Introduction to Python Why Python?

 Have your cake and eat it, too: Productivity and readable code Python is a general-purpose interpreted, interactive, object-oriented, and high-level . It was created by  VHLLs will gain on system languages Guido van Rossum during 1985- 1990. Like (John Ousterhout) , Python source code is also available under the GNU General Public License (GPL).  "Life's better without braces" (Bruce Eckel) Python is Interpreted: Python is processed at Tutorial Outline runtime by the interpreter. You do not need to compile your program before executing it. This is similar to PERL and PHP.  interactive "shell" Python is Interactive: You can actually sit at a Python prompt and interact with the  basic types: numbers, strings interpreter directly to write your programs.  container types: lists, dictionaries, tuples  variables Python is Object-Oriented: Python supports Object-Oriented style or technique of  control structures programming that encapsulates code  functions & procedures within objects.  classes & instances

Python is a Beginner's Language: Python is a  modules & packages great language for the beginner-level  exceptions programmers and supports the  files & standard library development of a wide range of applications from simple text processing to WWW browsers to games. $sudo apt-get install python3-minimal

In the bash shell (Linux): type export PYTHONPATH=/usr/local/bin/python3.4 and press Interactive “Shell” Enter.

 Great for learning the language  Great for experimenting with the library Unix: IDLE is the very first Unix IDE for Python.  Great for testing your own modules  Two variations: IDLE (GUI), python (command line)  Type statements or expressions at prompt: #!/usr/bin/python3 >>> print "Hello, world" print ("Hello, Python!") Hello, world >>> x = 12**2 >>> x/2 72 >>> # this is a comment Python supports four different numerical types −

int (signed integers): They are often called just Numbers integers or ints, are positive or negative whole numbers with no decimal point.

long (long integers ): Also called longs, they are  The usual suspects integers of unlimited size, written like integers and  12, 3.14, 0xFF, 0377, (-1+2)*3/4**5, abs(x), followed by an uppercase or lowercase L. 0 0 # 1./2. -> 0.5, float(1)/2 -> 0.5 parts. Floats may also be in scientific notation, with E  Will be fixed in the future or e indicating the power of 10 (2.5e2 = 2.5 x 102 = 250).  Long (arbitrary precision), complex  2L**100 -> 1267650600228229401496703205376L complex (complex numbers) : are of the form a + bJ,  In Python 2.2 and beyond, 2**100 does the same thing where a and b are floats and J (or j) represents the  1j**2 -> (-1+0j) square root of -1 (which is an imaginary number). The real part of the number is a, and the imaginary part is b. Complex numbers are not used much in Python programming. Operator Description Example Strings + Concatenation - Adds values on a + b will give HelloPython either side of the operator * Repetition - Creates new strings, a*2 will give -HelloHello concatenating multiple copies "hello"+"world" "helloworld" # concatenation of the same string [] Slice - Gives the character from a[1] will give e "hello"*3 "hellohellohello" # repetition the given index [ : ] Range Slice - Gives the a[1:4] will give ell "hello"[0] "h" # indexing characters from the given range in Membership - Returns true if a H in a will give 1 "hello"[-1] "o" # (from end) character exists in the given string "hello"[1:4] "ell" # slicing not in Membership - Returns true if a M not in a will give 1 character does not exist in the len("hello") 5 # size given string r/R Raw String - Suppresses actual print r'\n' prints \n and print "hello" < "jello" 1 # comparison meaning of Escape characters. R'\n'prints \n The syntax for raw strings is "e" in "hello" 1 # search exactly the same as for normal strings with the exception of the "escapes: \n etc, \033 etc, \if etc" raw string operator, the letter "r," which precedes the quotation marks. The "r" can be lowercase 'single quotes' """triple quotes""" r"raw strings" (r) or uppercase (R) and must be placed immediately preceding the first quote mark. % Format - Performs String formatting Lists

 Flexible arrays, not Lisp-like linked lists  a = [99, "bottles of beer", ["on", "the", "wall"]]  Same operators as for strings  a+b, a*3, a[0], a[-1], a[1:], len(a)  Item and slice assignment  a[0] = 98  a[1:2] = ["bottles", "of", "beer"]

-> [98, "bottles", "of", "beer", ["on", "the", "wall"]]  del a[-1] # -> [98, "bottles", "of", "beer"]  The method append() appends a passed obj into the existing list.

