semvec/pypi-packages huggingface dataset:
SumOfSquares-yuanchenyang 1.2
Python implementation of Sum-of-Squares optimization built on picos
Requires Python: >=3.6

SumOfSquares.py
---------------

Sum of squares optimization built on top of
[picos](https://picos-api.gitlab.io/picos/). Easy access to pseudoexpectation
operators for both formulating problems and extracting solutions via rounding
algorithms.

[Examples](https://sums-of-squares.github.io/sos/index.html#python)

(Detailed documentation coming soon)
eva-tools 1.0.0
Set of tools for manipulating research data related to the Easy Volcanic Aerosol Model, and other stratospheric aerosol datasets.
Requires Python: >=3.6

The eva_tools package is set of tools used for research on stratospheric aerosol data sets. In particular, the package
was created to aid in the development of the Easy Volcanic Aerosol model (EVA).

This package was created by C.J. Ogilvie under the supervision of Dr. Matthew Toohey, for the Institute of Space and
Atmospheric Studies at the University of Saskatchewan.

For questions, contact:
    - C.J. Ogilvie: cfo188@usask.ca
    - Dr. Matthew Toohey: matthew.toohey@usask.ca

The package contains four tools. These are:
    - read_eva: Reads stratospheric aerosol files into python-usable data.
    - write_eva: Writes stratospheric aerosol data into files (netCDF4 and Excel files currently supported).
    - plot_eva: Quickly generate data plots from stratospheric aerosol files.
    - merge_eva: Concatenates two or more stratospheric aerosol files to cover a larger time period.

Last updated April 28th, 2022.
mapview 1.0.6
A kivy garden mapview demo.
Keywords: Kivy kivy-garden

# Mapview

[![Github Build Status](https://github.com/kivy-garden/mapview/workflows/Tests/badge.svg)](https://github.com/kivy-garden/mapview/actions?query=workflow%3ATests)
[![Build Status](https://travis-ci.com/kivy-garden/mapview.svg?branch=develop)](https://travis-ci.com/kivy-garden/mapview)
[![Coverage Status](https://coveralls.io/repos/github/kivy-garden/mapview/badge.svg?branch=develop)](https://coveralls.io/github/kivy-garden/mapview?branch=develop)
[![PyPI version](https://badge.fury.io/py/mapview.svg)](https://badge.fury.io/py/mapview)

Mapview is a Kivy widget for displaying interactive maps. It has been
designed with lot of inspirations of
[Libchamplain](https://wiki.gnome.org/Projects/libchamplain) and
[Leaflet](http://leafletjs.com/).

The goal of this widget is to be a replacement of Google Maps widget,
even if this one works very well, it just works on Android with Kivy.
I wanted a map widget that can support custom map, and designed with
the latests state-of-the-art Kivy's methods.

![ScreenShot](https://cloud.githubusercontent.com/assets/37904/22764226/925c93ce-ee69-11e6-90ed-88123bfa731f.png)

![Marker clustering](https://cloud.githubusercontent.com/assets/37904/22764225/92516f12-ee69-11e6-99d5-6346e302766d.png)

# Features

* native multitouch (one for translate, many for translate and zoom)
* asynchronous downloading
* avoided GPU limitation / float precisions issues on tiles coordinates
* marker support
* blazing fast!
* supports Z/X/Y providers by default with `MapSource`
* supports [.mbtiles](http://mbtiles.org) via `MBTilesMapSource`
* supports marker clustering, via `ClusteredMarkerLayer`

# Requirements

It requires the `concurrent.futures` and `requests`.
If you use it on Android / iOS, don't forget to add `openssl` as a requirements,
otherwise you'll have an issue when importing `urllib3` from `requests`.

# Install

```
pip install mapview
```

# Usage

This widget can be either used within Python or Kv. That's said, not
everything can be done in Kv, to prevent too much computing.

```python
from kivy_garden.mapview import MapView
from kivy.app import App

class MapViewApp(App):
    def build(self):
        mapview = MapView(zoom=11, lat=50.6394, lon=3.057)
        return mapview

MapViewApp().run()
```

Find out more:
- [examples/](https://github.com/kivy-garden/mapview/tree/master/examples)
- <https://mapview.readthedocs.io/en/latest/>


Contributing
--------------

Check out our [contribution guide](CONTRIBUTING.md) and feel free to improve the flower.

License
---------

This software is released under the terms of the MIT License.
Please see the [LICENSE.txt](LICENSE.txt) file.

How to release
===============

See the garden [instructions](https://kivy-garden.github.io/#makingareleaseforyourflower) for how to make a new release.
kivy-garden.mapview 1.0.6
A kivy garden mapview demo.
Keywords: Kivy kivy-garden

# Mapview

[![Github Build Status](https://github.com/kivy-garden/mapview/workflows/Tests/badge.svg)](https://github.com/kivy-garden/mapview/actions?query=workflow%3ATests)
[![Build Status](https://travis-ci.com/kivy-garden/mapview.svg?branch=develop)](https://travis-ci.com/kivy-garden/mapview)
[![Coverage Status](https://coveralls.io/repos/github/kivy-garden/mapview/badge.svg?branch=develop)](https://coveralls.io/github/kivy-garden/mapview?branch=develop)
[![PyPI version](https://badge.fury.io/py/mapview.svg)](https://badge.fury.io/py/mapview)

Mapview is a Kivy widget for displaying interactive maps. It has been
designed with lot of inspirations of
[Libchamplain](https://wiki.gnome.org/Projects/libchamplain) and
[Leaflet](http://leafletjs.com/).

