import requests
from bs4 import BeautifulSoup
from sheets import ExcelAutomator
from seleliumdriver import WebScraper

browser = requests.session()

def save(data:str):
    with open("data.html", "w") as op:
        op.write(str(data))

def get_headers(data: str) -> dict:
    """This funciton helps to get the headers form the string to the dict

    Args:
        data (str): Pass the headers as a string (You can go to firefox click on copy and copy request or response header and it will convert it to th e)

    Returns:
        dict: Return the dict or you can say header
    """
    data = data.strip()
    data = data.split("\n")
    out = {}
    for dt in data:
        key = dt.split(":", 1)[0].strip()
        value = dt.split(":", 1)[1].strip()

        if value.lower() == "none":
            value = None
        elif value.lower() == "true":
            value = True
        elif value.lower() == "false":
            value = False

        out[key] = value
    return out

def get_links(url: str, issue: int) -> list:
    headers = """
    User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:109.0) Gecko/20100101 Firefox/115.0
    Accept: text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,*/*;q=0.8
    Accept-Language: en-US,en;q=0.5
    Accept-Encoding: gzip, deflate, br
    Alt-Used: onlinelibrary.wiley.com
    Connection: keep-alive
    Cookie: MAID=5SmfjugKsbanANmqY7QFTQ==; MACHINE_LAST_SEEN=2024-07-13T00%3A17%3A54.434-07%3A00; osano_consentmanager_uuid=a09cf48c-a316-44da-a630-b284fe618561; osano_consentmanager=wtFVO73sxrqPK1QjgWvz2PRznZ_IuLc6ARcv2t0_pFtepafXHZgrg-S478uJo9AvbIWsu3sbpgmvaCKL_zNkJQZzpvdHNzGX6NQQ6cwL_c09p-7H9gmYq7lFeOBlGJxYVbwgVIa5TZDqtpLjvla4iYf-rEyPZ0zXi8nZVVY5aCRrKBkWiIYkwIWvpeVeBLepXirD0RkYCGg-O2PWE000CQi4kWVXGTOkNMFqFOSQ-tthQqpC7pvT9AeCAodC2z6CeM6tTjz3TNmp8sTxikwwT4jzZ9HRy76gqQjb8g==; kndctr_1B6E34B85282A0AC0A490D44_AdobeOrg_identity=CiY4MDg5NTE5MTAxMTg2NDkzMzQzMTI2OTY5MjMzMTU3OTYwODc1N1ITCM6izY3mMRABGAEqBElORDEwAPAB5cnS14oy; Hm_lvt_953dddc9c7bea72022e3bd3ba7782e7b=1720765103,1720855080; AMCV_1B6E34B85282A0AC0A490D44%40AdobeOrg=MCMID|80895191011864933431269692331579608757; JSESSIONID=90BFBDCF8874DBB2B708D37ACC4172DD; __cf_bm=FgCtBcokrG75eoj6.nqj2jTcbcl.vtSPGArq4iAYwYk-1720855074-1.0.1.1-OCKWcrDvKtyaaNLld1aBjaFFwZLoLHauSzJ0NEZFn1JLYK4G4lqmaTMEE50PAzZCReTc13aRgLNyLlqu6JOllleWjBRMQr5vc3YjxJ4kdPs; kndctr_1B6E34B85282A0AC0A490D44_AdobeOrg_cluster=ind1; cf_clearance=B0r0CEgCWVP2M5CKvRhRTvIW8MyIJM2WBVS14NsHxxE-1720855079-1.0.1.1-CqrZHd19zoe3QCemtBtqxsHiVLXILmnPkb9RjSG2yHndhy.XZzt14jGpjymiEPzjA0nFP7xw1hU6xsXIz6UDSg; Hm_lpvt_953dddc9c7bea72022e3bd3ba7782e7b=1720855160; HMACCOUNT=C851A9F6625CC221; randomizeUser=0.5543043437474287
    Upgrade-Insecure-Requests: 1
    Sec-Fetch-Dest: document
    Sec-Fetch-Mode: navigate
    Sec-Fetch-Site: none
    Sec-Fetch-User: ?1
    Sec-GPC: 1
    TE: trailers
    """
    # url = f"https://onlinelibrary.wiley.com/toc/14679590/{year}/{volume}/{issue}"
    data = browser.get(url, headers=get_headers(headers))
    fullPage = BeautifulSoup(data.text, "lxml")
    issuelinks = []
    for link in fullPage.findAll("a", {"class" : "issue-item__title visitable"}):
        issuelinks.append(f'https://onlinelibrary.wiley.com{link.get("href")}')
    return issuelinks

def decode_email(encoded_str):
    key = int(encoded_str[:2], 16)
    encoded_bytes = bytes.fromhex(encoded_str[2:])
    decoded_email = ''.join(chr(byte ^ key) for byte in encoded_bytes)
    return decoded_email

def get_details(url: str):
    driver = WebScraper(browser="firefox", hidden=False)
    driver.get(url)
    data = driver.get_html()
    # save(data.text)
    full_page = BeautifulSoup(data, "lxml")
    author_detail = full_page.find("div", {"class" : "accordion-tabbed"})
    output = []
    save(full_page)
    for author in author_detail.findAll("span", {"class" : "accordion-tabbed__tab-mobile accordion__closed"}):
        author_name = author.find("p", {"class" : "author-name"}).text.strip()
        if author.find("span", {"class" : "__cf_email__"}) == None:
            continue
        email = decode_email(author.find("span", {"class" : "__cf_email__"}).get("data-cfemail"))
        address = author.find("p", {"class" : "author-name"}).findNext("p").text.strip()
        output.append(
            {
                "Name" : author_name,
                "Email" : email,
                'Address' : address
            }
        )

    return output