Implement the necessary functions for PSQL.

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junos 2021-11-17 18:49:25 +01:00
parent 7a1e4f7139
commit fcec3e2f93
1 changed files with 107 additions and 0 deletions

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# 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)
}