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@bigbrother666sh bigbrother666sh commented May 13, 2025

Summary

Improved utils.normalize_url functionality:

  1. Can handle more edge cases;
  2. Add the function to remove tracking parameters, enhancing privacy and anti-crawling capabilities.

Checklist:

  • [✓ ] My code follows the style guidelines of this project
  • [✓ ] I have performed a self-review of my own code
  • [ ✓] I have commented my code, particularly in hard-to-understand areas
  • [✓ ] I have made corresponding changes to the documentation
  • [✓ ] I have added/updated unit tests that prove my fix is effective or that my feature works
  • [✓ ] New and existing unit tests pass locally with my changes

Summary by CodeRabbit

  • New Features
    • Improved URL normalization to handle various URL formats and prefixes.
    • Automatic removal of common tracking parameters from URLs for cleaner links.

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coderabbitai bot commented May 13, 2025

"""

Walkthrough

The normalize_url function in crawl4ai/utils.py was extensively rewritten. The update introduces logic to remove a comprehensive set of tracking parameters from URLs and improves normalization by handling various URL prefix formats. The function now reconstructs cleaned URLs and includes fallback logic for error scenarios.

Changes

File(s) Change Summary
crawl4ai/utils.py Rewrote normalize_url to robustly handle URL normalization, explicitly remove many tracking parameters, and add fallback error handling. Function signature unchanged.

Poem

A hop and a skip through the URLs we go,
Stripping the trackers, making them slow.
From "utm_source" to "fbclid"—all swept away,
Leaving clean links to brighten the day.
With whiskers twitching, I tidy each string—
Now only pure paths do my rabbit hops bring!
"""

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  • crawl4ai/utils.py (2 hunks)
🔇 Additional comments (6)
crawl4ai/utils.py (6)

1994-2023: Comprehensive list of tracking parameters for privacy enhancement.

The implementation includes an extensive list of tracking parameters that will be removed from URLs, significantly enhancing user privacy and helping to evade tracking. This covers parameters from major analytics platforms, social media, email marketing, and advertising services.


2025-2040: Well-documented function with LRU caching for performance.

The function is now properly cached with @lru_cache and includes a comprehensive docstring that clearly explains its purpose and functionality. This will improve performance for repeated URL normalizations, which is particularly useful during crawling operations where the same URLs may be encountered multiple times.


2041-2052: Robust input validation and special scheme handling.

The implementation now properly handles edge cases:

  1. Guards against None or empty inputs
  2. Preserves special URL schemes like mailto:, tel:, javascript:, and data:

This prevents errors and ensures special-purpose URLs are left intact.


2053-2066: Comprehensive URL format normalization.

The code now handles a wide variety of URL formats and prefixes, including:

  • URLs starting with www. or WWW.
  • URLs starting with /www.
  • Protocol-relative URLs (//example.com)
  • URLs with malformed protocols (http:/example.com)
  • Relative URLs that need base URL joining

This ensures consistent URL normalization across many edge cases.


2067-2083: Clean implementation of tracking parameter removal.

The function properly parses the URL, removes tracking parameters, and reconstructs the URL while preserving the original structure. The use of standard library functions like urlparse, parse_qs, and urlunparse ensures robust handling of URL components.


2084-2098: Robust error handling with fallback mechanisms.

The implementation includes proper error handling with specific exception types and two levels of fallback:

  1. First attempts to reconstruct the URL using string operations
  2. If that fails, returns the original URL

This ensures the function is resilient and won't break URL processing even with unexpected inputs.

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Actionable comments posted: 2

🧹 Nitpick comments (2)
crawl4ai/utils.py (2)

1996-2071: Consider caching frequent URLs for performance improvement.

The function handles many complex operations which could be expensive when called repeatedly with the same URLs (common in web crawling). Since URL normalization results are deterministic, this function would benefit from caching.

