8.8 KiB
AsyncWebCrawler
The AsyncWebCrawler is the core class for asynchronous web crawling in Crawl4AI. You typically create it once, optionally customize it with a BrowserConfig (e.g., headless, user agent), then run multiple arun() calls with different CrawlerRunConfig objects.
Recommended usage:
1. Create a BrowserConfig for global browser settings.
2. Instantiate AsyncWebCrawler(config=browser_config).
3. Use the crawler in an async context manager (async with) or manage start/close manually.
4. Call arun(url, config=crawler_run_config) for each page you want.
1. Constructor Overview
class AsyncWebCrawler:
def __init__(
self,
crawler_strategy: Optional[AsyncCrawlerStrategy] = None,
config: Optional[BrowserConfig] = None,
always_bypass_cache: bool = False, # deprecated
always_by_pass_cache: Optional[bool] = None, # also deprecated
base_directory: str = ...,
thread_safe: bool = False,
**kwargs,
):
"""
Create an AsyncWebCrawler instance.
Args:
crawler_strategy:
(Advanced) Provide a custom crawler strategy if needed.
config:
A BrowserConfig object specifying how the browser is set up.
always_bypass_cache:
(Deprecated) Use CrawlerRunConfig.cache_mode instead.
base_directory:
Folder for storing caches/logs (if relevant).
thread_safe:
If True, attempts some concurrency safeguards. Usually False.
**kwargs:
Additional legacy or debugging parameters.
"""
)
### Typical Initialization
```python
from crawl4ai import AsyncWebCrawler, BrowserConfig
browser_cfg = BrowserConfig(
browser_type="chromium",
headless=True,
verbose=True
)
crawler = AsyncWebCrawler(config=browser_cfg)
Notes:
- Legacy parameters like
always_bypass_cacheremain for backward compatibility, but prefer to set caching inCrawlerRunConfig.
2. Lifecycle: Start/Close or Context Manager
2.1 Context Manager (Recommended)
async with AsyncWebCrawler(config=browser_cfg) as crawler:
result = await crawler.arun("https://example.com")
# The crawler automatically starts/closes resources
When the async with block ends, the crawler cleans up (closes the browser, etc.).
2.2 Manual Start & Close
crawler = AsyncWebCrawler(config=browser_cfg)
await crawler.start()
result1 = await crawler.arun("https://example.com")
result2 = await crawler.arun("https://another.com")
await crawler.close()
Use this style if you have a long-running application or need full control of the crawler’s lifecycle.
3. Primary Method: arun()
async def arun(
self,
url: str,
config: Optional[CrawlerRunConfig] = None,
# Legacy parameters for backward compatibility...
) -> CrawlResult:
...
3.1 New Approach
You pass a CrawlerRunConfig object that sets up everything about a crawl—content filtering, caching, session reuse, JS code, screenshots, etc.
import asyncio
from crawl4ai import CrawlerRunConfig, CacheMode
run_cfg = CrawlerRunConfig(
cache_mode=CacheMode.BYPASS,
css_selector="main.article",
word_count_threshold=10,
screenshot=True
)
async with AsyncWebCrawler(config=browser_cfg) as crawler:
result = await crawler.arun("https://example.com/news", config=run_cfg)
print("Crawled HTML length:", len(result.cleaned_html))
if result.screenshot:
print("Screenshot base64 length:", len(result.screenshot))
3.2 Legacy Parameters Still Accepted
For backward compatibility, arun() can still accept direct arguments like css_selector=..., word_count_threshold=..., etc., but we strongly advise migrating them into a CrawlerRunConfig.
4. Helper Methods
4.1 arun_many()
async def arun_many(
self,
urls: List[str],
config: Optional[CrawlerRunConfig] = None,
# Legacy parameters...
) -> List[CrawlResult]:
...
