# This script reads OpenStudio_standards.xlsx # and creates a JSON file containing all the information require 'json' require 'rubyXL' require 'csv' class String def snake_case downcase.gsub(' ', '_').gsub('-', '_') end end # Convert OpenStudio_Standards.xlsx to a series # of JSON files for easier consumption. class Hash def sort_by_key_updated(recursive = false, &block) self.keys.sort(&block).reduce({}) do |seed, key| seed[key] = self[key] if recursive && seed[key].is_a?(Hash) seed[key] = seed[key].sort_by_key(true, &block) elsif recursive && seed[key].is_a?(Array) && seed[key][0].is_a?(Hash) # Sort by the set of unique properties uniq_props = unique_properties(key) if uniq_props.size > 0 # Temporarily replace real values with placeholders for sorting nil_placeholder = 'zzzz' true_placeholder = 'TRUETRUETRUE' false_placeholder = 'FALSEFALSEFALSE' seed[key].each do |item| item.keys.each do |key2| if item[key2].nil? item[key2] = nil_placeholder elsif [true].include?(item[key2]) item[key2] = true_placeholder elsif [false].include?(item[key2]) item[key2] = false_placeholder elsif item[key2].is_a?(String) && /(\d|\.)+E\d/.match(item[key2]) # Replace scientific notation strings with floats item[key2] = item[key2].to_f end end end # Sort seed[key] = seed[key].sort_by do |hsh| sort_order = [] uniq_props.each do |prop| if hsh.has_key?(prop) sort_order << hsh[prop] end end sort_order end # Replace placeholders with real values seed[key].each do |item| item.keys.each do |key2| if item[key2] == nil_placeholder item[key2] = nil elsif item[key2] == true_placeholder item[key2] = true elsif item[key2] == false_placeholder item[key2] = false end end end else seed[key] = seed[key] end end seed end end end # Defines the set of properties that should be unique across all objects of the same type. # This set is used for checking for duplicate objects and for sorting objects in the JSON files. def unique_properties(sheet_name) return case sheet_name when 'templates', 'standards', 'climate_zone_sets', 'constructions', 'curves', 'fans' ['name'] when 'prm_constructions' ['template', 'name'] when 'prm_exterior_lighting' ['template'] when 'materials' ['name', 'code_category'] when 'space_types', 'space_types_lighting', 'space_types_rendering_color', 'space_types_ventilation', 'space_types_occupancy', 'space_types_infiltration', 'space_types_equipment', 'space_types_thermostats', 'space_types_swh', 'space_types_exhaust' ['template', 'building_type', 'space_type'] when 'exterior_lighting' ['exterior_lighting_zone_number', 'template'] when 'schedules' ['name', 'day_types', 'start_date', 'end_date'] when 'construction_properties' ['template', 'climate_zone_set', 'operation_type', 'intended_surface_type', 'standards_construction_type', 'building_category', 'orientation', 'minimum_percent_of_surface', 'maximum_percent_of_surface'] when 'boilers' ['template', 'fluid_type', 'fuel_type', 'condensing', 'condensing_control', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'chillers' ['template', 'cooling_type', 'condenser_type', 'compressor_type', 'absorption_type', 'variable_speed_drive', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'furnaces' ['template', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'heat_rejection' ['template', 'equipment_type', 'fan_type', 'start_date', 'end_date'] when 'water_source_heat_pumps' ['template', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'water_source_heat_pumps_heating' ['template', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'heat_pumps' ['template', 'cooling_type', 'heating_type', 'subcategory', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'heat_pumps_heating' ['template', 'cooling_type', 'subcategory', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'unitary_acs' ['template', 'cooling_type', 'heating_type', 'subcategory', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'water_heaters' ['template', 'fuel_type', 'minimum_capacity', 'maximum_capacity', 'start_date', 'end_date'] when 'elevators' ['template', 'building_type'] when 'refrigeration_system_lineup', 