semvec/pypi-packages huggingface dataset:
pbgca 0.1.2a0
Physically based galaxy clustering algorithm
License: MIT

# PBGCA -  Physically based galaxy clustering algorithm

Agglomenative clustering algorithm for galaxy clusters considering physical form of galaxy's structures

Clustering algoritm's initial purpose of which was to solve galaxy clustering task. But it can be scaled to solve simillar problem of finding clusters elongated to center of coordinates grid in N-dimentional grid

### Installation
```
pip install pbgca
```

### Get started
How to multiply one number by another with this lib:

```Python
from pbgca import Clusterer as PBGCA

#Get your data
data = pd.read_csv('some_data.csv')

# Instantiate a PBGCA object
clusterer=PBGCA()

# Call fit method
clusterer.fit(data)

# Get result of clustering
result = clusterer.labels_
```


Input Example:
  3d coordinates of galaxies in form of np matrix or pandas dataframe (here units: Mpc)
  Example:

| x      | y | z    |
| ------------- | ------------- |------------- |
| 1      | 34       | 0.45   |
| -1   | 94        | -0.322      |
| ..   | ...       | ...      |
bw-util 2.0.3
A simple utility that wraps bitwarden-cli
License: MIT
Keywords: bitwarden,utility

# bitwarden-attachments-tool

> A Gui client is also available now
![image](https://user-images.githubusercontent.com/36378555/164945130-3ae45ec8-f0fd-40f2-ad27-b0343e9a9328.png)

> This repo is based on https://github.com/ckabalan/bitwarden-attachment-exporter

> Designed for personal use case but includes limited generic interfaces

> Script functions are accomplished using `Popen, Pipe` in subprocess, may introduce security vulnerabilities

# install 
```
pip install bw-util
```
> this tool requires bitwarden-cli to run

# Methods to run
## 1. in shell
```
bw-export [commands] [options]

# gui version as

bw-export-gui
```
## 2. (windows only) download release
at https://github.com/ZackaryW/bitwarden-attachments-tool/releases

# documentation

## base options
|option| description
|----|----|
pw      | password
session | sessionKey
savepath| export location
debug   | debug logging
apppath | specifies the location of bitwarden-cli

> it is also possible to set `BW_PATH` as an environment variables as a replacement to `apppath`

## commands and options table
| command / option | description
|----|-----|
login [username]    | required if user have not initialized bitwarden-cli
sync                | syncs local bitwarden vault
unlock              | unlocks the vault to obtain session
savejson            | export userdata
export              | export attachments
--dump              | will also export the appdata that contains more sensitive information
autoe               | all-in-one press to go
--

# example
## autoe
```
bw-export --pw [password] autoe
```

## login
```
bw-export --pw [password] login [username]
```

## chained
```
bw-export --pw [password] login [username] unlock sync savejson export --dump
```


# required package
click

# Author
Zackary W
aws-helper-zin 0.0.1
This repo consist of a python tool that has some AWS utility functions that are not directly available on AWS
License: MIT
Requires Python: >=3.6.1
Keywords: AWS,Cognito,amazon web service

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit) ![coverage](https://img.shields.io/badge/coverage-81%25-green)

# AWS Helper

Use `aws-helper configure` to configure the tool

# Currently Supporting

## AWS Cognito

A Querying support for AWS Cognito

- Support to Query **ALL** users instead of the standard limit of _60_
- Support to Query Users **Before** a certain UserCreationDate
- Support to Query Users **After** a certain UserCreationDate
- Support to **Save as CSV**

# Installation

`pip install aws-helper`

# Usage

```console
foo@bar:~$ aws-helper cognito --help

usage: aws-helper cognito [-h] [--user-pool-id USER_POOL_ID] [--region REGION] [--list-user-pools] [--list-users | --count] [--before BEFORE] [--after AFTER] [--save]

optional arguments:
  -h, --help            show this help message and exit
  --user-pool-id USER_POOL_ID, -p USER_POOL_ID
                        Provide User Pool ID to Fetch Users
  --region REGION, -r REGION
                        Provide AWS Region [Default: Configuration Region]
  --list-user-pools, -lu
                        List All User Pools in a given region
  --list-users, -l      list all users in aws cognito
  --count, -c           Return Count of users
  --before BEFORE, -b BEFORE
                        All users before date Date in format yyyy-mm-dd
  --after AFTER, -a AFTER
                        All users after date Date in format yyyy-mm-dd
  --save, -s            Save as a CSV file
```