import json
import glob
import re
import os
from io import StringIO

import numpy as np
import click
import pandas as pd
import requests

from ocrd_models.ocrd_page import parse
from ocrd_utils import bbox_from_points

from .ned import ned
from .ner import ner
from .tsv import read_tsv, write_tsv, extract_doc_links
from .ocr import get_conf_color


@click.command()
@click.argument('tsv-file', type=click.Path(exists=True), required=True, nargs=1)
@click.argument('url-file', type=click.Path(exists=False), required=True, nargs=1)
def extract_document_links(tsv_file, url_file):

    parts = extract_doc_links(tsv_file)

    urls = [part['url'] for part in parts]

    urls = pd.DataFrame(urls, columns=['url'])

    urls.to_csv(url_file, sep="\t", quoting=3, index=False)


@click.command()
@click.argument('tsv-file', type=click.Path(exists=True), required=True, nargs=1)
@click.argument('annotated-tsv-file', type=click.Path(exists=False), required=True, nargs=1)
def annotate_tsv(tsv_file, annotated_tsv_file):

    parts = extract_doc_links(tsv_file)

    annotated_parts = []

    for part in parts:

        part_data = StringIO(part['header'] + part['text'])

        df = pd.read_csv(part_data, sep="\t", comment='#', quoting=3)

        df['url_id'] = len(annotated_parts)

        annotated_parts.append(df)

    df = pd.concat(annotated_parts)

    df.to_csv(annotated_tsv_file, sep="\t", quoting=3, index=False)


@click.command()
@click.argument('page-xml-file', type=click.Path(exists=True), required=True, nargs=1)
@click.argument('tsv-out-file', type=click.Path(), required=True, nargs=1)
@click.option('--purpose', type=click.Choice(['NERD', 'OCR'], case_sensitive=False), default="NERD",
              help="Purpose of output tsv file. "
                   "\n\nNERD: NER/NED application/ground-truth creation. "
                   "\n\nOCR: OCR application/ground-truth creation. "
                   "\n\ndefault: NERD.")
@click.option('--image-url', type=str, default='http://empty')
@click.option('--ner-rest-endpoint', type=str, default=None,
              help="REST endpoint of sbb_ner service. See https://github.com/qurator-spk/sbb_ner for details. "
                   "Only applicable in case of NERD.")
@click.option('--ned-rest-endpoint', type=str, default=None,
              help="REST endpoint of sbb_ned service. See https://github.com/qurator-spk/sbb_ned for details. "
                   "Only applicable in case of NERD.")
@click.option('--noproxy', type=bool, is_flag=True, help='disable proxy. default: enabled.')
@click.option('--scale-factor', type=float, default=0.5685, help='default: 0.5685')
@click.option('--ned-threshold', type=float, default=None)
@click.option('--min-confidence', type=float, default=None)
@click.option('--max-confidence', type=float, default=None)
def page2tsv(page_xml_file, tsv_out_file, purpose, image_url, ner_rest_endpoint, ned_rest_endpoint, noproxy, scale_factor,
             ned_threshold, min_confidence, max_confidence):
    if purpose == "NERD":
        out_columns = ['No.', 'TOKEN', 'NE-TAG', 'NE-EMB', 'ID', 'url_id', 'left', 'right', 'top', 'bottom', 'conf']
    elif purpose == "OCR":
        out_columns = ['TEXT', 'url_id', 'left', 'right', 'top', 'bottom', 'conf', 'line_id']
        if min_confidence is not None and max_confidence is not None:
            out_columns += ['ocrconf']
    else:
        raise RuntimeError("Unknown purpose.")

    if noproxy:
        os.environ['no_proxy'] = '*'

    urls = []
    if os.path.exists(tsv_out_file):
        parts = extract_doc_links(tsv_out_file)
        urls = [part['url'] for part in parts]
    else:
        pd.DataFrame([], columns=out_columns).to_csv(tsv_out_file, sep="\t", quoting=3, index=False)

    pcgts = parse(page_xml_file)
    tsv = []
    line_info = []

    for region_idx, region in enumerate(pcgts.get_Page().get_AllRegions(classes=['Text'], order='reading-order')):
        for text_line in region.get_TextLine():
            left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(text_line.get_Coords().points)]

            if min_confidence is not None and max_confidence is not None:
                conf = np.max([textequiv.conf for textequiv in text_line.get_TextEquiv()])
            else:
                conf = np.nan

            line_info.append((len(urls), left, right, top, bottom, conf, text_line.id))

            for word in text_line.get_Word():
                for text_equiv in word.get_TextEquiv():
                    # transform OCR coordinates using `scale_factor` to derive
                    # correct coordinates for the web presentation image
                    left, top, right, bottom = [int(scale_factor * x) for x in bbox_from_points(word.get_Coords().points)]

                    tsv.append((region_idx, len(line_info) - 1, left + (right - left) / 2.0,
                                text_equiv.get_Unicode(), len(urls), left, right, top, bottom, text_line.id))

    line_info = pd.DataFrame(line_info, columns=['url_id', 'left', 'right', 'top', 'bottom', 'conf', 'line_id'])

    if min_confidence is not None and max_confidence is not None:
        line_info['ocrconf'] = line_info.conf.map(lambda x: get_conf_color(x, min_confidence, max_confidence))

    tsv = pd.DataFrame(tsv, columns=['rid', 'line', 'hcenter'] + ['TEXT', 'url_id', 'left', 'right', 'top', 'bottom', 'line_id'])

    if len(tsv) == 0:
        return

    with open(tsv_out_file, 'a') as f:

        f.write('# ' + image_url + '\n')

