// Minimum transactions in a group to be displayed
export const MIN_GROUP_SIZE = 1;

// Common words to filter out when suggesting keywords
export const STOP_WORDS = [
  "de",
  "du",
  "la",
  "le",
  "les",
  "des",
  "un",
  "une",
  "et",
  "ou",
  "par",
  "pour",
  "avec",
  "sur",
  "dans",
  "en",
  "au",
  "aux",
  "ce",
  "cette",
  "ces",
  "mon",
  "ma",
  "mes",
  "ton",
  "ta",
  "tes",
  "son",
  "sa",
  "ses",
  "notre",
  "nos",
  "votre",
  "vos",
  "leur",
  "leurs",
];

// Function to normalize transaction descriptions for grouping
export function normalizeDescription(description: string): string {
  return description
    .toLowerCase()
    .replace(/\d{2}\/\d{2}\/\d{4}/g, "") // Remove dates
    .replace(/\d{2}-\d{2}-\d{4}/g, "") // Remove dates
    .replace(/\d+[.,]\d+/g, "") // Remove amounts
    .replace(/carte \*+\d+/gi, "CARTE") // Normalize card numbers
    .replace(/cb\*+\d+/gi, "CB") // Normalize CB numbers
    .replace(/\s+/g, " ") // Normalize spaces
    .replace(/[^\w\s]/g, " ") // Remove special chars
    .trim();
}

// Extract meaningful keywords from description
export function extractKeywords(description: string): string[] {
  const normalized = normalizeDescription(description);
  const words = normalized.split(/\s+/);

  return words
    .filter((word) => word.length > 2)
    .filter((word) => !STOP_WORDS.includes(word.toLowerCase()))
    .filter((word) => !/^\d+$/.test(word)); // Remove pure numbers
}

// Suggest a keyword based on common patterns in descriptions
export function suggestKeyword(descriptions: string[]): string {
  // Find common substrings
  const keywords = descriptions.flatMap(extractKeywords);
  const frequency: Record<string, number> = {};

  keywords.forEach((keyword) => {
    frequency[keyword] = (frequency[keyword] || 0) + 1;
  });

  // Find the most frequent keyword that appears in most descriptions
  const sorted = Object.entries(frequency)
    .filter(([_, count]) => count >= Math.ceil(descriptions.length * 0.5))
    .sort((a, b) => b[1] - a[1]);

  if (sorted.length > 0) {
    // Return the longest frequent keyword
    return sorted.reduce((best, current) =>
      current[0].length > best[0].length ? current : best
    )[0];
  }

  // Fallback: first meaningful word from first description
  const firstKeywords = extractKeywords(descriptions[0]);
  return firstKeywords[0] || descriptions[0].slice(0, 15);
}