moves testing into python, appropriately or not...

W. Trevor King: I dropped Readme1.md from the original 092cecd,
because I had not been cherry-picking its history.  It looked fairly
similar to the "Building a Library of Code you Trust" section of our
current README.

Conflicts:
	python/testing/Readme1.md

diff --git a/testing/Readme.md b/python/testing/Readme.md
similarity index 89%
rename from testing/Readme.md
rename to python/testing/Readme.md
index 4cdf2e23a461e3225c2ba1e701020d20f454d8b5..562892bb2a725039f2abf9f389b793927ff337b4 100644 (file)
--- a/testing/Readme.md
+++ b/python/testing/Readme.md
@@ -543,3 +543,57 @@ p1 = np.array([0.0, 0.0])
 p2 = np.array([1.0, 1.0])
 data = np.array([[0.3, 0.6], [0.25, 0.5], [1.0, 0.75]])
 ```
+Building a Library of Code you Trust
+====================================
+
+Suppose we’re going to be dealing a lot with these animal count files,
+and doing many different kinds of analysis with them. In the
+introduction to Python lesson we wrote a function that reads these files
+but it’s stuck off in an IPython notebook. We could copy and paste it
+into a new notebook every time we want to use it but that gets tedious
+and makes it difficult to add features to the function. The ideal
+solution would be to keep the function in one spot and use it over and
+over again from many different places. Python modules to the rescue!
+
+We’re going to move beyond the IPython notebook. Most Python code is
+stored in \`.py\` files and then used in other \`.py\` files where it
+has been pulled in using an \`import\` statement. Today we’ll show you
+how to do that.
+
+Exercises
+=========
+
+Exercise 1
+----------
+
+Make a new text file called \`animals.py\`. Copy the file reading
+function from yesterday’s IPython notebook into the file and modify it
+so that it returns the columns of the file as lists (instead of printing
+certain lines).
+
+Exercise 2
+----------
+
+We’re going to make a function to calculate the mean of all the values
+in a list, but we’re going to write the tests for it first. Make a new
+text file called \`test\_animals.py\`. Make a function called
+\`test\_mean\` that runs your theoretical mean function through several
+tests.
+
+Exercise 3
+----------
+
+Write the mean function in \`animals.py\` and verify that it passes your
+tests.
+
+Exercise 4
+----------
+
+Write tests for a function that will take a file name and animal name as
+arguments, and return the average number of animals per sighting.
+
+Exercise 5
+----------
+
+Write a function that takes a file name and animal name and returns the
+average number of animals per sighting. Make sure it passes your tests.

diff --git a/testing/close_line.py b/python/testing/close_line.py
similarity index 100%
rename from testing/close_line.py
rename to python/testing/close_line.py

diff --git a/testing/evo_sol1.png b/python/testing/evo_sol1.png
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rename from testing/evo_sol1.png
rename to python/testing/evo_sol1.png

diff --git a/testing/mean.py b/python/testing/mean.py
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rename from testing/mean.py
rename to python/testing/mean.py

diff --git a/testing/test_mean.py b/python/testing/test_mean.py
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rename from testing/test_mean.py
rename to python/testing/test_mean.py

diff --git a/testing/test_prod.jpg b/python/testing/test_prod.jpg
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rename from testing/test_prod.jpg
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