python101.play

$ clear
# Python is a general-purpose high-level programming language.
# It is very easy to learn

# in Python variables are references
a = 3
a = 'hello world'
a = [1,2,3]
b = a
print a, b
b[1] = 7
print a, b
# in Python variables do not have a type, objects do
print type(3)
a = 3
print type(a)
print type('hello world')
a = 'hello world'
print type(a)

# strings can be delimited in multiple equivalent ways
a = 'this is an ASCII string'
a = "this is an ASCII string"
a = '''this is an ASCII string'''
a = """this is an ASCII string"""

# strings can be concatenated

a = 'hello'
b = 'world'
c = a+' '+b
print c

# in Python you always loop using an iterator
# a list is an example of iterator
a = [4,6,7]
for i in a: print i

# you can make lists with the function range
for i in range(0,5): print i

# you can append elements to lists
a = []
a.append('x')
a.append('y')
print a
# you can insert elements
a.insert(0,'u')
print a
# delete elements
del a[2]
print a
# concatenate lists
a = a+a+a
print a
# slice them
a = a[1:-1]
print a
# and of course query them for length
print len(a)

# a tuple is a like a list but you cannot change its elements
a = [1,2,3]
b = (1,2,3)
# let us try with the list a
a[1]='changed'
print a
# let us try the same with a tuple
b[1]='changed'
# that is called a traceback

# tuples are useful to pack and unpack variables

(a,b,c) = (1, 'hello', 8)
print a
print b
print c

# Python has dictionaries and they are hash tables for key-value store
a = {}
a['key']='value'
a['Max']='111-111-1111'
a['John']='123-123-1234'

print a['Max']
print a.keys()
print a.values()
print a.items()
print a

# you delete values
del a['Max']
print a

# you can ask for membership

print 'john' in a

# there is another syntax for dictionaries
a = {'max':'111-111-1111', 'John':'123-123-1234'}
a = dict(max='111-111-1111', John='123-123-1234')

# almost everything is hashable
print hash("hello world")

# in Python blocks of code are delimited by indentation
for i in range(3):
    for j in range(3):
        print i,j


# some times you need loop and count
pets = ['dog','cat','mouse']
for i, pet in enumerate(pets):
    print i, pet


# if you prefer you can loop with while
i = 0 
while i<3:
    print i
    i = i+1 


# you can exit loops with break
for i in range(10):
    print i
    if i==3: break


# sometimes you want to skip a loop and jump to the next iteration
for i in range(10):
    if 3<i<9: continue
    print i


# if statements are also very easy,
# we generate a random number between 0 and 1
import random
x = random.random()
# and we check for its value
if x<0.5:
   print 'x less than 0.5'


# for a more complex example let us write a program
# to factorize a random input number
rm tmp_*.py
@@UPDATE@@ tmp_factorize.py
# we import two modules
import random
import math

# we generate a random number
x=random.randint(0,10e5)

# we loop over all possible factors y
y = 2
while y <= x:
    # we assume y is not factor of x
    power = 0
    # but if it is a factor... 
    while x % y  == 0:
         # we divide x by y and count the power
         power, x = power+1, x/y
    # and if y is a factor we print it
    if power:
         print '%i ^ %i' % (y,power)
    # try next number
    y = y+1
@@END@@

# now we run the program
python tmp_factorize.py

# Python throws exceptions on error.
@@UPDATE@@ tmp_exceptions.py
if True:
    for i in [1,2,3]:
        print 1/(i-2)
@@END@@

python tmp_exceptions.py

# exceptions can be caught

@@UPDATE@@ tmp_exceptions.py
try:
    for i in [1,2,3]:
        print 1/(i-2)
except ZeroDivisionError, e:
    print 'division by zero!'
except Exception, e:
    print 'some other error occurred: %s' % e
finally:
    print 'cleanup code goes here'
@@END@@

python tmp_exceptions.py

# functions are very easy in Python
def f(a):
    return a*2

print f(4)
print f('hello')

# functions can take multiple arguments are return multiple arguments
def g(a,b,c):
    return a,a+b,a+b+c

print g(3,5,6)
print g(3,b=5,c=6)

# you can pass arguments out of order
print g(c=6,b=5,a=3)

# you can give default values
def g(a,b=5,c=5):
    return a,a+b,a+b+c

print g(3)

# Sometimes you are not sure how many arguments you will be passing to a function
def h(*ks,**kv):
    return sum(ks)+sum(kv.values()), ks, kv

print h(3)
print h(3,5,6)
print h(3,5,6,8,9)
print h(3,5,a=6,b=17)

# classes in Python are different than in languages like C++ and Java
# they are simply models for containers
class A: pass

