Overview🔗
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
:🔗
-
In your terminal, run:
python3 -m pip install --upgrade pip python3 -m pip install synthetic-data-generators
-
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
:🔗
-
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
-
Or, in your
requirements.txt
file, add:synthetic-data-generators
Then run:
python3 -m run pipenv install --verbose --skip-lock --requirements=requirements.txt
-
Or just run this:
python3 -m pipenv install --verbose --skip-lock synthetic-data-generators
Using poetry
:🔗
-
In your
pyproject.toml
file, add:[project] dependencies = [ synthetic-data-generators = "*", ]
Then run:
poetry install
-
Or just run this:
poetry add synthetic-data-generators poetry install poetry sync
Using uv
:🔗
-
In your
pyproject.toml
file, add:[project] dependencies = [ synthetic-data-generators = "*", ]
Then run:
uv sync
-
Or just run this:
uv add synthetic-data-generators uv sync
Contribution🔗
Contribution is always welcome.
-
Clone your forked/branched repo.
-
Build your environment:
-
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
-
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
-
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
-
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
-
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
-
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
-
-
Start contributing.
-
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:
- You write your code as per PEP8 requirements.
- You write a UnitTest for each function/feature you include.
- The CodeCoverage is 100%.
- All UnitTests are passing.
- MyPy is passing 100%.