I have a CO2 sensor on my Arduino Mega and sometimes randomly when I'm reading the CO2 measurement, the sensor will return a "?". The question mark causes my program to crash and return "input string was not in a correct format".
I haven't tried anything because I don't know what approach would be the best for this. The CO2 sensor returns the measurement in the form of "Z 00000" but when this question mark appears it shows that all that returned was a "\n". Currently, I have the program just reading the 5 digits after the Z.
if (returnString != "")
{
val = Convert.ToDouble(returnString.Substring(returnString.LastIndexOf('Z')+ 1));
}
What I expect to return is the digits after Z which works but every so often I will get a random line return which crashes everything.
According to the C# documentation the ToDouble method throws FormatException whenever the input string is invalid. You should catch the exception to avoid further issues.
try {
val = Convert.ToDouble(returnString.Substring(returnString.LastIndexOf('Z')+ 1));
}
catch(FormatException e) {
//If you want to do anything in case of an error
//Otherwise you can leave it blank
}
Also I'd recommend using some sort of statemachine for parsing the data in your case, that could discard all invalid characters. Something like this:
bool z_received = false;
int digits = 0;
int value = 0;
//Called whenever you receive a byte from the serial port
void onCharacter(char input) {
if(input == 'Z') {
z_received = true;
}
else if(z_received && input <= '9' && input >= '0') {
value *= 10;
value += (input - '0');
digits++;
if(digits == 5) {
onData(value);
value = 0;
z_received = false;
digits = 0;
}
}
else {
value = 0;
z_received = false;
digits = 0;
}
}
void onData(int data) {
//do something with the data
}
This is just a mock-up, should work in your case if you can direct the COM port's byte stream into the onCharacter function.
I'm writing a for loop for a project that prompts the user to input a number and keeps prompting, continually adding the numbers up. When a string is introduced, the loop should stop. I've done it with a while loop, but the project states that we must do it with a for loop also. The problem is that the prompt keeps running even when 'a = false'. Could someone explain javascript's thinking process? I want to understand why it keeps running back through the loop even though the condition isn't met. Thank you
var addSequence2 = function() {
var total = 0;
var a;
for (; a = true; ) {
var input = prompt("Your current score is " +total+ "\n" + "Next number...");
if (!isNaN(input)) {
a = true;
total = +total + +input;
}
else if (isNaN(input)) {
a = false;
document.write("Your total is " + total);
}
}
};
There is a difference between a = true and a == true.
Your for-loop is basically asking "can I set 'a' to true?", to which the answer is yes, and the loop continues.
Change the condition to a == true (thus asking "Is the value of 'a' true?")
To elaborate, in most programming languages, we distinguish between assignment ("Make 'x' be 4") and testing for equality ("Is 'x' 4?"). By convention (at least in languages that derive their syntax from C), we use '=' to assign/set a value, and '==' to test.
If I'm understanding the specification correctly (no guarantee), what happens here is that the condition condenses as follows:
Is (a = true) true?
Complete the bracket: set a to true
Is (a) true? (we just set it to true, so it must be!)
Try using the equal to operator, i.e. change
for (; a = true; ) {
to
for (; a == true; ) {
You should use a == true instead of a = true......= is an assignment operator
for (; a = true; ), you are assigning the value to the variable "a" and it will always remain true and will end up in infinite loop. In JavaScript it should a===true.
I suspect you want your for to look like this :
for(;a==true;)
as a=true is an assignment, not a comparison.
a == true. The double equal sign compares the two. Single equal assigns the value true to a so this always returns true.
for (; a = true; ) <-- this is an assignation
for (; a == true; ) <-- this should be better
Here's your fixed code :
var addSequence2 = function() {
var total = 0;
var a = true;
for(;Boolean(a);) {
var input = prompt("Your current score is " +total+ "\n" + "Next number...");
if (!isNaN(input)) {
total = total + input;
}
else{
a = false;
document.write("Your total is " + total);
}
}
};
I am trying to write some logic to determine if all values of a certain property of an object in a collection are numeric and greater than zero. I can easily write this using ForEach but I'd like to do it using Linq to Object. I tried this:
var result = entity.Reports.Any(
x =>
x.QuestionBlock == _question.QuestionBlock
&& (!string.IsNullOrEmpty(x.Data)) && Int32.TryParse(x.Data, out tempVal)
&& Int32.Parse(x.Data) > 0);
It does not work correctly. I also tried this, hoping that the TryParse() on Int32 will return false the first time it encounter a string that cannot be parsed into an int. But it appears the out param will contain the first value string value that can be parsed into an int.
