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ShinyApp_4_New_Functionality

Source: vignettes/ShinyApp_4_New_Functionality.Rmd
ShinyApp_4_New_Functionality.Rmd

Introduction: Innovate or die

The commands embedded with this app are just basic building blocks and nowhere near sufficient to do all the analyses that may be required. The app is designed to be extended by allowing users to add new functions outside theAlphavantagepf package.

New functions will take (as inputs) the command (and options) to be executed and a named list with the current values of every design element in the app, augmented with a few more parameters to simplify function definitions. The function can call upon a number of “interface” functions to both get data from the app’s internal store, and to interface with the feedback elements of the app. As output, the function should return a (possibly named) list of tables (gt objects), dygraphs, or ggplots. The element names can correspond to the output names defined in the next section, or (if the list is unnamed) will be filled in order.

App layout: Outputs

Outputs in the main page are shown in the following order:

TAB Name Order Shown Class Type
MAIN MSG 1 character text
MAIN GT1 2 gt_tbl gt
MAIN GT2 3 gt_tbl gt
MAIN GT3L 4 (L) gt_tbl gt
MAIN GT3R 5 (R) gt_tbl gt
MAIN TS1 6 dygraphs dygraphs
MAIN TS2 7 dygraphs dygraphs
MAIN SCAT1 8 ggplot2::ggplot ggplots
MAIN SCAT2 9 ggplot2::ggplot ggplots
DETAILS DGT1 1 gt_tbl gt
DETAILS DGT2 2 gt_tbl gt
DETAILS DSCAT1 3 ggplot2::ggplot ggplots
DETAILS DSCAT2 4 ggplot2::ggplot ggplots

So for example, a named list of the form

will show mtcars as a table followed by a scatterplot on the MAIN tab, and a truncated table first in the DETAILS tab.

App layout: inputs

The values of input design elements are all passed into a user function as (de-reacted) named list. The following table, which is not comprehensive, gives the most relevant items:

inputId Type Description Example
assetline character Asset string QQQ;DIA
todo character Full Command to Run QQQ;DIA GPD -6m::
todofunc character Command base GPD
todoargs character Command arguments -6m::
istr1 character Full input line QQQ;DIA GPD -6m::
inTabset character Currently selected Tab MAIN
istr2 character Counterasset SPY
dtstr_hist character Analysis date string -2y::
logopts character Logical Options from AVOPTS useLivePx,verbos
maxage_earn_days integer Maximum age for earnings data 3
maxage_px_hrs integer Maximum age for price data 0
cachedir character Directory with cached data c:/t/avsh
ts_volparams character Volatility parameters gk.yz;20;252
sigpct character Highlight p-value 0.025
gropts character Time Series Graphing options last
scatopts character Scatter plot options last
ts_events character Time Series Events tp,5
ts_colorset character Graphics color set lines

All other items in the named list can be found either by inspection when the function is run within the shiny app, or by inspecting the source code of the ui function generator in the file app.R.

Writing and registering new functions and commands

New functions that provide analytics must have the following properties:

  • Take two arguments: todo with the command, and rv (For Reactive values)
  • Return a list of gt() tables, dygraphs or ggplots.
  • Be accessable from .GlobalEnv
  • Be registered with the av_add_analytic() function, which requires
    • A runcode which is the command that will be typed (e.g. COR for correlation analysis)
    • The func_name of the function to run
    • An optional help string to be shown when AV.H is run
    • The focus tab to be shown upon completion of the function.

Functions can also access the data contained in the app and interact with the user using a few helper functions. The data can also be accessed directly if you’re familiar with its format and location.

Helper Functions: Data

The most important thing a user needs is access to the data held by the app. A list of the internal tables which can be accessed via the av_load_shinydata() function (and listed by running from the console dump_state("data")) is

Name Description
assetgroups Table of asset groups
avsh_funcs Current list of functions
cmdhist Rolling history of commands issued
earn Earnings Data
earnest Earnings Forecasts
listings Equity Listings obtained from av_get_pf("","LISTING_STATUS")
pxd Price Time Series Data
pxinv Data inventory
renderset Table of output elements
tickerlist List of indices and crypto pairs availble form AlphaVantage

