What is Python?

Python - Tutorial

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. It was created by Guido van Rossum during 1985- 1990. Like Perl, Python source code is also available under the GNU General Public License (GPL). This tutorial gives enough understanding on Python programming language.

Audience

This tutorial is designed for software programmers who need to learn Python programming language from scratch.

Prerequisites

You should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages is a plus.
Python - Object Oriented

Python has been an object-oriented language since it existed. Because of this, creating and using classes and objects are downright easy. This chapter helps you become an expert in using Python's object-oriented programming support.

If you do not have any previous experience with object-oriented (OO) programming, you may want to consult an introductory course on it or at least a tutorial of some sort so that you have a grasp of the basic concepts.

However, here is small introduction of Object-Oriented Programming (OOP) to bring you at speed −

Overview of OOP Terminology

Class − A user-defined prototype for an object that defines a set of attributes that characterize any object of the class. The attributes are data members (class variables and instance variables) and methods, accessed via dot notation.

Class variable − A variable that is shared by all instances of a class. Class variables are defined within a class but outside any of the class's methods. Class variables are not used as frequently as instance variables are.

Data member − A class variable or instance variable that holds data associated with a class and its objects.

Function overloading − The assignment of more than one behavior to a particular function. The operation performed varies by the types of objects or arguments involved.

Instance variable − A variable that is defined inside a method and belongs only to the current instance of a class.

Inheritance − The transfer of the characteristics of a class to other classes that are derived from it.

Instance − An individual object of a certain class. An object obj that belongs to a class Circle, for example, is an instance of the class Circle.

Instantiation − The creation of an instance of a class.

Method − A special kind of function that is defined in a class definition.

Object − A unique instance of a data structure that's defined by its class. An object comprises both data members (class variables and instance variables) and methods.

Operator overloading − The assignment of more than one function to a particular operator.

Creating Classes

The class statement creates a new class definition. The name of the class immediately follows the keyword class followed by a colon as follows −

class ClassName: 'Optional class documentation string' class_suite

The class has a documentation string, which can be accessed via ClassName.__doc__.

The class_suite consists of all the component statements defining class members, data attributes and functions.

Example

Following is the example of a simple Python class −

class Employee: 'Common base class for all employees' empCount = 0 def __init__(self, name, salary): self.name = name self.salary = salary Employee.empCount += 1 def displayCount(self): print "Total Employee %d" % Employee.empCount def displayEmployee(self): print "Name : ", self.name, ", Salary: ", self.salary

The variable empCount is a class variable whose value is shared among all instances of a this class. This can be accessed as Employee.empCount from inside the class or outside the class.

The first method __init__() is a special method, which is called class constructor or initialization method that Python calls when you create a new instance of this class.

You declare other class methods like normal functions with the exception that the first argument to each method is self. Python adds the self argument to the list for you; you do not need to include it when you call the methods.

Creating Instance Objects

To create instances of a class, you call the class using class name and pass in whatever arguments its __init__ method accepts.

"This would create first object of Employee class" emp1 = Employee("Zara", 2000) "This would create second object of Employee class" emp2 = Employee("Manni", 5000)

Accessing Attributes

You access the object's attributes using the dot operator with object. Class variable would be accessed using class name as follows −

emp1.displayEmployee() emp2.displayEmployee() print "Total Employee %d" % Employee.empCount

Now, putting all the concepts together −

#!/usr/bin/python class Employee: 'Common base class for all employees' empCount = 0 def __init__(self, name, salary): self.name = name self.salary = salary Employee.empCount += 1 def displayCount(self): print "Total Employee %d" % Employee.empCount def displayEmployee(self): print "Name : ", self.name, ", Salary: ", self.salary "This would create first object of Employee class" emp1 = Employee("Zara", 2000) "This would create second object of Employee class" emp2 = Employee("Manni", 5000) emp1.displayEmployee() emp2.displayEmployee() print "Total Employee %d" % Employee.empCount

When the above code is executed, it produces the following result −

Name : Zara ,Salary: 2000 Name : Manni ,Salary: 5000 Total Employee 2

You can add, remove, or modify attributes of classes and objects at any time −

emp1.age = 7 # Add an 'age' attribute. emp1.age = 8 # Modify 'age' attribute. del emp1.age # Delete 'age' attribute.

Instead of using the normal statements to access attributes, you can use the following functions −

The getattr(obj, name[, default]) : to access the attribute of object.

The hasattr(obj,name) : to check if an attribute exists or not.

The setattr(obj,name,value) : to set an attribute. If attribute does not exist, then it would be created.

The delattr(obj, name) : to delete an attribute.

hasattr(emp1, 'age') # Returns true if 'age' attribute exists getattr(emp1, 'age') # Returns value of 'age' attribute setattr(emp1, 'age', 8) # Set attribute 'age' at 8 delattr(empl, 'age') # Delete attribute 'age'

Built-In Class Attributes

Every Python class keeps following built-in attributes and they can be accessed using dot operator like any other attribute −

__dict__ − Dictionary containing the class's namespace.

__doc__ − Class documentation string or none, if undefined.

__name__ − Class name.

__module__ − Module name in which the class is defined. This attribute is "__main__" in interactive mode.

__bases__ − A possibly empty tuple containing the base classes, in the order of their occurrence in the base class list.

For the above class let us try to access all these attributes −

#!/usr/bin/python class Employee: 'Common base class for all employees' empCount = 0 def __init__(self, name, salary): self.name = name self.salary = salary Employee.empCount += 1 def displayCount(self): print "Total Employee %d" % Employee.empCount def displayEmployee(self): print "Name : ", self.name, ", Salary: ", self.salary print "Employee.__doc__:", Employee.__doc__ print "Employee.__name__:", Employee.__name__ print "Employee.__module__:", Employee.__module__ print "Employee.__bases__:", Employee.__bases__ print "Employee.__dict__:", Employee.__dict__

When the above code is executed, it produces the following result −

Employee.__doc__: Common base class for all employees Employee.__name__: Employee Employee.__module__: __main__ Employee.__bases__: () Employee.__dict__: {'__module__': '__main__', 'displayCount': <function displayCount at 0xb7c84994>, 'empCount': 2, 'displayEmployee': <function displayEmployee at 0xb7c8441c>, '__doc__': 'Common base class for all employees', '__init__': <function __init__ at 0xb7c846bc>}

Destroying Objects (Garbage Collection)

Python deletes unneeded objects (built-in types or class instances) automatically to free the memory space. The process by which Python periodically reclaims blocks of memory that no longer are in use is termed Garbage Collection.

Python's garbage collector runs during program execution and is triggered when an object's reference count reaches zero. An object's reference count changes as the number of aliases that point to it changes.

An object's reference count increases when it is assigned a new name or placed in a container (list, tuple, or dictionary). The object's reference count decreases when it's deleted with del, its reference is reassigned, or its reference goes out of scope. When an object's reference count reaches zero, Python collects it automatically.

a = 40 # Create object <40> b = a # Increase ref. count of <40> c = [b] # Increase ref. count of <40> del a # Decrease ref. count of <40> b = 100 # Decrease ref. count of <40> c[0] = -1 # Decrease ref. count of <40>

You normally will not notice when the garbage collector destroys an orphaned instance and reclaims its space. But a class can implement the special method __del__(), called a destructor, that is invoked when the instance is about to be destroyed. This method might be used to clean up any non memory resources used by an instance.

Example

This __del__() destructor prints the class name of an instance that is about to be destroyed −

#!/usr/bin/python class Point: def __init( self, x=0, y=0): self.x = x self.y = y def __del__(self): class_name = self.__class__.__name__ print class_name, "destroyed" pt1 = Point() pt2 = pt1 pt3 = pt1 print id(pt1), id(pt2), id(pt3) # prints the ids of the obejcts del pt1 del pt2 del pt3

When the above code is executed, it produces following result −

3083401324 3083401324 3083401324 Point destroyed

Note: Ideally, you should define your classes in separate file, then you should import them in your main program file using import statement.

Class Inheritance

Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing the parent class in parentheses after the new class name.

The child class inherits the attributes of its parent class, and you can use those attributes as if they were defined in the child class. A child class can also override data members and methods from the parent.

Syntax

Derived classes are declared much like their parent class; however, a list of base classes to inherit from is given after the class name −

class SubClassName (ParentClass1[, ParentClass2, ...]): 'Optional class documentation string' class_suite

Example

#!/usr/bin/python class Parent: # define parent class parentAttr = 100 def __init__(self): print "Calling parent constructor" def parentMethod(self): print 'Calling parent method' def setAttr(self, attr): Parent.parentAttr = attr def getAttr(self): print "Parent attribute :", Parent.parentAttr class Child(Parent): # define child class def __init__(self): print "Calling child constructor" def childMethod(self): print 'Calling child method' c = Child() # instance of child c.childMethod() # child calls its method c.parentMethod() # calls parent's method c.setAttr(200) # again call parent's method c.getAttr() # again call parent's method

When the above code is executed, it produces the following result −

Calling child constructor Calling child method Calling parent method Parent attribute : 200

Similar way, you can drive a class from multiple parent classes as follows −

class A: # define your class A ..... class B: # define your class B ..... class C(A, B): # subclass of A and B .....

You can use issubclass() or isinstance() functions to check a relationships of two classes and instances.

The issubclass(sub, sup) boolean function returns true if the given subclass sub is indeed a subclass of the superclass sup.

The isinstance(obj, Class) boolean function returns true if obj is an instance of class Class or is an instance of a subclass of Class

Overriding Methods

You can always override your parent class methods. One reason for overriding parent's methods is because you may want special or different functionality in your subclass.

Example

#!/usr/bin/python class Parent: # define parent class def myMethod(self): print 'Calling parent method' class Child(Parent): # define child class def myMethod(self): print 'Calling child method' c = Child() # instance of child c.myMethod() # child calls overridden method

When the above code is executed, it produces the following result −

Calling child method

Base Overloading Methods

Following table lists some generic functionality that you can override in your own classes −

Sr.No.Method, Description & Sample Call1

__init__ ( self [,args...] )

Constructor (with any optional arguments)

Sample Call : obj = className(args)

2

__del__( self )

Destructor, deletes an object

Sample Call : del obj

3

__repr__( self )

Evaluatable string representation

Sample Call : repr(obj)

4

__str__( self )

Printable string representation

Sample Call : str(obj)

5

__cmp__ ( self, x )

Object comparison

Sample Call : cmp(obj, x)

Overloading Operators

Suppose you have created a Vector class to represent two-dimensional vectors, what happens when you use the plus operator to add them? Most likely Python will yell at you.

You could, however, define the __add__ method in your class to perform vector addition and then the plus operator would behave as per expectation −

Example

#!/usr/bin/python class Vector: def __init__(self, a, b): self.a = a self.b = b def __str__(self): return 'Vector (%d, %d)' % (self.a, self.b) def __add__(self,other): return Vector(self.a + other.a, self.b + other.b) v1 = Vector(2,10) v2 = Vector(5,-2) print v1 + v2

When the above code is executed, it produces the following result −

Vector(7,8)

Data Hiding

An object's attributes may or may not be visible outside the class definition. You need to name attributes with a double underscore prefix, and those attributes then are not be directly visible to outsiders.

