# Livesplit-Parser
#### A Python Package to Parse Your Data Regarding Your Speedruns
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](https://trevorbushnell.github.io/livesplit_parser/).
## Example Usage
```python
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)
```
## TODO Features to Include
- [x] Include a `StandDev` column in the `split_info_df` that includes the standard deviation of all your attempts for that split
- [x] Plot split time distributions using *violinplots*
- [x] Plot runtime distributions with the splits on the x-axis and standard deviation on the y-axis
- [x] Plot number of runs that reset between completed runs
- [x] Plot completed runs over time (run ID on x-axis, final time on y-axis)
- [x] 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](https://github.com/TrevorBushnell/livesplit_parser/issues) on my GitHub repo :)
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"description": "\n# Livesplit-Parser\n\n#### A Python Package to Parse Your Data Regarding Your Speedruns\n\nThis Pyton package parses LiveSplit files and parses data within LiveSplit files.\n\nInstall this package with `pip install livesplit_parser`\n\nCheck out the documentation for this package [here](https://trevorbushnell.github.io/livesplit_parser/).\n\n\n## Example Usage\n\n```python\nfrom livesplit_parser import LivesplitData\n\nlss_path = '' # put the path to your .lss file here\nmy_run = LivesplitData(lss_path)\n\nprint('NUMBER OF ATTEMPTS:', my_run.num_attempts)\nprint('NUMBER OF COMPLETED ATTEMPTS:', my_run.num_completed_attempts)\nprint('PERCENTAGE OF RUNS COMPLETED:', my_run.percent_runs_completed)\nprint('YOUR ATTEMPT DATA\\n:', my_run.attempt_info_df)\nprint('YOUR SPLIT DATA:\\n', my_run.split_info_df)\n```\n\n## TODO Features to Include\n\n- [x] Include a `StandDev` column in the `split_info_df` that includes the standard deviation of all your attempts for that split\n- [x] Plot split time distributions using *violinplots*\n- [x] Plot runtime distributions with the splits on the x-axis and standard deviation on the y-axis\n- [x] Plot number of runs that reset between completed runs\n- [x] Plot completed runs over time (run ID on x-axis, final time on y-axis)\n- [x] Plot completed runs with a heatmap showing how good that segment was for that run\n- [ ] Create a Runner class that contains a list of Runners with their data and methods that plot runs against each other\n\t* example: plot each runner's PB over time (runners can compare themselves against each other)\n\t* 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\n\nOther ideas for plots and features can be submitted to the [Issues board](https://github.com/TrevorBushnell/livesplit_parser/issues) on my GitHub repo :)\n",
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