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Load smartabaseR

library(smartabaseR)

Requirements

smartabaseR can only be used on Smartabase versions 6.14 or greater (if your account has superadmin or site owner privileges, then smartabaseR can also be used with v6.13).

In 2023, Smartabase switched to calendar versioning. smartabaseR can be used on any site that uses calendar versioning e.g. 2023.1, 2023.2 etc.

Credentials

Please see vignette("credentials").

Exporting data from Smartabase

Exporting Smartabase data with smartabaseR is easy with the sb_get_event() function. You will at a minimum need to supply values to the form, date_range, url, username and password arguments. Note that date_range contains a start_date and an end_date and each must be in dd/mm/YYYY format.

sb_get_event(
  form = "Training Log",
  date_range = c("01/03/2023", "07/03/2023"),
  url = "example.smartabase.com/site",
  username = "example.username", # note: must be valid username, not email
  password = "example_password"
)

#> ✔ Successfully logged example.username into example.smartabase.com/site.
#> ✔ User details export successful.
#> ✔ Training Log export successful (Mar 03 2020 - Mar 07 2023).

A successful export! We have Training Log data for two athletes named Aiden Thomas and Jamie Anderson.

#> # A tibble: 2 × 7
#>   start_date user_id about          distance   rpe event_id entered_by_user_id
#>   <chr>        <dbl> <chr>             <dbl> <dbl>    <dbl>              <dbl>
#> 1 03/01/2023   37204 Aiden Thomas       2530     5  2381840              37204
#> 2 03/01/2023   37201 Jamie Anderson     5411     7  2382033              37201

Note, frequently exporting data (especially large data sets) can put stress on your Smartabase server which may affect your organisation’s Smartabase experience. At a minimum, please save your exported data to a variable (here we saved it to a variable called “training_data”). This minimises unnecessary API calls.

Importing data to Smartabase

We can also import an R data frame into Smartabase using sb_insert_event().

Imagine we want to calculate the difference between each athlete’s RPE and the team average RPE and upload the results to a form called “Team Summary”

First, to calculate the team average:

# Need to load dplyr
library(dplyr)

rpe_average <- training_data %>%
  select(-entered_by_user_id) %>%
  mutate(team_rpe = round(mean(rpe), 1))

rpe_average
#> # A tibble: 2 × 7
#>   start_date user_id about          distance   rpe event_id team_rpe
#>   <chr>        <dbl> <chr>             <dbl> <dbl>    <dbl>    <dbl>
#> 1 03/01/2023   37204 Aiden Thomas       2530     5  2381840        6
#> 2 03/01/2023   37201 Jamie Anderson     5411     7  2382033        6

Now to compare the group average to each athlete’s RPE:

rpe_average <- rpe_average %>%
  mutate(rpe_diff = rpe - team_rpe)

rpe_average
#> # A tibble: 2 × 8
#>   start_date user_id about          distance   rpe event_id team_rpe rpe_diff
#>   <chr>        <dbl> <chr>             <dbl> <dbl>    <dbl>    <dbl>    <dbl>
#> 1 03/01/2023   37204 Aiden Thomas       2530     5  2381840        6       -1
#> 2 03/01/2023   37201 Jamie Anderson     5411     7  2382033        6        1

Finally, to upload our results back up to Smartabase, we need to supply a data frame and a form name as well as our credentials:

sb_insert_event(
  df = rpe_average,
  form = "Team Summary",
  url = "example.smartabase.com/site",
  username = "example.username", # note: must be valid username, not email
  password = "example_password"
)

#> ✔ SUCCESSFULLY_INSERTED: 2 out of 2 records successfully inserted into Team Summary.

Success! Our data should now be imported into the “Team Summary” form on Smartabase.

To learn more about how to get the most out of smartabaseR, please see the exporting-data and importing-data vignettes.