# if you need a new package, you should add it with renv::install(package) so your renv venv is updated
library(RPostgres)
# Needs libpq-dev for compiling from source.

# Error installing package 'RPostgres':
#   =====================================
#   
#   * installing *source* package 'RPostgres' ...
# ** package 'RPostgres' successfully unpacked and MD5 sums checked
# ** using staged installation
# Using PKG_CFLAGS=
#   Using PKG_LIBS=-lpq
# Using PKG_PLOGR=
#   ------------------------- ANTICONF ERROR ---------------------------
#   Configuration failed because libpq was not found. Try installing:
#   * deb: libpq-dev (Debian, Ubuntu, etc)
# * rpm: postgresql-devel (Fedora, EPEL)
# * rpm: postgreql8-devel, psstgresql92-devel, postgresql93-devel, or postgresql94-devel (Amazon Linux)
# * csw: postgresql_dev (Solaris)
# * brew: libpq (OSX)
# If libpq is already installed, check that either:
#   (i)  'pkg-config' is in your PATH AND PKG_CONFIG_PATH contains
# a libpq.pc file; or
# (ii) 'pg_config' is in your PATH.
# If neither can detect , you can set INCLUDE_DIR
# and LIB_DIR manually via:
#   R CMD INSTALL --configure-vars='INCLUDE_DIR=... LIB_DIR=...'
# --------------------------[ ERROR MESSAGE ]----------------------------
#   <stdin>:1:10: fatal error: libpq-fe.h: No such file or directory
# compilation terminated.

library(yaml)

#' @description
#' Auxiliary function to parse the connection credentials from a specifc group in ./credentials.yaml
#' You can reause most of this function if you are connection to a DB or Web API.
#' It's OK to delete this function if you don't need credentials, e.g., you are pulling data from a CSV for example.
#' @param group the yaml key containing the credentials to connect to a database
#' @preturn dbEngine a database engine (connection) ready to perform queries
get_db_engine <- function(group){
  # The working dir is aways RAPIDS root folder, so your credentials file is always /credentials.yaml
  credentials <- read_yaml("./credentials.yaml")
  if(!group %in% names(credentials))
    stop(paste("The credentials group",group, "does not exist in ./credentials.yaml. The only groups that exist in that file are:", paste(names(credentials), collapse = ","), ". Did you forget to set the group in [PHONE_DATA_STREAMS][aware_mysql][DATABASE_GROUP] in config.yaml?"))
  dbEngine <- dbConnect(Postgres(), db = credentials[[group]][["database"]],
                        user = credentials[[group]][["user"]],
                        password = credentials[[group]][["password"]],
                        host = credentials[[group]][["host"]],
                        port = credentials[[group]][["port"]])
  return(dbEngine)
}

# This file gets executed for each PHONE_SENSOR of each participant
# If you are connecting to a database the env file containing its credentials is available at "./.env"
# If you are reading a CSV file instead of a DB table, the @param sensor_container wil contain the file path as set in config.yaml
# You are not bound to databases or files, you can query a web API or whatever data source you need.

#' @description
#' RAPIDS allows users to use the keyword "infer" (previously "multiple") to automatically infer the mobile Operative System a device was running.
#' If you have a way to infer the OS of a device ID, implement this function. For example, for AWARE data we use the "aware_device" table.
#'  
#' If you don't have a way to infer the OS, call stop("Error Message") so other users know they can't use "infer" or the inference failed, 
#' and they have to assign the OS manually in the participant file
#' 
#' @param stream_parameters The PHONE_STREAM_PARAMETERS key in config.yaml. If you need specific parameters add them there.
#' @param device A device ID string
#' @return The OS the device ran, "android" or "ios"

infer_device_os <- function(stream_parameters, device){
  #dbEngine <- get_db_engine(stream_parameters$DATABASE_GROUP)
  #query <- paste0("SELECT device_id,brand FROM aware_device WHERE device_id = '", device, "'")
  #message(paste0("Executing the following query to infer phone OS: ", query)) 
  #os <- dbGetQuery(dbEngine, query)
  #dbDisconnect(dbEngine)
  
  #if(nrow(os) > 0)
  #  return(os %>% mutate(os = ifelse(brand == "iPhone", "ios", "android")) %>% pull(os))
  #else
  stop(paste("We cannot infer the OS of the following device id because the aware_device table does not exist."))
  
  #return(os)
}

#' @description
#' Gets the sensor data for a specific device id from a database table, file or whatever source you want to query
#' 
#' @param stream_parameters The PHONE_STREAM_PARAMETERS key in config.yaml. If you need specific parameters add them there.
#' @param device A device ID string
#' @param sensor_container database table or file containing the sensor data for all participants. This is the PHONE_SENSOR[CONTAINER] key in config.yaml
#' @param columns the columns needed from this sensor (we recommend to only return these columns instead of every column in sensor_container)
#' @return A dataframe with the sensor data for device

pull_data <- function(stream_parameters, device, sensor, sensor_container, columns){
  dbEngine <- get_db_engine(stream_parameters$DATABASE_GROUP)
  query <- paste0("SELECT ", paste(columns, collapse = ",")," FROM ", sensor_container, " WHERE ", columns$DEVICE_ID ," = '", device,"'")
  # Letting the user know what we are doing
  message(paste0("Executing the following query to download data: ", query)) 
  sensor_data <- dbGetQuery(dbEngine, query)
  
  dbDisconnect(dbEngine)
  
  if(nrow(sensor_data) == 0)
    warning(paste("The device '", device,"' did not have data in ", sensor_container))
  
  return(sensor_data)
}