1. June 11-13 2008www.roboteducation.org1 IPRE 2008 WORKSHOP Advanced Python Keith O’Hara keith.ohara@gatech.edu School of Interactive Computing Georgia Tech

2. June 11-13 2008www.roboteducation.org2 Python  Interactive  Cross-platform  Looks like pseudo-code  Indentation matters  Support for functional programming  Large collection of libraries  Object system built on top of functions  Syntax support for common data structures  Used by Google, Yahoo, NASA among others

3. June 11-13 2008www.roboteducation.org3 Interacting with the User with Myro  ask(“prompt”) prompt user with dialog box and return response  askQuestion(“prompt”, [choices]) prompt user with dialog box and return response  raw_input(“prompt”) prompt user with text interface and return response

4. June 11-13 2008www.roboteducation.org4 Myro and Files  pickAFile() prompts user for file  pickAFolder() prompts user for folder  open(file, mode) open file with mode ( `r’,`w’,`a’ )  file.read(); file.readlines() read file and return contents as a string (list of strings)  string.split() Turn string into a list of strings based on whitespace from myro import * f = open(pickAFile(), ‘r’) data = f.read().split() print data f.close() from myro import * f = open(pickAFile(), ‘r’) data = f.read().split() print data f.close()

5. June 11-13 2008www.roboteducation.org5 Myro Control Flow Constructs  wait(seconds) pause for seconds before executing next statement  currentTime() returns the current time in seconds  while timeRemaining(seconds): print "running..." execute loop for at least seconds  for s in timer(seconds): print "running for", s, "..." loop for at least seconds; s is the value of the timer

6. June 11-13 2008www.roboteducation.org6 Myro Random Utilities  flipCoin() returns ‘heads’ or ‘tails’ with equal probability  heads() returns True 50% of the time  tails() returns True 50% of the time  pickOne(v1, v2, …, vn) chose one value from the values with equal probability  randomNumber() return a uniform random number between [0,1)

7. June 11-13 2008www.roboteducation.org7 random module  random. uniform(low, high)  Float: low <= x < high  random.randint(low,high)  Integer: low <= x <= high  random.choice(sequence)  Random element of a sequence  random.shuffle(sequence)  Randomly shuffle a sequence

8. June 11-13 2008www.roboteducation.org8 Scribbler Music  Random notes  Use choice function import random notes = [440, 494, 523, 587, 659] for i in range(10): dur = random.random() freq = random.choice(notes) beep(dur, freq)

9. June 11-13 2008www.roboteducation.org9 Tuples  Immutable sequences (a, b)  Multiple return values return a, b  Tuple Assignment a, b = b, a  zip - useful for iterating through multiple sequences zip ([a1, a2, … an], [b1, b2, …, bn]) --> [(a1, b1), (a2, b2), …, (an, bn)] names = [“al”, “bob”, “ted”] grades = [90, 88, 98] for n,g in zip(names, grades): print n, “got a”, g names = [“al”, “bob”, “ted”] grades = [90, 88, 98] for n,g in zip(names, grades): print n, “got a”, g

10. June 11-13 2008www.roboteducation.org10 Set  Unordered collection of unique elements a = set(‘abca’) b = set(‘cbcbcb’) ‘a’ in a ‘a’ in b a - b # set difference a & b # set intersection a | b # set union a ^ b # exclusive or a = set(‘abca’) b = set(‘cbcbcb’) ‘a’ in a ‘a’ in b a - b # set difference a & b # set intersection a | b # set union a ^ b # exclusive or

11. June 11-13 2008www.roboteducation.org11 Dictionaries  Associative Arrays  Collection of key-value pairs  dict[key] = value  {} is the empty dictionary notes = {‘a’: 440, ‘b’:494 } notes[‘c’] = 523 beep(1, notes[‘a’]) notes[‘a’] = 440 * 2 for key in notes: print ‘Beeping’, key beep(1, notes[key]) notes = {‘a’: 440, ‘b’:494 } notes[‘c’] = 523 beep(1, notes[‘a’]) notes[‘a’] = 440 * 2 for key in notes: print ‘Beeping’, key beep(1, notes[key])

12. June 11-13 2008www.roboteducation.org12 Functions  Default values  Keyword arguments  Multiple return values def mult (x, y=2): return x * y def div(x, y=1): return x/y, x%y print mult(1,3) print mult(1) print mult(x=3, y=2) quo,rem = div (5, 2) def mult (x, y=2): return x * y def div(x, y=1): return x/y, x%y print mult(1,3) print mult(1) print mult(x=3, y=2) quo,rem = div (5, 2)

13. June 11-13 2008www.roboteducation.org13 Getting Functional  Functions are first class citizens in python  Lambdas - nameless or anonymous functions  Limited to one expression  Higher order functions  Functions that take or return functions def mult (x, y): return x * y mult2 = lambda x,y: x*y mult3 = mult def makeMult(): return lambda x,y:x*y print mult2(1,3) print mult3(2,3) print makeMult()(4,2) def mult (x, y): return x * y mult2 = lambda x,y: x*y mult3 = mult def makeMult(): return lambda x,y:x*y print mult2(1,3) print mult3(2,3) print makeMult()(4,2)

14. June 11-13 2008www.roboteducation.org14 Filter/Map/Reduce in Python  Lots of computations can be described as filter, map, and reduce operations.  Filter - pick items from a list  Map - perform an operation on each item of a list, returning a new list  Reduce - combine all the items in a list in some way  Shortcut for a for-loop and append/delete  Google has extended this concept to multiple computers  MapReduce - terabytes of data!

