Julia is a dynamic general purpose programming language popular for scientific computing and big data analytics. It is extremely fast thanks to its use of a JIT compiler and allows developers to write concise, yet powerful code. 

#compsci #programming #100SecondsOfCode

🔗 Resources

Julia Language https://julialang.org/
Why Julia? https://julialang.org/blog/2012/02/why-we-created-julia/
Python in 100 Seconds https://youtu.be/x7X9w_GIm1s
C in 100 Seconds https://youtu.be/U3aXWizDbQ4

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🔖 Topics Covered

- Julia basics tutorial
- Julia vs Python
- Julia vs R
- what is Julia used for?
- who created Julia?
- parametric types and polymorphism explained
- Julia type system explained
- is Julia easy to learn?
2024-02-04T05:26:41.913Z
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2024-01-09.29447
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67875a7f-c9c4-48a0-aa55-5bdb8a91c34a
deprecated
Julia, a dynamic general purpose programming language capable of high performance scientific computing with high level code.
It was created in 2012 by a gang of scientists, who set out to build a language with the speed of c, the dynamism of Ruby, the practicality of Python that can do statistics like and linear algebra like MATLAB out of the box.
It's a general purpose language, but is most well known for its use in numerical analysis, data visualization, and machine learning.
It's fast because unlike most high level languages, it uses a just in time compiler to convert your source code into machine code before running it.
And unlike most dynamic languages, computers.
It has a flexible parametric type system.
That means static typing is optional by default and types can take parameters allowing one type to represent many different possibilities.
This opens the door to the multiple dispatch pattern where one function can have multiple methods or implementations based on its input parameters, and the language will determine which method to dispatch at runtime.
In fact, even operators like plus are functions that use multiple dispatch to handle a variety of different type combinations.
To get started, install Julia, then create a file ending in dot jl.
Declare a variable by providing a name, then assign a value to it.
Name support UTF8 like emojis or mathematical symbols.
It uses symbols to represent built in constants like pi, allowing you to write equations more elegantly in your code.
Like Perl, it's very good at string parsing and supports multiple expressions on a single line resulting in terse yet powerful code.
Define a function with the function keyword and close with the end keyword or shorten it to a single line with the equal sign or because functions are first class objects, they can be assigned to a variable or passed to another function anonymously.
What's interesting no.
Is that by default, a function is untyped, which means it implements one method to handle all inputs.
If the function is redefined, but this time with a type for the arguments, a another method is added to it.
When this function is called at runtime, Julia will look at the type of the arguments and dispatch the corresponding method.
In we can pass a type as a parameter, then use keywords like where to perform logic on the type itself.
In this case, it will assert that both types are the same.
Now, Julia is not an object oriented language in the classic sense.
However, it does support composite types with structs, which contain multiple fields and optional types.
Like any good scientific language, It has very well thought out support for arrays, with many built in functions to initialize and compute values over multidimensional arrays.
It supports asynchronous computing with its task model, which can pause and synchronize the execution of code like coroutines in other languages.
And finally, when it comes to big data, it can even distribute process into multiple memory spaces or machines and run natively on a GPU.
This has been Julia in 100 seconds.
If you wanna see more short videos hit the like button and subscribe.
Thanks for watching and I will see you in the next one.

Speaker 0: Julia, a dynamic general purpose programming language capable of high performance scientific computing with high level code. It was created in 2012 by a gang of scientists, who set out to build a language with the speed of c, the dynamism of Ruby, the practicality of Python that can do statistics like and linear algebra like MATLAB out of the box. It's a general purpose language, but is most well known for its use in numerical analysis, data visualization, and machine learning. It's fast because unlike most high level languages, it uses a just in time compiler to convert your source code into machine code before running it. And unlike most dynamic languages, computers.

It has a flexible parametric type system. That means static typing is optional by default and types can take parameters allowing one type to represent many different possibilities. This opens the door to the multiple dispatch pattern where one function can have multiple methods or implementations based on its input parameters, and the language will determine which method to dispatch at runtime. In fact, even operators like plus are functions that use multiple dispatch to handle a variety of different type combinations. To get started, install Julia, then create a file ending in dot jl.

Declare a variable by providing a name, then assign a value to it. Name support UTF8 like emojis or mathematical symbols. It uses symbols to represent built in constants like pi, allowing you to write equations more elegantly in your code. Like Perl, it's very good at string parsing and supports multiple expressions on a single line resulting in terse yet powerful code. Define a function with the function keyword and close with the end keyword or shorten it to a single line with the equal sign or because functions are first class objects, they can be assigned to a variable or passed to another function anonymously.

