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我目前正在评估drake一个项目，我想知道是否有办法以编程方式生成包含触发器的目标或计划的一部分。

我的理想用例/示例代码如下，但我在尝试使其工作时遇到问题，因为德雷克将我的函数用作命令，并且不读取触发器。

drake_fetch_remote_data <- function(remote_path, ...) {
  hash = retrive_remote_hash(remote_path)
  target(
    command = fetch_remote_data(remote_path),
    trigger = trigger(
      change = hash
    )
  )
}

plan <- drake_plan(
  df1 = drake_fetch_remote_data('path1'),
  df2 = drake_fetch_remote_data('path2'),
)
#> # A tibble: 2 x 2
#>   target   command                         
#>   <chr>    <expr>                          
#> 1 df1 drake_fetch_remote_data("path1")
#> 2 df2 drake_fetch_remote_data("path2")

下面的代码包括触发器。

drake_fetch_remote_data <- function(remote_path, ...) {
  hash = retrive_remote_hash(remote_path)
  target(
    command = fetch_remote_data(remote_path),
    trigger = trigger(
      change = hash
    )
  )
}

plan <- drake_plan(
  df1 = target(
    command = fetch_remote_data('path1'),
    trigger = trigger(change = lookup_hash('path1'))
  )
)
# A tibble: 1 x 3
#   target command                    trigger                               
#   <chr>  <expr>                     <expr>                                
# 1 df1    fetch_remote_data("path1") trigger(change = lookup_hash("path1"))
4

1 回答 1

2

绝对地！有几种方法。请查看https://ropenscilabs.github.io/drake-manual/plans.html#large-plans。

library(drake)

# Write out paths one by one.
drake_plan(
  df = target(
    drake_fetch_remote_data(path),
    transform = map(path = c("path1", "path2"))
  )
)
#> # A tibble: 2 x 2
#>   target   command                         
#>   <chr>    <expr>                          
#> 1 df_path1 drake_fetch_remote_data("path1")
#> 2 df_path2 drake_fetch_remote_data("path2")

# Or generate a large collection of paths.
drake_plan(
  df = target(
    drake_fetch_remote_data(path),
    transform = map(path = !!paste0("path", seq_len(10)))
  )
)
#> # A tibble: 10 x 2
#>    target    command                          
#>    <chr>     <expr>                           
#>  1 df_path1  drake_fetch_remote_data("path1") 
#>  2 df_path2  drake_fetch_remote_data("path2") 
#>  3 df_path3  drake_fetch_remote_data("path3") 
#>  4 df_path4  drake_fetch_remote_data("path4") 
#>  5 df_path5  drake_fetch_remote_data("path5") 
#>  6 df_path6  drake_fetch_remote_data("path6") 
#>  7 df_path7  drake_fetch_remote_data("path7") 
#>  8 df_path8  drake_fetch_remote_data("path8") 
#>  9 df_path9  drake_fetch_remote_data("path9") 
#> 10 df_path10 drake_fetch_remote_data("path10")

# You can reference a variable that stores the paths.
paths <- paste0("path", seq_len(10))
drake_plan(
  df = target(
    drake_fetch_remote_data(path),
    transform = map(path = !!paths)
  )
)
#> # A tibble: 10 x 2
#>    target    command                          
#>    <chr>     <expr>                           
#>  1 df_path1  drake_fetch_remote_data("path1") 
#>  2 df_path2  drake_fetch_remote_data("path2") 
#>  3 df_path3  drake_fetch_remote_data("path3") 
#>  4 df_path4  drake_fetch_remote_data("path4") 
#>  5 df_path5  drake_fetch_remote_data("path5") 
#>  6 df_path6  drake_fetch_remote_data("path6") 
#>  7 df_path7  drake_fetch_remote_data("path7") 
#>  8 df_path8  drake_fetch_remote_data("path8") 
#>  9 df_path9  drake_fetch_remote_data("path9") 
#> 10 df_path10 drake_fetch_remote_data("path10")

