Firecrawl Python SDK
The Firecrawl Python SDK is a library that lets you easily search, scrape, and interact with the web for AI agents — returning clean Markdown or structured data your agents can ship with. It provides a simple and intuitive interface for the Firecrawl API.
Installation
To install the Firecrawl Python SDK, you can use pip:
pip install firecrawl-py
Usage
- Get an API key from firecrawl.dev
- Set the API key as an environment variable named
FIRECRAWL_API_KEYor pass it as a parameter to theFirecrawlclass.
Here's an example of how to use the SDK:
from firecrawl import Firecrawl
from firecrawl.types import ScrapeOptions
firecrawl = Firecrawl(api_key="fc-YOUR_API_KEY")
# Scrape a website (v2):
data = firecrawl.scrape(
'https://firecrawl.dev',
formats=['markdown', 'html']
)
print(data)
# Crawl a website (v2 waiter):
crawl_status = firecrawl.crawl(
'https://firecrawl.dev',
limit=100,
scrape_options=ScrapeOptions(formats=['markdown', 'html'])
)
print(crawl_status)
Scraping a URL
To scrape a single URL, use the scrape method. It takes the URL as a parameter and returns a document with the requested formats.
# Scrape a website (v2):
scrape_result = firecrawl.scrape('https://firecrawl.dev', formats=['markdown', 'html'])
print(scrape_result)
Video extraction
Use the video format on supported video URLs, including YouTube and TikTok. The returned video field is a signed URL to the extracted video file.
doc = firecrawl.scrape('https://www.youtube.com/watch?v=dQw4w9WgXcQ', formats=['video'])
print(doc.video)
Product extraction
Use the product format on product pages to deterministically pull structured product data (title, price, availability, variants). It is the deterministic counterpart to the LLM-based json format.
doc = firecrawl.scrape('https://firecrawl.dev', formats=['product'])
print(doc.product)
Menu extraction
Use the menu format on menu pages to deterministically pull structured menu data (merchant, sections, items, prices, availability). It is the deterministic counterpart to the LLM-based json format.
doc = firecrawl.scrape('https://example.com/restaurant/menu', formats=['menu'])
print(doc.menu)
Parsing uploaded files
Use parse to upload local bytes/files (html, pdf, docx, etc.) as multipart form data and return the parsed document.
parse does not support change tracking or browser-only options (actions, wait_for, location, mobile, screenshot, branding, audio, video).
from firecrawl import Firecrawl
from firecrawl.v2.types import ParseOptions
firecrawl = Firecrawl(api_key="fc-YOUR_API_KEY")
doc = firecrawl.parse(
b"<!DOCTYPE html><html><body><h1>Python Parse</h1></body></html>",
filename="upload.html",
content_type="text/html",
options=ParseOptions(formats=["markdown"]),
)
print(doc.markdown)
Crawling a Website
To crawl a website, use the crawl method. It takes the starting URL and optional parameters as arguments. You can control depth, limits, formats, and more.
crawl_status = firecrawl.crawl(
'https://firecrawl.dev',
limit=100,
scrape_options=ScrapeOptions(formats=['markdown', 'html']),
poll_interval=30
)
print(crawl_status)
Asynchronous Crawling
Looking for async operations? Check out the Async Class section below.
To enqueue a crawl asynchronously, use start_crawl. It returns the crawl ID which you can use to check the status of the crawl job.
crawl_job = firecrawl.start_crawl(
'https://firecrawl.dev',
limit=100,
scrape_options=ScrapeOptions(formats=['markdown', 'html']),
)
print(crawl_job)
Checking Crawl Status
To check the status of a crawl job, use the get_crawl_status method. It takes the job ID as a parameter and returns the current status of the crawl job.
crawl_status = firecrawl.get_crawl_status("<crawl_id>")
print(crawl_status)
Manual Pagination (v2)
Crawl and batch scrape status responses may include a next URL when more data is available. The SDK auto-paginates by default; to page manually, disable auto-pagination and pass the opaque next URL back to the SDK.
from firecrawl.v2.types import PaginationConfig
# Crawl: fetch one page at a time
crawl_job = firecrawl.start_crawl("https://firecrawl.dev", limit=100)
status = firecrawl.get_crawl_status(
crawl_job.id,
pagination_config=PaginationConfig(auto_paginate=False),
)
if status.next:
page2 = firecrawl.get_crawl_status_page(status.next)
# Batch scrape: fetch one page at a time
batch_job = firecrawl.start_batch_scrape(["https://firecrawl.dev"])
status = firecrawl.get_batch_scrape_status(
batch_job.id,
pagination_config=PaginationConfig(auto_paginate=False),
)
if status.next:
page2 = firecrawl.get_batch_scrape_status_page(status.next)
Cancelling a Crawl
To cancel an asynchronous crawl job, use the cancel_crawl method. It takes the job ID of the asynchronous crawl as a parameter and returns the cancellation status.
cancel_crawl = firecrawl.cancel_crawl(id)
print(cancel_crawl)
Map a Website
Use map to generate a list of URLs from a website. Options let you customize the mapping process, including whether to use the sitemap or include subdomains.
# Map a website (v2):
map_result = firecrawl.map('https://firecrawl.dev')
print(map_result)
Search
Use search to search the web and optionally scrape the results in the same call.
