Created using the following ChatGPT conversation: https://chat.openai.com/share/9cac1fad-851d-4f43-87da-17d64b3f4e02
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{ | |
"name": "Dactyl Manuform (5x6+6)", | |
"vendorId": "0xFDDD", | |
"productId": "0x06AD", | |
"lighting": "none", | |
"matrix": { "rows": 12, "cols": 6 }, | |
"layouts": { | |
"keymap": [ | |
[{ "x": 3 }, "0,3", { "x": 8.5 }, "6,2"], | |
[ |
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[tool.pylint.messages_control] | |
disable = [ | |
"arguments-differ", | |
"attribute-defined-outside-init", | |
"bad-continuation", | |
"blacklisted-name", | |
"duplicate-code", | |
"fixme", | |
"import-error", | |
"no-member", |
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sudo dnf install kernel --enablerepo=updates-testing --best --allowerasing | |
sudo dnf config-manager --add-repo=https://negativo17.org/repos/fedora-nvidia.repo | |
sudo dnf update | |
sudo dnf -y remove "nouveau*" | |
sudo dnf -y install nvidia-driver akmod-nvidia nvidia-driver-cuda |
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""" | |
Iterates through a directory of exported MindMup .mup files and prints the title of each file that matches the given | |
regular expression, as well as the matched node contents. | |
MindMup is a mind mapping tool which represents the Directed Acyclic Graph (DAG) of a mind map as a nested dictionary encoded as JSON. | |
""" | |
import argparse | |
import json | |
from pathlib import Path |
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""" | |
An example of nested fanout using Ray Workflows. | |
The full workflow creates several batches given a single input, then each of those batches is fanned-out and evaluated. | |
""" | |
import time | |
import ray | |
from ray import workflow |
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import math | |
import numpy as np | |
import matplotlib.pyplot as plot | |
import matplotlib.cm as cm | |
import sys | |
import pylab | |
from matplotlib.widgets import Slider | |
range_inc = lambda start, end: range(start, end+1) #Because this is easier to write and read |
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import numpy as np | |
import math | |
from mpl_toolkits.mplot3d import Axes3D | |
import matplotlib.pyplot as plt | |
import sys | |
import pylab | |
from matplotlib.widgets import Slider | |
#from IPython.core import ultratb | |
#sys.excepthook = ultratb.FormattedTB(mode='Verbose', | |
# color_scheme='Linux', call_pdb=1) |
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import concurrent.futures | |
import random | |
import time | |
import ray | |
@ray.remote | |
def append_a(in_str): | |
print(in_str) | |
time.sleep(random.uniform(0, 1.5)) |
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def hello(name): | |
return "Hello" + name | |
name = input("Enter your name: ") | |
print(hello(name)) |
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