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This is an example of the JSON file I'm working with, it has around 600 rows of the same nested JSON structure.

{
  "at": {
    "Availability": "Yes",
    "Message": "NV",
    "Delivery option": "fast",
  },
  "childNodeIds": [],
  "crawlMessageFlags": null,
  "pd": {
    "product_id": "product_id value",
    "product_name": "product_name value",
    "retailerName": "retailerName value",
    "stock_status": "InStock",
    "subClassName": "n/a"
  },
  "sellers": [],
  "zipDetails": {}
}

I want to generate a report that has the keys inside PD as the column names. Example

--------------------------------------------------------
    product_id  |   product_name     | retailerName
-----------------------------------------------------------
productid value1| product_name value1| retailerName value1
productid value2| product_name value2| retailerName value2
productid value3| product_name value3| retailerName value3
productid value4| product_name value4| retailerName value4

I can generate this table with hardcoded values but I want to do it dynamically as we have several different use cases.

I have tried several solutions from the web but none solves this without hardcoding.

Any solutions?

Kostas Minaidis
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Worker
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    What have you tried so far and where does it seem to fail? – Kostas Minaidis May 04 '22 at 10:05
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    Extract the column names from the first object with `Object.keys`, and then iterate over the array grabbing each `pd` `Object.values`. – Andy May 04 '22 at 10:09
  • The closest solution was this https://community.snowflake.com/s/article/Dynamically-extract-multi-level-JSON-object-using-lateral-flatten but i cannot make it fit my case. Through this I get PD.keys as individual rows. – Worker May 04 '22 at 10:13

1 Answers1

1

Here's one approach that might work for you. Depending on the structure of the resulting variable (output) you might want to refactor accordingly.

const list = [
  {
  "at": {
    "Availability": "Yes",
    "Message": "NV",
    "Delivery option": "fast",
  },
  "childNodeIds": [],
  "crawlMessageFlags": null,
  "pd": {
    "product_id": "product_id value1",
    "product_name": "product_name value1",
    "retailerName": "retailerName value1",
    "stock_status": "InStock 1",
    "subClassName": "n/a"
  },
  "sellers": [],
  "zipDetails": {}
},
  {
  "at": {
    "Availability": "Yes",
    "Message": "NV",
    "Delivery option": "fast",
  },
  "childNodeIds": [],
  "crawlMessageFlags": null,
  "pd": {
    "product_id": "product_id value2",
    "product_name": "product_name value2",
    "retailerName": "retailerName value2",
    "stock_status": "InStock 2",
    "subClassName": "n/a"
  },
  "sellers": [],
  "zipDetails": {}
}
]

const output = list.reduce((acc,{ pd })=>{
  acc.push([ pd.product_id, pd.product_name, pd.retailerName ])
  return acc;
}, [["product_id", "product_name", "retailerName"]]);


console.log( output );
Kostas Minaidis
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