var result = entity.GranteeReportDataModels.Any(
x =>
x.QuestionBlock == _question.QuestionBlock
&& (!string.IsNullOrEmpty(x.Data)) && Int32.TryParse(x.Data, out tempVal));
Any help is greatly appreciated!
If you want to test if "all" values meet a condition, you should use the All extension method off IEnumerable<T>, not Any. I would write it like this:
var result = entity.Reports.All(x =>
{
int result = 0;
return int.TryParse(x.Data, out result) && result > 0;
});
I don't believe you need to test for an null or empty string, because int.TryPrase will return false if you pass in a null or empty string.
var allDataIsNatural = entity.Reports.All(r =>
{
int i;
if (!int.TryParse(r.Data, out i))
{
return false;
}
return i > 0;
});
Any will return when the first row is true but, you clearly say you would like to check them all.
You can use this extension which tries to parse a string to int and returns a int?:
public static int? TryGetInt(this string item)
{
int i;
bool success = int.TryParse(item, out i);
return success ? (int?)i : (int?)null;
}
Then this query works:
bool all = entity.Reports.All(x => {
if(x.QuestionBlock != _question.QuestionBlockint)
return false;
int? data = x.Data.TryGetInt();
return data.HasValue && data.Value > 0;
});
or more readable (a little bit less efficient):
bool all = entityReports
.All(x => x.Data.TryGetInt().HasValue && x.Data.TryGetInt() > 0
&& x.QuestionBlock == _question.QuestionBlockint);
This approach avoids using a local variable as out parameter which is an undocumented behaviour in Linq-To-Objects and might stop working in future. It's also more readable.
I have a piece of code, which I am not sure how to refactor.. It is not very readable and I would like to make it readable. Here is a the problem
There are two columns in database which can be either NULL, 0 or have a value each. On the web page there is a checkbox - enable and text box - value for each of those two columns.
x = checkbox1
z = textbox1
y = checkbox2
w = textbox2
The logic is if both the checkboxes are not selected, then both the values should be 0. If either one is selected and other is not, then others value should be NULL. and for the one that is selected, if the textbox is empty its value should be NULL else should be the value in the textbox
if{x}
{
if(z)
{
a = NULL;
}
else
{
a = z;
}
if(y)
{
if(w)
{
b=w;
}
else
{
b = NULL;
}
}
else
{
b = null
}
}
else
{
if(y)
{
a = NULL;
if(w)
{
b=w;
}
else
{
b = NULL;
}
}
else
{
a = 0;
b = 0;
}
}
Trust me this is a valid scenario. Let me know if this makes sense or I should give more information
Using some logical ands and nots, we get something more readable.
We can save a little by defaulting to NULL (thus not needing to set the other to NULL). We can also save by putting the code for checking if a textbox is set or using null into a little function.
In pseudo code:
a = NULL
b = NULL
if (not checkbox1) and (not checkbox2):
a = 0
b = 0
if (checkbox1):
a = valueornull(textbox1)
if (checkbox2):
b = valueornull(textbox2)
function valueornull(textbox):
if textbox value:
return value
else:
return null
I think it would help to use more descriptive names that the single letters here, but assuming this is C code, it looks a lot neater with inline if statements:
if(x)
{
a = z ? NULL : z;
b = (y && w) ? w : NULL;
}
else
{
a = y ? NULL : 0;
b = (y && w) ? w : 0;
}
I have come across an interview question "If you were designing a web crawler, how would you avoid getting into infinite loops? " and I am trying to answer it.
How does it all begin from the beginning.
Say Google started with some hub pages say hundreds of them (How these hub pages were found in the first place is a different sub-question).
As Google follows links from a page and so on, does it keep making a hash table to make sure that it doesn't follow the earlier visited pages.
What if the same page has 2 names (URLs) say in these days when we have URL shorteners etc..
