Get a List of Link of a Website using Php

It'll be convenient if we could grab all link on a website just like firefox add-on--DownThemAll, and put it in our pages.

Fortunately, PHP has fopen function we could use for it. Here the code. It'll get this blog source, search for link, and print to screen the result.



<?php
$url = 'http://aravir-rose.blogspot.com';
$f = @fopen($url,"r");
while( $buf = fgets($f,1024) )
{
$buf = fgets($f, 4096);
preg_match_all("/<\s*a\s+[^>]*href\s*=\s*[\"']?([^\"' >]+)[\"' >]/isU",$buf,$words);
for( $i = 0; $words[$i]; $i++ )
{
for( $j = 0; $words[$i][$j]; $j++ )
{
$cur_word = strtolower($words[$i][$j]);
print "$cur_word<br>";
}
}
}
?>


Here the screenshot

From php

LLVM-GCC on OS X Lion

I confused about GCC version brought by XCode 4.2 on OS X Lion, so I surfing and landing on several sites to find out what is this llvm version.

Here some result.

Llvm stand for low level virtual machine



The LLVM Project (llvm.org) is a collection of modular and reusable compiler and toolchain technologies. Despite its name, LLVM has little to do with traditional virtual machines, though it does provide helpful libraries that can be used to build them.

The llvm-gcc command is the LLVM C front end. It is a modified version of gcc that compiles C/ObjC programs into native objects, LLVM bitcode or LLVM assembly language, depending upon the options.

By default, llvm-gcc compiles to native objects just like GCC does. If the -emit-llvm and -c options are given then it will generate LLVM bitcode files instead. If -emit-llvm and -S are given, then it will generate LLVM assembly.

Being derived from the GNU Compiler Collection, llvm-gcc has many of gcc's features and accepts most of gcc's options. It handles a number of gcc's extensions to the C programming language. See the gcc documentation for details.

Clang vs GCC (GNU Compiler Collection)

Clang ( /ˈklæŋ/)[2] is a compiler front end for the C, C++, Objective-C, and Objective-C++ programming languages. It uses the Low Level Virtual Machine (LLVM) as its back end, and Clang has been part of LLVM releases since LLVM 2.6.

Its goal is to offer a replacement to the GNU Compiler Collection (GCC). Development is sponsored by Apple. Clang is available under a free software license.

The Clang project includes the Clang front end and the Clang static analyzer among others.[3]

Pro's of GCC vs clang:

• GCC supports languages that clang does not aim to, such as Java, Ada, FORTRAN, etc.
• GCC has a few C++'11 features that Clang does not yet support.
• GCC supports more targets than LLVM.
• GCC is popular and widely adopted.
• GCC does not require a C++ compiler to build it.

Pro's of clang vs GCC:

• The Clang ASTs and design are intended to be easily understandable by anyone who is familiar with the languages involved and who has a basic understanding of how a compiler works. GCC has a very old codebase which presents a steep learning curve to new developers.
• Clang is designed as an API from its inception, allowing it to be reused by source analysis tools, refactoring, IDEs (etc) as well as for code generation. GCC is built as a monolithic static compiler, which makes it extremely difficult to use as an API and integrate into other tools. Further, its historic design and current policy makes it difficult to decouple the front-end from the rest of the compiler.
• Various GCC design decisions make it very difficult to reuse: its build system is difficult to modify, you can't link multiple targets into one binary, you can't link multiple front-ends into one binary, it uses a custom garbage collector, uses global variables extensively, is not reentrant or multi-threadable, etc. Clang has none of these problems.
• For every token, clang tracks information about where it was written and where it was ultimately expanded into if it was involved in a macro. GCC does not track information about macro instantiations when parsing source code. This makes it very difficult for source rewriting tools (e.g. for refactoring) to work in the presence of (even simple) macros.
• Clang does not implicitly simplify code as it parses it like GCC does. Doing so causes many problems for source analysis tools: as one simple example, if you write "x-x" in your source code, the GCC AST will contain "0", with no mention of 'x'. This is extremely bad for a refactoring tool that wants to rename 'x'.
• Clang can serialize its AST out to disk and read it back into another program, which is useful for whole program analysis. GCC does not have this. GCC's PCH mechanism (which is just a dump of the compiler memory image) is related, but is architecturally only able to read the dump back into the exact same executable as the one that produced it (it is not a structured format).
• Clang is much faster and uses far less memory than GCC.
• Clang aims to provide extremely clear and concise diagnostics (error and warning messages), and includes support for expressive diagnostics. GCC's warnings are sometimes acceptable, but are often confusing and it does not support expressive diagnostics. Clang also preserves typedefs in diagnostics consistently, showing macro expansions and many other features.
• GCC is licensed under the GPL license. clang uses a BSD license, which allows it to be used by projects that do not themselves want to be GPL.
• Clang inherits a number of features from its use of LLVM as a backend, including support for a bytecode representation for intermediate code, pluggable optimizers, link-time optimization support, Just-In-Time compilation, ability to link in multiple code generators, etc.
• Clang's support for C++ is more compliant than GCC's in many ways (e.g. conformant two phase name lookup).

