Liquidsoap’s scripting language
The following is adapted from the Liquidsoap book. The reader is avised to check out the whole chapter in the book for more details about the liquidsoap language
General features
Liquidsoap is a novel language which was designed from scratch to handle media stream. It takes some inspiration from functional languages such as OCaml but features a syntax that is more intuitive to the general purpose programmer, similar to Ruby or Javascript.
Typing
One of the main features of the language is that it is
typed. This means that every expression belongs to some type
which indicates what it is. For instance, "hello"
is a
string whereas 23
is an integer, and,
when presenting a construction of the language, we will always indicate
the associated type. Liquidsoap implements a typechecking
algorithm which ensures that whenever a string is expected a string will
actually be given, and similarly for other types. This is done without
running the program, so that it does not depend on some dynamic tests,
but is rather enforced by theoretical considerations. Another
distinguishing feature of this algorithm is that it also performs
type inference: you never actually have to write a type, those
are guessed automatically by Liquidsoap. This makes the language very
safe, while remaining very easy to use.
Functional programming
The language is functional, which means that you can very easily define functions, and that functions can be passed as arguments of other functions. This might look like a crazy thing at first, but it is actually quite common in some language communities (such as OCaml). It also might look quite useless: why should we need such functions when describing webradios? You will soon discover that it happens to be quite convenient in many places: for handlers (we can specify the function which describes what to do when some event occurs such as when a DJ connects to the radio), for transitions (we pass a function which describes the shape we want for the transition) and so on.
Streams
The unique feature of Liquidsoap is that it allows the manipulation of sources which are functions which will generate streams. These streams typically consist of stereo audio data, but we do restrict to this: they can contain audio with arbitrary number of channels, they can also contain an arbitrary number of video channels, and also MIDI channels (there is limited support for sound synthesis).
Standard library
Although the core of Liquidsoap is written in OCaml, many of the
functions of Liquidsoap are written in the Liquidsoap language itself.
Those are defined in the stdlib.liq
script, which is loaded
by default and includes all the libraries. You should not be frightened
to have a look at the standard library, it is often useful to better
grasp the language, learn design patterns and tricks, and add
functionalities. Its location on your system is indicated in the
variable configure.libdir
and can be obtained by typing
Basic values
Integers and floats
The integers, such as 3
or 42
, are
of type int
. Depending on the current architecture of the
computer on which we are executing the script (32 or 64 bits, the latter
being the most common nowadays) they are stored on 31 or 63 bits. The
minimal (resp. maximal) representable integer can be obtained as the
constant min_int
(resp. max_int
); typically,
on a 64 bits architecture, they range from -4611686018427387904 to
4611686018427387903.
The floating point numbers, such as 2.45
, are
of type float
, and are in double precision, meaning that
they are always stored on 64 bits. We always write a decimal point in
them, so that 3
and 3.
are not the same thing:
the former is an integer and the latter is a float. This is a source of
errors for beginners, but is necessary for typing to work well.
Strings
Strings are written between double or single quotes,
e.g. "hello!"
or 'hello!'
, and are of type
string
.
In order to write the character “"
” in a string, one
cannot simply type “"
” since this is already used to
indicate the boundaries of a string: this character should be
escaped, which means that the character “\
” should
be typed first so that
print("My name is \"Sam\"!")
will actually display “My name is "Sam"!
”. Other
commonly used escaped characters are “\\
” for backslash and
“\n
” for new line. Alternatively, one can use the single
quote notation, so that previous example can also be written as
print('My name is "Sam"!')
This is most often used when testing JSON data which can contain many
quotes or for command line arguments when calling external scripts. The
character “\
” can also be used at the end of the string to
break long strings in scripts without actually inserting newlines in the
strings. For instance, the script
print("His name is \
Romain.")
will actually print
His name is Romain.
Note that there is no line change between “is” and “Romain”, and the indentation before “Romain” is not shown either.
