Casting to a "number" (both int and float)?

[Victor Hooi]

I'm reading JSON output from an input file, and extracting values.

Many of the fields are meant to be numerical, however, some fields are wrapped 
in a "floatApprox" dict, which messed with my parsing.

For example:

{
    "hostname": "example.com",
    "version": "3.0.5",
    "pid": {
        "floatApprox": 18403
    }
    "network": {
        "bytesIn": 123123,
        "bytesOut": {
            "floatApprox": 213123123
        }
}

The floatApprox wrapping appears to happen sporadically in the input.

I'd like to find a way to deal with this robustly.

For example, I have the following function:

def strip_floatApprox_wrapping(field):
    # Extracts a integer value from a field. Workaround for the float_approx 
wrapping.
    try:
        return int(field)
    except TypeError:
        return int(field['floatApprox'])

which I can then call on each field I want to extract.

However, this relies on casting to int, which will only work for ints - for 
some fields, they may actually be floats, and I'd like to preserve that if 
possible.

(I know there's a isnumber() field - but you can only call that on a string - 
so if I do hit a floatApprox field, it will trigger a AttributeError exception, 
which seems a bit clunky to handle).

def strip_floatApprox_wrapping(field):
    # Extracts a integer value from a field. Workaround for the float_approx 
wrapping.
    try:
        if field.isnumeric():
            return field
    except AttributeError:
        return field['floatApprox']

Is there a way to re-write strip_floatApprox_wrapping to handle both 
ints/floats, and preserve the original format?

Or is there a more elegant way to deal with the arbitrary nesting with 
floatApprox?
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