From forum (http://www.cocos2d-iphone.org/forum/topic/7923)
"Have you experienced any incompatibility between LLVM compiler and GCC compiler ?


I found one strange issue:
If you compile ParticleTests with GCC and if you try sub-test "issue 872", it works as expected: a particle system will emit particles.
But if you compile it with LLVM 1.5, you won't see any particle at all. I'm not sure what's the problem, but I'll investigate it a bit further.


I can only reproduce this bug on the simulator. It seems that this bug can't be reproduced on the devices.


I tested it both in Release & Debug mode using Xcode 3.2.3"
............

"A developer at Apple (guy working on LLVM) highly suggested moving away from GCC immediately. He says Apple is no longer fixing bugs in GCC, and in XCode 4 GCC-LLVM will be the default option.


I've noticed sometimes LLVM will not compile against really old libraries compiled with GCC (gives errors about built in runtime functions not found). I can fix that by using GCC-LLVM (gcc parser, LLVM code generator).


A few days ago I noticed a bug in my code that only showed up when using LLVM (but not GCC). I tracked it down to a non initialized local variable that was being read from, and GCC would always initialize to zero (even with O3 optimizations). Since the variable value should be undefined, LLVM was giving the correct behavior of using whatever was in that memory already (even though it's clearly not the desired result). I'd speculate something similar is going on with ParticleTests.


I did a quick test, and compiling Cocos2D with GCC-LLVM works correctly with issue 872."

Robert Cross Edge Detection using Python on OS X Lion

The code below will convert an image to grayscale, get its pixel value and save it in array. With its pixel value in array, it's easy to apply Robert Cross Edge detect operation.

This operator is simpler than Sobel's.

print 'Program Python Deteksi Tepi'
print 'oleh Nugroho Adi Pramono'
'''Komentar diantara tiga-tanda petik tidak akan dibaca
oleh python'''
#komentar setelah tanda pagar juga tidak di baca oleh python
import Image        #memanggil modul untuk olah gambar
import os,sys       #memanggil modul untuk mengakses file
import numpy as np  #memanggil modul untuk operasi maatematika matrik/array
gb = Image.open('../gambar.jpg')                   #memasukkan gambar ke variabel gb
print 'format awal: ' ,gb.format, "%dx%d" % gb.size, gb.mode
print 'konversi ke grayscale'
gbw = gb.convert("L")
gbw.save('gambarBW.jpg')                #simpan hasil konversi ddg nama gambarBW.jpg
gbw = Image.open('gambarBW.jpg')        #masukkan gambar grayscale hasil konversi ke variabel gbw
print 'format: ',gbw.format, "%dx%d" % gbw.size, gbw.mode
ukuran=gbw.size                         #mengambil nilai resolusi gambar
'''buat array r dan s berukuran sama dengan ukuran gambar'''
r=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
s=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
print 'Mengambil nilai piksel, masukkan ke array r'
for i in range (ukuran[0]):
    for j in range (ukuran[1]):
        r[i,j]=gbw.getpixel((i,j))
print 'Deteksi tepi menggunakan operator Robert'
gx=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
gy=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
g=np.zeros((ukuran[0],ukuran[1]),dtype=np.float)
for i in range (ukuran[0]-1):
    for j in range (ukuran[1]-1):
        gx[i,j]=r[i,j]-r[i+1,j+1]
        gy[i,j]=r[i,j+1]-r[i+1,j]
g=np.sqrt(np.power(gx,2)+np.power(gy,2))
print 'Atur threshold'
for i in range (ukuran[0]-1):
    for j in range (ukuran[1]-1):
        if (g[i,j]<11):
            s[i,j]=0
        else:
            s[i,j]=255
            
