wulymammoth

#!/usr/bin/env python
"""
Very simple HTTP server in python.

Usage::
    ./dummy-web-server.py [<port>]

Send a GET request::
    curl http://localhost

wulymammoth

Domain-driven Design (DDD)

Context mapping

Exercise to help us discover all the concepts living in our organization, and our systems

Get everyone in a room and discover the...

• Nouns - entities
• Verbs - events

wulymammoth

def next_permutation(nums):
    '''
    brute force:
    - generate all permutations, loop and find the matching, return the next
    - time: O(N^2 * N!) + O(N) [printing/string/char concatenation is the N^2]

    procedure:
    1. find largest increasing suffix
    2. get pivot
    3. find pivot's right-most successor in suffix

wulymammoth

Open iTerm.
Go to iTerm > Preferences... > Profiles > Keys
Under Profile Shortcut Keys, click the + sign.
Type your key shortcut (option-b, option-f, option-d, option-left, etc.)
For Action, choose Send Escape Sequence.
Write b, d or f in the input field.

wulymammoth

#0: Given an input, accounts, write a function to produce the given output. Feel free to ask questions

accounts = [
  ["John", "[email protected]", "[email protected]"],
  ["John", "[email protected]"],
  ["John", "[email protected]", "[email protected]"],
  ["Mary", "[email protected]"]
]

Output: [

wulymammoth

import random
random.seed()
hash = random.getrandbits(128)

print "hash value: %016x" % hash

wulymammoth

from collections import deque

class TrieNode:
    def __init__(self, char):
        self.char = char
        self.is_word = False
        self.children = {}

class Trie:
    def __init__(self):

wulymammoth

from heapq import *
from collections import *

def djikstra(graph, start, end):
    """
    algo:
    - bfs with PQ
    - track total weight from start to a given vertex
      - initialize a table where each weight is infinite, except for the starting vertex (w = 0)
      - keep updating the total weight if we encounter a path that is smaller in weight

wulymammoth

from collections import defaultdict
from heapq import *

def dijkstra(edges, f, t):
    g = defaultdict(list)
    for l,r,c in edges:
        g[l].append((c,r))

    q, seen, mins = [(0,f,())], set(), {f: 0}
    while q:

wulymammoth

Latency Comparison Numbers (~2012)
----------------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD