In what follows in this tutorial, the result of a statement is expressed
in the form of #result#, unless otherwise mentioned.
Basic arithmetic operations
# Comments start with a hash sign (#). 1 + 2 # Addition 1 / 2 #0# Division 1 / 2. #0.5# If either one of the numbers in a division is a float, # so does the result. 3 % 2 #1# Modulus 2 ** 3 #8# Power. Equivalent to pow(2,3).Variables
# A valid name of a variable is an alpha-numeric string # consisting of one or more letters, digits or underscore characters, # just like in C. x = 3 # Assignment x + 1 #4# x = None # None is is a built-in constant # that represents the absence of a value. x, y = 1, 2 # Multiple assignments at a timeImport modules
import math math.sqrt(4) # If you do not want to write the module name each time you call the function from math import * sqrt(4) # If you are sure that you only need sqrt() in the math module from math import sqrt sqrt(4) # Module alias import math as m m.sqrt(4) # Function alias from math import sqrt as sq sq(4)Strings
# Strings can be expressed with double quotes (") or single quotes ('). # There is no difference bettwen double quotes and single quotes. x = "abc" x = 'abc' # Exactly the same as above y = "ab'cd'ef" # 'cd' is part of the string. z = 'ab"cd"ef' # "cd" is part of the string. The strings y and z are not the same. # String formatting # Use C-like conversion specifiers. 'test %s %d %.1f' % ('abc', 10, 10.33) #'test abc 10 10.3'# # String methods ' /sys/fs '.strip() #'/sys/fs'# Remove whitespaces on the left and the right. '/sys/fs'.split('/') #['', 'sys', 'fs']#Lists
# Lists start with [ and end with ]. # Elements are separated by a comma (,). x = [1, 2, 3] # A list can hold different types of elements. y = [1, 2, "abc", [5,6]] # List methods z = ['b', 'a'] z.append('c') #['b','a','c']# z.index('b') #0# Returns the index of the first occurrence of a value z.sort() #['a','b','c']# z.remove('a') # Removes the element that appears first.Tuples
# Tuples start with ( and end with ). # Tuples are just like lists with an exception that they cannot be changed. x = (1, 2) # Values separated by commas automatically becomes a tuple. x = 1, 2 # The same as above. # A tuple with a single element x = (1,) # Here the comma is important. (1) is just 1.Sequence commons: strings, lists, and tuples are called sequences.
x = '123' y = [1, 2, 3] z = (1, 2, 3) # Sequences can be indexed as follows: x[0] #'1'# y[0:2] #[1,2]# Returns a list with elements such that 0<=index<2. z[1:] #(2,3)# Return a tuple with elements such that 1<=index. x[:2] #'12'# Returns a string with elements such that index<2. y[-1] #3# Returns the last element. z[-2] #2# Returns the second last element. y[:] #[1, 2, 3]# Returns a list with all elements. # Addition and multiplication for sequences # Two objects of the same type can be added. x + '4' #'1234'# y + [4, 5] #[1, 2, 3, 4, 5]# z + (4,) #(1, 2, 3, 4)# # Multiplication can be understood as multiple additions. y*3 #[1, 2, 3, 1, 2, 3, 1, 2, 3]# Regard it as y+y+y. # Pairing elements of two sequences x = [1, 2, 3] y = [4, 5, 6] zip(x, y) #[(1, 4), (2, 5), (3, 6)]# # * operator: argument unpacking z = [x, y] zip(*z) #[(1, 4), (2, 5), (3, 6)]# The same as zip(x,y)Dictionaries
# A dictionary starts with { and ends with }, # and it is like a hash table that maps a key to a value. # An element is defined as a pair of a key and a value. d = {'key1':'value1', 'key2':'value2'} d = {} # An empty dictionary d['key3'] = 'value3' # Adds a key-value pair. d['key3'] #'value3'# Returns a value for the key # The key must be immutable. d['abc'] = 3 # OK d[(a,b)] = [1,2] # OK d[3] = 'abc' # OK d[[1,2,3]] = 2 # Not OK, since a list is mutable. # Dictionary methods d.get(key) # Returns a value corresponding to the key. d.has_key(key) # Returns True if the key in the dictionary, and False otherwise. d.items() # Returns a list of (key, value) tuple pairs. d.keys() # Returns a list of keys. d.values() # Returns a list of values. d.copy() # Return a dictionary object that # has exactly the same contents as d.Print to screen
# Note that what is shown here valid in Python 2.7 only. # Syntax for print is quite changed in Python 3.4. x = 1 y = [1,2] print 3 #3# print 3, "abc" #3 abc# print "%d %d" % (3, 4) #3 4# print x, #1# Trailing comma suppresses newline. print str(y) #[1, 2]# str() transforms an object into a string. print repr(y) #[1, 2]# # Most of times, repr() results in the same as str().Assignment is by reference!