print 'update gambar'
for i in range (ukuran[0]):
    for j in range (ukuran[1]):
        gbw.putpixel((i,j),s[i,j])      #letakkan pixel yang telah dimodifikasi ke posisi i,j
print 'Menyimpan gambar'
gbw.save('gambarRobert.jpg')          #simpan dengan nama gambarRobert.jpg
print 'Gambar tersimpan'
print 'Program Selesai'

Here, the result

Image source

From python

Gray-scaled image

From python

Edge-detected image

From python

Vertical Sobel Operator Manual Edge Detection using Python and PIL

This python code is used to detect the edge, of course, using Sobel Operator. The 'manual' word in this post title means I apply it manually as scipy python module has it capability. This code convert a jpeg image to grayscale and then detect its edge.



Here the code, I used vertical detection only as my horizontal code result is scrambling. I will update it as soon as all code success

print 'Program Python Deteksi Tepi'
print 'oleh Nugroho Adi Pramono'
'''Komentar diantara tiga-tanda petik tidak akan dibaca
oleh python'''
#komentar setelah tanda pagar juga tidak di baca oleh python
import Image        #memanggil modul untuk olah gambar
import os,sys       #memanggil modul untuk mengakses file
import numpy as np  #memanggil modul untuk operasi maatematika matrik/array
gb = Image.open('../gambar.jpg')                   #memasukkan gambar ke variabel gb
print 'format awal: ' ,gb.format, "%dx%d" % gb.size, gb.mode
print 'konversi ke grayscale'
gbw = gb.convert("L")
gbw.save('gambarBW.jpg')                #simpan hasil konversi ddg nama gambarBW.jpg
gbw = Image.open('gambarBW.jpg')        #masukkan gambar grayscale hasil konversi ke variabel gbw
print 'format: ',gbw.format, "%dx%d" % gbw.size, gbw.mode
ukuran=gbw.size                         #mengambil nilai resolusi gambar
'''buat array r dan s berukuran sama dengan ukuran gambar'''
r=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
s=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
print 'Mengambil nilai piksel, masukkan ke array r'
for i in range (ukuran[0]):
    for j in range (ukuran[1]):
        r[i,j]=gbw.getpixel((i,j))
print 'Deteksi tepi menggunakan operator Sobel'
gx=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
gy=np.zeros((ukuran[0],ukuran[1]),dtype=np.integer)
g=np.zeros((ukuran[0],ukuran[1]),dtype=np.float)
for i in range (1,ukuran[0]-1):
    for j in range (1,ukuran[1]-1):
        gy[i,j]=r[i+1,j-1]+2*r[i+1,j]+r[i+1,j+1]-r[i-1,j-1]-2*r[i-1,j]-r[i-1,j+1]
print 'Atur threshold'
print 'update gambar Vertikal'
for i in range (ukuran[0]):
    for j in range (ukuran[1]):
        gbw.putpixel((i,j),np.abs(gy[i,j]))      #letakkan pixel yang telah dimodifikasi ke posisi i,j
print 'Menyimpan gambar Vertikal'
gbw.save('gambarSobelVertikal.jpg')          #simpan dengan nama gambarSobelVertikal.jpg
print 'Gambar tersimpan'
print 'Program Selesai'

And here the result

Image source

From python

Gray-scaled image

From python

Edge-detected image

From python

JPEG Support for Python 2.7's PIL Module on OS X Lion

My PIL module refuse to process jpeg image. It says that there is no decoder jpeg on my system. It's no good  since I want to process that kind of file using PIL in future, and my older iPhoto picture on my 13 inch MacBook Pro is generally in jpeg format too.

