25 June, 2009
Comparing Python to Other Languages
Python is often compared to other interpreted languages such as Java, JavaScript, Perl, Tcl, or Smalltalk. Comparisons to C++, Common Lisp and Scheme can also be enlightening. In this section I will briefly compare Python to each of these languages. These comparisons concentrate on language issues only. In practice, the choice of a programming language is often dictated by other real-world constraints such as cost, availability, training, and prior investment, or even emotional attachment. Since these aspects are highly variable, it seems a waste of time to consider them much for this comparison.
Java
Python programs are generally expected to run slower than Java programs, but they also take much less time to develop. Python programs are typically 3-5 times shorter than equivalent Java programs. This difference can be attributed to Python's built-in high-level data types and its dynamic typing. For example, a Python programmer wastes no time declaring the types of arguments or variables, and Python's powerful polymorphic list and dictionary types, for which rich syntactic support is built straight into the language, find a use in almost every Python program. Because of the run-time typing, Python's run time must work harder than Java's. For example, when evaluating the expression a+b, it must first inspect the objects a and b to find out their type, which is not known at compile time. It then invokes the appropriate addition operation, which may be an overloaded user-defined method. Java, on the other hand, can perform an efficient integer or floating point addition, but requires variable declarations for a and b, and does not allow overloading of the + operator for instances of user-defined classes.
For these reasons, Python is much better suited as a "glue" language, while Java is better characterized as a low-level implementation language. In fact, the two together make an excellent combination. Components can be developed in Java and combined to form applications in Python; Python can also be used to prototype components until their design can be "hardened" in a Java implementation. To support this type of development, a Python implementation written in Java is under development, which allows calling Python code from Java and vice versa. In this implementation, Python source code is translated to Java bytecode (with help from a run-time library to support Python's dynamic semantics).
Javascript
Python's "object-based" subset is roughly equivalent to JavaScript. Like JavaScript (and unlike Java), Python supports a programming style that uses simple functions and variables without engaging in class definitions. However, for JavaScript, that's all there is. Python, on the other hand, supports writing much larger programs and better code reuse through a true object-oriented programming style, where classes and inheritance play an important role.
Perl
Python and Perl come from a similar background (Unix scripting, which both have long outgrown), and sport many similar features, but have a different philosophy. Perl emphasizes support for common application-oriented tasks, e.g. by having built-in regular expressions, file scanning and report generating features. Python emphasizes support for common programming methodologies such as data structure design and object-oriented programming, and encourages programmers to write readable (and thus maintainable) code by providing an elegant but not overly cryptic notation. As a consequence, Python comes close to Perl but rarely beats it in its original application domain; however Python has an applicability well beyond Perl's niche.
Tcl
Like Python, Tcl is usable as an application extension language, as well as a stand-alone programming language. However, Tcl, which traditionally stores all data as strings, is weak on data structures, and executes typical code much slower than Python. Tcl also lacks features needed for writing large programs, such as modular namespaces. Thus, while a "typical" large application using Tcl usually contains Tcl extensions written in C or C++ that are specific to that application, an equivalent Python application can often be written in "pure Python". Of course, pure Python development is much quicker than having to write and debug a C or C++ component. It has been said that Tcl's one redeeming quality is the Tk toolkit. Python has adopted an interface to Tk as its standard GUI component library.
Tcl 8.0 addresses the speed issuse by providing a bytecode compiler with limited data type support, and adds namespaces. However, it is still a much more cumbersome programming language.
Smalltalk
Perhaps the biggest difference between Python and Smalltalk is Python's more "mainstream" syntax, which gives it a leg up on programmer training. Like Smalltalk, Python has dynamic typing and binding, and everything in Python is an object. However, Python distinguishes built-in object types from user-defined classes, and currently doesn't allow inheritance from built-in types. Smalltalk's standard library of collection data types is more refined, while Python's library has more facilities for dealing with Internet and WWW realities such as email, HTML and FTP.
Python has a different philosophy regarding the development environment and distribution of code. Where Smalltalk traditionally has a monolithic "system image" which comprises both the environment and the user's program, Python stores both standard modules and user modules in individual files which can easily be rearranged or distributed outside the system. One consequence is that there is more than one option for attaching a Graphical User Interface (GUI) to a Python program, since the GUI is not built into the system.
C++
Almost everything said for Java also applies for C++, just more so: where Python code is typically 3-5 times shorter than equivalent Java code, it is often 5-10 times shorter than equivalent C++ code! Anecdotal evidence suggests that one Python programmer can finish in two months what two C++ programmers can't complete in a year. Python shines as a glue language, used to combine components written in C++.