What's interesting no. Is that by default, a function is untyped, which means it implements one method to handle all inputs. If the function is redefined, but this time with a type for the arguments, a another method is added to it. When this function is called at runtime, Julia will look at the type of the arguments and dispatch the corresponding method. In we can pass a type as a parameter, then use keywords like where to perform logic on the type itself.

In this case, it will assert that both types are the same. Now, Julia is not an object oriented language in the classic sense. However, it does support composite types with structs, which contain multiple fields and optional types. Like any good scientific language, It has very well thought out support for arrays, with many built in functions to initialize and compute values over multidimensional arrays. It supports asynchronous computing with its task model, which can pause and synchronize the execution of code like coroutines in other languages.

And finally, when it comes to big data, it can even distribute process into multiple memory spaces or machines and run natively on a GPU. This has been Julia in 100 seconds. If you wanna see more short videos hit the like button and subscribe. Thanks for watching and I will see you in the next one.
Julia, a dynamic general purpose programming language capable of high performance scientific computing with high level code. It was created in 2012 by a gang of scientists, who set out to build a language with the speed of c, the dynamism of Ruby, the practicality of Python that can do statistics like and linear algebra like MATLAB out of the box. It's a general purpose language, but is most well known for its use in numerical analysis, data visualization, and machine learning. It's fast because unlike most high level languages, it uses a just in time compiler to convert your source code into machine code before running it. And unlike most dynamic languages, computers. It has a flexible parametric type system. That means static typing is optional by default and types can take parameters allowing one type to represent many different possibilities. This opens the door to the multiple dispatch pattern where one function can have multiple methods or implementations based on its input parameters, and the language will determine which method to dispatch at runtime. In fact, even operators like plus are functions that use multiple dispatch to handle a variety of different type combinations.
machine learning
programming
languages
software development
software
computer science
operations
To get started, install Julia, then create a file ending in dot jl.
Declare a variable by providing a name, then assign a value to it. Name support UTF8 like emojis or mathematical symbols. It uses symbols to represent built in constants like pi, allowing you to write equations more elegantly in your code. Like Perl, it's very good at string parsing and supports multiple expressions on a single line resulting in terse yet powerful code.
programming
Define a function with the function keyword and close with the end keyword or shorten it to a single line with the equal sign or because functions are first class objects, they can be assigned to a variable or passed to another function anonymously. What's interesting no. Is that by default, a function is untyped, which means it implements one method to handle all inputs. If the function is redefined, but this time with a type for the arguments, a another method is added to it. When this function is called at runtime, Julia will look at the type of the arguments and dispatch the corresponding method. In we can pass a type as a parameter, then use keywords like where to perform logic on the type itself.
In this case, it will assert that both types are the same. Now, Julia is not an object oriented language in the classic sense. However, it does support composite types with structs, which contain multiple fields and optional types. Like any good scientific language, It has very well thought out support for arrays, with many built in functions to initialize and compute values over multidimensional arrays. It supports asynchronous computing with its task model, which can pause and synchronize the execution of code like coroutines in other languages. And finally, when it comes to big data, it can even distribute process into multiple memory spaces or machines and run natively on a GPU. This has been Julia in 100 seconds. If you wanna see more short videos hit the like button and subscribe. Thanks for watching and I will see you in the next one.
programming
youtube
databases
languages
Julia, a dynamic general purpose programming language capable of high performance scientific computing with high level code. It was created in 2012 by a gang of scientists, who set out to build a language with the speed of c, the dynamism of Ruby, the practicality of Python that can do statistics like and linear algebra like MATLAB out of the box. It's a general purpose language, but is most well known for its use in numerical analysis, data visualization, and machine learning. It's fast because unlike most high level languages, it uses a just in time compiler to convert your source code into machine code before running it. And unlike most dynamic languages, computers. It has a flexible parametric type system. That means static typing is optional by default and types can take parameters allowing one type to represent many different possibilities. This opens the door to the multiple dispatch pattern where one function can have multiple methods or implementations based on its input parameters, and the language will determine which method to dispatch at runtime. In fact, even operators like plus are functions that use multiple dispatch to handle a variety of different type combinations. To get started, install Julia, then create a file ending in dot jl. Declare a variable by providing a name, then assign a value to it. Name support UTF8 like emojis or mathematical symbols. It uses symbols to represent built in constants like pi, allowing you to write equations more elegantly