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This is a console app that generates an arbitrary length of columnar fake data using python.

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dareljohnson/fake-data-generator-app

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Project Title

Fake data generator using python

Project Description

This repository contains the source code for a Python console app, using the Faker library to generate an arbitrary length of columnar data. This generator creates a CSV file.

Assumptions

I assume you are developing this project on a Microsoft Windows PC. A built-in Windows tool like notepad.exe is used in this project to create and edit files. If you are developing on Linux, you can use vim.

notepad .gitignore

On Linux:

vim .gitignore

You can also use a modern code editor like VSCode to follow along.

How to Use the Project

You can clone this project.

 git clone https://github.com/dareljohnson/fake-data-generator-app.git

Project Requirements

Requirements:

  • Python 3.10.0
  • Faker==18.11.1

How to install python packages

Create a custom python environment for your project:

conda create --name faker python=3.10

If you are using the PowerShell command line interface, you may need to initialize a shell for the conda environment.

To initialize your shell, run

$ conda init <SHELL_NAME>

Currently supported shells are:

  • bash
  • cmd.exe
  • fish
  • tcsh
  • xonsh
  • zsh
  • powershell

I'm going to use cmd.exe:

conda init cmd.exe

Activate the environment:

conda activate faker

Clone the repo

Clone repo to current directory

git clone https://github.com/dareljohnson/fake-data-generator-app.git .

Install the packages

pip install -r requirements.txt

How to Run the Project

Run the local application:

python main.py filename # You don't need to add a file extension

How to Build the Project for production

N/A

Include Credits

TBA

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

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This is a console app that generates an arbitrary length of columnar fake data using python.

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