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mk8dx

The mk8dx package converts lss files for MK8DX speedruns into usable table data. It also has tools to help clean up the data.

Installation

You can install the development version of mk8dx from GitHub with:

# install.packages("devtools")
devtools::install_github("sj-io/mk8dx")

Load the package to your library to use it.

library(mk8dx)

mk_lss(): Create a table from lss data

Provide a folder or file path to mk_lss() to create a table from lss data.

library(dplyr)

bell_cup <- mk_lss("inst/extdata/bell-cup.lss")

head(bell_cup, 4)
## # A tibble: 4 × 16
##   category   total_attempts individual_cup cc    items    version attempt_id
##   <chr>               <dbl> <chr>          <chr> <chr>    <chr>        <dbl>
## 1 Bonus Cups              2 Bell Cup       150cc No Items Digital          1
## 2 Bonus Cups              2 Bell Cup       150cc No Items Digital          1
## 3 Bonus Cups              2 Bell Cup       150cc No Items Digital          1
## 4 Bonus Cups              2 Bell Cup       150cc No Items Digital          1
## # ℹ 9 more variables: attempt_started <dttm>, attempt_ended <dttm>,
## #   attempt_real_time <dbl>, attempt_game_time <dbl>, segment_id <dbl>,
## #   segment_real_time <dbl>, segment_game_time <dbl>, segment_name <chr>,
## #   best_segment_real_time <dbl>

The mk_lss() function reads the data using xml2. It gets the file’s variables, attempts, and split data.

Note: All split/run times are given in seconds. If runs are not completed, the attempt time will be NA.

You can also provide a folder path to create one table from all lss files in the folder.

path <- "inst/extdata"

all_runs <- mk_lss(path)

all_runs[7:14, ]
## # A tibble: 8 × 16
##   category      total_attempts individual_cup cc    items    version  attempt_id
##   <chr>                  <dbl> <chr>          <chr> <chr>    <chr>         <dbl>
## 1 Bonus Cups                 2 Bell Cup       150cc No Items Digital           2
## 2 Bonus Cups                 2 Bell Cup       150cc No Items Digital           2
## 3 DLC Cups                   0 Boomerang Cup  150cc No Items Digital          NA
## 4 DLC Cups                   0 Boomerang Cup  150cc No Items Digital          NA
## 5 DLC Cups                   0 Boomerang Cup  150cc No Items Digital          NA
## 6 DLC Cups                   0 Boomerang Cup  150cc No Items Digital          NA
## 7 Lightning Cup              5 <NA>           150cc <NA>     Cartrid…          1
## 8 Lightning Cup              5 <NA>           150cc <NA>     Cartrid…          1
## # ℹ 9 more variables: attempt_started <dttm>, attempt_ended <dttm>,
## #   attempt_real_time <dbl>, attempt_game_time <dbl>, segment_id <dbl>,
## #   segment_real_time <dbl>, segment_game_time <dbl>, segment_name <chr>,
## #   best_segment_real_time <dbl>

tracks dataset

The tracks dataset contains every track in MK8DX (96 tracks). It can be used as a reference or to standardize/correct track names.

Included is:

  • the track name, both long (track) and abbreviated (trk)
  • the original console the track appeared (console)
  • some id columns to help sort/match tracks
tracks[c(15:18, 79:82), ]
## # A tibble: 8 × 9
##   trk_ID trk   track        console cup_ID cup   trks16_ID trks16_name trks48_ID
##    <dbl> <chr> <chr>        <chr>    <int> <chr>     <int> <chr>           <dbl>
## 1     15 BC    Bowser's Ca… <NA>         3 Spec…        15 Nitro Trac…        15
## 2     16 RR    Rainbow Road <NA>         4 Spec…        16 Nitro Trac…        16
## 3     17 rMMM  Moo Moo Mea… Wii          1 Shel…         1 Retro Trac…        17
## 4     18 rMC   Mario Circu… GBA          2 Shel…         2 Retro Trac…        18
## 5     79 bWS   Waluigi Sta… GCN          3 Boom…        15 Wave 3 + 4…        31
## 6     80 bSSy  Singapore S… Tour         4 Boom…        16 Wave 3 + 4…        32
## 7     81 bAtD  Athens Dash  Tour         1 Feat…         1 Wave 5 + 6…        33
## 8     82 bDC   Daisy Cruis… GCN          2 Feat…         2 Wave 5 + 6…        34

Credits

This package is based on Chipdelmal’s MK8D package, which uses python to convert lss files to a dataframe.