What Is Web Scraping? All You Need to Know

Web
scraping
is
the
process
of
extracting
data
from
websites,
typically
employing
automatic
tools
or
bots.
It
is
used
across
different
industries,
such
as
marketing,
finance,
E-commerce,
and
real
estate.
Web
scraping
helps
companies
find
their
target
audience,
generate
leads,
analyze
the
market
and
their
competitors,
and
create
a
better
strategy
to
grow
their
businesses.

What
Is
Web
Scraping?

The
act
of
copying
data
from
websites
by
using
bots
or
automatic
tools
and
collecting
or
storing
it
for
later
use
is
called
web
scraping.
The
process
involves
downloading
web
pages
and
copying
their
data
into
a
local
database
or
spreadsheet.
Companies
or
individuals
who
web
scrape
want
to
gather
a
sizable
amount
of
data
that
can’t
be
collected
manually
in
a
short
timeframe.

Web
scraping
is
a
common
approach
to
collecting
data.
After
receiving
the
data
through
web
scraping,
the
analyzing
process
begins,
and
the
data
is
organized
and
curated
for
different
use
cases.
Legal
web
scraping
is
about
retrieving
public
web
data
that
is
freely
accessible;
it
does
not
refer
to
accessing
private
data
from
the
web.

Some
websites
tend
to
prevent
web
scraping
with
bot
detection
methods
to
preserve
server
resources
for
actual
users.
Due
to
this,
the
web
scraping
process
can
get
tedious
if
you
don’t
utilize
the
most
advanced
techniques
and
tools.

How
Web
Scraping
Works

The
web
scraping
process
is
divided
into
5
main
stages.

1.
HTTP
Request

When
you
specify
the
webpage
URL
to
scrape,
the
web
scraping
tool
sends
an
HTTP
request
to
the
web
server.
This
is
a
GET
request
for
retrieving
data,
but
occasionally,
it
can
be
a
POST
request
for
submitting
data,
such
as
when
filling
out
a
website
form.

2.
Server
Response

The
server
will
receive
the
request
and
process
it.
The
web
server
will
send
back
an
HTTP
response.
The
response
includes
a
status
code
indicating
whether
the
request
was
successful.
For
unsuccessful
requests,
you
can
see
error
messages
such
as
“403
Forbidden”
or
“404
Not
Found”.
The
successful
requests
will
include
the
HTML
content
of
the
requested
webpage.

3.
Parsing
Process

The
HTML
document
is
challenging
to
navigate;
hence,
parsing
is
required.
HTML
parsing
can
be
done
using
different
libraries
such
as
BeautifulSoup
and
Cheerio.
This
helps
you
better
navigate
the
HTML
content’s
Document
Object
Model
(DOM)
tree
and
locate
the
specific
data
you
want.

4.
Handling
Dynamic
Content

If
you
want
to
scrape
modern
websites
that
utilize
JavaScript
to
load
content
dynamically,
the
data
you
need
won’t
be
available
through
the
initial
HTML
response.
To
access
the
data
on
these
websites,
web
data
scraping
tools
and
bots
use
techniques
like
headless
browsers
to
execute
JavaScript
and
extract
the
dynamically
loaded
content.

5.
Data
Storage

Lastly,
you
have
to
store
the
data
in
a
clean
and
structured
way
to
analyze
the
data
effectively.
Web
scraping
tools
can
remove
unwanted
characters
from
the
data
and
convert
it
into
a
consistent
and
manageable
format,
like
a
table
or
list.
Then,
you
can
store
the
data
in
a
usable
format,
such
as
SQL
databases,
Excel
files,
JSON
files,
and
more.

Different
Types
of
Web
Scrapers

Web
scrapers
have
3
different
types,
which
are
based
on
their
functions
and
features.

1. 
   Self-built
   Scrapers:
   The
   most
   flexible
   type
   of
   Web
   Scrapers
   are
   self-built
   scrapers.
   These
   custom-built
   programs
   or
   scripts
   can
   be
   easily
   integrated
   with
   other
   programs
   and
   handle
   large-scale
   web
   scraping.
   There
   are
   many

   web
   scraping
   frameworks
   that
   you
   can
   employ
   to
   build
   a
   suitable
   scraper
   for
   your
   needs.

