The Python language has many similarities to Perl, C, and Java. However, there are some definite differences between the languages.
First Python Program
Let us execute programs in different modes of programming.
Interactive Mode Programming
Invoking the interpreter without passing a script file as a parameter brings up the following prompt −
$ python Python 2.4.3 (#1, Nov 11 2010, 13:34:43) [GCC 4.1.2 20080704 (Red Hat 4.1.2-48)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>>
Type the following text at the Python prompt and press the Enter −
>>> print "Hello, Python!"
If you are running new version of Python, then you would need to use print statement with parenthesis as in print ("Hello, Python!");. However in Python version 2.4.3, this produces the following result −
Hello, Python!
Script Mode Programming
Invoking the interpreter with a script parameter begins execution of the script and continues until the script is finished. When the script is finished, the interpreter is no longer active.
Let us write a simple Python program in a script. Python files have extension .py. Type the following source code in a test.py file −
Live Demoprint "Hello, Python!"
We assume that you have Python interpreter set in PATH variable. Now, try to run this program as follows −
$ python test.py
This produces the following result −
Hello, Python!
Let us try another way to execute a Python script. Here is the modified test.py file −
Live Demo#!/usr/bin/python print "Hello, Python!"
We assume that you have Python interpreter available in /usr/bin directory. Now, try to run this program as follows −
$ chmod +x test.py # This is to make file executable $./test.py
This produces the following result −
Hello, Python!
Python Identifiers
A Python identifier is a name used to identify a variable, function, class, module or other object. An identifier starts with a letter A to Z or a to z or an underscore (_) followed by zero or more letters, underscores and digits (0 to 9).
Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case sensitive programming language. Thus, Manpower and manpower are two different identifiers in Python.
Here are naming conventions for Python identifiers −
- Class names start with an uppercase letter. All other identifiers start with a lowercase letter.
- Starting an identifier with a single leading underscore indicates that the identifier is private.
- Starting an identifier with two leading underscores indicates a strongly private identifier.
- If the identifier also ends with two trailing underscores, the identifier is a language-defined special name.
Reserved Words
The following list shows the Python keywords. These are reserved words and you cannot use them as constant or variable or any other identifier names. All the Python keywords contain lowercase letters only.
| and | exec | not |
| assert | finally | or |
| break | for | pass |
| class | from | |
| continue | global | raise |
| def | if | return |
| del | import | try |
| elif | in | while |
| else | is | with |
| except | lambda | yield |
Lines and Indentation
Python provides no braces to indicate blocks of code for class and function definitions or flow control. Blocks of code are denoted by line indentation, which is rigidly enforced.
The number of spaces in the indentation is variable, but all statements within the block must be indented the same amount. For example −
if True: print "True" else: print "False"
However, the following block generates an error −
if True: print "Answer" print "True" else: print "Answer" print "False"
Thus, in Python all the continuous lines indented with same number of spaces would form a block. The following example has various statement blocks −
Note − Do not try to understand the logic at this point of time. Just make sure you understood various blocks even if they are without braces.
#!/usr/bin/python import sys try: # open file stream file = open(file_name, "w") except IOError: print "There was an error writing to", file_name sys.exit() print "Enter '", file_finish, print "' When finished" while file_text != file_finish: file_text = raw_input("Enter text: ") if file_text == file_finish: # close the file file.close break file.write(file_text) file.write("\n") file.close() file_name = raw_input("Enter filename: ") if len(file_name) == 0: print "Next time please enter something" sys.exit() try: file = open(file_name, "r") except IOError: print "There was an error reading file" sys.exit() file_text = file.read() file.close() print file_text
Multi-Line Statements
Statements in Python typically end with a new line. Python does, however, allow the use of the line continuation character (\) to denote that the line should continue. For example −
total = item_one + \
item_two + \
item_three
Statements contained within the [], {}, or () brackets do not need to use the line continuation character. For example −
days = ['Monday', 'Tuesday', 'Wednesday',
'Thursday', 'Friday']
Quotation in Python
Python accepts single ('), double (") and triple (''' or """) quotes to denote string literals, as long as the same type of quote starts and ends the string.
The triple quotes are used to span the string across multiple lines. For example, all the following are legal −
word = 'word' sentence = "This is a sentence." paragraph = """This is a paragraph. It is made up of multiple lines and sentences."""
Comments in Python
A hash sign (#) that is not inside a string literal begins a comment. All characters after the # and up to the end of the physical line are part of the comment and the Python interpreter ignores them.
Live Demo#!/usr/bin/python # First comment print "Hello, Python!" # second comment
This produces the following result −
Hello, Python!
You can type a comment on the same line after a statement or expression −
name = "Madisetti" # This is again comment
You can comment multiple lines as follows −
# This is a comment. # This is a comment, too. # This is a comment, too. # I said that already.
Following triple-quoted string is also ignored by Python interpreter and can be used as a multiline comments:
''' This is a multiline comment. '''
Using Blank Lines
A line containing only whitespace, possibly with a comment, is known as a blank line and Python totally ignores it.
