kvc supports Key Value Coding-like queries on common Erlang data structures. A common use case for kvc is to quickly access one or more deep values in decoded JSON, or some other nested data structure. It can also help with some aggregate operations. It solves similar problems that you might want to use a tool like XPath or jQuery for, but it is far simpler and strictly less powerful.
The following common Erlang data structures are supported:
list()
dict()
gb_trees()
proplist()
{struct, proplist()}
(commonly used in mochijson2){proplist()}
(EEP 18)
Only the following data types are permitted for keys, and they must be UTF-8 if any type coercion takes place:
atom()
binary()
string()
Another limitation is that it is assumed that the given data structure has a
homogeneous key type. For example, if any key is binary()
, all keys should
be binary()
.
Not used in production, but it has a test suite that passes.
Simple proplist()
example:
wibble =:= kvc:path(foo.bar.baz, [{foo, [{bar, [{baz, wibble}]}]}]).
mochijson2 {struct, proplist()}
example:
<<"wibble">> =:= kvc:path(foo.bar.baz,
{struct,
[{<<"foo">>,
{struct,
[{<<"bar">>,
{struct, [{<<"baz">>, <<"wibble">>}]}}]}}]}).
Aggregate example:
2.0 =:= kvc:path('foo.bar.baz.@avg',
{struct,
[{<<"foo">>,
{struct,
[{<<"bar">>,
{struct, [{<<"baz">>, [1, 2, 3]}]}}]}}]}).
to_proplist normalization:
[{<<"foo">>, [{<<"bar">>, <<"baz">>}]}] =:=
kvc:to_proplist({struct,
[{<<"foo">>,
{struct,
[{<<"bar">>, <<"baz">>}]}}]}).