mapstructure is a Go library for decoding generic map values to structures and vice versa, while providing helpful error handling.
This library is most useful when decoding values from some data stream (JSON,
Gob, etc.) where you don't quite know the structure of the underlying data
until you read a part of it. You can therefore read a map[string]interface{}
and use this library to decode it into the proper underlying native Go
structure.
Standard go get
:
$ go get github.com/goinggo/mapstructure
For usage and examples see the Godoc.
The Decode
, DecodePath
and DecodeSlicePath
functions have examples associated with it there.
Go offers fantastic standard libraries for decoding formats such as JSON. The standard method is to have a struct pre-created, and populate that struct from the bytes of the encoded format. This is great, but the problem is if you have configuration or an encoding that changes slightly depending on specific fields. For example, consider this JSON:
{
"type": "person",
"name": "Mitchell"
}
Perhaps we can't populate a specific structure without first reading
the "type" field from the JSON. We could always do two passes over the
decoding of the JSON (reading the "type" first, and the rest later).
However, it is much simpler to just decode this into a map[string]interface{}
structure, read the "type" key, then use something like this library
to decode it into the proper structure.
Sometimes you have a large and complex JSON document where you only need to decode a small part.
{
"userContext": {
"conversationCredentials": {
"sessionToken": "06142010_1:75bf6a413327dd71ebe8f3f30c5a4210a9b11e93c028d6e11abfca7ff"
},
"valid": true,
"isPasswordExpired": false,
"cobrandId": 10000004,
"channelId": -1,
"locale": "en_US",
"tncVersion": 2,
"applicationId": "17CBE222A42161A3FF450E47CF4C1A00",
"cobrandConversationCredentials": {
"sessionToken": "06142010_1:b8d011fefbab8bf1753391b074ffedf9578612d676ed2b7f073b5785b"
},
"preferenceInfo": {
"currencyCode": "USD",
"timeZone": "PST",
"dateFormat": "MM/dd/yyyy",
"currencyNotationType": {
"currencyNotationType": "SYMBOL"
},
"numberFormat": {
"decimalSeparator": ".",
"groupingSeparator": ",",
"groupPattern": "###,##0.##"
}
}
},
"lastLoginTime": 1375686841,
"loginCount": 299,
"passwordRecovered": false,
"emailAddress": "johndoe@email.com",
"loginName": "sptest1",
"userId": 10483860,
"userType":
{
"userTypeId": 1,
"userTypeName": "normal_user"
}
}
It is nice to be able to define and pull the documents and fields you need without having to map the entire JSON structure.
type UserType struct {
UserTypeId int
UserTypeName string
}
type NumberFormat struct {
DecimalSeparator string `jpath:"userContext.preferenceInfo.numberFormat.decimalSeparator"`
GroupingSeparator string `jpath:"userContext.preferenceInfo.numberFormat.groupingSeparator"`
GroupPattern string `jpath:"userContext.preferenceInfo.numberFormat.groupPattern"`
}
type User struct {
Session string `jpath:"userContext.cobrandConversationCredentials.sessionToken"`
CobrandId int `jpath:"userContext.cobrandId"`
UserType UserType `jpath:"userType"`
LoginName string `jpath:"loginName"`
NumberFormat // This can also be a pointer to the struct (*NumberFormat)
}
docScript := []byte(document)
var docMap map[string]interface{}
json.Unmarshal(docScript, &docMap)
var user User
mapstructure.DecodePath(docMap, &user)
Sometimes you have a slice of documents that you need to decode into a slice of structures
[
{"name":"bill"},
{"name":"lisa"}
]
Just Unmarshal your document into a slice of maps and decode the slice
type NameDoc struct {
Name string `jpath:"name"`
}
sliceScript := []byte(document)
var sliceMap []map[string]interface{}
json.Unmarshal(sliceScript, &sliceMap)
var myslice []NameDoc
err := DecodeSlicePath(sliceMap, &myslice)
var myslice []*NameDoc
err := DecodeSlicePath(sliceMap, &myslice)
Sometimes you have a document with arrays
{
"cobrandId": 10010352,
"channelId": -1,
"locale": "en_US",
"tncVersion": 2,
"people": [
{
"name": "jack",
"age": {
"birth":10,
"year":2000,
"animals": [
{
"barks":"yes",
"tail":"yes"
},
{
"barks":"no",
"tail":"yes"
}
]
}
},
{
"name": "jill",
"age": {
"birth":11,
"year":2001
}
}
]
}
You can decode within those arrays
type Animal struct {
Barks string `jpath:"barks"`
}
type People struct {
Age int `jpath:"age.birth"` // jpath is relative to the array
Animals []Animal `jpath:"age.animals"`
}
type Items struct {
Categories []string `jpath:"categories"`
Peoples []People `jpath:"people"` // Specify the location of the array
}
docScript := []byte(document)
var docMap map[string]interface{}
json.Unmarshal(docScript, &docMap)
var items Items
DecodePath(docMap, &items)