townie

# select the movie Troll 2
SELECT title FROM movies WHERE title LIKE '%Troll 2%';

#select the year that Troll 2 was made in
SELECT year FROM movies WHERE title LIKE '%Troll 2%';

#select all the movies with a rating above 90
SELECT title FROM movies WHERE rating > 90;

#select all the movies that came out in 1996

townie

string = ['12 oz pepper' , 'One can of tomatoes' ] 

class LineItem
	attr_accessor :a,:u,:i
	def initialize(a, u, i)
		@a= a
		@u = u
		@i = i
	end
end

townie

class ChildOf
  include Neo4j::ActiveRel

  from_class GoogleDriveItem
  to_class GoogleDriveItem
  type 'child_of'

  property :since, type: Integer

  validates_presence_of :since

townie

ds_bos_mysql_tutorial_Keith_and_Pam

What customers are from the UK
What is the name of the customer who has the most orders?
What supplier has the highest average product price?
What category has the most orders?

5. What employee made the most sales (by number of sales)?
** 6. What employee made the most sales (by value of sales)?

townie

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

townie

import os
import hashlib
from sets import Set

hash_set = Set([])
for dirpath, dir, files in os.walk("."):
    files

hasher = hashlib.md5()
for file in files:

townie

    # This is designed to be a dummy email that will satisfy our SSO's requirement
    # for an email, yet still be canonical to the Datto partner
    def self.convert_username_to_email(username)
      "#{username}@datto.zzz"
    end

townie

#!/usr/bin/python

# csv_parser.py - read csv check if shit is present
# Usage:
# python csv_parser.py <file.csv>
# CONFIGURE THESE 2 value
# postion_of_cig = 2 
# value_of_cig_in_string = '1'
#
#

townie

This face-boxer.py script is more-or-less the same code that you'll find in the OpenCV tutorial: Face Detection using Haar Cascades. For another variation, with more explanation, check out RealPython's tutorial.

Usage

The face-boxer.py script is designed to be run from the command-line. It has two required arugments:

1. The path to a XML file containing a Haar-cascade of visual features. In this example, it will be the features that make up a face.
2. The path to an image file that you want to perform face-detection on. You can pass in more than one image file as space-separated arguments.

townie

String info = 'Starting Program';

// SOQL query to load data into object(s)

// Load ALL books into the list of books
List<Book__c> books = [SELECT  Price__c, Name From Book__c]; 

// Load only 1 book into a single book object
Book__c book = [SELECT  Price__c, Name From Book__c limit 1];