An Introduction to Python – Part IV

1. An Introduction to Python – Part IV Dr. Nancy Warter-Perez

2. Overview • Creating 2-D Lists (already covered) • Scopes • Modules • Doc Strings • Debugging • Project Development Time Introduction to Python – Part IV

3. To create a 2-D list L, with C columns and R rows initialized to 0: L = [[]] #empty 2-Dlist L = [[0 for col in range(C)] for row in range(R)] To create a 2-D list initialized to 0 based on the length of strings c and r: L = [[0 for col in c] for row in r] To assign the value 5 to the element at the 2nd row and 3rd column of L L[2][3] = 5 Creating 2-D Lists Introduction to Python – Part IV

4. Mutable and Immutable Objects • Immutable objects can not be changed in place. They must be reassigned. • Immutable objects: simple variables, tuples, strings • Ex: >>>T = (1,2,3) >>>T [2] = 5 # error! >>>T = T[0:2] + (5,) # (1,2,5) • Note: there are no constant variables in python Introduction to Python – Part IV

5. Mutable objects • Mutable objects such as lists and dictionaries can be changed in place • Ex: >>> L = [1, 2, 3] >>> L[2] = 88 # [1,2,88] >>> D = {‘a’:1, ‘b’:2} >>> D[‘c’] = 3 # {‘a’:1,’b’:2,’c’:3} Introduction to Python – Part IV

6. Functions are passed by assignment –Call by value or call by reference? • Immutable objects are similar to call by value. • Call by value will pass a copy of a variable a the parameter and thus, will not change the variable • Example: def fn(x): x = x + 1 y = 5 fn(y) print y --- prints 5 Introduction to Python – Part IV

7. Functions are passed by assignment –Call by value or call by reference? • Mutable objects are similar to call by reference • Call by reference – will pass the location of the parameter and thus, will change the parameter • Example: def fn(x): x[1] = 77 y = [1, 2, 3] fn(y) print y --- prints [1, 77, 3] Introduction to Python – Part IV

8. Scopes • Scopes divine the “visibility” of a variable • Variables defined outside of a function are visible to all of the functions within a module (file) • Variables defined within a function are local to that function • To make a variable that is defined within a function global, use the global keyword Ex 2: x = 5 def fnc(): global x x = 2 print x, fnc() print x >>> 2 2 Ex 1: x = 5 def fnc(): x = 2 print x, fnc() print x >>> 2 5 Introduction to Python – Part IV

9. Modules • Why use? • Code reuse • System namespace partitioning (avoid name clashes) • Implementing shared services or data • How to structure a Program • One top-level file • Main control flow of program • Zero or more supplemental files known as modules • Libraries of tools Introduction to Python – Part IV

10. Modules - Import • Import – used to gain access to tools in modules Ex: contents of file b.py def spam(text): print text, 'spam' contents of file a.py import b b.spam('gumby') Introduction to Python – Part IV

11. Contents of aa.py y = 5 def x(): global y y = y + 1 def z(): global y y = y + 1 return y Contents of bb.py import aa aa.x() print aa.z() print aa.y #ref global var Output after running bb: 7 7 Using Global Variables with Modules Introduction to Python – Part IV

12. Import happens only once! • Imports load and run a module’s code only the first time • Later imports use the already loaded module object • So, if you make changes to a module that you’ve already imported, make sure to reload the module in the interactive window Ex: After making changes to module aa (previous slide) >>> reload (aa) #reload module aa Introduction to Python – Part IV

13. #comments In-file documentation The dir function Lists of attributes available on objects Docstrings:__doc__ In-file documentation attached to objects Python Documentation Sources Introduction to Python – Part IV

14. Dir and DocString Example Ex: b.py # Internal comment """Module Docstring comment """ def fn(): """Function Docstring comment """ >>> import b >>> dir(b) ['__builtins__', '__doc__', '__file__', '__name__', 'fn'] >>> print b.__doc__ Module Docstring comment >>> print b.fn.__doc__ Function Doctring comment Introduction to Python – Part IV

15. Debugging • Two types of bugs • Syntax errors – “easy” to find • Logical errors – harder to find • Can be a problem in your algorithm • Can be a problem in your coding • Debugging a program is like solving a puzzle • Must first understand what your program is supposed to do • Logically trace what is happening in your program • What do you expect to happen versus what happened • Follow the flow of data • Follow the flow of control Introduction to Python – Part IV

16. Debugging Tools/Methods • Can use print statements to “manually” debug • Can use debugger in PythonWin • In Class Example Introduction to Python – Part IV

17. Workshop • Separate your LCS functions into a different module • Import the module and call the functions from within your while loop (continually prompting the user if they want to continue) • Trace through your program • Use print statements to view the score and trace back matrices as they are formed • Using the debugger to view the score and trace back matrices Introduction to Python – Part IV