| import pandas as pd |
| import os |
| import sys |
|
|
| def align_csv_structure(csv1_path, csv2_path): |
| """ |
| Reads csv1 and csv2, reformats csv1 to match csv2's columns, |
| and overwrites csv1. |
| """ |
| |
| |
| try: |
| df1 = pd.read_csv(csv1_path) |
| df2 = pd.read_csv(csv2_path) |
| except FileNotFoundError as e: |
| print(f"Error: {e}") |
| return |
|
|
| |
| target_columns = df2.columns.tolist() |
| |
| |
| for col in target_columns: |
| if col in df1.columns: |
| |
| continue |
| |
| |
| if col == 'id': |
| |
| df1['id'] = df1['path'].apply(lambda x: os.path.splitext(os.path.basename(x))[0] if pd.notnull(x) else '') |
| |
| elif col == 'relpath': |
| |
| df1['relpath'] = df1['path'].apply(lambda x: os.path.basename(x) if pd.notnull(x) else '') |
| |
| elif col == 'audio_id': |
| |
| if 'audio_path' in df1.columns: |
| df1['audio_id'] = df1['audio_path'].apply(lambda x: os.path.splitext(os.path.basename(x))[0] if pd.notnull(x) else '') |
| else: |
| df1['audio_id'] = '' |
| |
| elif col == 'audio_fps': |
| |
| df1['audio_fps'] = 16000 |
| |
| |
| elif 'title' in col and col.startswith('cat'): |
| |
| df1[col] = '' |
| |
| |
| else: |
| |
| df1[col] = pd.NA |
|
|
| |
| |
| df1_final = df1.reindex(columns=target_columns) |
|
|
| |
| df1_final.to_csv(csv1_path, index=False) |
| print(f"Successfully processed and overwritten: {csv1_path}") |
| print(f"Columns aligned: {len(target_columns)}") |
|
|
| if __name__ == "__main__": |
| if len(sys.argv) != 3: |
| print("Usage: python align_csv.py <csv-to-align> <reference-schema-csv>", file=sys.stderr) |
| raise SystemExit(2) |
| align_csv_structure(sys.argv[1], sys.argv[2]) |
|
|