The concatenation of two strings is achieved by the infix operator
“^
”, as in
user = "dj"
print("Current user is " ^ user)
Instead of using concatenation, it is often rather convenient to use
string interpolation: in a string, #{e}
is
replaced by the string representation of the result of the evaluation of
the expression e
:
user = "admin"
print("The user #{user} has just logged.")
will print The user admin has just logged.
or
print("The number #{random.float()} is random.")
will print The number 0.663455738438 is random.
(at
least it did last time I tried).
Escaping strings
Liquidsoap strings follow the most common lexical conventions from
C
and javascript
and JSON
, in
particular, string.unescape
recognizes the same escape
sequences as C
(except for UTF-16
characters)
and javascript.
The following sequences are recognized:
Escape sequence | Hex value in ASCII | Character represented |
---|---|---|
\a |
\x07 |
Alert (Beep, Bell) |
\b |
\x08 |
Backspace |
\e |
\x1B |
Escape character |
\f |
\x0C |
Formfeed, Page Break |
\n |
\x0A |
Newline (Line Feed) |
\r |
\x0D |
Carriage Return |
\t |
\x09 |
Horizontal Tab |
\v |
\x0B |
Vertical Tab |
\\ |
\x5C |
Backslash |
\/ |
\x2f |
Forward slash |
\' |
\x27 |
Apostrophe or single quotation mark |
\" |
\x22 |
Double quotation mark |
\? |
\x3F |
Question mark (used to avoid Digraphs and trigraphs) |
\nnn |
any | The byte whose numerical value is given by nnn interpreted as an octal number |
\xhh |
any | The byte whose numerical value is given by hh interpreted as a hexadecimal number |
\uhhhh |
none | UTF8-8 code point given by hhhh interpreted as an hexadecimal number |
This convention has been decided to follow the most common practices.
In particular, \nnn
is an octal escape sequence in
most languages including C, Ruby, Javascript, Python and more. This
differs from OCaml where \nnn
is considered a
digital escape sequence.
These lexical conventions are used in the default
string.escape
and string.unescape
.
Here’s an example of an escaped string:
# "\" \t \045 \x2f \u4f32";;
- : string = "\" \t % / 2"
The function string.quote
returns JSON-compatible
strings.
Regular expressions
This feature was introduced in liquidsoap version 2.1.0
Regular expressions can be created using the regexp
operator or the syntactic sugar: r/.../<flags>
. For
instance:
# Using the regexp operator:
r = regexp(flags=["g","i"], "foo([\\w])+bar")
# Using the r/../ syntactic sugar:
r = r/foo([\w])bar/gi
Using the r/../
syntactic sugar makes it possible to
write regular expressions without having to escape \
characters, which makes them more easily readable.
Regular expression flags are:
i
: perform case-insensitive matchg
: substitute all matched sub-strings, not just the first ones
: match all characters, including\n
when using the.
patternm
:^
and$
match before/after newlines, not just at the beginning/end of a string
Regular expressions have the following methods:
replace(fn, s)
: replace matched substrings ofs
using functionfn
. If theg
flag is not passed, only the first match is replaced otherwise, all matches are replacedsplit(s)
: split the given string on all substrings matching the regular expression.test(s)
: returnstrue
if the given string matches the regular expression.exec(s)
: execute the regular expression and return a of list matches of the form:[(<match index>, <match>), ..]
. Named matches are also supported and returned as propertygroups
of type[string * string]
:
g.exec("foogni")
r/(foo)(?<gno>gni)?/
- : [int * string].{groups : [string * string]} =
[2, "gni"),
(1, "foo"),
(0, "foogni")
(
].{groups = [
"gno", "gni")
(
] }
Booleans
The booleans are either true
or
false
and are of type bool
. They can be
combined using the usual boolean operations
and
: conjunction,or
: disjunction,not
: negation.
Booleans typically originate from comparison operators, which take two values and return booleans:
==
: compares for equality,!=
: compares for inequality,<=
: compares for inequality,
and so on (<
, >=
, >
).