# One thing to remember # when you assign a list or a dictionary (i.e., mutable objects) to another variable: # Assignment is always by reference, not by copy. x = [1, 2, 3] y = x # Here, y get a reference to what x points to, i.e., [1, 2, 3] y[0] = 4 x #[4, 2, 3]# Note that x is changed by y. # To copy a list y = x[:] # Creates a new list that contains all elements of x. y[0] = 4 x #[1 ,2 ,3]# # To copy a dictionary x = {1: 1} y = x z = x.copy() # Use the copy() method. y[1] = 2 z[1] = 3 print str(x), str(y), str(z) #{1: 2} {1: 2} {1: 3}#Conditionals
if x == 5: # Note that there is a colon (:) at the end. # VERY IMPORTANT: # All statements in a block must be indented by the same amount. # Otherwise, you will see an error. x += 1 y = x + 2 print x, y elif x in [4,5,6]: # True if x is one of 4, 5, or 6. if x != 2: # Conditions can be nested. print x else: # Empty blocks are not allowed. # Put 'pass' for a placeholder when you want do nothing. passThe for-loops
x = [1, 2, 3] for v in x: # Iterates the elements of x from the first to the last. print v, #1 2 3# range(3) #[0, 1, 2]# Returns a list of integers from 0 to 3-1. range(1,4) #[1, 2, 3]# Returns a list of integers from 1 to 4-1. for i in range(3): print x[i], #1 2 3#The while-loops
x = 5 while x > 0: x -= 1 if x == 3: continue # continue as in C if x == 1: break # break as in C print x, #4 2#List comprehension: making a list from other list
x = [i*2 for i in range(5)] y = [i*2 for i in range(5) if i%2 == 0] x #[0, 2, 4, 6, 8]# y #[0, 4, 8]#Iterating over a dictionary
d = {1: 'a', 2: 'b', 3: 'c'} for k, v in d.items(): print str(k) + ':' + v, #1:a 2:b 3:c# # The following is the same as above. key = d.keys() value = d.values() for k, v in zip(key, value): print str(k) + ':' + v, #1:a 2:b 3:c#Functions
# Writing your own functions def foo(arg1): # Do not forget the colon at the end. x = arg1 + 1 return x # You can omit the return statement # if there is nothing to return. def bar(arg1, arg2 = 3): # arg2 gets its value as 3 by default. x = arg2 + 1 return arg1[0], x # Here, arg1 can be of any type except # a literal constant. q, w = bar('abc') # You can omit the argument that has its default value. print q, w #a 4# print bar('abc') #('a', 4)# arg1 is a string. print bar('abc', 4) #('a', 5)# Put something to change the default value. print bar([1, 2]) #(1, 4)# arg1 is a list. print bar((5, 6)) #(5, 4)# arg1 is a tuple. print bar(7) # An error # Make use of argument unpacking operator (*). x = (1, 2) def add(a, b): return a+b print add(*x) #3# Just add(x) will cause an error. # A function can have a different name. my_add = add my_add(1,2) #3# # Lambda expressions add2 = lambda arg1, arg2: arg1+arg2 add2(1,2) #3# # Lambda expressions may be used when you pass an argument that is a function. a = [(1,1),(1,0),(2,0),(2,1)] sorted(a, key=lambda x:x[0]) #[(1, 1), (1, 0), (2, 0), (2, 1)]# # Sort by the first element of tuples sorted(a, key=lambda x:x[1]) #[(1, 0), (2, 0), (1, 1), (2, 1)]# # Sort by the second element of tuples sorted(a, key=lambda x:(x[0],x[1])) #[(1, 0), (1, 1), (2, 0), (2, 1)]# # Sort by the first and then the second # To change global variables within a function x = 1 def