Example

#!/usr/bin/python class JustCounter: __secretCount = 0 def count(self): self.__secretCount += 1 print self.__secretCount counter = JustCounter() counter.count() counter.count() print counter.__secretCount

When the above code is executed, it produces the following result −

1 2 Traceback (most recent call last): File "test.py", line 12, in <module> print counter.__secretCount AttributeError: JustCounter instance has no attribute '__secretCount'

Python protects those members by internally changing the name to include the class name. You can access such attributes as object._className__attrName. If you would replace your last line as following, then it works for you −

......................... print counter._JustCounter__secretCount

When the above code is executed, it produces the following result −

1 2 2
Python - Regular Expressions

regular expression is a special sequence of characters that helps you match or find other strings or sets of strings, using a specialized syntax held in a pattern. Regular expressions are widely used in UNIX world.

The module re provides full support for Perl-like regular expressions in Python. The re module raises the exception re.error if an error occurs while compiling or using a regular expression.

We would cover two important functions, which would be used to handle regular expressions. But a small thing first: There are various characters, which would have special meaning when they are used in regular expression. To avoid any confusion while dealing with regular expressions, we would use Raw Strings as r'expression'.

The match Function

This function attempts to match RE pattern to string with optional flags.

Here is the syntax for this function −

re.match(pattern, string, flags = 0)

Here is the description of the parameters −

Sr.No.Parameter & Description1

pattern

This is the regular expression to be matched.

2

string

This is the string, which would be searched to match the pattern at the beginning of string.

3

flags

You can specify different flags using bitwise OR (|). These are modifiers, which are listed in the table below.

The re.match function returns a match object on success, None on failure. We usegroup(num) or groups() function of match object to get matched expression.

Sr.No.Match Object Method & Description1

group(num = 0)

This method returns entire match (or specific subgroup num)

2

groups()

This method returns all matching subgroups in a tuple (empty if there weren't any)

Example

#!/usr/bin/python import re line = "Cats are smarter than dogs" matchObj = re.match( r'(.*) are (.*?) .*', line, re.M|re.I) if matchObj: print "matchObj.group() : ", matchObj.group() print "matchObj.group(1) : ", matchObj.group(1) print "matchObj.group(2) : ", matchObj.group(2) else: print "No match!!"

When the above code is executed, it produces following result −

matchObj.group() : Cats are smarter than dogs matchObj.group(1) : Cats matchObj.group(2) : smarter

The search Function

This function searches for first occurrence of RE pattern within string with optional flags.

Here is the syntax for this function −

re.search(pattern, string, flags = 0)

Here is the description of the parameters −

Sr.No.Parameter & Description1

pattern

This is the regular expression to be matched.

2

string

This is the string, which would be searched to match the pattern anywhere in the string.

3

flags

You can specify different flags using bitwise OR (|). These are modifiers, which are listed in the table below.

The re.search function returns a match object on success, none on failure. We use group(num) or groups() function of match object to get matched expression.

Sr.No.Match Object Method & Description1

group(num=0)

This method returns entire match (or specific subgroup num)

2

groups()

This method returns all matching subgroups in a tuple (empty if there weren't any)

Example

#!/usr/bin/python import re line = "Cats are smarter than dogs"; searchObj = re.search( r'(.*) are (.*?) .*', line, re.M|re.I) if searchObj: print "searchObj.group() : ", searchObj.group() print "searchObj.group(1) : ", searchObj.group(1) print "searchObj.group(2) : ", searchObj.group(2) else: print "Nothing found!!"

When the above code is executed, it produces following result −

matchObj.group() : Cats are smarter than dogs matchObj.group(1) : Cats matchObj.group(2) : smarter

Matching Versus Searching

Python offers two different primitive operations based on regular expressions: match checks for a match only at the beginning of the string, while search checks for a match anywhere in the string (this is what Perl does by default).

Example

#!/usr/bin/python import re line = "Cats are smarter than dogs"; matchObj = re.match( r'dogs', line, re.M|re.I) if matchObj: print "match --> matchObj.group() : ", matchObj.group() else: print "No match!!" searchObj = re.search( r'dogs', line, re.M|re.I) if searchObj: print "search --> searchObj.group() : ", searchObj.group() else: print "Nothing found!!"

When the above code is executed, it produces the following result −

No match!! search --> matchObj.group() : dogs

Search and Replace

One of the most important re methods that use regular expressions is sub.

Syntax

re.sub(pattern, repl, string, max=0)

This method replaces all occurrences of the RE pattern in string with repl, substituting all occurrences unless max provided. This method returns modified string.

Example

#!/usr/bin/python import re phone = "2004-959-559 # This is Phone Number" # Delete Python-style comments num = re.sub(r'#.*$', "", phone) print "Phone Num : ", num # Remove anything other than digits num = re.sub(r'\D', "", phone) print "Phone Num : ", num

When the above code is executed, it produces the following result −

Phone Num : 2004-959-559 Phone Num : 2004959559

Regular Expression Modifiers: Option Flags

Regular expression literals may include an optional modifier to control various aspects of matching. The modifiers are specified as an optional flag. You can provide multiple modifiers using exclusive OR (|), as shown previously and may be represented by one of these −

Sr.No.Modifier & Description1

re.I

Performs case-insensitive matching.

2

re.L

Interprets words according to the current locale. This interpretation affects the alphabetic group (\w and \W), as well as word boundary behavior (\b and \B).

3

re.M

Makes $ match the end of a line (not just the end of the string) and makes ^ match the start of any line (not just the start of the string).

4

re.S

Makes a period (dot) match any character, including a newline.

5

re.U

Interprets letters according to the Unicode character set. This flag affects the behavior of \w, \W, \b, \B.

6

re.X

Permits "cuter" regular expression syntax. It ignores whitespace (except inside a set [] or when escaped by a backslash) and treats unescaped # as a comment marker.

Regular Expression Patterns

Except for control characters, (+ ? . * ^ $ ( ) [ ] { } | \), all characters match themselves. You can escape a control character by preceding it with a backslash.

Following table lists the regular expression syntax that is available in Python −

Sr.No.Pattern & Description1

^

Matches beginning of line.

2

$

Matches end of line.

3

.

Matches any single character except newline. Using m option allows it to match newline as well.

4

[...]

Matches any single character in brackets.

5

[^...]

Matches any single character not in brackets

6

re*

Matches 0 or more occurrences of preceding expression.

7

re+

Matches 1 or more occurrence of preceding expression.

8

re?

Matches 0 or 1 occurrence of preceding expression.

9

re{ n}

Matches exactly n number of occurrences of preceding expression.

10

re{ n,}

Matches n or more occurrences of preceding expression.

11

re{ n, m}

Matches at least n and at most m occurrences of preceding expression.

12

a| b

Matches either a or b.

13

(re)

Groups regular expressions and remembers matched text.

14

(?imx)

Temporarily toggles on i, m, or x options within a regular expression. If in parentheses, only that area is affected.

15

(?-imx)

Temporarily toggles off i, m, or x options within a regular expression. If in parentheses, only that area is affected.

16

(?: re)

Groups regular expressions without remembering matched text.

17

(?imx: re)

Temporarily toggles on i, m, or x options within parentheses.

18

(?-imx: re)

Temporarily toggles off i, m, or x options within parentheses.

19

(?#...)

Comment.

20

(?= re)

Specifies position using a pattern. Doesn't have a range.

21

(?! re)

Specifies position using pattern negation. Doesn't have a range.

22

(?> re)

Matches independent pattern without backtracking.

23

\w

Matches word characters.

24

\W

Matches nonword characters.

25

\s

Matches whitespace. Equivalent to [\t\n\r\f].

26

\S

Matches nonwhitespace.

27

\d

Matches digits. Equivalent to [0-9].

28

\D

Matches nondigits.

29

\A

Matches beginning of string.

30

\Z

Matches end of string. If a newline exists, it matches just before newline.

31

\z

Matches end of string.

32

\G

Matches point where last match finished.

33

\b

Matches word boundaries when outside brackets. Matches backspace (0x08) when inside brackets.

34

\B

Matches nonword boundaries.

35

\n, \t, etc.

Matches newlines, carriage returns, tabs, etc.

36

\1...\9

Matches nth grouped subexpression.

37

\10

Matches nth grouped subexpression if it matched already. Otherwise refers to the octal representation of a character code.

Regular Expression Examples

Literal characters

Sr.No.Example & Description1

python

Match "python".

Character classes

Sr.No.Example & Description1

[Pp]ython

Match "Python" or "python"

2

rub[ye]

Match "ruby" or "rube"

3

[aeiou]

Match any one lowercase vowel

4

[0-9]

Match any digit; same as [0123456789]

5

[a-z]

Match any lowercase ASCII letter

6

[A-Z]

Match any uppercase ASCII letter

7

[a-zA-Z0-9]

Match any of the above

8

[^aeiou]

Match anything other than a lowercase vowel

9

[^0-9]

Match anything other than a digit

Special Character Classes

Sr.No.Example & Description1

.

Match any character except newline

2

\d

Match a digit: [0-9]

3

\D

Match a nondigit: [^0-9]

4

\s

Match a whitespace character: [ \t\r\n\f]

5

\S

Match nonwhitespace: [^ \t\r\n\f]

6

\w

Match a single word character: [A-Za-z0-9_]

7

\W

Match a nonword character: [^A-Za-z0-9_]

Repetition Cases

Sr.No.Example & Description1

ruby?

Match "rub" or "ruby": the y is optional

2

ruby*

Match "rub" plus 0 or more ys

3

ruby+

Match "rub" plus 1 or more ys

4

\d{3}

Match exactly 3 digits

5

\d{3,}

Match 3 or more digits

6

\d{3,5}

Match 3, 4, or 5 digits

Nongreedy repetition

This matches the smallest number of repetitions −

Sr.No.Example & Description1

<.*>

Greedy repetition: matches "<python>perl>"

2

<.*?>

Nongreedy: matches "<python>" in "<python>perl>"

Grouping with Parentheses

Sr.No.Example & Description1

\D\d+

No group: + repeats \d

2

(\D\d)+

Grouped: + repeats \D\d pair

3

([Pp]ython(, )?)+

Match "Python", "Python, python, python", etc.

Backreferences

This matches a previously matched group again −

Sr.No.Example & Description1

([Pp])ython&\1ails

Match python&pails or Python&Pails

2

(['"])[^\1]*\1

Single or double-quoted string. \1 matches whatever the 1st group matched. \2 matches whatever the 2nd group matched, etc.

Alternatives

Sr.No.Example & Description1

python|perl

Match "python" or "perl"

2

rub(y|le))

Match "ruby" or "ruble"

3

Python(!+|\?)

"Python" followed by one or more ! or one ?

Anchors

This needs to specify match position.

Sr.No.Example & Description1

^Python

Match "Python" at the start of a string or internal line

2

Python$

Match "Python" at the end of a string or line

3

\APython

Match "Python" at the start of a string

4

Python\Z

Match "Python" at the end of a string

5

\bPython\b

Match "Python" at a word boundary

6

\brub\B

\B is nonword boundary: match "rub" in "rube" and "ruby" but not alone

7

Python(?=!)

