DeepSeek Chat LLM via x402 Gateway

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  "content": "# Python Function to Parse CSV File into List of Dictionaries\n\nHere's a robust Python function that parses a CSV file and returns a list of dictionaries, with comprehensive error handling:\n\n```python\nimport csv\nfrom typing import List, Dict, Optional\n\ndef parse_csv_to_dicts(file_path: str, \n                      delimiter: str = ',',\n                      skip_errors: bool = True) -> List[Dict[str, str]]:\n    \"\"\"\n    Parses a CSV file and returns a list of dictionaries.\n    \n    Args:\n        file_path: Path to the CSV file\n        delimiter: Character used to separate fields (default: ',')\n        skip_errors: Whether to skip malformed rows (True) or raise exception (False)\n    \n    Returns:\n        List of dictionaries where keys are column headers and values are row values\n    \n    Raises:\n        FileNotFoundError: If the file doesn't exist\n        csv.Error: If skip_errors=False and a CSV parsing error occurs\n    \"\"\"\n    result = []\n    \n    try:\n        with open(file_path, mode='r', encoding='utf-8') as csv_file:\n            reader = csv.DictReader(csv_file, delimiter=delimiter)\n            \n            for row_number, row in enumerate(reader, start=1):\n                try:\n                    # Skip empty rows\n                    if not any(row.values()):\n                        continue\n                        \n                    # Convert empty strings to None for consistency\n                    processed_row = {\n                        key: value if value != '' else None\n                        for key, value in row.items()\n                    }\n                    \n                    result.append(processed_row)\n                    \n                except Exception as e:\n                    if not skip_errors:\n                        raise csv.Error(f\"Error processing row {row_number}: {str(e)}\")\n                    # Otherwise silently skip the error row\n                    \n    except FileNotFoundError:\n        raise FileNotFoundError(f\"The file {file_path} does not exist\")\n    except csv.Error as e:\n        raise csv.Error(f\"CSV parsing error: {str(e)}\")\n    except Exception as e:\n        raise Exception(f\"Unexpected error: {str(e)}\")\n    \n    return result\n```\n\n## Features\n\n1. **Error Handling**:\n   - Handles missing files\n   - Handles malformed CSV rows\n   - Option to skip errors or raise exceptions\n\n2. **Data Processing**:\n   - Uses first row as dictionary keys (headers)\n   - Converts empty strings to `None` for consistency\n   - Skips completely empty rows\n\n3. **Flexibility**:\n   - Customizable delimiter (works with TSV files too)\n   - Type hints for better code documentation\n\n## Usage Example\n\n```python\ntry:\n    data = parse_csv_to_dicts('data.csv')\n    for row in data:\n        print(row)\nexcept Exception as e:\n    print(f\"Error processing file: {e}\")\n```\n\n## Alternative Version (Strict Typing)\n\nFor Python 3.9+ with stricter typing:\n\n```python\nfrom typing import List, Dict, Union, Optional\n\ndef parse_csv_to_dicts(file_path: str, \n                      delimiter: str = ',',\n                      skip_errors: bool = True) -> List[Dict[str, Optional[str]]]:\n    # ... (same implementation as above)\n```\n\nThis version makes it clear that dictionary values can be either strings or None."
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