semvec/pypi-packages huggingface dataset:
zoslogs 0.3.0
Library for breaking z/OS log files up into individual messages
Requires Python: >=3.6
Keywords: zoslogs, z/OS, mainframe

m=======
zoslogs
=======


.. image:: https://img.shields.io/pypi/v/zoslogs.svg
        :target: https://pypi.python.org/pypi/zoslogs
        :alt:  Pypi

.. image:: https://github.com/Tam-Lin/zoslogs/actions/workflows/build.yml/badge.svg
        :target: https://github.com/Tam-Lin/zoslogs/actions/workflows/build.yml
        :alt: Build Status

.. image:: https://readthedocs.org/projects/zoslogs/badge/?version=latest
        :target: https://zoslogs.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status


Library for parsing z/OS log files (syslog, operlog) up into individual messages.  Because logs can be messy, and
authorized programs can write whatever they want to the log, by default it will discard anything that doesn't match
what a log entry should look like, and return whatever it can make sense of.

Please note that this was written to solve a problem I was having; it's by no means perfect, but it may solve a problem
you have, too, and I do plan on continuing to improve it as I have time.  Pull requests and bug reports will certainly
be appreciated.


* Free software: Apache Software License 2.0
* Documentation: https://zoslogs.readthedocs.io.


Features
--------

* Handle compressed files
* Filtering messages



Credits
-------

Created by Kevin McKenzie
kmckenzi@us.ibm.com

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
airflow-stubs 0.0.2
Type stubs for when Airflow is not installed
Requires Python: >=3.8

# airflow-stubs

[![PyPI - Version](https://img.shields.io/pypi/v/airflow-stubs.svg)](https://pypi.org/project/airflow-stubs)

-----

## Table of Contents

- [airflow-stubs](#airflow-stubs)
  - [Table of Contents](#table-of-contents)
  - [Installation](#installation)
  - [Introduction](#introduction)
  - [Motivation](#motivation)
  - [Notes on regenerating](#notes-on-regenerating)
  - [License](#license)

## Installation

```console
pip install airflow-stubs
```

## Introduction

This is not meant to improve the type hints of Airflow. Instead it's meant to offer some basic type hints when Airflow is not installed.

Lots of stuff is broken. Use at your own risk.

## Motivation

Airflow has lots of dependencies.
I want to be able to run it via Docker Compose as in [simple-airflow](https://github.com/maresb/simple-airflow) without installing it in my project.
I do however want to define DAGs in my project that use [`@task.docker`](https://airflow.apache.org/docs/apache-airflow/stable/tutorial/taskflow.html#dependency-separation-using-docker-operator).
Installing the stubs alleviates some of the errors from not having Airflow installed in my environment.

## Notes on regenerating

```bash
rm -rf dist
docker run -it --name generate-airflow-stubs -v "$(pwd)/generate-stubs-in-container.sh:/generate-stubs-in-container.sh:ro" apache/airflow bash /generate-stubs-in-container.sh
docker cp generate-airflow-stubs:/home/airflow/out/airflow .
docker rm generate-airflow-stubs
rm -rf airflow-stubs
mv airflow airflow-stubs
python -m build .
```

In order to render `airflow.models.dag` I had to patch
[`get_members`](https://github.com/python/mypy/blob/5db161ffbfd7d9cdd837410cd5d581c0ba597623/mypy/stubgenc.py#L475-L488)
in mypy in order to retry on `RuntimeError: dictionary changed size during iteration`.
(I used `try: ... except RuntimeError: return self.get_members(obj)`.)

Publishing to PyPI is manual for now: `twine upload dist/*`.

## License

`airflow-stubs` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
danielle 0.1.0
A Python package implementing core data structures from scratch
Requires Python: >=3.7

# 🧠 Python Data Structures Package

Welcome to the **Data Structures Package** — a clean, modular, and beginner-friendly Python library implementing essential data structures. This package is designed for learning, teaching, and experimenting with core data structure concepts in Python.

---

## 🚀 Features

This package includes Python implementations of the following data structures:

- 🧱 **Array**
- 🔗 **Singly Linked List**
- 🔁 **Circular Linked List**
- 🔄 **Doubly Linked List**
- 🗃️ **Stack (LIFO)**
- 📬 **Queue (FIFO)**
- 🌳 **Tree**
- 🕸️ **Graph**

Each data structure is implemented from scratch with easy-to-read code and useful methods to manipulate and visualize data.

---

## 📦 Installation

Clone this repository and use it locally:

```bash
git clone https://github.com/your-username/data_structures.git
cd data_structures
```

No external dependencies required. Just use Python 3.7+.

---

## 🧪 Usage

Each data structure is placed in its own module inside the package. Example usage:

```python
from danielle.stack import Stack

stack = Stack()
stack.push(10)
stack.push(20)
stack.pop()
```

---

## 📁 Project Structure

```
data_structures/
└── danielle/
    ├── __init__.py
    ├── array.py
    ├── linked_list.py
    ├── circular_linked_list.py
    ├── doubly_linked_list.py
    ├── stack.py
    ├── queue.py
    ├── tree.py
    ├── graph.py
    └── __main__.py
```

- Each `.py` file represents one data structure
- `__main__.py` can be used to test the structures via `python -m danielle`

---

## 🧰 Contributing

Want to improve a data structure or add new features (like visualization or performance benchmarking)? Contributions are welcome! Feel free to open issues or pull requests.

---

## 👩🏽‍💻 Author

Created with ❤️ by **Kapsa Danielle**  
African Master’s in Machine Intelligence (AMMI) 2025

---

## 📜 License

This project is open source and available under the [MIT License](LICENSE).

---

## ⭐️ Show Your Support

If you found this helpful or inspiring, give the project a ⭐️ on GitHub!
rc23104uno-stanleyr 0.1.2
Librería para resolver sistemas de ecuaciones lineales y no lineales
Requires Python: >=3.6

# RC23104UNO

LibrerÃ­a Python para resolver sistemas de ecuaciones lineales y no lineales.

## MÃ©todos implementados

### Sistemas lineales
- EliminaciÃ³n de Gauss
- Gauss-Jordan
- Regla de Crammer
- DescomposiciÃ³n LU
- Jacobi
- Gauss-Seidel

### Sistemas no lineales
- BisecciÃ³n

## InstalaciÃ³n

```bash
pip install RC23104