Match "Python", if followed by an exclamation point.

8

Python(?!!)

Match "Python", if not followed by an exclamation point.

Special Syntax with Parentheses

Sr.No.Example & Description1

R(?#comment)

Matches "R". All the rest is a comment

2

R(?i)uby

Case-insensitive while matching "uby"

3

R(?i:uby)

Same as above

4

rub(?:y|le))

Group only without creating \1 backreference
Python - CGI Programming

The Common Gateway Interface, or CGI, is a set of standards that define how information is exchanged between the web server and a custom script. The CGI specs are currently maintained by the NCSA.

What is CGI?

The Common Gateway Interface, or CGI, is a standard for external gateway programs to interface with information servers such as HTTP servers.

The current version is CGI/1.1 and CGI/1.2 is under progress.

Web Browsing

To understand the concept of CGI, let us see what happens when we click a hyper link to browse a particular web page or URL.

Your browser contacts the HTTP web server and demands for the URL, i.e., filename.

Web Server parses the URL and looks for the filename. If it finds that file then sends it back to the browser, otherwise sends an error message indicating that you requested a wrong file.

Web browser takes response from web server and displays either the received file or error message.

However, it is possible to set up the HTTP server so that whenever a file in a certain directory is requested that file is not sent back; instead it is executed as a program, and whatever that program outputs is sent back for your browser to display. This function is called the Common Gateway Interface or CGI and the programs are called CGI scripts. These CGI programs can be a Python Script, PERL Script, Shell Script, C or C++ program, etc.

Web Server Support and Configuration

Before you proceed with CGI Programming, make sure that your Web Server supports CGI and it is configured to handle CGI Programs. All the CGI Programs to be executed by the HTTP server are kept in a pre-configured directory. This directory is called CGI Directory and by convention it is named as /var/www/cgi-bin. By convention, CGI files have extension as.cgi, but you can keep your files with python extension .py as well.

By default, the Linux server is configured to run only the scripts in the cgi-bin directory in /var/www. If you want to specify any other directory to run your CGI scripts, comment the following lines in the httpd.conf file −

<Directory "/var/www/cgi-bin"> AllowOverride None Options ExecCGI Order allow,deny Allow from all </Directory> <Directory "/var/www/cgi-bin"> Options All </Directory>

Here, we assume that you have Web Server up and running successfully and you are able to run any other CGI program like Perl or Shell, etc.

First CGI Program

Here is a simple link, which is linked to a CGI script called hello.py. This file is kept in /var/www/cgi-bin directory and it has following content. Before running your CGI program, make sure you have change mode of file using chmod 755 hello.py UNIX command to make file executable.

#!/usr/bin/python print "Content-type:text/html\r\n\r\n" print '<html>' print '<head>' print '<title>Hello Word - First CGI Program</title>' print '</head>' print '<body>' print '<h2>Hello Word! This is my first CGI program</h2>' print '</body>' print '</html>'

If you click hello.py, then this produces the following output −

Hello Word! This is my first CGI program

This hello.py script is a simple Python script, which writes its output on STDOUT file, i.e., screen. There is one important and extra feature available which is first line to be printed Content-type:text/html\r\n\r\n. This line is sent back to the browser and it specifies the content type to be displayed on the browser screen.

By now you must have understood basic concept of CGI and you can write many complicated CGI programs using Python. This script can interact with any other external system also to exchange information such as RDBMS.

HTTP Header

The line Content-type:text/html\r\n\r\n is part of HTTP header which is sent to the browser to understand the content. All the HTTP header will be in the following form −

HTTP Field Name: Field Content For Example Content-type: text/html\r\n\r\n

There are few other important HTTP headers, which you will use frequently in your CGI Programming.

Sr.No.Header & Description1

Content-type:

A MIME string defining the format of the file being returned. Example is Content-type:text/html

2

Expires: Date

The date the information becomes invalid. It is used by the browser to decide when a page needs to be refreshed. A valid date string is in the format 01 Jan 1998 12:00:00 GMT.

3

Location: URL

The URL that is returned instead of the URL requested. You can use this field to redirect a request to any file.

4

Last-modified: Date

The date of last modification of the resource.

5

Content-length: N

The length, in bytes, of the data being returned. The browser uses this value to report the estimated download time for a file.

6

Set-Cookie: String

Set the cookie passed through the string

CGI Environment Variables

All the CGI programs have access to the following environment variables. These variables play an important role while writing any CGI program.

Sr.No.Variable Name & Description1

CONTENT_TYPE

The data type of the content. Used when the client is sending attached content to the server. For example, file upload.

2

CONTENT_LENGTH

The length of the query information. It is available only for POST requests.

3

HTTP_COOKIE

Returns the set cookies in the form of key & value pair.

4

HTTP_USER_AGENT

The User-Agent request-header field contains information about the user agent originating the request. It is name of the web browser.

5

PATH_INFO

The path for the CGI script.

6

QUERY_STRING

The URL-encoded information that is sent with GET method request.

7

REMOTE_ADDR

The IP address of the remote host making the request. This is useful logging or for authentication.

8

REMOTE_HOST

The fully qualified name of the host making the request. If this information is not available, then REMOTE_ADDR can be used to get IR address.

9

REQUEST_METHOD

The method used to make the request. The most common methods are GET and POST.

10

SCRIPT_FILENAME

The full path to the CGI script.

11

SCRIPT_NAME

The name of the CGI script.

12

SERVER_NAME

The server's hostname or IP Address

13

SERVER_SOFTWARE

The name and version of the software the server is running.

Here is small CGI program to list out all the CGI variables.

#!/usr/bin/python import os print "Content-type: text/html\r\n\r\n"; print "<font size = +1>Environment</font><\br>"; for param in os.environ.keys(): print "<b>%20s</b>: %s<\br>" % (param, os.environ[param])

GET and POST Methods

You must have come across many situations when you need to pass some information from your browser to web server and ultimately to your CGI Program. Most frequently, browser uses two methods two pass this information to web server. These methods are GET Method and POST Method.

Passing Information using GET method

The GET method sends the encoded user information appended to the page request. The page and the encoded information are separated by the ? character as follows −

http://www.test.com/cgi-bin/hello.py?key1=value1&key2=value2

The GET method is the default method to pass information from browser to web server and it produces a long string that appears in your browser's Location:box. Never use GET method if you have password or other sensitive information to pass to the server. The GET method has size limtation: only 1024 characters can be sent in a request string. The GET method sends information using QUERY_STRING header and will be accessible in your CGI Program through QUERY_STRING environment variable.

You can pass information by simply concatenating key and value pairs along with any URL or you can use HTML <FORM> tags to pass information using GET method.

Simple URL Example:Get Method

Here is a simple URL, which passes two values to hello_get.py program using GET method.

/cgi-bin/hello_get.py?first_name = ZARA&last_name = ALI

Below is hello_get.py script to handle input given by web browser. We are going to use cgi module, which makes it very easy to access passed information −

#!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields first_name = form.getvalue('first_name') last_name = form.getvalue('last_name') print "Content-type:text/html\r\n\r\n" print "<html>" print "<head>" print "<title>Hello - Second CGI Program</title>" print "</head>" print "<body>" print "<h2>Hello %s %s</h2>" % (first_name, last_name) print "</body>" print "</html>"

This would generate the following result −

Hello ZARA ALI

Simple FORM Example:GET Method

This example passes two values using HTML FORM and submit button. We use same CGI script hello_get.py to handle this input.

<form action = "/cgi-bin/hello_get.py" method = "get"> First Name: <input type = "text" name = "first_name"> <br /><br /> Last Name: <input type = "text" name = "last_name" /> <input type = "submit" value = "Submit" /> </form>

Here is the actual output of the above form, you enter First and Last Name and then click submit button to see the result.

First Name: 

Last Name:  

Passing Information Using POST Method

A generally more reliable method of passing information to a CGI program is the POST method. This packages the information in exactly the same way as GET methods, but instead of sending it as a text string after a ? in the URL it sends it as a separate message. This message comes into the CGI script in the form of the standard input.

Below is same hello_get.py script which handles GET as well as POST method.

#!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields first_name = form.getvalue('first_name') last_name = form.getvalue('last_name') print "Content-type:text/html\r\n\r\n" print "<html>" print "<head>" print "<title>Hello - Second CGI Program</title>" print "</head>" print "<body>" print "<h2>Hello %s %s</h2>" % (first_name, last_name) print "</body>" print "</html>"

Let us take again same example as above which passes two values using HTML FORM and submit button. We use same CGI script hello_get.py to handle this input.

<form action = "/cgi-bin/hello_get.py" method = "post"> First Name: <input type = "text" name = "first_name"><br /><br /> Last Name: <input type = "text" name = "last_name" /> <input type = "submit" value = "Submit" /> </form>

Here is the actual output of the above form. You enter First and Last Name and then click submit button to see the result.

First Name: 

Last Name:  

Passing Checkbox Data to CGI Program

Checkboxes are used when more than one option is required to be selected.

Here is example HTML code for a form with two checkboxes −

<form action = "/cgi-bin/checkbox.cgi" method = "POST" target = "_blank"> <input type = "checkbox" name = "maths" value = "on" /> Maths <input type = "checkbox" name = "physics" value = "on" /> Physics <input type = "submit" value = "Select Subject" /> </form>

The result of this code is the following form −

 Maths  Physics 

Below is checkbox.cgi script to handle input given by web browser for checkbox button.

#!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('maths'): math_flag = "ON" else: math_flag = "OFF" if form.getvalue('physics'): physics_flag = "ON" else: physics_flag = "OFF" print "Content-type:text/html\r\n\r\n" print "<html>" print "<head>" print "<title>Checkbox - Third CGI Program</title>" print "</head>" print "<body>" print "<h2> CheckBox Maths is : %s</h2>" % math_flag print "<h2> CheckBox Physics is : %s</h2>" % physics_flag print "</body>" print "</html>"

Passing Radio Button Data to CGI Program

Radio Buttons are used when only one option is required to be selected.

Here is example HTML code for a form with two radio buttons −

<form action = "/cgi-bin/radiobutton.py" method = "post" target = "_blank"> <input type = "radio" name = "subject" value = "maths" /> Maths <input type = "radio" name = "subject" value = "physics" /> Physics <input type = "submit" value = "Select Subject" /> </form>

The result of this code is the following form −

 Maths  Physics 

Below is radiobutton.py script to handle input given by web browser for radio button −

#!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('subject'): subject = form.getvalue('subject') else: subject = "Not set" print "Content-type:text/html\r\n\r\n" print "<html>" print "<head>" print "<title>Radio - Fourth CGI Program</title>" print "</head>" print "<body>" print "<h2> Selected Subject is %s</h2>" % subject print "</body>" print "</html>"

Passing Text Area Data to CGI Program

TEXTAREA element is used when multiline text has to be passed to the CGI Program.