 Syntax  Following is the syntax for append() method −  list.append(obj)

 Parameters  obj -- This is the object to be appended in the list.

 Return Value  This method does not return any value but updates existing list.

 Example  The following example shows the usage of append() method.

 #!/usr/bin/python

 aList = [123, 'xyz', 'zara', 'abc'];  aList.append( 2009 );  print "Updated List : ", aList  When we run above program, it produces following result −

 Updated List : [123, 'xyz', 'zara', 'abc', 2009] More List Operations

>>> a = [0,1,2,3,4] ; >>> a.append(5) # [0,1,2,3,4,5] >>> a.pop() # [0,1,2,3,4] 5 >>> a.insert(0, 42) # [42,0,1,2,3,4] >>> a.pop(0) # [0,1,2,3,4] 5.5 >>> a.reverse() # [4,3,2,1,0] >>> a.sort() # [0,1,2,3,4] Dictionaries

 Hash tables, "associative arrays"  = {"duck": "eend", "water": "water"}  Lookup:  d["duck"] -> "eend"  d["back"] # raises KeyError exception  Delete, insert, overwrite:  del d["water"] # {"duck": "eend", "back": "rug"}  d["back"] = "rug" # {"duck": "eend", "back": "rug"}  d["duck"] = "duik" # {"duck": "duik", "back": "rug"} More Dictionary Ops

 Keys, values, items:  d.keys() -> ["duck", "back"]  d.values() -> ["duik", "rug"]  d.items() -> [("duck","duik"), ("back","rug")]  Presence check:  d.has_key("duck") -> 1; d.has_key("spam") -> 0  Values of any type; keys almost any  {"name":"Guido", "age":43, ("hello","world"):1, 42:"yes", "flag": ["red","white","blue"]} Dictionary Details

 Keys must be immutable:  numbers, strings, tuples of immutables  these cannot be changed after creation  reason is hashing (fast lookup technique)  not lists or other dictionaries  these types of objects can be changed "in place"  no restrictions on values  Keys will be listed in arbitrary order  again, because of hashing Tuples

A tuple is a sequence of immutable Python objects. Tuples are sequences, just like lists. tup1 = ('physics', 'chemistry', 1997, 2000); The differences between tuples and lists are, tup2 = (1, 2, 3, 4, 5 ); tup3 = "a", "b", "", "d"; the tuples cannot be changed unlike lists and tuples use parentheses, whereas lists use square brackets.  key = (lastname, firstname)  point = x, y, z # parentheses optional  x, y, z = point # unpack  lastname = key[0]  singleton = (1,) # trailing comma!!!  empty = () # parentheses!  tuples vs. lists; tuples immutable Variables

 No need to declare  Need to assign (initialize)  use of uninitialized variable raises exception  Not typed if friendly: greeting = "hello world" else: greeting = 12**2 print greeting  Everything is a "variable":  Even functions, classes, modules Reference Semantics

 Assignment manipulates references  x = y does not make a copy of y  x = y makes x reference the object y references  Very useful; but beware!  Example: >>> a = [1, 2, 3] >>> b = a >>> a.append(4) >>> print b [1, 2, 3, 4] Changing a Shared List

a = [1, 2, 3] a 1 2 3

a b = a 1 2 3 b

a a.append(4) 1 2 3 4 b Changing an Integer a = 1 a 1

a b = a 1

b new int object created by add operator (1+1)

a 2 a = a+1 old reference deleted by assignment (a=...) b 1 Control Structures

if condition: while condition: statements statements [elif condition: statements] ... for var in sequence: else: statements statements break continue Grouping Indentation

0 Bingo! In C: ------3 In Python: --- for (i = 0; i < 20; i++) ------6 { ------for i in range(20): if (i%3 == 0) { --- 9 --- if i%3 == 0: printf("%d\n", i); ------if (i%5 == 0) { 12 print i ------printf("Bingo!\n"); } --- if i%5 == 0: 15 Bingo! print "Bingo!" } ------printf("---\n"); --- print "---" 18 --- } --- Functions, Procedures

def name(arg1, arg2, ...): """documentation""" # optional doc string statements return # from procedure return expression # from function Example Function

def gcd(a, b): "greatest common divisor" while a != 0: a, b = b%a, a # parallel assignment return b

