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.
Why to Learn Python?
Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. It uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages.
Python is a MUST for students and working professionals to become a great Software Engineer specially when they are working in Web Development Domain. I will list down some of the key advantages of learning Python:
Python is Interpreted − Python is processed at runtime by the interpreter. You do not need to compile your program before executing it. This is similar to PERL and PHP.
Python is Interactive − You can actually sit at a Python prompt and interact with the interpreter directly to write your programs.
Python is Object-Oriented − Python supports Object-Oriented style or technique of programming that encapsulates code within objects.
Python is a Beginner's Language − Python is a great language for the beginner-level programmers and supports the development of a wide range of applications from simple text processing to WWW browsers to games.
Characteristics of Python
Following are important characteristics of Python Programming −
It supports functional and structured programming methods as well as OOP.
It can be used as a scripting language or can be compiled to byte-code for building large applications.
It provides very high-level dynamic data types and supports dynamic type checking.
It supports automatic garbage collection.
It can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java.
Applications of Python
As mentioned before, Python is one of the most widely used language over the web. I'm going to list few of them here:
Easy-to-learn − Python has few keywords, simple structure, and a clearly defined syntax. This allows the student to pick up the language quickly.
Easy-to-read − Python code is more clearly defined and visible to the eyes.
Easy-to-maintain − Python's source code is fairly easy-to-maintain.
A broad standard library − Python's bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh.
Interactive Mode − Python has support for an interactive mode which allows interactive testing and debugging of snippets of code.
Portable − Python can run on a wide variety of hardware platforms and has the same interface on all platforms.
Extendable − You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient.
Databases − Python provides interfaces to all major commercial databases.
GUI Programming − Python supports GUI applications that can be created and ported to many system calls, libraries and windows systems, such as Windows MFC, Macintosh, and the X Window system of Unix.
Scalable − Python provides a better structure and support for large programs than shell scripting.
Audience
This Python 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 - Overview
Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. It uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages.
Python is Interpreted − Python is processed at runtime by the interpreter. You do not need to compile your program before executing it. This is similar to PERL and PHP.
Python is Interactive − You can actually sit at a Python prompt and interact with the interpreter directly to write your programs.
Python is Object-Oriented − Python supports Object-Oriented style or technique of programming that encapsulates code within objects.
Python is a Beginner's Language − Python is a great language for the beginner-level programmers and supports the development of a wide range of applications from simple text processing to WWW browsers to games.
History of Python
Python was developed by Guido van Rossum in the late eighties and early nineties at the National Research Institute for Mathematics and Computer Science in the Netherlands.
Python is derived from many other languages, including ABC, Modula-3, C, C++, Algol-68, SmallTalk, and Unix shell and other scripting languages.
Python is copyrighted. Like Perl, Python source code is now available under the GNU General Public License (GPL).
Python is now maintained by a core development team at the institute, although Guido van Rossum still holds a vital role in directing its progress.
Python Features
Python's features include −
Easy-to-learn − Python has few keywords, simple structure, and a clearly defined syntax. This allows the student to pick up the language quickly.
Easy-to-read − Python code is more clearly defined and visible to the eyes.
Easy-to-maintain − Python's source code is fairly easy-to-maintain.
A broad standard library − Python's bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh.
Interactive Mode − Python has support for an interactive mode which allows interactive testing and debugging of snippets of code.
Portable − Python can run on a wide variety of hardware platforms and has the same interface on all platforms.
Extendable − You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient.
Databases − Python provides interfaces to all major commercial databases.
GUI Programming − Python supports GUI applications that can be created and ported to many system calls, libraries and windows systems, such as Windows MFC, Macintosh, and the X Window system of Unix.
Scalable − Python provides a better structure and support for large programs than shell scripting.
Apart from the above-mentioned features, Python has a big list of good features, few are listed below −
It supports functional and structured programming methods as well as OOP.
It can be used as a scripting language or can be compiled to byte-code for building large applications.
It provides very high-level dynamic data types and supports dynamic type checking.
It supports automatic garbage collection.
It can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java.
Python - Environment Setup
Python is available on a wide variety of platforms including Linux and Mac OS X. Let's understand how to set up our Python environment.
Local Environment Setup
Open a terminal window and type "python" to find out if it is already installed and which version is installed.
- Unix (Solaris, Linux, FreeBSD, AIX, HP/UX, SunOS, IRIX, etc.)
- Win 9x/NT/2000
- Macintosh (Intel, PPC, 68K)
- OS/2
- DOS (multiple versions)
- PalmOS
- Nokia mobile phones
- Windows CE
- Acorn/RISC OS
- BeOS
- Amiga
- VMS/OpenVMS
- QNX
- VxWorks
- Psion
- Python has also been ported to the Java and .NET virtual machines
Getting Python
The most up-to-date and current source code, binaries, documentation, news, etc., is available on the official website of Python https://www.python.org/
You can download Python documentation from https://www.python.org/doc/. The documentation is available in HTML, PDF, and PostScript formats.
Installing Python
Python distribution is available for a wide variety of platforms. You need to download only the binary code applicable for your platform and install Python.
If the binary code for your platform is not available, you need a C compiler to compile the source code manually. Compiling the source code offers more flexibility in terms of choice of features that you require in your installation.
Here is a quick overview of installing Python on various platforms −
Unix and Linux Installation
Here are the simple steps to install Python on Unix/Linux machine.
Open a Web browser and go to https://www.python.org/downloads/.
Follow the link to download zipped source code available for Unix/Linux.