Here is example HTML code for a form with a TEXTAREA box −

<form action = "/cgi-bin/textarea.py" method = "post" target = "_blank"> <textarea name = "textcontent" cols = "40" rows = "4"> Type your text here... </textarea> <input type = "submit" value = "Submit" /> </form>

The result of this code is the following form −

 

Below is textarea.cgi script to handle input given by web browser −

#!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('textcontent'): text_content = form.getvalue('textcontent') else: text_content = "Not entered" print "Content-type:text/html\r\n\r\n" print "<html>" print "<head>"; print "<title>Text Area - Fifth CGI Program</title>" print "</head>" print "<body>" print "<h2> Entered Text Content is %s</h2>" % text_content print "</body>"

Passing Drop Down Box Data to CGI Program

Drop Down Box is used when we have many options available but only one or two will be selected.

Here is example HTML code for a form with one drop down box −

<form action = "/cgi-bin/dropdown.py" method = "post" target = "_blank"> <select name = "dropdown"> <option value = "Maths" selected>Maths</option> <option value = "Physics">Physics</option> </select> <input type = "submit" value = "Submit"/> </form>

The result of this code is the following form −

 Maths Physics  

Below is dropdown.py script to handle input given by web browser.

#!/usr/bin/python # Import modules for CGI handling import cgi, cgitb # Create instance of FieldStorage form = cgi.FieldStorage() # Get data from fields if form.getvalue('dropdown'): subject = form.getvalue('dropdown') else: subject = "Not entered" print "Content-type:text/html\r\n\r\n" print "<html>" print "<head>" print "<title>Dropdown Box - Sixth CGI Program</title>" print "</head>" print "<body>" print "<h2> Selected Subject is %s</h2>" % subject print "</body>" print "</html>"

Using Cookies in CGI

HTTP protocol is a stateless protocol. For a commercial website, it is required to maintain session information among different pages. For example, one user registration ends after completing many pages. How to maintain user's session information across all the web pages?

In many situations, using cookies is the most efficient method of remembering and tracking preferences, purchases, commissions, and other information required for better visitor experience or site statistics.

How It Works?

Your server sends some data to the visitor's browser in the form of a cookie. The browser may accept the cookie. If it does, it is stored as a plain text record on the visitor's hard drive. Now, when the visitor arrives at another page on your site, the cookie is available for retrieval. Once retrieved, your server knows/remembers what was stored.

Cookies are a plain text data record of 5 variable-length fields −

Expires − The date the cookie will expire. If this is blank, the cookie will expire when the visitor quits the browser.

Domain − The domain name of your site.

Path − The path to the directory or web page that sets the cookie. This may be blank if you want to retrieve the cookie from any directory or page.

Secure − If this field contains the word "secure", then the cookie may only be retrieved with a secure server. If this field is blank, no such restriction exists.

Name = Value − Cookies are set and retrieved in the form of key and value pairs.

Setting up Cookies

It is very easy to send cookies to browser. These cookies are sent along with HTTP Header before to Content-type field. Assuming you want to set UserID and Password as cookies. Setting the cookies is done as follows −

#!/usr/bin/python print "Set-Cookie:UserID = XYZ;\r\n" print "Set-Cookie:Password = XYZ123;\r\n" print "Set-Cookie:Expires = Tuesday, 31-Dec-2007 23:12:40 GMT";\r\n" print "Set-Cookie:Domain = www.tutorialspoint.com;\r\n" print "Set-Cookie:Path = /perl;\n" print "Content-type:text/html\r\n\r\n" ...........Rest of the HTML Content....

From this example, you must have understood how to set cookies. We use Set-Cookie HTTP header to set cookies.

It is optional to set cookies attributes like Expires, Domain, and Path. It is notable that cookies are set before sending magic line "Content-type:text/html\r\n\r\n.

Retrieving Cookies

It is very easy to retrieve all the set cookies. Cookies are stored in CGI environment variable HTTP_COOKIE and they will have following form −

key1 = value1;key2 = value2;key3 = value3....

Here is an example of how to retrieve cookies.

#!/usr/bin/python # Import modules for CGI handling from os import environ import cgi, cgitb if environ.has_key('HTTP_COOKIE'): for cookie in map(strip, split(environ['HTTP_COOKIE'], ';')): (key, value ) = split(cookie, '='); if key == "UserID": user_id = value if key == "Password": password = value print "User ID = %s" % user_id print "Password = %s" % password

This produces the following result for the cookies set by above script −

User ID = XYZ Password = XYZ123

File Upload Example

To upload a file, the HTML form must have the enctype attribute set to multipart/form-data. The input tag with the file type creates a "Browse" button.

<html> <body> <form enctype = "multipart/form-data" action = "save_file.py" method = "post"> <p>File: <input type = "file" name = "filename" /></p> <p><input type = "submit" value = "Upload" /></p> </form> </body> </html>

The result of this code is the following form −

File: 

Above example has been disabled intentionally to save people uploading file on our server, but you can try above code with your server.

Here is the script save_file.py to handle file upload −

#!/usr/bin/python import cgi, os import cgitb; cgitb.enable() form = cgi.FieldStorage() # Get filename here. fileitem = form['filename'] # Test if the file was uploaded if fileitem.filename: # strip leading path from file name to avoid # directory traversal attacks fn = os.path.basename(fileitem.filename) open('/tmp/' + fn, 'wb').write(fileitem.file.read()) message = 'The file "' + fn + '" was uploaded successfully' else: message = 'No file was uploaded' print """\ Content-Type: text/html\n <html> <body> <p>%s</p> </body> </html> """ % (message,)

If you run the above script on Unix/Linux, then you need to take care of replacing file separator as follows, otherwise on your windows machine above open() statement should work fine.

fn = os.path.basename(fileitem.filename.replace("\\", "/" ))

How To Raise a "File Download" Dialog Box ?

Sometimes, it is desired that you want to give option where a user can click a link and it will pop up a "File Download" dialogue box to the user instead of displaying actual content. This is very easy and can be achieved through HTTP header. This HTTP header is be different from the header mentioned in previous section.

For example, if you want make a FileName file downloadable from a given link, then its syntax is as follows −

#!/usr/bin/python # HTTP Header print "Content-Type:application/octet-stream; name = \"FileName\"\r\n"; print "Content-Disposition: attachment; filename = \"FileName\"\r\n\n"; # Actual File Content will go here. fo = open("foo.txt", "rb") str = fo.read(); print str # Close opend file fo.close()
Python - MySQL Database Access

The Python standard for database interfaces is the Python DB-API. Most Python database interfaces adhere to this standard.

You can choose the right database for your application. Python Database API supports a wide range of database servers such as −

GadFlymSQLMySQLPostgreSQLMicrosoft SQL Server 2000InformixInterbaseOracleSybase

Here is the list of available Python database interfaces: Python Database Interfaces and APIs .You must download a separate DB API module for each database you need to access. For example, if you need to access an Oracle database as well as a MySQL database, you must download both the Oracle and the MySQL database modules.

The DB API provides a minimal standard for working with databases using Python structures and syntax wherever possible. This API includes the following −

Importing the API module.Acquiring a connection with the database.Issuing SQL statements and stored procedures.Closing the connection

We would learn all the concepts using MySQL, so let us talk about MySQLdb module.

What is MySQLdb?

MySQLdb is an interface for connecting to a MySQL database server from Python. It implements the Python Database API v2.0 and is built on top of the MySQL C API.

How do I Install MySQLdb?

Before proceeding, you make sure you have MySQLdb installed on your machine. Just type the following in your Python script and execute it −

#!/usr/bin/python import MySQLdb

If it produces the following result, then it means MySQLdb module is not installed −

Traceback (most recent call last): File "test.py", line 3, in <module> import MySQLdb ImportError: No module named MySQLdb

To install MySQLdb module, use the following command −

For Ubuntu, use the following command - $ sudo apt-get install python-pip python-dev libmysqlclient-dev For Fedora, use the following command - $ sudo dnf install python python-devel mysql-devel redhat-rpm-config gcc For Python command prompt, use the following command - pip install MySQL-python

Note − Make sure you have root privilege to install above module.

Database Connection

Before connecting to a MySQL database, make sure of the followings −

You have created a database TESTDB.You have created a table EMPLOYEE in TESTDB.This table has fields FIRST_NAME, LAST_NAME, AGE, SEX and INCOME.User ID "testuser" and password "test123" are set to access TESTDB.Python module MySQLdb is installed properly on your machine.You have gone through MySQL tutorial to understand MySQL Basics.

Example

Following is the example of connecting with MySQL database "TESTDB"

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # execute SQL query using execute() method. cursor.execute("SELECT VERSION()") # Fetch a single row using fetchone() method. data = cursor.fetchone() print "Database version : %s " % data # disconnect from server db.close()

While running this script, it is producing the following result in my Linux machine.

Database version : 5.0.45

If a connection is established with the datasource, then a Connection Object is returned and saved into db for further use, otherwise db is set to None. Next, db object is used to create a cursor object, which in turn is used to execute SQL queries. Finally, before coming out, it ensures that database connection is closed and resources are released.

Creating Database Table

Once a database connection is established, we are ready to create tables or records into the database tables using execute method of the created cursor.

Example

Let us create Database table EMPLOYEE −

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # Drop table if it already exist using execute() method. cursor.execute ("DROP TABLE IF EXISTS EMPLOYEE") # Create table as per requirement sql = """CREATE TABLE EMPLOYEE ( FIRST_NAME CHAR(20) NOT NULL, LAST_NAME CHAR(20), AGE INT, SEX CHAR(1), INCOME FLOAT )""" cursor.execute(sql) # disconnect from server db.close()

INSERT Operation

It is required when you want to create your records into a database table.

Example

The following example, executes SQL INSERT statement to create a record into EMPLOYEE table −

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # Prepare SQL query to INSERT a record into the database. sql = """INSERT INTO EMPLOYEE(FIRST_NAME, LAST_NAME, AGE, SEX, INCOME) VALUES ('Mac', 'Mohan', 20, 'M', 2000)""" try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close()

Above example can be written as follows to create SQL queries dynamically −

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # Prepare SQL query to INSERT a record into the database. sql = "INSERT INTO EMPLOYEE(FIRST_NAME, \ LAST_NAME, AGE, SEX, INCOME) \ VALUES ('%s', '%s', '%d', '%c', '%d' )" % \ ('Mac', 'Mohan', 20, 'M', 2000) try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close()

Example

Following code segment is another form of execution where you can pass parameters directly −

.................................. user_id = "test123" password = "password" con.execute('insert into Login values("%s", "%s")' % \ (user_id, password)) ..................................

READ Operation

READ Operation on any database means to fetch some useful information from the database.

Once our database connection is established, you are ready to make a query into this database. You can use either fetchone() method to fetch single record or fetchall() method to fetech multiple values from a database table.

fetchone() − It fetches the next row of a query result set. A result set is an object that is returned when a cursor object is used to query a table.

fetchall() − It fetches all the rows in a result set. If some rows have already been extracted from the result set, then it retrieves the remaining rows from the result set.

rowcount − This is a read-only attribute and returns the number of rows that were affected by an execute() method.

