semvec/pypi-packages huggingface dataset:
orbitalml 0.2.2
Machine Learning pipeline to SQL converter (proxy for orbital)
Requires Python: >=3.9

# OrbitalML

**Machine Learning pipeline to SQL converter**

⚠️ **Migration Notice**: OrbitalML is a transitional proxy package for users upgrading from legacy versions. **New projects should use the [orbital](https://github.com/posit-dev/orbital) package directly**. We recommend migrating existing code to use `import orbital` instead of `import orbitalml as orbital` when convenient.

OrbitalML provides the same functionality as the [orbital](https://github.com/posit-dev/orbital) library with backward-compatible import names.
devdraft-python-sdk 1.0.9
Devdraft SDK - A Python library for Devdraft's Payment & Business Management API
Keywords: Swagger, Devdraft Payment &amp; Business Management API

Devdraft SDK
============

A Python library for Devdraft's Payment & Business Management API.

Devdraft SDK provides a comprehensive solution for integrating cryptocurrency and traditional payment methods into your applications. It offers a robust set of tools for payment processing, business management, and seamless integration with the Devdraft platform.

Setup
-----

You can install this package using pip::

    pip install devdraft-sdk

Setting up a Devdraft Account
-----------------------------

1. Sign up for a Devdraft account at https://console.devdraft.ai/
2. Once logged in, navigate to the Apps section
3. Create a new app to get your API credentials
4. You'll receive two important credentials:
   - x-client-key
   - x-client-secret

Usage
-----

To use the SDK, you'll need to configure it with your API credentials.

For detailed API documentation and examples, visit our API Reference: https://docs.devdraft.ai

Features
--------

- Cryptocurrency payment processing
- Traditional payment method integration
- Business management tools
- Real-time transaction monitoring
- Comprehensive API coverage

Support
-------

For support, please visit our documentation or contact our support team at engineering@devdraft.ai.
termcolorsfx 0.1.0
Advanced terminal color formatting and logging
Requires Python: >=3.7

# termcolors

Advanced terminal formatting library with class-based structure and logger integration.

## Example

```python
from termcolors import TerminalFormatter, ColorLogger

fmt = TerminalFormatter(color="green", style="bold")
print(fmt.format("Success"))

logger = ColorLogger()
logger.info("Info message")
logger.warning("Warning!")
logger.error("Something went wrong")
django-kubernetes 1.1.0
Middleware for Kubernetes probes and Django management commands for Kubernetes jobs.
Requires Python: >=3.10
Keywords: django, kubernetes, liveness, readiness, probes, health checks, management commands, ensure admin user, migrations

# Django Kubernetes

[![Tests](https://github.com/rotationalio/django-kubernetes/actions/workflows/tests.yaml/badge.svg)](https://github.com/rotationalio/django-kubernetes/actions/workflows/tests.yaml)
[![Documentation Status](https://readthedocs.org/projects/django-kubernetes/badge/?version=latest)](http://django-kubernetes.readthedocs.io/en/latest/?badge=latest)

Middleware and Views for Kubernetes liveness and readiness probes and Django management commands for Kubernetes jobs such as waiting for the database to be ready or ensuring an admin user exists or is created from environment variables.

Let's face it; running a Django app on a Kubernetes cluster is a bit difficult - Django was built by folks who were running it on virtual machines or even bare metal hardware! They expected a shell environment available to them to be able to run management commands and influence how Django started up when in production.

When Django is orchestrated, we somehow have to manage these commands in our clusters; either by manually running the commands or creating init containers or Jobs that our deployments depend on. Moreover, once the pods are up and running, we need to ensure that the Kubernetes control layer can manipulate them as needed.

That's where this package comes in, it provides the following helpers to make your Django deployments on Kubernetes easier:

**Readiness Probes**

- `DatabaseProbe`: Checks that a connection can be established to the database
- `MemcachedProbe`: Checks that the cache nodes are available and ready

**Views**

- `LivenessView`: responds Ok to `/livez` and `/healthz` path requests
- `ReadinessView`: respond Ok if readiness probes are fine, else 503

**Middleware**

- `ProbeMiddleware`: performs `/livez`, `/healthz`, and `/readyz` checks with readiness probes before any middleware or views might interact with those services and raise a 500 error or some other error.

**Management Commands**

- `./manage.py probe`: a CLI version of the probes with `--live`, `--health`, and `--ready` checks that can be used by Kubernetes probe `exec` commands.
- `./manage.py wait4db`: sleeps until the database is ready and available
- `./manage.py ensureadmin`: reads environment variables for an admin user and creates that super user if the record does not already exist in the database.
- `./manage.py lockedmigrate`: uses a postgres advisory lock to ensure migration safety across multiple processes; useful for a multi-replica deployment with a migrate init container.

See the [documentation](https://django-kubernetes.readthedocs.io/en/latest/) for more on how to get started and use this app in your Django project.
novapipe 1.0.0
NovaPipe: An advanced, plugin-driven ETL CLI tool
Requires Python: <4.0,>=3.8

# NovaPipe

[![PyPI version](https://img.shields.io/pypi/v/novapipe.svg)](https://pypi.org/project/novapipe)  
[![Build Status](https://github.com/muqtarM/novapipe/actions/workflows/release.yml/badge.svg)](https://github.com/muqtarM/novapipe/actions)  
[![Coverage Status](https://img.shields.io/codecov/c/github/your-org/novapipe.svg)](https://codecov.io/gh/muqtarM/novapipe)  
[![Documentation Status](https://readthedocs.org/projects/novapipe/badge/?version=latest)](https://novapipe.readthedocs.io/)  
[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE)

---

> **NovaPipe** — lightweight, plugin-driven ETL & orchestration for Python.

## 🎯 Quickstart

Install from PyPI:

