[Python] Normalise across multi-dimensional array

I have large multi-dimensional array data that at its most basic looks something like this:

[
{
'a': 'a1',
'b': [
{
'ba': 'ba1',
'bb': 1,
'bc': {
'bca': 'bca1',
'bcb': 4
}
},
{
'ba': 'ba2',
'bb': 2,
'bc': {
'bca': 'bca2',
'bcb': 5
}
},
{
'ba': 'ba3',
'bb': 3,
'bc': {
'bca': 'bca3',
'bcb': 6
}
}
]
},
...
]


and what I want to do is to normalise the "bb" and "bcb" values within each object in the top-level array.

That is, I want to end up with this:

[
{
'a': 'a1',
'b': [
{
'ba': 'ba1',
'bb': 0,
'bc': {
'bca': 'bca1',
'bcb': 0
}
},
{
'ba': 'ba2',
'bb': 0.5,
'bc': {
'bca': 'bca2',
'bcb': 0.5
}
},
{
'ba': 'ba3',
'bb': 1,
'bc': {
'bca': 'bca3',
'bcb': 1
}
}
]
},
...
]


Is there a package or similar I can do this with in python?

Obviously I can do this with a complicated loop, but I am wondering if there is a more efficient way of doing this?

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