Example

The following procedure queries all the records from EMPLOYEE table having salary more than 1000 −

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # Prepare SQL query to INSERT a record into the database. sql = "SELECT * FROM EMPLOYEE \ WHERE INCOME > '%d'" % (1000) try: # Execute the SQL command cursor.execute(sql) # Fetch all the rows in a list of lists. results = cursor.fetchall() for row in results: fname = row[0] lname = row[1] age = row[2] sex = row[3] income = row[4] # Now print fetched result print "fname=%s,lname=%s,age=%d,sex=%s,income=%d" % \ (fname, lname, age, sex, income ) except: print "Error: unable to fecth data" # disconnect from server db.close()

This will produce the following result −

fname = Mac, lname = Mohan, age = 20, sex = M, income = 2000

Update Operation

UPDATE Operation on any database means to update one or more records, which are already available in the database.

The following procedure updates all the records having SEX as 'M'. Here, we increase AGE of all the males by one year.

Example

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # Prepare SQL query to UPDATE required records sql = "UPDATE EMPLOYEE SET AGE = AGE + 1 WHERE SEX = '%c'" % ('M') try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close()

DELETE Operation

DELETE operation is required when you want to delete some records from your database. Following is the procedure to delete all the records from EMPLOYEE where AGE is more than 20 −

Example

#!/usr/bin/python import MySQLdb # Open database connection db = MySQLdb.connect ("localhost","testuser","test123","TESTDB" ) # prepare a cursor object using cursor()method cursor = db.cursor() # Prepare SQL query to DELETE required records sql = "DELETE FROM EMPLOYEE WHERE AGE > '%d'" % (20) try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback() # disconnect from server db.close()

Performing Transactions

Transactions are a mechanism that ensures data consistency. Transactions have the following four properties −

Atomicity − Either a transaction completes or nothing happens at all.

Consistency − A transaction must start in a consistent state and leave the system in a consistent state.

Isolation − Intermediate results of a transaction are not visible outside the current transaction.

Durability − Once a transaction was committed, the effects are persistent, even after a system failure.

The Python DB API 2.0 provides two methods to either commit or rollback a transaction.

Example

You already know how to implement transactions. Here is again similar example −

# Prepare SQL query to DELETE required records sql = "DELETE FROM EMPLOYEE WHERE AGE > '%d'" % (20) try: # Execute the SQL command cursor.execute(sql) # Commit your changes in the database db.commit() except: # Rollback in case there is any error db.rollback()

COMMIT Operation

Commit is the operation, which gives a green signal to database to finalize the changes, and after this operation, no change can be reverted back.

Here is a simple example to call commit method.

db.commit()

ROLLBACK Operation

If you are not satisfied with one or more of the changes and you want to revert back those changes completely, then use rollback() method.

Here is a simple example to call rollback() method.

db.rollback()

Disconnecting Database

To disconnect Database connection, use close() method.

db.close()

If the connection to a database is closed by the user with the close() method, any outstanding transactions are rolled back by the DB. However, instead of depending on any of DB lower level implementation details, your application would be better off calling commit or rollback explicitly.

Handling Errors

There are many sources of errors. A few examples are a syntax error in an executed SQL statement, a connection failure, or calling the fetch method for an already canceled or finished statement handle.

The DB API defines a number of errors that must exist in each database module. The following table lists these exceptions.

Sr.No.Exception & Description1

Warning

Used for non-fatal issues. Must subclass StandardError.

2

Error

Base class for errors. Must subclass StandardError.

3

InterfaceError

Used for errors in the database module, not the database itself. Must subclass Error.

4

DatabaseError

Used for errors in the database. Must subclass Error.

5

DataError

Subclass of DatabaseError that refers to errors in the data.

6

OperationalError

Subclass of DatabaseError that refers to errors such as the loss of a connection to the database. These errors are generally outside of the control of the Python scripter.

7

IntegrityError

Subclass of DatabaseError for situations that would damage the relational integrity, such as uniqueness constraints or foreign keys.

8

InternalError

Subclass of DatabaseError that refers to errors internal to the database module, such as a cursor no longer being active.

9

ProgrammingError

Subclass of DatabaseError that refers to errors such as a bad table name and other things that can safely be blamed on you.

10

NotSupportedError

Subclass of DatabaseError that refers to trying to call unsupported functionality.

Your Python scripts should handle these errors, but before using any of the above exceptions, make sure your MySQLdb has support for that exception. You can get more information about them by reading the DB API 2.0 specification.

Python - Networking Programming

Python provides two levels of access to network services. At a low level, you can access the basic socket support in the underlying operating system, which allows you to implement clients and servers for both connection-oriented and connectionless protocols.

Python also has libraries that provide higher-level access to specific application-level network protocols, such as FTP, HTTP, and so on.

This chapter gives you understanding on most famous concept in Networking - Socket Programming.

What is Sockets?

Sockets are the endpoints of a bidirectional communications channel. Sockets may communicate within a process, between processes on the same machine, or between processes on different continents.

Sockets may be implemented over a number of different channel types: Unix domain sockets, TCP, UDP, and so on. The socket library provides specific classes for handling the common transports as well as a generic interface for handling the rest.

Sockets have their own vocabulary −

Sr.No.Term & Description1

domain

The family of protocols that is used as the transport mechanism. These values are constants such as AF_INET, PF_INET, PF_UNIX, PF_X25, and so on.

2

type

The type of communications between the two endpoints, typically SOCK_STREAM for connection-oriented protocols and SOCK_DGRAM for connectionless protocols.

3

protocol

Typically zero, this may be used to identify a variant of a protocol within a domain and type.

4

hostname

The identifier of a network interface −

A string, which can be a host name, a dotted-quad address, or an IPV6 address in colon (and possibly dot) notation

A string "<broadcast>", which specifies an INADDR_BROADCAST address.

A zero-length string, which specifies INADDR_ANY, or

An Integer, interpreted as a binary address in host byte order.

5

port

Each server listens for clients calling on one or more ports. A port may be a Fixnum port number, a string containing a port number, or the name of a service.

The socket Module

To create a socket, you must use the socket.socket() function available in socket module, which has the general syntax −

s = socket.socket (socket_family, socket_type, protocol=0)

Here is the description of the parameters −

socket_family − This is either AF_UNIX or AF_INET, as explained earlier.

socket_type − This is either SOCK_STREAM or SOCK_DGRAM.

protocol − This is usually left out, defaulting to 0.

Once you have socket object, then you can use required functions to create your client or server program. Following is the list of functions required −

Server Socket Methods

Sr.No.Method & Description1

s.bind()

This method binds address (hostname, port number pair) to socket.

2

s.listen()

This method sets up and start TCP listener.

3

s.accept()

This passively accept TCP client connection, waiting until connection arrives (blocking).

Client Socket Methods

Sr.No.Method & Description1

s.connect()

This method actively initiates TCP server connection.

General Socket Methods

Sr.No.Method & Description1

s.recv()

This method receives TCP message

2

s.send()

This method transmits TCP message

3

s.recvfrom()

This method receives UDP message

4

s.sendto()

This method transmits UDP message

5

s.close()

This method closes socket

6

socket.gethostname()

Returns the hostname.

A Simple Server

To write Internet servers, we use the socket function available in socket module to create a socket object. A socket object is then used to call other functions to setup a socket server.

Now call bind(hostname, port) function to specify a port for your service on the given host.

Next, call the accept method of the returned object. This method waits until a client connects to the port you specified, and then returns a connection object that represents the connection to that client.

#!/usr/bin/python # This is server.py file import socket # Import socket module s = socket.socket() # Create a socket object host = socket.gethostname() # Get local machine name port = 12345 # Reserve a port for your service. s.bind((host, port)) # Bind to the port s.listen(5) # Now wait for client connection. while True: c, addr = s.accept() # Establish connection with client. print 'Got connection from', addr c.send('Thank you for connecting') c.close() # Close the connection

A Simple Client

Let us write a very simple client program which opens a connection to a given port 12345 and given host. This is very simple to create a socket client using Python's socket module function.

The socket.connect(hosname, port ) opens a TCP connection to hostname on the port. Once you have a socket open, you can read from it like any IO object. When done, remember to close it, as you would close a file.

The following code is a very simple client that connects to a given host and port, reads any available data from the socket, and then exits −

#!/usr/bin/python # This is client.py file import socket # Import socket module s = socket.socket() # Create a socket object host = socket.gethostname() # Get local machine name port = 12345 # Reserve a port for your service. s.connect((host, port)) print s.recv(1024) s.close # Close the socket when done

Now run this server.py in background and then run above client.py to see the result.

# Following would start a server in background. $ python server.py & # Once server is started run client as follows: $ python client.py

This would produce following result −

Got connection from ('127.0.0.1', 48437) Thank you for connecting

Python Internet modules

A list of some important modules in Python Network/Internet programming.

ProtocolCommon functionPort NoPython moduleHTTPWeb pages80httplib, urllib, xmlrpclibNNTPUsenet news119nntplibFTPFile transfers20ftplib, urllibSMTPSending email25smtplibPOP3Fetching email110poplibIMAP4Fetching email143imaplibTelnetCommand lines23telnetlibGopherDocument transfers70gopherlib, urllib

Please check all the libraries mentioned above to work with FTP, SMTP, POP, and IMAP protocols.
Python - Sending Email using SMTP

Simple Mail Transfer Protocol (SMTP) is a protocol, which handles sending e-mail and routing e-mail between mail servers.

Python provides smtplib module, which defines an SMTP client session object that can be used to send mail to any Internet machine with an SMTP or ESMTP listener daemon.

Here is a simple syntax to create one SMTP object, which can later be used to send an e-mail −

import smtplib smtpObj = smtplib.SMTP( [host [, port [, local_hostname]]] )

Here is the detail of the parameters −

host − This is the host running your SMTP server. You can specifiy IP address of the host or a domain name like tutorialspoint.com. This is optional argument.

port − If you are providing host argument, then you need to specify a port, where SMTP server is listening. Usually this port would be 25.

local_hostname − If your SMTP server is running on your local machine, then you can specify just localhost as of this option.

An SMTP object has an instance method called sendmail, which is typically used to do the work of mailing a message. It takes three parameters −

The sender - A string with the address of the sender.

The receivers - A list of strings, one for each recipient.

The message - A message as a string formatted as specified in the various RFCs.

Example

Here is a simple way to send one e-mail using Python script. Try it once −

#!/usr/bin/python import smtplib sender = 'from@fromdomain.com' receivers = ['to@todomain.com'] message = """From: From Person <from@fromdomain.com> To: To Person <to@todomain.com> Subject: SMTP e-mail test This is a test e-mail message. """ try: smtpObj = smtplib.SMTP('localhost') smtpObj.sendmail(sender, receivers, message) print "Successfully sent email" except SMTPException: print "Error: unable to send email"

Here, you have placed a basic e-mail in message, using a triple quote, taking care to format the headers correctly. An e-mail requires a From, To, and Subject header, separated from the body of the e-mail with a blank line.

To send the mail you use smtpObj to connect to the SMTP server on the local machine and then use the sendmail method along with the message, the from address, and the destination address as parameters (even though the from and to addresses are within the e-mail itself, these aren't always used to route mail).

If you are not running an SMTP server on your local machine, you can use smtplib client to communicate with a remote SMTP server. Unless you are using a webmail service (such as Hotmail or Yahoo! Mail), your e-mail provider must have provided you with outgoing mail server details that you can supply them, as follows −

smtplib.SMTP('mail.your-domain.com', 25)

Sending an HTML e-mail using Python

When you send a text message using Python, then all the content are treated as simple text. Even if you include HTML tags in a text message, it is displayed as simple text and HTML tags will not be formatted according to HTML syntax. But Python provides option to send an HTML message as actual HTML message.