I have taken Google as an example. Though Google doesn't leak how its web crawler algorithms and page ranking etc work, but any guesses?
If you want to get a detailed answer take a look at section 3.8 this paper, which describes the URL-seen test of a modern scraper:
In the course of extracting links, any
Web crawler will encounter multiple
links to the same document. To avoid
downloading and processing a document
multiple times, a URL-seen test must
be performed on each extracted link
before adding it to the URL frontier.
(An alternative design would be to
instead perform the URL-seen test when
the URL is removed from the frontier,
but this approach would result in a
much larger frontier.)
To perform the
URL-seen test, we store all of the
URLs seen by Mercator in canonical
form in a large table called the URL
set. Again, there are too many entries
for them all to fit in memory, so like
the document fingerprint set, the URL
set is stored mostly on disk.
To save
space, we do not store the textual
representation of each URL in the URL
set, but rather a fixed-sized
checksum. Unlike the fingerprints
presented to the content-seen test’s
document fingerprint set, the stream
of URLs tested against the URL set has
a non-trivial amount of locality. To
reduce the number of operations on the
backing disk file, we therefore keep
an in-memory cache of popular URLs.
The intuition for this cache is that
links to some URLs are quite common,
so caching the popular ones in memory
will lead to a high in-memory hit
rate.
In fact, using an in-memory
cache of 2^18 entries and the LRU-like
clock replacement policy, we achieve
an overall hit rate on the in-memory
cache of 66.2%, and a hit rate of 9.5%
on the table of recently-added URLs,
for a net hit rate of 75.7%. Moreover,
of the 24.3% of requests that miss in
both the cache of popular URLs and the
table of recently-added URLs, about
1=3 produce hits on the buffer in our
random access file implementation,
which also resides in user-space. The
net result of all this buffering is
that each membership test we perform
on the URL set results in an average
of 0.16 seek and 0.17 read kernel
calls (some fraction of which are
served out of the kernel’s file system
buffers). So, each URL set membership
test induces one-sixth as many kernel
calls as a membership test on the
document fingerprint set. These
savings are purely due to the amount
of URL locality (i.e., repetition of
popular URLs) inherent in the stream
of URLs encountered during a crawl.
Basically they hash all of the URLs with a hashing function that guarantees unique hashes for each URL and due to the locality of URLs, it becomes very easy to find URLs. Google even open-sourced their hashing function: CityHash
WARNING!
They might also be talking about bot traps!!! A bot trap is a section of a page that keeps generating new links with unique URLs and you will essentially get trapped in an "infinite loop" by following the links that are being served by that page. This is not exactly a loop, because a loop would be the result of visiting the same URL, but it's an infinite chain of URLs which you should avoid crawling.
Update 12/13/2012- the day after the world was supposed to end :)
Per Fr0zenFyr's comment: if one uses the AOPIC algorithm for selecting pages, then it's fairly easy to avoid bot-traps of the infinite loop kind. Here is a summary of how AOPIC works:
Get a set of N seed pages.
Allocate X amount of credit to each page, such that each page has X/N credit (i.e. equal amount of credit) before crawling has started.
Select a page P, where the P has the highest amount of credit (or if all pages have the same amount of credit, then crawl a random page).
Crawl page P (let's say that P had 100 credits when it was crawled).
Extract all the links from page P (let's say there are 10 of them).
Set the credits of P to 0.
Take a 10% "tax" and allocate it to a Lambda page.
Allocate an equal amount of credits each link found on page P from P's original credit - the tax: so (100 (P credits) - 10 (10% tax))/10 (links) = 9 credits per each link.
Repeat from step 3.
Since the Lambda page continuously collects tax, eventually it will be the page with the largest amount of credit and we'll have to "crawl" it. I say "crawl" in quotes, because we don't actually make an HTTP request for the Lambda page, we just take its credits and distribute them equally to all of the pages in our database.
Since bot traps only give internal links credits and they rarely get credit from the outside, they will continually leak credits (from taxation) to the Lambda page. The Lambda page will distribute that credits out to all of the pages in the database evenly and upon each cycle the bot trap page will lose more and more credits, until it has so little credits that it almost never gets crawled again. This will not happen with good pages, because they often get credits from back-links found on other pages. This also results in a dynamic page rank and what you will notice is that any time you take a snapshot of your database, order the pages by the amount of credits they have, then they will most likely be ordered roughly according to their true page rank.
