anupam.io anupam-io

Git: The version control system

git remote add origin https://github.com/akcgjc007/avl_tree.git: Connect your git to an existring online repository
git remote -v: Show connected repositories

	var path = require('path');
	var solc = require('solc');
	var fs = require('fs-extra');

	const buildPath = path.resolve(__dirname, 'build');
	fs.removeSync(buildPath);
	fs.mkdirSync(buildPath);

	fs.readdir(path.resolve(__dirname, 'contracts'), function (err, files) {
	//listing all files using forEach

	const Web3 = require('web3');

	const compiledContract = require('./../build/MyContract.json');

	const rpcEndpoint = 'rpc-END-POINT';
	// you will get from ganache-GUI

	// Setting up the provider
	const provider = new Web3.providers.HttpProvider(rpcEndpoint);
	const web3 = new Web3(provider);

	import matplotlib.pyplot as plt
	import numpy as np
	import time
	from random import randint

	n = 10
	x = []
	y = []

	plt.ion()

	import matplotlib.pyplot as plt
	from random import randint, uniform

	plt.rcParams['figure.figsize'] = [10, 6]
	n = 20

	x = [uniform(0, 100) for i in range(n)] # x axis position
	y = [uniform(0, 100) for i in range(n)] # y axis position
	rad = [uniform(0, 1000) for i in range(n)] # radius of the circle
	cat = [randint(1, 5) for i in range(n)] # category

	from time import time
	n = 10**4
	arr = [i for i in range(n)]

	def test_fun(i):
	# some compuatations
	a =0
	b =0
	a+=arr[i]arr[i]arr[i]arr[i]arr[i]*arr[i]
	b+=arr[i]+arr[i]+arr[i]+arr[i]+arr[i]+arr[i]

	drop database if exists db;
	create database db;
	use db;

	drop table if exists a,b;

	create table a(attr1 varchar(50), score int(10));
	insert into a (attr1, score)values
	("info1", 1), ("info2", 2);

	SET GLOBAL validate_password.length = 4;
	SET GLOBAL validate_password.mixed_case_count = 0;
	SET GLOBAL validate_password.number_count = 0;
	SET GLOBAL validate_password.policy = LOW;
	SET GLOBAL validate_password.special_char_count = 0;
	ALTER USER 'root'@'localhost' IDENTIFIED WITH mysql_native_password BY 'test';

	import numpy as np
	import cv2

	img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
	img = cv2.resize(img, (20, 20))
	img = np.array(img).ravel()
	img = img.reshape(-1)

	print(img)