the HTML themselves.

Key capabilities

• It provides a consistent API for ingredients, instructions, cooking times, and other recipe metadata.
• It parses standard HTML structure, Schema markup including JSON-LD, Microdata, and RDFa, and OpenGraph metadata.
• It offers scrape_me for a recipe URL and scrape_html when the caller supplies the HTML content and source domain.
• It exposes fields such as title and instructions, and it returns complete data with to_json.
• It enables higher-quality image detection by default when multiple image options are present, with per-call or global settings to disable that behavior.
• It lists supported recipe websites programmatically through SCRAPERS.keys().
• It keeps scope to HTML parsing, leaving fetching, network management, and bot-protection handling to the user.

Who uses it and how

• Developers building food, meal, or nutrition datasets use it to normalize recipe content into Python objects or JSON records.
• Data pipelines fetch page HTML, pass it to scrape_html with the source domain, then call methods for required fields.
• Site-aware workflows use SCRAPERS.keys() to identify supported domains and select the appropriate parser.
• Applications needing recipe images rely on default image selection, or disable it to preserve the first site image.
• Contributors use the package as the parsing layer for recipe-site support, guided by documentation and the contribution guide.

Getting started

Install the package with pip install recipe-scrapers, then call scrape_me with a recipe URL or use scrape_html with supplied HTML and source domain.

When to use it — and when not to

Use recipe-scrapers when you need a Python parsing layer for recipe pages and can manage HTTP requests, site changes, and bot-protection rules yourself. It is not a complete scraping service, because it does not fetch pages or circumvent protections, so pipelines must add network handling around the parsers. Its usefulness depends on the maintained supported-site list, and open issues indicate ongoing site-specific parsing work.

pip install recipe-scrapers

from recipe_scrapers import scrape_me

scraper = scrape_me("https://www.allrecipes.com/recipe/158968/spinach-and-feta-turkey-burgers/")
scraper.title()
scraper.instructions()
scraper.to_json()
# for a complete list of methods:
# help(scraper)

from recipe_scrapers import scrape_html

scraper = scrape_html(html, url, best_image=False)
image_url = scraper.image()

from recipe_scrapers.settings import settings

settings.BEST_IMAGE_SELECTION = False

from recipe_scrapers import SCRAPERS

SCRAPERS.keys()