import re
import os
import os.path as op
from glob import glob
import urllib
import subprocess
import requests
from bs4 import BeautifulSoup, NavigableString


# or https://cloud.science-miner.com/grobid/ for cloud service
GROBID_URL = "http://localhost:8070"
DIR_PATH = op.dirname(op.abspath(__file__))
PDF_FIGURES_JAR_PATH = op.join(
    DIR_PATH, "pdffigures2", "pdffigures2-assembly-0.0.12-SNAPSHOT.jar"
)


def list_pdf_paths(pdf_folder: str):
    """
    list of pdf paths in pdf folder
    """
    return glob(op.join(pdf_folder, "*", "*", "*.pdf"))


def validate_url(path: str):
    """
    Validate a given ``path`` if it is URL or not
    """
    regex = re.compile(
        r"^(?:http|ftp)s?://"  # http:// or https://
        # domain...
        r"(?:(?:[A-Z0-9](?:[A-Z0-9-]{0,61}[A-Z0-9])?\.)+(?:[A-Z]{2,6}\.?|[A-Z0-9-]{2,}\.?)|"
        r"localhost|"  # localhost...
        r"\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})"  # ...or ip
        r"(?::\d+)?"  # optional port
        r"(?:/?|[/?]\S+)$",
        re.IGNORECASE,
    )
    return re.match(regex, path) is not None


def parse_pdf(
    pdf_path: str,
    fulltext: bool = True,
    soup: bool = False,
    grobid_url: str = GROBID_URL,
):
    """
    Function to parse PDF to XML or BeautifulSoup using GROBID tool

    You can see http://grobid.readthedocs.io/en/latest/Install-Grobid/ on how to run GROBID locally
    After loading GROBID zip file, you can run GROBID by using the following
    >> ./gradlew run

    Parameters
    ==========
    pdf_path: str or bytes, path or URL to publication or article or bytes string of PDF
    fulltext: bool, option for parsing, if True, parse full text of the article
        if False, parse only header
    grobid_url: str, url to GROBID parser, default at 'http://localhost:8070'
        This could be changed to "https://cloud.science-miner.com/grobid/" for the cloud service
    soup: bool, if True, return BeautifulSoup of the article

    Output
    ======
    parsed_article: if soup is False, return parsed XML in text format,
        else return BeautifulSoup of the XML
    Example
    =======
    >> parsed_article = parse_pdf(pdf_path, fulltext=True, soup=True)
    """
    # GROBID URL
    if fulltext:
        url = "%s/api/processFulltextDocument" % grobid_url
    else:
        url = "%s/api/processHeaderDocument" % grobid_url

    if isinstance(pdf_path, str):
        if validate_url(pdf_path) and op.splitext(pdf_path)[-1].lower() != ".pdf":
            print("The input URL has to end with ``.pdf``")
            parsed_article = None
        elif validate_url(pdf_path) and op.splitext(pdf_path)[-1] == ".pdf":
            page = urllib.request.urlopen(pdf_path).read()
            parsed_article = requests.post(url, files={"input": page}).text
        elif op.exists(pdf_path):
            parsed_article = requests.post(
                url, files={"input": open(pdf_path, "rb")}
            ).text
        else:
            parsed_article = None
    elif isinstance(pdf_path, bytes):
        # assume that incoming is byte string
        parsed_article = requests.post(url, files={"input": pdf_path}).text
    else:
        parsed_article = None

    if soup and parsed_article is not None:
        parsed_article = BeautifulSoup(parsed_article, "lxml")
    return parsed_article


def parse_authors(article):
    """
    Parse authors from a given BeautifulSoup of an article
    """
    author_names = article.find("sourcedesc").findAll("persname")
    authors = []
    for author in author_names:
        firstname = author.find("forename", {"type": "first"})
        firstname = firstname.text.strip() if firstname is not None else ""
        middlename = author.find("forename", {"type": "middle"})
        middlename = middlename.text.strip() if middlename is not None else ""
        lastname = author.find("surname")
        lastname = lastname.text.strip() if lastname is not None else ""
        if middlename != "":
            authors.append(firstname + " " + middlename + " " + lastname)
        else:
            authors.append(firstname + " " + lastname)
    authors = "; ".join(authors)
    return authors


def parse_date(article):
    """
    Parse date from a given BeautifulSoup of an article
    """
    pub_date = article.find("publicationstmt")
    year = pub_date.find("date")
    year = year.attrs.get("when") if year is not None else ""
    return year