# Shorter target names.
ids = as.numeric(seq_len(10))
paths <- paste0("path", seq_len(10))
drake_plan(
  df = target(
    drake_fetch_remote_data(path),
    transform = map(path = !!paths, id = !!ids, .id = id)
  )
)
#> # A tibble: 10 x 2
#>    target command                          
#>    <chr>  <expr>                           
#>  1 df_1   drake_fetch_remote_data("path1") 
#>  2 df_2   drake_fetch_remote_data("path2") 
#>  3 df_3   drake_fetch_remote_data("path3") 
#>  4 df_4   drake_fetch_remote_data("path4") 
#>  5 df_5   drake_fetch_remote_data("path5") 
#>  6 df_6   drake_fetch_remote_data("path6") 
#>  7 df_7   drake_fetch_remote_data("path7") 
#>  8 df_8   drake_fetch_remote_data("path8") 
#>  9 df_9   drake_fetch_remote_data("path9") 
#> 10 df_10  drake_fetch_remote_data("path10")

由reprex 包（v0.2.1）于 2019 年 5 月 3 日创建

编辑 2019-05-05

触发器可以像命令一样使用分组变量。

library(drake)
ids <- as.numeric(seq_len(10))
paths <- paste0("path", seq_len(10))
drake_plan(
  df = target(
    fetch_data(path),
    trigger = trigger(change = hash_data(path)),
    transform = map(path = !!paths, id = !!ids, .id = id)
  )
)
#> # A tibble: 10 x 3
#>    target command              trigger                              
#>    <chr>  <expr>               <expr>                               
#>  1 df_1   fetch_data("path1")  trigger(change = hash_data("path1")) 
#>  2 df_2   fetch_data("path2")  trigger(change = hash_data("path2")) 
#>  3 df_3   fetch_data("path3")  trigger(change = hash_data("path3")) 
#>  4 df_4   fetch_data("path4")  trigger(change = hash_data("path4")) 
#>  5 df_5   fetch_data("path5")  trigger(change = hash_data("path5")) 
#>  6 df_6   fetch_data("path6")  trigger(change = hash_data("path6")) 
#>  7 df_7   fetch_data("path7")  trigger(change = hash_data("path7")) 
#>  8 df_8   fetch_data("path8")  trigger(change = hash_data("path8")) 
#>  9 df_9   fetch_data("path9")  trigger(change = hash_data("path9")) 
#> 10 df_10  fetch_data("path10") trigger(change = hash_data("path10"))

由reprex 包（v0.2.1）于 2019 年 5 月 6 日创建

为了更清楚起见，您还可以将命令target()作为命名参数。

library(drake)
ids <- as.numeric(seq_len(10))
paths <- paste0("path", seq_len(10))
drake_plan(
  df = target(
    command = fetch_data(path), # now named for clarity
    trigger = trigger(change = hash_data(path)),
    transform = map(path = !!paths, id = !!ids, .id = id)
  )
)
#> # A tibble: 10 x 3
#>    target command              trigger                              
#>    <chr>  <expr>               <expr>                               
#>  1 df_1   fetch_data("path1")  trigger(change = hash_data("path1")) 
#>  2 df_2   fetch_data("path2")  trigger(change = hash_data("path2")) 
#>  3 df_3   fetch_data("path3")  trigger(change = hash_data("path3")) 
#>  4 df_4   fetch_data("path4")  trigger(change = hash_data("path4")) 
#>  5 df_5   fetch_data("path5")  trigger(change = hash_data("path5")) 
#>  6 df_6   fetch_data("path6")  trigger(change = hash_data("path6")) 
#>  7 df_7   fetch_data("path7")  trigger(change = hash_data("path7")) 
#>  8 df_8   fetch_data("path8")  trigger(change = hash_data("path8")) 
#>  9 df_9   fetch_data("path9")  trigger(change = hash_data("path9")) 
#> 10 df_10  fetch_data("path10") trigger(change = hash_data("path10"))

由reprex 包（v0.2.1）于 2019 年 5 月 6 日创建

于 2019-05-03T11:28:12.553 回答