15. June 11-13 2008www.roboteducation.org15 Filter  Higher-order function  A predicate to decide if an item is “filtered” through  The sequence to be filtered  Returns the filtered sequence def even(x): if (x % 2) == 0: return True else: return False filter(even, [1, 2, 3, 4, 6]) def even(x): if (x % 2) == 0: return True else: return False filter(even, [1, 2, 3, 4, 6]) #odds filter(lambda x: x % 2, [1, 2, 3, 4, 5, 6]) #odds filter(lambda x: x % 2, [1, 2, 3, 4, 5, 6])

16. June 11-13 2008www.roboteducation.org16 Map  Higher-order function  A function to apply to each item  Sequence to be “mapped”  Returns a sequence combining the results of the maps (possibly an empty list)  Can take multiple sequences and a function of multiple arguments def upOctave(note): return note *2 def play(note): beep (.1, note) notes = [440, 466, 494, 523] map(play, notes) newNotes = map(upOctave, notes) map(play, newNotes) def upOctave(note): return note *2 def play(note): beep (.1, note) notes = [440, 466, 494, 523] map(play, notes) newNotes = map(upOctave, notes) map(play, newNotes)

17. June 11-13 2008www.roboteducation.org17 Implementing a simple map def ourMap(f, lst): newlst = [] for x in lst: newx = f(x) newlst.append(newx) return newlst def ourMap(f, lst): newlst = [] for x in lst: newx = f(x) newlst.append(newx) return newlst

18. June 11-13 2008www.roboteducation.org18 Reduce  Higher-order function  A function to accumulate the item in some way  The sequence to be “reduced”  Returns the accumulated sequence def mul(x, y): return x * y data = [88, 90, 91, 66, 100] geomean = reduce(mul, data)**(1.0/len(data)) arimean = reduce(add, data)* (1.0/len(data)) def mul(x, y): return x * y data = [88, 90, 91, 66, 100] geomean = reduce(mul, data)**(1.0/len(data)) arimean = reduce(add, data)* (1.0/len(data))

19. June 11-13 2008www.roboteducation.org19 Dot Product  Vector dot product using map/reduce v1 = [8, 9, 1, 6, 0] v2 = [1, 2, 3, 4, 5] dp = reduce(add, map(mul, v1, v2)) v1 = [8, 9, 1, 6, 0] v2 = [1, 2, 3, 4, 5] dp = reduce(add, map(mul, v1, v2))

20. June 11-13 2008www.roboteducation.org20 Gather Data with the Scribbler  Program to gather and analyze data about light levels of the room  Average  Minimum  Maximum  Variance Light Sensors

21. June 11-13 2008www.roboteducation.org21 Computing Statistics  Compute statistics about light levels of the room  Average  Minimum  Maximum  Variance  Use list to store data  Use map/reduce to write this program without any loops!  Assume max and min don’t exist already data = getLightData(10) avg = computeAverage(data) min = computeMinimum(data) max = computeMaximum(data) var = computeVariance(data) data = getLightData(10) avg = computeAverage(data) min = computeMinimum(data) max = computeMaximum(data) var = computeVariance(data)

22. June 11-13 2008www.roboteducation.org22 Putting it together def max(x,y): if x > y: return x else: return y def moveAndSense(x): turnRight(1,.1) return getLight(“center”) # get 10 readings from sensor readings = map(moveAndSense, range(10)) avg = reduce(lambda x, y: x + y, readings)/ len(readings) maximum = reduce(max, readings) minimum = reduce(min, readings) def max(x,y): if x > y: return x else: return y def moveAndSense(x): turnRight(1,.1) return getLight(“center”) # get 10 readings from sensor readings = map(moveAndSense, range(10)) avg = reduce(lambda x, y: x + y, readings)/ len(readings) maximum = reduce(max, readings) minimum = reduce(min, readings)

23. June 11-13 2008www.roboteducation.org23 List Comprehensions  From definition of mathematical sets  Subsumes map and filter in many ways  “queries” on a sequence lst = range(7) # [0,1,2,3,4,5,6] #odds filter(lambda x: x % 2, lst) [x for x in lst if x % 2] lst = range(7) # [0,1,2,3,4,5,6] #odds filter(lambda x: x % 2, lst) [x for x in lst if x % 2] for in

