robin-sparkless 0.11.5

PySpark-like DataFrame API in Rust on Polars; no JVM.
Documentation 
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"""Tests for #404: select("*") and select("*", col) expand to all columns."""

from __future__ import annotations

import robin_sparkless as rs


def _spark():
    return rs.SparkSession.builder().app_name("issue_404").get_or_create()


def test_select_star() -> None:
    """df.select("*") returns all columns."""
    spark = _spark()
    df = spark.createDataFrame(
        [{"a": 1, "b": 2, "c": 3}],
        schema=[("a", "int"), ("b", "int"), ("c", "int")],
    )
    result = df.select("*").collect()
    rows = list(result)
    assert len(rows) == 1
    assert rows[0] == {"a": 1, "b": 2, "c": 3}
    # Column set
    out_df = df.select("*")
    names = out_df.columns()
    assert names == ["a", "b", "c"]


def test_select_star_plus_column() -> None:
    """df.select("*", "a") expands "*" then adds the extra column (duplicate a)."""
    spark = _spark()
    df = spark.createDataFrame(
        [{"a": 10, "b": 20}],
        schema=[("a", "int"), ("b", "int")],
    )
    result = df.select("*", "a").collect()
    rows = list(result)
    assert len(rows) == 1
    # Order: all columns then "a" again
    assert rows[0]["a"] == 10
    assert rows[0]["b"] == 20
    # Second "a" may appear as last; PySpark keeps order so we expect a, b, a
    out_df = df.select("*", "a")
    names = out_df.columns()
    assert "a" in names and "b" in names
    assert len(names) == 3  # a, b, a