author electron github electron electron docs awesome-electron electron-react-boilerplate
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const MY_DOMAIN = 'example.com'; | |
/* | |
* Enter your Notion URL slug to page ID mapping | |
*/ | |
const SLUG_TO_PAGE = { | |
'': '771ef38657244c27b9389734a9cbff44', | |
}; | |
const PAGE_TITLE = ''; |
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#------------------------------------------------------------------- | |
# This is a compound interest calculator, along with some challenge | |
# Written by Leon Wee, March 2018. | |
# Anyone may freely copy or modify this program. | |
#------------------------------------------------------------------- | |
# C = P[(1+r)^n - 1] | |
# Where: | |
# C = the compound interest | |
# P = the principal investment amount (the initial deposit or loan amount) |
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# Online k-means algorithm | |
# see http://www.cs.princeton.edu/courses/archive/fall08/cos436/Duda/C/sk_means.htm | |
import numpy as np | |
def k_means(data, k, threshhold=2): | |
""" | |
Does k-means clustering of the data. | |
Args: |
$ sudo npm install -g hexo-cli
$ hexo -v
hexo-cli: 0.1.9
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// https://maktabkhooneh.org/course/%D9%85%D8%A8%D8%A7%D9%86%DB%8C-%D8%A7%D9%82%D8%AA%D8%B5%D8%A7%D8%AF-mk170/ | |
[...document.querySelectorAll('a.chapter__unit')] | |
.map(x => () => fetch(x.href) | |
.then(x => x.text()) | |
.then(x => new DOMParser().parseFromString(x, 'text/html').querySelector('meta[property="og:video"]').content) | |
.then(y => console.log(y, x.children[1].innerText.trim().replace(/\s/g, '_') + '.mp4')) | |
) | |
.reduce((promise, next) => promise.then(next), Promise.resolve()) | |
.then(() => console.log('Finished!')); |
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/* | |
* LetterAvatar | |
* | |
* Create Letter avatar based on Initials - | |
* based on https://gist.github.com/leecrossley/6027780 | |
*/ | |
(function(w, d){ | |
function LetterAvatar (name, size) { |
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.DS_Store | |
Thumbs.db | |
db.json | |
debug.log | |
node_modules/ | |
public/ | |
.deploy/ | |
themes/ |
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