import gradio as gr
from textclassifier import TextClassifier as tc
import pandas as pd
from functions import functions as f
import time

USER_LIST = ['jimmieakesson', 'BuschEbba', 'annieloof', 'JohanPehrson', 'bolund', 'martastenevi', 'SwedishPM',
             'dadgostarnooshi']

UserNameDict = dict(zip(['Jimmie Åkesson', 'Ebba Busch', 'Annie Lööf', 'Johan Pehrson', 'Per Bolund',
                         'Märta Stenevi', 'Magdalena Andersson', 'Nooshi Dadgostar'], USER_LIST))

Columns = ['username', 'nlikes', 'nreplies', 'nretweets', 'main_topic', 'sub_topic', 'sentiment', 'target', 'tweet',
           'date', 'urls', 'id', 'class_tuple', 'user_id']


def show_all_stats(ListChoices, SeeFullStats):
    dataframe = pd.read_csv("{}/data/twitterdata.csv".format(tc.ROOT_PATH))
    if SeeFullStats:
        return dataframe[ListChoices]
    else:
        return pd.DataFrame()


def fixChoicesCorrectOrder(Choices):
    ListChoices = [x for x in Columns if x in Choices]
    return ListChoices


def MatchNameToUser(Name):
    return UserNameDict[Name]


def main(From,
         To,
         Username,
         UserNameChoices,
         Nbr_Of_Tweets_To_Classify,
         ListChoices,
         SeeFullStats
         ):
    def WhoToScrape():
        if Username == "":
            return MatchNameToUser(UserNameChoices[0])
        else:
            return Username

    text_classifier = tc.TextClassifier(
        from_date=From,
        to_date=To,
        user_list=WhoToScrape(),
        num_tweets=int(Nbr_Of_Tweets_To_Classify))

    text_classifier.run_main_pipeline()
    dataframe = text_classifier.get_dataframe()
    dataframe = dataframe[
        ['username', 'nlikes', 'nreplies', 'nretweets', 'main_topic', 'sub_topic', 'sentiment', 'target', 'tweet',
         'date', 'urls', 'id', 'class_tuple', 'user_id']]

    return dataframe[fixChoicesCorrectOrder(ListChoices)], show_all_stats(fixChoicesCorrectOrder(ListChoices), SeeFullStats)


if __name__ == "__main__":
    from datetime import date

    demo = gr.Interface(
        article="</a><br>From = The date from which you want to start the analysis.</a><br> To = The date to which "
                "you want to end "
                "the analysis.</a><br> Username = The username of the user you want to analyze.</a><br> How many "
                "tweets to classify = "
                "The number of tweets you want to analyze.</a><br>",
        analytics_enabled=False,
        theme="default",
        title="Twitter data analysis",
        fn=main,
        inputs=[gr.components.Textbox(label="From", value='2022-01-01'),
                gr.components.Textbox(label="To", value='2022-01-25'),
                gr.components.Textbox(label="Username", value="BuschEbba"),
                gr.components.Checkboxgroup(
                    choices=['Jimmie Åkesson', 'Ebba Busch', 'Annie Lööf', 'Johan Pehrson', 'Per Bolund',
                             'Märta Stenevi',
                             'Magdalena Andersson', 'Nooshi Dadgostar'], label=""),
                gr.components.Textbox(label="How many Tweets to Classify", value="20"),
                gr.components.Checkboxgroup(label="Options",
                                            choices=['username', 'nlikes', 'nreplies', 'nretweets', 'main_topic',
                                                     'sub_topic', 'sentiment', 'target', 'tweet', 'date', 'urls', 'id',
                                                     'class_tuple', 'user_id'],
                                            value=['username', 'nlikes', 'nreplies', 'nretweets', 'main_topic',
                                                   'sub_topic', 'sentiment', 'target', 'tweet', 'date']
                                            ),
                gr.components.Checkbox(label="Show full statistics")
                ],
        outputs=[
            gr.components.DataFrame(label="Summary statistics of the intervall you selected", max_rows=None),
            gr.components.DataFrame(label="Summary statistics of the total database", max_rows=None, )])

    demo.launch(share=False)