"""Runs INSIDE the fiscal-hub container (read-only on PostgreSQL): classifies [ncm, description] pairs with the
production Classifier through a memoizing repository wrapper. Same code path as /v1/classify, minus HTTP and the
classification_cache write; the wrapper only memoizes pure dataset lookups (datasets are static during the run).
usage: python /tmp/bulk_classify_in_container.py /tmp/in.json /tmp/out.json
"""
import json
import sys
from functools import lru_cache

from central.app.classification import Classifier
from central.app.datasets.service import DatasetService
from central.app.db import SessionLocal


class Memo:
    def __init__(self, service):
        self._s = service; self._cache = {}

    def __getattr__(self, name):
        attr = getattr(self._s, name)
        if not callable(attr):
            return attr
        def wrapped(*a, **kw):
            key = (name, a, tuple(sorted(kw.items())))
            try:
                hash(key)
            except TypeError:
                return attr(*a, **kw)
            if key not in self._cache:
                self._cache[key] = attr(*a, **kw)
            return self._cache[key]
        return wrapped


def main():
    pairs = json.load(open(sys.argv[1], encoding="utf-8"))
    out = []
    with SessionLocal() as session:
        classifier = Classifier(Memo(DatasetService(session)))
        for ncm, desc in pairs:
            out.append(classifier.classify({"current_ncm": ncm, "description": desc}))
    json.dump(out, open(sys.argv[2], "w", encoding="utf-8"), ensure_ascii=False, default=str)
    print(len(out))


main()