Common Lisp and Scheme
These languages are close to Python in their dynamic semantics, but so different in their approach to syntax that a comparison becomes almost a religious argument: is Lisp's lack of syntax an advantage or a disadvantage? It should be noted that Python has introspective capabilities similar to those of Lisp, and Python programs can construct and execute program fragments on the fly. Usually, real-world properties are decisive: Common Lisp is big (in every sense), and the Scheme world is fragmented between many incompatible versions, where Python has a single, free, compact implementation.
you see this essay on :-
www.python.org/doc/essays/comparisons.html
Java
Python programs are generally expected to run slower than Java programs, but they also take much less time to develop. Python programs are typically 3-5 times shorter than equivalent Java programs. This difference can be attributed to Python's built-in high-level data types and its dynamic typing. For example, a Python programmer wastes no time declaring the types of arguments or variables, and Python's powerful polymorphic list and dictionary types, for which rich syntactic support is built straight into the language, find a use in almost every Python program. Because of the run-time typing, Python's run time must work harder than Java's. For example, when evaluating the expression a+b, it must first inspect the objects a and b to find out their type, which is not known at compile time. It then invokes the appropriate addition operation, which may be an overloaded user-defined method. Java, on the other hand, can perform an efficient integer or floating point addition, but requires variable declarations for a and b, and does not allow overloading of the + operator for instances of user-defined classes.
For these reasons, Python is much better suited as a "glue" language, while Java is better characterized as a low-level implementation language. In fact, the two together make an excellent combination. Components can be developed in Java and combined to form applications in Python; Python can also be used to prototype components until their design can be "hardened" in a Java implementation. To support this type of development, a Python implementation written in Java is under development, which allows calling Python code from Java and vice versa. In this implementation, Python source code is translated to Java bytecode (with help from a run-time library to support Python's dynamic semantics).
Javascript
Python's "object-based" subset is roughly equivalent to JavaScript. Like JavaScript (and unlike Java), Python supports a programming style that uses simple functions and variables without engaging in class definitions. However, for JavaScript, that's all there is. Python, on the other hand, supports writing much larger programs and better code reuse through a true object-oriented programming style, where classes and inheritance play an important role.
Perl
Python and Perl come from a similar background (Unix scripting, which both have long outgrown), and sport many similar features, but have a different philosophy. Perl emphasizes support for common application-oriented tasks, e.g. by having built-in regular expressions, file scanning and report generating features. Python emphasizes support for common programming methodologies such as data structure design and object-oriented programming, and encourages programmers to write readable (and thus maintainable) code by providing an elegant but not overly cryptic notation. As a consequence, Python comes close to Perl but rarely beats it in its original application domain; however Python has an applicability well beyond Perl's niche.
Tcl
Like Python, Tcl is usable as an application extension language, as well as a stand-alone programming language. However, Tcl, which traditionally stores all data as strings, is weak on data structures, and executes typical code much slower than Python. Tcl also lacks features needed for writing large programs, such as modular namespaces. Thus, while a "typical" large application using Tcl usually contains Tcl extensions written in C or C++ that are specific to that application, an equivalent Python application can often be written in "pure Python". Of course, pure Python development is much quicker than having to write and debug a C or C++ component. It has been said that Tcl's one redeeming quality is the Tk toolkit. Python has adopted an interface to Tk as its standard GUI component library.
Tcl 8.0 addresses the speed issuse by providing a bytecode compiler with limited data type support, and adds namespaces. However, it is still a much more cumbersome programming language.
Smalltalk
Perhaps the biggest difference between Python and Smalltalk is Python's more "mainstream" syntax, which gives it a leg up on programmer training. Like Smalltalk, Python has dynamic typing and binding, and everything in Python is an object. However, Python distinguishes built-in object types from user-defined classes, and currently doesn't allow inheritance from built-in types. Smalltalk's standard library of collection data types is more refined, while Python's library has more facilities for dealing with Internet and WWW realities such as email, HTML and FTP.
Python has a different philosophy regarding the development environment and distribution of code. Where Smalltalk traditionally has a monolithic "system image" which comprises both the environment and the user's program, Python stores both standard modules and user modules in individual files which can easily be rearranged or distributed outside the system. One consequence is that there is more than one option for attaching a Graphical User Interface (GUI) to a Python program, since the GUI is not built into the system.
C++
Almost everything said for Java also applies for C++, just more so: where Python code is typically 3-5 times shorter than equivalent Java code, it is often 5-10 times shorter than equivalent C++ code! Anecdotal evidence suggests that one Python programmer can finish in two months what two C++ programmers can't complete in a year. Python shines as a glue language, used to combine components written in C++.
