EDIT: Whoops, forgot the config

Try to write the most efficient and concise code

Sure... for me "efficient" means "understandable" - if they wanted performance they should have said "performant" isntead :). And concise code... well, that doesn't always mean quality code, so I'll try to balance.

My approach would be to at least somewhat unify the data, then use smaller functions and deal with the super confusing data structure there.

If this was a very big project and a more generic project would actually be needed, only then would I consider making anything generic with such data. Often it's not actually necessary and just introduces a whole lot of complexity.

const payload1 = [
  {
    data: [
      [
        {
          name: "Handbag",
          url: "https://example.com/products/handbag",
          images: {
            small: "https://example.com/products/handbag/images/small.png",
            medium: "https://example.com/products/handbag/images/medium.png",
            large: "https://example.com/products/handbag/images/large.png",
          },
          color: "black",
          price: "$50.00",
        },
      ],
      [
        {
          name: "Shoes",
          url: "https://example.com/products/shoes",
          images: {
            small: "https://example.com/products/shoes/images/small.png",
            medium: "https://example.com/products/shoes/images/medium.png",
            large: "https://example.com/products/shoes/images/large.png",
          },
          color: "red",
          price: "$35.00",
        },
      ],
    ],
  },
];

const payload2 = [
  [
    {
      product_id: "000001",
      meta: {
        en_US: {
          product_name: "Handbag",
          product_urls: ["https://example.com/products/handbag"],
          product_image_small: "https://example.com/products/handbag/images/small.png",
          product_image_medium: "https://example.com/products/handbag/images/medium.png",
          product_image_large: "https://example.com/products/handbag/images/large.png",
          product_price_cents: 5000,
          product_custom_attributes: {
            product_price_string: "$50.00",
            product_color: "black",
          },
        },
      },
    },
    {
      product_id: "000002",
      meta: {
        en_US: {
          product_name: "Shoes",
          product_urls: ["https://example.com/products/shoes"],
          product_image_small: "https://example.com/products/shoes/images/small.png",
          product_image_medium: "https://example.com/products/shoes/images/medium.png",
          product_image_large: "https://example.com/products/shoes/images/large.png",
          product_price_cents: 3500,
          product_custom_attributes: {
            product_price_string: "$35.00",
            product_color: "red",
          },
        },
      },
    },
  ],
];

// main function
const parseProducts = (data, config) => {
    const saneData = config.array ? data[0] : data[0].data;
    return saneData.map(product => {
        return [
            { type: 'TEXT',  value: getText(product, config) },   // 'Handbag'
            { type: 'URL',   value: getUrl(product, config) },    // 'https://example.com/products/handbag'
            { type: 'IMAGE', value: getImage(product, config) },  // 'https://example.com/products/handbag/images/medium.png'
            { type: 'TEXT',  value: getPrice(product, config) }   // '$50.00'
        ]
    });
};

const getText = (product, config) => {
    if (Array.isArray(product)) {
        return product[0].name;
    }
    const meta = product?.meta[config.lang];
    return meta?.product_name;
}

const getUrl = (product, config) => {
    if (Array.isArray(product)) {
        return product[0].url;
    }
    const meta = product?.meta[config.lang];
    return meta?.product_urls[0];
}

const getImage = (product, config) => {
    if (Array.isArray(product)) {
        return product[0].images.medium;
    }
    const meta = product?.meta[config.lang];
    return meta?.product_image_medium;
}

const getPrice = (product, config) => {
    if (Array.isArray(product)) {
        return product[0].price;
    }
    const meta = product?.meta[config.lang];
    return meta?.product_custom_attributes.product_price_string;
}

// Test
console.log(parseProducts(payload1, { array: 0 }));
console.log(parseProducts(payload2, { array: 1, lang: "en_US" }));

That first option works fine but a nested object needs its own subquery. Here is an example on the emp/dept sample dataset. It selects from dual since the outer level is a single key that has the all rows in an array, but that can also be from a table like you're doing.

