nested xml/json to table

Hello,

in python pandas there is for example a json_normalize function,
i didn't find something similar or better in postgresql?

what would be the general idea: "easily" convert an hierarchical
structure like json or xml to a table; for example creating columns by
appending the key-names when going doing down the three, using null for
empty values, adding more columns as needed by the given structure.
(1-way operation)

a few conceptual gists:
jsonX=
{
    "glossary": {
        "title": "example glossary",
        "GlossDiv": {
            "title": "S",
            "GlossList": {
                "GlossEntry": {
                                "ID": "SGML",
                    "SortAs": "SGML",
                    "GlossTerm": "Sta.."; 
                    "Acronym": "SGML",
                    "Abbrev": "ISO 8879:1986",
                    "GlossDef": {
                                    "para": "A meta-m..",
                        "GlossSeeAlso": 
                            ["GML", "XML"]
                                },
                    "GlossSee": "markup"
                }
            }
        }
    }
}

select *
from json_to_table('jsonX');
-- generated columns with no data/only nulls could be removed..
-- arrays could be unnested in the process as well

glossary | glossary.title   | glossary.title.GlossDiv.title | .. 
-------------------------------------------------------------
null     | example glossary | S                        |
..

the last column: glossary.title.GlossDiv.GlossList.GlossEntry.GlossSee
with value "markup"

---

what if there are different structures that need to be combined?
(they could be added in the same manner as before)

jsonY=
{
s1:[{
    "f1": "a",
    "f2": "b",
    "f3": { "f3.1": "c",
        "f3.2": "d"}
   },
   { 
    "f1": "e",
    "f4": "g"
   }
   ]
}
           
select *
from json_to_table('jsonY');
-- generated columns with no data/only nulls could be removed..
-- separator sign is untrusted

s1  | s1.f1 | s1.f2 | s1.f3 | s1.f3.f3.1 | s1.f3.f3.2 | s1.f4
-------------------------------------------------------------
null| a     | b     | null  | c          | d          | null
null| e     | null  | null  | null       | null       | g


any ideas or suggestions (apart from plpython)? 
Wim