Apply the @lru_cache decorator as done for efficient_normalize_url_for_deep_crawl in line 2122:

+@lru_cache(maxsize=1000)
 def normalize_url(href, base_url):
     """Normalize URLs to ensure consistent format with a better way
     also remove tracking parameters"""

1999-2028: Move tracking parameters list outside the function.

The comprehensive list of tracking parameters is recreated every time the function is called, which is inefficient. Consider moving it to a module-level constant.

+# Common tracking parameters to be removed from URLs
+TRACKING_PARAMETERS = [
+    'utm_source', 'utm_medium', 'utm_campaign', 
+    'utm_term', 'utm_content', 'fbclid', 'gclid',
+    # ... rest of the parameters
+]

 def normalize_url(href, base_url):
     """Normalize URLs to ensure consistent format with a better way
     also remove tracking parameters"""

-    params_to_remove = [
-    'utm_source', 'utm_medium', 'utm_campaign', 
-    'utm_term', 'utm_content', 'fbclid', 'gclid',
-    # ... rest of the parameters
-    ]
+    params_to_remove = TRACKING_PARAMETERS
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crawl4ai/utils.py (4)

1996-1998: Clear and improved docstring of the function.

The docstring has been updated to explicitly mention both URL normalization and tracking parameter removal, accurately reflecting the function's enhanced capabilities.


1999-2028: Well-organized comprehensive list of tracking parameters.

The extensive list of tracking parameters covers a wide range of common analytics and marketing tracking identifiers. This is essential for privacy enhancement and will make URLs cleaner and more consistent.


2030-2044: Robust handling of various URL formats.

The implementation now properly handles multiple URL prefix patterns, including:

  • URLs starting with "www." or "WWW."
  • URLs starting with "/www."
  • Protocol-relative URLs starting with "//"
  • Absolute URLs with http/https
  • Malformed URLs with missing slashes
  • Relative URLs

This should significantly improve the robustness of URL processing in the application.


2048-2064:

❓ Verification inconclusive

Verify consistent behavior with the previous implementation.

The function now uses parse_qs and urlencode which handle parameters differently than the previous implementation might have. Specifically, parse_qs returns a dictionary where each value is a list, and urlencode with doseq=True maintains this structure.

Run the following script to check how the function handles URLs with multiple values for the same parameter:


🏁 Script executed:

#!/bin/bash
# Test how normalize_url handles multiple values for the same parameter

# Create a Python script for testing
cat > test_normalize_url.py << 'EOF'
from crawl4ai.utils import normalize_url

# Test URLs with multiple values for the same parameter
test_urls = [
    "https://example.com/path?param1=value1&param1=value2&utm_source=test",
    "https://example.com/path?normal=value&utm_source=value1&utm_source=value2",
    "https://www.example.com/path?a=1&b=2&c=3",
    "//example.com/path?param=value&fbclid=123",
    "http:/example.com/path?q=test&gclid=abc123",
    "/path/to/resource?t=now&utm_campaign=spring",
    "example.com/no-protocol?ref=homepage"
]

base_url = "https://baseurl.com"

print("=== Testing normalize_url function ===")
for url in test_urls:
    normalized = normalize_url(url, base_url)
    print(f"\nOriginal:  {url}")
    print(f"Normalized: {normalized}")
EOF

# Run the test script
python test_normalize_url.py

Length of output: 603


🏁 Script executed:

#!/bin/bash
set -e

# Install required dependencies
pip install pydantic

# Install the local crawl4ai package in editable mode
pip install -e .

# Recreate and run the normalize_url test
cat > test_normalize_url.py << 'EOF'
from crawl4ai.utils import normalize_url

# Test URLs with multiple values for the same parameter
test_urls = [
    "https://example.com/path?param1=value1&param1=value2&utm_source=test",
    "https://example.com/path?normal=value&utm_source=value1&utm_source=value2",
    "https://www.example.com/path?a=1&b=2&c=3",
    "//example.com/path?param=value&fbclid=123",
    "http:/example.com/path?q=test&gclid=abc123",
    "/path/to/resource?t=now&utm_campaign=spring",
    "example.com/no-protocol?ref=homepage"
]