'refrigeration_system' ['template', 'building_type', 'size_category', 'system_type'] when 'refrigerated_cases' ['template', 'size_category', 'case_type', 'case_category'] when 'refrigeration_condenser' ['template', 'building_type', 'system_type', 'size_category'] when 'refrigeration_walkins' ['template', 'size_category', 'walkin_type'] when 'refrigeration_compressors' ['template', 'compressor_name', 'compressor_type'] when 'economizers' ['template', 'climate_zone', 'data_center'] when 'prm_economizers' ['template', 'climate_ID'] when 'motors' ['template', 'number_of_poles', 'type', 'synchronous_speed', 'minimum_capacity', 'maximum_capacity'] when 'ground_temperatures' ['building_type', 'template', 'climate_zone'] when 'hvac_inference' ['template', 'size_category', 'heating_source', 'cooling_source', 'delivery_type'] when 'size_category' ['template', 'building_category', 'minimum_floors', 'maximum_floors', 'minimum_area', 'maximum_area'] when 'construction_sets' ['template', 'building_type', 'space_type', 'is_residential'] when 'parking', 'entryways' ['building_type'] when 'prototype_inputs' ['template', 'building_type', 'hvac_system'] when 'climate_zones' ['name', 'standard'] when 'energy_recovery' ['template', 'climate_zone', 'under_8000_hours', 'nontransient_dwelling', 'enthalpy_recovery_ratio_design_conditions'] when 'space_types_lighting_control' ['template', 'building_type', 'space_type'] when 'prm_hvac_bldg_type' ['template', 'hvac_building_type'] when 'prm_swh_bldg_type' ['template', 'swh_building_type'] when 'prm_wwr_bldg_type' ['template', 'wwr_building_type'] when 'prm_baseline_hvac' ['template', 'hvac_building_type', 'bldg_area_min', 'bldg_area_max', 'bldg_flrs_min', 'bldg_flrs_max'] when 'prm_heat_type' ['template', 'hvac_building_type', 'climate_zone'] when 'prm_interior_lighting' ['template', 'lpd_space_type'] when 'lpd_space_type' ['template', 'lpd_space_type'] else [] end end # Shortens JSON file path names to avoid Windows build errors when # compiling the OpenStudio CLI def shorten_sheet_name(sheet_name) short_sheet_name = sheet_name short_sheet_name = short_sheet_name.gsub('refrigeration_system_lineup', 'ref_lnup') # 19 saved short_sheet_name = short_sheet_name.gsub('refrigerated_cases', 'ref_cases') # 9 saved short_sheet_name = short_sheet_name.gsub('exterior_lighting', 'ext_ltg') # 10 saved short_sheet_name = short_sheet_name.gsub('space_types', 'spc_typ') # 10 saved return short_sheet_name end # Determine the directory of the data based on the spreadsheet name def standard_parent_directory_from_spreadsheet_title(spreadsheet_title) data_directory = spreadsheet_title.downcase.gsub('openstudio_standards-', '').gsub(/\(\w*\)/, '').split('-').first # puts "Extracting standard parent directory from spreadsheet title #{spreadsheet_title} = #{data_directory}" return data_directory end # Determine the directory name from the template def standard_directory_name_from_template(template) directory_name = template.downcase.gsub(/\W/, '_').gsub('90_1', 'ashrae_90_1') # puts "Extracting standard directory from template #{template} = #{directory_name}" return directory_name end # checks whether your authorization credentials are set up to access the spreadsheets # @return [Boolean] returns true if api is working, false if not def check_google_drive_configuration require 'google_drive' client_config_path = File.join(Dir.home, '.credentials', "client_secret.json") unless File.exists? client_config_path puts "Unable to locate client_secret.json file at #{client_config_path}." return false end puts 'attempting to access spreadsheets...' puts 'if you get an SSL error, disconnect from the VPN and try again' session = GoogleDrive::Session.from_config(client_config_path) # Gets list of remote files session.files.each do |file| puts file.title if file.title.include? 