Objects + Tests = Magic

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Better version 80 books: 6s -> 20ms tags = [0,800,2*8*95,3*8*90,4*8*80,5*8*75] def best_price(t) : t=tuple(sorted(t)) m=min(t[0],t[2]-t[1]) return tags[5]*(t[0]-m)+tags[4]*(2*m+t[1]-t[0])+ tags[3]*(t[2]-t[1]-m)+tags[2]*(t[3]-t[2])+ tags[1]*(t[4]-t[3]) def price(l) : return best_price(tuple(l.count(i) for i in range(5)))/100 “ok, j'ai une version logarithmique qui passe les tests ;P. Version python avec test, c'est linéaire par rapport au log du nombre de bouquins achetés.” - Christophe
How can one encapsulate the computation logic in an object graph to enhance maintenance?
Page 1: pictures: sxc.hu pictures: sxc.hu O
Page 4 and 5: Reference
Page 6 and 7: The problem: Selling Harry Potter b
Page 8 and 9: Pricing Policy Example B1 B1 B2 B2
Page 10 and 11: Combinatorial situation! B1 B2 B3 O
Page 12 and 13: Yes we can !
Page 14 and 15: http://bfindeiss.blogspot.fr/2013/0
Page 17 and 18: Yes we Seriously? can !
Page 19 and 20: “ Bon, j'ai réfléchi un peu à
Page 21: Complexity survival guide if (chris
Page 25 and 26: Software engineering rule of three
Page 27 and 28: SOLIDity applied to OO code • S :
Page 29 and 30: Modularisation Basket Book Discount
Page 31 and 32: Computing a price with a discount d
Page 33 and 34: https://www.youtube.com/playlist?li
Page 35 and 36: Internal implementation We don’t
Page 37 and 38: Testing Critical Cases ~ ✔
Page 40 and 41: Testing the Discount concept
Page 42 and 43: is empty => 0.0 Let discounts = {d
Page 44 and 45: Let the battle begin! Benchmarking
Page 46 and 47: Each bench is executed 10 times 20
Page 48: # Run complete. Total time: 00:40:4

Objects + Tests = Magic

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