synthetic-data-generators 1.0.0

Helper methods for generating synthetic data for testing and development.

synthetic-data-generators

Introduction

The purpose of this package is to provide a set of tools for generating synthetic data for various use cases. The package includes a variety of data generators, including random number generators, text generators, image generators, and time series generators. The package is designed to be easy to use and flexible, allowing users to customize the generated data to meet their specific needs.

Key URLs

For reference, these URL's are used:

Type	Source	URL
Git Repo	GitHub	https://github.com/data-science-extensions/synthetic-data-generators
Python Package	PyPI	https://pypi.org/project/synthetic-data-generators
Package Docs	Pages	https://data-science-extensions.com/synthetic-data-generators/

Installation

You can install and use this package multiple ways by using pip, pipenv, or poetry.

Using pip:

1. In your terminal, run:

   python3 -m pip install --upgrade pip
   python3 -m pip install synthetic-data-generators
   

2. Or, in your requirements.txt file, add:

   synthetic-data-generators
   

   Then run:

   python3 -m pip install --upgrade pip
   python3 -m pip install --requirement=requirements.txt
   

Using pipenv:

1. Install using environment variables:

   In your Pipfile file, add:

   [[source]]
   url = "https://pypi.org/simple"
   verify_ssl = false
   name = "pypi"
   
   [packages]
   synthetic-data-generators = "*"
   

   Then run:

   python3 -m pip install pipenv
   python3 -m pipenv install --verbose --skip-lock --categories=root index=pypi synthetic-data-generators
   

2. Or, in your requirements.txt file, add:

   synthetic-data-generators
   

   Then run:

   python3 -m run pipenv install --verbose --skip-lock --requirements=requirements.txt
   

3. Or just run this:

   python3 -m pipenv install --verbose --skip-lock synthetic-data-generators
   

Using poetry:

1. In your pyproject.toml file, add:

   [project]
   dependencies = [
       synthetic-data-generators = "*",
   ]
   

   Then run:

   poetry install
   

2. Or just run this:

   poetry add synthetic-data-generators
   poetry install
   poetry sync
   

Using uv:

1. In your pyproject.toml file, add:

   [project]
   dependencies = [
       synthetic-data-generators = "*",
   ]
   

   Then run:

   uv sync
   

2. Or just run this:

   uv add synthetic-data-generators
   uv sync
   

Contribution

Contribution is always welcome.

1. First, either fork or branch the main repo.

2. Clone your forked/branched repo.

3. Build your environment:

   1. With pipenv on Windows:

      if (-not (Test-Path .venv)) {mkdir .venv}
      python -m pipenv install --requirements requirements.txt --requirements requirements-dev.txt --skip-lock
      python -m poetry run pre-commit install
      python -m poetry run pre-commit autoupdate
      python -m poetry shell
      

   2. With pipenv on Linux:

      mkdir .venv
      python3 -m pipenv install --requirements requirements.txt --requirements requirements-dev.txt --skip-lock
      python3 -m poetry run pre-commit install
      python3 -m poetry run pre-commit autoupdate
      python3 -m poetry shell
      

   3. With poetry on Windows:

      python -m pip install --upgrade pip
      python -m pip install poetry
      python -m poetry config virtualenvs.create true
      python -m poetry config virtualenvs.in-project true
      python -m poetry init
      python -m poetry lock
      python -m poetry install --no-interaction --with dev,docs,test
      python -m poetry run pre-commit install
      python -m poetry run pre-commit autoupdate
      python -m poetry shell
      

   4. With poetry on Linux:

      python3 -m pip install --upgrade pip
      python3 -m pip install poetry
      python3 -m poetry config virtualenvs.create true
      python3 -m poetry config virtualenvs.in-project true
      python3 -m poetry init
      python3 -m poetry lock
      python3 -m poetry install --no-interaction --with dev,docs,test
      python3 -m poetry run pre-commit install
      python3 -m poetry run pre-commit autoupdate
      python3 -m poetry shell
      

   5. With uv on Windows:

      python -m pip install --upgrade pip
      python -m pip install uv
      python -m uv sync
      python -m uv run pre-commit install
      python -m uv run pre-commit autoupdate
      

   6. With uv on Linux:

      python3 -m pip install --upgrade pip
      python3 -m pip install uv
      python3 -m uv sync
      python3 -m uv run pre-commit install
      python3 -m uv run pre-commit autoupdate
      

4. Start contributing.

5. When you're happy with the changes, raise a Pull Request to merge with the main branch again.

Build and Test

To ensure that the package is working as expected, please ensure that:

1. You write your code as per PEP8 requirements.
2. You write a UnitTest for each function/feature you include.
3. The CodeCoverage is 100%.
4. All UnitTests are passing.
5. MyPy is passing 100%.

Testing

• Run them all together

  uv run make check
  

• Or run them individually:

  • Black

    uv run make check-black
    

  • PyTests:

    uv run make ckeck-pytest
    

  • MyPy:

    uv run make check-mypy