'OpenStudio' end puts 'Spreadsheets accessed successfully' return true end # Downloads the OpenStudio_Standards.xlsx from Google Drive # @note This requires you to have a client_secret.json file saved in your # username/.credentials folder. To get one of these files, please contact # marley.praprost@nrel.gov def download_google_spreadsheets(spreadsheet_titles) require 'google_drive' client_config_path = File.join(Dir.home, '.credentials', "client_secret.json") unless File.exists? client_config_path puts "Unable to locate client_secret.json file at #{client_config_path}." return false end session = GoogleDrive::Session.from_config(client_config_path) # Gets list of remote files session.files.each do |file| if spreadsheet_titles.include?(file.title) puts "Found #{file.title}" file.export_as_file("#{File.dirname(__FILE__)}/#{file.title}.xlsx") puts "Downloaded #{file.title} to #{File.dirname(__FILE__)}/#{file.title}.xlsx" end end return true end def exclusion_list file_path = "#{__dir__}/exclude_list.csv" csv_file = CSV.read(file_path, headers:true) csv_data = csv_file.map {|row| row.to_hash} exclusion_array = { "os_stds" => { "worksheets" => [], "columns" => [] }, "data_lib" => { "worksheets" => [], "columns" => [] } } csv_file.each do |row| if row['columns'] == 'all' exclusion_array['os_stds']['worksheets'] << row['worksheet'] if row['exclude_from_os_stds'] == 'TRUE' exclusion_array['data_lib']['worksheets'] << row['worksheet'] if row['exclude_from_data_lib'] == 'TRUE' else exclusion_array['os_stds']['columns'] << row['columns'] if row['exclude_from_os_stds'] == 'TRUE' exclusion_array['data_lib']['columns'] << row['columns'] if row['exclude_from_data_lib'] == 'TRUE' end end return exclusion_array end def parse_units(unit) # useless_units = [nil, 'fraction', '%', 'COP_68F', 'COP_47F', '%/gal', 'Btu/hr/Btu/hr', 'Btu/hr/gal', 'BTU/hr/ft', 'W/BTU/h'] units_to_skip = [nil, 'fraction', '%', 'EER', '>23m^2', '>84m^2', '<23m^2', '<84m^2'] unit_parsed = nil if not units_to_skip.include?(unit) if unit == '%/gal' unit = '1/gal' end unit_parsed = OpenStudio.createUnit(unit) if unit_parsed.empty? unit_parsed = "Not recognized by OpenStudio" else unit_parsed = unit_parsed.get() end end return unit_parsed end # Exports spreadsheet data to data jsons, nested by the standards templates # # @param spreadsheet_titles # @param dataset_type [String] valid choices are 'os_stds' or 'data_lib' # 'os_stds' updates json files in openstudio standards, while 'data_lib' exports 90.1 jsons for the data library def export_spreadsheet_to_json(spreadsheet_titles, dataset_type: 'os_stds') if dataset_type == 'data_lib' standards_dir = File.expand_path("#{__dir__}/../../data/standards/export") skip_list = exclusion_list['data_lib'] skip_list['templates'] = ['DOE Ref Pre-1980', 'DOE Ref 1980-2004', 'NREL ZNE Ready 2017', 'ZE AEDG Multifamily', 'OEESC 2014', 'ICC IECC 2015', 'ECBC 2017', '189.1-2009'] else standards_dir = File.expand_path("#{__dir__}/../../lib/openstudio-standards/standards") skip_list = exclusion_list['os_stds'] skip_list['templates'] = [] end worksheets_to_skip = skip_list['worksheets'] cols_to_skip = skip_list['columns'] templates_to_skip = skip_list['templates'] # List of columns that are boolean # (rubyXL returns 0 or 1, will translate to true/false) bool_cols = [] bool_cols << 'hx' bool_cols << 'data_center' bool_cols << 'under_8000_hours' bool_cols << 'nontransient_dwelling' bool_cols << 'u_value_includes_interior_film_coefficient' bool_cols << 'u_value_includes_exterior_film_coefficient' warnings = [] duplicate_data = [] spreadsheet_titles.each do |spreadsheet_title| # Path to the xlsx file xlsx_path = "#{__dir__}/#{spreadsheet_title}.xlsx" unless File.exist?(xlsx_path) warnings << "could not find spreadsheet called #{spreadsheet_title}" next end puts "Parsing #{xlsx_path}" # Open workbook workbook = RubyXL::Parser.parse(xlsx_path) puts "After parse workbook" # Find all the template directories that match the search criteria embedded in the spreadsheet title dirs = spreadsheet_title.gsub('OpenStudio_Standards-', '').gsub(/\(\w*\)/, '').split('-') new_dirs = [] dirs.each { |d| d == 'ALL' ? new_dirs << '*' : new_dirs << "*#{d}*" } glob_string = "#{standards_dir}/#{new_dirs.join('/')}" puts "--spreadsheet title embedded search criteria: #{glob_string} yields:" # template_dirs = Dir.glob(glob_string).select { |f| File.directory?