Here the snapshot

Nugrohos-MacBook-Pro:olah gambar nugroho$ python olahgambar.py 
Program Image Enchancement
Oleh Nugroho Adi Pramono
275514
===========================
format awal:  JPEG 2448x3264 RGB
konversi ke grayscale
Traceback (most recent call last):
  File "olahgambar.py", line 14, in 
    gbw = gb.convert("L")
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/PIL/Image.py", line 679, in convert
    self.load()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/PIL/ImageFile.py", line 189, in load
    d = Image._getdecoder(self.mode, d, a, self.decoderconfig)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/PIL/Image.py", line 385, in _getdecoder
    raise IOError("decoder %s not available" % decoder_name)
IOError: decoder jpeg not available
Nugrohos-MacBook-Pro:olah gambar nugroho$ 

So I googling for it and found libjpeg at http://www.ijg.org/files/, download, exctract and install it using magic UNIX words ./configure, make, make install

Nugrohos-MacBook-Pro:~ nugroho$ cd Downloads/jpeg-8c/
Nugrohos-MacBook-Pro:jpeg-8c nugroho$ ./configure 
Nugrohos-MacBook-Pro:jpeg-8c nugroho$ make
Nugrohos-MacBook-Pro:jpeg-8c nugroho$ make test
rm -f testout*
./djpeg -dct int -ppm -outfile testout.ppm  ./testorig.jpg
./djpeg -dct int -bmp -colors 256 -outfile testout.bmp  ./testorig.jpg
./cjpeg -dct int -outfile testout.jpg  ./testimg.ppm
./djpeg -dct int -ppm -outfile testoutp.ppm ./testprog.jpg
./cjpeg -dct int -progressive -opt -outfile testoutp.jpg ./testimg.ppm
./jpegtran -outfile testoutt.jpg ./testprog.jpg
cmp ./testimg.ppm testout.ppm
cmp ./testimg.bmp testout.bmp
cmp ./testimg.jpg testout.jpg
cmp ./testimg.ppm testoutp.ppm
cmp ./testimgp.jpg testoutp.jpg
cmp ./testorig.jpg testoutt.jpg
Nugrohos-MacBook-Pro:jpeg-8c nugroho$ sudo make install

reinstall PIL

PIL 1.1.7 SETUP SUMMARY
--------------------------------------------------------------------
version       1.1.7
platform      darwin 2.7.2 (v2.7.2:8527427914a2, Jun 11 2011, 15:22:34)
              [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)]
--------------------------------------------------------------------
--- TKINTER support available
--- JPEG support available
--- ZLIB (PNG/ZIP) support available
*** FREETYPE2 support not available
*** LITTLECMS support not available
--------------------------------------------------------------------
To add a missing option, make sure you have the required
library, and set the corresponding ROOT variable in the
setup.py script.

Ubuntu 11.10 Oneiric Ocelot On OS X Lion's VBox (NAT and Host-Guest Sharing Folder)

After installing Ubuntu 11.10 on Mac OS X Lion using VirtualBox, here first impression of Oneiric Ocelot



There is dock at left, like on Mac.

Network is works flawlessy, I can surf internet using firefox, its NAT configuration come by default while installing it.

From Oneiric Ocelot

Firefox run at fullscreen(I mean ubuntu screen), just like Lion's or iPad's Safari (Lion's version of firefox didn't auto fullscreen yet). We can windowed-mode-ed it by hovering mouse at top edge of screen, it'll show menu-bar too

Hover mouse at top

From Oneiric Ocelot

It's windowed firefox

From Oneiric Ocelot

 If we click dash home, we'll got launchpad like (just like iPad or Lion's launchpad). At second tab, there's apps available to download.