For instance, the following is a boolean expression:
3) and not (s == "hello") (n <
Conditional branchings execute code depending on whether a condition is true or not. For instance, the code
if (1 <= x and x <= 12) or (not 10h-15h) then
print("The condition is satisfied")
else
print("The condition ain't satisfied")
end
will print that the condition is satisfied when either x
is between 1 and 12 or the current time is not between 10h and 15h. A
conditional branching might return a value, which is the last computed
value in the chosen branch. For instance,
y = if x < 3 then "A" else "B" end
will assign "A"
or "B"
to y
depending on whether x
is below 3 or not. The two branches
of a conditional should always have the same return type:
x = if 1 == 2 then "A" else 5 end
will result in
At line 1, char 19-21:
Error 5: this value has type string
but it should be a subtype of int
meaning that "A"
is a string but is expected to be an
integer because the second branch returns an integer, and the two should
be of same nature. The else
branch is optional, in which
case the then
branch should be of type
unit
:
if x == "admin" then print("Welcome admin") end
In the case where you want to perform a conditional branching in the
else
branch, the elsif
keyword should be used, as in the following example, which assigns 0, 1,
2 or 3 to s
depending on whether x
is
"a"
, "b"
, "c"
or something
else:
s = if x == "a" then 0
elsif x == "b" then 1
elsif x == "c" then 2
else 3 end
This is equivalent (but shorter to write) to the following sequence of imbricated conditional branchings:
s = if x == "a" then 0
else
if x == "b" then 1
else
if x == "c" then 2
else 3 end
end
end
Finally, we should mention that the notation c?a:b
is
also available as a shorthand for if c then a else b end
,
so that the expression
y = if x < 3 then "A" else "B" end
can be shortened to
y = (x<3)?"A":"B"
(and people will think that you are a cool guy).
Time predicates
Time predicates are special boolean values such as
{0h-7h}
. These values are true
or
false
depending on the current time. Some examples of time
predicates are
{11h15-13h}
between 11h15 and 13h {12h}
between 12h00 and 12h59 {12h00}
at 12h00 {00m}
on the first minute of every hour {00m-09m}
on the first 10
minutes of every hour {2w}
on Tuesday {6w-7w}
on weekends
Above, w
stands for weekday: 1 is Monday, 2 is Tuesday,
and so on. Sunday is both 0 and 7.
Time predicate can also be parsed at runtime, for instance if you want to create them dynamically. The syntax is:
# f = time.predicate("00m-30m");;
bool = <fun> f : () ->
Be aware that, if parsing fails, it will raise
error.string
:
# f = time.predicate("foo")
14: Uncaught runtime error:
Error "Failed to parse foo as time predicate" type: string, message:
Unit
Some functions, such as print
, do not return a
meaningful value: we are interested in what they are doing
(e.g. printing on the standard output) and not in their result. However,
since typing requires that everything returns something of some type,
there is a particular type for the return of such functions:
unit
. Just as there are only two values in the booleans
(true
and false
), there is only one value in
the unit type, which is written ()
. This value can be
thought of as the result of the expression saying “I’m done”.
Lists
Some more elaborate values can be constructed by combining the previous ones. A first kind is lists which are finite sequences of values, being all of the same type. They are constructed by square bracketing the sequence whose elements are separated by commas. For instance, the list
1, 4, 5] [
is a list of three integers (1, 4 and 5), and its type is
[int]
, and the type of ["A", "B"]
would
obviously be [string]
. Note that a list can be empty:
[]
.
You can extract list elements through splats such as
l = [1, 5, 7, 8, 9]
let [x, _, z, ...t] = l
In this example, the value of x
is 1
, the
value of z
is 7
and the value of
t
is [8, 9]
.
You can also combine lists in a similar way
x = [1, ...[2, 3, 4], 5, ...[6, 7]]
In this example, the value of x
is
[1, 2, 3, 4, 5, 6 ,7]
Tuples
Another construction present in Liquidsoap is tuples of values, which are finite sequences of values which, contrarily to lists, might have different types. For instance,
(3, 4.2, "hello")
is a triple (a tuple with three elements) of type
int * float * string
which indicate that the first element is an integer, the second a float and the third a string.