While sending an e-mail message, you can specify a Mime version, content type and character set to send an HTML e-mail.

Example

Following is the example to send HTML content as an e-mail. Try it once −

#!/usr/bin/python import smtplib message = """From: From Person <from@fromdomain.com> To: To Person <to@todomain.com> MIME-Version: 1.0 Content-type: text/html Subject: SMTP HTML e-mail test This is an e-mail message to be sent in HTML format <b>This is HTML message.</b> <h1>This is headline.</h1> """ try: smtpObj = smtplib.SMTP('localhost') smtpObj.sendmail(sender, receivers, message) print "Successfully sent email" except SMTPException: print "Error: unable to send email"

Sending Attachments as an E-mail

To send an e-mail with mixed content requires to set Content-type header to multipart/mixed. Then, text and attachment sections can be specified within boundaries.

A boundary is started with two hyphens followed by a unique number, which cannot appear in the message part of the e-mail. A final boundary denoting the e-mail's final section must also end with two hyphens.

Attached files should be encoded with the pack("m") function to have base64 encoding before transmission.

Example

Following is the example, which sends a file /tmp/test.txt as an attachment. Try it once −

#!/usr/bin/python import smtplib import base64 filename = "/tmp/test.txt" # Read a file and encode it into base64 format fo = open(filename, "rb") filecontent = fo.read() encodedcontent = base64.b64encode(filecontent) # base64 sender = 'webmaster@tutorialpoint.com' reciever = 'amrood.admin@gmail.com' marker = "AUNIQUEMARKER" body =""" This is a test email to send an attachement. """ # Define the main headers. part1 = """From: From Person <me@fromdomain.net> To: To Person <amrood.admin@gmail.com> Subject: Sending Attachement MIME-Version: 1.0 Content-Type: multipart/mixed; boundary=%s --%s """ % (marker, marker) # Define the message action part2 = """Content-Type: text/plain Content-Transfer-Encoding:8bit %s --%s """ % (body,marker) # Define the attachment section part3 = """Content-Type: multipart/mixed; name=\"%s\" Content-Transfer-Encoding:base64 Content-Disposition: attachment; filename=%s %s --%s-- """ %(filename, filename, encodedcontent, marker) message = part1 + part2 + part3 try: smtpObj = smtplib.SMTP('localhost') smtpObj.sendmail(sender, reciever, message) print "Successfully sent email" except Exception: print "Error: unable to send email"
Python - Multithreaded Programming

Running several threads is similar to running several different programs concurrently, but with the following benefits −

Multiple threads within a process share the same data space with the main thread and can therefore share information or communicate with each other more easily than if they were separate processes.

Threads sometimes called light-weight processes and they do not require much memory overhead; they are cheaper than processes.

A thread has a beginning, an execution sequence, and a conclusion. It has an instruction pointer that keeps track of where within its context it is currently running.

It can be pre-empted (interrupted)

It can temporarily be put on hold (also known as sleeping) while other threads are running - this is called yielding.

Starting a New Thread

To spawn another thread, you need to call following method available in thread module −

thread.start_new_thread ( function, args[, kwargs] )

This method call enables a fast and efficient way to create new threads in both Linux and Windows.

The method call returns immediately and the child thread starts and calls function with the passed list of args. When function returns, the thread terminates.

Here, args is a tuple of arguments; use an empty tuple to call function without passing any arguments. kwargs is an optional dictionary of keyword arguments.

Example

#!/usr/bin/python import thread import time # Define a function for the thread def print_time( threadName, delay): count = 0 while count < 5: time.sleep(delay) count += 1 print "%s: %s" % ( threadName, time.ctime(time.time()) ) # Create two threads as follows try: thread.start_new_thread( print_time, ("Thread-1", 2, ) ) thread.start_new_thread( print_time, ("Thread-2", 4, ) ) except: print "Error: unable to start thread" while 1: pass

When the above code is executed, it produces the following result −

Thread-1: Thu Jan 22 15:42:17 2009 Thread-1: Thu Jan 22 15:42:19 2009 Thread-2: Thu Jan 22 15:42:19 2009 Thread-1: Thu Jan 22 15:42:21 2009 Thread-2: Thu Jan 22 15:42:23 2009 Thread-1: Thu Jan 22 15:42:23 2009 Thread-1: Thu Jan 22 15:42:25 2009 Thread-2: Thu Jan 22 15:42:27 2009 Thread-2: Thu Jan 22 15:42:31 2009 Thread-2: Thu Jan 22 15:42:35 2009

Although it is very effective for low-level threading, but the thread module is very limited compared to the newer threading module.

The Threading Module

The newer threading module included with Python 2.4 provides much more powerful, high-level support for threads than the thread module discussed in the previous section.

The threading module exposes all the methods of the thread module and provides some additional methods −

threading.activeCount() − Returns the number of thread objects that are active.

threading.currentThread() − Returns the number of thread objects in the caller's thread control.

threading.enumerate() − Returns a list of all thread objects that are currently active.

In addition to the methods, the threading module has the Thread class that implements threading. The methods provided by the Thread class are as follows −

run() − The run() method is the entry point for a thread.

start() − The start() method starts a thread by calling the run method.

join([time]) − The join() waits for threads to terminate.

isAlive() − The isAlive() method checks whether a thread is still executing.

getName() − The getName() method returns the name of a thread.

setName() − The setName() method sets the name of a thread.

Creating Thread Using Threading Module

To implement a new thread using the threading module, you have to do the following −

Define a new subclass of the Thread class.

Override the __init__(self [,args]) method to add additional arguments.

Then, override the run(self [,args]) method to implement what the thread should do when started.

Once you have created the new Thread subclass, you can create an instance of it and then start a new thread by invoking the start(), which in turn calls run() method.

Example

#!/usr/bin/python import threading import time exitFlag = 0 class myThread (threading.Thread): def __init__(self, threadID, name, counter): threading.Thread.__init__(self) self.threadID = threadID self.name = name self.counter = counter def run(self): print "Starting " + self.name print_time(self.name, self.counter, 5) print "Exiting " + self.name def print_time(threadName, delay, counter): while counter: if exitFlag: threadName.exit() time.sleep(delay) print "%s: %s" % (threadName, time.ctime(time.time())) counter -= 1 # Create new threads thread1 = myThread(1, "Thread-1", 1) thread2 = myThread(2, "Thread-2", 2) # Start new Threads thread1.start() thread2.start() print "Exiting Main Thread"

When the above code is executed, it produces the following result −

Starting Thread-1 Starting Thread-2 Exiting Main Thread Thread-1: Thu Mar 21 09:10:03 2013 Thread-1: Thu Mar 21 09:10:04 2013 Thread-2: Thu Mar 21 09:10:04 2013 Thread-1: Thu Mar 21 09:10:05 2013 Thread-1: Thu Mar 21 09:10:06 2013 Thread-2: Thu Mar 21 09:10:06 2013 Thread-1: Thu Mar 21 09:10:07 2013 Exiting Thread-1 Thread-2: Thu Mar 21 09:10:08 2013 Thread-2: Thu Mar 21 09:10:10 2013 Thread-2: Thu Mar 21 09:10:12 2013 Exiting Thread-2

Synchronizing Threads

The threading module provided with Python includes a simple-to-implement locking mechanism that allows you to synchronize threads. A new lock is created by calling the Lock() method, which returns the new lock.

The acquire(blocking) method of the new lock object is used to force threads to run synchronously. The optional blocking parameter enables you to control whether the thread waits to acquire the lock.

If blocking is set to 0, the thread returns immediately with a 0 value if the lock cannot be acquired and with a 1 if the lock was acquired. If blocking is set to 1, the thread blocks and wait for the lock to be released.

The release() method of the new lock object is used to release the lock when it is no longer required.

Example

#!/usr/bin/python import threading import time class myThread (threading.Thread): def __init__(self, threadID, name, counter): threading.Thread.__init__(self) self.threadID = threadID self.name = name self.counter = counter def run(self): print "Starting " + self.name # Get lock to synchronize threads threadLock.acquire() print_time(self.name, self.counter, 3) # Free lock to release next thread threadLock.release() def print_time(threadName, delay, counter): while counter: time.sleep(delay) print "%s: %s" % (threadName, time.ctime(time.time())) counter -= 1 threadLock = threading.Lock() threads = [] # Create new threads thread1 = myThread(1, "Thread-1", 1) thread2 = myThread(2, "Thread-2", 2) # Start new Threads thread1.start() thread2.start() # Add threads to thread list threads.append(thread1) threads.append(thread2) # Wait for all threads to complete for t in threads: t.join() print "Exiting Main Thread"

When the above code is executed, it produces the following result −

Starting Thread-1 Starting Thread-2 Thread-1: Thu Mar 21 09:11:28 2013 Thread-1: Thu Mar 21 09:11:29 2013 Thread-1: Thu Mar 21 09:11:30 2013 Thread-2: Thu Mar 21 09:11:32 2013 Thread-2: Thu Mar 21 09:11:34 2013 Thread-2: Thu Mar 21 09:11:36 2013 Exiting Main Thread

Multithreaded Priority Queue

The Queue module allows you to create a new queue object that can hold a specific number of items. There are following methods to control the Queue −

get() − The get() removes and returns an item from the queue.

put() − The put adds item to a queue.

qsize() − The qsize() returns the number of items that are currently in the queue.

empty() − The empty( ) returns True if queue is empty; otherwise, False.

full() − the full() returns True if queue is full; otherwise, False.

Example

#!/usr/bin/python import Queue import threading import time exitFlag = 0 class myThread (threading.Thread): def __init__(self, threadID, name, q): threading.Thread.__init__(self) self.threadID = threadID self.name = name self.q = q def run(self): print "Starting " + self.name process_data(self.name, self.q) print "Exiting " + self.name def process_data(threadName, q): while not exitFlag: queueLock.acquire() if not workQueue.empty(): data = q.get() queueLock.release() print "%s processing %s" % (threadName, data) else: queueLock.release() time.sleep(1) threadList = ["Thread-1", "Thread-2", "Thread-3"] nameList = ["One", "Two", "Three", "Four", "Five"] queueLock = threading.Lock() workQueue = Queue.Queue(10) threads = [] threadID = 1 # Create new threads for tName in threadList: thread = myThread(threadID, tName, workQueue) thread.start() threads.append(thread) threadID += 1 # Fill the queue queueLock.acquire() for word in nameList: workQueue.put(word) queueLock.release() # Wait for queue to empty while not workQueue.empty(): pass # Notify threads it's time to exit exitFlag = 1 # Wait for all threads to complete for t in threads: t.join() print "Exiting Main Thread"

When the above code is executed, it produces the following result −

Starting Thread-1 Starting Thread-2 Starting Thread-3 Thread-1 processing One Thread-2 processing Two Thread-3 processing Three Thread-1 processing Four Thread-2 processing Five Exiting Thread-3 Exiting Thread-1 Exiting Thread-2 Exiting Main Thread
Python - XML Processing

XML is a portable, open source language that allows programmers to develop applications that can be read by other applications, regardless of operating system and/or developmental language.

