Pinterest Suggest Parser Overview
Pinterest search suggestions parser. The Pinterest suggestions parser solves one of the main SEO tasks, namely, fast automated obtaining of an extended semantic core. Thanks to the SE::Pinterest::Suggest parser, you can automatically collect keyword databases from Pinterest search suggestions by query. Using the SE::Pinterest::Suggest parser, you can easily and quickly parse Pinterest suggestions by query.
Thanks to the multi-threaded work of A-Parser, the processing speed of queries can reach 6000 queries per minute, which on average allows you to receive up to 16000 results per minute.
You can use automatic query replication, 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 up the result by removing all unnecessary garbage (using minus-words).
The A-Parser functionality allows you to save the parsing settings of 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 that you need, thanks to the built-in powerful Template Toolkit template engine, 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
- Suggestions for the query
- Type of suggestions
- Deep parsing using the Parse to level function
- Selection of the type of suggestions that will be used for substitution when parsing in depth
- Collection of keyword databases
- Search phrases should be specified as queries, for example:
Speak in english
Cats and dogs
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, we will specify several main queries:
In the query format, we will specify a macro for substituting additional words from the Keywords.txt file, this method allows you to increase the variability of queries many times over:
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 operation.
For example, if the Keywords.txt file contains:
As a result, the substitution macro will turn 3 main queries into 6:
Result output options
A-Parser supports flexible result formatting thanks to the built-in Template Toolkit template engine, which allows it to output results in an arbitrary form, as well as in a structured form, for example, CSV or JSON.
Exporting a list of suggestions
Outputting suggestions to a CSV table
Saving in SQL format
[% FOREACH p1.results; "INSERT INTO serp VALUES('" _ query _ "', '"; suggest _ "')\n"; END %]
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
A-Parser allows you to process results directly during parsing, in this section we have provided the most popular cases for the SE::Pinterest::Suggest parser.
Parse to level option
Results filtering (using minus-words)
|Parameter name||Default value||Description|
|Follow suggests||Choosing the type of suggestions that will be used for deep parsing.|