I
have developed an ”Adaptive Crawler” platform to address all types of crawling
tasks that described as follows in diﬀerent sections: Description

 Adaptive Crawler is a general
solution of crawling websites that is suitable for diﬀerent methods of crawling
for various types of websites. My Adaptive Crawler will distinguish the type of
website and crawl it by appropriate methods. This Adaptive method will ensure
the performance of web crawling and correctness of the output. First of all,
the diﬀerent rules of crawling according to the selected URL is stored in a
JSON ﬁle, and then the Crawler module uses these rules to retrieve diﬀerent
parts of the website. I used my IP rotation server to overcome any forbidden
access issues. This module helps the Crawler to have instant access to the
content of URLs. Incapsula, Mechanical Soup, and Google Bot are my main tools
for crawling the URLs according to their contents. My Adaptive Crawler uses
these tools to get access to the HTML of diﬀerent types of websites. To have
the best performance in processing time, Distributed Crawling module runs the
Crawler on diﬀerent workers with various cores of CPU. Parallel processing is
used to run our service in parallel mode to get our best performance. User Manual

 I need to organize our
websites in one input ﬁle, and select our output type for the result of
crawling. The input URLs can write in one JSON ﬁle and the output can store in
a database such as MySQL or MongoDB. Advantages

 My Adaptive
Crawler has diﬀerent advantages in comparison with other Crawlers that
mentioned follows. These advantages are our main novelties in crawling the
websites.

 Adaptive
Procedure Distributed
Architecture Parallel
Processing IP Rotation Why
work with me&nbsp; Experience:
I am experienced developer in the subject of web crawling techniques that
employ diﬀerent methods to instant access of websites’ html. 

Projects: I have done several
projects, crawling well-known sites such as Amazon, Alibaba, Wikipedia, etc. Architecture I
have demonstrated my model in Adaptive Crawler using a ﬂowchart to clearly
illustrate my features in crawling. This ﬂowchart consisted of diﬀerent parts
of our crawling method beside our features. IP Rotation

 I have bought an IP rotation
service that provides me about 25000 distinct IP and User-Agent sets to enables
us to overcome the forbidden content issues for some websites. This feature of our
Adaptive Crawler is needed to have instant access of websites to crawl them
without any interruption or manual IP setting. Incapsula

 Incapsula have identiﬁed that
most of the world’s bot traﬃc comes from 35 “Good” crawlers (including
Majestic) and a bunch of bad bots which we will not go into too much today.
Although, it is notable that some particularly unsophisticated ﬁrewall systems
block some bots by user agents without giving their customers any way out, this
is ill advised. The numbers below each bot represents the percentage of visits
to the pages tracked that were attributed to each bot. So at the top,
Facebook’s mobile app grabs a whopping 4.16 percent of bandwidth. Google is
commanding 3.87 percent of the entire world’s bandwidth. It’s actually more
when you look at the other bots owned by Google. This is, I would say, fair
enough. Google and Facebook have been instrumental in helping to keep an
otherwise chaotic system integrated, connected and navigable. Clearly the top
row of Search Engines have that in common, although Majestic is grateful to
Incapsula for categorizing Majestic as a search engine and on the top row. We
do appreciate that we have several peers on row two and Majestic would not have
looked out of place there. Mechanical
Soup A
Python library for automating interaction with websites. MechanicalSoup
automatically stores and sends cookies, follows redirects, and can follow links
and submit forms. It doesn’t do JavaScript. MechanicalSoup provides a similar
API, built on Python giants Requests (for http sessions) and BeautifulSoup (for
document navigation). Since 2017 it is a project actively maintained by a small
team. Google Bot Google
introduced a slight change into its Search Result Pages by attaching a short
explanation snippet to all URLs blocked by the Robots.txt ﬁle or an on-page
Robots Meta-tag. The announcement simply stated: ”A description for this result
is not available because of this site’s robots.txt” From time to time we’ve
seen website owners blocking URLs with robot.txt (i.e. admin panel URLs) and
later on surprised to ﬁnd them still appearing on Google. This is nothing new
because, as oﬃcially stated by Google. Googlebot is a website’s most loyal
returning visitor and for most of us, also the most important one.
Understanding Googlebot’s behavior, needs and wants is key to a website’s
success. Dynamic
Crawling Many
of the websites are JavaScript heavy and generates content by doing
asynchronous JavaScript calls after page is loaded. The diﬀerent JS frameworks
like Angular, React.js, and Vue.js are popular. The use of these frameworks
makes developer life simpler and provides many beneﬁts for creating dynamic sites.
The web crawler needs HTTP response code and header information to manage the
crawling. E.g. The Status code is important to check which redirects and
deletes for the page and to handle those appropriately. The diﬀerent headers
like Last-Modiﬁed, ETagare used by scheduler to identify frequently modiﬁed
pages and make schedule to crawl them more frequently. There is needed to know
the Cookies, Access Token, Xsrf-Id and so one to use them in the POST request
and get the accurate results. Parallel and Distributed
Crawling

Beside all
Adaptive Crawling requirements, time of computation (TOC) is the major factor
to fail a crawling system. Using he capacity of Multi-cores CPU and allowing
them to run as distributed in the cores of CPU, will help us to tackle the TOC
issue.

&nbsp;

 Tech Support

I will technically support my
Crawler services at any time of the day. It is possible to answer your question
and even adding new features to the service.

Distributed Smart Adaptive Web Crawler

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