in your code. Like Perl, it's very good at string parsing and supports multiple expressions on a single line resulting in terse yet powerful code. Define a function with the function keyword and close with the end keyword or shorten it to a single line with the equal sign or because functions are first class objects, they can be assigned to a variable or passed to another function anonymously. What's interesting no. Is that by default, a function is untyped, which means it implements one method to handle all inputs. If the function is redefined, but this time with a type for the arguments, a another method is added to it. When this function is called at runtime, Julia will look at the type of the arguments and dispatch the corresponding method. In we can pass a type as a parameter, then use keywords like where to perform logic on the type itself. In this case, it will assert that both types are the same. Now, Julia is not an object oriented language in the classic sense. However, it does support composite types with structs, which contain multiple fields and optional types. Like any good scientific language, It has very well thought out support for arrays, with many built in functions to initialize and compute values over multidimensional arrays. It supports asynchronous computing with its task model, which can pause and synchronize the execution of code like coroutines in other languages. And finally, when it comes to big data, it can even distribute process into multiple memory spaces or machines and run natively on a GPU. This has been Julia in 100 seconds. If you wanna see more short videos hit the like button and subscribe. Thanks for watching and I will see you in the next one.
Julia,
julia
a
a
dynamic
dynamic
general
general
purpose
purpose
programming
programming
language
language
capable
capable
of
of
high
high
performance
performance
scientific
scientific
computing
computing
with
with
high
high
level
level
code.
code
It
it
was
was
created
created
in
in
2012
2012
by
by
a
a
gang
gang
of
of
scientists,
scientists
who
who
set
set
out
out
to
to
build
build
a
a
language
language
with
with
the
the
speed
speed
of
of
c,
c
the
the
dynamism
dynamism
of
of
Ruby,
ruby
the
the
practicality
practicality
of
of
Python
python
that
that
can
can
do
do
statistics
statistics
like
like
and
and
linear
linear
algebra
algebra
like
like
MATLAB
matlab
out
out
of
of
the
the
box.
box
It's
it's
a
a
general
general
purpose
purpose
language,
language
but
but
is
is
most
most
well
well
known
known
for
for
its
its
use
use
in
in
numerical
numerical
analysis,
analysis
data
data
visualization,
visualization
and
and
machine
machine
learning.
learning
It's
it's
fast
fast
because
because
unlike
unlike
most
most
high
high
level
level
languages,
languages
it
it
uses
uses
a
a
just
just
in
in
time
time
compiler
compiler
to
to
convert
convert
your
your
source
source
code
code
into
into
machine
machine
code
code
before
before
running
running
it.
it
And
and
unlike
unlike
most
most
dynamic
dynamic
languages,
languages
computers.
computers
It
it
has
has
a
a
flexible
flexible
parametric
parametric
type
type
system.
system
That
that
means
means
static
static
typing
typing
is
is
optional
optional
by
by
default
default
and
and
types
types
can
can
take
take
parameters
parameters
allowing
allowing
one
one
type
type
to
to
represent
represent
many
many
different
different
possibilities.
possibilities
This
this
opens
opens
the
the
door
door
to
to
the
the
multiple
multiple
dispatch
dispatch
pattern
pattern
where
where
one
one
function
function
can
can
have
have
multiple
multiple
methods
methods
or
or
implementations
implementations
based
based
on
on
its
its
input
input
parameters,
parameters
and
and
the
the
language
language
will
will
determine
determine
which
which
method
method
to
to
dispatch
dispatch
at
at
runtime.
runtime
In
in
fact,
fact
even
even
operators
operators
like
like
plus
plus
are
are
functions
functions
that
that
use
use
multiple
multiple
dispatch
dispatch
to
to
handle
handle
a
a
variety
variety
of
of
different
different
type
type
combinations.
combinations
To
to
get
get
started,
started
install
install
Julia,
julia
then
then
create
create
a
a
file
file
ending
ending
in
in
dot
dot
jl.
jl
Declare
declare
a
a
variable
variable
by
by
providing
providing
a
a
name,
name
then
then
assign
assign
a
a
value
value
to
to
it.
it
Name
name
support
support
UTF8
utf8
like
like
emojis
emojis
or
or
mathematical
mathematical
symbols.
symbols
It
it
uses
uses
symbols
symbols
to
to
represent
represent
built
built
in
in
constants
constants
like
like
pi,
pi
allowing
allowing
you
you
to
to
write
write
equations
equations
more
more
elegantly
elegantly
in
in
your
your
code.
code
Like
like
Perl,
perl
it's
it's
very
very
good
good
at
at
string
string
parsing
parsing
and
and
supports
supports
multiple
multiple
expressions
expressions
on
on
a
a
single
single
line
line
resulting
resulting
in
in
terse
terse
yet
yet
powerful
powerful
code.
code
Define
define
a
a
function
function
with
with
the
the
function
function
keyword
keyword
and
and
close
close
with
with
the
the
end
end
keyword
keyword
or
or
shorten
shorten
it
it
to
to
a
a
single
single
line
line
with
with
the
the
equal
equal
sign
sign
or
or
because
because
functions
functions
are
are
first
first
class
class
objects,
objects
they
they
can
can
be
be
assigned
assigned
to
to
a
a
variable
variable
or
or
passed
passed
to
to
another
another
function
function
anonymously.
anonymously
What's
what's
interesting
interesting
no.
no
Is
is
that
that
by
by
default,
default
a
a
function
function
is
is
untyped,
untyped
which
which
means
means
it
it
implements
implements
one
one
method
method
to
to
handle
handle
all
all
inputs.
inputs
If
if
the
the
function
function
is
is
redefined,
redefined
but
but
this
this
time
time
with
with
a
a
type
type
for
for
the
the
arguments,
arguments
a
a
another
another
method
method
is
is
added
added
to
to
it.
it
When
when
this
this
function
function
is
is
called
called
at
at
runtime,
runtime
Julia
julia
will
will
look
look
at
at
the
the
type
type
of
of
the
the
arguments
arguments
and
and
dispatch
dispatch
the
the
corresponding
corresponding
method.
method
