Amazon introduced the ability to trade-in previously owned textbooks in exchange for Amazon gift cards. With an opportunity to "buy low-sell high", Brandon leveraged Python to automate many facets of simple workflows and operate at scale. This talk focuses how to enslave the Machine and put it to work for you with a full teardown of Brandon's automated Amazon adventure for fun and profit.

1. Arbitrage on
Amazon
Exploiting the Textbook
Trade-ins with Python
@blorenz
Brandon Lorenz
Saturday, July 27, 13

2. Why?
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3. This.
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4. From.
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5. @blorenz
Brandon Lorenz
★ Pythonista of two years
★ Djangonauting since 1.3
★ Web devving since `96
★ SSI => Perl => PHP => Python
Hi, friends.
You should follow me
[now!] on Twitter.
Why?
High tweet rate of
Python relevance!
Saturday, July 27, 13

6. Observing
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7. Amazon Trade-Ins
http://www.amazon.com/s/ref=nb_sb_noss?
url=search-alias%3Dtextbooks-tradein
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8. Amazon Trade-Ins
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9. Amazon Trade-Ins
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10. Amazon Trade-Ins
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11. Amazon Trade-Ins
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12. Amazon Trade-Ins
- >0if
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13. Amazon Trade-Ins
win()
pass
else:
- >0:if
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14. Analyzing
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15. we’re here to help.
Introduction to Tools
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16. Chrome Web Inspector
• Inspect the DOM (Document Object Model)
• Test selectors
Saturday, July 27, 13

17. requests 1.2.3
What it is:
Simple-to-use HTTP abstraction
How we use it:
Requesting content to parse
Saturday, July 27, 13

18. pyquery 1.2.4
What it is:
jQuery-like abstraction of lxml
How we use it:
Traversing and extracting content
Saturday, July 27, 13

19. django 1.6b1
What it is:
Full-featured Python web-framework
How we use it:
Querying and rendering the data
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20. Finding our Entry Point
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21. Exploring the Interface
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22. Exploring the Interface
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23. Exploring the Interface
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24. Exploring the Interface
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25. Exploring the Interface
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26. Looking for Patterns
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27. Looking for Patterns
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28. Looking for Patterns
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29. Looking for Patterns
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30. Looking for Patterns
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31. Looking for Patterns
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32. Looking for Patterns
URL Pattern!
http://www.amazon.com/gp/offer-listing/
SOME_CHANGING_VALUE/ref=dp_olp_used?
ie=UTF8&condition=used
The value of interest represents the
Amazon product code.
We can programmatically create valid
URLs based off the product code.
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33. Implementation
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34. Code. Finally.
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35. Code. Finally.
Our data representation
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36. Code. Finally.
Hooray, requests!
(thx kenneth.)
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37. Code. Finally.
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38. Code. Finally.
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39. Code. Finally.
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40. Code. Finally.
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41. Code. Finally.
Easy, admin.
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42. there will be problems.
Damnit.
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43. Too slow.
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44. Celery and RabbitMQ
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45. Oops. Data too fast.
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46. MySQL => MongoDB
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47. MySQL => MongoDB
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48. Amazon headfakes.
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49. Huh?
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50. Clever Girl.
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51. Proxified Success!
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52. Used Book Salesman.
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53. Trickiness
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54. Trickiness
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55. Deceit
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56. ... More Problems
omitted.
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57. what does it look like?
Succeeding
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58. Good deal!
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59. Good deal!
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60. Good deal!
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61. Good deal!
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62. Dashboard to Deals.
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63. • Purchased and processed over $3,085.51 in
books.
• Redeemed over $2,870.33 in purchases.
• $100 out-of-pocket initial investment.
• ~3-4 month activity window.
• Maintained and scraped 1.6 million books/day.
The Breakdown
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64. may the deals be with you.
Want the code?
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65. On the GitHub
http://github.com/blorenz/textbook-arbitrage-redux
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66. John Caserta, from The Noun Project
compose, arrange, from The Noun Project
Michael Rowe, from
The Noun Project
Brexebrex, from The Noun Project
Image Attribution
Attribute as
The Noun Project
Saturday, July 27, 13

67. Thanks!!!!
Questions???
@blorenz
Brandon Lorenz
Saturday, July 27, 13