# Value Parser Plugin The "value" data format translates single values into Telegraf metrics. This is done by assigning a measurement name and setting a single field ("value") as the parsed metric. ## Configuration ```toml [[inputs.exec]] ## Commands array commands = ["cat /proc/sys/kernel/random/entropy_avail"] ## override the default metric name of "exec" name_override = "entropy_available" ## override the field name of "value" # value_field_name = "value" ## Data format to consume. ## Each data format has its own unique set of configuration options, read ## more about them here: ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md data_format = "value" data_type = "integer" # required ``` ### Metric name It is recommended to set `name_override` to a measurement name that makes sense for your metric, otherwise it will just be set to the name of the plugin. ### Datatype You **must** tell Telegraf what type of metric to collect by using the `data_type` configuration option. Available options are: - `integer`: converts the received data to an integer value. This setting will produce an error on non-integer data. - `float`: converts the received data to a floating-point value. This setting will treat integers as floating-point values and produces an error on data that cannot be converted (e.g. strings). - `string`: outputs the data as a string. - `base64`: outputs the data as a base64 encoded string. - `boolean`: converts the received data to a boolean value. This setting will produce an error on any data except for `true` and `false` strings. - `auto_integer`: converts the received data to an integer value if possible and will return the data as string otherwise. This is helpful for mixed-type data. - `auto_float`: converts the received data to a floating-point value if possible and will return the data as string otherwise. This is helpful for mixed-type data. Integer data will be treated as floating-point values. **NOTE**: The `auto` conversions might convert data to their prioritized type by accident, for example if a string data-source provides `"55"` it will be converted to integer/float. This might break outputs that require the same datatype within a field or column. It is thus recommended to use *strict* typing whenever possible.