nickodell

 (1.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j)  (0.000000000000000000e+00+0.000000000000000000e+00j

nickodell

# 1.14.1 was benchmarked outside of SciPy's build directory
# It was done with the following command
for i in $(seq 1 7); do python3 bug-22655b.py; done
# This runs the benchmark fewer times than normal, but this is fine because 1.14.1 is very clearly faster.

nickodell

If you'd like to sign up to be notified of future SciPy releases, here's how.

1. Open our repository home page.
2. Make sure you're signed into GitHub.
3. Click Watch.
4. Click Custom.
5. Check the 'Releases' box.

nickodell

// ==UserScript==
// @name     Remove Search Pulsing
// @version  1
// @grant    none
// @match https://stackoverflow.com/*
// ==/UserScript==


(new MutationObserver(check)).observe(document, {childList: true, subtree: true});

nickodell

import numpy as np
import cv2
import scipy.ndimage
import matplotlib.pyplot as plt

img = cv2.imread('HjJto.jpg')
img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

blue = np.array((81,  93, 147)).reshape(1, 1, 3)
rmse = np.sqrt(((img_rgb - blue)**2).mean(axis=2))

nickodell

concatenated = data[['day', 'month', 'year', 'time']].astype(str).agg(' '.join, axis=1)
data['date'] = pd.to_datetime(concatenated)

nickodell

user www-data;
worker_processes auto;
pid /run/nginx/nginx.pid;  # only line changed from default
include /etc/nginx/modules-enabled/*.conf;

events {
	worker_connections 768;
	# multi_accept on;
}

nickodell

Installing Python 3.6.8 on Raspbian

As of March 2018, Raspbian does not yet include the latest Python release, Python 3.6.8 This means we will have to build it ourselves, and here is how to do it.

1. Install the required build-tools (some might already be installed on your system).

nickodell

Here's a guide about when and how to use prepared statements.

Why bother with prepared statements?

The first reason to use a prepared statement is to protect against SQL injections.

You can do this by removing all special characters, but there are times when that's not practical. (Example: you want to allow users who have apostrophes in their names to register for your website.) You can do it by escaping all of the strings that you pass into the SQL query, but it's easy to forget to sanitize a single field.

So how do you protect against SQL injection? Here is the simple way to never fall prey to SQL injection: never put a user-provided string into an SQL query, except as a parameter to a prepared statement.

nickodell

Introduction

This is a guide to install libfive. libfive is a very unfinished program that allows you to model volumes. In other words, you can give libfive a functional representation of a solid, and libfive will figure everything else out, and render the resulting mesh. Pretty cool.

Conventions used by this document: # indicates a command run by root, and $ indicates user.