Fake Data Generator

This script generates a specified number of fake records and saves each record as a JSON file in a designated folder. It uses the Faker library to create realistic-looking data.

Features

• Generates fake identity, contact details, and location data.
• Saves each record as a separate JSON file.
• Deletes any existing folder with dummy files before creating new ones.
• Allows control over the number of records generated via command-line arguments.

Requirements

• Python 3.x
• Faker library

Installation

1. Install Python 3.x from python.org.
2. Create and activate virtual environment.

python -m venv env
source env/Scripts/activate

3. Install the required packages from file:

   pip install -r requirements.txt

Usage

1. Clone the repository or download the script.

2. Run the script from the command line:

   python generate_fake_data.py [number_of_records]

   • number_of_records (optional): The number of fake records to generate. Defaults to 1,000,000 if not specified.

3. Run using Docker.

docker build -t pydatagen .
docker run pydatagen

Example

To generate 100,000 fake records:

python generate_fake_data.py 100000

Data Generated

Each record generated by the script includes the following fields:

• Identity

  • id: A unique identifier for the record.
  • full_name: A randomly generated full name.
  • ssn: A randomly generated Social Security Number.
  • dob: A randomly generated date of birth in the format YYYY-MM-DD.

• Contact Details

  • email: A randomly generated email address.
  • phone: A randomly generated phone number.

• Location

  • address: A randomly generated street address.
  • city: A randomly generated city name.
  • state: A randomly generated state name.
  • zipcode: A randomly generated ZIP code.
  • country: A randomly generated country name.

Script Details

The script performs the following steps:

1. Control the Number of Records: Checks if a number of records is provided as a command-line argument. If not, defaults to 1,000,000 records.
2. Delete Existing Folder: Deletes the existing files folder if it exists.
3. Recreate the Folder: Creates a new files folder.
4. Generate Fake Data: Uses the Faker library to generate fake data for each record, including identity, contact details, and location.
5. Save Data: Saves each record as a JSON file in the files folder.

Dependencies

• json: For handling JSON data.
• sys: For accessing command-line arguments.
• pathlib: For handling file paths.
• shutil: For removing directories.
• Faker: For generating fake data.
• tqdm: For displaying a progress bar.

License

This project is licensed under the MIT License.