For example, to get price data for a ticker string, use

> tickers_to_get=strsplit("IBM;QQQ;SPY",";")[[1]]
> pxdata <- av_load_shinydata("pxd")[data.table(symbol=tickers_to_get),on=.(symbol)]
> pxdata
 symbol  timestamp  open  high   low close adjusted_close   volume dividend_amount split_coefficient                  ts origclose
 <char>     <IDat> <num> <num> <num> <num>          <num>    <num>           <num>             <num>              <POSc>     <num>
    IBM 1999-11-01  98.5  98.8  96.4  96.8           47.1  9551800               0                 1 2026-08-03 15:10:30        NA
    IBM 1999-11-02  96.8  96.8  93.7  94.8           46.2 11105400               0                 1 2026-08-03 15:10:30        NA
    IBM 1999-11-03  95.9  95.9  93.5  94.4           46.0 10369100               0                 1 2026-08-03 15:10:30        NA
    IBM 1999-11-04  94.4  94.4  90.0  91.6           44.6 16697600               0                 1 2026-08-03 15:10:30        NA
    IBM 1999-11-05  92.8  92.9  90.2  90.2           44.0 13737600               0                 1 2026-08-03 15:10:30        NA
    ---        ---   ---   ---   ---   ---            ---      ---             ---               ---                 ---       ---
    SPY 2026-07-27 744.9 745.5 735.9 739.1          739.1 41461194               0                 1 2026-08-01 19:38:06        NA
    SPY 2026-07-28 739.2 742.8 736.0 740.9          740.9 47322247               0                 1 2026-08-01 19:38:06        NA
    SPY 2026-07-29 740.0 742.7 729.1 729.5          729.5 70697215               0                 1 2026-08-01 19:38:06        NA
    SPY 2026-07-30 736.0 742.5 734.6 741.7          741.7 66811268               0                 1 2026-08-01 19:38:06        NA
    SPY 2026-07-31 744.7 748.9 737.7 747.0          747.0 62445899               0                 1 2026-08-01 19:38:06        NA

Outside of the function, use av_load_shinydata() without arguments to load the data into the app without actually running it.

The sister package FinanceGraphs also contains some very helpful functions consistent with the design conventions of this app:

Function Description
narrowbydtstr() Filter a data.table() using a date string
extenddtstr() Expand a datestring into a new one
gendtstr() Expand a datestring into a list of dates

Helper Functions: UI Interaction

Three other functions may be used to interact with the user via the Shiny app:

Function Critical Arguments Description
quick_message where,this_message="" Give user feedback below a design element
avsh_clipboard data table Copy data to the clipboard
avsh_set_tabtitle newtext="",tabnm="detail" Set a Tab title and optionally change focus to it

Registering a new function

The minimal information necessary to integrate your function into the app is shown below:

Name Required Description
runcode Y What user need to type to run the function
func_name Y Name of function
helpstr N Help String to add to AV.H
focus N Tab to switch focus to

and is added to the app’s internal cache using av_add_analytic()

Example: Rolling Correlations

Suppose we wish to add an analytic which (given a set of assets) does the following with the assets entered with the command.

  • Produces a dygraph() with the an average rolling correlation, as well as 25th and 75th percentiles
  • Produces a gt() table with a full correlation table.

Putting the above information together we can write

my_corr <- function(todo,rv) {
    # Get Data
    tickers_to_get=strsplit(rv$assetline,";")[[1]]
    if(length(tickers_to_get)<3) { 
        quick_message("istr1","Need at least 3 tickers")
        return() }
    # Price Data
    allpx <- av_load_shinydata("pxd")[data.table(symbol=tickers_to_get),on=.(symbol)]
    allpx <- allpx[,.(symbol,timestamp, rtn = diff(log(adjusted_close),1))] |> FinanceGraphs::narrowbydtstr(rv$dtstr_hist)
    roll_window <- fcoalesce(as.numeric(rv$todoargs),22) # default to 22 day rolling correlation

    # Oraganize into pairs
    pairs <- CJ(var1=tickers_to_get,var2=tickers_to_get)[var1<var2,]
    corDT1<- allpx[,.(timestamp, var1=symbol, rtn1=rtn)][pairs,on=.(var1)]
    corDT2<- allpx[,.(timestamp, var2=symbol, rtn2=rtn)][pairs,on=.(var2)]
    corDT <- corDT1[corDT2, on=.(timestamp,var1,var2)]
    
    # Rolling correlation
    rollcor_DT <- corDT[,rcorr:=frollapply(.SD,roll_window,\(x) cor(x$rtn1,x$rtn2),by.column=FALSE), by=.(var1,var2)]
    cornames <- c("corr_p25","corr_p50","corr_p75")
    rollcor_toplot <- rollcor_DT[, (cornames):=lapply(.SD$rcorr,quantile,probs=c(0.25,0.5,0.75),na.rm=TRUE), by=.(timestamp)][
                                        ,.SD, .SDcols=c("timestamp",cornames)]    
    rollcorr_dyg <- fgts_dygraph(rollcor_toplot,title=paste0("Rolling percentiles of ",roll_window," bd correlations"),roller=1,events=rv$ts_events)
    
    # Overall correlations
    allcorr <- corDT[,.(allcorr=cor(rtn1,rtn2,use="pairwise.complete.obs")),by=.(var1,var2)]
    allcorr_gt <- dcast(corDT,var1 ~ var2,value.var="allcorr") |> gt() |> tab_header(title=paste0("Correlation matrix for ",rv$dttr_hist))
    
    # Return list
    return(list(allcorr_gt,rollcorr_dyg))
}

We need to define how users will call this function, so a reasonable choice is “RCOR”. To add that function to the stable of those available, just run

av_add_analytic("RCOR","my_corr",helpstr="Rolling Correlations")

Doing so will save the definition in the disk cache, so we just need to rerun av_runShiny() and then we can run it!