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As described earlier, Point A is a crucial slide on which you need to make sure that your audience feels emotionally connected with the challenge they face. To make sure that is the case, when you present the Point A slide, ask your audience, What are some of the problems you see that stand in our way Then, if you have a Tablet PC, write the responses directly on the screen, such as long hours, unfocused meetings, or too much e-mail, as shown on the lower left in Figure 9-8. This shifts the dynamic of the presentation because you are not telling your team what their problems are; rather, they are telling you. Instead of risking that they will be alienated by feeling that you know it all, you give your audience a feeling of ownership. When you advance to the Point B slide (lower right), you can af rm, Yes, those are all valid problems, and we need to overcome them in order to reach the nish line.

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0.090000 (

0.455168)

Although you opened the oor to the audience on the Point A slide, you also know from your research and your experience as a project manager that you need to cover the primary obstacles de ned as the three Key Points you write on the story template, shown in Figure 9-9.

The columns, in order, represent the amount of user CPU time, system CPU time, total CPU, and real time taken. In this case, although it took nine-hundredths of a second of CPU time to send 10,000 periods to the screen or terminal, it took almost half a second for them to finish being printed to the screen among all the other things the computer was doing. Because measure accepts code blocks, you can make it as elaborate as you wish:

The programs we ve written so far have been pretty small, but if you want to make something bigger, you ll soon run into trouble. Consider what happens if you have written some code in one place and need to use it in another place as well. For example, let s say you wrote a snippet of code that computed some Fibonacci numbers (a series of numbers in which each number is the sum of the two previous ones): fibs = [0, 1] for i in range(8): fibs.append(fibs[-2] + fibs[-1]) After running this, fibs contains the first ten Fibonacci numbers: >>> fibs [0, 1, 1, 2, 3, 5, 8, 13, 21, 34] This is all right if what you want is to calculate the first ten Fibonacci numbers once. You could even change the for loop to work with a dynamic range, with the length of the resulting sequence supplied by the user: fibs = [0, 1] num = input('How many Fibonacci numbers do you want ') for i in range(num-2): fibs.append(fibs[-2] + fibs[-1]) print fibs

require 'benchmark' iterations = 1000000 b = Benchmark.measure do for i in 1..iterations do x = i end end c = Benchmark.measure do iterations.times do |i| x = i end end

9

In this example, you benchmark two different ways of counting from one to one million. The results might look like this:

0.800000 0.890000

Note Remember that you can use raw_input if you want to read in a plain string. In this case, you would

Carry forward the race motif to your Call to Action sketch, shown on the upper left in Figure 9-10, and sketch the numbers 1, 2, and 3 on each hurdle. Carry through the numbering on each Key Point slide (upper right, lower left, and lower right) to indicate which hurdle in the sequence you are covering in that section of the presentation.

0.010000 0.010000

0.810000 ( 0.900000 (

9

0.949338) 1.033589)

These results show little difference, except that slightly more user CPU time is used when using the times method rather than using for. You can use this same technique to test different ways of calculating the same answers in your code, and optimize your code to use the fastest methods. Benchmark also includes a way to make completing multiple tests more convenient. You can rewrite the preceding benchmarking scenario like this:

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