Menambahkan Data Historis dengan API R Oanda

Sebagai tindak lanjut dari sebelumnya pasca, yang membahas tentang penambahan data, skrip di bawah ini menambahkan data historis ke rekaman data yang diasumsikan sudah ada.

% cd to the hourly data directory
setwd("~/Documents/octave/oanda_data/hourly")

all_current_historical_data_list = read.table("instrument_hourly_update_file",header=FALSE,sep="",colClasses=c("character","Date","numeric") )

for( ii in 1 : nrow( all_current_historical_data_list ) ) {  

   instrument = all_current_historical_data_list[ ii , 1 ]
   
   current_ohlc_record = read.table( file = paste( instrument , "raw_OHLC_hourly" , sep = "_" ) , header = FALSE , na = "" , sep = "," ,
                                      stringsAsFactors = FALSE )
   
   current_ohlc_record_begin_date_time = as.character( current_ohlc_record[ 1 , 1 ] ) % get the date/time value to be matched
   last_date_ix = as.Date( current_ohlc_record[ 1 , 1 ] )                             % the end date for new data to be downloaded             
   
   % last 40 weeks of hourly data approx = 5000 hourly bars            
   begin_date_ix = as.Date( last_date_ix - 280 )                      % the begin date for new data to be downloaded

   % download the missing historical data from begin_date_ix to last_date_x.
   new_historical_data = HisPricesDates( Granularity = "H1", DayAlign, TimeAlign, AccountToken, instrument,
                          begin_date_ix , last_date_ix + 2 ) % +2 to ensure that the end of the new downloaded data will
                                                             % overlap with the beginning of current_ohlc_record
  
   % having ensured no data is missed by overlaping with the current_ohlc_record, delete duplicated OHLC information
   new_historical_data_date_times = as.character( new_historical_data[ , 1 ] ) % vector to search for the above date value
   
   ix = charmatch( current_ohlc_record_begin_date_time , new_historical_data_date_times ) % get the matching index value

   % delete that part of new_historical_data which is already contained in filename
   new_historical_data = new_historical_data[ -( ix : nrow( new_historical_data ) ) , ]
   
   % before prepending new_historical_data in front of current_ohlc_record, need to give names to current_ohlc_record as
   % rbind needs to bind by named attributes
   names( current_ohlc_record ) = names( new_historical_data )
   
   % see https://stackoverflow.com/questions/11785710/rbind-function-changing-my-entries for reason for following
   % also need to coerce that dates in new_historical_data from POSIXct to character
   new_historical_data$TimeStamp = as.character( new_historical_data$TimeStamp )
   
   % and now prepend new_historical_data to current_ohlc_record
   combined_records = rbind( new_historical_data , current_ohlc_record , stringsAsFactors = FALSE )
   
   % and coerce character dates back to a POSIXct date format prior to printing
   combined_records$TimeStamp = as.POSIXct( combined_records$TimeStamp )
   
   % write combined_records to file
   write.table( combined_records , file = paste( instrument , "raw_OHLC_hourly" , sep = "_" ) , row.names = FALSE , 
                col.names = FALSE , sep = "," )
   
   added_data_length = nrow( new_historical_data ) % length of added new data

   % and amend Instrument_update file with lastest update information
   all_current_historical_data_list[ ii , 3 ] = all_current_historical_data_list[ ii , 3 ] + added_data_length
   
   % write updated Instrument_update_file to file
   write.table( all_current_historical_data_list , file = "instrument_hourly_update_file" , row.names = FALSE , col.names = FALSE )

} % end of for all_current_historical_data_list loop

Seperti yang dijelaskan dalam posting sebelumnya, fungsi HisPricesDates dipanggil untuk melakukan pengunduhan aktual, dengan tanggal yang relevan untuk input fungsi dibaca dan dihitung dari berkas data yang ada (saya telah membuat kode keras untuk data per jam tetapi ini, tentu saja, dapat diubah atau diimplementasikan sebagai input pengguna dalam sesi R). Seperti biasa, saya telah mengomentari skrip untuk menjelaskan apa yang sedang terjadi.

Namun, satu peringatan penting adalah diasumsikan bahwa sebenarnya ada beberapa data Oanda yang dapat diunduh dan ditambahkan sebelum tanggal paling awal dalam catatan yang ada, dan tidak ada pemeriksaan asumsi ini. Oleh karena itu, skrip mungkin gagal dengan cara yang tidak terduga jika seseorang mencoba menjangkau terlalu jauh ke belakang dalam sejarah untuk data yang dapat ditambahkan.