functions, modules, debugging

Transcription

1 functions, modules, debugging Matt Valeriote 21 January, 2019

2 Continuation of coin counting example Before coding up a solution, first describe it at a high level and then refine it: Initialization phase initialize the variables that will be used, such as variables to hold the total amount of money, the list of coin denominations being used, and a list of the results. For each denomination d in our list: determine how many coins of denomination d are needed. update our result list with this amount. update the total amount of money left. Print out the results More CodingBat examples: CodingBat > List-2 > count_evens CodingBat > string-2 > sum13 reverse a list (not using slicing)?

3 break break is a way to get out of a while or for loop early: for i in range(0,10): if i>5: break nested for loops We can look at (e.g.) all the combinations of i and j via: for i in range(0,3): for j in range(0,3): print([i,j])

4 Loops and indices From Secret Weblog: all of the following are equivalent... i = 0 while i < mylist_length: do_something(mylist[i]) i += 1 ## or i=i+1 vs. for i in range(mylist_length): do_something(mylist[i]) vs. for element in mylist_length: do_something(element)

5 prime walk Now let s look at the prime walk program again, and consider a high level description of it.... Initialization phase initialize the variables that will be used, such as variables to hold the lists of the x and y coordinates of the points visited on the walk, the current direction of the walk, and the number of steps to take on the walk For each step of the walk: update the x and y coordinates lists with the coordinates of the next step determine if the current step number is a prime number if so change the walk direction. display the walk.

6 Functions Reference: Python tutorial section 4.6 the most important tool for structuring programs allows modularity basic definition: def function_name(args): plus indented code block inputs are called arguments. outputs are called return values when function is called, go to the function, with the arguments, run code until you hit return() (return None if you get to the end without a return) Return values most functions return values might not... side effects input/output (create a plot, write output to a file, turn on a machine,... ) changing a (mutable!) variable

7 Function arguments ## 3 ## 2 ## 3 basic arguments: unnamed, mandatory think of them as dummy variables; could be the same or different from the name in the calling environment def add_one(x): x += 1 return(x) x = 2 print(add_one(x)) print(x) z = 2 print(add_one(z)) print(z)

8 Since z is a number (immutable), it doesn t change; if you want it to change, use z=add_one(z) Changes within functions follow the standard mutability rules:

9 Compare: def no_return(x): x = [2,3,4] return(none) z = [1,2,3] no_return(z) z With: def no_return(x): x[0] = 7 return(none) z = [1,2,3] no_return(z) z optional arguments: give default values e.g. logarithm: def log(value,math.e)

10 Docstrings always say something about what your function does. (Feel free to give me a hard time in class if I don t.) provide descriptions of the arguments and the return value. We will use some features of the numpy docstring standard

11 def add_function(a, b): """ the sum of two numbers Parameters a : num b : num Returns sum : num The sum of a and b Examples >>> add_function(2, 5) 7 >>> add_function(3, -1.4) 1.6 """ sum = a + b return sum

12 Errors Types of errors syntax errors vs. logic errors matrix sum program failure modes from logic errors: obvious failure program stops with an error partway through: bad matrix sum #0 Python crashes machine crashes program never stops (infinite loop) wrong answer always vs. sometimes (obvious categories) vs. sometimes (mysterious) obvious vs. subtle

13 infinite loops: print("please enter (y)es or (n)o") reponse = input() while ((response!= "y") or (response!= "n")): print("please try again") infinite loop matrix sum operator precedence mistakes, e.g. fahrenheit = Celsius 1.8 fahrdiff = celsius_high - celsius_low * 1.8 off-by-one error ( fencepost problem )... more generally, edge or corner cases code incorrectly inside/outside loops: bad matrix sum #2 bad matrix sum #3 array index error (outside bounds)

14 Error messages error messages are trying to tell you something Google error messages (with quotation marks) Debugging brute-force logic (the Feynman algorithm): stare at your code, try to figure out what s wrong test cases: why is it failing in one specific situation? flow charts, pseudocode tracing (print() statements) put print statements before and after if conditions before and after loops in places where you suspect something might go wrong interactive tracing debugging tools (breakpoints/watchpoints/watches)