semvec/pypi-packages huggingface dataset:
mednet 2.0.2
Multi-task Library to Develop Computer-Aided Tools for Medical Data Analysis
Requires Python: >=3.11

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# Multi-task Library to Develop Computer-Aided Tools for Medical Data Analysis

Framework for development and analysis of deep neural network architectures
applied to medical data (images, 2D and 3D). This package can be readily used
on a number of public datasets.  It can be extended to add more datasets, and
models.

For installation and usage instructions, check-out our documentation.
PyGHGaq 0.0.1
A package to calculate GHG emissions from aquatic ecosystems
Requires Python: >=3.12

# PyGHGaq 

This package contains different methods and properties to estimate GHG ($\text{CH}_4$ and $\text{CO}_2$) emissions and concentrations for aquatic ecosystems

## Installation
pip install pyghgaq

## Usage

```python
import pyghgaq

cw = np.random(20)
csat = np.random(20)
k = np.random(20)
flux = pyghgaq.atm_diff_flux(cw, csat, k)
```

## IMPORTANT
THIS PACKAGE IS STILL IN DEVELOPMENT
akmi-utils 0.1.9.0
Utilities for AKMI integration and instrumentation (FastAPI helpers with OpenTelemetry and Prometheus support).
Requires Python: >=3.12.8

# akmi-utils

A utility package for various functionalities including converting TOML files to YAML format, logging, and OpenTelemetry integration.

## Prerequisites

- Python 3.12 or higher
- Poetry

## Installation

1. Clone the repository:
    ```sh
    git clone https://github.com/yourusername/akmi-utils.git
    cd akmi-utils
    ```

2. Install dependencies using Poetry:
    ```sh
    poetry install
    ```

## Usage

### Converting TOML to YAML

To use the `convert_toml_to_yaml` function, follow these steps:

1. Import the function in your script:
    ```python
    from akmi_utils.convert_toml_yaml import convert_toml_to_yaml
    ```

2. Call the function with the input TOML file path and output YAML file path:
    ```python
    convert_toml_to_yaml('path/to/input.toml', 'path/to/output.yaml')
    ```

### Logging Requests

To log requests in a FastAPI application, use the `log_requests` middleware:

1. Import and add the middleware to your FastAPI app:
    ```python
    from akmi_utils.logging import log_requests

    app = FastAPI()
    app.middleware('http')(log_requests)
    ```

### OpenTelemetry Integration

To set up OpenTelemetry with FastAPI, use the `setting_otlp` function and `PrometheusMiddleware`:

1. Import and configure OpenTelemetry in your FastAPI app:
    ```python
    from akmi_utils.otel import setting_otlp, PrometheusMiddleware, metrics

    app = FastAPI()
    setting_otlp(app, app_name='your_app_name', endpoint='your_otlp_endpoint')
    app.add_middleware(PrometheusMiddleware, app_name='your_app_name')
    app.add_route('/metrics', metrics)
    ```

## Running Tests

To run the tests, use the following command:
```sh
poetry run pytest
django-jauth 3.7.3
Collection of small utilities for Django and Django REST framework projects.
Requires Python: >=3.8

django-jauth
============

Simple OAuth2 authentication client library for Django and Django REST framework projects. 
Django 3.0+ support. Unit test coverage 51%.


Features
========

* Supports simple integration both to single page apps (via postMessage) and traditional Django apps (via redirect)

* Does not require any JavaScript libraries

This is by no means comprehensive OAuth2 package but simple and serves single purpose.

## Supported / Tested OAuth2 Providers

* Facebook

* Google

## Other Features

* Supports deauthorize and delete Facebook callbacks
 

Configuration
=============

settings.JAUTH_AUTHENTICATION_SUCCESS_REDIRECT:

* Set this as URL of user home page after login. Set as None for single-page apps which open separate dialog for login (Value None causes postMessage to be called for the parent window with authentication result)

settings.JAUTH_AUTHENTICATION_ERROR_REDIRECT:

* Set this as URL of login page with querystring parameter "error" as error message. Can be None for single page apps.


Install
=======

* pip install django-jauth