from corpusparser import Sentence
from pathlib import Path
import re
from lxml import etree

# Read input file(.xml, .json; kres or ssj500k).  
# Create an iterator that outputs resulting sentences (python dict format).  
class Parser():

    def __init__(self, corpus, infiles):

        if corpus == "kres":
            self.kres_folder = Path(infiles[0])
            self.kres_srl_folder = Path(infiles[1])
        elif corpus == "ssj":
            self.ssj_file = Path(infiles[0])
        else:
            raise ValueError("Argument corpus should be 'ssj' or 'kres'.")

        self.corpus = corpus
        self.W_TAGS = ['w']
        self.C_TAGS = ['c']
        self.S_TAGS = ['S', 'pc']

    def parse_jos_links(self, sent_el):
        if self.corpus == "kres":
            return self.parse_jos_links_kres(sent_el)
        else:
            return self.parse_jos_links_ssj(sent_el)

    def parse_ssj_target_arg(self, text):
        # from: 0, to: 6
        # <link ana="syn:modra" target="#ssj1.1.3 #ssj1.1.3.t6"/>
        # from: 6, to: 7
        # <link ana="syn:dol" target="#ssj1.1.3.t6 #ssj1.1.3.t7"/>
        lst = [x.split(".")[-1] for x in text.split(" ")]
        return [int(x[1:] if x[0] == "t" else 0) for x in lst]

    def parse_jos_links_kres(self, sent_el):
        lgrps = sent_el.findall(".//links")
        if len(lgrps) < 1:
            raise IOError("Can't find links.")
        res_links = []
        for link in lgrps[0]:
            res_links += [{
                "from": int(link.get("from").split(".")[-1]),
                "afun": link.get("afun"),
                "to": int(link.get("dep").split(".")[-1]),
            }]
        return res_links

    def parse_jos_links_ssj(self, sent_el):
        lgrps = sent_el.findall(".//linkGrp")
        if len(lgrps) < 1:
            # print(etree.tostring(sent_el))
            raise IOError("Can't find links.")
        res_links = []
        for link in lgrps[0]:
            print(link)
            tar = self.parse_ssj_target_arg(link.get("target"))
            res_links += [{
                "from": tar[0],
                "afun": link.get("ana").split(":")[1],
                "to": [1],
            }]
        return res_links

    def parse(self):
        if self.corpus == "kres":
            print("parse kres: TODO")
        else:
            self.parse_xml_file(self.ssj_file)

    def parse_xml_file(self, filepath):
        res_dict = {}
        with filepath.open("rb") as fp:
            # remove namespaces
            bstr = fp.read()

            utf8str = bstr.decode("utf-8")
            utf8str = re.sub('\\sxmlns="[^"]+"', '', utf8str, count=1)
            utf8str = re.sub(' xml:', ' ', utf8str)

            root = etree.XML(utf8str.encode("utf-8"))

            divs = []  # in ssj, there are divs, in Kres, there are separate files
            if self.corpus == "kres":
                divs = [root]
            else:
                divs = root.findall(".//div")

            # parse divs
            for div in divs:
                f_id = div.get("id")

                # parse paragraphs
                for p in div.findall(".//p"):
                    p_id = p.get("id").split(".")[-1]

                    # parse sentences
                    for s in p.findall(".//s"):
                        s_id = s.get("id").split(".")[-1]
                        sentence_text = ""
                        sentence_tokens = []

                        # parse tokens
                        for el in s.iter():
                            if el.tag in self.W_TAGS:
                                el_id = el.get("id").split(".")[-1]
                                if el_id[0] == 't':
                                    el_id = el_id[1:]  # ssj W_TAG ids start with t
                                sentence_text += el.text
                                sentence_tokens += [{
                                    "word": True,
                                    "tid": int(el_id),
                                    "text": el.text,
                                    "lemma": el.get("lemma"),
                                    "msd": (el.get("msd") if self.corpus == "kres"
                                        else el.get("ana").split(":")[-1]),
                                }]
                            elif el.tag in self.C_TAGS:
                                # only Kres' C_TAGS have ids
                                el_id = el.get("id") or "none"
                                el_id = el_id.split(".")[-1]
                                sentence_text += el.text
                                sentence_tokens += [{
                                    "word": False,
                                    "tid": el_id,
                                    "text": el.text,
                                }]
                            elif el.tag in self.S_TAGS:
                                # Kres' <S /> doesn't contain .text
                                sentence_text += " "
                            else:
                                # pass links and linkGroups
                                pass
                        sentence_id = "{}.{}.{}".format(f_id, p_id, s_id)

                        # make a generator instead of holding the whole corpus in memory
                        if sentence_id in res_dict:
                            raise KeyError("duplicated id: {}".format(sentence_id))
                        res_dict[sentence_id] = {
                            "sid": sentence_id,
                            "text": sentence_text,
                            "tokens": sentence_tokens,
                            "jos_links": self.parse_jos_links(s)
                        }

                        print(res_dict[sentence_id])
                        break
        return res_dict