semvec/pypi-packages huggingface dataset:
dfuai 0.1.5
DFUai is a Python package that uses AI to assist clinical doctors in diagnosing the severity of diabetic foot ulcers. It classifies diabetic foot severity (mild, moderate, or severe) based on eight clinical features: PAD, CRP, HbA1c, DKD, ESR, ALB, SBP, and X25OHD.
Requires Python: >=3.7

DFUai is a Python package that utilizes AI to assist clinicians in diagnosing the severity of diabetic foot (DF). By simply inputting a file with the grouped information of eight clinical features (PAD, CRP, HbA1c, DKD, ESR, ALB, SBP, and X25OHD), DFUai predicts whether the diabetic foot condition is mild/moderate or severe.

Feature Grouping Criteria:

PAD (Peripheral Artery Disease): Grouped according to clinical guidelines.
DKD (Diabetic Kidney Disease): Grouped based on clinical guidelines.
CRP (C-Reactive Protein): Grouped as 1 if greater than 16.34 mg/L, otherwise 0.
ESR (Erythrocyte Sedimentation Rate): Grouped as 1 if greater than 44.5 mm/h, otherwise 0.
ALB (Albumin): Grouped as 1 if greater than 41.55 g/L, otherwise 0.
SBP (Systolic Blood Pressure): Grouped as 1 if greater than 136.5 mmHg, otherwise 0.
X25OHD (25-Hydroxyvitamin D): Grouped as 1 if greater than 12.945 ng/mL, otherwise 0.
HbA1c (Glycated Hemoglobin): Grouped as 1 if greater than 8.05%, otherwise 0.
The input format has rows as sample names, columns as variable feature names, and the cells filled with the grouped information of the variable features.


from dfuai import dfuai
dfuai.dfuai(filepath="../test.csv", i=0)
ctfdpy 0.1.0a1
A python wrapper around the CTFd API
Requires Python: >=3.11

# CTFdPy

CTFdPy is an API wrapper for CTFd, a Capture The Flag platform.

It is designed to make it easier to interact with the CTFd API in Python to streamline the setup process for CTFs.

> [!WARNING]
>  This tool is still under development. Bugs and breaking changes should be expected.

## Getting Started

### Installation 

#### Installing from PyPI

To install from PyPI, run the following command:

```console
$ pip install -U ctfdpy
```

#### Installing from Source

> [!WARNING]
> Installing from source will pull the latest changes from the repository. This may include new features, bug fixes, or breaking changes. If you want to use a stable version, it is recommended to install from PyPI.

Git clone the repository, and pip install it

```console
$ git clone https://github.com/Jus-Codin/CTFdPy.git

$ cd ctfdpy

$ pip install -e .
```

Alternatively, you can install it directly from the repository:

```console
$ pip install -U git+https://github.com/Jus-Codin/CTFdPy.git
```

### Example Usage
TODO
docker-remote-sync 0.7.0
Utility to sync docker image between 2 docker host machines
Requires Python: ~=3.12

A utility to sync docker images between two machines while transferring only the changed layers

# Setup
### Requirements
Apart from `docker`, `rsync` is needed on both the machines.

### Installation
`pipx install docker-remote-sync` or `pip install docker-remote-sync` or `uv tool install docker-remote-sync`


# Usage
```
usage: docker-remote-sync [-h] [--port PORT] [--docker-cmd DOCKER_CMD] image_name remote remote_cache_folder

Utility to sync updated docker layers between two docker host machines

positional arguments:
  image_name            Docker image on local machine
  remote                Address of remote
  remote_cache_folder   Cache folder on remote

options:
  -h, --help            show this help message and exit
  --port PORT           Alternate ssh port on remote
  --docker-cmd DOCKER_CMD
                        Alternate docker command. Defaults to `docker`. Eg. `colima x - docker` or `podman`

○ Do not delete the cache folder on the remote machine to be able to take advantage of incremental file sync
○ Example usage: `docker-remote-sync alpine:latest remotehost "~/my_alpine_cache"`