semvec/pypi-packages huggingface dataset:
jaraco.services 4.0.0
Service orchestration and pytest plugins
Requires Python: >=3.8

.. image:: https://img.shields.io/pypi/v/jaraco.services.svg
   :target: https://pypi.org/project/jaraco.services

.. image:: https://img.shields.io/pypi/pyversions/jaraco.services.svg

.. image:: https://github.com/jaraco/jaraco.services/actions/workflows/main.yml/badge.svg
   :target: https://github.com/jaraco/jaraco.services/actions?query=workflow%3A%22tests%22
   :alt: tests

.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/charliermarsh/ruff/main/assets/badge/v2.json
    :target: https://github.com/astral-sh/ruff
    :alt: Ruff

.. .. image:: https://readthedocs.org/projects/PROJECT_RTD/badge/?version=latest
..    :target: https://PROJECT_RTD.readthedocs.io/en/latest/?badge=latest

.. image:: https://img.shields.io/badge/skeleton-2024-informational
   :target: https://blog.jaraco.com/skeleton
rhdzmota 4.0.1
RHDZMOTA Package
Requires Python: >=3.8.10

# RHDZMOTA Package

[Rodrigo H. Mota](https://rhdzmota.com)'s personal python package that contains general tooling for facilitating the development of software engineering, data engineering, and machine learning projects.

**Aren't toolbox packages usually heavy?** One main concern of designing toolbox packages shared across projects is that the dependency set often becomes too heavy. This is specially true for data-related projects (e.g., installing pandas, request, tensorflow, sklearn, etc). To solve this issue, the `rhdzmota` package offers "package extensions" that can be installed by specifying their corresponding tags. This allows us to "split" the dependency set and functionality in sub-python packages; resulting in a lightweight and modular toolbox!

**How can I install a package extension?** You just need to specify their corresponing "extras-require" tag. Example:

```commandline
$ pip install 'rhdzmota[ext.hello_world]'
```

All the package extensions tag will follow the pattern: `ext.*`

**Are there any import patterns to consider?** Yes, both the core package and the extensions share a common namespace: `rhdzmota`. The core package contains their modules directly at the first level (e.g., `rhdzmota.*`) and the extensions share an inner namespace (i.e., `rhdzmota.ext`) resulting in the following pattern: `rhdzmota.ext.{{ext-slug}}`).

The following example imports the `Env` enum from the `settings` module in the core package and the `hello` function from the `hello_world` extension.

```python
from rhdzmota.settings import Env
from rhdzmota.ext.hello_world.functions import hello

...
```