def parse_abstract(article):
    """
    Parse abstract from a given BeautifulSoup of an article
    """
    div = article.find("abstract")
    abstract = ""
    for p in list(div.children):
        if not isinstance(p, NavigableString) and len(list(p)) > 0:
            abstract += " ".join(
                [elem.text for elem in p if not isinstance(
                    elem, NavigableString)]
            )
    return abstract


def calculate_number_of_references(div):
    """
    For a given section, calculate number of references made in the section
    """
    n_publication_ref = len(
        [ref for ref in div.find_all("ref") if ref.attrs.get("type") == "bibr"]
    )
    n_figure_ref = len(
        [ref for ref in div.find_all(
            "ref") if ref.attrs.get("type") == "figure"]
    )
    return {"n_publication_ref": n_publication_ref, "n_figure_ref": n_figure_ref}


def parse_sections(article, as_list: bool = False):
    """
    Parse list of sections from a given BeautifulSoup of an article

    Parameters
    ==========
    as_list: bool, if True, output text as a list of paragraph instead
        of joining it together as one single text
    """
    article_text = article.find("text")
    divs = article_text.find_all(
        "div", attrs={"xmlns": "http://www.tei-c.org/ns/1.0"})
    sections = []
    for div in divs:
        div_list = list(div.children)
        if len(div_list) == 0:
            heading = ""
            text = ""
            all_paragraphs = []
        elif len(div_list) == 1:
            if isinstance(div_list[0], NavigableString):
                heading = str(div_list[0])
                text = ""
                all_paragraphs = []
            else:
                heading = ""
                text = div_list[0].text
                all_paragraphs = [text]
        else:
            text = []
            heading = div_list[0]
            all_paragraphs = []
            if isinstance(heading, NavigableString):
                heading = str(heading)
                p_all = list(div.children)[1:]
            else:
                heading = ""
                p_all = list(div.children)
            for p in p_all:
                if p is not None:
                    try:
                        text.append(p.text)
                        all_paragraphs.append(p.text)
                    except:
                        pass
            if not as_list:
                text = "\n".join(text)
        if heading != "" or text != "":
            ref_dict = calculate_number_of_references(div)
            sections.append(
                {
                    "heading": heading,
                    "text": text,
                    "all_paragraphs": all_paragraphs,
                    "n_publication_ref": ref_dict["n_publication_ref"],
                    "n_figure_ref": ref_dict["n_figure_ref"],
                }
            )
    return sections


def parse_references(article):
    """
    Parse list of references from a given BeautifulSoup of an article
    """
    reference_list = []
    references = article.find("text").find("div", attrs={"type": "references"})
    references = references.find_all(
        "biblstruct") if references is not None else []
    reference_list = []
    for reference in references:
        title = reference.find("title", attrs={"level": "a"})
        if title is None:
            title = reference.find("title", attrs={"level": "m"})
        title = title.text if title is not None else ""
        journal = reference.find("title", attrs={"level": "j"})
        journal = journal.text if journal is not None else ""
        if journal == "":
            journal = reference.find("publisher")
            journal = journal.text if journal is not None else ""
        year = reference.find("date")
        year = year.attrs.get("when") if year is not None else ""
        authors = []
        for author in reference.find_all("author"):
            firstname = author.find("forename", {"type": "first"})
            firstname = firstname.text.strip() if firstname is not None else ""
            middlename = author.find("forename", {"type": "middle"})
            middlename = middlename.text.strip() if middlename is not None else ""
            lastname = author.find("surname")
            lastname = lastname.text.strip() if lastname is not None else ""
            if middlename != "":
                authors.append(firstname + " " + middlename + " " + lastname)
            else:
                authors.append(firstname + " " + lastname)
        authors = "; ".join(authors)
        reference_list.append(
            {"title": title, "journal": journal, "year": year, "authors": authors}
        )
    return reference_list


def parse_figure_caption(article):
    """
    Parse list of figures/tables from a given BeautifulSoup of an article
    """
    figures_list = []
    figures = article.find_all("figure")
    for figure in figures:
        figure_type = figure.attrs.get("type") or ""
        figure_id = figure.attrs["xml:id"] or ""
        label = figure.find("label").text
        if figure_type == "table":
            caption = figure.find("figdesc").text
            data = figure.table.text
        else:
            caption = figure.text
            data = ""
        figures_list.append(
            {
                "figure_label": label,
                "figure_type": figure_type,
                "figure_id": figure_id,
                "figure_caption": caption,
                "figure_data": data,
            }
        )
    return figures_list


def convert_article_soup_to_dict(article, as_list: bool = False):
    """
    Function to convert BeautifulSoup to JSON format
    similar to the output from https://github.com/allenai/science-parse/