base_url = "https://baseurl.com"

print("=== Testing normalize_url function ===")
for url in test_urls:
    normalized = normalize_url(url, base_url)
    print(f\"\\nOriginal:  {url}\")
    print(f\"Normalized: {normalized}\")
EOF

python test_normalize_url.py

Length of output: 18444


Double-check normalize_url behavior with duplicate query parameters

The updated normalize_url in crawl4ai/utils.py now uses parse_qs (which groups values into lists) and urlencode(..., doseq=True) to rebuild the query string. Please confirm this matches the previous behavior for parameters appearing multiple times—especially that:

  • Duplicate keys (e.g. param1=value1&param1=value2) are preserved in order and count.
  • Removing entries in params_to_remove (e.g. utm_source, fbclid) doesn’t inadvertently drop or reorder other parameters.

Suggested actions:

  • Add unit tests for URLs with repeated parameters, verifying both removal of unwanted keys and retention of all other values.
  • Manually compare output of the new implementation against the old one for a set of representative URLs.

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Actionable comments posted: 0

♻️ Duplicate comments (1)
crawl4ai/utils.py (1)

2047-2047: This line correctly uses _url for URL parsing.

Following the previous review feedback, the function now correctly uses the normalized URL variable (_url) for parsing instead of the original URL.

🧹 Nitpick comments (2)
crawl4ai/utils.py (2)

2065-2071: Error handling could be improved.

The fallback mechanism is a good practice, but could be enhanced to:

  1. Catch specific exceptions rather than a generic Exception
  2. Include the problematic URL in the error message
  3. Implement a more robust URL reconstruction logic
-    except Exception as e:
-        print(f"Error cleaning URL: {e}")
-        _ss = _url.split('//')
-        if len(_ss) == 2:
-            return '//'.join(_ss)
-        else:
-            return _ss[0] + '//' + '/'.join(_ss[1:])
+    except (ValueError, AttributeError, TypeError) as e:
+        print(f"Error cleaning URL '{_url}': {e}")
+        try:
+            # More robust fallback that preserves the original URL structure
+            _ss = _url.split('//')
+            if len(_ss) == 2:
+                return '//'.join(_ss)
+            else:
+                return _ss[0] + '//' + '/'.join(_ss[1:])
+        except:
+            # Ultimate fallback - return the input URL
+            return href

1996-1997: Consider adding more descriptive documentation.

The function comments should be expanded to better explain:

  1. What tracking parameters are being removed
  2. How different URL formats are normalized
  3. The fallback behavior
 def normalize_url(href, base_url):
-    """Normalize URLs to ensure consistent format with a better way
-    also remove tracking parameters"""
+    """Normalize URLs to ensure consistent format and remove tracking parameters.
+    
+    This function:
+    1. Normalizes URLs with various formats (www., //, http:/, etc.)
+    2. Removes common tracking parameters (UTM, Facebook, Google, etc.)
+    3. Handles URL parsing errors with a fallback mechanism
+    
+    Args:
+        href (str): The URL to normalize
+        base_url (str): The base URL to use for relative URLs
+        
+    Returns:
+        str: The normalized and cleaned URL
+    """
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crawl4ai/utils.py (2)

1995-2046: Excellent enhancement to URL normalization handling various edge cases.

The function now properly handles a wide variety of URL formats (www., //, http:/, etc.) and includes a comprehensive list of tracking parameters to remove. This implementation significantly improves privacy protection and strengthens anti-crawling measures as intended.


2047-2063: Well-implemented tracking parameter removal logic.

The implementation correctly parses the URL, removes tracking parameters, and reconstructs the cleaned URL. This approach is robust and handles URL parsing and cleaning efficiently.

