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def merge_sort(input_list): | |
""" | |
merge_sort is a divide-and-conquer algorithm that repeatedly breaks | |
down the large task of sorting into smaller sub-problems that are | |
much easier given the following insight: | |
Insight 1: If the list only contains 1 element, it's already sorted. | |
Insight 2: If you have two lists that are already sorted, you can merge | |
the two sorted lists to create a larger sorted list. |
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def selection_sort(input_list): | |
# Save the length of the list | |
n = len(input_list) | |
# NOTE: In Python, enumerate returns an index, value pair. | |
# The _ means that we're ignoring the value. | |
for current_index, _ in enumerate(input_list): | |
# Save the location of the smallest item in the list | |
smallest_index = current_index |
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# Here's a list of 5 people. | |
example_array = ["Alice", "Bob", "Jess", "Lisa", "Susan"] | |
middle = len(example_array) // 2 | |
# This is shorthand for saying: "Give me the first half of the array" | |
# This is equivalent to example_array[0:middle] | |
first_half = example_array[:middle] | |
# ['Alice', 'Bob'] |
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def binary_search(ordered_list, search_item): | |
# If the length of the list is zero, it's empty, | |
# so the search_item can't be in the list. | |
if len(ordered_list) == 0: | |
return False | |
# Otherwise, let's try to find the item... | |
else: | |
middle_item = len(ordered_list) // 2 |
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library(yaml) | |
# setwd("~/directory/to/nile/configs") | |
# Create data frame with desired input fields | |
yamlFile <- yaml.load_file("nile.yml") | |
# Load configurations into a dataframe | |
df <- data.frame( | |
lapply( |
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# Mixer ######################################## | |
theme_channel = 1 | |
bass_channel = 0 | |
slicer_channel = 0 | |
sparkle_channel = 0 | |
# Fader ######################################## | |
overall_volume = 1 | |
bass_volume = 0.5 | |
sparkle_volume = 1 | |
sparkle_speed = 0.125 |
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# Hello... World | |
use_bpm 75 | |
use_synth :fm | |
in_thread do | |
loop do | |
cue :tick | |
sleep 1 | |
end | |
end |
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