robin-sparkless 4.4.0

PySpark-like DataFrame API in Rust on Polars; no JVM.
Documentation
{
  "name": "complex_string_operations",
  "pyspark_version": "3.5",
  "input": {
    "schema": [
      {
        "name": "id",
        "type": "string"
      },
      {
        "name": "name",
        "type": "string"
      },
      {
        "name": "age",
        "type": "string"
      },
      {
        "name": "salary",
        "type": "string"
      },
      {
        "name": "department",
        "type": "string"
      },
      {
        "name": "hire_date",
        "type": "string"
      }
    ],
    "rows": [
      [
        1,
        "Alice",
        25,
        50000.0,
        "IT",
        "2020-01-15"
      ],
      [
        2,
        "Bob",
        30,
        60000.0,
        "HR",
        "2019-03-10"
      ],
      [
        3,
        "Charlie",
        35,
        70000.0,
        "IT",
        "2021-07-22"
      ],
      [
        4,
        "David",
        40,
        80000.0,
        "Finance",
        "2018-11-05"
      ],
      [
        5,
        "Eve",
        28,
        55000.0,
        "IT",
        "2022-02-14"
      ]
    ]
  },
  "operations": [],
  "expected": {
    "schema": [
      {
        "name": "id",
        "type": "string"
      },
      {
        "name": "name",
        "type": "string"
      },
      {
        "name": "age",
        "type": "string"
      },
      {
        "name": "salary",
        "type": "string"
      },
      {
        "name": "department",
        "type": "string"
      },
      {
        "name": "hire_date",
        "type": "string"
      }
    ],
    "rows": [
      [
        "1",
        "Alice",
        "25",
        "50000.0",
        "IT",
        "2020-01-15"
      ],
      [
        "2",
        "Bob",
        "30",
        "60000.0",
        "HR",
        "2019-03-10"
      ],
      [
        "3",
        "Charlie",
        "35",
        "70000.0",
        "IT",
        "2021-07-22"
      ],
      [
        "4",
        "David",
        "40",
        "80000.0",
        "Finance",
        "2018-11-05"
      ],
      [
        "5",
        "Eve",
        "28",
        "55000.0",
        "IT",
        "2022-02-14"
      ]
    ]
  }
}