import pandas as pd
import gradio as gr
from abc import ABC
from modules.module_word2Context import Word2Context
from typing import List, Tuple

class Connector(ABC):
    def parse_word(
        self, 
        word: str
    ) -> str:
        
        return word.lower().strip()

    def parse_words(
        self, 
        array_in_string: str
    ) -> List[str]:

        words = array_in_string.strip()
        if not words:
            return []

        words = [
            self.parse_word(word) 
            for word in words.split(',') if word.strip() != ''
        ]
        return words

    def process_error(
        self, 
        err: str
    ) -> str:

        if err:
            err = "<center><h3>" + err + "</h3></center>"
        return err    

class Word2ContextExplorerConnector(Connector):
    def __init__(
        self, 
        **kwargs
    ) -> None:

        vocabulary = kwargs.get('vocabulary', None)
        context = kwargs.get('context', None)

        if vocabulary is None or context is None:
            raise KeyError

        self.word2context_explorer = Word2Context(
            context,    # Context dataset HF name | path
            vocabulary  # Vocabulary class instance
        )

    def get_word_info(
        self, 
        word: str
    ) -> Tuple:
    
        word = self.parse_word(word)
        err = ""
        contexts = pd.DataFrame([], columns=[''])
        subsets_info = ""
        distribution_plot = None
        word_cloud_plot = None
        subsets_choice = gr.CheckboxGroup.update(choices=[])

        err = self.word2context_explorer.errorChecking(word)
        if err:
            return self.process_error(err), contexts, subsets_info, distribution_plot, word_cloud_plot, subsets_choice

        subsets_info, subsets_origin_info = self.word2context_explorer.getSubsetsInfo(word)

        clean_keys = [key.split(" ")[0].strip() for key in subsets_origin_info]
        subsets_choice = gr.CheckboxGroup.update(choices=clean_keys)

        distribution_plot = self.word2context_explorer.genDistributionPlot(word)
        word_cloud_plot = self.word2context_explorer.genWordCloudPlot(word)

        return self.process_error(err), contexts, subsets_info, distribution_plot, word_cloud_plot, subsets_choice

    def get_word_context(
        self,
        word: str,
        n_context: int,
        subset_choice: List[str]
    ) -> Tuple:

        word = self.parse_word(word)
        err = ""
        contexts = pd.DataFrame([], columns=[''])

        err = self.word2context_explorer.errorChecking(word)
        if err:
            return self.process_error(err), contexts

        if len(subset_choice) > 0:
            ds = self.word2context_explorer.findSplits(word, subset_choice)
        else:
            err = self.process_error("Error: Palabra no ingresada y/o conjunto/s de interés no seleccionado/s!")
            return err, contexts

        list_of_contexts = self.word2context_explorer.getContexts(word, n_context, ds)

        contexts = pd.DataFrame(list_of_contexts, columns=['#','contexto','conjunto'])
        contexts["buscar"] = contexts.contexto.apply(lambda text: self.word2context_explorer.genWebLink(text))

        return self.process_error(err), contexts