In StevenMMortimer/squareupr: An Implementation of 'Square' APIs

NOT_CRAN <- identical(tolower(Sys.getenv("NOT_CRAN")), "true")
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  purl = NOT_CRAN,
  eval = NOT_CRAN
)

Authenticate

First, load the squareupr package and login. There are two ways to authenticate: 1) OAuth 2.0 or a 2) Personal Access Token (PAT). It is recommended to use OAuth 2.0 so that your PAT does not have to be shared/embedded within scripts. However, note that before using OAuth 2.0 authentication it is necessary that you set up your own Connected App in the Square dashboard. An App ID and App Secret will be provided, then you will be able to plug into your script like so:

options(squareupr.app_id = "sq0-99-thisisatest99connected33app22id")
options(squareupr.app_secret = "sq0-Th1s1sMyAppS3cr3t")
sq_auth()

OAuth 2.0 User credentials will be stored in locally cached file entitled ".httr-oauth-squareupr" in the current working directory.

library(dplyr)
library(squareupr)
settings <- readRDS(here::here("tests", "testthat", "squareupr_test_settings.rds"))
suppressMessages(sq_auth(personal_access_token = settings$personal_access_token, 
                         verbose = FALSE))

library(dplyr)
library(squareupr)

# Using Personal Access Token (PAT)
sq_auth(personal_access_token = "sq-Th1s1sMyPers0nalAcessT0ken")

# Using OAuth 2.0 authentication
sq_auth()

Get Transactions

Transactions are organized by location. With the v2 Locations endpoint you can pull information regarding all locations first to obtain the location IDs. Then with the sq_list_transactions() function you can provide the location and timeframe to search. The function defaults to pulling transactions from the previous day using Sys.Date() - 1. Once you obtain the transactions the tenders field lists all methods of payment used to pay in the transaction.

# list all locations
our_locations <- sq_list_locations()
our_transactions <- sq_list_transactions(location = our_locations$id[2], 
                                         begin_time = as.Date('2018-05-11'), 
                                         end_time = as.Date('2018-05-12'))
our_transactions

Get Customers

Once you pull data about transactions you can take the customer_id from the transaction tenders field and match that up with customer details. In Square customers can be placed into groups that allow for the analysis of transactions at a group-level.

# list customers created in the last 90 days
created_start <- format(Sys.Date()-90, '%Y-%m-%dT00:00:00-00:00')
created_end <- format(Sys.Date(), '%Y-%m-%dT00:00:00-00:00')
our_customers <- sq_search_customers(query = list(filter=
                                                    list(created_at=
                                                           list(start_at=created_start,
                                                                end_at=created_end))))
our_customers$given_name <- "{HIDDEN}"
our_customers$family_name <- "{HIDDEN}"
our_customers %>% select(id, created_at, updated_at, 
                         given_name, family_name, preferences, groups)

# show the groups that each customer belongs to
# filter to the groups designated automatically by Square
sq_extract_cust_groups(our_customers) %>%
  filter(grepl("^CQ689YH4KCJMY", groups.id))

Check out the Tests

The squareupr package has quite a bit of unit test coverage to track any changes made between newly released versions of the Square APIs. These tests are great source of examples for how to interect with the API. The tests are available here.

StevenMMortimer/squareupr documentation built on July 12, 2019, 1:45 a.m.