This only avoid bot traps of the infinite-loop kind, but there are many other bot traps which you should watch out for and there are ways to get around them too.
While everybody here already suggested how to create your web crawler, here is how how Google ranks pages.
Google gives each page a rank based on the number of callback links (how many links on other websites point to a specific website/page). This is called relevance score. This is based on the fact that if a page has many other pages link to it, it's probably an important page.
Each site/page is viewed as a node in a graph. Links to other pages are directed edges. A degree of a vertex is defined as the number of incoming edges. Nodes with a higher number of incoming edges are ranked higher.
Here's how the PageRank is determined. Suppose that page Pj has Lj links. If one of those links is to page Pi, then Pj will pass on 1/Lj of its importance to Pi. The importance ranking of Pi is then the sum of all the contributions made by pages linking to it. So if we denote the set of pages linking to Pi by Bi, then we have this formula:
Importance(Pi)= sum( Importance(Pj)/Lj ) for all links from Pi to Bi
The ranks are placed in a matrix called hyperlink matrix: H[i,j]
A row in this matrix is either 0, or 1/Lj if there is a link from Pi to Bi. Another property of this matrix is that if we sum all rows in a column we get 1.
Now we need multiply this matrix by an Eigen vector, named I (with eigen value 1) such that:
I = H*I
Now we start iterating: IH, IIH, IIIH .... I^k *H until the solution converges. ie we get pretty much the same numbers in the matrix in step k and k+1.
Now whatever is left in the I vector is the importance of each page.
For a simple class homework example see http://www.math.cornell.edu/~mec/Winter2009/RalucaRemus/Lecture3/lecture3.html
As for solving the duplicate issue in your interview question, do a checksum on the entire page and use either that or a bash of the checksum as your key in a map to keep track of visited pages.
Depends on how deep their question was intended to be. If they were just trying to avoid following the same links back and forth, then hashing the URL's would be sufficient.
What about content that has literally thousands of URL's that lead to the same content? Like a QueryString parameter that doesn't affect anything, but can have an infinite number of iterations. I suppose you could hash the contents of the page as well and compare URL's to see if they are similar to catch content that is identified by multiple URL's. See for example, Bot Traps mentioned in #Lirik's post.
You'd have to have some sort of hash table to store the results in, you'd just have to check it before each page load.
The problem here is not to crawl duplicated URLS, wich is resolved by a index using a hash obtained from urls. The problem is to crawl DUPLICATED CONTENT. Each url of a "Crawler Trap" is different (year, day, SessionID...).
There is not a "perfect" solution... but you can use some of this strategies:
• Keep a field of wich level the url is inside the website. For each cicle of getting urls from a page, increase the level. It will be like a tree. You can stop to crawl at certain level, like 10 (i think google use this).
• You can try to create a kind of HASH wich can be compared to find similar documents, since you cant compare with each document in your database. There are SimHash from google, but i could not find any implementation to use. Then i´ve created my own. My hash count low and high frequency characters inside the html code and generate a 20bytes hash, wich is compared with a small cache of last crawled pages inside a AVLTree with an NearNeighbors search with some tolerance (about 2). You cant use any reference to characters locations in this hash. After "recognize" the trap, you can record the url pattern of the duplicate content and start to ignore pages with that too.
• Like google, you can create a ranking to each website and "trust" more in one than others.
The web crawler is a computer program which used to collect/crawling following key values(HREF links, Image links, Meta Data .etc) from given website URL. It is designed like intelligent to follow different HREF links which are already fetched from the previous URL, so in this way, Crawler can jump from one website to other websites. Usually, it called as a Web spider or Web Bot. This mechanism always acts as a backbone of the Web search engine.