The goal of this widget is to be a replacement of Google Maps widget,
even if this one works very well, it just works on Android with Kivy.
I wanted a map widget that can support custom map, and designed with
the latests state-of-the-art Kivy's methods.

![ScreenShot](https://cloud.githubusercontent.com/assets/37904/22764226/925c93ce-ee69-11e6-90ed-88123bfa731f.png)

![Marker clustering](https://cloud.githubusercontent.com/assets/37904/22764225/92516f12-ee69-11e6-99d5-6346e302766d.png)

# Features

* native multitouch (one for translate, many for translate and zoom)
* asynchronous downloading
* avoided GPU limitation / float precisions issues on tiles coordinates
* marker support
* blazing fast!
* supports Z/X/Y providers by default with `MapSource`
* supports [.mbtiles](http://mbtiles.org) via `MBTilesMapSource`
* supports marker clustering, via `ClusteredMarkerLayer`

# Requirements

It requires the `concurrent.futures` and `requests`.
If you use it on Android / iOS, don't forget to add `openssl` as a requirements,
otherwise you'll have an issue when importing `urllib3` from `requests`.

# Install

```
pip install mapview
```

# Usage

This widget can be either used within Python or Kv. That's said, not
everything can be done in Kv, to prevent too much computing.

```python
from kivy_garden.mapview import MapView
from kivy.app import App

class MapViewApp(App):
    def build(self):
        mapview = MapView(zoom=11, lat=50.6394, lon=3.057)
        return mapview

MapViewApp().run()
```

Find out more:
- [examples/](https://github.com/kivy-garden/mapview/tree/master/examples)
- <https://mapview.readthedocs.io/en/latest/>


Contributing
--------------

Check out our [contribution guide](CONTRIBUTING.md) and feel free to improve the flower.

License
---------

This software is released under the terms of the MIT License.
Please see the [LICENSE.txt](LICENSE.txt) file.

How to release
===============

See the garden [instructions](https://kivy-garden.github.io/#makingareleaseforyourflower) for how to make a new release.
loginator 0.0.16
A rudimentary command line tool to help you download logs and other files from S3
Requires Python: >=3.6
Keywords: logs aws loginator aws-s3 s3 bucket

# Loginator
 This is a rudimentary tool that will help you extract logs or other files stored in S3

 ## Installation

 ```
 pip install loginator
 ```

 ## Use
 Make sure you are logged in in an AWS account in your environment

 See instructions with:

 ```
 loginator --help
 ```

 ## Examples

 ```
 loginator example_bucket_name --prefix /2022/01/01 --out example_bucket_logs.gz
 ```
pymc3-hmm 0.2.5
Hidden Markov Models in PyMC3
Requires Python: >=3.6

![Build Status](https://github.com/AmpersandTV/pymc3-hmm/workflows/PyMC3-HMM/badge.svg)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/AmpersandTV/pymc3-hmm/main?filepath=examples)

# PyMC3 HMM

Hidden Markov models in [PyMC3](https://github.com/pymc-devs/pymc3).

### Features
- Fully implemented PyMC3 `Distribution` classes for HMM state sequences (`DiscreteMarkovChain`) and mixtures that are driven by them (`SwitchingProcess`)
- A forward-filtering backward-sampling (FFBS) implementation (`FFBSStep`) that works with NUTS&mdash;or any other PyMC3 sampler
- A conjugate Dirichlet transition matrix sampler (`TransMatConjugateStep`)
- Support for time-varying transition matrices in the FFBS sampler and all the relevant `Distribution` classes

To use these distributions and step methods in your PyMC3 models, simply import them from the `pymc3_hmm` package.

See the [examples directory](https://nbviewer.jupyter.org/github/AmpersandTV/pymc3-hmm/tree/main/examples/) for demonstrations of the aforementioned features.  You can also use [Binder](https://mybinder.org/v2/gh/AmpersandTV/pymc3-hmm/main?filepath=examples) to run the examples yourself.

## Installation

Currently, the package can be installed via `pip` directly from GitHub
```shell
$ pip install git+https://github.com/AmpersandTV/pymc3-hmm
```

## Development

First, pull in the source from GitHub:

```python
$ git clone git@github.com:AmpersandTV/pymc3-hmm.git
```

Next, you can run `make conda` or `make venv` to set up a virtual environment.

Once your virtual environment is set up, install the project, its dependencies, and the `pre-commit` hooks:

```bash
$ pip install -r requirements.txt
$ pre-commit install --install-hooks
```



After making changes, be sure to run `make black` in order to automatically format the code and then `make check` to run the linters and tests.

## License

[Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0)