document.qmd

---
title: "ETL Step 1 - Raw Data Refresh"
date: "`r lubridate::now(tzone = 'EST')` EST"
output: html_document
---

This notebook uses the [bikeHelpR](https://packagemanager.rstudio.com/client/#/repos/1/packages/bikeHelpR) package to update a database with the latest bike share data. The package pulls data from <https://capitalbikeshare.com> which provides an API to access bike share data. The raw data is written to the *Content DB* database to the *bike_raw_data* table.

```{r setup, include=FALSE}
knitr::opts_chunk$set(warning = FALSE, message = FALSE) 

library(dplyr)
library(dbplyr)
library(odbc)
```

## Get data from API

Use the the `bikeHelpR` package to get the latest data from <https://capitalbikeshare.com>.

### Station status

```{r station_status_data}
feeds_station_status <- 
  bikeHelpR::feeds_urls() %>% 
  filter(name == "station_status") %>% 
  pull(url) %>% 
  bikeHelpR::get_data() 

station_status <- 
  feeds_station_status %>%
  magrittr::extract2("data") %>%
  dplyr::mutate(time = feeds_station_status$last_updated) %>%
  dplyr::select(
    is_installed, 
    num_bikes_available, 
    last_reported, 
    is_renting, 
    eightd_has_available_keys, 
    num_docks_available, 
    num_docks_disabled, 
    is_returning, 
    station_id, num_ebikes_available, 
    num_bikes_disabled, 
    time
  )

glimpse(station_status)
```

### Station info

```{r station_info_data}
# The station information endpoint.
station_information_url <- 
  bikeHelpR::feeds_urls() %>% 
  filter(name == "station_information") %>% 
  pull(url)

# Call the endpoint to obtain the JSON data.
request <- httr2::request(station_information_url)
response <- httr2::req_perform(request)
json_data <- httr2::resp_body_json(response)

# Convert the JSON data into a tibble.
station_info <- 
  json_data$data %>%
  as_tibble() %>%
  tidyr::unnest_wider(stations) %>%
  select(station_id, name, lat, lon) %>%
  distinct() %>%
  mutate(
    last_updated = as.POSIXct(
      json_data$last_updated,
      origin = "1970-01-01 00:00:00 UTC"
    )
  )

glimpse(station_info)
```

## Update database

Write the new data from the API to the database.

```{r write_to_db}
con <- dbConnect(odbc(), "Content DB", timeout = 10)
dbWriteTable(con, "bike_raw_data", station_status, append = TRUE)
dbWriteTable(con, "bike_station_info", station_info, overwrite = TRUE)
dbDisconnect(con)
print("Raw data updated 🎉")
```

## Update the pin

Station info will also be written to a pin. This pin will be accessed by the shiny app so that it can easily get the bike station info without connecting to the database.

```{r pin_station_info}
board <- pins::board_rsconnect(
  server = Sys.getenv("CONNECT_SERVER"),
  key = Sys.getenv("CONNECT_API_KEY"),
  versioned = TRUE
)

# Write the model to the board.
pins::pin_write(
  board,
  x = station_info,
  type = "csv",
  name = "bike-predict-r-station-info-pin",
  title = "Bike Predict - ETL - Pinned Station Info",
  description = "Bike station info from https://capitalbikeshare.com."
)

print("Pin 🎉")
```