"""
make_previews.py — Render before/after PNG previews of the first rows.

Reads messy_orders.csv (before) and clean.csv (after), and renders the first
N rows of each as a PNG table using Pillow (monospace font, header row
highlighted). Pure stdlib + Pillow, no matplotlib needed.

Usage:
    python make_previews.py [messy.csv] [clean.csv] [n_rows]
Writes:
    before_messy.png
    after_clean.png
"""

from __future__ import annotations

import sys
from pathlib import Path

from PIL import Image, ImageDraw, ImageFont

N_ROWS_DEFAULT = 14
COL_PAD = 14
ROW_H = 30
HEADER_BG = (38, 50, 56)
HEADER_FG = (255, 255, 255)
ROW_BG_A = (255, 255, 255)
ROW_BG_B = (245, 247, 249)
GRID = (200, 208, 214)
TEXT = (33, 37, 41)
TITLE_BG = (27, 33, 37)


def load_font(size: int) -> ImageFont.FreeTypeFont:
    candidates = [
        "C:/Windows/Fonts/consola.ttf",
        "C:/Windows/Fonts/DejaVuSansMono.ttf",
        "/usr/share/fonts/truetype/dejavu/DejaVuSansMono.ttf",
        "C:/Windows/Fonts/lucidaconsole.ttf",
    ]
    for path in candidates:
        if Path(path).exists():
            return ImageFont.truetype(path, size)
    return ImageFont.load_default()


def truncate(s: str, width: int, font) -> str:
    if font.getlength(s) <= width:
        return s
    while s and font.getlength(s + "…") > width:
        s = s[:-1]
    return s + "…"


def render(path: Path, title: str, rows: list[list[str]],
           font: ImageFont.FreeTypeFont) -> None:
    ncols = max(len(r) for r in rows) if rows else 1
    # column widths from content (capped)
    caps = [260, 220, 260, 150, 130, 90, 120, 120, 150, 120]
    widths = []
    for c in range(ncols):
        cells = [r[c] if c < len(r) else "" for r in rows]
        natural = max((font.getlength(s) for s in cells), default=60) + 2 * COL_PAD
        cap = caps[c] if c < len(caps) else 200
        widths.append(int(min(max(natural, 70), cap)))
    total_w = sum(widths) + 2
    title_h = 56
    total_h = title_h + len(rows) * ROW_H + 2
    img = Image.new("RGB", (total_w, total_h), ROW_BG_A)
    d = ImageDraw.Draw(img)

    # title bar
    d.rectangle([0, 0, total_w, title_h], fill=TITLE_BG)
    d.text((16, 16), title, font=font, fill=(255, 255, 255))

    # header row
    y = title_h
    d.rectangle([0, y, total_w, y + ROW_H], fill=HEADER_BG)
    x = 1
    for c, w in enumerate(widths):
        label = rows[0][c] if c < len(rows[0]) else ""
        d.text((x + COL_PAD, y + 6), truncate(label, w - 2 * COL_PAD, font),
               font=font, fill=HEADER_FG)
        x += w
    y += ROW_H

    # data rows
    for i, row in enumerate(rows[1:]):
        bg = ROW_BG_A if i % 2 == 0 else ROW_BG_B
        d.rectangle([0, y, total_w, y + ROW_H], fill=bg)
        x = 1
        for c, w in enumerate(widths):
            val = row[c] if c < len(row) else ""
            d.text((x + COL_PAD, y + 6), truncate(val, w - 2 * COL_PAD, font),
                   font=font, fill=TEXT)
            x += w
        y += ROW_H

    # grid lines
    x = 1
    for w in widths:
        d.line([x + w - 1, title_h, x + w - 1, total_h], fill=GRID, width=1)
        x += w
    for ry in range(title_h, total_h, ROW_H):
        d.line([0, ry, total_w, ry], fill=GRID, width=1)

    img.save(path)
    print(f"wrote {path} ({total_w}x{total_h})")


def read_rows(path: Path, n: int) -> list[list[str]]:
    import csv
    with path.open(newline="", encoding="utf-8") as fh:
        r = csv.reader(fh)
        header = next(r)
        rows = [header]
        for i, row in enumerate(r):
            if i >= n - 1:
                break
            rows.append(row)
    return rows


def main() -> None:
    args = sys.argv[1:]
    messy = Path(args[0]) if len(args) > 0 else Path("messy_orders.csv")
    clean = Path(args[1]) if len(args) > 1 else Path("clean.csv")
    n = int(args[2]) if len(args) > 2 else N_ROWS_DEFAULT
    font = load_font(15)
    render(Path("before_messy.png"),
           "BEFORE  —  messy_orders.csv  (raw legacy export)",
           read_rows(messy, n), font)
    render(Path("after_clean.png"),
           "AFTER   —  clean.csv  (typed, deduplicated, ISO dates)",
           read_rows(clean, n), font)


if __name__ == "__main__":
    main()