    Parameters
    ==========
    article: BeautifulSoup

    Output
    ======
    article_json: dict, parsed dictionary of a given article in the following format
        {
            'title': ...,
            'abstract': ...,
            'sections': [
                {'heading': ..., 'text': ...},
                {'heading': ..., 'text': ...},
                ...
            ],
            'references': [
                {'title': ..., 'journal': ..., 'year': ..., 'authors': ...},
                {'title': ..., 'journal': ..., 'year': ..., 'authors': ...},
                ...
            ],
            'figures': [
                {'figure_label': ..., 'figure_type': ..., 'figure_id': ..., 'figure_caption': ..., 'figure_data': ...},
                ...
            ]
        }
    """
    article_dict = {}
    if article is not None:
        title = article.find("title", attrs={"type": "main"})
        title = title.text.strip() if title is not None else ""
        article_dict["authors"] = parse_authors(article)
        article_dict["pub_date"] = parse_date(article)
        article_dict["title"] = title
        article_dict["abstract"] = parse_abstract(article)
        article_dict["sections"] = parse_sections(article, as_list=as_list)
        article_dict["references"] = parse_references(article)
        article_dict["figures"] = parse_figure_caption(article)

        doi = article.find("idno", attrs={"type": "DOI"})
        doi = doi.text if doi is not None else ""
        article_dict["doi"] = doi

        return article_dict
    else:
        return None


def parse_pdf_to_dict(
    pdf_path: str,
    fulltext: bool = True,
    soup: bool = True,
    as_list: bool = False,
    grobid_url: str = GROBID_URL,
):
    """
    Parse the given PDF and return dictionary of the parsed article

    Parameters
    ==========
    pdf_path: str, path to publication or article
    fulltext: bool, whether to extract fulltext or not
    soup: bool, whether to return BeautifulSoup or not
    as_list: bool, whether to return list of sections or not
    grobid_url: str, url to grobid server, default is `GROBID_URL`
        This could be changed to "https://cloud.science-miner.com/grobid/" for the cloud service

    Ouput
    =====
    article_dict: dict, dictionary of an article
    """
    parsed_article = parse_pdf(
        pdf_path, fulltext=fulltext, soup=soup, grobid_url=grobid_url
    )
    article_dict = convert_article_soup_to_dict(
        parsed_article, as_list=as_list)
    return article_dict


def parse_figures(
    pdf_folder: str,
    jar_path: str = PDF_FIGURES_JAR_PATH,
    resolution: int = 300,
    output_folder: str = "figures",
):
    """
    Parse figures from the given scientific PDF using pdffigures2

    Parameters
    ==========
    pdf_folder: str, path to a folder that contains PDF files. A folder must contains only PDF files
    jar_path: str, default path to pdffigures2-assembly-0.0.12-SNAPSHOT.jar file
    resolution: int, resolution of the output figures
    output_folder: str, path to folder that we want to save parsed data (related to figures) and figures

    Output
    ======
    folder: making a folder of output_folder/data and output_folder/figures of parsed data and figures relatively
    """
    if not op.isdir(output_folder):
        os.makedirs(output_folder)

    # create ``data`` and ``figures`` subfolder within ``output_folder``
    data_path = op.join(output_folder, "data")
    figure_path = op.join(output_folder, "figures")
    if not op.exists(data_path):
        os.makedirs(data_path)
    if not op.exists(figure_path):
        os.makedirs(figure_path)

    if op.isdir(data_path) and op.isdir(figure_path):
        args = [
            "java",
            "-jar",
            jar_path,
            pdf_folder,
            "-i",
            str(resolution),
            "-d",
            os.path.join(os.path.abspath(data_path), ""),
            "-m",
            op.join(os.path.abspath(figure_path), ""),  # end path with "/"
        ]
        _ = subprocess.run(
            args, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=20
        )
        print("Done parsing figures from PDFs!")
    else:
        print("You may have to check of ``data`` and ``figures`` in the the output folder path.")