Kevin Zehnder k-zehnder

Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.

General rules

Follow standard conventions.
Keep it simple stupid. Simpler is always better. Reduce complexity as much as possible.
Boy scout rule. Leave the campground cleaner than you found it.
Always find root cause. Always look for the root cause of a problem.

Design rules

System Design Cheatsheet

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

Basic Steps

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?

	import datetime
	from flask import Flask, Response
	from kafka import KafkaConsumer

	# Fire up the Kafka Consumer
	topic = "distributed-video1"

	consumer = KafkaConsumer(
	topic,
	bootstrap_servers=['localhost:9092'])

	# List unique values in a DataFrame column
	df['Column Name'].unique() # Note, `NaN` is included as a unique value. If you just want the number, use `nunique()` which stands
	# for 'number of unique values'; By default, it excludes `NaN`. `.nunique(dropna=False)` will include `NaN` in the count of unique values.

	# To extract a specific column (subset the dataframe), you can use [ ] (brackets) or attribute notation.
	df.height
	df['height']
	# are same thing!!! (from http://www.stephaniehicks.com/learnPython/pages/pandas.html
	# -or-
	# http://www.datacarpentry.org/python-ecology-lesson/02-index-slice-subset/)

	# -- coding: utf-8 --
	"""Example Google style docstrings.

	This module demonstrates documentation as specified by the `Google Python
	Style Guide`_. Docstrings may extend over multiple lines. Sections are created
	with a section header and a colon followed by a block of indented text.

	Example:
	Examples can be given using either the ``Example`` or ``Examples``
	sections. Sections support any reStructuredText formatting, including

	from __future__ import print_function
	import requests
	import json
	import cv2

	addr = 'http://localhost:5000'
	test_url = addr + '/api/test'

	# prepare headers for http request
	content_type = 'image/jpeg'

	import * as sinon from 'sinon';
	import * as Mongoose from 'mongoose';
	import { expect } from 'chai';

	// test utility
	function areObjectIdsEqual(id1: Mongoose.Types.ObjectId \| string, id2: Mongoose.Types.ObjectId \| string) {
	let normalizedId1: Mongoose.Types.ObjectId = new Mongoose.Types.ObjectId(id1.toString());
	let normalizedId2: Mongoose.Types.ObjectId = new Mongoose.Types.ObjectId(id2.toString());
	return normalizedId1.equals(normalizedId2);
	}

	<!-- create a folder named templates, put this file into it -->
	<!DOCTYPE html>
	<title>Upload File</title>
	<h1>Photo Upload</h1>
	<form method="POST" enctype="multipart/form-data">
	{{ form.hidden_tag() }}
	{{ form.photo }}
	{% for error in form.photo.errors %}
	<span style="color: red;">{{ error }}</span>
	{% endfor %}

	## I'm working on a project using Flask to access a database and then
	## pass on query data to a client where the data will be graphed
	## in the browser.
	## I wanted to enable users to retrieve the graph data
	## in a csv file after clicking a button on the client.
	## This is a generalized version of how I did it:

	# imports other than Flask
	import csv
	from sqlalchemy import create_engine

	.*
	Dockerfile
	node_modules