使用 LogicApp 忽略第一个和最后一个记录

Question

我有一个非常简单的 LogicApp，我想忽略第一个和最后一个 x 条记录，定义如下，您应该可以看到我的结果：

{
    "definition": {
        "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#",
        "actions": {
            "Convert_Each_Row_into_Array": {
                "inputs": "@split(variables('CSV Data'),'\n')",
                "runAfter": {
                    "Initialize_CSV_Data": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            },
            "Initialize_CSV_Data": {
                "inputs": {
                    "variables": [
                        {
                            "name": "CSV Data",
                            "type": "string",
                            "value": "rubbish1,rubbish2,rubbish3\nblank1,blank2,blank3\nheader1,header2,header3\ndata1,data2,data3\ndata4,data5,data6\ndata7,data8,data9"
                        }
                    ]
                },
                "runAfter": {
                    "Parse_JSON": [
                        "Succeeded"
                    ]
                },
                "type": "InitializeVariable"
            },
            "Parse_JSON": {
                "inputs": {
                    "content": "@triggerBody()",
                    "schema": {
                        "properties": {
                            "NumberOfFooterRows": {
                                "type": "integer"
                            },
                            "NumberOfHeaderRows": {
                                "type": "integer"
                            }
                        },
                        "type": "object"
                    }
                },
                "runAfter": {},
                "type": "ParseJson"
            },
            "Skip_Footer": {
                "inputs": "@take(outputs('Skip_Header'),sub(length(outputs('Skip_Header')),body('Parse_JSON')?['NumberOfFooterRows']))",
                "runAfter": {
                    "Skip_Header": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            },
            "Skip_Header": {
                "inputs": "@take(skip(outputs('Convert_Each_Row_into_Array'),body('Parse_JSON')?['NumberOfHeaderRows']),sub(length(outputs('Convert_Each_Row_into_Array')),1))",
                "runAfter": {
                    "Convert_Each_Row_into_Array": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            }
        },
        "contentVersion": "1.0.0.0",
        "outputs": {},
        "parameters": {},
        "triggers": {
            "manual": {
                "inputs": {},
                "kind": "Http",
                "type": "Request"
            }
        }
    },
    "parameters": {}
}

负载是

{
    "NumberOfHeaderRows":3,
    "NumberOfFooterRows":2
}

这工作正常，但它仅用于测试，因为真实数据以 CSV 格式存储在 SFTP 中，因此添加了获取文件内容的额外步骤，然后将其放入 Initialise CSV Data 变量中：

CSV 文件与初始 CSV 数据变量完全相同，字面意思是：

rubbish1,rubbish2,rubbish3
blank1,blank2,blank3
header1,header2,header3
data1,data2,data3
data4,data5,data6

我现在剩下的是成功删除前 3 行但未删除最后 2 行的结果。它不会给出任何错误，但如果我点击

Download (Alt/Option + click)

然后就显示

[]

Answer 1

这是因为Initialize CSV data是字符串类型，skip()只跳过我们提到的字符，这就是为什么我们需要将字符串转换为数组并跳过数组对象。此外，查看要提供的有效负载，我们发现您正在发送字符串类型。相反，您可以通过 make

发送 int

{
    "NumberOfHeaderRows":"3",
    "NumberOfFooterRows":"2"
}

到

{
    "NumberOfHeaderRows":3,
    "NumberOfFooterRows":2
}

如果使用数组

将您的 csv 数据的字符串类型转换为数组后，它就可以工作了。我添加了一个额外的步骤 Parse_JSON 只是为了检索 NumberOfHeaderRows 和 NumberOfFooterRows 这让事情变得更加清晰。这是我的逻辑应用程序的屏幕截图 -

结果：

Skip Headers

中使用的表达式

@take(skip(variables('CSV Data'),body('Parse_JSON')?['NumberOfHeaderRows']),sub(length(variables('CSV Data')),1))

Skip Footer

中使用的表达式

@take(outputs('Skip_Header'),sub(length(outputs('Skip_Header')),body('Parse_JSON')?['NumberOfFooterRows']))

