conversor.py

#!/usr/bin/env python3


import csv
import argparse

TRANSLATION = {
    "First Name": "First Name",
    "Last Name": "Last Name",
    "Company": "Current Company",
    "Title": "Current Title",
    "Notes": "",
    "Email": "Email Address",
    "Phone": "Phone Number",
    "Social Media": "",
    "Website": "Profile URL",
    "Address": "",
    "Source": "Linkedin prospecting",
    "Who gets credit": "",
    "Job": "",
    "Department": "",
    "Office": "",
    "Prospect Pool": "",
    "Prospect Stage": "",
}


def parse_row(row, recruiter: str):
    new_row = {k: row.get(v, v) for k, v in TRANSLATION.items()}

    new_row["Who gets credit"] = recruiter
    return new_row


def main(input, recruiter):
    with open(input, newline="") as input_f, open(f"green-{input}", "w") as output_f:
        reader = csv.DictReader(input_f)
        writer = csv.DictWriter(
            output_f, TRANSLATION.keys(), quotechar='"', quoting=csv.QUOTE_ALL
        )
        writer.writeheader()
        for row in reader:
            writer.writerow(parse_row(row, recruiter))


def parse_args():
    parser = argparse.ArgumentParser(description="Convert Linkedin csv to Greenhouse")
    parser.add_argument("input", metavar="N", type=str)
    parser.add_argument("--recruiter", type=str, default="Yuliia Syrotiuk")
    return parser.parse_args()


if __name__ == "__main__":
    args = parse_args()
    recruiter = args.recruiter
    print(f"Converting {args.input} to Greenhouse format")
    main(input=args.input, recruiter=args.recruiter)