(f) && !f.include?('data') && !f.include?('prm')} template_dirs = Dir.glob(glob_string).select { |f| File.directory?(f) && !f.include?('data')} template_dirs.each do |template_dir| puts "----#{template_dir}" end # Export each tab to a hash, where the key is the sheet name # and the value is an array of objects standards_data = {} list_of_sheets = [] list_of_names = [] list_of_units = [] list_of_OS_okay_units = [] workbook.worksheets.each do |worksheet| sheet_name = worksheet.sheet_name.snake_case # Skip the specified worksheets if worksheets_to_skip.include?(sheet_name) puts "Skipping #{sheet_name}" next else puts "Processing #{sheet_name}" end # All spreadsheets must have headers in row 3 # and data from roworksheet 4 onward. header_row = 2 # Base 0 # Get all data # extract_data was deprecated in rubyXL # inputting the method here https://github.com/weshatheleopard/rubyXL/issues/201 all_data = worksheet.sheet_data.rows.map { |row| row.cells.map { |c| c && c.value() } unless row.nil? } # Get the header row data header_data = all_data[header_row] # Format the headers and parse out units (in parentheses) headers = [] header_data.each do |header_string| break if header_string.nil? header = {} header["name"] = header_string.gsub(/\(.*\)/, '').strip.snake_case header_unit_parens = header_string.scan(/\(.*\)/)[0] list_of_sheets << sheet_name list_of_names << header_string.gsub(/\(.*\)/, '').strip.snake_case if header_unit_parens.nil? header["units"] = nil list_of_units << nil list_of_OS_okay_units << nil else header["units"] = header_unit_parens.gsub(/\(|\)/, '').strip list_of_units << header_unit_parens.gsub(/\(|\)/, '').strip list_of_OS_okay_units << parse_units(header_unit_parens.gsub(/\(|\)/, '').strip) end headers << header end puts "--found #{headers.size} columns" # Loop through all rows and export # data for the row to a hash. objs = [] for i in (header_row + 1)..(all_data.size - 1) row = all_data[i] # Stop when reach a blank row break if row.nil? # puts "------row #{i} = #{row}" obj = {} # Check if all cells in the row are null all_null = true for j in 0..headers.size - 1 # Flip the switch if a value is found unless row[j].nil? all_null = false end end # Skip recording empty rows next if all_null == true # Store values from appropriate columns for j in 0..headers.size - 1 val = row[j] # Don't record nil values # next if val.nil? # Flip the switch if a value is found unless val.nil? all_null = false end # Skip specified columns next if cols_to_skip.include?(headers[j]['name']) # Convert specified columns to boolean if bool_cols.include?(headers[j]['name']) if val == 1 val = true elsif val == 0 val = false else val = nil end end # Convert date columns to standard format if headers[j]['name'].include?('_date') if val.is_a?(DateTime) val = val.to_s else begin val = DateTime.parse(val).to_s rescue ArgumentError, TypeError puts "ERROR - value '#{val}', class #{val.class} in #{sheet_name}, row #{i}, col #{j} is not a valid date" return false end end end # Record the value obj[headers[j]['name']] = val # Skip recording units for unitless values next if headers[j]['units'].nil? # Record the units # obj["#{headers[j]['name']}_units"] = headers[j]['units'] end # Store the array of objects # special cases for some types if sheet_name == 'climate_zone_sets' new_obj = {} new_obj['name'] = obj['name'] items = [] obj.each do |key, val2| # Skip the key next if key == 'name' # Skip blank climate zone values next if val2.nil? items << val2 end new_obj['climate_zones'] = items objs << new_obj elsif sheet_name == 'constructions' or sheet_name == 'prm_constructions' new_obj = {} new_obj['name'] = obj['name'] items = [] obj.each do |key, val2| # Skip the key next if key == 'name' # Put materials into an array, # record other fields normally if key.include?('material') # Skip blank material values next if val2.nil? items << val2 else new_obj[key] = val2 end end new_obj['materials'] = items objs << new_obj elsif sheet_name == 'schedules' new_obj = {} new_obj['name'] = obj['name'] items = [] obj.each do |key, val2| # Skip the key next if key == 'name' # Put materials into an array, # record other fields normally if key.include?