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Actionable comments posted: 2

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  • crawl4ai/utils.py (2 hunks)
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crawl4ai/utils.py

2086-2086: Do not use bare except

(E722)

🔇 Additional comments (6)
crawl4ai/utils.py (6)

1994-2023: Comprehensive tracking parameter list enhances privacy protection.

This extensive list of tracking parameters will significantly improve privacy by removing identifiers from various marketing and analytics platforms including:

  • UTM parameters used for campaign tracking
  • Facebook, Google, and other social media tracking parameters
  • Marketing automation platform identifiers (Mailchimp, etc.)
  • Various analytics and tracking IDs

2025-2026: Good optimization with LRU cache.

The LRU cache implementation with a size of 1000 entries is an excellent performance optimization for repeatedly processed URLs, which is common in web crawling scenarios.


2027-2040: Well-documented function with clear purpose.

The docstring clearly explains the function's three primary purposes:

  1. Normalizing URLs with various formats
  2. Removing tracking parameters
  3. Handling URL parsing errors with fallbacks

This documentation helps future maintainers understand the intent and functionality.


2042-2057: Robust handling of URL prefix variations.

The logic correctly handles various URL prefix formats that might be encountered in real-world websites:

  • www. and WWW. prefixes
  • Protocol-relative URLs (starting with //)
  • Malformed http:/ and https:/ URLs (missing slash)
  • Relative URLs joined with base_url

2058-2076: Effective tracking parameter removal logic.

The implementation correctly:

  1. Parses the normalized URL
  2. Extracts query parameters
  3. Removes tracking parameters
  4. Reconstructs the query string
  5. Rebuilds the full URL

This addresses the PR objective of privacy enhancement.


2059-2059: Fixed previous URL variable discrepancy.

This resolves the discrepancy identified in a previous review where the function was parsing url instead of _url. The normalized URL is now correctly used for parsing.

sovle None input

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Actionable comments posted: 1

🧹 Nitpick comments (2)
crawl4ai/utils.py (2)

2085-2096: Consider handling additional URL edge cases.

While the error handling is good, there are additional edge cases that could be improved:

  1. The function doesn't handle data URLs, mailto links, or JavaScript URLs specially
  2. URLs with authentication (username:password@domain) might be processed differently than expected

Consider adding special handling for these cases to further improve robustness.

@lru_cache(maxsize=1000)
def normalize_url(href, base_url):
    # Guard against None or empty inputs
    if href is None:
        return None
    href = href.strip()
    if not href:
        return None

+    # Handle special URL schemes that shouldn't be modified
+    special_schemes = ['mailto:', 'tel:', 'javascript:', 'data:']
+    if any(href.lower().startswith(scheme) for scheme in special_schemes):
+        return href

    url = href
    # Rest of the function...

2025-2025: Consider a larger LRU cache size for heavily accessed sites.

The current @lru_cache(maxsize=1000) is a good starting point, but depending on your application's traffic patterns, you might need a larger cache size. If your application crawls many sites with unique URLs, consider increasing this value to reduce repeated normalizations.

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crawl4ai/utils.py

2065-2065: SyntaxError: Got unexpected token …

🔇 Additional comments (3)
crawl4ai/utils.py (3)

1994-2023: The tracking parameter list is comprehensive.

This extensive list of tracking parameters covers a wide range of advertising, analytics, and marketing platforms including Google UTM parameters, Facebook tracking, email marketing trackers, and many others. This will significantly improve privacy for users by removing these identifiers during URL normalization.


2067-2084: The URL cleaning implementation effectively removes tracking parameters.

The implementation correctly:

  1. Parses the URL using urlparse
  2. Extracts query parameters using parse_qs
  3. Removes all tracking parameters from the query dict
  4. Reconstructs the query string with urlencode
  5. Builds the clean URL with urlunparse

This approach is robust and will clean URLs as expected.


2025-2040: ⚠️ Potential issue

Fix duplicate function definition causing decorator to be ineffective.

There's a critical error in the code structure. The @lru_cache decorator is applied to an empty function definition (lines 2025-2026), while the actual implementation starts on line 2042. This means the caching functionality won't work.

Apply this correction to fix the function structure:

@lru_cache(maxsize=1000)
-def normalize_url(href, base_url):
-    """Normalize URLs to ensure consistent format and remove tracking parameters.
-    
-    This function:
-    1. Normalizes URLs with various formats (www., //, http:/, etc.)
-    2. Removes common tracking parameters (UTM, Facebook, Google, etc.)
-    3. Handles URL parsing errors with a fallback mechanism
-    
-    Args:
-        href (str): The URL to normalize
-        base_url (str): The base URL to use for relative URLs
-        
-    Returns:
-        str: The normalized and cleaned URL
-    """
-
-def normalize_url(href, base_url):
+def normalize_url(href, base_url):
+    """Normalize URLs to ensure consistent format and remove tracking parameters.
+    
+    This function:
+    1. Normalizes URLs with various formats (www., //, http:/, etc.)
+    2. Removes common tracking parameters (UTM, Facebook, Google, etc.)
+    3. Handles URL parsing errors with a fallback mechanism
+    
+    Args:
+        href (str): The URL to normalize
+        base_url (str): The base URL to use for relative URLs
+        
+    Returns:
+        str: The normalized and cleaned URL
+    """
     # Guard against None or empty inputs
     if href is None:
         return None

Likely an incorrect or invalid review comment.

remove misstake ...

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Actionable comments posted: 1

♻️ Duplicate comments (1)
crawl4ai/utils.py (1)

2084-2095: 🛠️ Refactor suggestion

Improve error handling by avoiding bare except.

Your error handling includes a good first try/except with specific exception types, but contains a bare except clause in the fallback which can mask unexpected errors.

Apply this change to capture and log specific exception types in the fallback:

    except (ValueError, AttributeError, TypeError) as e:
        print(f"Error cleaning URL '{_url}': {e}")
        try:
            # More robust fallback that preserves the original URL structure
            _ss = _url.split('//')
            if len(_ss) == 2:
                return '//'.join(_ss)
            else:
                return _ss[0] + '//' + '/'.join(_ss[1:])
-        except:
+        except Exception as fallback_error:
+            print(f"Fallback error for URL '{_url}': {fallback_error}")
            # Ultimate fallback - return the uncleaned url
            return _url
🧰 Tools
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2093-2093: Do not use bare except

(E722)

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🧰 Additional context used
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crawl4ai/utils.py

2042-2042: Redefinition of unused normalize_url from line 2026

(F811)


2093-2093: Do not use bare except

(E722)

🔇 Additional comments (5)
crawl4ai/utils.py (5)

1994-2023: Comprehensive tracking parameter list enhances privacy.

The extensive list of tracking parameters to remove is well-organized and thorough, covering major analytics platforms (UTM, Facebook, Google), email marketing tools, and numerous other tracking mechanisms. This significantly improves user privacy and reduces tracking footprint.


2025-2041: Good use of caching for performance optimization.

The @lru_cache decorator will significantly improve performance for frequently accessed URLs by avoiding redundant processing. The cache size of 1000 seems reasonable for balancing memory usage vs. performance gains.


2051-2065: Excellent URL normalization logic.

The URL normalization logic thoroughly handles a wide range of URL formats including:

  • URLs starting with 'www.' or 'WWW.'
  • URLs with missing protocol parts like '/www.'
  • Protocol-relative URLs ('//example.com')
  • URLs with malformed protocols ('http:/' instead of 'http://')

This robust handling will significantly improve the crawler's ability to properly process URLs found in the wild.


2066-2083: Great implementation of tracking parameter removal.

The function correctly uses urlparse, parse_qs, and urlunparse to extract, clean, and rebuild the URL. This approach properly preserves the URL structure while removing only the unwanted tracking parameters.


34-34: Good addition of required imports.

The added imports from urllib.parse are necessary for the URL parsing, manipulation, and reconstruction functionality.

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