chelseatroy

import XCTest
import Hamcrest
import FutureKit

@testable import FruitApp

class ListOfFruitsViewControllerTest: XCTestCase {
    ...

    func testShowsFruitDetailsWhenFruitRowIsTapped() {

chelseatroy

import XCTest
import Hamcrest
import FutureKit

@testable import MyExampleApp

class ExampleViewControllerTest: XCTestCase {
    var fakeExampleService: FakeExampleService!

    override func setUp() {

chelseatroy

import XCTest
import Hamcrest
import FutureKit

@testable import MyExampleApp

class ExampleViewControllerTest: XCTestCase {

   ...
   

chelseatroy

@Configuration
@EnableBatchProcessing
public class XmlParsingApplication {

	@Bean
	public StaxEventItemReader itemReader() throws Exception {
		StaxEventItemReader reader = new StaxEventItemReader<>();

		reader.setName("birthday");
		reader.setResource(new ClassPathResource("all_members.xml"));

chelseatroy

import FutureKit
import SwiftyJSON

class VillainService {
    let url: String
    var session: URLSession = URLSession.shared

    func getVillainList() -> Future<VillainResponse> {
        let promise = Promise<VillainResponse>()
        

chelseatroy

import XCTest
import Nimble

import SwiftyJSON
import FutureKit

@testable import VillainApp

class VillainServiceTest: XCTestCase {
    var service: VillainService!

chelseatroy

class MockSession: URLSession {
    var completionHandler: ((Data?, URLResponse?, Error?) -> Void)?
    var request: URLRequest?
    let stubbedDataTask: MockURLSessionDataTask = MockURLSessionDataTask()
    
    override func dataTask(with request: URLRequest, completionHandler: @escaping (Data?, URLResponse?, Error?) -> Void) -> URLSessionDataTask {
        self.completionHandler = completionHandler
        self.request = request
        
        return stubbedDataTask

chelseatroy

import FutureKit
import UIKit

class VillainsMasterViewController: UIViewController {
  let villainService: VillainService?
  
  ...
  
  func viewDidLoad() {
      villainService?.getVillainList()

chelseatroy

class LinearRegressor(Object):
  
    def gradient_descent(self, x, y, alpha, max_iterations):
        num_rows = x.shape[1] + 1
        w = np.array([random.random() for item in range(num_rows)]).reshape(num_rows,1)
        
        best_weights = []
        lowest_cost = None

        iter = 1

chelseatroy

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import autograd.numpy as np  # Thinly-wrapped numpy
from autograd import grad as compute_grad   # The only autograd function you may ever need

class learner():
    def __init__(self,**args):