Please find the source code from my tech blog - http://www.algonuts.info/how-to-built-a-simple-web-crawler-in-php.html
<?php
class webCrawler
{
public $siteURL;
public $error;
function __construct()
{
$this->siteURL = "";
$this->error = "";
}
function parser()
{
global $hrefTag,$hrefTagCountStart,$hrefTagCountFinal,$hrefTagLengthStart,$hrefTagLengthFinal,$hrefTagPointer;
global $imgTag,$imgTagCountStart,$imgTagCountFinal,$imgTagLengthStart,$imgTagLengthFinal,$imgTagPointer;
global $Url_Extensions,$Document_Extensions,$Image_Extensions,$crawlOptions;
$dotCount = 0;
$slashCount = 0;
$singleSlashCount = 0;
$doubleSlashCount = 0;
$parentDirectoryCount = 0;
$linkBuffer = array();
if(($url = trim($this->siteURL)) != "")
{
$crawlURL = rtrim($url,"/");
if(($directoryURL = dirname($crawlURL)) == "http:")
{ $directoryURL = $crawlURL; }
$urlParser = preg_split("/\//",$crawlURL);
//-- Curl Start --
$curlObject = curl_init($crawlURL);
curl_setopt_array($curlObject,$crawlOptions);
$webPageContent = curl_exec($curlObject);
$errorNumber = curl_errno($curlObject);
curl_close($curlObject);
//-- Curl End --
if($errorNumber == 0)
{
$webPageCounter = 0;
$webPageLength = strlen($webPageContent);
while($webPageCounter < $webPageLength)
{
$character = $webPageContent[$webPageCounter];
if($character == "")
{
$webPageCounter++;
continue;
}
$character = strtolower($character);
//-- Href Filter Start --
if($hrefTagPointer[$hrefTagLengthStart] == $character)
{
$hrefTagLengthStart++;
if($hrefTagLengthStart == $hrefTagLengthFinal)
{
$hrefTagCountStart++;
if($hrefTagCountStart == $hrefTagCountFinal)
{
if($hrefURL != "")
{
if($parentDirectoryCount >= 1 || $singleSlashCount >= 1 || $doubleSlashCount >= 1)
{
if($doubleSlashCount >= 1)
{ $hrefURL = "http://".$hrefURL; }
else if($parentDirectoryCount >= 1)
{
$tempData = 0;
$tempString = "";
$tempTotal = count($urlParser) - $parentDirectoryCount;
while($tempData < $tempTotal)
{
$tempString .= $urlParser[$tempData]."/";
$tempData++;
}
$hrefURL = $tempString."".$hrefURL;
}
else if($singleSlashCount >= 1)
{ $hrefURL = $urlParser[0]."/".$urlParser[1]."/".$urlParser[2]."/".$hrefURL; }
}
$host = "";
$hrefURL = urldecode($hrefURL);
$hrefURL = rtrim($hrefURL,"/");
if(filter_var($hrefURL,FILTER_VALIDATE_URL) == true)
{
$dump = parse_url($hrefURL);
if(isset($dump["host"]))
{ $host = trim(strtolower($dump["host"])); }
}
else
{
$hrefURL = $directoryURL."/".$hrefURL;
if(filter_var($hrefURL,FILTER_VALIDATE_URL) == true)
{
$dump = parse_url($hrefURL);
if(isset($dump["host"]))
{ $host = trim(strtolower($dump["host"])); }
}
}
if($host != "")
{
$extension = pathinfo($hrefURL,PATHINFO_EXTENSION);
if($extension != "")
{
$tempBuffer ="";
$extensionlength = strlen($extension);
for($tempData = 0; $tempData < $extensionlength; $tempData++)
{
if($extension[$tempData] != "?")
