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Helper methods for generating synthetic data for testing and development.

Project description

synthetic-data-generators

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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 --all-groups
      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 --all-groups
      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 src/utils/scripts.py check
    
  • Or run them individually:

    • Black

      uv run src/utils/scripts.py check-black
      
    • PyTests:

      uv run src/utils/scripts.py check-pytest
      
    • MyPy:

      uv run src/utils/scripts.py check-mypy
      

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