24. June 11-13 2008www.roboteducation.org24 Dot Product  Vector dot product using list comprehensions v1 = [8, 9, 1, 6, 0] v2 = [1, 2, 3, 4, 5] dp = sum(x * y for x,y in zip(v1, v2)) v1 = [8, 9, 1, 6, 0] v2 = [1, 2, 3, 4, 5] dp = sum(x * y for x,y in zip(v1, v2)) v1 = [8, 9, 1, 6, 0] v2 = [1, 2, 3, 4, 5] dp = reduce(add, map(mul, v1, v2)) v1 = [8, 9, 1, 6, 0] v2 = [1, 2, 3, 4, 5] dp = reduce(add, map(mul, v1, v2))

25. June 11-13 2008www.roboteducation.org25 List Comp. and getPixels() [getX(px) for px in getPixels(pic) if getGreen(pix) > 100] [getX(px) for px in getPixels(pic) if getGreen(pix) > 100] # shuffling the pixels pxs = [px for px in getPixels(pic)] random.shuffle(pxs) # shuffling the pixels pxs = [px for px in getPixels(pic)] random.shuffle(pxs)  Much faster than for-loop equivalent

26. June 11-13 2008www.roboteducation.org26 Using Objects  Already used objects without knowing it  Picture Object  Controlling multiple robots from one python script  Use dot notation similar to java and c++ from myro import * r1 = Scribbler(‘COM4’) r2 = Scribbler(‘COM5’) r1.beep(1, 440) r2.beep(1, 483) from myro import * r1 = Scribbler(‘COM4’) r2 = Scribbler(‘COM5’) r1.beep(1, 440) r2.beep(1, 483) obj = CLASSNAME(PARAMS) obj.METHOD(PARAMS) print obj.ATTRIBUTE obj = CLASSNAME(PARAMS) obj.METHOD(PARAMS) print obj.ATTRIBUTE

27. June 11-13 2008www.roboteducation.org27 Creating Objects class CLASSNAME (PARENT1, PARENT2, …): CLASSVARIABLE = INITIAL_VALUE def __init__(self, PARAMS): self.ATTRIBUTE = INITIAL_VALUE def CLASSMETHOD(PARAMS): CLASSVARIABLE def METHOD(self, PARAMS): self.ATTRIBUTE obj = CLASSNAME(PARAMS) obj.METHOD(PARAMS) print obj.ATTRIBUTE class CLASSNAME (PARENT1, PARENT2, …): CLASSVARIABLE = INITIAL_VALUE def __init__(self, PARAMS): self.ATTRIBUTE = INITIAL_VALUE def CLASSMETHOD(PARAMS): CLASSVARIABLE def METHOD(self, PARAMS): self.ATTRIBUTE obj = CLASSNAME(PARAMS) obj.METHOD(PARAMS) print obj.ATTRIBUTE constructor (multiple) inheritance instance variable explicitly passed ‘this’ reference implicitly pass ‘this’ reference Everything is public and virtual!

28. June 11-13 2008www.roboteducation.org28 Modules and Namespaces import myModule myModule.f() print myModule.v import myModule myModule.f() print myModule.v  Unit of source code organization  e.g. myro  File Name = Module Name  Assume module is in current directory or in PYTHONPATH ( sys.path )  Runs script when imported  dir(module) lists things in module myModule.py v = 3 + 2 def f(): print “myModule:f()” myModule.py v = 3 + 2 def f(): print “myModule:f()” from myModule import f,v f() print v from myModule import f,v f() print v from myModule import * f() print v from myModule import * f() print v

29. June 11-13 2008www.roboteducation.org29 Other Modules Niceties  Every module has a __name__  Use conditional execution depending on whether script is imported or run explicitly  Comment in function enclosed with three quotes is a pydoc comment  help(myModule) myModule.py v = 3 + 2 def f(): ```prints a msg ’’’ print “myModule:f()” if __name__ == “__main__”: print v f() myModule.py v = 3 + 2 def f(): ```prints a msg ’’’ print “myModule:f()” if __name__ == “__main__”: print v f()

30. June 11-13 2008www.roboteducation.org30 Nested Modules import myLibs.myModule myModule.f() print myModule.v import myLibs.myModule myModule.f() print myModule.v  Modules nested in directories  Use ‘.’ to indicate containment  __init__.py file in the directory to signal module-ness mylibs/ __init__.py myModule.py v = 3 + 2 def f(): print “myModule:f()” mylibs/ __init__.py myModule.py v = 3 + 2 def f(): print “myModule:f()” from myModule import f,v f() print v from myModule import f,v f() print v from myModule import * f() print v from myModule import * f() print v

31. June 11-13 2008www.roboteducation.org31 sys - A very useful module  sys has lots of useful stuff!  How can you find out about it?  sys.argv - list of arguments to script  sys.path - path to look for modules  sys.modules - loaded modules  sys.version  sys.platform args.py import sys if __name__ == “__main__”: print sys.argv args.py import sys if __name__ == “__main__”: print sys.argv

32. June 11-13 2008www.roboteducation.org32 Other Standard Modules  math  zlib, csv, pickle, optparse  urllib2, thread, socket, cgi  tkinter, wave  http://docs.python.org/lib/