Casper 就在我之前,他使用了相同的想法(不知道我在哪里找到它,是前一段时间),但我相信我的解决方案更可靠
module DeepFetch
def deep_fetch(*keys, &fetch_default)
throw_fetch_default = fetch_default && lambda {|key, coll|
args = [key, coll]
# only provide extra block args if requested
args = args.slice(0, fetch_default.arity) if fetch_default.arity >= 0
# If we need the default, we need to stop processing the loop immediately
throw :df_value, fetch_default.call(*args)
}
catch(:df_value){
keys.inject(self){|value,key|
block = throw_fetch_default && lambda{|*args|
# sneak the current collection in as an extra block arg
args << value
throw_fetch_default.call(*args)
}
value.fetch(key, &block) if value.class.method_defined? :fetch
}
}
end
# Overload [] to work with multiple keys
def [](*keys)
case keys.size
when 1 then super
else deep_fetch(*keys){|key, coll| coll[key]}
end
end
end
response = { 'foo' => { 'bar' => [1, 2, 3] } }
response.extend(DeepFetch)
p response.deep_fetch('cars') { nil } # nil
p response.deep_fetch('cars', 0) { nil } # nil
p response.deep_fetch('foo') { nil } # {"bar"=>[1, 2, 3]}
p response.deep_fetch('foo', 'bar', 0) { nil } # 1
p response.deep_fetch('foo', 'bar', 3) { nil } # nil
p response.deep_fetch('foo', 'bar', 0, 'engine') { nil } # nil