SELECT JSON_OBJECT (
         KEY 'departments' VALUE (
           SELECT JSON_ARRAYAGG(
                    JSON_OBJECT (
                      KEY 'department_name' VALUE d.dname,
                      KEY 'department_no' VALUE d.deptno,
                      KEY 'employees' VALUE (
                        SELECT JSON_ARRAYAGG (
                                 JSON_OBJECT(
                                   KEY 'employee_number' VALUE e.empno,
                                   KEY 'employee_name' VALUE e.ename
                                 )
                               )
                        FROM   emp e
                        WHERE  e.deptno = d.deptno
                      )
                    )
                  )
           FROM   dept d
         )
       ) AS departments
FROM   dual;

{
  "departments": [
    {
      "department_name": "ACCOUNTING",
      "department_no": 10,
      "employees": [
        {
          "employee_number": 7839,
          "employee_name": "KING"
        },
        {
          "employee_number": 7782,
          "employee_name": "CLARK"
        },
        {
          "employee_number": 7934,
          "employee_name": "MILLER"
        }
      ]
    },
    {
      "department_name": "RESEARCH",
      "department_no": 20,
      "employees": [
        {
          "employee_number": 7566,
          "employee_name": "JONES"
        },
        {
          "employee_number": 7788,
          "employee_name": "SCOTT"
        },
        {
          "employee_number": 7902,
          "employee_name": "FORD"
        },
        {
          "employee_number": 7369,
          "employee_name": "SMITH"
        },
        {
          "employee_number": 7876,
          "employee_name": "ADAMS"
        }
      ]
    },
    {
      "department_name": "SALES",
      "department_no": 30,
      "employees": [
        {
          "employee_number": 7698,
          "employee_name": "BLAKE"
        },
        {
          "employee_number": 7499,
          "employee_name": "ALLEN"
        },
        {
          "employee_number": 7521,
          "employee_name": "WARD"
        },
        {
          "employee_number": 7654,
          "employee_name": "MARTIN"
        },
        {
          "employee_number": 7844,
          "employee_name": "TURNER"
        },
        {
          "employee_number": 7900,
          "employee_name": "JAMES"
        }
      ]
    },
    {
      "department_name": "OPERATIONS",
      "department_no": 40,
      "employees": null
    }
  ]
}

Send it as raw data and set the type to application/json

The first code is an example of Javascript code, which is similar, however not JSON. JSON would not have 1) comments and 2) the var keyword

You don't have any comments in your JSON, but you should remove the var and start like this:

Copyorders: {

The [{}] notation means "object in an array" and is not what you need everywhere. It is not an error, but it's too complicated for some purposes. AssociatedDrug should work well as an object:

Copy"associatedDrug": {
                "name":"asprin",
                "dose":"",
                "strength":"500 mg"
          }

Also, the empty object labs should be filled with something.

Other than that, your code is okay. You can either paste it into javascript, or use the JSON.parse() method, or any other parsing method (please don't use eval)

Update 2 answered:

Copyobj.problems[0].Diabetes[0].medications[0].medicationsClasses[0].className[0].associatedDrug[0].name

returns 'aspirin'. It is however better suited for foreaches everywhere

I found the solution:

payload = {
            "access_token": "123abc",
            "product_total": 2,
            "product_list[0][product_id]": 111,
            "product_list[1][product_id]": 222,
           }

r = requests.post(url, data=payload, verify=False)

How i solved it:

I reengineered the final post request that the python function should have by opening a local port and sending the working php-request to this port in order to see its payload.

(mac terminal)
user$ nc -l localhost 11111 # to open port
POST / HTTP/1.1
Host: localhost:11111
Accept: */*
Content-Length: 115
Content-Type: application/x-www-form-urlencoded

access_token=123abc&product_total=2&product_list%5B0%5D%5Bproduct_id%5D=111&product_list%5B1%5D%5Bproduct_id%5D=22

Just have to decode the payload:

from urllib import parse
parse.unquote("access_token=123abc&product_total=2&product_list%5B0%5D%5Bproduct_id%5D=111&product_list%5B1%5D%5Bproduct_id%5D=22")
'access_token=123abc&product_total=2&product_list[0][product_id]=111&product_list[1][product_id]=22'

Now the structure of the payload is clearly visible and just have to replicate it for the python post request.

And that is how the payload looked for my initial python post request:

'access_token=123abc&product_total=2&product_list=product_id&product_list=product_id'

You can clearly see why it didn't work...

If someone has an explanation why the post request with a json-payload doesn't work - i am still very interested in that. Only idea i could come up with so far is that the API simply doesn't support a json-payload?