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Explaining Terms
In the json, every dict will add one depth(peeling). We count depth from 0.
For example,
dummy_dict = {"a": "b", "c":{"aa": "bb", "cc": "d"}},
"a" is at depth 0, "aa" is at depth 1.
Because in normal method, if we want to get "b" or "bb", we should write dummy_dict["a"] or dummy_dict["c"]["aa"].
We have to specify 1 or 2 keys, so the depth is 0 or 1.
Sub_df are those dfs with table name containing the table name of the specifics. For example, "temp__attachments__data", "temp__attachments__data__media" and so on, are sub_dfs of "temp__attachments".
The sub_df can be viewd as one column but recording mutilple value of one df.
Take "dummy_dict" as example, this repo will turn it into,
temp
id_0| a |
----+---+
0 | b |
----+---+
temp_c(table name)
id_0|id_c_1| aa | cc |
----+------+----+----+
0 | 0 | bb | d |
----+------+----+----+
but it can be viewed as
temp
id_0| a | c |
----+---+------------------------+
0 | b |{"aa": "bb", "cc": "d"} |
----+---+------------------------+
The "temp_c" is like something growing from "temp", so I call it sub_df.
Top_df refers to the base df when we want to merge sub_df.