# now we make an instance of the class
a=A()

# and we can store stuff inside
a.x=5
a.y=8

# now x and y belong to the instance
# we can also store stuff into the class
A.z = 7

# and retrieve the stuff
print a.x, a.y, a.z

# notice that if we make another instance
b = A()

# z is in there
print b.z

# but x and y are not
print a.x

# you can create member variables in a constructor
class C:
    def __init__(this,x,y):
        this.x = x
        this.y = y

a = C(3,5)
print a.x, a.y


# notice that 'this' MUST be the first argument of the constructor 
# 'this' plays the same role as Java 'this'
# Python programmers prefer using 'self' instead of 'self'

class C:
    def __init__(self,x,y):
        self.x = x
        self.y = y


# 'self' or 'this' are not keywords but variables

# __init__ is a special method but you can define other additional methods

@@UPDATE@@ tmp_class.py
class C:
    def __init__(self,x,y):
        self.x = x
        self.y = y
    def getxy(self):
        return self.x,self.y

b = C(4,5)
print b
@@END@@

python tmp_class.py

# __init__ is not the only special method. there are more for example

@@UPDATE@@ tmp_class.py
class C:
    def __init__(self,x,y):
        self.x = x
        self.y = y
    def getxy(self):
        return self.x,self.y    
    def __add__(self,other):
        return C(self.x+other.x, self.y+other.y)

a = C(1,3)
b = C(4,5)

# and now this
c = a + b 
# is the same as this
c = a.__add__(b)

# and they generate
print c.getxy()
@@END@@

python tmp_class.py

# Python is very handy to handle files
# we can create a file for writing
f1 = open('tmp_file.txt','wb')
# write something in it
f1.write('dataxyz')
# reopen for reading
f2 = open('tmp_file.txt','rb')
# read all data
data = f2.read()
# and print what we got
print data

# normally you define functions with
def f(a,b): return a+b

# this can also be broken into two steps
# step one: we define the function without giving it a name
lambda a,b: a+b
# step two: we give it a name
f = lambda a,b: a+b
# we can now call
print f(3,4)
# why would we do such a thing?
# consider this definition of a derivative
def D(f,x,h=1e-5): return (f(x+h)-f(x))/h
# we can now compute the derivative of the function sin at 1 with
from math import sin
print D(sin,5)
# what if we had 
def g(x,y): return sin(x*y)
# and we wanted the derivative respect to y for x=7, y=1?
print D(lambda y: g(7,y),1)
# notice lambda y says y is the variable

# sometimes you have code in a string
a = "x+y"
# an you want it to be executed for given values of b and c
# yes you can do it in Python, first store b and c in a dict
env = dict(x=5,y=7)
# now use eval
print eval(a,env)

# if your string contained a statement instead of an expression
# then the syntax becomes
a = "print x+y"
exec a in env

# the real power of Python is in modules, there are modules for everything

# for example
import math
# you can check what a module contains
dir(math)
# and you can ask Python for help
help(math.sin)
# and of course you can call functions in modules
print math.sin(1)

# the pickle module allows you to serialize objects
@@UPDATE@@ tmp_pickle.py
import pickle
class A: pass
a = A()
a.x = 6
pickle.dump(a,open('tmp_pickle.pickle','wb'))
@@END@@

python tmp_pickle.py

# pickled data be de-serialized
@@UPDATE@@ tmp_pickle.py
import pickle
# notice class A must be defined to un-pickle
class A: pass
b = pickle.load(open('tmp_pickle.pickle','rb'))
print b.x
@@END@@ 

python tmp_pickle.py

# the time module is useful to waste some time
import time
time.sleep(1) # one second!

# but datetime is better to manipulate dates and times and intervals
import datetime
today = datetime.date.today()
print today
print today.day, today.month, today.year
now = datetime.datetime.now()
print now
print now.day, now.month, now.year, now.hour, now.minute, now.second
midnight = datetime.datetime(today.year, today.month, today.day, 0,0,0)
print (now - midnight).seconds

# we have used the random module already
# let us play with it some more
import random
# we make a list of 1000 random numbers
v = [random.random() for i in range(1000)]
# and a function to create the expectation value of a function
def E(f,v): return sum(f(x) for x in v)/len(v)
# and now we can compute an average
mu = E(lambda x:x,v)
# the variance
variance = E(lambda x:(x-mu)**2,v)
# the standard deviation
import math
sigma = math.sqrt(variance)
# we can compute skewness
skewness = E(lambda x:((x-mu)/sigma)**3,v)
# and the kurtosis
kurtosis = E(lambda x:(x/sigma)**4,v)

# if we make a random integer in range
a = random.randint(10,20)
# and if we have a list we can pick a random element from it
a = ['a','b','c','d','e']
print random.choice(a)

# module urllib allows you to download web pages
import urllib
html = urllib.urlopen('http://python.org').read()
print html[:100]+'...'+html[-100:]
# it is useful to download all sort of data from the web

# produced by Massimo Di Pierro with Kryten
# you can redistrubute this video freely

quit