>>> gcd.__doc__ 'greatest common divisor' >>> gcd(12, 20) 4 Classes

class name: "documentation" statements -or- class name(base1, base2, ...): ... Most, statements are method definitions: def name(self, arg1, arg2, ...): ... May also be class variable assignments Example Class

class Stack: "A well-known data structure…" def __init__(self): # constructor self.items = [] def push(self, x): self.items.append(x) # the sky is the limit def pop(self): x = self.items[-1] # what happens if it’s empty? del self.items[-1] return x def empty(self): return len(self.items) == 0 # Boolean result Using Classes

 To create an instance, simply call the class object: x = Stack()# no 'new' operator!

 To use methods of the instance, call using dot notation: x.empty() # -> 1 x.push(1) # [1] x.empty() # -> 0 x.push("hello") # [1, "hello"] x.pop() # -> "hello" # [1]

 To inspect instance variables, use dot notation: x.items # -> [1] Subclassing

class FancyStack(Stack): "stack with added ability to inspect inferior stack items"

def peek(self, n): "peek(0) returns top; peek(-1) returns item below that; etc." size = len(self.items) assert 0 <= n < size # test precondition return self.items[size-1-n] Subclassing (2)

class LimitedStack(FancyStack): "fancy stack with limit on stack size"

def __init__(self, limit): self.limit = limit FancyStack.__init__(self) # base class constructor

def push(self, x): assert len(self.items) < self.limit FancyStack.push(self, x) # "super" method call Class / Instance Variables

class Connection: verbose = 0 # class variable def __init__(self, host): self.host = host # instance variable def debug(self, v): self.verbose = v # make instance variable! def connect(self): if self.verbose: # class or instance variable? print "connecting to", self.host Instance Variable Rules

 On use via instance (self.x), search order:  (1) instance, (2) class, (3) base classes  this also works for method lookup  On assignment via instance (self.x = ...):  always makes an instance variable  Class variables "default" for instance variables  But...!  mutable class variable: one copy shared by all  mutable instance variable: each instance its own Modules

 Collection of stuff in foo.py file  functions, classes, variables  Importing modules:  import re; print re.match("[a-z]+", s)  from re import match; print match("[a-z]+", s)  Import with rename:  import re as regex  from re import match as m  Before Python 2.0:  import re; regex = re; del re Packages

 Collection of modules in directory  Must have __init__.py file  May contain subpackages  Import syntax:  from P.Q.M import foo; print foo()  from P.Q import M; print M.foo()  import P.Q.M; print P.Q.M.foo()  import P.Q.M as M; print M.foo() # new Catching Exceptions

def foo(x): return 1/x

def bar(x): try: print foo(x) except ZeroDivisionError, message: print "Can’t divide by zero:", message

bar(0) Try-finally: Cleanup

f = open(file) try: process_file(f) finally: f.close() # always executed print "OK"# executed on success only Raising Exceptions

 raise IndexError  raise IndexError("k out of range")  raise IndexError, "k out of range"  try: something except: # catch everything print "Oops" raise # reraise More on Exceptions

 User-defined exceptions  subclass Exception or any other standard exception  Old Python: exceptions can be strings  WATCH OUT: compared by object identity, not ==  Last caught exception info:  sys.exc_info() == (exc_type, exc_value, exc_traceback)  Last uncaught exception (traceback printed):  sys.last_type, sys.last_value, sys.last_traceback  Printing exceptions: traceback module File Objects

 f = open(filename[, mode[, buffersize])  mode can be "r", "w", "a" (like C stdio); default "r"  append "b" for text translation mode  append "+" for read/write open  buffersize: 0=unbuffered; 1=line-buffered; buffered  methods:  read([nbytes]), readline(), readlines()  write(string), writelines(list)  seek(pos[, how]), tell()  flush(), close()  fileno() Standard Library

