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class Python < Formula | |
desc "Interpreted, interactive, object-oriented programming language" | |
homepage "https://www.python.org/" | |
url "https://www.python.org/ftp/python/3.8.6/Python-3.8.6.tar.xz" | |
sha256 "a9e0b79d27aa056eb9cce8d63a427b5f9bab1465dee3f942dcfdb25a82f4ab8a" | |
head "https://github.com/python/cpython.git" | |
license "Python-2.0" | |
revision 1 | |
bottle do |
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""" | |
unpacks rar files that are double-packed | |
-usually scene-release files are packed this way | |
""" | |
__author__ = 'iexa' | |
from pathlib import Path | |
import rarfile as rf | |
from time import time | |
# import zipfile as zf |
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// dl.js script, dl.json is {'folder_name1': [url1, url2, url3, ...], 'folder_name2': [...], ...} | |
// | |
// 1st "major" mod - now uses async "threads" to download several files at once. m.o. is not the | |
// best way to do it; but it saves some time and does not overwhelm servers | |
// | |
// examples for data scraping :D | |
// a = document.querySelectorAll('ul#list>li>a.folder') | |
// JSON.stringify(Array.prototype.map.call(a, i => decodeURI(i.href.split('/').reverse()[1]))) | |
// | |
// ... and files from inside folders: |
This document is a collection of concepts and strategies to make large Elm projects modular and extensible.
We will start by thinking about the structure of signals in our program. Broadly speaking, your application state should live in one big foldp
. You will probably merge
a bunch of input signals into a single stream of updates. This sounds a bit crazy at first, but it is in the same ballpark as Om or Facebook's Flux. There are a couple major benefits to having a centralized home for your application state:
- There is a single source of truth. Traditional approaches force you to write a decent amount of custom and error prone code to synchronize state between many different stateful components. (The state of this widget needs to be synced with the application state, which needs to be synced with some other widget, etc.) By placing all of your state in one location, you eliminate an entire class of bugs in which two components get into inconsistent states. We also think yo
Picking the right architecture = Picking the right battles + Managing trade-offs
- Clarify and agree on the scope of the system
- User cases (description of sequences of events that, taken together, lead to a system doing something useful)
- Who is going to use it?
- How are they going to use it?
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#!/usr/bin/env python3 | |
""" | |
Handbrake (json) Queue Creator | |
last updated: 2021/oct/9 iexa | |
changelog: | |
- 21/oct/9: open hb.json file in utf8 encoding to be sure | |
- 21/jul/15: added rotation check | |
- 21/jun/23: added ffmpeg automatic resolution sniffing | |
""" |
- modern data science with r:
https://mdsr-book.github.io/mdsr2e/
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user = { | |
name: 'Joe', | |
active: true, | |
purchases: [], | |
cart: [] | |
} | |
const compose = (f, g) => { return (...args) => f(g(...args)) } // in reduce new acc/f will be a fn | |
// all functions are coiled up from last to first - |
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// const {log} = console | |
// merge sorted | |
a = [0, 4, 6, 7]; | |
b = [1, 2, 3, 4, 8]; | |
function mergeSorted(x1, x2) { | |
const out = []; | |
const [l1, l2] = [x1.length, x2.length]; | |
let [i1, i2] = [0, 0]; |
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