Quick and dirty CSV to JSON converter. Does not chunk files, so really large files might be an issue depending on available memory.

css_to_json.py

import csv
import json
import argparse

def convert_csv_to_json(input_file, output_file, verbose=False):
   
    print(f"Converting {input_file} >>> {output_file}")

    output_dict = { "rows": [], "sourceFile": input_file }

    # !!! Assumes a CRLF/UTF-8 encoded file
    converted_rows = 0
    with open(input_file, "r", encoding="utf-8") as f:
        for row in csv.reader(f):

            if converted_rows == 0:
                headers = row  # Assumes CSV has a headers row.
                print(f"Detected colummn headers: {headers}")
            else:
                output_dict["rows"].append( dict(zip(headers, row)) )

            converted_rows += 1

    output_dict["convertedRows"] = converted_rows

    if verbose:
        print(json.dumps(output_dict, indent=2))

    with open(output_file, "w", encoding="utf-8") as f:
        json.dump(output_dict, f, ensure_ascii=False, indent=2)

    #


if __name__ == "__main__":

    parser = argparse.ArgumentParser(
            prog="Quick and Dirty CSV to JSON parser",
            description="Converts a CRLF UTF-8 CSV file to a JSON object.",
            epilog="Please don't feed the wild animals")

    parser.add_argument("-f", "--input-file")
    parser.add_argument("-o", "--output-file")
    parser.add_argument("-v", "--verbose", action="store_true")

    args = parser.parse_args()

    INPUT_FILE = args.input_file
    OUTPUT_FILE = args.output_file \
        if args.output_file is not None \
            else f"{'.'.join(args.input_file.split('.')[:-1])}.json"
    
    VERBOSE = args.verbose

    convert_csv_to_json(INPUT_FILE, OUTPUT_FILE, VERBOSE)