2. 
   Browser
   Extension:
   If
   you’re
   looking
   for
   a
   user-friendly
   and
   lightweight
   scraping
   tool,
   web
   scraping
   or
   screen
   scraping
   browser
   extensions
   are
   a
   good
   choice.
   The
   setup
   is
   quick,
   it’s
   easy
   to
   use,
   and
   doesn’t
   require
   any
   coding.
   However,
   these
   types
   of
   scrapers
   are
   designed
   for
   small
   amounts
   of
   data
   extraction
   and
   have
   limited
   capabilities.
3. 
   Cloud-based:
   Many
   web
   scraping
   services
   are
   cloud-based
   and
   run
   on
   remote
   servers.
   The
   setup
   for
   these

   web
   scraping
   solutions
   is
   easy,
   and
   they
   offer
   advanced
   features
   like
   CAPTCHA
   solving
   and
   data
   storage.
   However,
   you
   need
   to
   pay
   a
   subscription
   cost
   to
   access
   the
   tools.

What
Is
Web
Scraping
Used
for?

There
are
12
main
reasons
to
use
a
web
scraper.

1. 
   Price
   Comparison:
   Collecting
   and
   comparing
   the
   prices
   of
   products
   and
   services
   from
   e-commerce
   sites
   helps
   individuals
   find
   the
   best
   deals,
   and
   companies
   can
   stay
   ahead
   of
   their
   competitors
   by
   offering
   the
   most
   affordable
   price.
2. 
   Lead
   Generation:
   Gathering
   leads
   from
   websites,
   such
   as
   LinkedIn
   and
   Facebook,
   can
   help
   businesses
   find
   their
   target
   audience
   and
   plan
   marketing
   campaigns.
3. 
   Market
   Research:
   Extracting
   data
   on
   consumer
   behavior,
   market
   trends,
   and
   competitor
   analysis
   provides
   valuable
   insights
   for
   companies.
   This
   helps
   them
   make
   accurate
   business
   decisions,
   business
   intelligence
   strategies,
   and
   product
   development
   plans.
4. 
   News
   Aggregation:
   News
   aggregation
   sites
   like
   Google
   News
   scrape
   headlines
   and
   articles
   from
   multiple
   sources.
5. 
   Academic
   Research:
   Research
   requires
   large
   datasets,
   and
   website
   scraping
   can
   quickly
   provide
   them.
   Content
   aggregation
   from
   online
   databases
   and
   social
   media
   is
   helpful
   to
   academic
   researchers.
6. 
   Real
   Estate:
   Collecting
   data
   on
   property
   prices,
   locations,
   and
   listings
   is
   a
   routine
   procedure
   for
   real
   estate
   agents.
   This
   enables
   users
   to
   find
   the
   best
   property
   based
   on
   different
   factors.
   It
   also
   helps
   real
   estate
   platforms
   find
   more
   customers
   and
   track
   market
   trends.
7. 
   Financial
   Data:
   Scraping
   market
   news,
   financial
   statements,
   and
   stock
   prices
   benefit
   investors.
   Financial
   analysts
   make
   investment
   decisions
   and
   enhance
   their
   risk
   management
   strategy
   based
   on
   the
   data
   scraped
   from
   various
   websites.
8. 
   Sentiment
   Analysis:
   Gauging
   sentiment
   around
   different
   factors
   of
   a
   product,
   service,
   event,
   or
   a
   certain
   topic
   through
   web
   scraping
   can
   lead
   to
   improved
   marketing
   strategies
   and
   meaningful
   communication
   with
   the
   audience.
9. 
   Email
   Marketing:
   Collecting
   email
   addresses
   of
   potential
   customers
   from
   various
   websites
   is
   one
   of
   web
   scraping’s
   most
   common
   uses.
   With
   this
   approach,
   businesses
   can
   quickly
   build
   target
   audience
   email
   lists
   and
   elevate
   the
   effectiveness
   of
   email
   marketing
   campaigns.
10. 
    Brand
    Monitoring:
    Managing
    a
    brand’s
    reputation
    is
    crucial
    to
    stay
    ahead
    of
    competitors.
    Analyzing
    overall
    public
    opinion
    about
    the
    brand
    and
    studying
    product
    reviews
    can
    be
    used
    for
    brand
    management
    purposes
    and
    help
    businesses
    respond
    to
    customer
    feedback.
11. 
    Business
    Automation:
    Another
    benefit
    of
    web
    scraping
    is
    streamlining
    repetitive
    business
    processes
    and
    tasks
    like
    content
    monitoring,
    data
    entry,
    and
    reporting.
    This
    can
    significantly
    save
    businesses
    time
    and
    resources.
12. 
    MAP
    Monitoring:
    Minimum
    Advertised
    Price
    (MAP)
    monitoring
    refers
    to
    the
    process
    of
    tracking
    how
    products
    are
    priced
    across
    different
    platforms
    and
    retailers.
    If
    a
    partner
    retailer
    sells
    the
    product
    below
    the
    agreed
    price,
    the
    company
    can
    easily
    find
    out
    by
    using
    web
    scraping
    and
    taking
    the
    proper
    action.

