| 1. compile the above code using nasm using the command : | |
| nasm -f bin boot.asm -o boot.img | |
| 2. make a bootable usb of the image file created above. |
| import sys | |
| from socket import socket, AF_INET, SOCK_DGRAM | |
| SERVER_IP = '127.0.0.1' | |
| PORT_NUMBER = 5000 | |
| SIZE = 1024 | |
| print("Test client sending packets to IP {0}, via port {1}\n".format(SERVER_IP, PORT_NUMBER)) | |
| mySocket = socket(AF_INET, SOCK_DGRAM) |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <meta charset="utf-8"> | |
| <link href="https://raw.githubusercontent.com/novus/nvd3/master/build/nv.d3.css" rel="stylesheet" type="text/css"> | |
| <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.2/d3.min.js" charset="utf-8"></script> | |
| <script src="https://raw.githubusercontent.com/novus/nvd3/master/build/nv.d3.js"></script> | |
| <style> | |
| text { |
| var eventQueue = []; | |
| var svg; | |
| var element; | |
| var drawingArea; | |
| var width; | |
| var height; | |
| var volume = 0.6; | |
| var ULTIMATE_DREAM_KILLER = false; // https://github.com/debugger22/github-audio/pull/19 | |
| var orgRepoFilterNames = []; |
#System Design Cheatsheet
Picking the right architecture = Picking the right battles + Managing trade-offs
##Basic Steps
| import os, json, subprocess | |
| file = open('pycon_*.json', 'r') | |
| video = json.loads(file.read()) | |
| for i, v in video.items(): | |
| print("Installing {} ... ".format(v)) | |
| url = "youtube-dl -ciw --no-mtime -f 18 \"" + str(i)+ "\"" | |
| os.system(url) |
This tutorial was created by Shopify for internal purposes. We've created a public version of it since we think it's useful to anyone creating a GraphQL API.
It's based on lessons learned from creating and evolving production schemas at Shopify over almost 3 years. The tutorial has evolved and will continue to change in the future so nothing is set in stone.
| def _dilate(self, img, str_img=[]): | |
| '''Expands the poindary of img | |
| ''' | |
| w, h = img.shape | |
| res = np.asarray([[0 for _ in range(h)] for _ in range(w)]) | |
| # Iterating the anchor of the structure image over the original image | |
| for i, im_row in enumerate(img): | |
| for j, im_ele in enumerate(im_row): | |
| if img[i][j]: | |
| for k in range(-1, 2): |
| import matplotlib.pyplot as plt | |
| import cv2 as cv | |
| import numpy as np | |
| import os | |
| # import math | |
| from sobel import sobel | |
| OUTPUT_DIR = "outputs/" | |
| img_name = "./hough.jpg" |
• 45-minute systems interview, focus on responding to real world problems with an unhealthy service, such as a web server or database. The interview will start off at a high level troubleshooting a likely scenario, dig deeper to find the cause and some possible solutions for it. The goal is to probe your knowledge of systems at scale and under load, so keep in mind the challenges of the Facebook environment.
• Focus on things such as tooling, memory management and unix process lifecycle.
More specifically, linux troubleshooting and debugging. Understanding things like memory, io, cpu, shell, memory etc. would be pretty helpful. Knowing how to actually write a unix shell would also be a good idea. What tools might you use to debug something? On another note, this interview will likely push your boundaries of what you know (and how to implement it).
Interview is all about taking an ambiguous question of how you might build a system and letting