crawl4ai/docs/md_v2/api/async-webcrawler.md

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# 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.
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**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.
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---
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## 1. Constructor Overview
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```python
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:
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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.
"""
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)
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### Typical Initialization
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```python
from crawl4ai import AsyncWebCrawler, BrowserConfig
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browser_cfg = BrowserConfig(
browser_type="chromium",
headless=True,
verbose=True
)
crawler = AsyncWebCrawler(config=browser_cfg)
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```
**Notes**:
- **Legacy** parameters like `always_bypass_cache` remain for backward compatibility, but prefer to set **caching** in `CrawlerRunConfig`.
---
## 2. Lifecycle: Start/Close or Context Manager
### 2.1 Context Manager (Recommended)
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```python
async with AsyncWebCrawler(config=browser_cfg) as crawler:
result = await crawler.arun("https://example.com")
# The crawler automatically starts/closes resources
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```
When the `async with` block ends, the crawler cleans up (closes the browser, etc.).
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### 2.2 Manual Start & Close
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```python
crawler = AsyncWebCrawler(config=browser_cfg)
await crawler.start()
result1 = await crawler.arun("https://example.com")
result2 = await crawler.arun("https://another.com")
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await crawler.close()
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```
Use this style if you have a **long-running** application or need full control of the crawlers lifecycle.
---
## 3. Primary Method: `arun()`
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```python
async def arun(
self,
url: str,
config: Optional[CrawlerRunConfig] = None,
# Legacy parameters for backward compatibility...
) -> CrawlResult:
...
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```
### 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.
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```python
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))
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```
### 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()`
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```python
async def arun_many(
self,
urls: List[str],
config: Optional[CrawlerRunConfig] = None,
# Legacy parameters...
) -> List[CrawlResult]:
...
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```
Crawls multiple URLs in concurrency. Accepts the same style `CrawlerRunConfig`. Example:
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```python
run_cfg = CrawlerRunConfig(
# e.g., concurrency, wait_for, caching, extraction, etc.
semaphore_count=5
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)
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))
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```
### 4.2 `start()` & `close()`
Allows manual lifecycle usage instead of context manager:
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```python
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()
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```
---
## 5. `CrawlResult` Output
Each `arun()` returns a **`CrawlResult`** containing:
- `url`: Final URL (if redirected).
- `html`: Original HTML.
- `cleaned_html`: Sanitized HTML.
- `markdown_v2` (or future `markdown`): 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](./crawl-result.md).
---
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## 6. Quick Example
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Below is an example hooking it all together:
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```python
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": [
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{
"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 **`BrowserConfig`** with Firefox, no headless, and `verbose=True`.
- We define a **`CrawlerRunConfig`** that **bypasses cache**, uses a **CSS** extraction schema, has a `word_count_threshold=15`, etc.
- We pass them to `AsyncWebCrawler(config=...)` and `arun(url=..., config=...)`.
---
## 7. Best Practices & Migration Notes
1. **Use** `BrowserConfig` for **global** settings about the browsers 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:
```python
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()` and `close()` explicitly.
**Migration**:
- If you used `AsyncWebCrawler(browser_type="chromium", css_selector="...")`, move browser settings to `BrowserConfig(...)` and content/crawl logic to `CrawlerRunConfig(...)`.
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This modular approach ensures your code is **clean**, **scalable**, and **easy to maintain**. For any advanced or rarely used parameters, see the [BrowserConfig docs](../api/parameters.md).