Eugen Hoppe eugen-hoppe

echo $(htpasswd -nB USERNAME) | sed -e s/\$/\$\$/g

How to create a new user (Linux) with SSH Public Key?

To create new users and add their public keys on an Ubuntu server, follow these steps:

First, open a terminal and enter the following command to create a new user. Replace newuser with your desired username.

sudo adduser newuser

	import matplotlib.pyplot as plt
	import pandas as pd
	import seaborn as sns
	import phik # pip install phik==0.12.4


	# see: https://phik.readthedocs.io/en/latest/


	def correlation_mtx(df_: pd.DataFrame, *columns: list[str], title: str = "") -> None:

	"""
	Database Utility Module
	=======================

	This module provides a lightweight database configuration and query execution setup
	using SQLAlchemy and Pandas. It facilitates database interactions with SQLite
	and offers utilities for managing SQL queries in a structured manner.

	Features:
	---------

	from dataclasses import dataclass
	import pandas as pd
	import matplotlib.pyplot as plt
	import matplotlib.axes as type_ax


	@dataclass
	class Plot:
	"""src: https://gist.github.com/eugen-hoppe/400e47930f733229eaf773f070c81e62"""
	df: pd.DataFrame # . Cache pd.Dataframe for plot

	import shutil
	import zipfile
	import os

	from google.colab import drive


	def copy_and_unzip_from_drive(drive_path, local_path, drive_mount = "/content/drive"):
	"""docs: https://gist.github.com/eugen-hoppe/93ece48e0b224b853698249502aa9ba9"""
	drive.mount(drive_mount)

	def create_sample_csv(path: str, name: str, rows: int, shuffle: int = 0) -> None:
	path_file_csv = f'{path}/' + name.removesuffix('.csv') + '.csv'
	input_df = pd.read_csv(path_file_csv)
	if bool(shuffle):
	input_df.sample(frac=1, random_state=shuffle)
	output_df = input_df.head(rows)
	output_df.to_csv(path_file_csv.replace('.csv', '_sample.csv'), index=False)

	import pkg_resources
	import os


	INPUT_FILE = "requirements.txt"
	OUTPUT_FILE = "requirements_.txt"
	# OUTPUT_FILE = "requirements.txt"


	def get_installed_version(package_name):

	@dataclass
	class Cat:
	ignore_steps: bool = False
	step: int = 0
	labels: pd.DataFrame \| None = None
	categories: pd.DataFrame \| None = None
	sorted_labels: pd.DataFrame \| None = None
	merged_final: pd.DataFrame \| None = None
	category_prefixes: list[str] = field(
	default_factory=lambda: ['c1', 'c2']

	from typing import Callable, Tuple, Type, Optional
	from functools import wraps


	def try_except(
	errors: Tuple[Type[Exception], ...] = (Exception,),
	raise_: Optional[Type[Exception]] = None,
	txt_: str = ""
	) -> Callable:
	"""A decorator that wraps a function to handle exceptions"""