What is XML?

The Extensible Markup Language (XML) is a markup language much like HTML or SGML. This is recommended by the World Wide Web Consortium and available as an open standard.

XML is extremely useful for keeping track of small to medium amounts of data without requiring a SQL-based backbone.

XML Parser Architectures and APIs

The Python standard library provides a minimal but useful set of interfaces to work with XML.

The two most basic and broadly used APIs to XML data are the SAX and DOM interfaces.

Simple API for XML (SAX) − Here, you register callbacks for events of interest and then let the parser proceed through the document. This is useful when your documents are large or you have memory limitations, it parses the file as it reads it from disk and the entire file is never stored in memory.

Document Object Model (DOM) API − This is a World Wide Web Consortium recommendation wherein the entire file is read into memory and stored in a hierarchical (tree-based) form to represent all the features of an XML document.

SAX obviously cannot process information as fast as DOM can when working with large files. On the other hand, using DOM exclusively can really kill your resources, especially if used on a lot of small files.

SAX is read-only, while DOM allows changes to the XML file. Since these two different APIs literally complement each other, there is no reason why you cannot use them both for large projects.

For all our XML code examples, let's use a simple XML file movies.xml as an input −

<collection shelf = "New Arrivals"> <movie title = "Enemy Behind"> <type>War, Thriller</type> <format>DVD</format> <year>2003</year> <rating>PG</rating> <stars>10</stars> <description>Talk about a US-Japan war</description> </movie> <movie title = "Transformers"> <type>Anime, Science Fiction</type> <format>DVD</format> <year>1989</year> <rating>R</rating> <stars>8</stars> <description>A schientific fiction</description> </movie> <movie title = "Trigun"> <type>Anime, Action</type> <format>DVD</format> <episodes>4</episodes> <rating>PG</rating> <stars>10</stars> <description>Vash the Stampede!</description> </movie> <movie title = "Ishtar"> <type>Comedy</type> <format>VHS</format> <rating>PG</rating> <stars>2</stars> <description>Viewable boredom</description> </movie> </collection>

Parsing XML with SAX APIs

SAX is a standard interface for event-driven XML parsing. Parsing XML with SAX generally requires you to create your own ContentHandler by subclassing xml.sax.ContentHandler.

Your ContentHandler handles the particular tags and attributes of your flavor(s) of XML. A ContentHandler object provides methods to handle various parsing events. Its owning parser calls ContentHandler methods as it parses the XML file.

The methods startDocument and endDocument are called at the start and the end of the XML file. The method characters(text) is passed character data of the XML file via the parameter text.

The ContentHandler is called at the start and end of each element. If the parser is not in namespace mode, the methods startElement(tag, attributes) and endElement(tag) are called; otherwise, the corresponding methods startElementNS and endElementNS are called. Here, tag is the element tag, and attributes is an Attributes object.

Here are other important methods to understand before proceeding −

The make_parser Method

Following method creates a new parser object and returns it. The parser object created will be of the first parser type the system finds.

xml.sax.make_parser( [parser_list] )

Here is the detail of the parameters −

parser_list − The optional argument consisting of a list of parsers to use which must all implement the make_parser method.

The parse Method

Following method creates a SAX parser and uses it to parse a document.

xml.sax.parse( xmlfile, contenthandler[, errorhandler])

Here is the detail of the parameters −

xmlfile − This is the name of the XML file to read from.

contenthandler − This must be a ContentHandler object.

errorhandler − If specified, errorhandler must be a SAX ErrorHandler object.

The parseString Method

There is one more method to create a SAX parser and to parse the specified XML string.

xml.sax.parseString(xmlstring, contenthandler[, errorhandler])

Here is the detail of the parameters −

xmlstring − This is the name of the XML string to read from.

contenthandler − This must be a ContentHandler object.

errorhandler − If specified, errorhandler must be a SAX ErrorHandler object.

Example

#!/usr/bin/python import xml.sax class MovieHandler( xml.sax.ContentHandler ): def __init__(self): self.CurrentData = "" self.type = "" self.format = "" self.year = "" self.rating = "" self.stars = "" self.description = "" # Call when an element starts def startElement(self, tag, attributes): self.CurrentData = tag if tag == "movie": print "*****Movie*****" title = attributes["title"] print "Title:", title # Call when an elements ends def endElement(self, tag): if self.CurrentData == "type": print "Type:", self.type elif self.CurrentData == "format": print "Format:", self.format elif self.CurrentData == "year": print "Year:", self.year elif self.CurrentData == "rating": print "Rating:", self.rating elif self.CurrentData == "stars": print "Stars:", self.stars elif self.CurrentData == "description": print "Description:", self.description self.CurrentData = "" # Call when a character is read def characters(self, content): if self.CurrentData == "type": self.type = content elif self.CurrentData == "format": self.format = content elif self.CurrentData == "year": self.year = content elif self.CurrentData == "rating": self.rating = content elif self.CurrentData == "stars": self.stars = content elif self.CurrentData == "description": self.description = content if ( __name__ == "__main__"): # create an XMLReader parser = xml.sax.make_parser() # turn off namepsaces parser.setFeature (xml.sax.handler.feature_namespaces, 0) # override the default ContextHandler Handler = MovieHandler() parser.setContentHandler( Handler ) parser.parse("movies.xml")

This would produce following result −

*****Movie***** Title: Enemy Behind Type: War, Thriller Format: DVD Year: 2003 Rating: PG Stars: 10 Description: Talk about a US-Japan war *****Movie***** Title: Transformers Type: Anime, Science Fiction Format: DVD Year: 1989 Rating: R Stars: 8 Description: A schientific fiction *****Movie***** Title: Trigun Type: Anime, Action Format: DVD Rating: PG Stars: 10 Description: Vash the Stampede! *****Movie***** Title: Ishtar Type: Comedy Format: VHS Rating: PG Stars: 2 Description: Viewable boredom

Parsing XML with DOM APIs

The Document Object Model ("DOM") is a cross-language API from the World Wide Web Consortium (W3C) for accessing and modifying XML documents.

The DOM is extremely useful for random-access applications. SAX only allows you a view of one bit of the document at a time. If you are looking at one SAX element, you have no access to another.

Here is the easiest way to quickly load an XML document and to create a minidom object using the xml.dom module. The minidom object provides a simple parser method that quickly creates a DOM tree from the XML file.

The sample phrase calls the parse( file [,parser] ) function of the minidom object to parse the XML file designated by file into a DOM tree object.

#!/usr/bin/python from xml.dom.minidom import parse import xml.dom.minidom # Open XML document using minidom parser DOMTree = xml.dom.minidom.parse("movies.xml") collection = DOMTree.documentElement if collection.hasAttribute("shelf"): print "Root element : %s" % collection.getAttribute("shelf") # Get all the movies in the collection movies = collection.getElementsByTagName("movie") # Print detail of each movie. for movie in movies: print "*****Movie*****" if movie.hasAttribute("title"): print "Title: %s" % movie.getAttribute("title") type = movie.getElementsByTagName('type')[0] print "Type: %s" % type.childNodes[0].data format = movie.getElementsByTagName('format')[0] print "Format: %s" % format.childNodes[0].data rating = movie.getElementsByTagName('rating')[0] print "Rating: %s" % rating.childNodes[0].data description = movie.getElementsByTagName('description')[0] print "Description: %s" % description.childNodes[0].data

This would produce the following result −

Root element : New Arrivals *****Movie***** Title: Enemy Behind Type: War, Thriller Format: DVD Rating: PG Description: Talk about a US-Japan war *****Movie***** Title: Transformers Type: Anime, Science Fiction Format: DVD Rating: R Description: A schientific fiction *****Movie***** Title: Trigun Type: Anime, Action Format: DVD Rating: PG Description: Vash the Stampede! *****Movie***** Title: Ishtar Type: Comedy Format: VHS Rating: PG Description: Viewable boredom
Python - GUI Programming (Tkinter)

Python provides various options for developing graphical user interfaces (GUIs). Most important are listed below.

Tkinter − Tkinter is the Python interface to the Tk GUI toolkit shipped with Python. We would look this option in this chapter.

wxPython − This is an open-source Python interface for wxWindows http://wxpython.org.

JPython − JPython is a Python port for Java which gives Python scripts seamless access to Java class libraries on the local machine http://www.jython.org.

There are many other interfaces available, which you can find them on the net.

Tkinter Programming

Tkinter is the standard GUI library for Python. Python when combined with Tkinter provides a fast and easy way to create GUI applications. Tkinter provides a powerful object-oriented interface to the Tk GUI toolkit.

Creating a GUI application using Tkinter is an easy task. All you need to do is perform the following steps −

Import the Tkinter module.

Create the GUI application main window.

Add one or more of the above-mentioned widgets to the GUI application.

Enter the main event loop to take action against each event triggered by the user.

Example

#!/usr/bin/python import tkinter top = tkinter.Tk() # Code to add widgets will go here... top.mainloop()

The above code would create a window.

Tkinter Widgets

Tkinter provides various controls, such as buttons, labels and text boxes used in a GUI application. These controls are commonly called widgets.

There are currently 15 types of widgets in Tkinter. We present these widgets as well as a brief description in the following table −

Sr.No.Operator & Description1

Button

The Button widget is used to display buttons in your application.

2

Canvas

The Canvas widget is used to draw shapes, such as lines, ovals, polygons and rectangles, in your application.

3

Checkbutton

The Checkbutton widget is used to display a number of options as checkboxes. The user can select multiple options at a time.

4

Entry

The Entry widget is used to display a single-line text field for accepting values from a user.

5

Frame

The Frame widget is used as a container widget to organize other widgets.

6

Label

The Label widget is used to provide a single-line caption for other widgets. It can also contain images.

7

Listbox

The Listbox widget is used to provide a list of options to a user.

8

Menubutton

The Menubutton widget is used to display menus in your application.

9

Menu

The Menu widget is used to provide various commands to a user. These commands are contained inside Menubutton.

10

Message

The Message widget is used to display multiline text fields for accepting values from a user.

11

Radiobutton

The Radiobutton widget is used to display a number of options as radio buttons. The user can select only one option at a time.

12

Scale

The Scale widget is used to provide a slider widget.

13

Scrollbar

The Scrollbar widget is used to add scrolling capability to various widgets, such as list boxes.

14

Text

The Text widget is used to display text in multiple lines.

15

Toplevel

The Toplevel widget is used to provide a separate window container.

16

Spinbox

The Spinbox widget is a variant of the standard Tkinter Entry widget, which can be used to select from a fixed number of values.

17

PanedWindow

A PanedWindow is a container widget that may contain any number of panes, arranged horizontally or vertically.

18

LabelFrame

A labelframe is a simple container widget. Its primary purpose is to act as a spacer or container for complex window layouts.

19

tkMessageBox

This module is used to display message boxes in your applications.

Standard attributes

Following are the list of attribute −

DimensionsColorsFontsAnchorsRelief stylesBitmapsCursors

Geometry Management

All Tkinter widgets have access to specific geometry management methods, which have the purpose of organizing widgets throughout the parent widget area. Tkinter exposes the following geometry manager classes: pack, grid, and place.

