Module: CSVDecision::Decide Private

Defined in:
lib/csv_decision/decide.rb

Overview

This module is part of a private API. You should avoid using this module if possible, as it may be removed or be changed in the future.

Main module for searching the decision table looking for one or more matches

Class Method Summary collapse

Class Method Details

.decide(table:, input:, symbolize_keys:) ⇒ Hash

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Main method for making decisions.

Parameters:

  • table (CSVDecision::Table) —

    Decision table.

  • input (Hash) —

    Input hash (keys may or may not be symbolized)

  • symbolize_keys (true, false) —

    Set to false if keys are symbolized and it's OK to mutate the input hash. Otherwise a copy of the input hash is symbolized.

Returns:

  • (Hash) —

    Decision result.



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# File 'lib/csv_decision/decide.rb', line 33

def self.decide(table:, input:, symbolize_keys:)
  # Parse and transform the hash supplied as input
  parsed_input = Input.parse(table: table, input: input, symbolize_keys: symbolize_keys)

  # The decision object collects the results of the search and
  # calculates the final result
  decision = Decision.new(table: table, input: parsed_input)

  # table_scan(table: table, input: parsed_input, decision: decision)
  decision.scan(table: table, input: parsed_input)
end

.matches?(row:, input:, scan_row:) ⇒ Boolean

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Match the table row against the input hash.

Parameters:

  • row (Array) —

    Table row.

  • input (Hash{Symbol=>Object}) —

    Input hash data structure.

  • scan_row (ScanRow)

Returns:

  • (Boolean) —

    Returns true if a match, false otherwise.



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# File 'lib/csv_decision/decide.rb', line 17

def self.matches?(row:, input:, scan_row:)
  match = scan_row.match_constants?(row: row, scan_cols: input[:scan_cols])
  return false unless match

  return true if scan_row.procs.empty?

  scan_row.match_procs?(row: row, input: input)
end