Iris: What the study does (short line)

# anon <- function() {
#
# ###########################################################
# # R script for IRIS
# #
# #                                                         #
# ###########################################################
#
# # Install necessary packages if needed
# #install.packages("devtools")
# require(devtools)
# #next line prevents problem with previous version of SqlRender
# #remove.packages("SqlRender")
# #install_github("ohdsi/SqlRender")
# #install_github("ohdsi/DatabaseConnector")
#
#
#
# # Load libraries
# require(SqlRender)
# require(DatabaseConnector)
# packageVersion("SqlRender")
# packageVersion("DatabaseConnector")
#
# ###########################################################
# # Parameters: Please change these to the correct values:  #
# ###########################################################
#
# useInterimTables = 1  #change to 0  (zero) if you have no write access to any schema. later variable result schema variable will be ignored (can be set to anything) if useInterimTables is set to zero
# folder        = "C:/d/sandA" # Folder containing the R and SQL files, use forward slashes
# cdmSchema     = "ccae_cdm4"
# resultsSchema = "results"  #ignored if useInterimTable is 0
#
# sourceName    = "CCAE"
# dbms          = "postgresql"      # Should be "sql server", "oracle", "postgresql" or "redshift"
#
#
#
# # If you want to use R to run the SQL and extract the results tables, please create a connectionDetails
# # object. See ?createConnectionDetails for details on how to configure for your DBMS.
#
# connectionDetails <- createConnectionDetails(dbms     = dbms,
#                                              user     = "postgres",
#                                              password = "F1r3starter",
#                                              server   = "localhost/ohdsi")
# #example for redshift
# # connectionDetails <- createConnectionDetails(dbms=dbms
# #                                              ,server="omop-datasets.redacted.redshift.amazonaws.com/redacted"
# #                                              ,user="redacted"
# #                                              ,password="redacted"
# #                                              ,port="5439")
#
#
# ###########################################################
# # End of parameters. Make no changes after this           #
# ###########################################################
#
#
#
# setwd(folder)
#
# #source("HelperFunctions.R")
#
# # Create the parameterized SQL files:
# inputFile <- "../inst/sql/sql_server/iris_parameterized.sql"
# studyName <-'iris'  #does not need changing
# outputFile <- paste(studyName,"-autoTranslate-",dbms,".sql",sep="")
#
# parameterizedSql <- readSql(inputFile)
# renderedSql <- renderSql(parameterizedSql, cdmSchema=cdmSchema, resultsSchema=resultsSchema, studyName = studyName, sourceName=sourceName,useInterimTables=useInterimTables )$sql
# #sourceDialect should not be changed
#
# translatedSql <- translateSql(renderedSql, sourceDialect = "sql server", targetDialect = dbms)$sql
# writeSql(translatedSql,outputFile)
# writeLines(paste("Created file '",outputFile,"'",sep=""))
#
#
# #this code only facilitates distribution of SQL code
#                 otherDialect<-'oracle'
#                 outputFileOther <- paste(studyName,"-autoTranslate-",otherDialect,".sql",sep="")
#                 translatedSqlOther <- translateSql(renderedSql, sourceDialect = "sql server", targetDialect = otherDialect)$sql
#                 writeSql(translatedSqlOther,outputFileOther)
#
#
#                 otherDialect<-'postgresql'
#                 outputFileOther <- paste(studyName,"-autoTranslate-",otherDialect,".sql",sep="")
#                 translatedSqlOther <- translateSql(renderedSql, sourceDialect = "sql server", targetDialect = otherDialect)$sql
#                 writeSql(translatedSqlOther,outputFileOther)
#
#
#                 otherDialect<-'ms sql'
#                 outputFileOther <- paste(studyName,"-autoTranslate-",otherDialect,".sql",sep="")
#                 #translatedSqlOther <- translateSql(renderedSql, sourceDialect = "sql server", targetDialect = otherDialect)$sql
#                 writeSql(renderedSql,outputFileOther)
#
#
#
# #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# #if you don't want to execute the code -  you can end here and just use the outputFile "manually"
#
# # Execute the SQL:
# .jinit()  #this tiny step resolves optional issues with JVM
# conn <- connect(connectionDetails)
#
#
# executeSql(conn,readSql(outputFile))
#
# dbDisconnect(conn)
#
# #--end of code
# }
#
#