Download and extract files.
Editing the Modules/Setup file if you want to customize some options.
run ./configure script
make
make install
This installs Python at standard location /usr/local/bin and its libraries at /usr/local/lib/pythonXX where XX is the version of Python.
Windows Installation
Here are the steps to install Python on Windows machine.
Open a Web browser and go to https://www.python.org/downloads/.
Follow the link for the Windows installer python-XYZ.msi file where XYZ is the version you need to install.
To use this installer python-XYZ.msi, the Windows system must support Microsoft Installer 2.0. Save the installer file to your local machine and then run it to find out if your machine supports MSI.
Run the downloaded file. This brings up the Python install wizard, which is really easy to use. Just accept the default settings, wait until the install is finished, and you are done.
Macintosh Installation
Recent Macs come with Python installed, but it may be several years out of date. See http://www.python.org/download/mac/ for instructions on getting the current version along with extra tools to support development on the Mac. For older Mac OS's before Mac OS X 10.3 (released in 2003), MacPython is available.
Jack Jansen maintains it and you can have full access to the entire documentation at his website − http://www.cwi.nl/~jack/macpython.html. You can find complete installation details for Mac OS installation.
Setting up PATH
Programs and other executable files can be in many directories, so operating systems provide a search path that lists the directories that the OS searches for executables.
The path is stored in an environment variable, which is a named string maintained by the operating system. This variable contains information available to the command shell and other programs.
The path variable is named as PATH in Unix or Path in Windows (Unix is case sensitive; Windows is not).
In Mac OS, the installer handles the path details. To invoke the Python interpreter from any particular directory, you must add the Python directory to your path.
Setting path at Unix/Linux
To add the Python directory to the path for a particular session in Unix −
In the csh shell − type setenv PATH "$PATH:/usr/local/bin/python" and press Enter.
In the bash shell (Linux) − type export PATH="$PATH:/usr/local/bin/python" and press Enter.
In the sh or ksh shell − type PATH="$PATH:/usr/local/bin/python" and press Enter.
Note − /usr/local/bin/python is the path of the Python directory
Setting path at Windows
To add the Python directory to the path for a particular session in Windows −
At the command prompt − type path %path%;C:\Python and press Enter.
Note − C:\Python is the path of the Python directory
Python Environment Variables
Here are important environment variables, which can be recognized by Python −
| Sr.No. | Variable & Description |
|---|---|
| 1 | PYTHONPATH It has a role similar to PATH. This variable tells the Python interpreter where to locate the module files imported into a program. It should include the Python source library directory and the directories containing Python source code. PYTHONPATH is sometimes preset by the Python installer. |
| 2 | PYTHONSTARTUP It contains the path of an initialization file containing Python source code. It is executed every time you start the interpreter. It is named as .pythonrc.py in Unix and it contains commands that load utilities or modify PYTHONPATH. |
| 3 | PYTHONCASEOK It is used in Windows to instruct Python to find the first case-insensitive match in an import statement. Set this variable to any value to activate it. |
| 4 | PYTHONHOME It is an alternative module search path. It is usually embedded in the PYTHONSTARTUP or PYTHONPATH directories to make switching module libraries easy. |
Running Python
There are three different ways to start Python −
Interactive Interpreter
You can start Python from Unix, DOS, or any other system that provides you a command-line interpreter or shell window.
Enter python the command line.
Start coding right away in the interactive interpreter.
$python # Unix/Linux or python% # Unix/Linux or C:> python # Windows/DOS
Here is the list of all the available command line options −
| Sr.No. | Option & Description |
|---|---|
| 1 | -d It provides debug output. |
| 2 | -O It generates optimized bytecode (resulting in .pyo files). |
| 3 | -S Do not run import site to look for Python paths on startup. |
| 4 | -v verbose output (detailed trace on import statements). |
| 5 | -X disable class-based built-in exceptions (just use strings); obsolete starting with version 1.6. |
| 6 | -c cmd run Python script sent in as cmd string |
| 7 | file run Python script from given file |
Script from the Command-line
A Python script can be executed at command line by invoking the interpreter on your application, as in the following −
$python script.py # Unix/Linux or python% script.py # Unix/Linux or C: >python script.py # Windows/DOS
Note − Be sure the file permission mode allows execution.
Integrated Development Environment
You can run Python from a Graphical User Interface (GUI) environment as well, if you have a GUI application on your system that supports Python.
Unix − IDLE is the very first Unix IDE for Python.
Windows − PythonWin is the first Windows interface for Python and is an IDE with a GUI.
Macintosh − The Macintosh version of Python along with the IDLE IDE is available from the main website, downloadable as either MacBinary or BinHex'd files.
If you are not able to set up the environment properly, then you can take help from your system admin. Make sure the Python environment is properly set up and working perfectly fine.
Note − All the examples given in subsequent chapters are executed with Python 2.4.3 version available on CentOS flavor of Linux.
We already have set up Python Programming environment online, so that you can execute all the available examples online at the same time when you are learning theory. Feel free to modify any example and execute it online.
Python - Basic Syntax
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 −
print "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 −
#!/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.
#!/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.
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 the complete tuple print tuple[0] # Prints first element of the tuple print tuple[1:3] # Prints elements of the tuple starting from 2nd till 3rd print tuple[2:] # Prints elements of the tuple starting from 3rd element print tinytuple * 2 # Prints the contents of the tuple twice print tuple + tinytuple # Prints concatenated tuples
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 st |
1 Comments
good keep it up !!
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