('hr') # Skip blank hourly values next if val2.nil? items << val2 else new_obj[key] = val2 end end new_obj['values'] = items objs << new_obj else objs << obj end end # Report how many objects were found puts "--found #{objs.size} rows" # Skip to the next sheet if no objects were found if objs.size.zero? warnings << "did not export #{sheet_name} in #{spreadsheet_title} because no rows were found" next end # Save the objects to the hash standards_data[sheet_name] = objs end filename_out = spreadsheet_title.gsub(/[()]/, '') # CSV.open("metadata.csv", "wb") {|csv| headers.to_a.each {|elem| csv << elem} } # list_metadata = [list_of_sheets, list_of_names, list_of_units, list_of_OS_okay_units].transpose list_metadata = [list_of_sheets, list_of_names, list_of_units].transpose list_metadata.insert(0, ['Sheet', 'Name', 'Unit']) # [1, 2, 2.5, 3, 4] File.write("data/standards/metadata_units_#{filename_out}.csv", list_metadata.map(&:to_csv).join) # Check for duplicate data in space_types_* sheets standards_data.each_pair do |sheet_name, objs| skip_duplicate_check = [] next if skip_duplicate_check.include?(sheet_name) # Defines the set of properties that should be unique across all objects of the same type unique_props = unique_properties(sheet_name) # Ensure that a set of properties was defined if unique_props.empty? puts "--ERROR no unique set of properties was defined for #{sheet_name}, cannot check for duplicates" return false end # Check for duplicates using unique property set puts "Checking #{sheet_name} for duplicates based on columns: #{unique_props.join(', ')}" found_objs = {} objs.each_with_index do |obj, i| unique_aspects = [] unique_props.each { |prop| unique_aspects << obj[prop] } unique_aspect = unique_aspects.join('|') if found_objs.include?(unique_aspect) status = 'different' status = 'same' if obj.to_s == found_objs[unique_aspect] duplicate_data << [spreadsheet_title, sheet_name, i, status, unique_aspect] end found_objs[unique_aspect] = obj.to_s end end # Merge all space_types_* sheets into a single space_types sheet space_types = {} standards_data.each_pair do |sheet_name, objs| next unless sheet_name.include?('space_types_') puts "Merging #{sheet_name} into space_types" objs.each do |obj| name = "#{obj['template']}|#{obj['building_type']}|#{obj['space_type']}" if space_types[name].nil? space_types[name] = obj else space_types[name].merge!(obj) end end # Remove space_types_* from the standards_data standards_data.delete(sheet_name) end standards_data['space_types'] = space_types.values unless space_types.empty? # Export each set of objects to a JSON file standards_data.each_pair do |sheet_name, objs| puts "Writing #{sheet_name} which has #{objs.size} objects" # Record the number of files that were exported for error checking jsons_written = 0 # Split template-specific datasets into separate files. # Store common/shared datasets under a higher-level folder parent_dir = standard_parent_directory_from_spreadsheet_title(spreadsheet_title) if objs.first.has_key?('template') puts '--template-specific, writing a file for each template with just that templates objects' # Split objects by template templates_to_objects = {} objs.each do |obj| temp = obj['template'] if templates_to_objects[temp] templates_to_objects[temp] << obj else templates_to_objects[temp] = [obj] end end # Write out a file for each template with the objects for that template. templates_to_objects.each_pair do |template, objs| next if template == 'Any' next if templates_to_skip.include?(template) template_dir_name = standard_directory_name_from_template(template) # Sort the objects sorted_objs = {sheet_name => objs}.sort_by_key_updated(true) {|x, y| x.to_s <=> y.to_s} # Also check directly underneath the parent directory if /prm/.match(template_dir_name) && !/prm/.match(parent_dir) child_dir = "#{standards_dir}/#{parent_dir}_prm/#{template_dir_name}" else child_dir = "#{standards_dir}/#{parent_dir}/#{template_dir_name}" end additional_dirs = [] additional_dirs << child_dir if Dir.exist?