foo(a): global x # Without this, x won't be changed. x += a returnExceptions
# If something bad happens within a try block, an exception is raised. def foo(x): y = 1 try: y = y/x except ZeroDivisionError: # You can specify the type of # an exception to deal with. print "divided by zero" except: # All exceptions other than # the above are handled here. print "something else" foo(0) #divided by zero# foo('1') #something else# # Raise exceptions and catch exception objects. import traceback # To use print_exc() try: raise Exception("my exception") # Raise an exception with some argument. except Exception as e: # The 'Exception' is the base of all exception # objects, so it can catch all exceptions. if e.args == ("my exception",): # You can check what argument is in. print "my exception occurs" print e.args[0] #my exception# # Print the argument of the exception. # Print exception information by which you can locate the culprit. traceback.print_exc() # The else-clause: executed when there is no problem in the try block. while True: default = '1' menu = 1 try: # Take an input from a user # Just typing the enter key will cause the default value to be chosen. t = raw_input("Enter a number (default="+default+"): ") or default menu = int(t) % 10 print 'You selected ' + str(menu) except: print 'Invalid input' # e.g., character inputs will come to here. else: break # Executed if no exceptions are raised in the try block.Reading from and writing to a file
fr = open('text.txt', 'r') # Open text.txt to read. fw = open('result.txt', 'w') # Open result.txt to write. for line in fr.readlines(): # Iterate text.txt line by line. fw.write(line + ' some') # Write a string as a a line fr.close() # Do not forget to close files fw.close()Some useful built-in functions
x = [1, 0, 2] len(x) #3# Returns a length of a sequence. max(x) #2$ Returns the largest element. min(x) #0# Returns the smallest element. sorted(x) # Returns a list of sorted elements of a sequence. sum(x) #3# Returns the sum of all elements. # The 'in' operator returns True if a value is in a sequence and False otherwise. 2 in x #True# # To delete an element of a list or a dictionary del x[1] # Here, 1 is an index. d = {1:2, 3:4} del d[1] # Here, 1 is a key. # Convert a string or a number to an integer or an floating number. int('12') #12# int(12.3) #12# float("3.3") #3.3#
Drawing a graph
You may need to additionally install numpy and matplotlib modules to plot a graph. In Ubuntu, the easiest way to get them is to type:
$ sudo apt-get install python-numpy python-matplotlib
import numpy as np
import matplotlib.pyplot as plt
x1 = [1, 4, 8]
y1 = [0.5, 2, 4]
x2 = [1, 2, 3]
x2_array = np.array(x2) # np.array() makes an array object.
y2_array = x2_array ** 2 # The array object enables
# MATLAB-like element-wise operations
# plt.plot() takes lists or arrays as its data arguments.
plt.plot(x1, y1, x2_array, y2_array)
# The following commands are self-explanatory.
plt.title('title')
plt.xlabel('label for x-axis')
plt.ylabel('label for y-axis', fontsize=15)
plt.grid()
plt.legend(['x/2', 'pow(x,2)'])
plt.xlim(0, 9)
plt.ylim(0, 10)
plt.savefig('fig1.png', format='png') # Try pdf, eps, ... almost all you can imagine.
