Learn R Programming

FinancialInstrument (version 1.3.1)

saveInstruments: Save and Load all instrument definitions

Description

Saves (loads) the .instrument environment to (from) disk.

Usage

saveInstruments(file_name = "MyInstruments", dir = "", compress = "gzip")

loadInstruments(file_name = "MyInstruments", dir = "")

reloadInstruments(file_name = "MyInstruments", dir = "")

Arguments

file_name

name of file. e.g. “MyInstruments.RData”. As an experimental feature, a list or environment can be passed to file_name.

dir

Directory of file (defaults to current working directory. ie. "")

compress

argument passed to save, default is "gzip"

Value

Called for side-effect

Details

After you have defined some instruments, you can use saveInstruments to save the entire .instrument environment to disk.

loadInstruments will read a file that contains instruments and add those instrument definitions to your .instrument environment. reloadInstruments will remove all instruments in the current .instrument environment before loading instruments from disk.

The file_name should have a file extension of “RData”, “rda”, “R”, or “txt”. If the file_name does not end with one of those, “.RData” will be appended to the file_name

If the file extension is “R” or “txt”, saveInstruments will create a text file of R code that can be sourced to load instruments back into the .instrument environment.

See Also

save, load load.instrument define_stocks, define_futures, define_options (option_series.yahoo)

Examples

Run this code
# NOT RUN {
stock("SPY", currency("USD"), 1)
tmpdir <- tempdir()
saveInstruments("MyInstruments.RData", dir=tmpdir)
rm_instruments(keep.currencies=FALSE)
loadInstruments("MyInstruments.RData", dir=tmpdir)
# write .R file that can be sourced
saveInstruments("MyInstruments.R", dir=tmpdir)
rm_instruments(keep.currencies=FALSE)
loadInstruments("MyInstruments.R", dir=tmpdir)
#source(file=paste(tmpdir, "MyInstruments.R", sep="/")) # same
unlink(tmpdir, recursive=TRUE)     
# }

Run the code above in your browser using DataLab