Here's a pure python impl that can be used today! We still need the rust one for SQL things 🙂

import daft

def summarize(df: daft.DataFrame):
    cols = []  # column             :: utf8
    typs = []  # type               :: utf8
    mins = []  # min                :: utf8
    maxs = []  # max                :: utf8
    cnts = []  # count              :: int64
    nuls = []  # nulls              :: int64
    unqs = []  # approx_distinct    :: int64
    for field in df.schema():
        col = daft.col(field.name)
        cols.append(daft.lit(field.name))
        typs.append(daft.lit(str(field.dtype)))
        mins.append(col.min().cast(daft.DataType.string()))
        maxs.append(col.max().cast(daft.DataType.string()))
        cnts.append(col.count("valid"))
        nuls.append(col.count("null"))
        unqs.append(col.approx_count_distinct())
    df = df.agg(
        [
            daft.list_(*cols).alias("column"),
            daft.list_(*typs).alias("type"),
            daft.list_(*mins).alias("min"),
            daft.list_(*maxs).alias("max"),
            daft.list_(*cnts).alias("count"),
            daft.list_(*nuls).alias("count_nulls"),
            daft.list_(*unqs).alias("approx_count_distinct"),
        ]
    )
    return df.explode(*df.columns)