 Core:  os, sys, string, getopt, StringIO, struct, pickle, ...  Regular expressions:  re module; Perl-5 style patterns and matching rules  Internet:  socket, rfc822, httplib, htmllib, ftplib, smtplib, ...  Miscellaneous:  pdb (debugger), profile+pstats  Tkinter (Tcl/Tk interface), audio, *dbm, ... Python 2.0: What's New

 Augmented assignment: x += y  List comprehensions: [s.strip() for s in f.readlines()]  Extended print: print >>sys.stderr, "Hello!"  Extended import: import foo as bar  Unicode strings: u"\u1234"  New re implementation (faster, Unicode)  Collection of cyclic garbage  XML, distutils URLs

 http://www.python.org  official site  http://starship.python.net  Community  http://www.python.org/psa/bookstore/  (alias for http://www.amk.ca/bookstore/)  Python Bookstore Further Reading

 Learning Python: Lutz, Ascher (O'Reilly '98)  Python Essential Reference: Beazley (New Riders '99)  Programming Python, 2nd Ed.: Lutz (O'Reilly '01)  Core Python Programming: Chun (Prentice-Hall '00)  The Quick Python Book: Harms, McDonald (Manning '99)  The Standard Python Library: Lundh (O'Reilly '01)  Python and Tkinter Programming: Grayson (Manning '00)  Python Programming on Win32: Hammond, Robinson (O'Reilly '00)  Learn to Program Using Python: Gauld (Addison-W. '00)  And many more titles... The Problem

The Subaru Software Development team (SSD) is migrating their instrument control software from C/C++ to Python. Lack of performance comparisons directly between the two languages. Information on performance impacts from migrated code is needed.

40 Write performance benchmarking software in both C/C++ and Python. Execute software on Subaru’s Real Time System (AO188RTS) Construct a Wiki page on Subaru’s Wiki to present an analysis on the results.

41 Why Python? C++ Python

Complex syntax Minimal Syntax Difficult to read Easier to read and debug Faster development time Increases productivity Compiled vs. Interpreted

C++ is a compiled Python is an interpreted language. language. Code is translated from a Code is translated into a human readable text form machine readable form into an executable form that during run time by an a machine can read. interpreter application. Compiled code is hardware Interpreted code run on any specific. platform with the interpreter installed. Benchmarking Suite

Output GUI

SearchingResults(Shorter - Theis better) GoodSorting Runtime (ms)

C++ Python C++ Python 45 ResultsVector Normalization– The Bad

C++ Python Jitter

46 Results – The Ugly Matrix Inversion

C++ Python Jitter

47 Conclusions

Python ran an average of 4x slower than C++ in averaging all test results. Runtime jitter is more important for real-time applications than average execution times. Mathematical, memory intensive, or complex algorithms suffer the biggest performance impacts in Python. Utilizing Pythons built in methods or external modules can produce near or better than C++ performance. Exercises Exercise

Rewrite your pay computation with time-and-a- half for overtime and create a function called computepay which takes two parameters ( hours and rate).

Enter Hours: 45 Enter Rate: 10 Pay: 475.0 475 = 40 * 10 + 5 * 15  Installing Python  Installing your text editor (NotePad++ or TextWrangler)  Setting tab expansion  Using the Command Line or Terminal Interface  Editing and running Python Programs Exercise 2.3

Write a program to prompt the user for their name and welcome them.

Enter your name: Chuck Hello Chuck Exercise 2.4

Write a program to prompt the user for hours and rate per hour to compute gross pay.

Enter Hours: 35 Enter Rate: 2.75 Pay: 96.25 Exercise 3.1

Rewrite your pay computation to give the employee 1.5 times the hourly rate for hours worked above 40 hours.

Enter Hours: 45 Enter Rate: 10 Pay: 475.0

475 = 40 * 10 + 5 * 15 Exercise 3.2 Rewrite your pay program using try and except so that your program handles non-numeric input gracefully.

Enter Hours: 20 Enter Rate: nine Error, please enter numeric input

Enter Hours: forty Error, please enter numeric input Exercise 5.1 Write a program which reads list of numbers until ``done'' is entered. Once ``done'' is entered, print out the total, count, and average of the numbers. If the user enters anything other than a number, print an error message and skip to the next number.

Enter a number: 4 Enter a number: 5 Enter a number: bad data Invalid input Enter a number: 7 Enter a number: done Average: 5.33333333333