Learn R Programming

quantmod (version 0.4.20)

attachSymbols: Attach and Flush DDB

Description

Attach a demand database (lazy load) as a new environment.

Usage

attachSymbols(DB = DDB_Yahoo(),
              pos = 2,
              prefix = NULL,
              postfix = NULL,
              mem.cache = TRUE,
              file.cache = !mem.cache,
              cache.dir = tempdir())

flushSymbols(DB = DDB_Yahoo())

Arguments

DB

A DDB data base object

pos

position in search path to attach DB

prefix

character to prefix all symbols with

postfix

character to postfix all symbols with

mem.cache

should objects be cached in memory

file.cache

should objects be cached in on disk

cache.dir

directory to use for file.cache=TRUE

Author

Jeffrey A. Ryan

Details

An experimental function to allow access to remote objects without requiring explicit calls to a loading function.

attachSymbols requires a DDB object to define where the data is to come from, as well as what symbols are loaded on-demand.

attachSymbols calls the method referred to by the DDB object. In the default case this is DDB_Yahoo. See this function for specific details about the Yahoo implementation.

The individual methods make use of getSymbols to load the data. This requires a corresponding getSymbols method.

Internally, attachSymbols makes use of quantmod's unexported create.bindings to dynamically create active bindings to each symbol listed in the DDB object.

In turn, create.bindings uses one of two R methods to create the binding to the names required. This depends on the cache method requested.

Immediately after a call to attachSymbols, a new environment is attached that contains the names of objects yet to be loaded. This is similar to the lazy-load mechanism in R, though extended to be both more general and easier to use.

It is important to note that no data is loaded at this stage. What occurs instead is that these symbols now have active bindings using either delayedAssign (mem.cache) or makeActiveBinding (file.cache).

During all future requests for the object(s) in question, the binding will be used to determine how this data is loaded into R. mem.cache will simply load the data from its corresponding source (as defined by the DDB object) and leave it in the environment specified in the original call. The effect of this is to allow lazy-loading of data from a variety of external sources (Yahoo in the default case). Once loaded, these are cached in R's memory. Nothing further differentiates these from standard variables. This also means that the environment will grow as more symbols are loaded.

If the file.cache option is set, the data is loaded from its source the first time the symbol is referenced. The difference is that the data is then written to a temporary file and maintained there. Data is loaded and subsequently removed upon each request for the object. See makeActiveBinding for details of how this occurs at the R level.

A primary advantage of using the file.cache option is the ability to maintain hundreds or thousands of objects in your current session without using memory, or explicitly loading and removing. The main downside of this approach is the that data must be loaded from disk each time, with the corresponding (if generally negligible) overhead of file access.

References

Luke's stuff and Mark Brevington and Roger Peng

See Also

delayedAssign, makeActiveBinding

Examples

Run this code
if (FALSE) {
attachSymbols()
SBUX
QQQQ
ls()
}

Run the code above in your browser using DataLab