semvec/pypi-packages huggingface dataset:
python-hbk 0.1.3
Python tool to work with .hbk bookmark files from Hex Workshop
Requires Python: >=3.11,<4.0

## How to use

```python
from python_hbk.Hbk import Hbk

my_hbk = Hbk(filepath="test.hbk")
for name, address, length in my_hbk.get_bookmarks():
    print(f"{name=}, {address=}, {length=}")

print(my_hbk.to_json())
```

## Output
```
name='Test float', address='0000016A', length=4
name='Test double', address='0000016E', length=8
name='Test string', address='00000176', length=72
name='Test float array [0]', address='00000241', length=4
...
name='Test double array [15]', address='000002C7', length=8

[
  {
    "name": "Test float",
    "address": "0000016A",
    "length": 4
  },
  {
    "name": "Test double",
    "address": "0000016E",
    "length": 8
  },
  {
    "name": "Test string",
    "address": "00000176",
    "length": 72
  },
  {
    "name": "Test float array [0]",
    "address": "00000241",
    "length": 4
  },
  ...
  {
    "name": "Test double array [15]",
    "address": "000002C7",
    "length": 8
  }
]

```
retask 1.1.0
Task Queue implementation in python using redis.
Requires Python: >=3.9

Welcome to retask
=================
retask is a python module to create distributed task
queues using Redis.

You can read the latest documentation `here <http://retask.readthedocs.org/>`_.

Release build is done via [asaman](https://pypi.org/project/asaman/) from the tarball.
pydantic-lambda-handler 0.13.2
Pydantic lambda handler modelled on FastAPI

![example workflow](https://github.com/harvey251/pydantic-lambda-handler/actions/workflows/main.yml/badge.svg) [![codecov](https://codecov.io/gh/harvey251/pydantic-lambda-handler/branch/main/graph/badge.svg?token=PX0GRFCYQE)](https://codecov.io/gh/harvey251/pydantic-lambda-handler) ![pypi package](https://img.shields.io/pypi/v/pydantic-lambda-handler?color=%2334D058&label=pypi%20package)

# Vision

Aim to create an easy-to-use decorator on a lambda for quick development of apis on AWS lambda using AWS Gateway.

Inspired by, and attempting to match the [Fast API](https://fastapi.tiangolo.com) api.

Currently, I'm working through the first steps to hit the basics.

This is very much at the beginning of the project, so I could do with all the help I can get :D

## MUST HAVE
* creates open api schema

API Gateway Lambda proxy integration
https://docs.aws.amazon.com/apigateway/latest/developerguide/set-up-lambda-proxy-integrations.html#api-gateway-simple-proxy-for-lambda-input-format

https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway-tutorial.html

```commandline
pip install --target ./demo_app ../.
```
funEnsemble 0.1.0
Ensemble Clustering for Functional Data
Requires Python: >=3.7

# funEnsemble

Clustering Functional Data Using Ensemble Clustering

## Instructions

1. Install:

```
pip install funEnsemble
```

2. Call the data decomposition module

```python
import funEnsemble.functional_ensemble_clustering as ec

# Data Decomposition Step
data_smooth, mean, principal_componenets, eigen_functions = ec.functional_data_decomposition(data, eigen_dimensions, b_spline_length)

```

3. Call the ensemble clustering module

```python

# Ensemble Clustering Step
membership_matrices, labels = ec.functional_data_clustering(principal_components, K)
```