🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 148 (from laksa166)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa148.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 = 27 AND (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://scikit-learn.org/stable/modules/model_evaluation.html\')), getAhrefsUnparsedNoserviceFromURL(\'https://scikit-learn.org/stable/modules/model_evaluation.html\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/scikit-learn.org\/stable\/modules\/model_evaluation.html","crawl_time":1779905558,"first_indexed_time":1535405033,"http_code":200,"src_unparsed":"org,scikit-learn!\/stable\/modules\/model_evaluation.html s443","src_root_hash":"6052685795207125548","history_drop_reason":null,"meta_title":"3.4. Metrics and scoring: quantifying the quality of predictions — scikit-learn 1.8.0 documentation","meta_descriptions":["Which scoring function should I use?: Before we take a closer look into the details of the many scores and evaluation metrics, we want to give some guidance, inspired by statistical decision theory..."],"meta_canonical":null,"ml_categories_json":"{\"\/Science\":403,\"\/Computers_and_Electronics\":324,\"\/Computers_and_Electronics\/Software\":297,\"\/Computers_and_Electronics\/Software\/Educational_Software\":237,\"\/Science\/Mathematics\":221,\"\/Science\/Mathematics\/Statistics\":220,\"\/Jobs_and_Education\":191,\"\/Jobs_and_Education\/Education\":190,\"\/Jobs_and_Education\/Education\/Computer_Education\":106}","ml_types_json":"{\"\/Document\":599,\"\/Document\/Manual\":483}","ml_intent_types_json":"{\"Informational\":999}","meta_language":"en","attrs_author":null,"attrs_publish_time":0,"attrs_original_publish_time":1535405033,"attrs_is_republished":0,"attrs_nr_words":"21141","attrs_boilerpipe_nr_words":"19632","body_ext_links_number":88,"body_int_links_number":181,"meta_nofollow":0,"meta_noarchive":0,"props_was_rendered":1,"src_redirect":"","download_time_msec":60,"download_ttfb_msec":57,"download_size":64192}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📍

LOCATION

Host 148 · Partition 27

laksa148

6052685795207125548

📄

INDEXABLE

✅

CRAWLED

7 days ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0.2 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

Page Details

Property

Value

URL

https://scikit-learn.org/stable/modules/model_evaluation.html

Last Crawled

2026-05-27 18:12:38 (7 days ago)

First Indexed

2018-08-27 21:23:53 (7 years ago)

HTTP Status Code

200

Content

Meta Title

3.4. Metrics and scoring: quantifying the quality of predictions — scikit-learn 1.8.0 documentation

Meta Description

Which scoring function should I use?: Before we take a closer look into the details of the many scores and evaluation metrics, we want to give some guidance, inspired by statistical decision theory...

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

/Science		40.3%
/Computers_and_Electronics		32.4%
/Computers_and_Electronics/Software		29.7%
/Computers_and_Electronics/Software/Educational_Software		23.7%
/Science/Mathematics		22.1%
/Science/Mathematics/Statistics		22.0%
/Jobs_and_Education		19.1%
/Jobs_and_Education/Education		19.0%
/Jobs_and_Education/Education/Computer_Education		10.6%

Raw JSON

{
    "/Science": 403,
    "/Computers_and_Electronics": 324,
    "/Computers_and_Electronics/Software": 297,
    "/Computers_and_Electronics/Software/Educational_Software": 237,
    "/Science/Mathematics": 221,
    "/Science/Mathematics/Statistics": 220,
    "/Jobs_and_Education": 191,
    "/Jobs_and_Education/Education": 190,
    "/Jobs_and_Education/Education/Computer_Education": 106
}

ML Page Types

/Document		59.9%
/Document/Manual		48.3%

Raw JSON

{
    "/Document": 599,
    "/Document/Manual": 483
}

ML Intent Types

Informational

99.9%

Raw JSON

{
    "Informational": 999
}

Content Metadata

Language

Author

null

Publish Time

not set

Original Publish Time

2018-08-27 21:23:53 (7 years ago)

Republished

Word Count (Total)

21,141

Word Count (Content)

19,632

Links

External Links

Internal Links

181

Technical SEO

Meta Nofollow

Meta Noarchive

JS Rendered

Yes

Redirect Target

null

Performance

Download Time (ms)

TTFB (ms)

Download Size (bytes)

64,192

Location

Host ID

148 (laksa148)

Partition ID

Root Hash

6052685795207125548

Unparsed URL

org,scikit-learn!/stable/modules/model_evaluation.html s443