semvec/pypi-packages huggingface dataset:
aiosmtplib 5.1.0
asyncio SMTP client
License: MIT
Requires Python: >=3.10
Keywords: asyncio, email, smtp

aiosmtplib
==========

|circleci| |precommit.ci| |codecov| |zero-deps| |pypi-version| |downloads| |pypi-license|

------------

aiosmtplib is an asynchronous SMTP client for use with asyncio.

For documentation, see `Read The Docs`_.

Quickstart
----------


..
  start quickstart

.. code-block:: python

    import asyncio
    from email.message import EmailMessage

    import aiosmtplib

    message = EmailMessage()
    message["From"] = "root@localhost"
    message["To"] = "somebody@example.com"
    message["Subject"] = "Hello World!"
    message.set_content("Sent via aiosmtplib")

    asyncio.run(aiosmtplib.send(message, hostname="127.0.0.1", port=25))

..
  end quickstart

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

..
  start requirements

Python 3.10+ is required.

..
  end requirements


Bug Reporting
-------------

..
  start bug-reporting

Bug reports (and feature requests) are welcome via `Github issues`_.

.. _Github issues: https://github.com/cole/aiosmtplib/issues

..
  end bug-reporting


.. |circleci| image:: https://circleci.com/gh/cole/aiosmtplib/tree/main.svg?style=shield
           :target: https://circleci.com/gh/cole/aiosmtplib/tree/main
           :alt: "aiosmtplib CircleCI build status"
.. |pypi-version| image:: https://img.shields.io/pypi/v/aiosmtplib.svg
                 :target: https://pypi.python.org/pypi/aiosmtplib
                 :alt: "aiosmtplib on the Python Package Index"
.. |pypi-status| image:: https://img.shields.io/pypi/status/aiosmtplib.svg
.. |pypi-license| image:: https://img.shields.io/pypi/l/aiosmtplib.svg
.. |codecov| image:: https://codecov.io/gh/cole/aiosmtplib/branch/main/graph/badge.svg
             :target: https://codecov.io/gh/cole/aiosmtplib
.. |downloads| image:: https://static.pepy.tech/badge/aiosmtplib/month
               :target: https://pepy.tech/project/aiosmtplib
               :alt: "aiosmtplib on pypy.tech"
.. |precommit.ci| image:: https://results.pre-commit.ci/badge/github/cole/aiosmtplib/main.svg
                  :target: https://results.pre-commit.ci/latest/github/cole/aiosmtplib/main
                  :alt: "pre-commit.ci status"
.. |zero-deps| image:: https://0dependencies.dev/0dependencies.svg
               :target: https://0dependencies.dev
               :alt: "0 dependencies"
.. _Read The Docs: https://aiosmtplib.readthedocs.io/en/stable/
tempest-sampler 0.1.5
Persistent Sampling
License: MIT
Requires Python: >=3.8

# **TEMPEST**

**Tempest is a Python implementation of the Persistent Sampling method for accelerated Bayesian inference**

[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/minaskar/tempest/blob/master/LICENCE)
[![Documentation Status](https://readthedocs.org/projects/tempest-sampler/badge/?version=latest)](https://tempest-sampler.readthedocs.io/en/latest/?badge=latest)


# Getting started

## Brief introduction

``Tempest`` is a Python package for fast Bayesian posterior and model evidence estimation. It leverages 
the Persistent Sampling (PS) algorithm, offering significant speed improvements over 
traditional methods like MCMC and Nested Sampling. Ideal for large-scale scientific problems 
with expensive likelihood evaluations, non-linear correlations, and multimodality, ``Tempest`` 
provides efficient and scalable posterior sampling and model evidence estimation. Widely used 
in cosmology and astronomy, ``Tempest`` is user-friendly, flexible, and actively maintained.

## Documentation

Read the docs at [tempest-sampler.readthedocs.io](https://tempest-sampler.readthedocs.io) for more information, examples and tutorials. For a detailed list of changes, see the [CHANGELOG.md](https://github.com/minaskar/tempest/blob/main/CHANGELOG.md).

