common/FastFacts.py

import pandas as pd

class FastFacts:
    def __init__(self):
        self.facts = {}  # Dictionary to store facts by category

    def add_fact(self, category, fact):
        """
        Add a single fact under a specific category.
        """
        if not isinstance(category, str) or not isinstance(fact, str):
            print("Both category and fact must be strings.")
            return

        # Initialize category if it doesn't exist
        if category not in self.facts:
            self.facts[category] = []

        self.facts[category].append(fact)

    def add_facts(self, category_facts):
        """
        Add multiple facts under their respective categories.
        category_facts should be a dictionary where keys are categories and values are lists of facts.
        """
        if not isinstance(category_facts, dict):
            print("Facts must be provided as a dictionary with categories as keys.")
            return

        for category, facts in category_facts.items():
            if not isinstance(category, str) or not isinstance(facts, list):
                print(f"Skipping invalid category or facts: {category}")
                continue
            
            if category not in self.facts:
                self.facts[category] = []
            
            self.facts[category].extend(f for f in facts if isinstance(f, str))

    def get_all_facts(self):
        """
        Returns all facts grouped by category.
        """
        return self.facts

    def get_facts_by_category(self, category):
        """
        Returns all facts under a specific category.
        """
        return self.facts.get(category, [])

    def get_categories(self):
        """
        Returns a list of all available categories.
        """
        return list(self.facts.keys())

    def __repr__(self):
        if not self.facts:
            return f"{self.__class__.__name__}: No facts available"
        
        return "\n".join(
            f"{category}: " + ", ".join(f"<{fact}>" for fact in facts)
            for category, facts in self.facts.items()
        )

    def to_dict(self):
        """
        Convert the FastFacts to a dictionary.
        """
        return {"facts": self.facts}

    @staticmethod
    def read_from_excel(fact_file):
        """
        Read facts from an Excel file and populate a FastFacts object.
        Args:
            fact_file (str): Path to the Excel file.
        Returns:
            FastFacts: A populated FastFacts object.
        """
        try:
            df = pd.read_excel(fact_file)

            # Ensure the expected columns exist
            if "Category" not in df.columns or "FastFacts" not in df.columns:
                print("Error: Expected columns 'Category' and 'FastFacts' not found in the file.")
                return None

            # Drop rows with missing FastFacts
            df = df.dropna(subset=["FastFacts"])

            # Group facts by category
            grouped_facts = df.groupby("Category")["FastFacts"].apply(list).to_dict()

            # Create a FastFacts object and populate it
            fast_facts_obj = FastFacts()
            fast_facts_obj.add_facts(grouped_facts)

            return fast_facts_obj

        except Exception as e:
            print(f"An error occurred while reading from the Excel file: {e}")
            return None