From Oneiric Ocelot

 To access shared folder on Lion named vbox, I opened terminal by clicking Dash home and type terminal on search box

From Oneiric Ocelot

 First create directory

aravir@aravir-VirtualBox:~$mkdir vbox

mount shared vbox on lion using this command

aravir@aravir-VirtualBox:~$sudo mount -t vboxsf vbox vbox 

at screenshot you know it generate error because ubuntu did'nt recognize vboxsf filesystem. To introduce it, guest addition must be installed.

From Oneiric Ocelot

From Oneiric Ocelot

From Oneiric Ocelot

From Oneiric Ocelot

Failed. Guest addition need root privilege.

aravir@aravir-VirtualBox:~$cd /Media/VBOXADDITIONS_4.1.6_74713
$sudo ./VBoxLinuxAdditions.run

After guest addition installed and the system restarted (it's support full screen on my Macbook monitor now), retype the command above, and done

 Vbox directory before mounted

From Oneiric Ocelot

After mounted

From Oneiric Ocelot

Installing Python-2.7's Imaging Library Module on OS X Lion

PIL, as its name suggest, is an imaging library for python. I used PIL to get every pixel of an image as 2x2 array information. With that I could modify it with many possibilities; edge detection, black and white transformation, log transformation, creating watermark, etc.

{update: I install this PIL module on my OS X El Capitan too, :), and easier } 



Installing PIL is an easy task, if we have its prerequities installed. Just download it and extract it and then install using this command

Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ python setup.py install
running install
running build
running build_py
creating build
creating build/lib.macosx-10.6-intel-2.7
...
unable to execute gcc-4.2: No such file or directory
error: command 'gcc-4.2' failed with exit status 1
Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ 

Oops, it is failed to install, it tell me that there is no gcc-4.2 on my machine, and that's true. I've modified my /usr/bin/gcc to point /usr/local/bin/gcc.

I have gcc 4.2 from Xcode4.2, which actually llvm-gcc. My existing gcc is gcc-4.6.2 so I cheated… I created symlink named gcc-4.2 on /usr/bin pointing /usr/local/bin/gcc

Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ ln -s /usr/local/bin/gcc /usr/bin/gcc-4.2
ln: /usr/bin/gcc-4.2: Permission denied
Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ sudo ln -s /usr/local/bin/gcc /usr/bin/gcc-4.2
Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ 

Still error, :(

gcc-4.2: error: x86_64: No such file or directory
gcc-4.2: error: unrecognized option ‘-arch’
gcc-4.2: error: unrecognized option ‘-arch’
error: command 'gcc-4.2' failed with exit status 1

Hm, maybe if I'm linking /usr/bin/gcc-4.2 to /usr/bin/llvm-gcc-4-2; it's gcc-4.2 after all, if we ignore llvm (don't know what is it stand for). It doesn't hurt if I'm trying, so..

Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ sudo rm /usr/bin/gcc-4.2 
Password:
Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ sudo ln -s /usr/bin/llvm-gcc-4.2 /usr/bin/gcc-4.2
Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ python setup.py install
running install
running build
running build_py
running build_ext
-
--------------------------------------------------------------------
PIL 1.1.7 SETUP SUMMARY
--------------------------------------------------------------------
version       1.1.7
platform      darwin 2.7.2 (v2.7.2:8527427914a2, Jun 11 2011, 15:22:34)
              [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)]
--------------------------------------------------------------------
--- TKINTER support available
*** JPEG support not available
--- ZLIB (PNG/ZIP) support available
*** FREETYPE2 support not available
*** LITTLECMS support not available
--------------------------------------------------------------------
creating /Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/PIL.pth
Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ 

Wow, success 

Well, no need gcc4.6.2 afterall, just create symbolic link of llvm-gcc-4.2 named gcc-4.2,:)

test

Nugrohos-MacBook-Pro:Imaging-1.1.7 nugroho$ python
Python 2.7.2 (v2.7.2:8527427914a2, Jun 11 2011, 15:22:34) 
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import image
Traceback (most recent call last):
  File "", line 1, in 
ImportError: No module named image
>>> import Image
>>> 

OK