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SE::Pinterest::Suggest - Pinterest Suggest Scraper

Overview of the parser

A parser for search suggestions by keywords in Pinterest. The Pinterest suggestions parser solves one of the main SEO tasks, namely the rapid automated acquisition of an expanded semantic core. Thanks to the SE::Pinterest::Suggest parser, you can automatically collect keyword databases from Pinterest search engine suggestions upon request. Using the SE::Pinterest::Suggest parser, you can easily and quickly parse Pinterest suggestions for a query.

Thanks to the multi-threaded operation of A-Parser, the query processing speed can reach 6000 queries per minute, which on average allows obtaining up to 16000 results per minute.

Parser overview: operation 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 results filtering you can immediately clean the result by removing all unnecessary clutter (using negative keywords).

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

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

Collected data

  • Suggestions for the query
  • Suggestion type

what data the SE::Pinterest::Suggest parser collects

Capabilities

  • Deep parsing using the Parse to level function
  • Selection of the suggestion type to be used for substitution during deep parsing

Use cases

  • Collection of keyword databases

Queries

Search phrases should be specified as queries, for example:

write essay
Football
Waterfall
Speak in english
Cats and dogs
forex
cheap essay

Query substitutions

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

essay
article
thesis

In the query format, we will specify a macro for substituting additional words from the Keywords.txt file; this method allows increasing query variability manifold:

{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:

buy
cheap

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 Toolkit template engine, which allows it to output results in arbitrary form, as well as in structured form, such as CSV or JSON

Exporting a list of suggestions

Same as in SE::Google::Suggest

Output to a CSV table

Same as in SE::Google::Suggest

Keyword competition

Same as in SE::Google

Saving in SQL format

Result format:

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

Result example:

INSERT INTO serp VALUES('write essay', 'write essay for me')
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 essays')
INSERT INTO serp VALUES('write essay', 'write essay conclusion')
INSERT INTO serp VALUES('write essay', 'write essay on covid 19')
INSERT INTO serp VALUES('write essay', 'write essay today')
INSERT INTO serp VALUES('write essay', 'write essays for money')
INSERT INTO serp VALUES('write essay', 'write essay online for free')
...

Dumping results to JSON

Same as in SE::Google::Suggest

Results processing

A-Parser allows processing results directly during parsing; in this section, we have provided the most popular cases for the SE::Pinterest::Suggest parser

Parse to level option

Same as in SE::Google::Suggest

Results filtering (using negative keywords)

Same as in SE::Google::Suggest

Possible settings

Parameter nameDefault valueDescription
Follow suggestsAllSelection of the suggestion type to be used for substitution during deep parsing