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增加基础数组映射处理

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This commit is contained in:
白茶清欢 2022-01-25 14:29:42 +08:00
parent a10c8cb9b5
commit 5233c30f60
2 changed files with 61 additions and 18 deletions
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70
json_tool/gabs.go
View File

@ -35,7 +35,7 @@ type FilterDataRule struct {
// Author : go_developer@163.com<白茶清欢>
//
// Date : 2022/1/22 9:50 PM
func NewDataFilter(source string, filterRule []FilterDataRule) *DataFilter {
func NewDataFilter(source string, filterRule []*FilterDataRule) *DataFilter {
return &DataFilter{
source: source,
filterRule: filterRule,
@ -48,8 +48,9 @@ func NewDataFilter(source string, filterRule []FilterDataRule) *DataFilter {
//
// Date : 2022/1/22 9:20 PM
type DataFilter struct {
source string
filterRule []FilterDataRule
source string
filterRule []*FilterDataRule
itemKeyToSlice bool
}
// Filter 数据过滤
@ -62,6 +63,8 @@ func (df *DataFilter) Filter() (string, error) {
jsonObject *gabs.Container
err error
)
// 格式化映射规则
df.formatRule()
// 记录 obj => slice 的数据类型
obg2slice := make(map[string]string)
// 创建数据的根结点
@ -70,19 +73,15 @@ func (df *DataFilter) Filter() (string, error) {
if df.pathIsArrayValue(item.SourceKey) {
// 数组, 特殊处理
// 0. 判断目标路径是否为数组
if !df.pathIsArrayValue(item.MapKey) {
// 目标路径不是数组, 转换为支持list, 后续逻辑会自动提取为list数组
item.MapKey = item.MapKey + ".[]"
} else {
// 1. 判断数据源数组深度与目标数组深度是否一致
sourcePathArr := strings.Split(item.SourceKey, ".[].")
mapPathArr := strings.Split(item.MapKey, ".[].")
if len(sourcePathArr) != len(mapPathArr) {
return "", errors.New("slice转化原始数据深度与目标数据深度不一致")
}
continue
// 1. 判断数据源数组深度与目标数组深度是否一致
sourcePathArr := strings.Split(item.SourceKey, ".[].")
mapPathArr := strings.Split(item.MapKey, ".[].")
if len(sourcePathArr) != len(mapPathArr) {
return "", errors.New("slice转化原始数据深度与目标数据深度不一致")
}
continue
}
// 数据源路径不识数组, 多个key写入到同一个map key, 并且map key 不是以[]结尾, 自动格式化
// 目标位置, 是一个数组
if df.pathIsArrayValue(item.MapKey) {
realMapKey := strings.ReplaceAll(item.MapKey, ".[]", "")
@ -120,6 +119,15 @@ func (df *DataFilter) Filter() (string, error) {
return jsonObject.String(), nil
}
// UserItemToSlice 支持多个独立的字段合并到slice中
//
// Author : go_developer@163.com<白茶清欢>
//
// Date : 3:27 PM 2022/1/24
func (df *DataFilter) UserItemToSlice() {
df.itemKeyToSlice = true
}
// getValueType 获取数据类型
//
// Author : go_developer@163.com<白茶清欢>
@ -144,3 +152,37 @@ func (df *DataFilter) getValueType(valueResult gjson.Result) string {
func (df *DataFilter) pathIsArrayValue(path string) bool {
return strings.Contains(path, "[]")
}
// formatRule 格式化映射规则
//
// Author : go_developer@163.com<白茶清欢>
//
// Date : 2:43 PM 2022/1/24
func (df *DataFilter) formatRule() {
mapKeyCnt := make(map[string]int)
for _, item := range df.filterRule {
// source 为数组, map 不是
if df.pathIsArrayValue(item.SourceKey) {
if !df.pathIsArrayValue(item.MapKey) {
item.MapKey = item.MapKey + ".[]"
} else {
// source 是数组, map也是数组, 检测数组层级匹配
}
} else {
if df.pathIsArrayValue(item.MapKey) {
continue
}
// source 不是数组, map 也不是
if !df.itemKeyToSlice {
continue
}
mapKeyCnt[item.MapKey]++
}
}
// 多个source指向一个map,自动转化为list
for _, item := range df.filterRule {
if mapKeyCnt[item.MapKey] > 1 {
item.MapKey = item.MapKey + ".[]"
}
}
}

9
json_tool/json_test.go
View File

@ -191,7 +191,7 @@ func TestDataFilter(t *testing.T) {
{"name": "bob", "age": 28, "number": 2, "list": []int{1, 2, 3}},
},
}
rule := []FilterDataRule{
rule := []*FilterDataRule{
{SourceKey: "name", MapKey: "user_name", DefaultValue: "用户姓名默认值"},
{SourceKey: "name", MapKey: "username", DefaultValue: "用户姓名默认值"},
{SourceKey: "name", MapKey: "user.name", DefaultValue: "用户姓名默认值"},
@ -230,12 +230,13 @@ func TestDataFilterForObiToSlice(t *testing.T) {
{"name": "bob", "age": 28, "number": 2, "list": []int{1, 2, 3}},
},
}
rule := []FilterDataRule{
rule := []*FilterDataRule{
// {SourceKey: "name", MapKey: "slice.[]", DefaultValue: "用户姓名默认值"},
{SourceKey: "age", MapKey: "slice.[]", DefaultValue: "用户姓名默认值"},
{SourceKey: "height", MapKey: "slice.[]", DefaultValue: "用户姓名默认值"},
{SourceKey: "age", MapKey: "slice", DefaultValue: "用户姓名默认值"},
{SourceKey: "height", MapKey: "slice", DefaultValue: "用户姓名默认值"},
}
byteData, _ := json.Marshal(source)
filter := NewDataFilter(string(byteData), rule)
filter.UserItemToSlice()
fmt.Println(filter.Filter())
}