问题

我是你的中文翻译，以下是代码部分的翻译：

我是初学者，正在尝试为一些Python脚本创建一个小型的nextflow管道。然而，我遇到了一个关于处理可选输入的问题，似乎无法找到解决方法。我也想知道处理可选输入和参数的最佳实践是什么。

```python
#!/usr/bin/env nextflow

params.out = ""
params.kml_1 = null
params.kml_2 = null
params.loc = ""
params.new_data_1 = false
params.new_data_2 = false

process getPolygons {
    input:
    tuple val(db_table), path(path_to_kml), val(new_data)
    val loc
    path path_to_outdir

    def new_data_arg = new_data ? "--new_data" : ""
    def kml_arg = (path_to_kml != null) ? "--kml $path_to_kml" : ""

    script:
    """
    python3 ${baseDir}/bin/polygon_data.py --loc $loc --db_table $db_table $kml_arg $new_data_arg --outdir $path_to_outdir
    """
}

workflow {
    outdir_ch = Channel.fromPath(params.out)
    location_ch = Channel.of(params.loc)

    tables = [
        tuple("Table1", params.kml_1 ? params.new_data_1 : null, params.new_data_1),
        tuple("Table2", params.kml_2 ? params.new_data_2: null, params.new_data_2)
    ]
    tables_ch = Channel.from(tables)

    getPolygons(tables_ch, location_ch, outdir_ch)
}

在添加可选输入之前，此代码是有效的。在这之前，tables 是一个包含表格名称的列表，没有考虑到 getPolygons 中的可选参数 path_to_kml 和 new_data。它看起来是这样的：

tables = ["Table1", "Table2"]

我一直遇到以下错误：

ERROR ~ No such variable: new_data

或

ERROR ~ No such variable: path_to_kml

具体的错误消息取决于创建变量 new_data_arg 和 kml_arg 以及在脚本中使用它们的顺序。

尝试使用元组的方法是我最新尝试解决此问题的方式，该程序在处理可选参数 new_data 和 path_to_kml 时遇到问题。我之前将它们作为 getPolygons 的独立输入。问题可能是在脚本中创建变量 new_data_arg 和 kml_arg 并在调用 polygon_data.py 时使用它们而不是直接使用 new_data 和 path_to_kml。如果是这样，我不太确定解决方法是什么，因为根据我的需求，我需要在调用 polygon_data.py 之前对 new_data 和 path_to_kml 进行一些逻辑处理。

<details>
<summary>英文:</summary>

I&#39;m new to nextflow and have been trying to create a small pipeline for some python scripts I have. However, I have encountered an issue regarding optional inputs to processes that I can&#39;t seem to figure out a workaround for. I&#39;m also curious what best practices would be for optional inputs and parameters.

#!/usr/bin/env nextflow

params.out = ""
params.kml_1 = null
params.kml_2 = null
params.loc = ""
params.new_data_1 = false
params.new_data_2 = false

process getPolygons {
input:
tuple val(db_table), path(path_to_kml), val(new_data)
val loc
path path_to_outdir

def new_data_arg = new_data ? "--new_data" : ""
def kml_arg = (path_to_kml != null) ? "--kml $path_to_kml" : ""

script:
"""
python3 ${baseDir}/bin/polygon_data.py --loc $loc --db_table $db_table $kml_arg $new_data_arg --outdir $path_to_outdir
"""

}

workflow {
outdir_ch = Channel.fromPath(params.out)
location_ch = Channel.of(params.loc)

tables = [
    tuple("Table1", params.kml_1 ? params.new_data_1 : null, params.new_data_1),
    tuple("Table2", params.kml_2 ? params.new_data_2: null, params.new_data_2)
]
tables_ch = Channel.from(tables)

getPolygons(tables_ch, location_ch, outdir_ch)

}

The code worked prior to adding in the optional inputs. This was before I had made `tables` a list of tuples in order to account for the optional parameters in getPolygons: path_to_kml and new_data, instead it was:

```tables = ["Table1", "Table2"]```

I keep running into the error

```ERROR ~ No such variable: new_data``` or ```ERROR ~ No such variable: path_to_kml```

depending on the order of creating the variables new_data_arg and kml_arg.


Trying the tuple method is the latest thing I have done to address this issue that the program has with the optional parameters new_data and path_to_kml. I previously had them as separate inputs to getPolygons. Could the issue be with creating the variables new_data_arg and kml_arg and using them in the script instead of using new_data and path_to_kml directly? If so, I'm not really sure what the work around is because for my purposes, I need some logic applied to new_data and path_to_kml before adding this information when invoking polygon_data.py.



</details>


# 答案1
**得分**: 0

我已找到一个解决方案，使用了元组。首先，“ERROR ~ No such variable”问题是因为变量`new_data_arg`和`kml_arg`不在流程的脚本组件中（初学者的错误）。

接下来，我意识到这不会遍历元组，所以我能够像这样利用每个元组，将元组作为变量`tuple_info`传递，并使用空字符串而不是null作为path_to_kml，因为它是一个路径，可能会出现null的问题。所以这是我的流程的最终可行版本：

```shell
process getPolygons {
    input:
    each tuple_info
    val loc
    path path_to_outdir

    script:
    def (db_table, path_to_kml, new_data) = tuple_info
    def new_data_arg = new_data ? "--new_data" : ""
    def kml_arg = (path_to_kml != "") ? "--kml $path_to_kml" : ""

    """
    python3 ${baseDir}/bin/polygon_data.py --loc $loc --db_table $db_table $kml_arg $new_data_arg --outdir $path_to_outdir
    """
}

我也意识到，我本可以简化tables列表，因为在处理参数的初始化时，没有必要围绕params.kml_1和params.kml_2构建额外的逻辑。

tables = [
    tuple("Table1", params.kml_1, params.new_data_1),
    tuple("Table2", params.kml_2, params.new_data_2)
]

process getPolygons {
    input:
    each tuple_info
    val loc
    path path_to_outdir

    script:
    def (db_table, path_to_kml, new_data) = tuple_info
    def new_data_arg = new_data ? "--new_data" : ""
    def kml_arg = (path_to_kml != "") ? "--kml $path_to_kml" : ""

    """
    python3 ${baseDir}/bin/polygon_data.py --loc $loc --db_table $db_table $kml_arg $new_data_arg --outdir $path_to_outdir
    """
}

tables = [
    tuple("Table1", params.kml_1, params.new_data_1),
    tuple("Table2", params.kml_2, params.new_data_2)
]