Common Lisp and Scheme
These languages are close to Python in their dynamic semantics, but so different in their approach to syntax that a comparison becomes almost a religious argument: is Lisp's lack of syntax an advantage or a disadvantage? It should be noted that Python has introspective capabilities similar to those of Lisp, and Python programs can construct and execute program fragments on the fly. Usually, real-world properties are decisive: Common Lisp is big (in every sense), and the Scheme world is fragmented between many incompatible versions, where Python has a single, free, compact implementation.
you see this essay on :-
www.python.org/doc/essays/comparisons.html
17 June, 2009
Use Your Linux System With A Broken Bootloader
Here are some simple steps that should allow you to make some very simple changes that could end up saving you a lot of time and possibly a reinstall of your Linux system.
1. Acquire a Linux liveCD of your choice. I prefer Elive, as it is bigger one and quick. There are in count of others such as KNOPPIX, ZenWalk, Ubuntu, Fedora Live, and DSL. Each of these would easily be up to the task.
2. Boot the live CD and get to a command line somehow. If you are in a GUI environment, this means starting a Terminal or Konsole session. If you are booted into a classic Linux login prompt, you're good to go.
3. Make sure you're the root user (you can do this by typing whoami). If you're not root, type su - and enter the root password when prompted.
4. Mount your linux root partition. These steps may vary depending on preference, but they should be fairly similar:
1. cd /mnt
2. mkdir myroot
3. mount /dev/hda5 /mnt/myroot
4. cd /mnt/myroot
5. Depending on the complexity of the tasks you wish to perform, you may need to mount your device list according to what your live CD detected:
1. mount /dev /mnt/myroot/dev
2. mount -t proc /proc /mnt/myroot/proc
6. Finally, switch into your installed system, specifying where your root partition is mounted and they shell you wish to use:
1. chroot /mnt/myroot /bin/bash
At this point you should be able to do several useful things, such as reinstall your bootloader into the MBR. You can also edit hosed configuration files this way.
If you need to add Windows into your boot configuration, and you use LILO, you could try adding something like this to your /etc/lilo.conf:
other = /dev/hda1
label = Windows
table = /dev/hda
(be sure to run lilo again to save the change)
When you are all done with your chroot environment, simply type exit or logout or what have you. Then be sure to unmount anything you may have mounted in order to use the system.
1. Acquire a Linux liveCD of your choice. I prefer Elive, as it is bigger one and quick. There are in count of others such as KNOPPIX, ZenWalk, Ubuntu, Fedora Live, and DSL. Each of these would easily be up to the task.
2. Boot the live CD and get to a command line somehow. If you are in a GUI environment, this means starting a Terminal or Konsole session. If you are booted into a classic Linux login prompt, you're good to go.
3. Make sure you're the root user (you can do this by typing whoami). If you're not root, type su - and enter the root password when prompted.
4. Mount your linux root partition. These steps may vary depending on preference, but they should be fairly similar:
1. cd /mnt
2. mkdir myroot
3. mount /dev/hda5 /mnt/myroot
4. cd /mnt/myroot
5. Depending on the complexity of the tasks you wish to perform, you may need to mount your device list according to what your live CD detected:
1. mount /dev /mnt/myroot/dev
2. mount -t proc /proc /mnt/myroot/proc
6. Finally, switch into your installed system, specifying where your root partition is mounted and they shell you wish to use:
1. chroot /mnt/myroot /bin/bash
At this point you should be able to do several useful things, such as reinstall your bootloader into the MBR. You can also edit hosed configuration files this way.
If you need to add Windows into your boot configuration, and you use LILO, you could try adding something like this to your /etc/lilo.conf:
other = /dev/hda1
label = Windows
table = /dev/hda
(be sure to run lilo again to save the change)
When you are all done with your chroot environment, simply type exit or logout or what have you. Then be sure to unmount anything you may have mounted in order to use the system.
Firebug for !Firefox
Pretty much anyone who's been doing any Web development in the last few years probably prefers to use Firefox because of the incredibly powerful extensions it offers. Among the extensions I hear from pavan mishra who is Web developers complain about not having in other browsers are Web Developer and Firebug. Several people feel that they could get by with another browser (such as Google Chrome) if it only had Firebug.
Firebug actually offer their amazing product for other browsers!
I happened upon this utility while perusing Django Snippets the other day. A member by the username of jfw posted a middleware which injects the Firebug Lite utility into a response when you're not using Firefox and when your site is in debug mode. I've found it to be quite useful. I hope you all do too!!
Firebug actually offer their amazing product for other browsers!
I happened upon this utility while perusing Django Snippets the other day. A member by the username of jfw posted a middleware which injects the Firebug Lite utility into a response when you're not using Firefox and when your site is in debug mode. I've found it to be quite useful. I hope you all do too!!
