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UNT canvas file finder utility

Nov 18, 2022AustinLeath
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Mongoose Model

Mar 11, 2021C S

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const mongoose = require('mongoose')
const UserSchema = new mongoose.Schema({
username: {
type: String,
required: true
},
email: {
type: String,
unique: true,
required: true
},
password: {
type: String,
required: true
},
date: {
type: Date,
default: Date.now
}
})
module.exports = User = mongoose.model('user', UserSchema)

Redux Setup

Mar 11, 2021C S

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import { configureStore } from "@reduxjs/toolkit";
import { combineReducers } from "redux";
import profile from "./profile";
import auth from "./auth";
import alert from "./alert";
const reducer = combineReducers({
profile,
auth,
alert,
});
const store = configureStore({ reducer });
export default store;
function printHeap(heap, index, level) {
if (index >= heap.length) {
return;
}
console.log(" ".repeat(level) + heap[index]);
printHeap(heap, 2 * index + 1, level + 1);
printHeap(heap, 2 * index + 2, level + 1);
}
//You can call this function by passing in the heap array and the index of the root node, which is typically 0, and level = 0.
let heap = [3, 8, 7, 15, 17, 30, 35, 2, 4, 5, 9];
printHeap(heap,0,0)

K-means clustering

Nov 19, 2022CodeCatch

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const kMeans = (data, k = 1) => {
const centroids = data.slice(0, k);
const distances = Array.from({ length: data.length }, () =>
Array.from({ length: k }, () => 0)
);
const classes = Array.from({ length: data.length }, () => -1);
let itr = true;
while (itr) {
itr = false;
for (let d in data) {
for (let c = 0; c < k; c++) {
distances[d][c] = Math.hypot(
...Object.keys(data[0]).map(key => data[d][key] - centroids[c][key])
);
}
const m = distances[d].indexOf(Math.min(...distances[d]));
if (classes[d] !== m) itr = true;
classes[d] = m;
}
for (let c = 0; c < k; c++) {
centroids[c] = Array.from({ length: data[0].length }, () => 0);
const size = data.reduce((acc, _, d) => {
if (classes[d] === c) {
acc++;
for (let i in data[0]) centroids[c][i] += data[d][i];
}
return acc;
}, 0);
for (let i in data[0]) {
centroids[c][i] = parseFloat(Number(centroids[c][i] / size).toFixed(2));
}
}
}
return classes;
};
kMeans([[0, 0], [0, 1], [1, 3], [2, 0]], 2); // [0, 1, 1, 0]

stripe api json iteration

Nov 18, 2022AustinLeath

0 likes • 1 view

var arr = [{
"success": true,
"data": [
{
"id": "ipi_1KrrbvDOiB2klwsKhuqUWqt1",
"object": "issuing.transaction",
"amount": -2743,
"amount_details": {
"atm_fee": null
},
"authorization": "iauth_1KrrbuDOiB2klwsKoFjQZhhd",
"balance_transaction": "txn_1KrrbwDOiB2klwsK1YkjJJRi",
"card": "ic_1Krqe5DOiB2klwsK44a35eiE",
"cardholder": "ich_1KrqL8DOiB2klwsKtBnZhzYr",
"created": 1650753567,
"currency": "usd",
"dispute": null,
"livemode": false,
"merchant_amount": -2743,
"merchant_currency": "usd",
"merchant_data": {
"category": "advertising_services",
"category_code": "7311",
"city": "San Francisco",
"country": "US",
"name": "Aeros Marketing, LLC",
"network_id": "1234567890",
"postal_code": "94103",
"state": "CA"
},
"metadata": {},
"type": "capture",
"wallet": null
},
{
"id": "ipi_1Krrbvc62B2klwsKhuqUWqt1",
"object": "issuing.transaction",
"amount": -9999,
"amount_details": {
"atm_fee": null
},
"authorization": "iauth_1KrrbuDOiB2klwsKoFjQZhhd",
"balance_transaction": "txn_1KrrbwDOiB2klwsK1YkjJJRi",
"card": "ic_1Krqe5DOiB2klwsK44a35eiE",
"cardholder": "ich_1KrqL8DOiB2klwsKtBnZhzYr",
"created": 1650753567,
"currency": "USD",
"dispute": null,
"livemode": false,
"merchant_amount": -9999,
"merchant_currency": "usd",
"merchant_data": {
"category": "fast_food",
"category_code": "7311",
"city": "San Francisco",
"country": "US",
"name": "Aeros Marketing, LLC",
"network_id": "1234567890",
"postal_code": "94103",
"state": "CA"
},
"metadata": {},
"type": "capture",
"wallet": null
}
]
}];
const reduced = arr.reduce((prev, curr) => {
prev.push({
amount: curr.data[0].merchant_amount,
id: curr.data[0].id,
currency: curr.data[0].currency,
category: curr.data[0].merchant_data.category
});
console.log(prev)
return prev;
}, []);

permutations

Nov 19, 2022CodeCatch

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const permutations = arr => {
if (arr.length <= 2) return arr.length === 2 ? [arr, [arr[1], arr[0]]] : arr;
return arr.reduce(
(acc, item, i) =>
acc.concat(
permutations([...arr.slice(0, i), ...arr.slice(i + 1)]).map(val => [
item,
...val,
])
),
[]
);
};
permutations([1, 33, 5]);
// [ [1, 33, 5], [1, 5, 33], [33, 1, 5], [33, 5, 1], [5, 1, 33], [5, 33, 1] ]