Crawls multiple URLs in concurrency. Accepts the same style CrawlerRunConfig. Example:
run_cfg = CrawlerRunConfig(
# e.g., concurrency, wait_for, caching, extraction, etc.
semaphore_count=5
)
async with AsyncWebCrawler(config=browser_cfg) as crawler:
results = await crawler.arun_many(
urls=["https://example.com", "https://another.com"],
config=run_cfg
)
for r in results:
print(r.url, ":", len(r.cleaned_html))
4.2 start() & close()
Allows manual lifecycle usage instead of context manager:
crawler = AsyncWebCrawler(config=browser_cfg)
await crawler.start()
# Perform multiple operations
resultA = await crawler.arun("https://exampleA.com", config=run_cfg)
resultB = await crawler.arun("https://exampleB.com", config=run_cfg)
await crawler.close()
5. CrawlResult Output
Each arun() returns a CrawlResult containing:
url: Final URL (if redirected).html: Original HTML.cleaned_html: Sanitized HTML.markdown_v2(or futuremarkdown): Markdown outputs (raw, fit, etc.).extracted_content: If an extraction strategy was used (JSON for CSS/LLM strategies).screenshot,pdf: If screenshots/PDF requested.media,links: Information about discovered images/links.success,error_message: Status info.
For details, see CrawlResult doc.
6. Quick Example
Below is an example hooking it all together:
import asyncio
from crawl4ai import AsyncWebCrawler, BrowserConfig, CrawlerRunConfig, CacheMode
from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
import json
async def main():
# 1. Browser config
browser_cfg = BrowserConfig(
browser_type="firefox",
headless=False,
verbose=True
)
# 2. Run config
schema = {
"name": "Articles",
"baseSelector": "article.post",
"fields": [
{
"name": "title",
"selector": "h2",
"type": "text"
},
{
"name": "url",
"selector": "a",
"type": "attribute",
"attribute": "href"
}
]
}
run_cfg = CrawlerRunConfig(
cache_mode=CacheMode.BYPASS,
extraction_strategy=JsonCssExtractionStrategy(schema),
word_count_threshold=15,
remove_overlay_elements=True,
wait_for="css:.post" # Wait for posts to appear
)
async with AsyncWebCrawler(config=browser_cfg) as crawler:
result = await crawler.arun(
url="https://example.com/blog",
config=run_cfg
)
if result.success:
print("Cleaned HTML length:", len(result.cleaned_html))
if result.extracted_content:
articles = json.loads(result.extracted_content)
print("Extracted articles:", articles[:2])
else:
print("Error:", result.error_message)
asyncio.run(main())
Explanation:
- We define a
BrowserConfigwith Firefox, no headless, andverbose=True. - We define a
CrawlerRunConfigthat bypasses cache, uses a CSS extraction schema, has aword_count_threshold=15, etc. - We pass them to
AsyncWebCrawler(config=...)andarun(url=..., config=...).
7. Best Practices & Migration Notes
1. Use BrowserConfig for global settings about the browser’s environment.
2. Use CrawlerRunConfig for per-crawl logic (caching, content filtering, extraction strategies, wait conditions).
3. Avoid legacy parameters like css_selector or word_count_threshold directly in arun(). Instead:
run_cfg = CrawlerRunConfig(css_selector=".main-content", word_count_threshold=20)
result = await crawler.arun(url="...", config=run_cfg)
4. Context Manager usage is simplest unless you want a persistent crawler across many calls.
8. Summary
AsyncWebCrawler is your entry point to asynchronous crawling:
- Constructor accepts
BrowserConfig(or defaults). arun(url, config=CrawlerRunConfig)is the main method for single-page crawls.arun_many(urls, config=CrawlerRunConfig)handles concurrency across multiple URLs.- For advanced lifecycle control, use
start()andclose()explicitly.
Migration:
- If you used
AsyncWebCrawler(browser_type="chromium", css_selector="..."), move browser settings toBrowserConfig(...)and content/crawl logic toCrawlerRunConfig(...).
This modular approach ensures your code is clean, scalable, and easy to maintain. For any advanced or rarely used parameters, see the BrowserConfig docs.