Is
Web
Scraping
Legal?

The
act
of
web
scraping
is
legal,
but
you
need
to
be
careful
about
what
you
scrape.
If
the
information
is
protected
by
terms
of
service
or
international
regulations,
scraping
such
information
will
lead
to
legal
issues.
Here
are
the
legal
and
ethical
considerations
of
web
scraping:

1.
Website
Terms
of
Service

Some
websites
prohibit
automated
scraping
in
their
Terms
of
Service
(ToS)
agreements.
Always
check
the
Terms
of
Service
before
starting
the
web
scraping
process.
Violating
these
agreements,
in
some
cases,
could
lead
to
legal
consequences.

2.
Data
Privacy
Regulations

Laws
and
regulations
vary
from
region
to
region,
and
some
countries
have
strict
rules
for
collecting
personal
data.
For
example,
in
the
European
Union,
based
on
the
General
Data
Protection
Regulation
(GDPR),
scraping
personal
data
can
result
in
significant
fines.

3.
Copyright
Laws

Ensure
that
your
data
scraping
process
doesn’t
involve
violating
copyright
laws.
Scraping
and
publishing
copyrighted
content
from
websites
without
permission
is
illegal.
However,
scraping
copyrighted
content
is
considered
fair
use
for
research
and
education.

4.
Ethical
Practices

Avoid
using
malicious
scrapers
or
bots
that
can
overwhelm
servers
with
excessive
requests
to
scrap
private
data.
If
the
tool
is
scraping
private
information,
immediately
stop
the
process.
Even
if
you
can’t
find
a
strict
regulation
against
your
specific
web
scraping
approach,
a
website
owner
or
user
can
identify
you
and
take
legal
action
for
malicious
web
scraping.

Common
Challenges
of
Web
Scraping

There
are
5
main
challenges
of
web
scraping.

• 
  Handling
  Dynamic
  Content:
  Modern
  websites
  employ
  JavaScript
  to
  load
  the
  content
  dynamically.
  As
  a
  result,
  the
  initial
  HTML
  document
  doesn’t
  provide
  the
  desired
  data.
  A
  basic
  web
  scraping
  bot
  can’t
  be
  used
  in
  this
  case.
  As
  a
  solution,
  scrapers
  use
  headless
  browsers
  or
  JavaScript
  scraping
  frameworks
  to
  access
  the
  content.
• 
  CAPTCHAs
  and
  Anti-Scraping
  Measures:
  Websites
  employ
  various
  anti-scraping
  measures,
  such
  as
  CAPTCHAs,
  to
  prevent
  bot
  access.
  CAPTCHAs
  are
  evolving;
  nowadays,
  they
  are
  much
  more
  than
  simple
  input
  of
  numbers
  and
  letters.
  These
  advanced
  measures
  hinder
  web
  scraping,
  so
  you
  need
  to
  use
  suitable
  tools
  like

  CAPTCHA
  solver
  APIs
  to
  access
  the
  protected
  websites.

