import requests
import pandas as pd
import numpy as np

def search_apps(term, country, media='software', limit=100):
    
    base_url = 'https://itunes.apple.com/search'
    params = {
        'term': term,
        'country': country,
        'media': media,
        'limit': limit
    }
    response = requests.get(base_url, params=params)
    response = response.json()['results']
    
    # Create a pandas DataFrame
    data = pd.DataFrame(response, columns=['trackName', 'averageUserRating','userRatingCount', 
                                           'price', 'currency','primaryGenreName', 'releaseDate', 
                                           'currentVersionReleaseDate', 'description',"releaseNotes" ,"screenshotUrls",
                                           'languageCodesISO2A', 'trackId', 'sellerName', "sellerUrl", 'trackViewUrl'])
    
    data["averageUserRating"] = np.round(data["averageUserRating"], 1)
    data["market"] = country
    data["search_term"] = term
    data["releaseDate"] = data["releaseDate"].apply(lambda x: x.split("T")[0])
    data["currentVersionReleaseDate"] = data["currentVersionReleaseDate"].apply(lambda x: x.split("T")[0])
    
    data.columns = ['name', 'average_rating', 'rating_count', 'price', 'currency', 
                    'genre', 'release_date', 'latest_version_release', 'description', 'release_notes',
                    "screenshots", 'languages', 'id',  'seller', 'seller_url', 'link', 'market', 'search_term']
    
    return data


def init_search(term, countries, media='software', limit=100):
    term = term.split(", ")
    countries = countries.split(", ")

    data = pd.DataFrame()

    for country in countries:
        for t in term:
            temp = search_apps(t, country, media=media, limit=limit)
            temp['languages'] = temp['languages'].apply(lambda x: ', '.join(x))
            temp['screenshots'] = temp['screenshots'].apply(lambda x: ', '.join(x))
            data = pd.concat([data, temp], ignore_index=True)

    data = data.drop_duplicates(subset=data.columns.difference(['search_term']))
    data = data.reset_index(drop=True)

    return data

def to_csv(data):
    csv = data.to_csv(index=False)
    return csv.encode('utf-8')