Skip to main content

SE::AOL::Suggest - AOL search suggestions parser

Overview of AOL Suggest parser

A parser of search suggestions for keywords in AOL. With the SE::AOL::Suggest parser, you can automatically collect keyword databases from AOL search suggestions by query. Using the SE::AOL::Suggest parser, you can easily and quickly parse AOL suggestions by query.

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

SE::AOL::Suggest parser processing speed

You can use automatic query multiplication, substitution of subqueries from files, enumeration of alphanumeric combinations and lists to obtain the maximum possible number of results. Using result filtering, you can immediately clean up the result by removing all unnecessary garbage (using minus-words).

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

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

List of collected data

  • Number of results by query
  • Suggestions for the query

SE::AOL::Suggest parser collected data


  • Support for all AOL search operators (site: etc.)
  • Parses the maximum number of results returned by AOL - 100 pages with 20 items in the output

Usage scenarios

  • Collection of keyword databases

Query examples

  • Queries must be specified as search phrases, for example:
write essay
Speak in english
cheap essay

Query substitutions

You can use built-in macros to automatically substitute 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, specify a macro for substituting additional words from the Keywords.txt file, this method allows you to increase the variability of queries many times:

{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 operation.

For example, if the Keywords.txt file 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

Result output options

A-Parser supports flexible formatting of results thanks to the built-in Template Toolkit, which allows it to output results in any form, as well as in a structured form, such as CSV or JSON.

Exporting a list of suggestions

Similar to SE::Google::Suggest.

Outputting suggestions to a CSV table

Similar to SE::Google::Suggest.

Saving in SQL format

Result format:

[%  FOREACH p1.results;     "INSERT INTO serp VALUES('" _ query _ "', '";   suggest _ "')\n"; END  %]

Example 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

Similar to SE::Google::Suggest.

Result processing

A-Parser allows you to process results directly during parsing, in this section we have provided the most popular cases for the SE::AOL::Suggest parser.

Parse to level option

Similar to SE::Google::Suggest.

Result filtering (using minus-words)

Similar to SE::Google::Suggest.

Possible settings