In VermeirJellen/essentialjsonserializer_r: JSON (de)serialization of complex R-objects

The intention of the package fuctionality is to (de)serialize language specific complex objects towards generic JSON-datatype objects. The JSON conversion allows for flexible cross language communication when the package is implemented across different languages. This package provides an R implementation of the (de)serialization functionality.

the package can be installed from github by using the devtools utility:

# install.packages("devtools") # if devtools currently not installed
devtools::install_github("VermeirJellen/essentialjsonserializer_r")

JSON (de)serialization of complex R-objects.

Currently, 6 generic complex JSON-datatypes are provided. Corresponding R-mappings are defined as follows:

• JSON datetime - maps to R POSIXct objects
• JSON timeseries - maps to R 1-dimensional xts objects
• JSON timeseries_n_dim - maps to R n-dimensional xts objects (n > 1)
• JSON series - maps to R 1-dimensional dataframe objects
• JSON dataframe - maps to R n-dimensional dataframe objects (n > 1)
• JSON matrix - maps to R matrix objects

The package provides the user with the EssentialJSONSerializer reference class. Following functions are provided:

• RToList: Convert complex R structures to a generic datatype list structure.
• RToJSON: Convert complex R structures to a generic datatype JSON structure.
• RFromList: Convert generic datatype list structure to complex R-specific objects.
• RFromJSON: Convert generic datatype JSON structure to complex R-specific objects.

Examples

EssentialJSONSerializer Object Construction

Sys.setenv(tz="UTC")
library(essentialjsonserializer)
essential.serializer <- EssentialJSONSerializer$new()

list

Serialize:

list.input <- list(c(1, 2, 3, 4, 5), 
                   c(6, 7, 8), list(c(1, 2, 3)))
list.json <- essential.serializer$RToJSON(list.input)
cat(list.json)

Deserialize:

list.json.revert <- essential.serializer$RFromJSON(list.json)

datetime

Serialize:

datetime.input  <- as.POSIXct(Sys.time(), tz="UTC")
datetime.json   <- essential.serializer$RToJSON(datetime.input)
cat(datetime.json)

Deserialize:

datetime.json.revert <- essential.serializer$RFromJSON(datetime.json)
datetime.json.revert

datetime (nested)

Serialize:

datetime.nested.input <- list(input.1 = datetime.input, 
                              input.2 = as.POSIXct(Sys.Date(), tz="UTC"))

datetime.nested.json    <- essential.serializer$RToJSON(datetime.nested.input)
cat(datetime.nested.json)

Deserialize:

datetime.nested.json.revert <- essential.serializer$RFromJSON(datetime.nested.json)
datetime.nested.json.revert

timeseries

Serialize:

timeseries.input  <- xts::xts(matrix(c(5, 7, 9, NA), ncol=1), 
                              order.by = c(as.POSIXct("2017-01-01", tz="UTC"),
                                        as.POSIXct("2017-01-02", tz="UTC"),
                                        as.POSIXct("2017-01-03", tz="UTC"),
                                        as.POSIXct("2017-01-04", tz="UTC")))
names(timeseries.input) <- "name_series"

timeseries.json    <- essential.serializer$RToJSON(timeseries.input)
cat(timeseries.json)

Deserialize:

timeseries.json.revert <- essential.serializer$RFromJSON(timeseries.json)
timeseries.json.revert

timeseries_n_dim

Serialize:

timeseriesndim.input  <- xts:::xts(matrix(c(5, 7, 9, 12, 15, 19), ncol=2), 
                             order.by = c(as.POSIXct("2017-01-01", tz="UTC"),
                                          as.POSIXct("2017-01-02", tz="UTC"),
                                          as.POSIXct("2017-01-03", tz="UTC")))
names(timeseriesndim.input) <- c("name_series_1", "name_series_2")

timeseriesndim.json <- essential.serializer$RToJSON(timeseriesndim.input)
cat(timeseriesndim.json)

Deserialize:

timeseriesndim.json.revert <- essential.serializer$RFromJSON(timeseriesndim.json)
timeseriesndim.json.revert

timeseries_n_dim (nested)

Serialize:

timeseries.nested.input <- list(ts1 = timeseries.input, 
                                ts2 = timeseriesndim.input)
timeseries.nested.json <- essential.serializer$RToJSON(timeseries.nested.input)
cat(timeseries.nested.json)

Deserialize:

timeseries.nested.json.revert <- essential.serializer$RFromJSON(timeseries.nested.json)
timeseries.nested.json.revert

series

Serialize:

series.input        <- data.frame(c(1, 2, 3, 4), 
                                  row.names = c("one", "two", "three", "four"))
names(series.input) <- "only_column"

series.json  <- essential.serializer$RToJSON(series.input)
cat(series.json)

Deserialize:

series.json.revert <- essential.serializer$RFromJSON(series.json)
series.json.revert

dataframe

Serialize:

dataframe.input        <- data.frame(c(1, 2, 3, 4), c(4, 5, 6, 7),
                                     row.names = c("one", "two", "three", "four"))
names(dataframe.input) <- c("first_col", "second_col")

dataframe.json <- essential.serializer$RToJSON(dataframe.input)
cat(dataframe.json)

Deserialize:

dataframe.json.revert <- essential.serializer$RFromJSON(dataframe.json)
dataframe.json.revert

matrix

Serialize:

matrix.input <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2, byrow = TRUE)

matrix.json <- essential.serializer$RToJSON(matrix.input)
cat(matrix.json)

Deserialize:

matrix.json.revert <- essential.serializer$RFromJSON(matrix.json)
matrix.json.revert

nested structure

Serialize:

r.input <- list(list.input           = list.input,
                datetime.input       = datetime.input,
                datetime.nested      = datetime.nested.input,
                timeseries.input     = timeseries.input,
                timeseriesndim.input = timeseriesndim.input,
                series.input         = series.input,
                dataframe.input      = dataframe.input,
                matrix.input         = matrix.input,
                timeseries.nested    = timeseries.nested.input)


r.json <- essential.serializer$RToJSON(r.input)
cat(r.json)

Deserialize:

r.json.revert <- essential.serializer$RFromJSON(r.json)
r.json.revert

Donations

If you find this software useful and/or you would like to see additional extensions, feel free to donate some btc:

• BTC: 3NmxUnuK8ZqAszzFzcpBerKsy4ajQpb8mi

Licensing

Copyright 2019 Essential Data Science Consulting ltd. (EssentialDataScience.com / [e-mail]). This software is copyrighted under the MIT license: View added LICENSE file.

VermeirJellen/essentialjsonserializer_r documentation built on May 16, 2019, 4:24 p.m.