This Pyton package parses LiveSplit files and parses data within LiveSplit files.
Install this package with pip install livesplit_parser
Check out the documentation for this package here.
from livesplit_parser import LivesplitData
lss_path = '' # put the path to your .lss file here
my_run = LivesplitData(lss_path)
print('NUMBER OF ATTEMPTS:', my_run.num_attempts)
print('NUMBER OF COMPLETED ATTEMPTS:', my_run.num_completed_attempts)
print('PERCENTAGE OF RUNS COMPLETED:', my_run.percent_runs_completed)
print('YOUR ATTEMPT DATA\n:', my_run.attempt_info_df)
print('YOUR SPLIT DATA:\n', my_run.split_info_df)
- Include a
StandDev
column in thesplit_info_df
that includes the standard deviation of all your attempts for that split - Plot split time distributions using violinplots
- Plot runtime distributions with the splits on the x-axis and standard deviation on the y-axis
- Plot number of runs that reset between completed runs
- Plot completed runs over time (run ID on x-axis, final time on y-axis)
- Plot completed runs with a heatmap showing how good that segment was for that run
- Create a Runner class that contains a list of Runners with their data and methods that plot runs against each other
- example: plot each runner's PB over time (runners can compare themselves against each other)
- another example: heatmap from before with splits on the x-axis, runner on the y-axis, and heatmap comparing that segment with the means of the personal bests of every runner included
Other ideas for plots and features can be submitted to the Issues board on my GitHub repo :)