Kyle Hovey kylehovey

## itt-coc.ts
// A nano dependent type-checker featuring inductive types via self encodings.
// All computation rules are justified by interaction combinator semantics,
// resulting in major simplifications and improvements over old Kind-Core.
// Specifically, computable annotations (ANNs) and their counterpart (ANN
// binders) and a new self encoding based on equality (rather than dependent
// motives) greatly reduce code size. A more complete file, including
// superpositions (for optimal unification) is available on the
// Interaction-Type-Theory repository.
// Credits also to Franchu and T6 for insights.

## Easy Minecraft on Apple Silicon.md

      
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                estyseesghosts
                / Easy Minecraft on Apple Silicon.md
            
            
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              October 11, 2024 12:12
            
              
                A (slightly) easier way to install Minecraft natively on Apple Silicon, inspired by https://gist.github.com/tanmayb123/d55b16c493326945385e815453de411a and https://gist.github.com/tanmayb123/d55b16c493326945385e815453de411a#gistcomment-3564251
              
          
    How to install Minecraft natively on Apple Silicon, the easiest way possible

1 - Download MultiMC from here
2 - Download Azul Zulu JDK from here (The version you want is Java 17, arm64, macOS, and you download the ZIP file.) Extract the ZIP file, open the folder and copy "zulu-17.jdk" to your home folder.
3 - Download tanmayb123's Minecraft on Apple Silicon package from here. Extract the ZIP and from the folder you are going to copy two files. One, the folder "lwjglnatives", and two, open the Libraries folder and copy "lwjglfat.jar". Move these to your home folder.
4 - Open MultiMC and create a new instance. Right click your instance and click edit instance. Make the following changes:

  
## tasks_to_ical.py
#!/usr/bin/env python3
import os.path
from ics import Calendar, Event
import subprocess
import json

def read_tasks():
    output = subprocess.check_output(['task', 'export'])
    for task in json.loads(output.decode('utf-8')):
        if task['status'] == 'completed':
	// A nano dependent type-checker featuring inductive types via self encodings.
	// All computation rules are justified by interaction combinator semantics,
	// resulting in major simplifications and improvements over old Kind-Core.
	// Specifically, computable annotations (ANNs) and their counterpart (ANN
	// binders) and a new self encoding based on equality (rather than dependent
	// motives) greatly reduce code size. A more complete file, including
	// superpositions (for optimal unification) is available on the
	// Interaction-Type-Theory repository.
	// Credits also to Franchu and T6 for insights.
	#!/usr/bin/env python3
	import os.path
	from ics import Calendar, Event
	import subprocess
	import json

	def read_tasks():
	output = subprocess.check_output(['task', 'export'])
	for task in json.loads(output.decode('utf-8')):
	if task['status'] == 'completed':