html - Scrapping using codeigniter and i need title and custom link - 


<div id="archive_content_block">     <div class="row">        <div class="col-md-6 col-sm-6">          <div class="archive_cat_caption">             <h4>অর্থনীতি</h4>         </div>       <ul>         <li><i class="fa fa-square-o"></i>&nbsp;           <a href="http://67.227.189.112/~rtvnews24/economy/2126/বাধ্যতামূলক-করারোপের-প্রস্তাব-অর্থমন্ত্রীর">          <font style="color:rgb(33, 33, 33)">বাধ্যতামূলক করারোপের প্রস্তাব অর্থমন্ত্রীর</font>         </a>       </li>      </ul>   </div>   <div class="col-md-6 col-sm-6">      <div class="archive_cat_caption">         <h4>খেলাধুলা</h4>      </div>      <ul>         <li><i class="fa fa-square-o"></i>&nbsp;<a href="http://67.227.189.112/~rtvnews24/sports/2096/অস্ট্রেলিয়া-রেকর্ড"><font style="color:rgb(33, 33, 33)">অস্ট্রেলিয়া রেকর্ড</font></a></li>       </ul>   </div> </div> </div>

[this scrapping html page code]

here have function scrapping title , link. not work 

   public function get_dom()     {        $this->load->library('scraping');     $date = date('y/m/d');  // custom date     $url = "http://67.227.189.112/~rtvnews24/archive/$date";  //my link     $html = file_get_html($url);     $row =   $html->find('div.archive_content_block',0);  // select content      foreach($row->find('div.archive_cat_caption', 0) $title) {       echo $title->find('h4', 0)->plaintext.'</br>'; //title          foreach($row->find('ul',0) $link) {           echo $link->find('li',0)->find('a', 0)->href.'</br>'; //link             }      }   }

here try title , link. please me. in advance


-

Comments

Post a Comment

Popular posts from this blog

serialization - Convert Any type in scala to Array[Byte] and back -

i have following question: i have variable value in program declared value. i want convert value byte array.. how can serialize byte array , back? found examples related other types such double or int, not any. this should need. it's pretty similar how 1 in java. import java.io.{bytearrayinputstream, bytearrayoutputstream, objectinputstream, objectoutputstream} object serialization extends app { def serialise(value: any): array[byte] = { val stream: bytearrayoutputstream = new bytearrayoutputstream() val oos = new objectoutputstream(stream) oos.writeobject(value) oos.close stream.tobytearray } def deserialise(bytes: array[byte]): = { val ois = new objectinputstream(new bytearrayinputstream(bytes)) val value = ois.readobject ois.close value } println(deserialise(serialise("my test"))) println(deserialise(serialise(list(1)))) println(deserialise(serialise(map(1 -> 2)))) println(deserialise(seri
Read more

matplotlib support failed in PyCharm on OSX -

any idea how fix ? how can debug might problem ? not seem : https://youtrack.jetbrains.com/issue/py-15520 i in console: python 2.6.9 (unknown, jul 14 2015, 19:46:31) [gcc 4.2.1 compatible apple llvm 6.0 (clang-600.0.39)] on darwin >>> import matplotlib.pyplot plt matplotlib support failed the backend : >>> import matplotlib >>> print(matplotlib.rcparams['backend']) macosx
Read more

python - Matplotlib: TypeError: 'AxesSubplot' object is not callable -

i new programming please pardon me if rookie mistake. i writing python script have defined functions create subplots of distributions. i have slider widget end user change value of variables(mu , sigma) , see effect on distribution. here's code import numpy np print np.__version__ import scipy print scipy.__version__ scipy.stats import norm, lognorm, uniform import matplotlib print matplotlib.__version__ import matplotlib.pyplot plt matplotlib.widgets import slider, button, radiobuttons, checkbuttons #####calculating mean , standard deviation##### global mu_a1 mu_a1 = 1 global mu_b1 mu_b1 = 10 global mu_c1 mu_c1 = -13 global sigma_a1 sigma_a1 = 0.14 global sigma_b1 sigma_b1 = 1.16 global sigma_c1 sigma_c1 = 2.87 mu_x01 = -11 sigma_x01 = 1.9 #####_____##### #####generating random data##### a1 = 0.75*mu_a1 + (1.25 - 0.75)*sigma_a1*np.random.sample(10000) b1 = 8*mu_b1 + (12 - 8)*sigma_b1*np.random.sample(10000) c1 = -12*mu_c1 + 2*sigma_c1*np.random.sample(10000)
Read more