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docs: Update URL seeding examples to use proper async context managers

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- Wrap all AsyncUrlSeeder usage with async context managers
- Update URL seeding adventure example to use "sitemap+cc" source, focus on course posts, and add stream=True parameter to fix runtime error
This commit is contained in:
Soham Kukreti
2025-08-13 18:16:46 +05:30
parent 11b310edef
commit ecbe5ffb84
1 changed files with 33 additions and 31 deletions
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64
docs/md_v2/core/url-seeding.md
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@@ -102,16 +102,16 @@ async def smart_blog_crawler():
# Step 2: Configure discovery - let's find all blog posts
config = SeedingConfig(
source="sitemap", # Use the website's sitemap
pattern="*/blog/*.html", # Only blog posts
source="sitemap+cc", # Use the website's sitemap+cc
pattern="*/courses/*", # Only courses related posts
extract_head=True, # Get page metadata
max_urls=100 # Limit for this example
)
# Step 3: Discover URLs from the Python blog
print("🔍 Discovering blog posts...")
print("🔍 Discovering course posts...")
urls = await seeder.urls("realpython.com", config)
print(f"✅ Found {len(urls)} blog posts")
print(f"✅ Found {len(urls)} course posts")
# Step 4: Filter for Python tutorials (using metadata!)
tutorials = [
@@ -134,7 +134,8 @@ async def smart_blog_crawler():
async with AsyncWebCrawler() as crawler:
config = CrawlerRunConfig(
only_text=True,
word_count_threshold=300 # Only substantial articles
word_count_threshold=300, # Only substantial articles
stream=True
)
# Extract URLs and crawl them
@@ -155,7 +156,7 @@ asyncio.run(smart_blog_crawler())
**What just happened?**
1. We discovered all blog URLs from the sitemap
1. We discovered all blog URLs from the sitemap+cc
2. We filtered using metadata (no crawling needed!)
3. We crawled only the relevant tutorials
4. We saved tons of time and bandwidth
@@ -282,8 +283,8 @@ config = SeedingConfig(
live_check=True, # Verify each URL is accessible
concurrency=20 # Check 20 URLs in parallel
)
urls = await seeder.urls("example.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("example.com", config)
# Now you can filter by status
live_urls = [u for u in urls if u["status"] == "valid"]
@@ -311,8 +312,8 @@ This is where URL seeding gets really powerful. Instead of crawling entire pages
config = SeedingConfig(
extract_head=True # Extract metadata from <head> section
)
urls = await seeder.urls("example.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("example.com", config)
# Now each URL has rich metadata
for url in urls[:3]:
@@ -387,8 +388,8 @@ config = SeedingConfig(
scoring_method="bm25",
score_threshold=0.3
)
urls = await seeder.urls("example.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("example.com", config)
# URLs are scored based on:
# 1. Domain parts matching (e.g., 'python' in python.example.com)
@@ -429,8 +430,8 @@ config = SeedingConfig(
extract_head=True,
live_check=True
)
urls = await seeder.urls("blog.example.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("blog.example.com", config)
# Analyze the results
for url in urls[:5]:
@@ -488,8 +489,8 @@ config = SeedingConfig(
scoring_method="bm25", # Use BM25 algorithm
score_threshold=0.3 # Minimum relevance score
)
urls = await seeder.urls("realpython.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("realpython.com", config)
# Results are automatically sorted by relevance!
for url in urls[:5]:
@@ -511,8 +512,8 @@ config = SeedingConfig(
score_threshold=0.5,
max_urls=20
)
urls = await seeder.urls("docs.example.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("docs.example.com", config)
# The highest scoring URLs will be API docs!
```
@@ -529,8 +530,8 @@ config = SeedingConfig(
score_threshold=0.4,
pattern="*/product/*" # Combine with pattern matching
)
urls = await seeder.urls("shop.example.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("shop.example.com", config)
# Filter further by price (from metadata)
affordable = [
@@ -550,8 +551,8 @@ config = SeedingConfig(
scoring_method="bm25",
score_threshold=0.35
)
urls = await seeder.urls("technews.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("technews.com", config)
# Filter by date
from datetime import datetime, timedelta
@@ -591,8 +592,8 @@ for query in queries:
score_threshold=0.4,
max_urls=10 # Top 10 per topic
)
urls = await seeder.urls("learning-platform.com", config)
async with AsyncUrlSeeder() as seeder:
urls = await seeder.urls("learning-platform.com", config)
all_tutorials.extend(urls)
# Remove duplicates while preserving order
@@ -625,7 +626,8 @@ config = SeedingConfig(
)
# Returns a dictionary: {domain: [urls]}
results = await seeder.many_urls(domains, config)
async with AsyncUrlSeeder() as seeder:
results = await seeder.many_urls(domains, config)
# Process results
for domain, urls in results.items():
@@ -654,8 +656,8 @@ config = SeedingConfig(
pattern="*/blog/*",
max_urls=100
)
results = await seeder.many_urls(competitors, config)
async with AsyncUrlSeeder() as seeder:
results = await seeder.many_urls(competitors, config)
# Analyze content types
for domain, urls in results.items():
@@ -690,8 +692,8 @@ config = SeedingConfig(
score_threshold=0.3,
max_urls=20 # Per site
)
results = await seeder.many_urls(educational_sites, config)
async with AsyncUrlSeeder() as seeder:
results = await seeder.many_urls(educational_sites, config)
# Find the best beginner tutorials
all_tutorials = []
@@ -731,8 +733,8 @@ config = SeedingConfig(
score_threshold=0.5, # High threshold for relevance
max_urls=10
)
results = await seeder.many_urls(news_sites, config)
async with AsyncUrlSeeder() as seeder:
results = await seeder.many_urls(news_sites, config)
# Collect all mentions
mentions = []