# CSV Data Processor

This utility reads a CSV file, filters rows based on a specific criteria, selects specific columns, and saves the result to a new file. It demonstrates how to use `csv.DictReader` and `csv.DictWriter` for robust and memory-efficient CSV handling.

**Modules Used:**
*   [[programming/python/modules/csv-module|csv]]: To read and write tabular data.
*   [[programming/python/modules/argparse-module|argparse]]: To handle command-line arguments.

## The Code

Save this as `csv_tool.py`.

```python
import csv
import argparse
import sys

def process_csv(input_file, output_file, filter_col=None, filter_val=None, columns=None):
    try:
        # Open input and output files
        with open(input_file, mode='r', newline='', encoding='utf-8') as infile, \
             open(output_file, mode='w', newline='', encoding='utf-8') as outfile:
            
            reader = csv.DictReader(infile)
            
            if not reader.fieldnames:
                print("Error: CSV file is empty or has no header.")
                return

            # Determine output columns (use all if none specified)
            out_fields = columns if columns else reader.fieldnames
            
            # Validate that requested columns exist in input
            for col in out_fields:
                if col not in reader.fieldnames:
                    print(f"Error: Column '{col}' not found in input CSV.")
                    return

            # Initialize writer
            writer = csv.DictWriter(outfile, fieldnames=out_fields, extrasaction='ignore')
            writer.writeheader()
            
            count = 0
            for row in reader:
                # 1. Filter Logic
                if filter_col:
                    if filter_col not in row:
                         print(f"Error: Filter column '{filter_col}' not found.")
                         return
                    # Skip row if it doesn't match the filter value
                    if row[filter_col] != filter_val:
                        continue
                
                # 2. Write Row
                # DictWriter with extrasaction='ignore' will automatically 
                # ignore keys in 'row' that aren't in 'out_fields'
                writer.writerow(row)
                count += 1
                
            print(f"Success! Processed {count} rows into '{output_file}'.")

    except FileNotFoundError:
        print(f"Error: File '{input_file}' not found.")
    except Exception as e:
        print(f"An error occurred: {e}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="CSV Data Processor")
    parser.add_argument("input", help="Input CSV file path")
    parser.add_argument("output", help="Output CSV file path")
    parser.add_argument("--filter-col", help="Column name to filter by")
    parser.add_argument("--filter-val", help="Value to match in the filter column")
    parser.add_argument("--columns", nargs="+", help="Specific columns to keep (space separated)")

    args = parser.parse_args()
    
    process_csv(args.input, args.output, args.filter_col, args.filter_val, args.columns)
```

## Usage

```bash
# Filter rows where 'Status' is 'Active' and keep only 'Name' and 'Email' columns
python csv_tool.py users.csv active_users.csv --filter-col Status --filter-val Active --columns Name Email
```

[[programming/python/python]]