下面是我的代码视图：

{
    "definition": {
        "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#",
        "actions": {
            "Initialize_CSV_Data": {
                "inputs": {
                    "variables": [
                        {
                            "name": "CSV Data",
                            "type": "array",
                            "value": [
                                "rubbish1,rubbish2,rubbish3",
                                "blank1,blank2,blank3",
                                "header1,header2,header3",
                                "data1,data2,data3",
                                "data4,data5,data6",
                                "data7,data8,data9"
                            ]
                        }
                    ]
                },
                "runAfter": {
                    "Parse_JSON": [
                        "Succeeded"
                    ]
                },
                "type": "InitializeVariable"
            },
            "Parse_JSON": {
                "inputs": {
                    "content": "@triggerBody()",
                    "schema": {
                        "properties": {
                            "NumberOfFooterRows": {
                                "type": "integer"
                            },
                            "NumberOfHeaderRows": {
                                "type": "integer"
                            }
                        },
                        "type": "object"
                    }
                },
                "runAfter": {},
                "type": "ParseJson"
            },
            "Skip_Footer": {
                "inputs": "@take(outputs('Skip_Header'),sub(length(outputs('Skip_Header')),body('Parse_JSON')?['NumberOfFooterRows']))",
                "runAfter": {
                    "Skip_Header": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            },
            "Skip_Header": {
                "inputs": "@take(skip(variables('CSV Data'),body('Parse_JSON')?['NumberOfHeaderRows']),sub(length(variables('CSV Data')),1))",
                "runAfter": {
                    "Initialize_CSV_Data": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            }
        },
        "contentVersion": "1.0.0.0",
        "outputs": {},
        "parameters": {},
        "triggers": {
            "manual": {
                "inputs": {},
                "kind": "Http",
                "type": "Request"
            }
        }
    },
    "parameters": {}
}

如果使用字符串

考虑到您只剩下字符串，那么您可以使用 split 函数将该字符串转换为数组，该函数将每一行转换为数组对象。这是逻辑应用

结果：

这是Convert Each Row into Array

中的表达式

split(variables('CSV Data'),'

')

现在您可以使用 Convert Each Row into Array 连接器输出来实现我们的要求

下面是进行上述更改后的代码视图

{
    "definition": {
        "$schema": "https://schema.management.azure.com/providers/Microsoft.Logic/schemas/2016-06-01/workflowdefinition.json#",
        "actions": {
            "Convert_Each_Row_into_Array": {
                "inputs": "@split(variables('CSV Data'),'\n')",
                "runAfter": {
                    "Initialize_CSV_Data": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            },
            "Initialize_CSV_Data": {
                "inputs": {
                    "variables": [
                        {
                            "name": "CSV Data",
                            "type": "string",
                            "value": "rubbish1,rubbish2,rubbish3\nblank1,blank2,blank3\nheader1,header2,header3\ndata1,data2,data3\ndata4,data5,data6\ndata7,data8,data9"
                        }
                    ]
                },
                "runAfter": {
                    "Parse_JSON": [
                        "Succeeded"
                    ]
                },
                "type": "InitializeVariable"
            },
            "Parse_JSON": {
                "inputs": {
                    "content": "@triggerBody()",
                    "schema": {
                        "properties": {
                            "NumberOfFooterRows": {
                                "type": "integer"
                            },
                            "NumberOfHeaderRows": {
                                "type": "integer"
                            }
                        },
                        "type": "object"
                    }
                },
                "runAfter": {},
                "type": "ParseJson"
            },
            "Skip_Footer": {
                "inputs": "@take(outputs('Skip_Header'),sub(length(outputs('Skip_Header')),body('Parse_JSON')?['NumberOfFooterRows']))",
                "runAfter": {
                    "Skip_Header": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            },
            "Skip_Header": {
                "inputs": "@take(skip(outputs('Convert_Each_Row_into_Array'),body('Parse_JSON')?['NumberOfHeaderRows']),sub(length(outputs('Convert_Each_Row_into_Array')),1))",
                "runAfter": {
                    "Convert_Each_Row_into_Array": [
                        "Succeeded"
                    ]
                },
                "type": "Compose"
            }
        },
        "contentVersion": "1.0.0.0",
        "outputs": {},
        "parameters": {},
        "triggers": {
            "manual": {
                "inputs": {},
                "kind": "Http",
                "type": "Request"
            }
        }
    },
    "parameters": {}
}

使用 LogicApp 忽略第一个和最后一个记录

Ignore first and last records using LogicApp

azure-logic-apps

如果使用数组

如果使用字符串