ckandoth

Use apt to install the necessary packages:

sudo apt install -y slurm-wlm slurm-wlm-doc

Load file:///usr/share/doc/slurm-wlm/html/configurator.html in a browser (or file://wsl%24/Ubuntu/usr/share/doc/slurm-wlm/html/configurator.html on WSL2), and:

1. Set your machine's hostname in SlurmctldHost and NodeName.
2. Set CPUs as appropriate, and optionally Sockets, CoresPerSocket, and ThreadsPerCore. Use command lscpu to find what you have.
3. Set RealMemory to the number of megabytes you want to allocate to Slurm jobs,
4. Set StateSaveLocation to /var/spool/slurm-llnl.
5. Set ProctrackType to linuxproc because processes are less likely to escape Slurm control on a single machine config.

ssaamm

import time

import requests
from bs4 import BeautifulSoup
from twilio.rest import Client
import redis

from secrets import twilio_account_sid, token, my_number

client = Client(twilio_account_sid, token)

hisplan

usage: cwltoil [-h] [--logOff] [--logCritical] [--logError] [--logWarning]
               [--logInfo] [--logDebug] [--logLevel LOGLEVEL]
               [--logFile LOGFILE] [--rotatingLogging] [--workDir WORKDIR]
               [--stats] [--clean {always,onError,never,onSuccess}]
               [--cleanWorkDir {always,never,onSuccess,onError}]
               [--clusterStats [CLUSTERSTATS]] [--restart]
               [--batchSystem BATCHSYSTEM] [--disableHotDeployment]
               [--scale SCALE] [--mesosMaster MESOSMASTERADDRESS]
               [--parasolCommand PARASOLCOMMAND]
               [--parasolMaxBatches PARASOLMAXBATCHES] [--provisioner {aws}]

alaingoldman

import DrawerLayout from 'react-native-drawer-layout';

export default class Inside extends Component {

  openSideBar(){
    this.refs['DRAWER'].openDrawer();
  }

  render() {
    var navigationView = 

ckandoth

Ensembl's VEP (Variant Effect Predictor) is popular for how it picks a single effect per gene as detailed here, its CLIA-compliant HGVS variant format, and Sequence Ontology nomenclature for variant effects.

To follow these instructions, we'll assume you have these packaged essentials installed:

## For Debian/Ubuntu system admins ##
sudo apt-get install -y build-essential git libncurses-dev

## For RHEL/CentOS system admins ##
sudo yum groupinstall -y 'Development Tools'
sudo yum install -y git ncurses-devel

acdlite

// getComponent is a function that returns a promise for a component
// It will not be called until the first mount
function asyncComponent(getComponent) {
  return class AsyncComponent extends React.Component {
    static Component = null;
    state = { Component: AsyncComponent.Component };

    componentWillMount() {
      if (!this.state.Component) {
        getComponent().then(Component => {

nvictus

"""Run Length Encoding utilities for NumPy arrays.

Authors
-------
- Nezar Abdennur
- Anton Goloborodko

"""
from __future__ import division, print_function
import numpy as np

josh-padnick

#!/usr/bin/env bash
#
# This is an adaptation of code I wrote to download a private binary from GitHub. Such...pain.
# Why can't GitHub just offer a standardized URL you can download a release binary from and attach 
# your Github Personal Access Token as a header? 
#
# Since this code is an adaptation it hasn't been directly tested, but the code it was adapted from works
# and hopefully you can get the missing piece you're after by looking here.
#

vanvaridiksha

#Spark Assignment 3

This assignment is based on the 3rd chapter of the book - 'Advanced Big Data Analytics with Spark'. You can find a copy of the book here.

In this assignment, you will be required to build a recommendation system using Spark and MLib using a dataset published by AudioScrobbler. This data is 500MB uncompressed and can be downloaded here.

You can glance through the chapter and understand how to build the recommendation system. The chapter will walk you through Scala code;

vasanthk

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

1. Clarify and agree on the scope of the system

• User cases (description of sequences of events that, taken together, lead to a system doing something useful)
  • Who is going to use it?
  • How are they going to use it?