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olooney / update_known_hosts.bash
Created Mar 23, 2020
Shell script to update the .ssh/known_hosts file for all users on a given machine when the host key of a target machine has changed
View update_known_hosts.bash
# for each user with a home directory
for USER in `ls /home`; do
# if the user has a known_hosts files
echo "checking /home/$USER/.ssh/known_hosts..."
if [ -f /home/$USER/.ssh/known_hosts ]; then
# remove the outdated key
olooney /
Last active Nov 20, 2019
Nginx site configuration for a secure REST API reverse proxy served on HTTPS
server {
listen 80;
# additional security
server_tokens off;
add_header X-Frame-Options "DENY";
add_header X-Content-Type-Options nosniff;
# performance
from scipy.optimize import linear_sum_assignment
import numpy as np
def maximize_trace(X):
Maximize the trace of a square matrix using only row and
column permutations. Furthermore, sort the trace
in desending order so that largest value ends
up the upper left and the smallest in the lower right.
olooney /
Created Oct 25, 2019
Python parallel worker threads with back-pressure
import os
import sys
from time import sleep
from threading import Thread
from queue import Queue
import codecs
def hard_work(x):
for n in range(100001):
x = codecs.encode(x, 'rot_13')
from typing import NamedTuple, Any, Optional
class Node(NamedTuple):
"""A single Node in a binary tree."""
value: Any
left: Node
right: Node
def count(node: Optional[Node]) -> int:
"""Count the total number of nodes in a tree rooted at this node."""
X = np.hstack([np.ones(shape=(23, 1)), np.random.normal(size=(23, 2))])
Theta = np.array([0.5, +0.1, -0.2]).reshape( (3, 1) )
Y = X @ Theta + np.random.normal(0, 0.1, size=(23, 1))
Theta_hat = np.linalg.inv(X.T @ X) @ X.T @ Y
def harmonic(x, y, n=6, epsilon=1e-3):
r = sqrt(x/y)
for a in range(1, n):
for b in range(1, n):
if abs(r - a/b) < epsilon:
return True
return False
for x in np.arange(1.6, 6.4, 0.2):
olooney /
Created Jul 11, 2018
Python 3 conversion of a Python 2 implementation of Knuth's "algorithm u" I found online
# Knuth's algorithm to partition ns into m sets.
# ns must be a list of integers
# m must be an integer less than len(ns)
# this is a generator expression
def algorithm_u(ns, m):
def visit(n, a):
olooney / sim.R
Created Jul 9, 2018 — forked from mikeguggis/sim.R
Stack Exchange
View sim.R
results <- NULL
# Generate simulated data
for ( seed in 1:30 ) {
mu = c(0,-1+seed/10)
Sigma = matrix(c(1.5,-.5,-.5,.7),2,2)
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