semvec/pypi-packages huggingface dataset:
in-toto-attestation 0.9.3
Python bindings for the in-toto Attestation Framework
Requires Python: ~=3.7
Keywords: in-toto,security,slsa,software supply chain

# Python implementation of in-toto attestations

This package contains Python bindings for in-toto/attestation. Its contents
are autogenerated using
[protobuf definitions](https://github.com/in-toto/attestation/tree/main/protos).

For more information, see the
[in-toto Attestation Framework](https://github.com/in-toto/attestation).

## Usage

Install via `pip install in-toto-attestation`.

The Python bindings for the attestation layers and predicates are provided in
the `in_toto_attestation.v1` and `in_toto_attestation.predicates` packages,
respectively. Please note that our package names use the term "attestation"
in the _singular_.

## Testing

See the [testing docs] for info and instructions for testing this
implementation.

## Versioning

At the moment, this library is versioned <1.0 as we work towards stabilizing
the protobuf definitions and the available predicates.

[testing docs]: ../docs/testing.md#testing-the-python-bindings
ullyses-utils 3.1.0
ULLYSES utility files and scripts
Requires Python: >=3.8
Keywords: astronomy,jwst,simulations

# ullyses-utils

## About

This repository contains utility scripts and data files for use in the ULLYSES program.

## Installation

To use the utility scripts and files in this repository, simply install like so:
```
pip install ullyses-utils
```
## Usage

### Utility Scripts
This repo houses several utility scripts that are needed to creates ULLYSES HLSPs. Most are specific to this purpose, but some may be generally useful: specific functions in such scripts are described below.

**`match_aliases.match_aliases`**

Given an input target name, an attempt is made to match it to any aliases in the ULLYSES sample.
By default, this returns the matched HLSP name, which is the target name used in ULLYSES products. You may alternatively specify that the ULLYSES name (generally recognized target name, with special characters) or the SIMBAD name (target name resolvable by SIMBAD) be returned instead.

```
from match_aliases import match_aliases
match_aliases("BAT99 105")
match_aliases("BAT99 105", return_name="target_name_ullyses")
match_aliases("BAT99 105", return_name="target_name_simbad")
```

### Utility data files

To use the utility data files, the package should be imported and then relative paths can be determined from your local installation.
For example, if you wish to reference the ULLYSES target alias file, you would do so like this:
```
import os
import ullyses_utils
local_dir = ullyses_utils.__path__[0]
alias_file = os.path.join(local_dir, "data/target_metadata/pd_all_aliases.json")
```
atsphinx-color-text 0.1.1
Text color changer for Sphinx.

===================
atsphinx-color-text
===================

.. image:: https://img.shields.io/pypi/v/atsphinx-color-text.svg
   :target: https://pypi.org/project/atsphinx-color-text/

.. image:: https://github.com/atsphinx/color-text/actions/workflows/main.yml/badge.svg
   :target: https://github.com/atsphinx/color-text/actions

Text color changer for Sphinx.

Overview
========

This extension adds simple role to set style of text-color for HTML-based builders.

Getting started
===============

.. code:: console

   pip install atsphinx-color-text

.. code:: python

   extensions = [
       "atsphinx.color_text",
   ]

Usage
=====

Write your text with ``:color:`` role.

.. code:: rst

   Your title
   ==========

   sphinx-revealjs is presentation library for Pythonista using reStructuredText and :color:red:`Sphinx`.

When you generate HTML by ``sphinx-build -b html`` ,
"Sphinx" rendered as red color by CSS ( likely ``font-color: red;`` ).

Notes and ToDo
==============

I will not implements all color-names, but plan "RGB code" mode and custom name mode.
cnncc 1.1.4
A simple CNN for cell-cycle phase classification

# CNNCC: Cell-Cycle phase Classification using CNNs

> This is a student project. Please use cautiously. 

Project EPFL 2023 @ ML4Science Machine Learning Class

---

This package provide multiple ML models that can be used to make real-time inference on images.

## How to use it ?

```console
$ cnncc --model <model> --image <path/to/img.[tif, png]>
```

`model` can be one of:

- Nagao
- ResNet
- LR
  

See our report for more details.
iterative-voting-consensus 0.1.2
Implement the Iterative Voting Consensus Algorithms of the article Consensus Clustering, N. Nguyen et al.
Requires Python: >=3.11,<4.0

# Voting Consensus Algorithms 

Implementation of the Iterative Voting Consensus Algorithm and of the Iterative Probabilistic Voting Consensus Algorithm presented in the article Consensus Clustering, N. Nguyen et al. These algorithms allows to combine various clusterings to get a consensus clustering.

Package available on Pypi : 
```
pip install iterative-voting-consensus
```

An example can be found in example.py
pywarthog 0.1.2
A Python library for the Warthog API
Requires Python: >=3.10

# PyWarthog V0.1.2

## Description

PyWarthog is a Python project that does API call and others stuff to a local Warthog Node. Currently it can only be used with a local node.

## Installation

    ```bash pip install pywarthog ```	

## Usage

    ```python
    from warthog.pywarthog import Warthog

    warthog = Warthog('http://127.0.0.1:3000') 

    warthog.get_mempool()

    ```	

There is a lot of other functions but i've don't make a documentation yet. You can see the code to see what you can do with it.