semvec/pypi-packages huggingface dataset:
gener8app 1.0
A CLI to generate bare-bone FastAPI project
Requires Python: >=3.10,<4.0

# GENER8APP

### About GENER8APP

Gener8app is a CLI tool for generating bare-bone FastAPI project.
When you run `gener8app new [project_name]`, it generates the following project structure:

    .
    ├── app/
    │   ├── __init__.py
    │   ├── config/
    │   │   ├── __init__.py
    │   │   └── config.py
    │   ├── database/
    │   │   ├── __init__.py
    │   │   └── database.py
    │   ├── models/
    │   │   ├── __init__.py
    │   │   └── models.py
    │   ├── routers/
    │   │   ├── __init__.py
    │   │   └── routes.py
    │   ├── schemas/
    │   │   ├── __init__.py
    │   │   └── schemas.py
    │   └── services/
    │   │   ├── __init__.py
    │   │   └── services.py
    │   └── statics/
    │   └── templates/
    │   └── tests/
    │   │   ├── __init__.py
    │   │   └── tests.py
    │   └── utils/
    │       ├── __init__.py
    │       └── utils.py
    ├── Dockerfile
    ├── docker-compose.yaml
    ├── [project_name]_ven
    ├── .env
    ├── .gitignore
    ├── requirements.txt
    └── README.md

### INSTALLATION

`pip install gener8app`

### COMMAND

`gener8app new [project_name]`

This command initialized an empty git repository, create a virtual environment using the python builtin `venv` by appending `_evv` to the project name, i.e `[project_name]_env`.

##### Activate the virtual environment before installing dependencies.

[view project on github](https://github.com/kenmoh/cli)
expkg 1.0.0
A sample Python project
Requires Python: >=3.7
Keywords: development,sample,setuptools

Copyright (c) 2018 The Python Packaging Authority

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
pyord 0.0.9
bitcoin jpegs
Requires Python: >=3.10,<4.0

[![pypi](https://img.shields.io/pypi/v/pyord.svg)](https://pypi.python.org/pypi/pyord)

A sandbox for working with [ord](https://github.com/casey/ord).

For now, api calls go through https://ordapi.xyz/ but an [official api is in the works](https://github.com/casey/ord/pull/1662). Will switch to that once available, or start wrapping the ord crate from python.

## Setup

Clone, `poetry install` then `pre-commit install`.

`poetry run pytest`


## Usage

All subject to change. Just exploring the api for now.

A simple example of iterating through inscriptions and printing any with plaintext content:

```python
from ord import client

for i, inscription_id in client.inscriptions(start=0, stop=100):
    inscription = client.get_content(inscription_id)
    try:
        plaintext = inscription.decode("utf-8")
        print(i, inscription_id, "plaintext content")
        print(plaintext, "\n\n")
    except UnicodeDecodeError:
        pass
```
mmkg-sgg 0.2.0
MMKG Models

# 图像场景图生成使用说明

## 1. 算法描述
该算法用于图像场景图生成(SGG)。该算法基于PyTorch框架开发，输入一张图片，算法会检测图片中人和物的交互关系，输出图像场景图。

## 2. 依赖及安装

CUDA版本: 11.3
其他依赖库的安装命令如下：

```bash
conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge
```

可使用如下命令下载安装算法包：
```bash
pip install -U mmkg-sgg
```

## 3. 使用示例及运行参数说明

**需要准备 pretrained_ckpt, labelmap_file, freq_prior 三个文件，可以通过 [mmkg-sgg](https://github.com/xu7yue/mmkg-sgg) 上所提供的链接进行下载**

```python
from mmkg_vrd import SGG

sgg = SGG(
    pretrained_ckpt='custom_io/ckpt/RX152FPN_reldn_oi_best.pth',
    labelmap_file='custom_io/ji_vrd_labelmap.json', 
    freq_prior='custom_io/vrd_frequency_prior_include_background.npy', 
)

sgg.det_and_vis(
    img_file='custom_io/imgs/1024px-Gen_Robert_E_Lee_on_Traveler_at_Gettysburg_Pa.jpg',
    save_file='custom_io/out/1024px-Gen_Robert_E_Lee_on_Traveler_at_Gettysburg_Pa.reldn_relation.jpg')

print('all done')

```
cytocluster 0.1.13
A package for clustering high-dimensional cytometry data in Python.
Requires Python: >=3.8,<4.0

<p align="center">
  <img src="https://i.imgur.com/cBdvN9o.png" height="25%" width="25%">
</p>

# CytoCluster
[![PyPi](https://img.shields.io/pypi/v/cytocluster)](https://pypi.org/project/cytocluster/)
[![Python](https://img.shields.io/pypi/pyversions/cytocluster)](https://pypi.org/project/cytocluster/)
[![Wheel](https://img.shields.io/pypi/wheel/cytocluster)](https://pypi.org/project/cytocluster/)
[![License]( https://img.shields.io/pypi/l/cytocluster)](https://opensource.org/licenses/MIT)
[![LastCommit](https://img.shields.io/github/last-commit/burtonrj/cytocluster)]()
[![CodeCov](https://img.shields.io/codecov/c/github/burtonrj/cytocluster)]()
[![GitHubActions](https://img.shields.io/github/workflow/status/burtonrj/cytocluster/CytoCluster%20Build)]()

---

## Overview

Welcome! This is CytoCluster, a package for clustering high-dimensional cytometry data in Python.
CytoCluster started as a module in the first release of <a src="https://github.com/burtonrj/CytoPy">CytoPy</a>.

CytoCluster is now a standalone package that provides functions and classes for:

* Popular clustering algorithms such as FlowSOM, Phenograph, SPADE etc.
* Plotting and visualising clustering results.
* Ensemble clustering for combining the results of many clustering algorithms into consensus clusters.

Examples of using the CytoCluster package are provided in the example notebooks (see notebooks folder in this repo).

## Installation

``
pip install cytocluster
``

---
## Release Notes

The CytoPy ecosystem is under development, see ### for details on release information.