首页 \ 问答 \ 我如何组织这些数据?(How do I organize this data?)

我如何组织这些数据?(How do I organize this data?)

我有一个有50多个问题的iOS应用程序。 每个问题都有:

  1. 一个问题
  2. 正确答案
  3. 三个错误的答案
  4. 图片名称

最初我尝试使用一个结构(如下图),并为每个问题创建一个常量,当用户得到这个问题时我可以调用/加载:

struct QuestionInfo {
    var question: String
    var correctAnswer: String
    var wrongAnswer_1: String?
    var wrongAnswer_2: String?
    var wrongAnswer_3: String?
    var imageName: String
}

不过,我被告知这是一个愚蠢的想法,我应该使用数组。 我明白数组是指这种类型的东西,但我如何保持它的组织?

好像我有六个数组:

let question = ["Is Mars a planet?", "Is Spain in Africa?", "+50 more"]
let correctAnswer = ["Yes", "No", "+50 more"]
//+Four more arrays

每个阵列将有50多个项目,每个问题将一次列入六个不同的列表,这使我很难保持组织。 我应该为每个问题创建一个数组/结构,然后创建一个数组/结构数组?

let questionPackage = QuestionInfo(
        question: "Is Mars a planet?",
        correctAnswer: "Yes",
        wrongAnswer_1: "No",
        wrongAnswer_2: "No one knows.",
        wrongAnswer_3: "It's a candy bar."
        imageName: "MarsPhoto",
    )
let questionPackage2  = QuestionInfo(
        question: "Is Spain in Africa?",
        correctAnswer: "No",
        wrongAnswer_1: "Yes",
        wrongAnswer_2: "It's up for debate",
        wrongAnswer_3: "Duh, it's in South America."
        imageName: "SpanishFlag",
    )

//Array of structs
let array = [questionPackage, questionPackage2, etc]

我试图根据最有效的运行方式和正常的设计模式进行选择。


I have an iOS app with 50+ questions. Each question has:

  1. A question
  2. Correct answer
  3. Three incorrect answers
  4. An image name

Originally I tried using a struct (like below) and creating a constant for each question that I could call/load when the user gets that question:

struct QuestionInfo {
    var question: String
    var correctAnswer: String
    var wrongAnswer_1: String?
    var wrongAnswer_2: String?
    var wrongAnswer_3: String?
    var imageName: String
}

However, I've been told that was a dumb idea and that I should use arrays. I understand arrays are meant for this type of thing, but how do I keep it organized?

It seems like I'll have six arrays:

let question = ["Is Mars a planet?", "Is Spain in Africa?", "+50 more"]
let correctAnswer = ["Yes", "No", "+50 more"]
//+Four more arrays

Each array will be 50+ items long and each question will be in six different lists at once, making it difficult for me to stay organized. Should I create an array/struct for each question and then make an array of arrays/structs??

let questionPackage = QuestionInfo(
        question: "Is Mars a planet?",
        correctAnswer: "Yes",
        wrongAnswer_1: "No",
        wrongAnswer_2: "No one knows.",
        wrongAnswer_3: "It's a candy bar."
        imageName: "MarsPhoto",
    )
let questionPackage2  = QuestionInfo(
        question: "Is Spain in Africa?",
        correctAnswer: "No",
        wrongAnswer_1: "Yes",
        wrongAnswer_2: "It's up for debate",
        wrongAnswer_3: "Duh, it's in South America."
        imageName: "SpanishFlag",
    )

//Array of structs
let array = [questionPackage, questionPackage2, etc]

I'm trying to choose based on what will run most efficiently and a normal design pattern.


原文:https://stackoverflow.com/questions/38297481
更新时间:2023-08-16 22:08

最满意答案

使用sparklyr你可以按照sparklyr建议使用arrayexplode

df_tbl %>% 
  mutate(arr = explode(array(1, 1, 1))) %>% 
  select(-arr)

# # Source:   lazy query [?? x 2]
# # Database: spark_connection
#    row1 row2 
#   <int> <chr>
# 1     1 A    
# 2     1 A    
# 3     1 A    
# 4     2 B    
# 5     2 B    
# 6     2 B    
# 7     3 C    
# 8     3 C    
# 9     3 C    

并且概括

library(rlang)

df_tbl %>%  
  mutate(arr = !!rlang::parse_quo(
    paste("explode(array(", paste(rep(1, 3), collapse = ","), "))")
  )) %>% select(-arr)

# # Source:   lazy query [?? x 2]
# # Database: spark_connection
#    row1 row2 
#   <int> <chr>
# 1     1 A    
# 2     1 A    
# 3     1 A    
# 4     2 B    
# 5     2 B    
# 6     2 B    
# 7     3 C    
# 8     3 C    
# 9     3 C   

您可以在其中轻松调整行数。


With sparklyr you can use array and explode as suggested by @Oli:

df_tbl %>% 
  mutate(arr = explode(array(1, 1, 1))) %>% 
  select(-arr)

# # Source:   lazy query [?? x 2]
# # Database: spark_connection
#    row1 row2 
#   <int> <chr>
# 1     1 A    
# 2     1 A    
# 3     1 A    
# 4     2 B    
# 5     2 B    
# 6     2 B    
# 7     3 C    
# 8     3 C    
# 9     3 C    

and generalized

library(rlang)

df_tbl %>%  
  mutate(arr = !!rlang::parse_quo(
    paste("explode(array(", paste(rep(1, 3), collapse = ","), "))")
  )) %>% select(-arr)

# # Source:   lazy query [?? x 2]
# # Database: spark_connection
#    row1 row2 
#   <int> <chr>
# 1     1 A    
# 2     1 A    
# 3     1 A    
# 4     2 B    
# 5     2 B    
# 6     2 B    
# 7     3 C    
# 8     3 C    
# 9     3 C   

where you can easily adjust number of rows.

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