tests/testthat/helper-src.R

In datacamp/tidymetrics: A Tidy Approach to Dimensional Modeling

# library(lubridate)
# library(tidyr)
# library(dplyr)
#
# PORT <- if (identical(Sys.getenv("TRAVIS"), "true")) {
#   5432
# } else {
#   port <- Sys.getenv("POSTGRES_PORT")
#   ifelse(port == "", 5433, port)
# }
# USER <- if (identical(Sys.getenv("TRAVIS"), "true")) {
#   "postgres"
# } else {
#   Sys.info()[["user"]]
# }
#
#
# # Connect to DB and add small_flights data ----
#
# dbcon <- DBI::dbConnect(RPostgreSQL::PostgreSQL(),
#   dbname = "postgres",
#   user = USER,
#   password = "",
#   host = "localhost",
#   port = PORT
# )
#
# con <- dbplyr::src_dbi(dbcon, auto_disconnect = TRUE)
#
# small_flights <-
#   nycflights13::flights %>%
#   filter(month < 3) %>%
#   mutate(date = as.Date(ISOdate(year, month, day))) %>%
#   select(date, carrier, origin, dep_delay, arr_delay, distance)
#
#
# tbl_small_flights <- copy_to(con, small_flights, "small_flights", overwrite = TRUE)
#
#
# # Copy in calendar dates to db ----
#
# dates <- seq(as.Date("2013-01-01"),
#   today() + years(2),
#   by = 1
# )
# calendar_periods <- tibble(date_original = dates) %>%
#   crossing(period = c("day", "week", "month", "quarter", "year")) %>%
#   group_by(period) %>%
#   mutate(date = floor_date(date_original, period[1], week_start = 1)) %>%
#   ungroup() %>%
#   select(period, date, date_original)
#
#
# tbl_remote_date_periods <-
#   copy_to(con, calendar_periods, "remote_date_periods", overwrite = TRUE)
#
# # set global remote_date_periods option
# options(remote_date_periods = function() {
#   tbl_remote_date_periods
# })