In an interactive interpreter session, you must enter an empty physical line to terminate a multiline statement.
Waiting for the User
The following line of the program displays the prompt, the statement saying “Press the enter key to exit”, and waits for the user to take action −
#!/usr/bin/python raw_input("\n\nPress the enter key to exit.")
Here, "\n\n" is used to create two new lines before displaying the actual line. Once the user presses the key, the program ends. This is a nice trick to keep a console window open until the user is done with an application.
Multiple Statements on a Single Line
The semicolon ( ; ) allows multiple statements on the single line given that neither statement starts a new code block. Here is a sample snip using the semicolon −
import sys; x = 'foo'; sys.stdout.write(x + '\n')
Multiple Statement Groups as Suites
A group of individual statements, which make a single code block are called suites in Python. Compound or complex statements, such as if, while, def, and class require a header line and a suite.
Header lines begin the statement (with the keyword) and terminate with a colon ( : ) and are followed by one or more lines which make up the suite. For example −
if expression : suite elif expression : suite else : suite
Command Line Arguments
Many programs can be run to provide you with some basic information about how they should be run. Python enables you to do this with -h −
$ python -h usage: python [option] ... [-c cmd | -m mod | file | -] [arg] ... Options and arguments (and corresponding environment variables): -c cmd : program passed in as string (terminates option list) -d : debug output from parser (also PYTHONDEBUG=x) -E : ignore environment variables (such as PYTHONPATH) -h : print this help message and exit [ etc. ]
You can also program your script in such a way that it should accept various options. Command Line Arguments is an advanced topic and should be studied a bit later once you have gone through rest of the Python concepts.
Python Variables Type
Variables are nothing but reserved memory locations to store values. This means that when you create a variable you reserve some space in memory.
Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to variables, you can store integers, decimals or characters in these variables.
Assigning Values to Variables
Python variables do not need explicit declaration to reserve memory space. The declaration happens automatically when you assign a value to a variable. The equal sign (=) is used to assign values to variables.
The operand to the left of the = operator is the name of the variable and the operand to the right of the = operator is the value stored in the variable. For example −
#!/usr/bin/python counter = 100 # An integer assignment miles = 1000.0 # A floating point name = "John" # A string print counter print miles print name
Here, 100, 1000.0 and "John" are the values assigned to counter, miles, and name variables, respectively. This produces the following result −
100 1000.0 John
Multiple Assignment
Python allows you to assign a single value to several variables simultaneously. For example −
a = b = c = 1
Here, an integer object is created with the value 1, and all three variables are assigned to the same memory location. You can also assign multiple objects to multiple variables. For example −
a,b,c = 1,2,"john"
Here, two integer objects with values 1 and 2 are assigned to variables a and b respectively, and one string object with the value "john" is assigned to the variable c.
Standard Data Types
The data stored in memory can be of many types. For example, a person's age is stored as a numeric value and his or her address is stored as alphanumeric characters. Python has various standard data types that are used to define the operations possible on them and the storage method for each of them.
Python has five standard data types −
- Numbers
- String
- List
- Tuple
- Dictionary
Python Numbers
Number data types store numeric values. Number objects are created when you assign a value to them. For example −
var1 = 1 var2 = 10
You can also delete the reference to a number object by using the del statement. The syntax of the del statement is −
del var1[,var2[,var3[....,varN]]]]
You can delete a single object or multiple objects by using the del statement. For example −
del var del var_a, var_b
Python supports four different numerical types −
- int (signed integers)
- long (long integers, they can also be represented in octal and hexadecimal)
- float (floating point real values)
- complex (complex numbers)
Examples
Here are some examples of numbers −
| int | long | float | complex |
|---|---|---|---|
| 10 | 51924361L | 0.0 | 3.14j |
| 100 | -0x19323L | 15.20 | 45.j |
| -786 | 0122L | -21.9 | 9.322e-36j |
| 080 | 0xDEFABCECBDAECBFBAEl | 32.3+e18 | .876j |
| -0490 | 535633629843L | -90. | -.6545+0J |
| -0x260 | -052318172735L | -32.54e100 | 3e+26J |
| 0x69 | -4721885298529L | 70.2-E12 | 4.53e-7j |
- Python allows you to use a lowercase l with long, but it is recommended that you use only an uppercase L to avoid confusion with the number 1. Python displays long integers with an uppercase L.
- A complex number consists of an ordered pair of real floating-point numbers denoted by x + yj, where x and y are the real numbers and j is the imaginary unit.
Python Strings
Strings in Python are identified as a contiguous set of characters represented in the quotation marks. Python allows for either pairs of single or double quotes. Subsets of strings can be taken using the slice operator ([ ] and [:] ) with indexes starting at 0 in the beginning of the string and working their way from -1 at the end.
