[JSONstore] stores a multidimentional JSON object into a WebDNA database
numero = 307{"first": "John","last": "Doe","age": 39,"interests": [ "Reading", "Mountain Biking", "Hacking" ],"favorites": { "color": "Blue", "sport": "Soccer", "food": "Spaghetti"}, "skills": [ { "category": "JavaScript", "tests": [ { "name": "One", "score": 90 }, { "name": "Two", "score": 96 } ] }, { "category": "CouchDB", "tests": [ { "name": "One", "score": 79 }, { "name": "Two", "score": 84 } ] }, { "category": "WebDNA", "tests": [ { "name": "One", "score": 97 }, { "name": "Two", "score": 93 } ] }]}We will make WebDNA store it in a database: simple data go the usual way, like
first=Johnlast=Doeage= 39The arrays will have a field with ":array" appended to the field name so WebDNA knows it is an array and the content should not be parsed; in this example, we have two arrays, that will be store into fields interests:array and skills:array:
interests:array=["Reading","Mountain Biking","Hacking"]skills:array=[{"category":"JavaScript","tests":[{"name":"One", "score":90},{"name": "Two", "score": 96 }]},{"category":"CouchDB","tests":[{"name":"One","score":79},{"name":"Two","score":84 }]}, {"category":"WebDNA","tests":[{"name":"One","score":97},{"name":"Two","score":93}]Nested objects will be parsed and stored by appending the second level field name to the first one, separated by a colon
favorites:color=bluefavorite:sport=Soccerfavorite:food=SpaghettiFirst, prepare your database to receive the JSON Object; it will include these fields
first - last - age - interests:array - favorites:color - favorite:sport - favorite:food - skills:array
If the database does not exist, then WebDNA will automatically create it with the proper fields
Then, using the new cell [JSONstore] and the database name[JSONstore db=whatever.db]JSONobject[/JSONstore]
From version 8.2, it is possible to use a table with [JSONstore table=whatever.db]
A debug=on option is available to know exactly what and how it is stored
by replacing JSONobject by the actual object, the cell [JSONstore] will populate the database like this, automaticallyfirst=Johnlast=Doeage= 39interests:array=["Reading", "Mountain Biking", "Hacking"]favorites:color=Bluefavorites:sport=Soccerfavorites:food=Spaghettiskills:array=[{"category": "JavaScript", "tests": [{ "name": "One", "score": 90 }, { "name": "Two", "score": 96 }]}, { "category": "CouchDB", "tests": [ { "name": "One", "score": 79 }, { "name": "Two", "score": 84 }]}, { "category": "WebDNA", "tests": [ { "name": "One", "score": 97 }, { "name": "Two", "score": 93 }]}]Sorting the data at a later time to recompose the original JSON Object is straightforward
{"first": "[first]","last": "[last]","interests": [interest:array],"favorites": { "color": "[favorite:color]", "food": "[favorite:food]" "sport": "[favorite:sport]" } "skills": [skills:array]}You can then use this data to feed JQUERY. JSON standard is language-independent and its data structures, arrays and objects, are universally recognized. These structures are supported in some way by nearly all modern programming languages and are familiar to nearly all programmers. These qualities make it an ideal format for data interchange on the web. It handles different types of data: numbers, strings, boolean, arrays... The problem relies in JSON objects structure that can be complicated to handle as it can include other nested objects, arrays, arrays with objects, objects with nested arrays, objects with nested objects, object with nested arrays and objects... a number of structures that are difficult to recognize and parse and even more complicated to store.
{
"first": "John",
"last": "Doe",
"age": 39,
"interests": [ "Reading", "Mountain Biking", "Hacking" ],
"favorites": {
"color": "Blue",
"sport": "Soccer",
"food": "Spaghetti"
},
"skills": [
{
"category": "JavaScript",
"tests": [
{ "name": "One", "score": 90 },
{ "name": "Two", "score": 96 }
]
},
{
"category": "CouchDB",
"tests": [
{ "name": "One", "score": 79 },
{ "name": "Two", "score": 84 }
]
},
{
"category": "WebDNA",
"tests": [
{ "name": "One", "score": 97 },
{ "name": "Two", "score": 93 }
]
}
]
}
first=John
last=Doe
age= 39
interests:array=["Reading","Mountain Biking","Hacking"]
skills:array=[{"category":"JavaScript","tests":[{"name":"One", "score":90},{"name": "Two", "score": 96 }]},{"category":"CouchDB","tests":[{"name":"One","score":79},{"name":"Two","score":84 }]}, {"category":"WebDNA","tests":[{"name":"One","score":97},{"name":"Two","score":93}]
favorites:color=blue
favorite:sport=Soccer
favorite:food=Spaghetti
first - last - age - interests:array - favorites:color - favorite:sport - favorite:food - skills:array
If the database does not exist, then WebDNA will automatically create it with the proper fields
[JSONstore db=whatever.db]
JSONobject
[/JSONstore]
From version 8.2, it is possible to use a table with [JSONstore table=whatever.db]
A debug=on option is available to know exactly what and how it is stored
first=John
last=Doe
age= 39
interests:array=["Reading", "Mountain Biking", "Hacking"]
favorites:color=Blue
favorites:sport=Soccer
favorites:food=Spaghetti
skills:array=[{"category": "JavaScript", "tests": [{ "name": "One", "score": 90 }, { "name": "Two", "score": 96 }]}, { "category": "CouchDB", "tests": [ { "name": "One", "score": 79 }, { "name": "Two", "score": 84 }]}, { "category": "WebDNA", "tests": [ { "name": "One", "score": 97 }, { "name": "Two", "score": 93 }]}]
{
"first": "[first]",
"last": "[last]",
"interests": [interest:array],
"favorites": {
"color": "[favorite:color]",
"food": "[favorite:food]"
"sport": "[favorite:sport]"
}
"skills": [skills:array]
}
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