# -*- coding: utf-8 -*-
import pandas as pd
import argparse
import json
from ase import Atoms
import ast

def deep_convert(val):
    """
    Recursively convert string representations of Python/JSON literals
    into actual Python objects.

    Rules:
    - Strings like "[...]" -> list
    - Strings like "{...}" -> dict
    - Nested structures are handled recursively
    - Invalid formats are safely ignored
    """

    # Step 1: Attempt to parse string literals
    if isinstance(val, str):

        val_strip = val.strip()

        # Check if the string looks like a list or dict
        if (
            (val_strip.startswith("[") and val_strip.endswith("]")) or
            (val_strip.startswith("{") and val_strip.endswith("}"))
        ):
            # Try JSON parsing first (strict format)
            try:
                val = json.loads(val_strip)
            except json.JSONDecodeError:
                # Fallback to Python literal parsing (more flexible)
                try:
                    val = ast.literal_eval(val_strip)
                except (ValueError, SyntaxError):
                    return val  # Return original if parsing fails

    # Step 2: Recursively process lists
    if isinstance(val, list):
        return [deep_convert(v) for v in val]

    # Step 3: Recursively process dictionaries
    if isinstance(val, dict):
        return {k: deep_convert(v) for k, v in val.items()}

    # Step 4: Return unchanged for other types
    return val

def read_phonix_summary(filename):
    
    df = pd.read_csv(filename)
    
    structures = []
    for i, struct_str in enumerate(df['structure'].values):
        
        mpid = df['mp_id'].values[i]
        
        if isinstance(struct_str, str):
            try:
                struct_dict = json.loads(struct_str)
                atoms = Atoms(
                    symbols=struct_dict["symbols"],
                    scaled_positions=struct_dict["positions"],
                    cell=struct_dict["cell"],
                    pbc=struct_dict["pbc"]
                )
                structures.append(atoms)
            except Exception as e:
                print(f"Warning: Failed to parse structure at row {mpid}.")
                structures.append(None)
        else:
            print(f"Warning: 'structure' column contains non-string value at row {mpid}, skipping.")
            structures.append(None)
            
    df['structure'] = structures
    
    df = df.map(deep_convert)
    return df

def main(options):
    
    print(" Reading", options.filename)

    df = read_phonix_summary(options.filename)
    print(df.head())
    
    print(df.count())

    df_filtered = df[df['kc[W/mK]'] > df['kp[W/mK]']]
    print(df_filtered[['kc[W/mK]', 'kp[W/mK]']])



if __name__ == '__main__':
    
    parser = argparse.ArgumentParser(description='Input parameters')

    parser.add_argument('-f', '--filename', dest='filename', type=str,
            default="out_csv/all_data.csv", help="input file name")
    
    args = parser.parse_args()
    
    main(args)