Read a table of fixed width formatted data of different types into a data.frame for each type. This package is for people that need to load a file that contains lines of different fixed with format. Think of it as an extension to the read.fwf function. One use-case is reading a log file containing messages of a fixed-width text protocol.

An example

library(multifwf)

# Create a temp file with a few lines from a simple exchange protocol.
ff <- tempfile()
cat(file = ff, 
    '10:15:03:279NOSLMT0000666    EVILCORP00010.77SomeClientId    SomeAccountId   ',
    '10:15:03:793OC000001BLMT0000666    EVILCORP00010.77SomeClientId    SomeAccountId   ',
    '10:17:45:153NOBLMT0000666    EVILCORP00001.10AnotherClientId AnotherAccountId',
    '10:17:45:487RJAnotherClientId 004price out of range                              ',
    '10:18:28:045NOBLMT0000666    EVILCORP00011.00AnotherClientId AnotherAccountId',
    '10:18:28:472OC000002BLMT0000666    EVILCORP00011.00AnotherClientId AnotherAccountId',
    '10:18:28:642TR0000010000010000666    EVILCORP00010.77',
    '10:18:28:687TR0000010000020000666    EVILCORP00010.77', 
    sep = '\n')

# Create a list of specs. Each item contains the specification for each message
# type of this simple protocol.
specs <- list()
specs[['newOrder']] = data.frame(widths    = c(12, 2, 1, 3, 7, 
                                                12, 8, 16, 16), 
                                  col.names = c('timestamp', 'msgType', 'side', 'type', 'volume', 
                                                'symbol', 'price', 'clientId', 'accountId'))
specs[['orderConf']] = data.frame(widths   = c(12, 2, 6, 1, 3,
                                                7, 12, 8, 16, 16), 
                                  col.names = c('timestamp', 'msgType', 'orderId', 'side', 'type', 
                                                'volume', 'symbol', 'price', 'clientId', 'accountId'))

specs[['rejection']] = data.frame(widths    = c(12, 2, 16, 3, 48), 
                                  col.names = c('timestamp', 'msgType', 'clientId', 'rejectionCode', 'text'))

specs[['trade']] = data.frame(widths   = c(12, 2, 6, 6, 7,
                                           12, 8), 
                              col.names = c('timestamp', 'msgType', 'tradeId', 'orderId', 'volume', 
                                            'symbol', 'price'))

# The selector function is responsible for identifying the message type of a line.
myselector <- function(line, specs) {
    s <- substr(line, 13, 14)
    spec_name = ''
    if (s == 'NO')
        spec_name = 'newOrder'
    else if (s == 'OC')
        spec_name = 'orderConf'
    else if (s == 'TR')
        spec_name = 'trade'
    else if (s == 'RJ')
        spec_name = 'rejection'

    spec_name
}

read.multi.fwf(ff, multi.specs = specs, select = myselector)
#> $newOrder
#>      timestamp msgType side type volume       symbol price
#> 1 10:15:03:279      NO    S  LMT    666     EVILCORP 10.77
#> 2 10:17:45:153      NO    B  LMT    666     EVILCORP  1.10
#> 3 10:18:28:045      NO    B  LMT    666     EVILCORP 11.00
#>           clientId        accountId
#> 1 SomeClientId     SomeAccountId   
#> 2 AnotherClientId  AnotherAccountId
#> 3 AnotherClientId  AnotherAccountId
#> 
#> $orderConf
#>      timestamp msgType orderId side type volume       symbol price
#> 1 10:15:03:793      OC       1    B  LMT    666     EVILCORP 10.77
#> 2 10:18:28:472      OC       2    B  LMT    666     EVILCORP 11.00
#>           clientId        accountId
#> 1 SomeClientId     SomeAccountId   
#> 2 AnotherClientId  AnotherAccountId
#> 
#> $rejection
#>      timestamp msgType         clientId rejectionCode
#> 1 10:17:45:487      RJ AnotherClientId              4
#>                                               text
#> 1 price out of range                              
#> 
#> $trade
#>      timestamp msgType tradeId orderId volume       symbol price
#> 1 10:18:28:642      TR       1       1    666     EVILCORP 10.77
#> 2 10:18:28:687      TR       1       2    666     EVILCORP 10.77

unlink(ff)

Installation

So far the package is not published in CRAN. You can either clone the repo and use RStudio to build and install the package or you could use devtools package to install directly from this repo.

To build the package you will also need: * roxygen2 * testthat (to check the package) * rstudio (optional)