main.py

import argparse
import json
import sys

from parser.csv_parser import parse_csv
from parser.json_parser import parse_json
from parser.xml_parser import parse_xml
from processor.cleaner import clean
from processor.transformer import filter_data, transform
from processor.aggregator import aggregate
from processor.validator import validate_schema
from output.writer import write_json
from utils.logger import log, banner, success_box
from utils.batch import get_files_from_batch, merge_results


FORMAT_PARSERS = {
    'csv': parse_csv,
    'json': parse_json,
    'xml': parse_xml,
}


def parse_args():
    parser = argparse.ArgumentParser(
        description="🛠️  CLI Data Parser — reads CSV/JSON/XML and outputs structured JSON",
        formatter_class=argparse.RawTextHelpFormatter
    )

    parser.add_argument('--input', required=True,
        help='Input file, directory, or glob pattern (e.g. data/*.csv)')
    parser.add_argument('--format', choices=['csv', 'json', 'xml'], default=None,
        help='Input format (auto-detected if not set)')
    parser.add_argument('--output', required=True,
        help='Output JSON file path')
    parser.add_argument('--filter', default=None,
        help='Filter expression e.g. "age>25" or "age>25 AND status=active"')
    parser.add_argument('--aggregate', action='store_true',
        help='Include aggregated summary in output')
    parser.add_argument('--schema', default=None,
        help='Path to JSON schema file for validation')
    parser.add_argument('--no-clean', action='store_true',
        help='Skip data cleaning step')
    parser.add_argument('--no-transform', action='store_true',
        help='Skip data transformation step')
    parser.add_argument('--chunk-size', type=int, default=10000,
        help='Chunk size for large file processing (default: 10000)')

    return parser.parse_args()


def load_schema(schema_path: str) -> dict:
    try:
        with open(schema_path) as f:
            return json.load(f)
    except Exception as e:
        log("ERROR", f"[SCHEMA] Could not load schema: {e}")
        return {}


def run():
    args = parse_args()

    banner("CLI Data Parser v2.0")

    # ── STEP 1: RESOLVE FILES ──────────────────────
    files = get_files_from_batch(args.input)

    if not files:
        log("ERROR", "No valid input files found. Exiting.")
        sys.exit(1)

    # If format is specified, override detected format
    if args.format:
        files = [(fp, args.format) for fp, _ in files]

    # ── STEP 2: PARSE (batch or single) ───────────
    all_data = []
    for filepath, fmt in files:
        log("INFO", f"Parsing '{filepath}' as {fmt.upper()}...")
        parser_fn = FORMAT_PARSERS.get(fmt)
        if not parser_fn:
            log("ERROR", f"Unsupported format: {fmt}")
            continue
        if fmt == 'csv':
            data = parse_csv(filepath, chunk_size=args.chunk_size)
        else:
            data = parser_fn(filepath)
        all_data.append(data)

    data = merge_results(all_data)

    if not data:
        log("ERROR", "No data parsed. Exiting.")
        sys.exit(1)

    # ── STEP 3: CLEAN ──────────────────────────────
    if not args.no_clean:
        data = clean(data)

    # ── STEP 4: SCHEMA VALIDATION ──────────────────
    invalid_records = []
    if args.schema:
        schema = load_schema(args.schema)
        if schema:
            data, invalid_records = validate_schema(data, schema)

    # ── STEP 5: FILTER ─────────────────────────────
    if args.filter:
        data = filter_data(data, args.filter)

    # ── STEP 6: TRANSFORM ──────────────────────────
    if not args.no_transform:
        data = transform(data)

    # ── STEP 7: AGGREGATE ──────────────────────────
    summary = None
    if args.aggregate:
        summary = aggregate(data)

    # ── STEP 8: OUTPUT ─────────────────────────────
    write_json(data, args.output, summary=summary, invalid=invalid_records or None)

    success_box(f"Done! {len(data)} records saved to '{args.output}'")


if __name__ == '__main__':
    run()