(child_dir) possible_template_dirs = template_dirs + additional_dirs puts "Additional dir = #{child_dir}" wrote_json = false possible_template_dirs.each do |template_dir| last_dir = template_dir.split('/').last next unless last_dir == template_dir_name data_dir = "#{template_dir}/data" Dir.mkdir(data_dir) unless Dir.exist?(data_dir) json_path = "#{data_dir}/#{template_dir_name}.#{shorten_sheet_name(sheet_name)}.json" if json_path.size > 256 puts "--ERROR the JSON path is #{json_path.size - 256} characters longer than the Window 256 character limit, cannot write to #{json_path}" return false end File.open(json_path, 'w:UTF-8') do |file| file << JSON.pretty_generate(sorted_objs) end puts "--successfully generated #{json_path}" jsons_written += 1 wrote_json = true end unless wrote_json warnings << "did not export data for template #{template} from #{sheet_name} in #{spreadsheet_title} because there was no valid directory matching '#{template_dir_name}' based on the spreadsheet title embedded search criteria" end end # Stop if no objects on this sheet list the template called 'Any' next if templates_to_objects['Any'].nil? # Sort the objects sorted_objs = {sheet_name => templates_to_objects['Any']}.sort_by_key_updated(true) {|x, y| x.to_s <=> y.to_s} # Write all objects that use the 'Any' template to the parent directories wrote_any_template_json = false template_dirs.uniq.each do |template_dir| data_dir = "#{template_dir}/data" Dir.mkdir(data_dir) unless Dir.exist?(data_dir) json_path = "#{data_dir}/Any.#{shorten_sheet_name(sheet_name)}.json" if json_path.size > 256 puts "--ERROR the JSON path is #{json_path.size - 256} characters longer than the Window 256 character limit, cannot write to #{json_path}" return false end File.open(json_path, 'w:UTF-8') do |file| file << JSON.pretty_generate(sorted_objs) end puts "--successfully generated #{json_path}" jsons_written += 1 wrote_any_template_json = true end unless wrote_any_template_json warnings << "did not export data for template 'Any' from #{sheet_name} in #{spreadsheet_title} because there was no valid directory to store 'Any' template data." end else puts '--not template-specific, writing a file with all objects for each template specified by search criteria' # Sort the objects sorted_objs = {sheet_name => objs}.sort_by_key_updated(true) {|x, y| x.to_s <=> y.to_s} # Write out a file for each template with all objects on the sheet template_dirs.each do |template_dir| data_dir = "#{template_dir}/data" Dir.mkdir(data_dir) unless Dir.exist?(data_dir) json_path = "#{data_dir}/#{parent_dir}.#{shorten_sheet_name(sheet_name)}.json" if json_path.size > 256 puts "--ERROR the JSON path is #{json_path.size - 256} characters longer than the Window 256 character limit, cannot write to #{json_path}" return false end File.open(json_path, 'w:UTF-8') do |file| file << JSON.pretty_generate(sorted_objs) end puts "--successfully generated #{json_path}" jsons_written += 1 end end # Confirm that at least 1 JSON file was written per sheet if jsons_written.zero? puts "--ERROR no JSON files were written for #{sheet_name} even though objects were found. Check sheet contents or delete rows." # return false end end end # Print out all the warnings in one place puts "\n**** WARNINGS ****" warnings.each { |w| puts "WARNING #{w}" } # Write duplicates out to file if duplicate_data.size > 0 duplicate_log_path = "#{__dir__}/openstudio_standards_duplicates_log.csv" puts "\n**** DUPLICATES ****" puts "There were #{duplicate_data.size} duplicate objects found. See detail in: #{duplicate_log_path}" CSV.open(duplicate_log_path, 'wb') do |csv| csv << ['Spreadsheet Name', 'Worksheet Name', 'Object Index in Worksheet', 'Similarity of Duplicate', 'Duplicate Object'] duplicate_data.each do |duplicate| csv << duplicate end end # Open the duplicates csv file if Gem.win_platform? system("start #{File.expand_path(duplicate_log_path)}") else system("open #{File.expand_path(duplicate_log_path)}") end end return true end