{
$tempBuffer = $tempBuffer.$extension[$tempData];
continue;
}
else
{
$extension = trim($tempBuffer);
break;
}
}
if(in_array($extension,$Url_Extensions))
{ $type = "domain"; }
else if(in_array($extension,$Image_Extensions))
{ $type = "image"; }
else if(in_array($extension,$Document_Extensions))
{ $type = "document"; }
else
{ $type = "unknown"; }
}
else
{ $type = "domain"; }
if($hrefURL != "")
{
if($type == "domain" && !in_array($hrefURL,$this->linkBuffer["domain"]))
{ $this->linkBuffer["domain"][] = $hrefURL; }
if($type == "image" && !in_array($hrefURL,$this->linkBuffer["image"]))
{ $this->linkBuffer["image"][] = $hrefURL; }
if($type == "document" && !in_array($hrefURL,$this->linkBuffer["document"]))
{ $this->linkBuffer["document"][] = $hrefURL; }
if($type == "unknown" && !in_array($hrefURL,$this->linkBuffer["unknown"]))
{ $this->linkBuffer["unknown"][] = $hrefURL; }
}
}
}
$hrefTagCountStart = 0;
}
if($hrefTagCountStart == 3)
{
$hrefURL = "";
$dotCount = 0;
$slashCount = 0;
$singleSlashCount = 0;
$doubleSlashCount = 0;
$parentDirectoryCount = 0;
$webPageCounter++;
while($webPageCounter < $webPageLength)
{
$character = $webPageContent[$webPageCounter];
if($character == "")
{
$webPageCounter++;
continue;
}
if($character == "\"" || $character == "'")
{
$webPageCounter++;
while($webPageCounter < $webPageLength)
{
$character = $webPageContent[$webPageCounter];
if($character == "")
{
$webPageCounter++;
continue;
}
if($character == "\"" || $character == "'" || $character == "#")
{
$webPageCounter--;
break;
}
else if($hrefURL != "")
{ $hrefURL .= $character; }
else if($character == "." || $character == "/")
{
if($character == ".")
{
$dotCount++;
$slashCount = 0;
}
else if($character == "/")
{
$slashCount++;
if($dotCount == 2 && $slashCount == 1)
$parentDirectoryCount++;
else if($dotCount == 0 && $slashCount == 1)
$singleSlashCount++;
else if($dotCount == 0 && $slashCount == 2)
$doubleSlashCount++;
$dotCount = 0;
}
}
else
{ $hrefURL .= $character; }
$webPageCounter++;
}
break;
}
$webPageCounter++;
}
}
$hrefTagLengthStart = 0;
$hrefTagLengthFinal = strlen($hrefTag[$hrefTagCountStart]);
$hrefTagPointer =& $hrefTag[$hrefTagCountStart];
}
}
else
{ $hrefTagLengthStart = 0; }
//-- Href Filter End --
//-- Image Filter Start --
if($imgTagPointer[$imgTagLengthStart] == $character)
{
$imgTagLengthStart++;
if($imgTagLengthStart == $imgTagLengthFinal)
{
$imgTagCountStart++;
if($imgTagCountStart == $imgTagCountFinal)
{
if($imgURL != "")
{
if($parentDirectoryCount >= 1 || $singleSlashCount >= 1 || $doubleSlashCount >= 1)
{
if($doubleSlashCount >= 1)
{ $imgURL = "http://".$imgURL; }
else if($parentDirectoryCount >= 1)
{
$tempData = 0;
$tempString = "";
$tempTotal = count($urlParser) - $parentDirectoryCount;
while($tempData < $tempTotal)
{
$tempString .= $urlParser[$tempData]."/";
$tempData++;
}
$imgURL = $tempString."".$imgURL;
}
else if($singleSlashCount >= 1)
{ $imgURL = $urlParser[0]."/".$urlParser[1]."/".$urlParser[2]."/".$imgURL; }
}
$host = "";
$imgURL = urldecode($imgURL);
$imgURL = rtrim($imgURL,"/");
if(filter_var($imgURL,FILTER_VALIDATE_URL) == true)
{
$dump = parse_url($imgURL);
$host = trim(strtolower($dump["host"]));
}
else
{
$imgURL = $directoryURL."/".$imgURL;
if(filter_var($imgURL,FILTER_VALIDATE_URL) == true)
{
$dump = parse_url($imgURL);
$host = trim(strtolower($dump["host"]));
}
}
if($host != "")
{
$extension = pathinfo($imgURL,PATHINFO_EXTENSION);
if($extension != "")
{
$tempBuffer ="";
$extensionlength = strlen($extension);
for($tempData = 0; $tempData < $extensionlength; $tempData++)
{
if($extension[$tempData] != "?")
