neuton

#!/bin/bash

HOST=example.com
FLAG=/tmp/host_is_up
SLEEP=60
RETRIES=3
RETRY_SLEEP=10
MSG_PREFIX="example.com is"
TG_TOKEN=
TG_CHAT_ID=

neuton

"""some decorators for methods of classes

	>>> class A:
	... 	"test class"
	... 	@(cached & dynamic(int))
	... 	def square(self, x=1):
	... 		"docstring"
	... 		print('computed!')
	... 		return x**2
	... 	@dynamic_array

neuton

#!/bin/sh
[ -z "$TG_TOKEN" ] && { echo "TG_TOKEN not set"; exit 1; }
[ -z "$TG_CHAT_ID" ] && { echo "TG_CHAT_ID not set"; exit 1; }
while IFS= read -r stdin; do
  # printf '%s\n' "$stdin"
  curl -s -d chat_id="$TG_CHAT_ID" --data-urlencode text="$stdin" "https://api.telegram.org/bot$TG_TOKEN/sendMessage"
done

neuton

#!/usr/bin/env python3
# coding: utf8

import time, glob, csv, os, logging, random, sys, requests, functools, io
from datetime import datetime, timedelta
from sqlitedict import SqliteDict
from bs4 import BeautifulSoup

prefix = 'https://www.rheinhessen-sparkasse.de'
target = '/en/home/onlinebanking/umsaetze/umsaetze.html'

neuton

#!/usr/bin/env python3
import numpy as np
from scipy.sparse import diags, linalg
import sympy as sp
from scipy import integrate
import matplotlib.pyplot as plt

# nucleus charge:
Z = 2

neuton

#!/usr/bin/env python3
import numpy as np
from scipy.sparse import diags, linalg
import matplotlib.pyplot as plt

# solving for function values excluding boundaries:
x = np.linspace(-.5, .5, 42)[1:-1]

# imposing psi=0 boundary conditions, aka infinite walls:
laplace = diags([1, -2, 1], [-1, 0, 1], shape=[len(x)]*2) / (x[1] - x[0])**2

neuton

#!/usr/bin/env python3
import numpy as np
from numpy import cos, sin, pi, exp
from functools import lru_cache


nt = 500 # number of timesteps of the animation per (default) period of the oscillation
nx = 200 # number of points to evaluate the function at for each frame

neuton

"""
parallel execution function decorator (with quite large overhead)

>>> @parallel(reduction=sum)
... def f(array):
...     return sum(array)
>>> f(range(1, 9))
36

>>> @parallel

neuton

"""Dynamic values (hack)

	Dynamic float value:
	>>> f = ffloat(lambda x=1.0, y=2.0: x**y)
	>>> f
	1.0
	>>> f(x=2, y=3)
	8.0
	>>> f
	1.0

neuton

import numpy as np

class ClassWraps(type):	# metaclass
	"""kinda like functools.wraps decorator, but a metaclass and specifically for descriptor-decorator classes,
	just to retain the documentation of the decorated methods inside a class"""
	def __new__(cls, clsname, parents, attrs):
		def copy_attr(attr):	# closure
			return property(lambda self: getattr(self._method, attr))
		for attr in ['__name__', '__doc__', '__module__', '__annotations__']:	# `__qualname__` won't work like this...
			attrs[attr] = copy_attr(attr)