The pack() Method − This geometry manager organizes widgets in blocks before placing them in the parent widget.

The grid() Method − This geometry manager organizes widgets in a table-like structure in the parent widget.

The place() Method − This geometry manager organizes widgets by placing them in a specific position in the parent widget.

Python - Extension Programming with C

Any code that you write using any compiled language like C, C++, or Java can be integrated or imported into another Python script. This code is considered as an "extension."

A Python extension module is nothing more than a normal C library. On Unix machines, these libraries usually end in .so (for shared object). On Windows machines, you typically see .dll (for dynamically linked library).

Pre-Requisites for Writing Extensions

To start writing your extension, you are going to need the Python header files.

On Unix machines, this usually requires installing a developer-specific package such as python2.5-dev.

Windows users get these headers as part of the package when they use the binary Python installer.

Additionally, it is assumed that you have good knowledge of C or C++ to write any Python Extension using C programming.

First look at a Python Extension

For your first look at a Python extension module, you need to group your code into four part −

The header file Python.h.

The C functions you want to expose as the interface from your module.

A table mapping the names of your functions as Python developers see them to C functions inside the extension module.

An initialization function.

The Header File Python.h

You need include Python.h header file in your C source file, which gives you access to the internal Python API used to hook your module into the interpreter.

Make sure to include Python.h before any other headers you might need. You need to follow the includes with the functions you want to call from Python.

The C Functions

The signatures of the C implementation of your functions always takes one of the following three forms −

static PyObject *MyFunction( PyObject *self, PyObject *args ); static PyObject *MyFunctionWithKeywords(PyObject *self, PyObject *args, PyObject *kw); static PyObject *MyFunctionWithNoArgs( PyObject *self );

Each one of the preceding declarations returns a Python object. There is no such thing as a void function in Python as there is in C. If you do not want your functions to return a value, return the C equivalent of Python's None value. The Python headers define a macro, Py_RETURN_NONE, that does this for us.

The names of your C functions can be whatever you like as they are never seen outside of the extension module. They are defined as static function.

Your C functions usually are named by combining the Python module and function names together, as shown here −

static PyObject *module_func(PyObject *self, PyObject *args) { /* Do your stuff here. */ Py_RETURN_NONE; }

This is a Python function called func inside of the module module. You will be putting pointers to your C functions into the method table for the module that usually comes next in your source code.

The Method Mapping Table

This method table is a simple array of PyMethodDef structures. That structure looks something like this −

struct PyMethodDef { char *ml_name; PyCFunction ml_meth; int ml_flags; char *ml_doc; };

Here is the description of the members of this structure −

ml_name − This is the name of the function as the Python interpreter presents when it is used in Python programs.

ml_meth − This must be the address to a function that has any one of the signatures described in previous seection.

ml_flags − This tells the interpreter which of the three signatures ml_meth is using.

This flag usually has a value of METH_VARARGS.

This flag can be bitwise OR'ed with METH_KEYWORDS if you want to allow keyword arguments into your function.

This can also have a value of METH_NOARGS that indicates you do not want to accept any arguments.

ml_doc − This is the docstring for the function, which could be NULL if you do not feel like writing one.

This table needs to be terminated with a sentinel that consists of NULL and 0 values for the appropriate members.

Example

For the above-defined function, we have following method mapping table −

static PyMethodDef module_methods[] = { { "func", (PyCFunction)module_func, METH_NOARGS, NULL }, { NULL, NULL, 0, NULL } };

The Initialization Function

The last part of your extension module is the initialization function. This function is called by the Python interpreter when the module is loaded. It is required that the function be named initModule, where Module is the name of the module.

The initialization function needs to be exported from the library you will be building. The Python headers define PyMODINIT_FUNC to include the appropriate incantations for that to happen for the particular environment in which we're compiling. All you have to do is use it when defining the function.

Your C initialization function generally has the following overall structure −

PyMODINIT_FUNC initModule() { Py_InitModule3(func, module_methods, "docstring..."); }

Here is the description of Py_InitModule3 function −

func − This is the function to be exported.

module_methods − This is the mapping table name defined above.

docstring − This is the comment you want to give in your extension.

Putting this all together looks like the following −

#include <Python.h> static PyObject *module_func(PyObject *self, PyObject *args) { /* Do your stuff here. */ Py_RETURN_NONE; } static PyMethodDef module_methods[] = { { "func", (PyCFunction)module_func, METH_NOARGS, NULL }, { NULL, NULL, 0, NULL } }; PyMODINIT_FUNC initModule() { Py_InitModule3(func, module_methods, "docstring..."); }

Example

A simple example that makes use of all the above concepts −

#include <Python.h> static PyObject* helloworld(PyObject* self) { return Py_BuildValue("s", "Hello, Python extensions!!"); } static char helloworld_docs[] = "helloworld( ): Any message you want to put here!!\n"; static PyMethodDef helloworld_funcs[] = { {"helloworld", (PyCFunction)helloworld, METH_NOARGS, helloworld_docs}, {NULL} }; void inithelloworld(void) { Py_InitModule3("helloworld", helloworld_funcs, "Extension module example!"); }

Here the Py_BuildValue function is used to build a Python value. Save above code in hello.c file. We would see how to compile and install this module to be called from Python script.

Building and Installing Extensions

The distutils package makes it very easy to distribute Python modules, both pure Python and extension modules, in a standard way. Modules are distributed in source form and built and installed via a setup script usually called setup.py as follows.

For the above module, you need to prepare following setup.py script −

from distutils.core import setup, Extension setup(name = 'helloworld', version = '1.0', \ ext_modules = [Extension('helloworld', ['hello.c'])])

Now, use the following command, which would perform all needed compilation and linking steps, with the right compiler and linker commands and flags, and copies the resulting dynamic library into an appropriate directory −

$ python setup.py install

On Unix-based systems, you'll most likely need to run this command as root in order to have permissions to write to the site-packages directory. This usually is not a problem on Windows.

Importing Extensions

Once you installed your extension, you would be able to import and call that extension in your Python script as follows −

#!/usr/bin/python import helloworld print helloworld.helloworld()

This would produce the following result −

Hello, Python extensions!!

Passing Function Parameters

As you will most likely want to define functions that accept arguments, you can use one of the other signatures for your C functions. For example, following function, that accepts some number of parameters, would be defined like this −

static PyObject *module_func(PyObject *self, PyObject *args) { /* Parse args and do something interesting here. */ Py_RETURN_NONE; }

The method table containing an entry for the new function would look like this −

static PyMethodDef module_methods[] = { { "func", (PyCFunction)module_func, METH_NOARGS, NULL }, { "func", module_func, METH_VARARGS, NULL }, { NULL, NULL, 0, NULL } };

You can use API PyArg_ParseTuple function to extract the arguments from the one PyObject pointer passed into your C function.

The first argument to PyArg_ParseTuple is the args argument. This is the object you will be parsing. The second argument is a format string describing the arguments as you expect them to appear. Each argument is represented by one or more characters in the format string as follows.

static PyObject *module_func(PyObject *self, PyObject *args) { int i; double d; char *s; if (!PyArg_ParseTuple(args, "ids", &i, &d, &s)) { return NULL; } /* Do something interesting here. */ Py_RETURN_NONE; }

Compiling the new version of your module and importing it enables you to invoke the new function with any number of arguments of any type −

module.func(1, s = "three", d = 2.0) module.func(i = 1, d = 2.0, s = "three") module.func(s = "three", d = 2.0, i = 1)

You can probably come up with even more variations.

The PyArg_ParseTuple Function

Here is the standard signature for PyArg_ParseTuple function −

int PyArg_ParseTuple(PyObject* tuple,char* format,...)

This function returns 0 for errors, and a value not equal to 0 for success. tuple is the PyObject* that was the C function's second argument. Here format is a C string that describes mandatory and optional arguments.

Here is a list of format codes for PyArg_ParseTuple function −

CodeC typeMeaningccharA Python string of length 1 becomes a C char.ddoubleA Python float becomes a C double.ffloatA Python float becomes a C float.iintA Python int becomes a C int.llongA Python int becomes a C long.Llong longA Python int becomes a C long longOPyObject*Gets non-NULL borrowed reference to Python argument.schar*Python string without embedded nulls to C char*.s#char*+intAny Python string to C address and length.t#char*+intRead-only single-segment buffer to C address and length.uPy_UNICODE*Python Unicode without embedded nulls to C.u#Py_UNICODE*+intAny Python Unicode C address and length.w#char*+intRead/write single-segment buffer to C address and length.zchar*Like s, also accepts None (sets C char* to NULL).z#char*+intLike s#, also accepts None (sets C char* to NULL).(...)as per ...A Python sequence is treated as one argument per item.| The following arguments are optional.: Format end, followed by function name for error messages.; Format end, followed by entire error message text.

Returning Values

Py_BuildValue takes in a format string much like PyArg_ParseTuple does. Instead of passing in the addresses of the values you are building, you pass in the actual values. Here's an example showing how to implement an add function −

static PyObject *foo_add(PyObject *self, PyObject *args) { int a; int b; if (!PyArg_ParseTuple(args, "ii", &a, &b)) { return NULL; } return Py_BuildValue("i", a + b); }

This is what it would look like if implemented in Python −

def add(a, b): return (a + b)

You can return two values from your function as follows, this would be cauptured using a list in Python.

static PyObject *foo_add_subtract(PyObject *self, PyObject *args) { int a; int b; if (!PyArg_ParseTuple(args, "ii", &a, &b)) { return NULL; } return Py_BuildValue("ii", a + b, a - b); }

This is what it would look like if implemented in Python −

def add_subtract(a, b): return (a + b, a - b)

The Py_BuildValue Function

Here is the standard signature for Py_BuildValue function −

PyObject* Py_BuildValue(char* format,...)

Here format is a C string that describes the Python object to build. The following arguments of Py_BuildValue are C values from which the result is built. The PyObject* result is a new reference.

Following table lists the commonly used code strings, of which zero or more are joined into string format.

CodeC typeMeaningccharA C char becomes a Python string of length 1.ddoubleA C double becomes a Python float.ffloatA C float becomes a Python float.iintA C int becomes a Python int.llongA C long becomes a Python int.NPyObject*Passes a Python object and steals a reference.OPyObject*Passes a Python object and INCREFs it as normal.O&convert+void*Arbitrary conversionschar*C 0-terminated char* to Python string, or NULL to None.s#char*+intC char* and length to Python string, or NULL to None.uPy_UNICODE*C-wide, null-terminated string to Python Unicode, or NULL to None.u#Py_UNICODE*+intC-wide string and length to Python Unicode, or NULL to None.w#char*+intRead/write single-segment buffer to C address and length.zchar*Like s, also accepts None (sets C char* to NULL).z#char*+intLike s#, also accepts None (sets C char* to NULL).(...)as per ...Builds Python tuple from C values.[...]as per ...Builds Python list from C values.{...}as per ...Builds Python dictionary from C values, alternating keys and values.

Code {...} builds dictionaries from an even number of C values, alternately keys and values. For example, Py_BuildValue("{issi}",23,"zig","zag",42) returns a dictionary like Python's {23:'zig','zag':42}.

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