Added a tool to create computational formats of data

I added a tool to read from Luke's google sheet and
converts results to a tidy csv format as well as a
json format. This script can serve as a place to
build further computed fields such as badges, etc.

.gitignore

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+.httr-oauth

tools/README.md

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+## Utilities
+
+### Create Accessory files
+
+The file, `create_files`, is an R script meant to run from the command-line. It accesses the Google Sheet here:
+
+https://docs.google.com/spreadsheets/d/1n3hXzzhrHZgClLD8P3cyIrK_6YgdjtdGlLswNAuoKSI/edit?usp=sharing
+
+And creates a tidy csv file of software after adding a few automatically-calculated columns. It also writes a json-format file of the same data, but with one record per software package. Categories are collapsed to a json array. To run:
+
+```
+create_files.R /path/to/git/repo
+# or
+create_files.R /path/to/directory/for/accessory_files
+```

tools/create_files.R

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+#!/usr/bin/env Rscript
+library(docopt)
+"Usage: create_files OUTPUT_DIR
+
+-h --help    show this
+
+This utility script converts the google spreadsheet here:
+
+  https://docs.google.com/spreadsheets/d/1n3hXzzhrHZgClLD8P3cyIrK_6YgdjtdGlLswNAuoKSI/edit?usp=sharing
+
+to a set of files including:
+
+  - OUTPUT/single-cell-software-tidy.csv
+  - OUTPUT/single-cell-software.json
+" -> doc
+opts = docopt(doc)
+print(opts)
+
+library(googlesheets)
+library(readr)
+library(jsonlite)
+library(dplyr)
+library(tidyr)
+library(lubridate)
+# this is the google spreadsheet ID to use
+gskey = "1n3hXzzhrHZgClLD8P3cyIrK_6YgdjtdGlLswNAuoKSI"
+gs_auth()
+
+
+#' Create tidy sheet from the google sheet
+#' @export
+get_tidy_sw_list = function(gskey) {
+  swsheet = gs_key(gskey) %>% 
+    gs_read() %>%
+    mutate(Preprint = (`Pub Date`=="PREPRINT")) %>%
+    mutate(`Pub Date`=as_date(`Pub Date`)) %>%
+    mutate(Preprint = ifelse(Preprint==TRUE,TRUE,NA)) %>%
+    mutate(Added = as_date(Added)) %>%
+    mutate(Updated = as_date(Updated)) %>% 
+    mutate(DOI_url = ifelse(is.na(DOI),NA,paste0('http://dx.doi.org/',DOI)))
+  gather(swsheet,key='category',value='val',-Description,-Name,-Platform,-DOI,-`Pub Date`,-Updated,-Added,-Preprint,-Code,-DOI_url,-License) %>%
+    mutate(Github = grepl('github',Code)) %>%
+    mutate(Bioconductor = grepl('bioconductor',Code,ignore.case = TRUE)) %>%
+    mutate(CRAN = grepl('cran\\.r-project',Code)) %>%
+    filter(val==TRUE) %>%
+    select(-val)
+}
+
+tidysw_to_list_df <- function(tidysw) {
+  catlist = split(tidysw$category,f=tidysw$Name)
+  tidyswl = tidysw %>% select(-category) %>% unique()
+  tidyswl[['categories']] = catlist[tidyswl$Name]
+  tidyswl
+}
+
+
+#' write out json and csv files
+#' 
+#' @export
+write_files = function(destdir) {
+  dir.create(destdir, recursive = TRUE)
+  swsheet = get_tidy_sw_list(gskey)
+  write_csv(swsheet,path=file.path(destdir,'single-cell-software_tidy.csv'))
+  writeLines(toJSON(tidysw_to_list_df(swsheet),pretty=TRUE),file.path(destdir,'single-cell-software.json'))
+}
+
+write_files(opts$OUTPUT_DIR)