我在演示者中制作了一个角色应用，并且不明白为什么会这样。
我有这个测试：
beforeEach(function() {
browser.get('http://localhost:8080/#/');
...
//name
let name = element(by.css("*[id='field_nombre']"));
}
it('Scenario 1', function () {
name.click();
....
我这样做：
beforeEach(function() {
browser.get('http://localhost:8080/#/');
...
}
it('Scenario 1', function () {
//name
let name = element(by.css("*[id='field_nombre']"));
name.click();
....
测试工作正常。有没有任何理由为什么它不会在之前认识到某些变量初始化？
答案 0 :(得分：1)
9:00:00 To 09:30:00
答案 1 :(得分：1)
if __name__ == '__main__':
n = int(input())
if n in range(2,11):
student_marks = {}
for _ in range(n):
line = input().split()
name = line[0]
scores = line[1:]
scores = list(map(float, scores))
truth,x,y = 0,0,0
y = len(scores)
for x in scores:
if 0<=x<=100:
truth = truth+1
if(truth == y):
student_marks[name] = scores
else:
print("Marks out of range")
query_name = input()
add = 0
m=0
for s in student_marks[query_name]:
m = m+1
if x in student_marks:
if x == query_name :
for y in student_marks[query_name]:
add = add + y
average = float(add/m)
else:
print("Name doesnt exist.Enter correct name and start again")
else:
print("The person not ideally linked,since incorrect marks entered,Enter properly and try again")
print("%.2f" % average)
有自己独立的功能范围，beforeEach有自己的功能范围。我们无法访问之前从其他函数初始化的变量。
在beforeeach函数之外初始化变量。
it答案 2 :(得分：1)
let name = element(by.css("*[id='field_nombre']"));
名称在beforeEach()内定义。因此，名称范围仅在beforeEach()内可用。它无法从方法外部访问
答案 3 :(得分：0)
因为您的 (type) Output Shape Param #
=================================================================
model_5 (Model) (None, 12) 26725324
=================================================================
Total params: 26,725,324
Trainable params: 26,670,156
Non-trainable params: 55,168
_________________________________________________________________
Found 1774 images belonging to 12 classes.
Found 313 images belonging to 12 classes.
.
.
.
Epoch 70/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5433 - acc: 0.8987 - val_loss: 0.8271 - val_acc: 0.7796
Epoch 71/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5353 - acc: 0.9145 - val_loss: 0.7954 - val_acc: 0.7508
Epoch 72/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5353 - acc: 0.8955 - val_loss: 0.8690 - val_acc: 0.7348
Epoch 73/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5310 - acc: 0.9037 - val_loss: 0.8673 - val_acc: 0.7476
Epoch 74/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5189 - acc: 0.8943 - val_loss: 0.8701 - val_acc: 0.7380
Epoch 75/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5333 - acc: 0.8952 - val_loss: 0.9399 - val_acc: 0.7188
Epoch 76/100
56/55 [==============================] - 49s 879ms/step - loss: 0.5106 - acc: 0.9043 - val_loss: 0.8107 - val_acc: 0.7700
Epoch 77/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5108 - acc: 0.9064 - val_loss: 0.9624 - val_acc: 0.6869
Epoch 78/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5214 - acc: 0.8994 - val_loss: 0.9602 - val_acc: 0.6933
Epoch 79/100
56/55 [==============================] - 49s 880ms/step - loss: 0.5246 - acc: 0.9009 - val_loss: 0.8379 - val_acc: 0.7572
Epoch 80/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4859 - acc: 0.9082 - val_loss: 0.7856 - val_acc: 0.7796
Epoch 81/100
56/55 [==============================] - 49s 881ms/step - loss: 0.5005 - acc: 0.9175 - val_loss: 0.7609 - val_acc: 0.7827
Epoch 82/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4690 - acc: 0.9294 - val_loss: 0.7671 - val_acc: 0.7636
Epoch 83/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4897 - acc: 0.9146 - val_loss: 0.7902 - val_acc: 0.7636
Epoch 84/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4604 - acc: 0.9291 - val_loss: 0.7603 - val_acc: 0.7636
Epoch 85/100
56/55 [==============================] - 49s 881ms/step - loss: 0.4750 - acc: 0.9220 - val_loss: 0.7325 - val_acc: 0.7668
Epoch 86/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4524 - acc: 0.9266 - val_loss: 0.7782 - val_acc: 0.7636
Epoch 87/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4643 - acc: 0.9172 - val_loss: 0.9892 - val_acc: 0.6901
Epoch 88/100
56/55 [==============================] - 49s 881ms/step - loss: 0.4718 - acc: 0.9177 - val_loss: 0.8269 - val_acc: 0.7380
Epoch 89/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4646 - acc: 0.9290 - val_loss: 0.7846 - val_acc: 0.7604
Epoch 90/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4433 - acc: 0.9341 - val_loss: 0.7693 - val_acc: 0.7764
Epoch 91/100
56/55 [==============================] - 49s 877ms/step - loss: 0.4706 - acc: 0.9196 - val_loss: 0.8200 - val_acc: 0.7604
Epoch 92/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4572 - acc: 0.9184 - val_loss: 0.9220 - val_acc: 0.7220
Epoch 93/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4479 - acc: 0.9175 - val_loss: 0.8781 - val_acc: 0.7348
Epoch 94/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4793 - acc: 0.9100 - val_loss: 0.8035 - val_acc: 0.7572
Epoch 95/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4329 - acc: 0.9279 - val_loss: 0.7750 - val_acc: 0.7796
Epoch 96/100
56/55 [==============================] - 49s 879ms/step - loss: 0.4361 - acc: 0.9212 - val_loss: 0.8124 - val_acc: 0.7508
Epoch 97/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4371 - acc: 0.9202 - val_loss: 0.9806 - val_acc: 0.7029
Epoch 98/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4298 - acc: 0.9149 - val_loss: 0.8637 - val_acc: 0.7380
Epoch 99/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4370 - acc: 0.9255 - val_loss: 0.8349 - val_acc: 0.7604
Epoch 100/100
56/55 [==============================] - 49s 880ms/step - loss: 0.4407 - acc: 0.9205 - val_loss: 0.8477 - val_acc: 0.7508
与其使用的范围不同。
在JS let name =中，关键字将范围从功能范围缩小到块范围：
let