The plus (+) sign is the string concatenation operator and the asterisk (*) is the repetition operator. For example −
#!/usr/bin/python str = 'Hello World!' print str # Prints complete string print str[0] # Prints first character of the string print str[2:5] # Prints characters starting from 3rd to 5th print str[2:] # Prints string starting from 3rd character print str * 2 # Prints string two times print str + "TEST" # Prints concatenated string
This will produce the following result −
Hello World! H llo llo World! Hello World!Hello World! Hello World!TEST
Python Lists
Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). To some extent, lists are similar to arrays in C. One difference between them is that all the items belonging to a list can be of different data type.
The values stored in a list can be accessed using the slice operator ([ ] and [:]) with indexes starting at 0 in the beginning of the list and working their way to end -1. The plus (+) sign is the list concatenation operator, and the asterisk (*) is the repetition operator. For example −
#!/usr/bin/python list = [ 'abcd', 786 , 2.23, 'john', 70.2 ] tinylist = [123, 'john'] print list # Prints complete list print list[0] # Prints first element of the list print list[1:3] # Prints elements starting from 2nd till 3rd print list[2:] # Prints elements starting from 3rd element print tinylist * 2 # Prints list two times print list + tinylist # Prints concatenated lists
This produce the following result −
['abcd', 786, 2.23, 'john', 70.2] abcd [786, 2.23] [2.23, 'john', 70.2] [123, 'john', 123, 'john'] ['abcd', 786, 2.23, 'john', 70.2, 123, 'john']
Python Tuples
A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parentheses.
The main differences between lists and tuples are: Lists are enclosed in brackets ( [ ] ) and their elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be thought of as read-only lists. For example −
#!/usr/bin/python tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 ) tinytuple = (123, 'john') print tuple # Prints complete list print tuple[0] # Prints first element of the list print tuple[1:3] # Prints elements starting from 2nd till 3rd print tuple[2:] # Prints elements starting from 3rd element print tinytuple * 2 # Prints list two times print tuple + tinytuple # Prints concatenated lists
This produce the following result −
('abcd', 786, 2.23, 'john', 70.2)
abcd
(786, 2.23)
(2.23, 'john', 70.2)
(123, 'john', 123, 'john')
('abcd', 786, 2.23, 'john', 70.2, 123, 'john')
The following code is invalid with tuple, because we attempted to update a tuple, which is not allowed. Similar case is possible with lists −
#!/usr/bin/python tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 ) list = [ 'abcd', 786 , 2.23, 'john', 70.2 ] tuple[2] = 1000 # Invalid syntax with tuple list[2] = 1000 # Valid syntax with list
Python Dictionary
Python's dictionaries are kind of hash table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. A dictionary key can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object.
Dictionaries are enclosed by curly braces ({ }) and values can be assigned and accessed using square braces ([]). For example −
#!/usr/bin/python dict = {} dict['one'] = "This is one" dict[2] = "This is two" tinydict = {'name': 'john','code':6734, 'dept': 'sales'} print dict['one'] # Prints value for 'one' key print dict[2] # Prints value for 2 key print tinydict # Prints complete dictionary print tinydict.keys() # Prints all the keys print tinydict.values() # Prints all the values
This produce the following result −
This is one
This is two
{'dept': 'sales', 'code': 6734, 'name': 'john'}
['dept', 'code', 'name']
['sales', 6734, 'john']
Dictionaries have no concept of order among elements. It is incorrect to say that the elements are "out of order"; they are simply unordered.
Data Type Conversion
Sometimes, you may need to perform conversions between the built-in types. To convert between types, you simply use the type name as a function.
There are several built-in functions to perform conversion from one data type to another. These functions return a new object representing the converted value.
| Sr.No. | Function & Description |
|---|---|
| 1 |
int(x [,base])
Converts x to an integer. base specifies the base if x is a string.
|
| 2 |
long(x [,base] )
Converts x to a long integer. base specifies the base if x is a string.
|
| 3 |
float(x)
Converts x to a floating-point number.
|
| 4 |
complex(real [,imag])
Creates a complex number.
|
| 5 |
str(x)
Converts object x to a string representation.
|
| 6 |
repr(x)
Converts object x to an expression string.
|
| 7 |
eval(str)
Evaluates a string and returns an object.
|
| 8 |
tuple(s)
Converts s to a tuple.
|
| 9 |
list(s)
Converts s to a list.
|
| 10 |
set(s)
Converts s to a set.
|
| 11 |
dict(d)
Creates a dictionary. d must be a sequence of (key,value) tuples.
|
| 12 |
frozenset(s)
Converts s to a frozen set.
|
| 13 |
chr(x)
Converts an integer to a character.
|
| 14 |
unichr(x)
Converts an integer to a Unicode character.
|
| 15 |
ord(x)
Converts a single character to its integer value.
|
| 16 |
hex(x)
Converts an integer to a hexadecimal string.
|
| 17 |
oct(x)
Converts an integer to an octal string.
|
