ryanwilsonperkin

# http://www.youtube.com/watch?v=CssC-DY4lO8

git config alias.up commit
git config alias.out push
git config alias.something pull

ryanwilsonperkin

# Use as `ldapuser username` to lookup ldap record for "username"
function ldapuser {
    ldapsearch -x -H ldap://directory.uoguelph.ca -b "ou=People,o=uoguelph.ca" "uid=$1"
}

ryanwilsonperkin

def deep_get(o, keys):
  return reduce(lambda prev, current: prev.get(current, {}), keys, o) or None

ryanwilsonperkin

import random

class ShittyList(list):
  def __len__(self):
    min, max = 0, super(ShittyList, self).__len__()
    return random.randrange(min, max)

ryanwilsonperkin

// Clever
function comprehension(arr, fn) {
  return arr.reduce((obj, key) => Object.assign(obj, {[key]: fn(key)}), {});
}

// Legible
function comprehension(arr, fn) {
  const obj = {};
  for (key of arr) {
    obj[key] = fn(key);

ryanwilsonperkin

Keybase proof

I hereby claim:

• I am ryanwilsonperkin on github.
• I am ryanwilsonperkin (https://keybase.io/ryanwilsonperkin) on keybase.
• I have a public key whose fingerprint is 5664 AF96 D17B 16E8 F21B F431 FBA8 1CE4 75C6 7F0D

To claim this, I am signing this object:

ryanwilsonperkin

# Having fun with context managers
from contextlib import contextmanager

@contextmanager
def deity():
    print 'The Father'
    yield
    print 'The Holy Ghost'

god = deity()

ryanwilsonperkin

const PRODUCTION = process.env.NODE_ENV === 'production';
const HASH_MODE = PRODUCTION ? 'chunkhash' : 'hash';

module.exports = {
  output: {
    filename: `[name].[${HASH_MODE}].js`,
    chunkFilename: `[name].[${HASH_MODE}].js`,
  },
  ...
};

ryanwilsonperkin

# Regular decorator
def decorator(f):
    def wrapped(*args, **kwargs):
        print('Before')
        result = f(*args, **kwargs)
        print('After')
        return result
    return wrapped

# Regular decorator usage

ryanwilsonperkin

Profiling!

A simple way to get line profiling on your python functions.

1. pip install line_profiler
2. Decorate your function with @profile (no import needed)
3. Launch a shell with kernprof -l manage.py shell
4. Call the function you want to profile. Preferably several times! (%timeit is great for running it several times)
5. Exit the shell. You'll see a dumped file created called manage.py.lprof