Crawler Inspector

1. Shard Calculation

Query:

Response:

Calculated Shard: 108 (from laksa064)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa108.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, meta_canonical AS meta_canonical, ml_categories_json AS ml_categories_json, ml_types_json AS ml_types_json, ml_intent_types_json AS ml_intent_types_json, meta_language AS meta_language, attrs_author AS attrs_author, ifNull(toUnixTimestamp(attrs_publish_time), 0) AS attrs_publish_time, ifNull(toUnixTimestamp(attrs_original_publish_time), 0) AS attrs_original_publish_time, ifNull(attrs_is_republished, 0) AS attrs_is_republished, ifNull(attrs_nr_words, 0) AS attrs_nr_words, ifNull(attrs_boilerpipe_nr_words, 0) AS attrs_boilerpipe_nr_words, ifNull(body_ext_links_number, 0) AS body_ext_links_number, ifNull(body_int_links_number, 0) AS body_int_links_number, ifNull(meta_nofollow, 0) AS meta_nofollow, ifNull(meta_noarchive, 0) AS meta_noarchive, ifNull(props_was_rendered, 0) AS props_was_rendered, ifNull(src_redirect, \'\') AS src_redirect, ifNull(download_time_msec, 0) AS download_time_msec, ifNull(download_ttfb_msec, 0) AS download_ttfb_msec, ifNull(download_size, 0) AS download_size FROM crawler3.page_info_local FINAL PREWHERE int_partition_id = 47 AND (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://www.enjoyalgorithms.com/blog/introduction-to-seaborn-library-in-python/\')), getAhrefsUnparsedNoserviceFromURL(\'https://www.enjoyalgorithms.com/blog/introduction-to-seaborn-library-in-python/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/www.enjoyalgorithms.com\/blog\/introduction-to-seaborn-library-in-python\/","crawl_time":1779129833,"first_indexed_time":1665195497,"http_code":200,"src_unparsed":"com,enjoyalgorithms!www,\/blog\/introduction-to-seaborn-library-in-python\/ s443","src_root_hash":"17796266760850149508","history_drop_reason":null,"meta_title":"Introduction to Seaborn in Python","meta_descriptions":["Seaborn is an open-source library built over Matplotlib and makes plots more appealing and understandable. It works excellently with data frames and pandas libraries. In this blog, we have discussed: 1) Advantages of Seaborn over Matplotlib library, 2) Installation process of Seaborn in Python 3) Various Data Plots using the Seaborn library."],"meta_canonical":null,"ml_categories_json":"","ml_types_json":"","ml_intent_types_json":"","meta_language":"en","attrs_author":"Shashank Gupta","attrs_publish_time":0,"attrs_original_publish_time":1665195497,"attrs_is_republished":0,"attrs_nr_words":"3232","attrs_boilerpipe_nr_words":"3112","body_ext_links_number":6,"body_int_links_number":25,"meta_nofollow":0,"meta_noarchive":0,"props_was_rendered":0,"src_redirect":"","download_time_msec":603,"download_ttfb_msec":598,"download_size":19665}

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0.5 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Property	Value
URL	https://www.enjoyalgorithms.com/blog/introduction-to-seaborn-library-in-python/
Last Crawled	2026-05-18 18:43:53 (15 days ago)
First Indexed	2022-10-08 02:18:17 (3 years ago)
HTTP Status Code	200
Content
Meta Title	Introduction to Seaborn in Python
Meta Description	Seaborn is an open-source library built over Matplotlib and makes plots more appealing and understandable. It works excellently with data frames and pandas libraries. In this blog, we have discussed: 1) Advantages of Seaborn over Matplotlib library, 2) Installation process of Seaborn in Python 3) Various Data Plots using the Seaborn library.
Meta Canonical	null
Boilerpipe Text	heavy column, fetched on demand
Markdown	heavy column, fetched on demand
Readable Markdown	heavy column, fetched on demand
ML Classification
ML Categories	null
ML Page Types	null
ML Intent Types	null
Content Metadata
Language	en
Author	Shashank Gupta
Publish Time	not set
Original Publish Time	2022-10-08 02:18:17 (3 years ago)
Republished	No
Word Count (Total)	3,232
Word Count (Content)	3,112
Links
External Links	6
Internal Links	25
Technical SEO
Meta Nofollow	No
Meta Noarchive	No
JS Rendered	No
Redirect Target	null
Performance
Download Time (ms)	603
TTFB (ms)	598
Download Size (bytes)	19,665
Location
Host ID	108 (laksa108)
Partition ID	47
Root Hash	17796266760850149508
Unparsed URL	com,enjoyalgorithms!www,/blog/introduction-to-seaborn-library-in-python/ s443

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