Graham Duncan duncangh

Falsehoods programmers believe about time

This is a compiled list of falsehoods programmers tend to believe about working with time.

Don't re-invent a date time library yourself. If you think you understand everything about time, you're probably doing it wrong.

There are always 24 hours in a day.
February is always 28 days long.
Any 24-hour period will always begin and end in the same day (or week, or month).

	import xml.etree.ElementTree as ET
	import csv
	import datetime

	def convert_xml_to_csv(file_path):

	with open(file_path, 'rb') as fd:
	root = ET.parse(fd).getroot()

	records = []

	<link rel="stylesheet" href="http://leaverou.github.io/awesomplete/awesomplete.css">
	<script src="http://leaverou.github.io/awesomplete/awesomplete.js"></script>
	<script>
	document.addEventListener('DOMContentLoaded', () => {
	const input = document.querySelector('input.blah');
	const awesomplete = new Awesomplete(input);
	input.addEventListener("awesomplete-selectcomplete", (ev) => console.log(ev.text));
	input.addEventListener('keyup', (e) => {
	var code = (e.keyCode \|\| e.which);
	if (code === 37 \|\| code === 38 \|\| code === 39 \|\| code === 40 \|\| code === 27 \|\| code === 13) {

	# Script to convert yolo annotations to voc format

	# Sample format
	# <annotation>
	# <folder>_image_fashion</folder>
	# <filename>brooke-cagle-39574.jpg</filename>
	# <size>
	# <width>1200</width>
	# <height>800</height>
	# <depth>3</depth>

	# Code adapted from Tensorflow Object Detection Framework
	# https://github.com/tensorflow/models/blob/master/research/object_detection/object_detection_tutorial.ipynb
	# Tensorflow Object Detection Detector

	import numpy as np
	import tensorflow as tf
	import cv2
	import time

	from time import sleep

	print ("Welcome to the DCF calculator.")


	def ask_perpetuity():
	earnings = float(input("Enter last twelve months earnings: "))
	discount_rate = float(input("Enter discount rate in %: "))/100
	growth_rate = float(input("Enter future expected annual compounded growth rate in %: "))/100
	growth_period = int(input("Enter amount of future years of growth, after which earnings will flatten: "))

	'''
	Extracted and modified from django-model-logging
	It used it's own LogEntry model but since django
	has it's own LogEntry maybe someone would want to
	register in the same model instead of creating a
	new one.
	'''
	from django.contrib.admin.models import LogEntry, ADDITION, CHANGE, ContentType, DELETION
	from django.utils.translation import gettext as _

	import os

	import boto3
	from flask import Flask, render_template, request, url_for, redirect

	app = Flask(__name__)

	AWS_ACCESS_KEY_ID = os.environ['AWS_ACCESS_KEY_ID']
	AWS_SECRET_ACCESS_KEY = os.environ['AWS_SECRET_ACCESS_KEY']
	S3_BUCKET = os.environ['S3_BUCKET']