werterzz

# using lambda function inside filter function
drinks = ['beer', 'beer', 'milk', 'beer']
print(list(filter(lambda drink: (drink == 'beer'), drinks)))

# output: ['beer', 'beer', 'beer']

werterzz

# using lambda function inside filter function
drinks = ['beer', 'beer', 'milk', 'beer']
print(list(filter(lambda drink: (drink == 'beer'), drinks)))
# output: ['beer', 'beer', 'beer']

werterzz

# create grill function receive 1 argument
grill = lambda food: "grilled " + food
print(grill('beef'))
# output: grilled beef

# create cook function receive 2 arguments
cook = lambda cook, food: cook + " " + food
print(cook("boil", "egg"))
# output: boil egg

werterzz

# global scope
outer = "eggshell"


def egg():
    # enclosing scope
    middle = "egg white"

    def inner_egg():
        # local scope

werterzz

const doYouLikeDog = (answer) => {
  return answer === true ? "you like dogs." : answer === false ? "you don't like dogs." : "you didn't answer my question."
}

test('pass true on doYouLikeDog()', () => {
  expect(doYouLikeDog(true)).toBe("you like dogs.");
});

test('pass false on doYouLikeDog()', () => {
  expect(doYouLikeDog(false)).toBe("you don't like dogs.");

werterzz

const doYouLikeDog = (answer) => { // cover
  if (answer === true) return "you like dogs." // cover
  else if (answer === false) return "you don't like dogs." // cover
  else return "you didn't answer my question." // not cover
} // cover

//-----------------------------------

test('pass true on doYouLikeDog()', () => {
  expect(doYouLikeDog(true)).toBe("you like dogs.");

werterzz

npArrData = np.array([1, 2, 3])
listData = npArrData.tolist()

print("npArrData: ", type(npArrData), ": ", npArrData)
print("listData:", type(listData), ": ", listData)

# Output
# npArrData:  <class 'numpy.ndarray'> :  [1 2 3]
# listData: <class 'list'> :  [1, 2, 3]

werterzz

listData = [1, 2, 3]
npArrData = np.asarray(listData)

print("listData:", type(listData), ": ", listData)
print("npArrData: ", type(npArrData), ": ", npArrData)

# Output
# listData: <class 'list'> :  [1, 2, 3]
# npArrData:  <class 'numpy.ndarray'> :  [1 2 3]

werterzz

floatArr = np.random.rand(2, 4)
intArr = np.random.randint(100, size=(2, 4))

print("floatArr: \n" + str(floatArr))
print("\nintArr: \n" + str(intArr))

multArr = np.multiply(floatArr, intArr)

print("\nmultArr: \n" + str(multArr))

werterzz

np.random.rand(2,4)

# Output
# array([[0.62998756, 0.59149609, 0.57944416, 0.485989  ],
#        [0.72946946, 0.47362045, 0.14221045, 0.27405028]])