davidosomething

This is roughly the same test run in both casper and nightwatch.

oyvindholmstad

/*	
	A script to generate a Google BigQuery-complient JSON-schema from a JSON object.
	
	Make sure the JSON object is complete before generating, null values will be skipped.
	
	References:
	https://cloud.google.com/bigquery/docs/data
	https://cloud.google.com/bigquery/docs/personsDataSchema.json
	https://gist.github.com/igrigorik/83334277835625916cd6
	... and a couple of visits to StackOverflow

garystafford

For a small number of variables ('tokens'), I use a simple shell script along with a templated version of my YAML file. Here's an actual example:

files:

docker-compose-template.yml
docker-compose.yml
compose_replace.sh

run:

rsmoorthy

fw Extended Models

This hook extends the models, its definition and its behaviour.

For now, various features will get added in this hook. And we will migrate them to proper ones, as we go by.

Extended enum support

This feature extends the values of enum from other sources. Other sources could be:

simonrw

Database transactions

pymysql

• Defaults to autocommit=False

connection = pymysql.connect(user='user', db='test')
cursor = connection.cursor()
cursor.execute('insert into test (value) values (10)')

Zhaoyilunnn

Architecture

Papers

Chips

• An Energy-Efficient Configurable Lattice Cryptography Processor for the Quantum-Secure Internet of Things. ISSCC-2019
• A 28nm Bulk-CMOS 4-to-8GHz ¡2mW Cryogenic Pulse Modulator for Scalable Quantum Computing. ISSCC-2019
• A Scalable Quantum Magnetometer in 65nm CMOS with Vector-Field Detection Capability. ISSCC-2019
• A 48GHz 5.6mW Gate-Level-Pipelined Multiplier Using Single-Flux Quantum Logic. ISSCC-2019

hrldcpr

One-line Tree in Python

Using Python's built-in defaultdict we can easily define a tree data structure:

def tree(): return defaultdict(tree)

That's it!

paulkaplan

// From http://www.tannerhelland.com/4435/convert-temperature-rgb-algorithm-code/

    // Start with a temperature, in Kelvin, somewhere between 1000 and 40000.  (Other values may work,
    //  but I can't make any promises about the quality of the algorithm's estimates above 40000 K.)

    
function colorTemperatureToRGB(kelvin){

    var temp = kelvin / 100;

fchollet

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

lizthegrey

default['sshd']['sshd_config']['AuthenticationMethods'] = 'publickey,keyboard-interactive:pam'
default['sshd']['sshd_config']['ChallengeResponseAuthentication'] = 'yes'
default['sshd']['sshd_config']['PasswordAuthentication'] = 'no'