Analyze

A predicate expression evaluator designed to embed logical expressions in YAML or JSON. Think of being able to apply a SQL where clause on a set of data that you supply. For example, let say we have an array of objects.

[
{
"firstName": "John", "lastName": "Smith"
},
{
"firstName": "Mary",
"lastName": "Jones"
}
]

You could then apply the following expression to see if there were someone with the first name John in your collection of objects.

@len( @select(data, "$elt.firstName == 'John'")) >0

This becomes useful when you want to build tools that perform analysis defined in a configuration file, so you might collect data on resources in kubernetes and check to see if a particular value is defined in a ConfigMap. The Go code to perform this looks like this. In this case we'd put the results of our collection in a map[string]interface{} rooted at 'resources' and 'config_maps' would refer to an array of config map resources.

ctx, err:=context.New(data)
iferr!=nil {
log.Fatal(err)
}
result, err:=expression.EvaluateContext(ctx, `@len( @select( $resources.config_maps, "$elt.firstName == 'John'" ) ) > 0`)
ifresult {
fmt.Println("found John!")
}

Expressions are composed of operators needed to compose a predicate expression and a way to declare variables that will reference a supplied data set as well as a set of builtin functions. If the existing functionality doesn't support your use case it's easy to define your own functions.

funcMyFunction(args []interface{})(interface{}, error) {
// your implementation 
}
ctx, _:=context.New(data, context.Func("@myfunc", MyFunction))
result, _:=expression.EvaluateContext(ctx, `@myfunc($foo) == "hello"`)

Examples

Programs illustrating the usage of Analyze can be found in the examples directory. Also see the unit tests in the analyzer/expression package for more examples of expressions and how they are used.