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There are no example programs for chapter 3, but there is a text file: download chapter3.zip.
If you do happen to discover that you care about such things as floating-point accuracy and the loss of precision caused by computer representation of floating-point numbers, then by all means check out Donald Knuth’s The Art of Computer Programming, particularly Volume 2, Seminumerical Algorithms, chapter 4. It includes lots of history.
If the topic of large numbers like the googol interests you, here are a few web sites to investigate. Some of the algorithms given are amenable to implementation in Python. You can find some of them at this book’s web site.
1. Large
Finite and Infinite Numbers: http://www.sci.wsu.edu/math/faculty/hudelson/moser.html
2. How
Much is a Gazillion?: http://www.straightdope.com/mailbag/mgazilli.html
3. How
to Get a Googolplex: http://www.informatik.uni-frankfurt.de/~fp/Tools/GetAGoogol.html
4.
Names of large and small numbers:
http://www.uni-bonn.de/~manfear/numbers_names.php
5. Googolplex:
http://www.informatik.uni-frankfurt.de/~fp/Tools/Googool.html (best)
6.
Ridiculously Enhanced Pi Page: http://www.exploratorium.edu/learning_studio/pi/
7. Mayan
Time Periods and Period Glyphs: http://www.pauahtun.org/Calendar/calglyph.html
Find out how big a number it takes to crash Python. How big must a number be to crash your computer? (Back up all your files first.)
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