semvec/pypi-packages huggingface dataset:
PGPym 0.6.1
Pretty Good Privacy for Python
Requires Python: >=3.6
Keywords: OpenPGP, PGP, Pretty Good Privacy, GPG, GnuPG, openpgp, pgp, gnupg, gpg, encryption, signature

PGPym: Pretty Good Privacy for Python
=====================================

.. image:: https://badge.fury.io/py/PGPy.svg
    :target: https://badge.fury.io/py/PGPy
    :alt: Latest stable version

.. image:: https://travis-ci.com/SecurityInnovation/PGPy.svg?branch=master
    :target: https://travis-ci.com/SecurityInnovation/PGPy?branch=master
    :alt: Travis-CI

.. image:: https://coveralls.io/repos/github/SecurityInnovation/PGPy/badge.svg?branch=master
    :target: https://coveralls.io/github/SecurityInnovation/PGPy?branch=master
    :alt: Coveralls

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

`PGPym` is a hopefully temporary fork of `PGPy` with additional maintenance fixes.
`PGPy` is Python library for implementing Pretty Good Privacy into Python programs, conforming to the OpenPGP specification per RFC 4880.

Features
--------

Currently, PGPy can load keys and signatures of all kinds in both ASCII armored and binary formats.

It can create and verify RSA, DSA, and ECDSA signatures, at the moment. It can also encrypt and decrypt messages using RSA and ECDH.

Installation
------------

To install PGPym, simply:

.. code-block:: bash

    $ pip install PGPym

Documentation
-------------

`PGPy Documentation <https://pgpy.readthedocs.io/en/latest/>`_ on Read the Docs

Discussion
----------

Please report any bugs found on the `issue tracker <https://github.com/eaaltonen/PGPy/issues>`_

You can also join ``#pgpy`` on Freenode to ask questions or get involved

Requirements
------------

- Python >= 3.6

  Tested with: 3.14, 3.13, 3.12, 3.11, 3.10

- `Cryptography <https://pypi.python.org/pypi/cryptography>`_

- `pyasn1 <https://pypi.python.org/pypi/pyasn1/>`_

- `six <https://pypi.python.org/pypi/six>`_

License
-------

BSD 3-Clause licensed. See the bundled `LICENSE <https://github.com/SecurityInnovation/PGPy/blob/master/LICENSE>`_ file for more details.
gigalens 1.2.1
This is a package for Gradient Informed, GPU Accelerated Lens modelling (GIGALens).
Requires Python: >=3.12

GIGA-Lens
========================

.. image:: https://img.shields.io/pypi/v/gigalens.svg
    :target: https://pypi.python.org/pypi/gigalens
    :alt: Latest PyPI version

Gradient Informed, GPU Accelerated Lens modelling (GIGA-Lens) is a package for fast Bayesian inference on strong gravitational lenses, with support for multi-device and multi-node GPU acceleration for large-scale inference workloads. For details, please see `our paper <https://arxiv.org/abs/2202.07663>`__. See
`here <https://giga-lens.github.io/gigalens/>`__ for our documentation.

Usage
-----
Note: Some ``.ipynb`` files cannot be run directly in the GitHub preview and must be downloaded to be opened in Jupyter Notebook or JupyterLab.

Installation
------------
``GIGA-Lens`` can be installed via pip: ::

    pip install gigalens[cuda]

If pip notes an error after installation about conflicting dependencies, these can usually be safely ignored.
If you wish to test the installation, tests can be run simply by running ``tox`` in the root directory.

If you don’t have access to institutional GPUs, one easy way is to use GPU on Google Colab.  Please remember the
very first cell should have ``!pip install gigalens[cuda]``. If you do have access to institutional GPUs, you can set up a
notebook to run on GPU.  For example, at `NESRC <https://jupyter.nersc.gov/hub/>`__, you can choose the kernel
``tensorflow-2.6.0``, and include in the first cell: ``!pip install gigalens[cuda]``.

Requirements
------------
Python Version >= 3.12

The following packages are requirements for GIGA-Lens. However, ``!pip install gigalens[cuda]`` is all you need to do. In fact,
separately installing other packages can cause issues with subpackage dependencies. Some users may find it necessary
to install PyYAML.

- ``jax==0.6.2``
- ``tensorflow-probability==0.25.0``
- ``lenstronomy>=1.13.2,<2.0.0``
- ``optax>=0.2.6,<0.3.0``
- ``objax>=1.8.0,<2.0.0``
- ``numpy==2.1.3``
- ``tqdm>=4.67.1,<5.0.0``

Authors
-------

`GIGALens` was written by `Andi Gu <andi.gu@berkeley.edu>`_.
tracebloc-ingestor 0.2.10
A flexible data ingestion library for various file formats
Requires Python: >=3.8

# The Data Ingestor

## Official Documentation
Follow the [official documentation](https://docs.tracebloc.io/create-use-case/prepare-dataset) to add your training/test dataset to your tracebloc client.

## Features
- Multi-source data ingestion
- API endpoints for data management
- Containerized deployment
- Kubernetes support

## License
This project is licensed under the MIT License [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT).

## Support
For additional support or questions, please refer to our documentation or contact the Tracebloc support team at `support@tracebloc.io`.
guadalupe-weather 0.3.1
Paquete analisis de clima en Isla Guadalupe
Requires Python: >=3.9

<a href="https://www.islas.org.mx/"><img src="https://www.islas.org.mx/img/logo.svg" align="right" width="256" /></a>
# Dummy Transformations
[![codecov](https://codecov.io/gh/IslasGECI/guadalupe_weather/graph/badge.svg?token=RY807ST1T1)](https://codecov.io/gh/IslasGECI/guadalupe_weather)
![example branch
parameter](https://github.com/IslasGECI/guadalupe_weather/actions/workflows/actions.yml/badge.svg)
![licencia](https://img.shields.io/github/license/IslasGECI/guadalupe_weather)
![languages](https://img.shields.io/github/languages/top/IslasGECI/guadalupe_weather)
![commits](https://img.shields.io/github/commit-activity/y/IslasGECI/guadalupe_weather)
![PyPI - Version](https://img.shields.io/pypi/v/guadalupe_weather)