{
$tempBuffer = $tempBuffer.$extension[$tempData];
continue;
}
else
{
$extension = trim($tempBuffer);
break;
}
}
if(in_array($extension,$Url_Extensions))
{ $type = "domain"; }
else if(in_array($extension,$Image_Extensions))
{ $type = "image"; }
else if(in_array($extension,$Document_Extensions))
{ $type = "document"; }
else
{ $type = "unknown"; }
}
else
{ $type = "domain"; }
if($imgURL != "")
{
if($type == "domain" && !in_array($imgURL,$this->linkBuffer["domain"]))
{ $this->linkBuffer["domain"][] = $imgURL; }
if($type == "image" && !in_array($imgURL,$this->linkBuffer["image"]))
{ $this->linkBuffer["image"][] = $imgURL; }
if($type == "document" && !in_array($imgURL,$this->linkBuffer["document"]))
{ $this->linkBuffer["document"][] = $imgURL; }
if($type == "unknown" && !in_array($imgURL,$this->linkBuffer["unknown"]))
{ $this->linkBuffer["unknown"][] = $imgURL; }
}
}
}
$imgTagCountStart = 0;
}
if($imgTagCountStart == 3)
{
$imgURL = "";
$dotCount = 0;
$slashCount = 0;
$singleSlashCount = 0;
$doubleSlashCount = 0;
$parentDirectoryCount = 0;
$webPageCounter++;
while($webPageCounter < $webPageLength)
{
$character = $webPageContent[$webPageCounter];
if($character == "")
{
$webPageCounter++;
continue;
}
if($character == "\"" || $character == "'")
{
$webPageCounter++;
while($webPageCounter < $webPageLength)
{
$character = $webPageContent[$webPageCounter];
if($character == "")
{
$webPageCounter++;
continue;
}
if($character == "\"" || $character == "'" || $character == "#")
{
$webPageCounter--;
break;
}
else if($imgURL != "")
{ $imgURL .= $character; }
else if($character == "." || $character == "/")
{
if($character == ".")
{
$dotCount++;
$slashCount = 0;
}
else if($character == "/")
{
$slashCount++;
if($dotCount == 2 && $slashCount == 1)
$parentDirectoryCount++;
else if($dotCount == 0 && $slashCount == 1)
$singleSlashCount++;
else if($dotCount == 0 && $slashCount == 2)
$doubleSlashCount++;
$dotCount = 0;
}
}
else
{ $imgURL .= $character; }
$webPageCounter++;
}
break;
}
$webPageCounter++;
}
}
$imgTagLengthStart = 0;
$imgTagLengthFinal = strlen($imgTag[$imgTagCountStart]);
$imgTagPointer =& $imgTag[$imgTagCountStart];
}
}
else
{ $imgTagLengthStart = 0; }
//-- Image Filter End --
$webPageCounter++;
}
}
else
{ $this->error = "Unable to proceed, permission denied"; }
}
else
{ $this->error = "Please enter url"; }
if($this->error != "")
{ $this->linkBuffer["error"] = $this->error; }
return $this->linkBuffer;
}
}
?>
Well the web is basically a directed graph, so you can construct a graph out of the urls and then do a BFS or DFS traversal while marking the visited nodes so you don't visit the same page twice.
This is a web crawler example. Which can be used to collect mac Addresses for mac spoofing.
#!/usr/bin/env python
import sys
import os
import urlparse
import urllib
from bs4 import BeautifulSoup
def mac_addr_str(f_data):
global fptr
global mac_list
word_array = f_data.split(" ")
for word in word_array:
if len(word) == 17 and ':' in word[2] and ':' in word[5] and ':' in word[8] and ':' in word[11] and ':' in word[14]:
if word not in mac_list:
mac_list.append(word)
fptr.writelines(word +"\n")
print word
url = "http://stackoverflow.com/questions/tagged/mac-address"
url_list = [url]
visited = [url]
pwd = os.getcwd();
pwd = pwd + "/internet_mac.txt";
fptr = open(pwd, "a")
mac_list = []
while len(url_list) > 0:
try:
htmltext = urllib.urlopen(url_list[0]).read()
except:
url_list[0]
mac_addr_str(htmltext)
soup = BeautifulSoup(htmltext)
url_list.pop(0)
for tag in soup.findAll('a',href=True):
tag['href'] = urlparse.urljoin(url,tag['href'])
if url in tag['href'] and tag['href'] not in visited:
url_list.append(tag['href'])
visited.append(tag['href'])
Change the url to crawl more sites......good luck