## Installation

To install ``tempest`` using ``pip`` run:

```bash
pip install tempest-sampler
```

or, to install from source:

```bash
git clone https://github.com/minaskar/tempest.git
cd tempest
pip install .
```

## Basic example

For instance, if you wanted to draw samples from a 10-dimensional Rosenbrock distribution with a uniform prior, you would do something like:

```python
import tempest as tp
import numpy as np

n_dim = 10  # Number of dimensions

# Define prior transform: U(-10, 10) for each dimension
def prior_transform(u):
    return 20 * u - 10

# Define log-likelihood
def log_likelihood(x):
    return -np.sum(10.0*(x[:,::2]**2.0 - x[:,1::2])**2.0 \
            + (x[:,::2] - 1.0)**2.0, axis=1)

# Create and run sampler
sampler = tp.Sampler(
    prior_transform=prior_transform,
    log_likelihood=log_likelihood,
    n_dim=n_dim,
    vectorize=True,
)
sampler.run()

samples, weights, logl = sampler.posterior() # Weighted posterior samples

logz, logz_err = sampler.evidence() # Bayesian model evidence estimate and uncertainty
```


# Attribution & Citation

Please cite the following papers if you found this code useful in your research:

```bash
@article{karamanis2025persistent,
  title={Persistent Sampling: Enhancing the Efficiency of Sequential Monte Carlo},
  author={Karamanis, Minas and Seljak, Uro{\v{s}}},
  journal={Statistics and Computing},
  volume={35},
  number={5},
  pages={1--22},
  year={2025},
  publisher={Springer}
}
```

# Licence

Copyright 2026-Present Minas Karamanis and contributors.

``Tempest`` is free software made available under the MIT License. For details see the `LICENCE` file.
yazi-bin 26.1.22
💥 Blazing fast terminal file manager written in Rust, based on async I/O.
License: MIT
Requires Python: >=3.7
Keywords: file-manager, terminal, terminal-file-manager, tui

# yazi-bin

https://github.com/sxyazi/yazi

https://yazi-rs.github.io/

## Yazi - ⚡️ Blazing Fast Terminal File Manager

Yazi (means "duck") is a terminal file manager written in Rust, based on non-blocking async I/O. It aims to provide an efficient, user-friendly, and customizable file management experience.

💡 A new article explaining its internal workings: [Why is Yazi Fast?](https://yazi-rs.github.io/blog/why-is-yazi-fast)

- 🚀 **Full Asynchronous Support**: All I/O operations are asynchronous, CPU tasks are spread across multiple threads, making the most of available resources.
- 💪 **Powerful Async Task Scheduling and Management**: Provides real-time progress updates, task cancellation, and internal task priority assignment.
- 🖼️ **Built-in Support for Multiple Image Protocols**: Also integrated with Überzug++ and Chafa, covering almost all terminals.
- 🌟 **Built-in Code Highlighting and Image Decoding**: Combined with the pre-loading mechanism, greatly accelerates image and normal file loading.
- 🔌 **Concurrent Plugin System**: UI plugins (rewriting most of the UI), functional plugins, custom previewer/preloader/spotter/fetcher; Just some pieces of Lua.
- 📡 **Data Distribution Service**: Built on a client-server architecture (no additional server process required), integrated with a Lua-based publish-subscribe model, achieving cross-instance communication and state persistence.
- 📦 **Package Manager**: Install plugins and themes with one command, keeping them up-to-date, or pin them to a specific version.
- 🧰 Integration with ripgrep, fd, fzf, zoxide
- 💫 Vim-like input/pick/confirm/which/notify component, auto-completion for cd paths
- 🏷️ Multi-Tab Support, Cross-directory selection, Scrollable Preview (for videos, PDFs, archives, code, directories, etc.)
- 🔄 Bulk Renaming, Archive Extraction, Visual Mode, File Chooser, [Git Integration](https://github.com/yazi-rs/plugins/tree/main/git.yazi), [Mount Manager](https://github.com/yazi-rs/plugins/tree/main/mount.yazi)
- 🎨 Theme System, Mouse Support, Trash Bin, Custom Layouts, CSI u, OSC 52
- ... and more!

https://github.com/sxyazi/yazi/assets/17523360/92ff23fa-0cd5-4f04-b387-894c12265cc7

## install

```sh
pip install yazi-bin
```