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SE::AOL::Suggest - AOL Search Suggestions Scraper

Scraper Overview

Scraper for search suggestions by keywords in AOL. Thanks to the SE::AOL::Suggest scraper, you can automatically collect keyword databases from AOL search engine suggestions by query. Using the SE::AOL::Suggest scraper, you can easily and quickly scrape AOL suggestions by query.

Thanks to the multithreading work of A-Parser, the speed of processing requests can reach 4700 requests per minute, which on average allows obtaining up to 13500-14500 results per minute.

Overview: speed of operation

You can use automatic query multiplication, substitution of subqueries from files, iteration of alphanumeric combinations and lists to get the maximum possible number of results. Using result filtering, you can immediately clean up the result by removing all unnecessary junk (using negative keywords).

A-Parser functionality allows you to save scraping settings of the SE::AOL::Suggest scraper for further use (presets), set a scraping schedule, and much more.

Saving results is possible in the form and structure that you need, thanks to the built-in powerful template engine Template Toolkit which allows applying additional logic to the results and outputting data in various formats, including JSON, SQL, and CSV.

Collected Data

  • Number of results by query
  • Suggestions for the query

what data does the SE::AOL::Suggest scraper collect


  • Support for all AOL search operators (site:, etc.)
  • Scrapes the maximum number of results provided by AOL - 100 pages of 20 items each in the search results

Use Cases

  • Collection of keyword databases


As queries, you need to specify search phrases, for example:

write essay
Speak in english
cheap essay

Query Substitutions

You can use built-in macros for automatic substitution of subqueries from files, for example, we want to add some list of other words to each query, let's specify several main queries:


In the query format, we will specify a macro for substituting additional words from the file Keywords.txt, this method allows to increase the variability of queries many times over:

{subs:Keywords} $query 

This macro will create as many additional queries as there are in the file for each original search query, which in total will give [number of original queries (domains)] x [number of queries in the Keywords file] = [total number of queries] as a result of the macro's work.

For example, if the file Keywords.txt contains:


As a result, the substitution macro will turn 3 main queries into 6:

buy essay
cheap essay
buy article
cheap article
buy thesis
cheap thesis

Output Results Examples

A-Parser supports flexible result formatting thanks to the built-in template engine Template Toolkit, which allows it to output results in an arbitrary form, as well as in a structured one, for example, CSV or JSON

Exporting a List of Suggestions

Similar to SE::Google::Suggest.

Output in a CSV Table

Similar to SE::Google::Suggest.

Saving in SQL Format

Result format:

[% FOREACH results;
"INSERT INTO serp VALUES('" _ query _ "', '"; suggest _ "')\n";
END %]

Example of result:

INSERT INTO serp VALUES('write essay', 'write essay for me')
INSERT INTO serp VALUES('write essay', 'write essay')
INSERT INTO serp VALUES('write essay', 'write essay online')
INSERT INTO serp VALUES('write essay', 'write essay for you')
INSERT INTO serp VALUES('write essay', 'write essay free')
INSERT INTO serp VALUES('write essay', 'write essay conclusion')
INSERT INTO serp VALUES('write essay', 'write essay today')
INSERT INTO serp VALUES('write essay', 'write essays for money')

Dumping results to JSON

Similarly as in SE::Google::Suggest.

Results processing

A-Parser allows processing results directly during scraping, in this section we have provided the most popular cases for the scraper SE::AOL::Suggest

Parse to level option

Similarly as in SE::Google::Suggest.

Filtering results (using negative keywords)

Similarly as in SE::Google::Suggest.

Possible settings