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+====================================
+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.