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The Firecrawl Python SDK is a library that allows you to easily scrape and crawl websites, and output the data in a format ready for use with language models (LLMs). It provides a simple and intuitive interface for interacting with the Firecrawl API.
To install the Firecrawl Python SDK, you can use pip:
pip install firecrawl-py
FIRECRAWL_API_KEY
or pass it as a parameter to the FirecrawlApp
class.Here's an example of how to use the SDK:
from firecrawl.firecrawl import FirecrawlApp
app = FirecrawlApp(api_key="fc-YOUR_API_KEY")
# Scrape a website:
scrape_status = app.scrape_url(
'https://firecrawl.dev',
params={'formats': ['markdown', 'html']}
)
print(scrape_status)
# Crawl a website:
crawl_status = app.crawl_url(
'https://firecrawl.dev',
params={
'limit': 100,
'scrapeOptions': {'formats': ['markdown', 'html']}
},
poll_interval=30
)
print(crawl_status)
To scrape a single URL, use the scrape_url
method. It takes the URL as a parameter and returns the scraped data as a dictionary.
url = 'https://example.com'
scraped_data = app.scrape_url(url)
With LLM extraction, you can easily extract structured data from any URL. We support pydantic schemas to make it easier for you too. Here is how you to use it:
class ArticleSchema(BaseModel):
title: str
points: int
by: str
commentsURL: str
class TopArticlesSchema(BaseModel):
top: List[ArticleSchema] = Field(..., max_items=5, description="Top 5 stories")
data = app.scrape_url('https://news.ycombinator.com', {
'extractorOptions': {
'extractionSchema': TopArticlesSchema.model_json_schema(),
'mode': 'llm-extraction'
},
'pageOptions':{
'onlyMainContent': True
}
})
print(data["llm_extraction"])
To crawl a website, use the crawl_url
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.
idempotency_key = str(uuid.uuid4()) # optional idempotency key
crawl_result = app.crawl_url('firecrawl.dev', {'excludePaths': ['blog/*']}, 2, idempotency_key)
print(crawl_result)
To crawl a website asynchronously, use the async_crawl_url
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.
crawl_result = app.async_crawl_url('firecrawl.dev', {'excludePaths': ['blog/*']}, "")
print(crawl_result)
To check the status of a crawl job, use the check_crawl_status
method. It takes the job ID as a parameter and returns the current status of the crawl job.
id = crawl_result['id']
status = app.check_crawl_status(id)
Use map_url
to generate a list of URLs from a website. The params
argument let you customize the mapping process, including options to exclude subdomains or to utilize the sitemap.
# Map a website:
map_result = app.map_url('https://example.com')
print(map_result)
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', { 'excludePaths': ['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()
To batch scrape multiple URLs, use the batch_scrape_urls
method. It takes the URLs and optional parameters as arguments. The params
argument allows you to specify additional options for the scraper such as the output formats.
idempotency_key = str(uuid.uuid4()) # optional idempotency key
batch_scrape_result = app.batch_scrape_urls(['firecrawl.dev', 'mendable.ai'], {'formats': ['markdown', 'html']}, 2, idempotency_key)
print(batch_scrape_result)
To run a batch scrape asynchronously, use the async_batch_scrape_urls
method. It takes the starting URL and optional parameters as arguments. The params
argument allows you to specify additional options for the scraper, such as the output formats.
batch_scrape_result = app.async_batch_scrape_urls(['firecrawl.dev', 'mendable.ai'], {'formats': ['markdown', 'html']})
print(batch_scrape_result)
To check the status of an asynchronous batch scrape job, use the check_batch_scrape_status
method. It takes the job ID as a parameter and returns the current status of the batch scrape job.
id = batch_scrape_result['id']
status = app.check_batch_scrape_status(id)
To use batch scrape with WebSockets, use the batch_scrape_urls_and_watch
method. It takes the starting URL and optional parameters as arguments. The params
argument allows you to specify additional options for the scraper, such as the output formats.
# 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.batch_scrape_urls_and_watch(['firecrawl.dev', 'mendable.ai'], {'formats': ['markdown', 'html']})
# 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()
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.
To ensure the functionality of the Firecrawl Python SDK, we have included end-to-end tests using pytest
. These tests cover various aspects of the SDK, including URL scraping, web searching, and website crawling.
To run the tests, execute the following commands:
Install pytest:
pip install pytest
Run:
pytest firecrawl/__tests__/e2e_withAuth/test.py
Contributions to the Firecrawl Python SDK are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the GitHub repository.
The Firecrawl Python SDK is licensed under the MIT License. This means you are free to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the SDK, subject to the following conditions:
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Please note that while this SDK is MIT licensed, it is part of a larger project which may be under different licensing terms. Always refer to the license information in the root directory of the main project for overall licensing details.
FAQs
Python SDK for Firecrawl API
We found that firecrawl-py demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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