"""Extra statistical significance analyses for quant report."""
# %% Imports

from utils import QualtricsSurvey
import polars as pl
import argparse
import json
import re




# %% Fixed Variables
RESULTS_FILE = 'data/exports/2-4-26/JPMC_Chase Brand Personality_Quant Round 1_February 4, 2026_Labels.csv'
QSF_FILE = 'data/exports/OneDrive_2026-01-21/Soft Launch Data/JPMC_Chase_Brand_Personality_Quant_Round_1.qsf'


# %% CLI argument parsing for batch automation
# When run as script: uv run XX_statistical_significance.script.py --age '["18
# Central filter configuration - add new filters here only
# Format: 'cli_arg_name': 'QualtricsSurvey.options_* attribute name'
FILTER_CONFIG = {
    'age': 'options_age',
    'gender': 'options_gender',
    'ethnicity': 'options_ethnicity',
    'income': 'options_income',
    'consumer': 'options_consumer',
    'business_owner': 'options_business_owner',
    'ai_user': 'options_ai_user',
    'investable_assets': 'options_investable_assets',
    'industry': 'options_industry',
}

def parse_cli_args():
    parser = argparse.ArgumentParser(description='Generate quant report with optional filters')
    
    # Dynamically add filter arguments from config
    for filter_name in FILTER_CONFIG:
        parser.add_argument(f'--{filter_name}', type=str, default=None, help=f'JSON list of {filter_name} values')
    
    parser.add_argument('--filter-name', type=str, default=None, help='Name for this filter combination (used for .txt description file)')
    
    # Only parse if running as script (not in Jupyter/interactive)
    try:
        # Check if running in Jupyter by looking for ipykernel
        get_ipython()  # noqa: F821 # type: ignore
        # Return namespace with all filters set to None
        no_filters = {f: None for f in FILTER_CONFIG}
        return argparse.Namespace(**no_filters, filter_name=None)
    except NameError:
        args = parser.parse_args()
        # Parse JSON strings to lists
        for filter_name in FILTER_CONFIG:
            val = getattr(args, filter_name)
            setattr(args, filter_name, json.loads(val) if val else None)
        return args

cli_args = parse_cli_args()


# %%
S = QualtricsSurvey(RESULTS_FILE, QSF_FILE)
data_all = S.load_data()


# %% Build filtered dataset based on CLI args

# CLI args: None means "no filter applied" - filter_data() will skip None filters

# Build filter values dict dynamically from FILTER_CONFIG
_active_filters = {filter_name: getattr(cli_args, filter_name) for filter_name in FILTER_CONFIG}

_d = S.filter_data(data_all, **_active_filters)

# Write filter description file if filter-name is provided
if cli_args.filter_name and S.fig_save_dir:
    # Get the filter slug (e.g., "All_Respondents", "Cons-Starter", etc.)
    _filter_slug = S._get_filter_slug()
    _filter_slug_dir = S.fig_save_dir / _filter_slug
    _filter_slug_dir.mkdir(parents=True, exist_ok=True)
    
    # Build filter description
    _filter_desc_lines = [
        f"Filter: {cli_args.filter_name}",
        "",
        "Applied Filters:",
    ]
    _short_desc_parts = []
    for filter_name, options_attr in FILTER_CONFIG.items():
        all_options = getattr(S, options_attr)
        values = _active_filters[filter_name]
        display_name = filter_name.replace('_', ' ').title()
        # None means no filter applied (same as "All")
        if values is not None and values != all_options:
            _short_desc_parts.append(f"{display_name}: {', '.join(values)}")
            _filter_desc_lines.append(f"  {display_name}: {', '.join(values)}")
        else:
            _filter_desc_lines.append(f"  {display_name}: All")
    
    # Write detailed description INSIDE the filter-slug directory
    # Sanitize filter name for filename usage (replace / and other chars)
    _safe_filter_name = re.sub(r'[^\w\s-]', '_', cli_args.filter_name)
    _filter_file = _filter_slug_dir / f"{_safe_filter_name}.txt"
    _filter_file.write_text('\n'.join(_filter_desc_lines))
    
    # Append to summary index file at figures/<export_date>/filter_index.txt
    _summary_file = S.fig_save_dir / "filter_index.txt"
    _short_desc = "; ".join(_short_desc_parts) if _short_desc_parts else "All Respondents"
    _summary_line = f"{_filter_slug}  |  {cli_args.filter_name}  |  {_short_desc}\n"
    
    # Append or create the summary file
    if _summary_file.exists():
        _existing = _summary_file.read_text()
        # Avoid duplicate entries for same slug
        if _filter_slug not in _existing:
            with _summary_file.open('a') as f:
                f.write(_summary_line)
    else:
        _header = "Filter Index\n" + "=" * 80 + "\n\n"
        _header += "Directory  |  Filter Name  |  Description\n"
        _header += "-" * 80 + "\n"
        _summary_file.write_text(_header + _summary_line)

# Save to logical variable name for further analysis
data = _d
data.collect()

# %%