In
in
we
we
can
can
pass
pass
a
a
type
type
as
as
a
a
parameter,
parameter
then
then
use
use
keywords
keywords
like
like
where
where
to
to
perform
perform
logic
logic
on
on
the
the
type
type
itself.
itself
In
in
this
this
case,
case
it
it
will
will
assert
assert
that
that
both
both
types
types
are
are
the
the
same.
same
Now,
now
Julia
julia
is
is
not
not
an
an
object
object
oriented
oriented
language
language
in
in
the
the
classic
classic
sense.
sense
However,
however
it
it
does
does
support
support
composite
composite
types
types
with
with
structs,
structs
which
which
contain
contain
multiple
multiple
fields
fields
and
and
optional
optional
types.
types
Like
like
any
any
good
good
scientific
scientific
language,
language
It
it
has
has
very
very
well
well
thought
thought
out
out
support
support
for
for
arrays,
arrays
with
with
many
many
built
built
in
in
functions
functions
to
to
initialize
initialize
and
and
compute
compute
values
values
over
over
multidimensional
multidimensional
arrays.
arrays
It
it
supports
supports
asynchronous
asynchronous
computing
computing
with
with
its
its
task
task
model,
model
which
which
can
can
pause
pause
and
and
synchronize
synchronize
the
the
execution
execution
of
of
code
code
like
like
coroutines
coroutines
in
in
other
other
languages.
languages
And
and
finally,
finally
when
when
it
it
comes
comes
to
to
big
big
data,
data
it
it
can
can
even
even
distribute
distribute
process
process
into
into
multiple
multiple
memory
memory
spaces
spaces
or
or
machines
machines
and
and
run
run
natively
natively
on
on
a
a
GPU.
gpu
This
this
has
has
been
been
Julia
julia
in
in
100
100
seconds.
seconds
If
if
you
you
wanna
wanna
see
see
more
more
short
short
videos
videos
hit
hit
the
the
like
like
button
button
and
and
subscribe.
subscribe
Thanks
thanks
for
for
watching
watching
and
and
I
i
will
will
see
see
you
you
in
in
the
the
next
next
one.
one
success
In this video, the host explains the capabilities of Julia, a dynamic programming language used for scientific computing. The language uses a flexible parametric system and supports multiple dispatch patterns, allowing for multiple methods to be used depending on input parameters. Julia also supports multiple data types and supports IO computing, including a task model and asynchronous computing. The language is not an object-oriented language and can even distribute data into multiple memory spaces or machines.
Julia in 100 Seconds
Julia, a dynamic general purpose programming language capable of high performance scientific computing with high level code. It was created in 2012 by a gang of scientists, who set out to build a language with the speed of c, the dynamism of Ruby, the practicality of Python that can do statistics like and linear algebra like MATLAB out of the box. It's a general purpose language, but is most well known for its use in numerical analysis, data visualization, and machine learning. It's fast because unlike most high level languages, it uses a just in time compiler to convert your source code into machine code before running it. And unlike most dynamic languages, computers. It has a flexible parametric type system. That means static typing is optional by default and types can take parameters allowing one type to represent many different possibilities. This opens the door to the multiple dispatch pattern where one function can have multiple methods or implementations based on its input parameters, and the language will determine which method to dispatch at runtime. In fact, even operators like plus are functions that use multiple dispatch to handle a variety of different type combinations. To get started, install Julia, then create a file ending in dot jl. Declare a variable by providing a name, then assign a value to it. Name support UTF8 like emojis or mathematical symbols. It uses symbols to represent built in constants like pi, allowing you to write equations more elegantly in your code. Like Perl, it's very good at string parsing and supports multiple expressions on a single line resulting in terse yet powerful code. Define a function with the function keyword and close with the end keyword or shorten it to a single line with the equal sign or because functions are first class objects, they can be assigned to a variable or passed to another function anonymously. What's interesting no. Is that by default, a function is untyped, which means it implements one method to handle all inputs. If the function is redefined, but this time with a type for the arguments, a another method is added to it. When this function is called at runtime, Julia will look at the type of the arguments and dispatch the corresponding method. In we can pass a type as a parameter, then use keywords like where to perform logic on the type itself. In this case, it will assert that both types are the same. Now, Julia is not an object oriented language in the classic sense. However, it does support composite types with structs, which contain multiple fields and optional types. Like any good scientific language, It has very well thought out support for arrays, with many built in functions to initialize and compute values over multidimensional arrays. It supports asynchronous computing with its task model, which can pause and synchronize the execution of code like coroutines in other languages. And finally, when it comes to big data, it can even distribute process into multiple memory spaces or machines and run natively on a GPU. This has been Julia in 100 seconds. If you wanna see more short videos hit the like button and subscribe. Thanks for watching and I will see you in the next one.
In this video, the host explains the capabilities of Julia, a dynamic programming language used for scientific computing. The language uses a flexible parametric system and supports multiple dispatch patterns, allowing for multiple methods to be used depending on input parameters. Julia also supports multiple data types and supports IO computing, including a task model and asynchronous computing. The language is not an object-oriented language and can even distribute data into multiple memory spaces or machines.