• 
  IP
  Blocking
  and
  Rate
  Limiting:
  Excessive
  scraping
  from
  a
  single
  IP
  address
  can
  trigger
  IP
  blocking
  and
  rate
  limiting
  from
  websites.
  Hence,
  users
  take
  advantage
  of
  proxies
  and
  IP
  rotation
  features
  to
  access
  the
  website
  with
  another
  IP
  address.
• 
  Website
  Structure
  Changes:
  Websites
  frequently
  update
  their
  structure
  and
  HTML/CSS
  code,
  which
  can
  disrupt
  web
  scraping.
  Using
  flexible
  scraping
  tools
  can
  only
  minimize
  the
  effects
  of
  these
  changes
  and
  not
  eliminate
  them.
• 
  JavaScript
  Rendering:
  Websites
  that
  utilize
  JavaScript
  frameworks,
  like
  Angular,
  often
  render
  content
  on
  the
  client
  side.
  So,
  a
  simple
  HTTP
  request
  won’t
  provide
  the
  full
  content.
  Headless
  browsers
  and
  dynamic
  scraping
  libraries
  can
  handle
  JavaScript
  rendering
  and
  deal
  with
  modern
  JavaScript
  frameworks.

Web
scraping
is
not
without
its
challenges,
and
these
obstacles
are
becoming
increasingly
complex
with
advances
in
website
security
measures
and
new
technologies
for
IP
blocks.

Can
I
Use
ChatGPT
to
Scrape
Website?

Yes,
you
can
use
ChatGPT
to
scrape
a
website.
However,
the
standard
version
of
ChatGPT
can’t
handle
Web
Scraping
requests.
With
a
“Scraper”
plugin,
ChatGPT
gains
scraping
capabilities.
To
use
this
plugin,
you
need
to
subscribe
to
the
paid
version
of
ChatGPT.

Installing
the
Scraper
plugin
won’t
be
enough
if
you
want
to
scrape
a
website
with
a
complex
structure
or
anti-scraping
measures.
In
these
situations,
you
have
to
use
the
ChatGPT
Code
Interpreter.
For
this,
you
must
download
the
source
HTML,
upload
it
to
the
Code
Interpreter,
and
ask
the
AI
to
scrape
the
data.
You
can
use
our

ChatGPT
guide
for
web
scraping
and
follow
the
listed
steps
to
successfully
scrape
using
ChatGPT.

Future
Trends
in
Web
Scraping

There
are
4
key
trends
for
the
future
of
web
scraping.

• 
  API-Based
  Scraping:
  The
  trend
  of
  API-first
  designs
  for
  websites
  is
  on
  the
  rise.
  Compared
  to
  traditional
  HTML
  scraping,
  API
  (Application
  Programming
  Interface)
  scraping
  is
  more
  efficient.
• 
  AI
  and
  Machine
  Learning:
  With
  the
  rise
  of
  Artificial
  Intelligence
  tools,
  some
  technologies
  can
  automatically
  identify
  and
  extract
  data
  from
  websites.
  Furthermore,
  Machine
  Learning
  models
  are
  becoming
  more
  accurate
  at
  recognizing
  web
  content
  patterns.
• 
  Open
  Source
  Scraping
  Tools:
  Many
  open-source
  communities
  are
  constantly
  developing
  advanced
  web
  scraping
  tools
  and
  libraries.
  As
  more
  AI
  scraping
  tools
  are
  created
  and
  big
  tech
  teams
  are
  less
  likely
  to
  develop
  bots,
  the
  open-source
  communities
  will
  likely
  grow,
  and
  we
  can
  expect
  more
  collaborations
  and
  tools
  to
  be
  accessible
  to
  everyone.
• 
  Cloud-Based
  Services:
  With
  the
  advancements
  in
  web
  scraping
  technologies,
  many
  cloud-based
  platforms
  like
  Bright
  Data
  emerge
  and
  offer
  services
  that
  simplify
  the
  process.
  These
  platforms
  have
  started
  taking
  advantage
  of
  AI.
  Expect
  to
  see
  more
  services
  with
  advanced
  AI
  tools
  and
  real-time
  scraping
  capabilities
  in
  the
  future.

There
are
4
popular
web
scraping
tools,
based
on
their
functionalities
and
features.