#!/usr/bin/env python3
"""Economic impact of the recovered discard table, over OWNED instances.

Informational only: it exists to make the promotion decision explicit, never to
justify altering a value. Values come from the matrix emitted by
`cargo run -p openfut-adapter-fifa17 --example discard_matrix`, i.e. the shipped
implementation.

Usage:
    python3 scripts/fifa17-discard-impact.py --matrix /tmp/discard-matrix.csv
"""
import argparse
import collections
import csv
import sqlite3

DB = "/home/alex/openfut-sold-staging/staging-core.db"


def main():
    ap = argparse.ArgumentParser()
    ap.add_argument("--matrix", required=True)
    ap.add_argument("--db", default=DB)
    a = ap.parse_args()

    matrix = {}
    with open(a.matrix) as fh:
        for row in csv.DictReader(fh):
            matrix[row["definition"]] = row

    con = sqlite3.connect("file:%s?mode=ro" % a.db, uri=True)
    owned = con.execute("SELECT card_id, content_kind FROM owned_cards").fetchall()
    con.close()

    by_kind = collections.defaultdict(lambda: [0, 0, 0])  # n, legacy, recovered
    deltas = []
    missing = 0
    for card_id, kind in owned:
        row = matrix.get(card_id)
        if row is None:
            missing += 1
            continue
        legacy = int(row["legacy"])
        rec = int(row["recovered"]) if row["recovered"] != "-" else legacy
        b = by_kind[kind]
        b[0] += 1
        b[1] += legacy
        b[2] += rec
        deltas.append((rec - legacy, kind, card_id, legacy, rec))

    print("OWNED-INSTANCE DISCARD IMPACT  (informational)")
    print("%-12s %6s %14s %14s %8s" % ("kind", "n", "legacy", "recovered", "ratio"))
    tl = tr = tn = 0
    for kind in sorted(by_kind):
        n, legacy, rec = by_kind[kind]
        ratio = (rec / legacy) if legacy else 0
        print("%-12s %6d %14s %14s %7.2fx" % (kind, n, f"{legacy:,}", f"{rec:,}", ratio))
        tl += legacy
        tr += rec
        tn += n
    print("%-12s %6d %14s %14s %7.2fx"
          % ("TOTAL", tn, f"{tl:,}", f"{tr:,}", (tr / tl) if tl else 0))
    if missing:
        print("\ndefinitions absent from the matrix: %d" % missing)

    deltas.sort()
    print("\nlargest DECREASES")
    for d, kind, cid, legacy, rec in deltas[:5]:
        print("  %-10s %-18s %6d -> %-7d  (%+d)" % (kind, cid, legacy, rec, d))
    print("largest INCREASES")
    for d, kind, cid, legacy, rec in deltas[-5:][::-1]:
        print("  %-10s %-18s %6d -> %-7d  (%+d)" % (kind, cid, legacy, rec, d))


if __name__ == "__main__":
    main()