        [INST]
        You are youtuber called Fireship you make engaging high-intensity and entertaining coding tutorials and tech news. 
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        Given the title of the video : Julia in 100 Seconds 
        and a small summary : In this video, the host explains the capabilities of Julia, a dynamic programming language used for scientific computing. The language uses a flexible parametric system and supports multiple dispatch patterns, allowing for multiple methods to be used depending on input parameters. Julia also supports multiple data types and supports IO computing, including a task model and asynchronous computing. The language is not an object-oriented language and can even distribute data into multiple memory spaces or machines.
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        Generate the video : Julia, a dynamic general purpose programming language capable of high performance scientific computing with high level code. It was created in 2012 by a gang of scientists, who set out to build a language with the speed of c, the dynamism of Ruby, the practicality of Python that can do statistics like and linear algebra like MATLAB out of the box. It's a general purpose language, but is most well known for its use in numerical analysis, data visualization, and machine learning. It's fast because unlike most high level languages, it uses a just in time compiler to convert your source code into machine code before running it. And unlike most dynamic languages, computers. It has a flexible parametric type system. That means static typing is optional by default and types can take parameters allowing one type to represent many different possibilities. This opens the door to the multiple dispatch pattern where one function can have multiple methods or implementations based on its input parameters, and the language will determine which method to dispatch at runtime. In fact, even operators like plus are functions that use multiple dispatch to handle a variety of different type combinations. To get started, install Julia, then create a file ending in dot jl. Declare a variable by providing a name, then assign a value to it. Name support UTF8 like emojis or mathematical symbols. It uses symbols to represent built in constants like pi, allowing you to write equations more elegantly in your code. Like Perl, it's very good at string parsing and supports multiple expressions on a single line resulting in terse yet powerful code. Define a function with the function keyword and close with the end keyword or shorten it to a single line with the equal sign or because functions are first class objects, they can be assigned to a variable or passed to another function anonymously. What's interesting no. Is that by default, a function is untyped, which means it implements one method to handle all inputs. If the function is redefined, but this time with a type for the arguments, a another method is added to it. When this function is called at runtime, Julia will look at the type of the arguments and dispatch the corresponding method. In we can pass a type as a parameter, then use keywords like where to perform logic on the type itself. In this case, it will assert that both types are the same. Now, Julia is not an object oriented language in the classic sense. However, it does support composite types with structs, which contain multiple fields and optional types. Like any good scientific language, It has very well thought out support for arrays, with many built in functions to initialize and compute values over multidimensional arrays. It supports asynchronous computing with its task model, which can pause and synchronize the execution of code like coroutines in other languages. And finally, when it comes to big data, it can even distribute process into multiple memory spaces or machines and run natively on a GPU. This has been Julia in 100 seconds. If you wanna see more short videos hit the like button and subscribe. Thanks for watching and I will see you in the next one.
        