How to json.loads with custom separator in python?

TLDR: How can I json.loads with custom separator without replacing the separator with a comma?

I have a spark dataframe, that I want to write to CSV, and for that I need to jsonize every row in it.

So I have the following pyspark row:

Row(type='le', v=Row(occ=False, oov=False, v=True), x=966, y=340)

I want to make the row ready for CSV. If I write to CSV with normal json.dumps, I will get line with many commas, then the read csv method doesn't read the file (a lot more commas)

So, I perform json.dumps with separators=("| ", ": ")), and I get the string s:

'["le"| [false| false| true]| 966| 340]'

Now i'm able to do:

json.loads(s.replace('|',','))

And I receive the desired output:

['le', [False, False, True], 966, 340]

Now is the problematic part:

I write it to csv. When I read it, before trying to json.loads, I receive:

'[\\le\\"| [false| false| true]| 966| 340]"'

The desired output, is as before:

['le', [False, False, True], 966, 340]

But I can't reach it.

When I try to do json.loads, I get:

json.decoder.JSONDecodeError: Expecting value: line 1 column 2 (char 1)

When I try to change the '|' to ',':

s = s.replace('|',',')
s
Out: '[\\left_ear\\", [false, false, true], 966, 340]"'
json.loads(s)
json.decoder.JSONDecodeError: Expecting value: line 1 column 2 (char 1)

This post is a try to overcome a previous problem which I didn't find answer to: Convert multiple array of structs columns in pyspark sql

If I find a solution to this problem it will help me.

Bottom line this is the line I need to parse:

'[\\le\\"| [false| false| true]| 966| 340]"'

How can I do it?