    vlinecenter = pd.DataFrame(tsv[['line', 'top']].groupby('line', sort=False).mean().top +
                               (tsv[['line', 'bottom']].groupby('line', sort=False).mean().bottom -
                                tsv[['line', 'top']].groupby('line', sort=False).mean().top) / 2,
                               columns=['vlinecenter'])

    tsv = tsv.merge(vlinecenter, left_on='line', right_index=True)

    regions = [region.sort_values(['vlinecenter', 'hcenter']) for rid, region in tsv.groupby('rid', sort=False)]

    tsv = pd.concat(regions)

    if purpose == 'NERD':

        tsv['No.'] = 0
        tsv['NE-TAG'] = 'O'
        tsv['NE-EMB'] = 'O'
        tsv['ID'] = '-'
        tsv['conf'] = '-'

        tsv = tsv.rename(columns={'TEXT': 'TOKEN'})
    elif purpose == 'OCR':

        tsv = pd.DataFrame([(line, " ".join(part.TEXT.to_list())) for line, part in tsv.groupby('line')],
                           columns=['line', 'TEXT'])

        tsv = tsv.merge(line_info, left_on='line', right_index=True)

    tsv = tsv[out_columns].reset_index(drop=True)

    try:
        if purpose == 'NERD' and ner_rest_endpoint is not None:

            tsv, ner_result = ner(tsv, ner_rest_endpoint)

            if ned_rest_endpoint is not None:

                tsv, _ = ned(tsv, ner_result, ned_rest_endpoint, threshold=ned_threshold)

        tsv.to_csv(tsv_out_file, sep="\t", quoting=3, index=False, mode='a', header=False)
    except requests.HTTPError as e:
        print(e)


@click.command()
@click.argument('tsv-file', type=click.Path(exists=True), required=True, nargs=1)
@click.argument('tsv-out-file', type=click.Path(), required=True, nargs=1)
@click.option('--ner-rest-endpoint', type=str, default=None,
              help="REST endpoint of sbb_ner service. See https://github.com/qurator-spk/sbb_ner for details.")
@click.option('--ned-rest-endpoint', type=str, default=None,
              help="REST endpoint of sbb_ned service. See https://github.com/qurator-spk/sbb_ned for details.")
@click.option('--ned-json-file', type=str, default=None)
@click.option('--noproxy', type=bool, is_flag=True, help='disable proxy. default: proxy is enabled.')
@click.option('--ned-threshold', type=float, default=None)
def find_entities(tsv_file, tsv_out_file, ner_rest_endpoint, ned_rest_endpoint, ned_json_file, noproxy, ned_threshold):

    if noproxy:
        os.environ['no_proxy'] = '*'

    tsv, urls = read_tsv(tsv_file)

    try:
        if ner_rest_endpoint is not None:

            tsv, ner_result = ner(tsv, ner_rest_endpoint)

        elif os.path.exists(tsv_file):

            print('Using NER information that is already contained in file: {}'.format(tsv_file))

            tmp = tsv.copy()
            tmp['sen'] = (tmp['No.'] == 0).cumsum()
            tmp.loc[~tmp['NE-TAG'].isin(['O', 'B-PER', 'B-LOC', 'B-ORG', 'I-PER', 'I-LOC', 'I-ORG']), 'NE-TAG'] = 'O'

            ner_result = [[{'word': str(row.TOKEN), 'prediction': row['NE-TAG']} for _, row in sen.iterrows()]
                          for _, sen in tmp.groupby('sen')]
        else:
            raise RuntimeError("Either NER rest endpoint or NER-TAG information within tsv_file required.")

        if ned_rest_endpoint is not None:

            tsv, ned_result = ned(tsv, ner_result, ned_rest_endpoint, json_file=ned_json_file, threshold=ned_threshold)

            if ned_json_file is not None and not os.path.exists(ned_json_file):

                with open(ned_json_file, "w") as fp_json:
                    json.dump(ned_result, fp_json, indent=2, separators=(',', ': '))

        write_tsv(tsv, urls, tsv_out_file)

    except requests.HTTPError as e:
        print(e)


@click.command()
@click.option('--xls-file', type=click.Path(exists=True), default=None,
              help="Read parameters from xls-file. Expected columns:  Filename, iiif_url, scale_factor.")
@click.option('--directory', type=click.Path(exists=True), default=None,
              help="Search directory for PPN**/*.xml files. Extract PPN and file number into image-url.")
@click.option('--purpose', type=click.Choice(['NERD', 'OCR'], case_sensitive=False), default="NERD",
              help="Purpose of output tsv file. "
                   "\n\nNERD: NER/NED application/ground-truth creation. "
                   "\n\nOCR: OCR application/ground-truth creation. "
                   "\n\ndefault: NERD.")
def make_page2tsv_commands(xls_file, directory, purpose):
    if xls_file is not None:
        df = pd.read_excel(xls_file)

        for _, row in df.iterrows():
            print('page2tsv $(OPTIONS) {}.xml {}.tsv --image-url={} --scale-factor={} --purpose={}'.
                  format(row.Filename, row.Filename, row.iiif_url.replace('/full/full', '/left,top,width,height/full'),
                         row.scale_factor, purpose))

    elif directory is not None:
        for file in glob.glob('{}/**/*.xml'.format(directory), recursive=True):

            ma = re.match('(.*/(PPN[0-9]+)/.*?([0-9]+).*?).xml', file)

            if ma:
                print('page2tsv {} {}.tsv '
                      '--image-url=https://content.staatsbibliothek-berlin.de/dc/'
                      '{}-{:08d}/left,top,width,height/full/0/default.jpg --scale-factor=1.0 --purpose={}'.
                      format(file, ma.group(1), ma.group(2), int(ma.group(3)), purpose))