This script will automatically stop the video and play the next one in the list
- Replace 192.168.1.188:8080 with the correct ip address and port
- Install Chorus
| import path from "path"; | |
| import { listFiles } from "./listFiles"; | |
| /** | |
| └── test | |
| ├── file1.txt | |
| └── folder1 | |
| └── file2.txt | |
| */ |
| -- Sequence and defined type | |
| CREATE SEQUENCE IF NOT EXISTS events_id_seq; | |
| CREATE SEQUENCE IF NOT EXISTS countries_id_seq; | |
| CREATE SEQUENCE IF NOT EXISTS browsers_id_seq; | |
| CREATE SEQUENCE IF NOT EXISTS devices_id_seq; | |
| -- Table Definition | |
| CREATE TABLE "public"."countries" ( | |
| "id" int4 NOT NULL DEFAULT nextval('countries_id_seq'::regclass), | |
| "name" varchar, |
| /* | |
| How to map fields from an existing database to a Sequelize model with: | |
| - @Table({ tableName: '...' }) | |
| - @Column({ field: '...' }) | |
| */ | |
| import { | |
| Sequelize, | |
| Table, | |
| Model, |
| from sklearn.feature_extraction.text import CountVectorizer | |
| from sklearn.metrics.pairwise import cosine_similarity | |
| corpus = [ | |
| 'This is my first sentence', | |
| 'This is my second sentence' | |
| ] | |
| vectorizer = CountVectorizer() |
| prettier --write frontend/**/*.ts | |
| prettier --write backend/**/*.ts | |
| if [[ $(git ls-files -m) ]]; then | |
| echo "You need to run prettier on those files" | |
| git ls-files -m | |
| exit 1 | |
| fi |
| version: "3" | |
| services: | |
| web: | |
| build: . | |
| ports: | |
| - "3000:3000" | |
| - "5858:5858" | |
| volumes: | |
| - "./:/wanderpay" | |
| command: 'npm run dev' |
| from random import random | |
| from statistics import mean | |
| variables = [3, 5, 7, 10, 12, 13] | |
| weight = [.1, .05, .05, .2, .4, .2] | |
| if sum(weight) != 1: | |
| raise 'sum(weight) != 1' | |
| range_of_weight = [sum(weight[0:index + 1]) for index, w in enumerate(weight)] |
| # BBC Dataset: http://mlg.ucd.ie/datasets/bbc.html | |
| import os | |
| import glob | |
| import sys | |
| import nltk | |
| import numpy as np | |
| import scipy as sp | |
| from sklearn.cluster import KMeans |
This script will automatically stop the video and play the next one in the list
| { | |
| "presets": ["es2015", "stage-0"], | |
| "plugins": ["transform-decorators-legacy"] | |
| } |