# Whenever you want another figure
plt.figure()
plt.subplot(211)
plt.plot(x1, y1, 'r--')
plt.subplot(212)
plt.plot(x2_array, y2_array, 'b.', markersize=30)
plt.xlim(0, 4)
plt.ylim(0, 10)
plt.savefig('fig2.png')
Redirect a text stream to your Python script
Sometimes you may want to process the output of Linux commands within
Python scripts by redirecting. Use the following example script in such
a case. Say you write the codes in find_keyword.py and you want to
catch the lines that contain ‘kworker’ from /proc/kmsg. Then, type:
$ sudo cat /proc/kmsg | python find_keyword.py kworker file1.txt
import sys
if (len(sys.argv) != 3):
print '\n Usage example:'
print ' When you want to find lines from /proc/kmsg that contain "kworker",'
print ' print them to screen, and store them into file1.txt,'
print ' sudo cat /proc/kmsg | python '+sys.argv[0]+' kworker file1.txt\n'
sys.exit(1)
fo = open(sys.argv[2], "w")
while True:
try:
line = sys.stdin.readline() # Reads a line from stdin
except KeyboardInterrupt: # until a user hits ctrl+c
break
if not line: # or until there is nothing left to read
break
if sys.argv[1] in line:
print line
fo.write(line + '\n')
fo.close()
Regular expressions
A regular expression specifies a set of strings that matches it. You may have to spend non-trivial time to be familiar with all pattern syntaxes of regular expressions. Here, we show just a few of use cases. For more detail, refer to:
https://docs.python.org/2/library/re.html
import re
text1 = 'Fig. 1: initially there are 60 points in each class.'
text2 = 'My phone number is 123-456-7890.'
text3 = 'MemFree: 50116 kB'
lines = [text1, text2, text3]
# See if text1 contains 'where'.
m1 = re.search('where', text1, flags=0)
print repr(m1) #None#
if m1: # None is equivalent to False in a condition.
print "This won'n be printed."
# See if text1 is a string that contains 'there' somewhere in it.
m2 = re.search('.*there.*', text1, flags=0)
# '.*' means any character of 0 or more occurrences.
if m2: # If matched, m2 is not None.
# m2.group() is the whole string that matches the pattern '.*there.*'.
print m2.group()
# Use parentheses for grouping
m3 = re.search(r'.*([A-Z]).*there.*\s(\d+).*', text1, flags=0)
# Why 'r' before the opening quote? Check raw strings!
# Without the 'r', all backslashes must be twice-typed.
# To avoid confusion, patterns in Python code are
# usually expressed in raw string notation.
# '[A-Z]' means an alphabet between A and Z,
# '\s' a white space, and
# '\d+' a digit of 1 or more occurrences.
if m3:
print m3.group()
print m3.group(1) #F# The string captured within the first parentheses.
print m3.group(2) #60# The string captured within the second parentheses.
# See if text2 contains a phone number
m4 = re.search(r'\d{3}-\d{3}-\d{4}', text2, flags=0)
if m4:
print m4.group() #123-456-7890#
# Parse the number that corresponds to Memfree from a list of strings.
for line in lines:
m5 = re.search(r'MemFree:\s+(\d+)\s+kB', line, flags=0)
if m5:
print m5.group(1) #50116#
Classes
Python provides all the standard features of object oriented programming by classes:
class Person:
# Class variables defined in this way
# are shared by all instances,
# like static member variables in C++.
cnt = 0
# The initializer method, like a constructor in C++.
def __init__(self, name_):
# Class variables defined in this way
# are unique to each instance.
self.name = name_
# Access like a static member variable in C++.
Person.cnt += 1
# Class methods
def showCount(self):
print "The number of Persons are %d." % (Person.cnt)
def showName(self):
print "My name is %s." % (self.name)
# Creating instances
p1 = Person('James')
p2 = Person('Matt')
p1.showName() #My name is James.#
p2.showName() #My name is Matt.#
p1.showCount() #The number of Persons are 2.#
# Class members are normally all public in C++ terminology.
print Person.cnt, p1.name, p2.name #2 James Matt#
# Add or remove attributes of class instances.
p1.age = 10
del p1.age
# Inheritance
class Student(Person): # Inherits from Persion
def __init__(self, name_, grade_):
self.grade = grade_
Person.__init__(self, name_)
def showGrade(self):
print "Hmm.. My grade is %s." % (self.grade)
# All methods in Python are virtual in C++ terminology:
# Derived classes override methods of the same name defined in their base classes.
def showName(self):
# This is how to extend rather than simply replace
# the base class method of the same name.
Person.showName(self)
print 'And I am a student.'
s = Student('Aaron', 'A+')
s.showName() #My name is Aaron.\nAnd I am a student.#
s.showGrade() #Hmm.. My grade is A+.#