semvec/pypi-packages huggingface dataset:
beiboot 1.4.3
Getdeck Beiboot client project.
Requires Python: >=3.9,<4.0
Keywords: Kubernetes,Development,Cloud-native

<p align="center">
  <img src="https://github.com/Getdeck/beiboot/raw/main/docs/static/img/logo.png" alt="Gefyra Logo"/>
</p>

# Getdeck Beiboot
_Getdeck Beiboot_ (or just Beiboot for brevity) is a Kubernetes-in-Kubernetes solution. It was born from the idea to 
provide Getdeck users a simple yet flexible solution to spin up **hybrid cloud development** infrastructure. This is 
useful for Kubernetes development workloads which grew too large to run on a development machine (or with pony workloads 
on MacOS and Windows machines). 

# Beiboot Client
The Beiboot client is a Python API to manage Beiboot clusters. It can set up and tear down Kubernetes instances
as well as establish connections.
ignf_gpf_api 0.1.10
Python API to simplify the use of the GPF HTTPS API.
Requires Python: >=3.8

# API Python pour la Géoplateforme

## Installation

Installez le module via pip :

```sh
pip install ignf_gpf_api
```

Vous pouvez ensuite l'[utiliser comme exécutable](docs/comme-executable.md) ou l'[importer dans vos scripts Python](docs/comme-module.md).

## Développement

Si vous souhaitez participer au développement du projet, consultez le [document détaillant comment procéder](docs/development.md).
KKMeans-JO 0.1.0
An implementation of the Kernel k-means algorithm for a bachelorthesis.

# kkmeans

Implementation of the Kernel k-means clustering algorithm for multiple dimensions (including as well one-dimensional data) in Python. The results are visualized in plots and measured with quality metrics (e.g. Silhouette Coefficient). The algorithm can be used as a framework.

https://sites.google.com/site/dataclusteringalgorithms/kernel-k-means-clustering-algorithm

The related bachelor thesis can be found here: https://www.overleaf.com/read/shnzrthjgqtw (read only) or as an exported .pdf here [Bachelor_Thesis\_\_\_\_Kernel_k_means_clustering_framework_in_Python.pdf](./Bachelor_Thesis____Kernel_k_means_clustering_framework_in_Python.pdf)

## Local Development

The following commands assume you run on a Linux or Mac, for Windows instructions take a look at the official [documentations](https://docs.python.org/3/library/venv.html).

- (optional) Create a venv `python3 -m venv .venv`
- (optional) Active venv `source .venv/bin/activate`
- (optional) Update pip `pip install --upgrade pip`
- Install all required packages `pip install -r requirements.txt`

## Test

Testing is set up using `pytest`. Run all tests running the command `pytest` in the root directory. For detailed description on pytest see: [Full pytest documentation](https://pytest.org/en/7.3.x/contents.html)

## Examples

Take a look at the examples folder to see benchmarking and plotted examples of the algorithm in action. The playground notebook should give you a comprehensive overview of the evaluation of the algorithm. It can be run after [installing jupyter](https://jupyter-org.translate.goog/install?_x_tr_sl=en&_x_tr_tl=de&_x_tr_hl=de&_x_tr_pto=sc) and running `jupyter notebook` from this folder.

## Installation

The package can be installed directly from this repository using `pip install git+ssh://git@git01lab.cs.univie.ac.at/osterj97/oster-bachelor-thesis.git`.
open-aea-flashbots 1.3.0
web3-flashbots.py
Requires Python: >=3.9,<4.0

This library works by injecting flashbots as a new module in the Web3.py instance, which allows submitting "bundles" of transactions directly to miners. This is done by also creating a middleware which captures calls to `eth_sendBundle` and `eth_callBundle`, and sends them to an RPC endpoint which you have specified, which corresponds to `mev-geth`.

To apply correct headers we use the `flashbot` method which injects the correct header on POST.

## Quickstart

```python
from eth_account.signers.local import LocalAccount
from web3 import Web3, HTTPProvider
from flashbots import flashbot
from eth_account.account import Account
import os

ETH_ACCOUNT_SIGNATURE: LocalAccount = Account.from_key(os.environ.get("ETH_SIGNATURE_KEY"))


w3 = Web3(HTTPProvider("http://localhost:8545"))
flashbot(w3, ETH_ACCOUNT_SIGNATURE)
```

Now the `w3.flashbots.sendBundle` method should be available to you. Look in [examples/simple.py](./examples/simple.py) for usage examples.

### Goerli

To use goerli, add the goerli relay RPC to the `flashbot` function arguments.

```python
flashbot(w3, ETH_ACCOUNT_SIGNATURE, "https://relay-goerli.flashbots.net")
```

## Development and testing

Install [poetry](https://python-poetry.org/)

Poetry will automatically fix your venv and all packages needed.

```sh
poetry install
```

Tips: PyCharm has a poetry plugin

## Simple Goerli Example

See [examples/simple.py](./examples/simple.py) for environment variable definitions.

```sh
poetry shell
ETH_SENDER_KEY=<sender_private_key> \nPROVIDER_URL=https://eth-goerli.alchemyapi.io/v2/<alchemy_key> \nETH_SIGNER_KEY=<signer_private_key> \npython examples/simple.py
```

## Linting

It's advisable to run black with default rules for linting

```sh
sudo pip install black # Black should be installed with a global entrypoint
black .
```