cjvt-corpusparser/corpusparser/main.py

from pathlib import Path
from corpusparser import Parser 
import argparse
import logging
import json
from pymongo import MongoClient
import pymongo
import sys
from multiprocessing import Pool
import time

CORPORA = ["kres", "ssj"]

# logging.basicConfig(filename=Path("/var/tmp/corpusparser.log"), filemode='a', level=logging.INFO)
logger = logging.getLogger(__name__)

lfh = logging.FileHandler("/project/logs/fill-database.log")
# lfh = logging.StreamHandler(sys.stdout)
formatter = logging.Formatter("%(asctime)s %(levelname)s %(message)s")
lfh.setFormatter(formatter)
logger.addHandler(lfh)
logger.setLevel(logging.INFO)

n_kres_files = -1  # for logging


def enriched_lemma(token):
    return (token["lemma"] if token["msd"][0] == "G" else token["lemma"] + "_")


def _helper_tid_to_token(tid, tokens):
    for t in tokens:
        if t["tid"] == tid:
            return t
    return None


def _db_preprocess(e):
    if e["srl_links"] is None:
        e["headwords"] = []
        e["functors"] = []
    else:
        hw_tids = list(set([x["from"] for x in e["srl_links"]]))
        hw_tokens = [_helper_tid_to_token(tid, e["tokens"]) for tid in hw_tids]
        headwords = [enriched_lemma(t) for t in hw_tokens]
        e["headwords"] = headwords

        functors = list(set([x["afun"] for x in e["srl_links"]]))
        e["functors"] = functors
    return e


# handler for concurrency
def _handle_kres_file_tpl(kres_file_tpl):
    tstart = time.time()
    kres_file_idx = kres_file_tpl[0]
    kres_file = kres_file_tpl[1]
    kres_data = kres_parser.parse_xml_file(kres_file)
    if args.output == "file":
        kres_outdir = outdir / "kres_json"
        kres_outdir.mkdir(parents=True, exist_ok=True)
        kres_outfile = kres_outdir / Path(kres_file.name.split(".")[0]).with_suffix(".json")
        with kres_outfile.open("w") as fp:
            json.dump(kres_data, fp)
    elif args.output == "db":
        # mongoclient needs to be created after forking
        dbclient = MongoClient(
            "mongodb://{}".format(args.dbaddr),
            username=args.dbuser,
            password=args.dbpass,
            authSource="valdb",
            authMechanism='SCRAM-SHA-1'
        )
        valdb = dbclient.valdb
        kres_col = valdb["kres"]

        # HUUUUGE BOTTLENECK
        """
        for sentence in kres_data:
            kres_col.update({"sid": sentence["sid"]}, sentence, upsert=True)
        """

        # skip if one of the sentences is already in DB
        if kres_col.find({"sid": kres_data[0]["sid"]}).count() > 0:
            logger.info("File {} already in DB ({}/{})".format(
                kres_file, kres_file_idx, n_kres_files))
            return

        kres_data_1 = [_db_preprocess(x) for x in kres_data]
        kres_col.insert_many(kres_data_1)  # much much better (just make sure sid has a unique index)
        logger.info("Inserted data from {} ({}/{}) in {:.2f} s".format(
            kres_file, kres_file_idx, n_kres_files, time.time() - tstart))

def _get_dbclient(args):
    dbclient = MongoClient(
        "mongodb://{}".format(args.dbaddr),
        username=args.dbuser,
        password=args.dbpass,
        authSource="valdb",
        authMechanism='SCRAM-SHA-1'
    )
    return dbclient


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Parsing corpora kres and ssj500k.")
    parser.add_argument('--corpus', required=True)
    parser.add_argument('--kres-folder', required=False)
    parser.add_argument('--kres-srl-folder', required=False)
    parser.add_argument('--ssj-file', required=False)
    parser.add_argument('--output', required=False, default=None)
    parser.add_argument('--outdir', required=False, default=None)
    parser.add_argument('--dbaddr', required=False, default=None)
    parser.add_argument('--dbuser', required=False, default=None)
    parser.add_argument('--dbpass', required=False, default=None)
    parser.add_argument('--cores', required=False, default=1)
    args = parser.parse_args()


    corpus = args.corpus
    assert (corpus in CORPORA), "Wrong corpus name."


    outdir = None
    if args.output == "file":
        outdir = Path(args.outdir)
        outdir.mkdir(parents=True, exist_ok=True)
    elif args.output == "db":
        dbclient = _get_dbclient(args)
        dbclient.valdb[corpus].ensure_index([("sid", pymongo.ASCENDING)])
        dbclient.valdb[corpus].ensure_index([("headwords", pymongo.ASCENDING)])
        dbclient.valdb[corpus].ensure_index([("functors", pymongo.ASCENDING)])


    if corpus == "ssj":
        logger.info("Parsing Ssj: {}".format(args.ssj_file))
        ssj_parser = Parser(logger=logger, corpus="ssj")
        ssj_data = ssj_parser.parse_xml_file(Path(args.ssj_file))
        if args.output == "file":
            ssj_outfile = outdir / "ssj500k.json"
            with ssj_outfile.open("w") as fp:
                json.dump(ssj_data, fp)
        elif args.output == "db":
            dbclient = _get_dbclient(args)
            valdb = dbclient.valdb
            ssj_col = valdb["ssj"]
            for sentence in ssj_data:
                sentence = _db_preprocess(sentence)
                ssj_col.update({"sid": sentence["sid"]}, sentence, upsert=True)


    if corpus == "kres":
        # Kres
        logger.info("Parsing Kres: {}".format(args.kres_folder))
        kres_parser = Parser(
            logger=logger,
            corpus="kres",
            kres_srl_folder=args.kres_srl_folder
        )

        # [(idx, filepath)]
        kres_files = [x for x in Path(args.kres_folder).iterdir()]
        kres_files = [x for x in enumerate(kres_files)]
        n_kres_files = len(kres_files)

        p = Pool(int(args.cores))
        p.map(_handle_kres_file_tpl, kres_files)

    
    logger.info("Finished parsing.")