Mask sensitive data with dummy.

First, git clone and pip install.

$ git clone https://github.com/ohbarye/Hermes
$ cd Hermes
$ pip install fake-factory

To mask data, prepare 2 files.

1. in.csv

   It's CSV data to mask. Any name is OK, but don't forget edit env.py's in_file.

   id,name,age,hire_date,phone_number,address,e-mail
   1,Tormas,25,1977/9/21,09-0000-0002,Ireland,tormas@te.te
   2,Yonaus,3,1990/2/26,039-0000-0002,神奈川県,yonaus@te.te
   3,Hermes,44,1982/5/21,092-0000-0002,東京,hermes@te.te

2. rules.json

   The rules how to mask data. It's written in JSON. The Key means column number (it starts from 0), and the value does data type.

   {
       "1": "name",
       "2": "age",
       "3": "date",
       "4": "phone_number",
       "5": "address",
       "6": "email"
   }

The above sample generates the following result: out.csv.

id,name,age,hire_date,phone_number,address,e-mail
1,杉山 和也,99,2004-10-04,73-7004-3804,青森県日野市独鈷沢15丁目2番6号 パーク九段南823,sequiy@example.org
2,山田 裕美子,54,1988-12-08,48-8365-9175,長崎県西多摩郡檜原村細竹15丁目25番16号 ハイツ日光446,qui84@example.com
3,宇野 香織,22,1973-03-09,30-8595-4194,愛知県北区三ノ輪22丁目6番15号 前弥六パーク361,veroy@example.net

• If you want to mask data by other location style.Edit env.py's location. e.g. en_US: English(United States), it_IT: Italian, and so on.

• If there is no header row in in.csv, then edit env.py's skip_header to False.

• This tool depends heavily on faker for data generation. For more information, refer to https://github.com/joke2k/faker.

MIT

• generate frees style dummy data
• skip any row