ttrpg-tools/src/components/utils/spark-table.ts

/**
 * Spark Table — markdown table where the first column header is a dice
 * formula (d6, d20, d100, etc.). Rolling a spark table means:
 *
 * 1. Roll the dice formula once for each data column (non-dice columns)
 * 2. Look up the row whose dice-column value matches each roll
 * 3. Return the rolled values keyed by column slug
 */

import Slugger from "github-slugger";
import { rollFormula } from "../md-commander/hooks";

// ---------------------------------------------------------------------------
// Types
// ---------------------------------------------------------------------------

export interface MarkdownTable {
  headers: string[];
  rows: string[][];
}

export interface SparkTableColumn {
  header: string;
  slug: string;
  value: string;
}

export interface SparkTableResult {
  /** The dice notation (e.g. "d6", "d20") */
  notation: string;
  /** The roll results keyed by column slug */
  columns: SparkTableColumn[];
  /** Source file path */
  source: string;
}

export interface SparkTableMeta {
  /** Dice notation from the first column header */
  notation: string;
  /** Concatenated slug of data columns */
  slug: string;
  /** Data column headers (excluding dice column) */
  dataHeaders: string[];
  /** Full list of rows */
  rows: string[][];
}

// ---------------------------------------------------------------------------
// Markdown table parser
// ---------------------------------------------------------------------------

/**
 * Parse all markdown tables from a markdown string.
 * Handles both leading/trailing `|` styles and bare styles.
 */
export function parseMarkdownTables(markdown: string): MarkdownTable[] {
  const tables: MarkdownTable[] = [];
  const lines = markdown.split(/\r?\n/);

  for (let i = 0; i < lines.length; i++) {
    const headerCells = splitTableRow(lines[i]);
    if (!headerCells || headerCells.length < 2) continue;

    // Peek at the next line — must be a separator row
    if (i + 1 >= lines.length) continue;
    const sepCells = splitTableRow(lines[i + 1]);
    if (!sepCells || sepCells.length < headerCells.length) continue;
    if (!sepCells.every((c) => /^:?-{3,}:?$/.test(c))) continue;

    // Valid table header + separator — collect body rows
    const rows: string[][] = [];
    let j = i + 2;
    while (j < lines.length) {
      const rowCells = splitTableRow(lines[j]);
      if (!rowCells) break;
      // Allow rows with fewer cells (unfilled trailing columns)
      rows.push(rowCells);
      j++;
    }

    // Only include tables with at least one data row
    if (rows.length > 0) {
      tables.push({ headers: headerCells, rows });
    }
    i = j - 1;
  }

  return tables;
}

/** Split a pipe-delimited table row, stripping optional leading/trailing `|` */
function splitTableRow(line: string): string[] | null {
  const trimmed = line.trim();
  if (!trimmed.includes("|")) return null;

  // Strip optional leading and trailing `|`
  let inner = trimmed;
  if (inner.startsWith("|")) inner = inner.slice(1);
  if (inner.endsWith("|")) inner = inner.slice(0, -1);

  return inner.split("|").map((c) => c.trim());
}

// ---------------------------------------------------------------------------
// Spark table detection & metadata
// ---------------------------------------------------------------------------

const DICE_HEADER_RE = /^d\d+$/i;

/** Check whether a table is a spark table (first header is a dice formula) */
export function isSparkTable(table: MarkdownTable): boolean {
  if (table.headers.length < 2) return false;
  return DICE_HEADER_RE.test(table.headers[0]);
}

/**
 * Generate the spark table slug by concatenating slugs of all data column
 * headers (excluding the dice column).
 */
export function sparkTableSlug(table: MarkdownTable): string {
  const slugger = new Slugger();
  return table.headers
    .slice(1)
    .map((h) => slugger.slug(h.toLowerCase()))
    .join("-");
}

/**
 * Find a spark table in the given markdown content matching `slug`.
 * Returns null if not found.
 */
export function findSparkTable(
  markdown: string,
  slug: string,
): SparkTableMeta | null {
  const tables = parseMarkdownTables(markdown);
  for (const table of tables) {
    if (!isSparkTable(table)) continue;
    if (sparkTableSlug(table) === slug) {
      return {
        notation: table.headers[0],
        slug,
        dataHeaders: table.headers.slice(1),
        rows: table.rows,
      };
    }
  }
  return null;
}

/**
 * Find a spark table by its combined slug (`pageName-columnSlug`).
 * Iterates every spark table in the content, constructs the combined slug,
 * and returns the first match.  Avoids the need to guess where the page
 * name ends and the column slug begins (page names may contain `-`).
 */
export function findSparkTableByCombinedSlug(
  markdown: string,
  combinedSlug: string,
  pageName: string,
): SparkTableMeta | null {
  const tables = parseMarkdownTables(markdown);
  for (const table of tables) {
    if (!isSparkTable(table)) continue;
    const colSlug = sparkTableSlug(table);
    const candidate = `${pageName}-${colSlug}`;
    if (candidate === combinedSlug) {
      return {
        notation: table.headers[0],
        slug: colSlug,
        dataHeaders: table.headers.slice(1),
        rows: table.rows,
      };
    }
  }
  return null;
}

/** Scan all spark tables in a markdown file and return their metadata */
export function scanSparkTables(
  markdown: string,
): Omit<SparkTableMeta, "rows">[] {
  const tables = parseMarkdownTables(markdown);
  return tables.filter(isSparkTable).map((table) => ({
    notation: table.headers[0],
    slug: sparkTableSlug(table),
    dataHeaders: table.headers.slice(1),
  }));
}

// ---------------------------------------------------------------------------
// Rolling
// ---------------------------------------------------------------------------

/**
 * Roll a spark table: for each data column, roll the dice formula and look
 * up the corresponding row value.
 */
export function rollSparkTable(meta: SparkTableMeta): SparkTableResult {
  const slugger = new Slugger();
  const columns: SparkTableColumn[] = [];

  for (let colIdx = 0; colIdx < meta.dataHeaders.length; colIdx++) {
    const header = meta.dataHeaders[colIdx];
    const slug = slugger.slug(header.toLowerCase());

    const roll = rollFormula(meta.notation);
    const rolledValue = roll.result.total;

    // Find the row matching the rolled value — compare as integers,
    // falling back to string comparison.
    let value = `(no row for ${rolledValue})`;
    for (const row of meta.rows) {
      const diceCell = row[0] ?? "";
      const cellNum = parseInt(diceCell.trim(), 10);
      const match =
        !isNaN(cellNum) && rolledValue === cellNum
          ? true
          : String(rolledValue) === diceCell.trim();
      if (match) {
        value = row[colIdx + 1] ?? "";
        break;
      }
    }

    columns.push({ header, slug, value });
  }

  return {
    notation: meta.notation,
    columns,
    source: "",
  };
}