```bash
pip install novapipe
```

Create `pipeline.yaml`:

```yaml
tasks:
  - name: extract
    task: extract_data
    params:
      source: "s3://my-bucket/input.csv"

  - name: transform
    task: transform_data
    params:
      input_path: "{{ extract }}"
    depends_on:
      - extract

  - name: load
    task: load_data
    params:
      path: "{{ transform }}"
    depends_on:
      - transform
```

Run it:

```bash
novapipe run pipeline.yaml \
  --var environment=prod \
  --summary-json summary.json \
  --metrics-port 8000
```

View a human-friendly report:

```bash
novapipe report summary.json
```

---

## 🚀 Features

|Category	| Features |
|-----------|----------|
|Core CLI	| `init`, `run`, `inspect`, `describe`, `tutorial`, `dag`, `report`, `playground`|
|Plugin Mgmt.	|Scaffold, list (with filters), CI-template, version-gating|
|Pipeline Modeling	|`run_if`/`run_unless`, branches, skip-downstream, retries, timeouts, ignore-failures|
|Execution Engine	|Async/sync, layered parallelism, resource tagging, rate-limit|
|Templating & Context	|Jinja2 with built-ins, multi-output unpacking, CLI vars, interactive REPL|
|Resource & Env	|CPU/memory caps, rate limits, env injection|
|Observability	|Structured logging, JSON summary, human report, Prometheus metrics|
|Testing & CI/CD	|Unit & integration tests, plugin + repo CI templates|

---

## 📖 Documentation

Full docs and examples are hosted on ReadTheDocs:

> https://novapipe.readthedocs.io/

---

## 💡 Getting Help

- Ask questions on [Discussions](https://github.com/muqtarM/novapipe/discussions)

- Report bugs via [Issues](https://github.com/muqtarM/novapipe/discussions)

---

## 🤝 Contributing

1. Fork & clone
2. `poetry install` (or `pip install -e .[dev]`)
3. Create a feature branch, commit, and open a PR
4. Ensure tests pass: `pytest`

See CONTRIBUTING.md & CODE_OF_CONDUCT.md for details.

---

## 📜 License

MIT © Muqtar Shaikh

1. **Replace** badge URLs with your actual GitHub org/repo and PyPI project names.  
2. **Link** the Quickstart to real example pipelines in your `examples/` folder.  
3. **Populate** the “Features” table with any additional items as you add them.