# Search the web (v2):
results = firecrawl.search("what is retrieval augmented generation?", limit=5)
for result in results.web or []:
print(result.url, "-", result.title)
# Scrape every result as part of the search:
results = firecrawl.search(
"firecrawl changelog",
limit=3,
scrape_options={"formats": ["markdown"]},
)
Results are grouped by source: .web, .news, .images and .developer.
Use categories to narrow web search to a kind of site:
results = firecrawl.search("nanopore basecalling accuracy", categories=["research"])
categories=["research"]is a website filter, not the paper index. It restricts ordinary web search to roughly 14 academic domains (arxiv.org, pubmed.ncbi.nlm.nih.gov, nature.com, biorxiv.org, ...) and returns web page results. To search papers themselves, usesearch_papersbelow.
Research / paper search
Use search_papers to search Firecrawl's research paper index: ~43M paper
abstracts, roughly 90% biomedical and life sciences (PubMed, bioRxiv, medRxiv),
plus arXiv for physics, mathematics and computer science.
# Search the paper index (semantic search over abstracts):
papers = firecrawl.search_papers(
"CRISPR base editing off-target effects in primary human T cells",
k=10,
)
for paper in papers["results"]:
print(paper["primaryId"], "-", paper["title"])
# Inspect one paper's metadata (accepts pmid:, pmcid:, doi: or arxiv: ids):
paper = firecrawl.inspect_paper("pmid:<id>")
# Read the passages inside a paper that answer a specific question:
passages = firecrawl.read_paper(
"pmid:<id>",
"what was the primary endpoint and the reported hazard ratio?",
k=4,
)
# Expand along the citation graph, re-ranked for your stated intent:
related = firecrawl.related_papers(
"pmid:<id>",
intent="replication attempts in larger cohorts",
k=20,
)
A companion search_github searches indexed GitHub issue/PR history and repo
readmes.
Response keys are camelCase. Unlike the rest of the SDK, the research methods return the raw JSON body as a
dict— they are not parsed into typed models and not normalized to snake_case. ExpectpaperId,primaryId,createdDate,articleRank,poolSize, and so on.
Every method above is also available on AsyncFirecrawl with the same name.
Scrape-bound interactive browsing (v2)
Use a scrape job ID to keep interacting with the replayed browser context:
doc = firecrawl.scrape(
"https://example.com",
actions=[{"type": "click", "selector": "a[href='/pricing']"}],
)
scrape_job_id = doc.metadata_typed.scrape_id
if not scrape_job_id:
raise RuntimeError("Missing scrape job id")
run = firecrawl.interact(
scrape_job_id,
code="print(await page.url())",
language="python",
timeout=60,
)
print(run.stdout)
firecrawl.stop_interaction(scrape_job_id)
{/* ### Extracting Structured Data from Websites
To extract structured data from websites, use the extract method. It takes the URLs to extract data from, a prompt, and a schema as arguments. The schema is a Pydantic model that defines the structure of the extracted data.
*/}
Crawling a Website with WebSockets
To crawl a website with WebSockets, use the crawl_url_and_watch method. It takes the starting URL and optional parameters as arguments. The params argument allows you to specify additional options for the crawl job, such as the maximum number of pages to crawl, allowed domains, and the output format.
# inside an async function...
nest_asyncio.apply()
# Define event handlers
def on_document(detail):
print("DOC", detail)
def on_error(detail):
print("ERR", detail['error'])
def on_done(detail):
print("DONE", detail['status'])
# Function to start the crawl and watch process
async def start_crawl_and_watch():
# Initiate the crawl job and get the watcher
watcher = app.crawl_url_and_watch('firecrawl.dev', exclude_paths=['blog/*'], limit=5)
# Add event listeners
watcher.add_event_listener("document", on_document)
watcher.add_event_listener("error", on_error)
watcher.add_event_listener("done", on_done)
# Start the watcher
await watcher.connect()
# Run the event loop
await start_crawl_and_watch()
Error Handling
The SDK handles errors returned by the Firecrawl API and raises appropriate exceptions. If an error occurs during a request, an exception will be raised with a descriptive error message.
Async Class
For async operations, you can use the AsyncFirecrawl class. Its methods mirror the Firecrawl class, but you await them.
from firecrawl import AsyncFirecrawl
firecrawl = AsyncFirecrawl(api_key="YOUR_API_KEY")
# Async Scrape (v2)
async def example_scrape():
scrape_result = await firecrawl.scrape(url="https://example.com")
print(scrape_result)
# Async Parse (v2)
async def example_parse():
parse_result = await firecrawl.parse(
b"<!DOCTYPE html><html><body><h1>Async Parse</h1></body></html>",
filename="upload.html",
content_type="text/html",
)
print(parse_result)
# Async Crawl (v2)
async def example_crawl():
crawl_result = await firecrawl.crawl(url="https://example.com")
print(crawl_result)
v1 compatibility
For legacy code paths, v1 remains available under firecrawl.v1 with the original method names.
from firecrawl import Firecrawl
firecrawl = Firecrawl(api_key="YOUR_API_KEY")
# v1 methods (feature‑frozen)
doc_v1 = firecrawl.v1.scrape_url('https://firecrawl.dev', formats=['markdown', 'html'])
crawl_v1 = firecrawl.v1.crawl_url('https://firecrawl.dev', limit=100)
map_v1 = firecrawl.v1.map_url('https://firecrawl.dev')
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