| """ | |
| Solves the Knapsack overflow problem. | |
| In this problem, we attempt to fill a Knapsack with items. | |
| The constraints: | |
| - The Knapsack may not underflow (i.e. the Knapsack must have no space left) | |
| - The Knapsack may overflow | |
| - The value of items should be minimized | |
| - The quantity should be minimized |
| import random | |
| X_Y = [(2, 4), (3, 6), (4, 9), (5, 10), (6, 12), (7, 15), (8,17), (9,20)] | |
| w = [1, 2, 3, 4] | |
| a = 0.0001 | |
| iterations = 15000 | |
| h = lambda x: w[0] * x**3 + w[1] * x**2 + w[2]*x + w[3] | |
| l = lambda x, y: (h(x) - y)**2 | |
| dl = lambda x, y, w_: 2.0 * (h(x) - y) * w_ |
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| rm -r ~/Library/Application\ Support/Google | |
| rm -r /Library/Application\ Support/Google | |
| rm -r ~/Library/Caches/com.google.* | |
| rm -r ~/Library/Caches/Google | |
| rm -r ~/Library/Google | |
| rm -r /Library/Google |
| """ | |
| Simple implementation of the Caesar cipher that works for the English alphabet | |
| """ | |
| alphabet = [chr(letter) for letter in range(97, 123)] | |
| def caesar_cipher(text, key): | |
| """ | |
| Enciphers/deciphers a text. | |
| @param text: to encipher/decipher |
| # /bin/bash | |
| # Setup Cloudwatch config for Apache2 logs | |
| ERROR_LOGS=( $( ls /var/log/apache2/*error.log ) ) | |
| ACCESS_LOGS=( $( ls /var/log/apache2/*access.log ) ) | |
| CONFIG_PATH="/opt/aws/amazon-cloudwatch-agent/etc/amazon-cloudwatch-agent.json" | |
| CONFIG="{\"logs\":{ \"logs_collected\": { \"files\": { \"collect_list\": [" | |
| LOGS=(${ERROR_LOGS[@]} ${ACCESS_LOGS[@]}) |
| # !/bin/bash | |
| # Source http://blog.dscpl.com.au/2015/06/installing-custom-python-version-into.html | |
| PYTHON_VERSION="3.6" | |
| sudo apt-get install apache2-dev -y | |
| cd /tmp | |
| git clone https://github.com/python/cpython.git | |
| cd cpython | |
| git checkout "$PYTHON_VERSION" |
| package main | |
| import ( | |
| "os" | |
| "math" | |
| "image" | |
| "flag" | |
| "image/png" | |
| "image/color" | |
| ) |
| """ | |
| A simple implementation of a n-gram (2-gram) | |
| Markov model written for Python 3.6+ | |
| """ | |
| import re | |
| import random | |
| from typing import List | |
| from collections import defaultdict |
| FROM python:3.6-alpine | |
| RUN pip install gunicorn | |
| COPY . /app | |
| WORKDIR /app | |
| RUN python setup.py develop | |
| VOLUME ['/conf'] |