Similarly to lists, there is a special syntax in order to access
tuple elements. For instance, if t
is the above tuple
(3, 4.2, "hello")
, we can write
let (n, x, s) = t
which will assign the first element to the variable n
,
the second element to the variable x
and the third element
to the variable s
.
Programming primitives
Variables
We have already seen many examples of uses of variables: we use
x = e
in order to assign the result of evaluating an expression
e
to a variable x
, which can later on be
referred to as x
. Variables can be masked: we can define
two variables with the same name, and at any point in the program the
last defined value for the variable is used:
n = 3
print(n)
n = n + 2
print(n)
will print 3
and 5
. Contrarily to most
languages, the value for a variable cannot be changed (unless we
explicitly require this by using references, see below), so the above
program does not modify the value of n
, it is simply that a
new n
is defined.
There is an alternative syntax for declaring variables which is
def x =
eend
It has the advantage that the expression e
can spread
over multiple lines and thus consist of multiple expressions, in which
case the value of the last one will be assigned to x
. This
is particularly useful to use local variables when defining a value.
References
As indicated above, by default, the value of a variable cannot be
changed. However, one can use a reference in order to be able
to do this. Those can be seen as memory cells, containing values of a
given fixed type, which can be modified during the execution of the
program. They are created with the ref
keyword, with the
initial value of the cell as argument. For instance,
r = ref(5)
declares that r
is a reference which contains
5
as initial value. Since 5
is an integer (of
type int
), the type of the reference r
will
be
ref(int)
meaning that its a memory cell containing integers. On such a reference, two operations are available.
One can obtain the value of the reference by applying the reference to
()
, so thatr()
denotes the value contained in the referencer
, for instancex = r() + 4
declares the variable
x
as being 9 (which is 5+4).One can change the value of the reference by using the
:=
keyword, e.g.2 r :=
will assign the value 2 to
r
. Internally, this is done by calling theset
method of the reference, so that the above is equivalent to writingr.set(2)
which used to be the syntax for some reference manipulations.
Loops
The usual looping constructions are available in Liquidsoap. The
for
loop repeatedly executes a portion of code with an
integer variable varying between two bounds, being increased by one each
time. For instance, the following code will print the integers
1
, 2
, 3
, 4
and
5
, which are the values successively taken by the variable
i
:
for i = 1 to 5 do
print(i)
end
In practice, such loops could be used to add a bunch of numbered
files (e.g. music1.mp3
, music2.mp3
,
music3.mp3
, etc.) in a request queue for instance.
The while
loop repeatedly executes a portion of code, as
long a condition is satisfied. For instance, the following code doubles
the contents of the reference n
as long as its value is
below 10
:
n = ref(1)
while n() < 10 do
n() * 2
n := end
print(n())
The variable n
will thus successively take the values
1
, 2
, 4
, 8
and
16
, at which point the looping condition
n() < 10
is not satisfied anymore and the loop is
exited. The printed value is thus 16
.
Functions
Liquidsoap is built around the notion of function: most operations
are performed by those. For some reason, we sometimes call
operators the functions acting on sources. Liquidsoap includes
a standard library which consists of functions defined in the Liquidsoap
language, including fairly complex operators such as
playlist
which plays a playlist or crossfade
which takes care of fading between songs.
Basics
A function is a construction which takes a bunch of arguments and
produces a result. For instance, we can define a function f
taking two float arguments, prints the first and returns the result of
adding twice the first to the second:
def f(x, y)
print(x)
2*x+y
end
This function can also be written on one line if we use semicolons
(;
) to separate the instructions instead of changing
line:
def f(x, y) = print(x); 2*x+y end
The type of this function is
(int, int) -> int
The arrow ->
means that it is a function, on the left
are the types of the arguments (here, two arguments of type
int
) and on the right is the type of the returned value of
the function (here, int
). In order to use this function, we
have to apply it to arguments, as in
f(3, 4)
This will trigger the evaluation of the function, where the argument
x
(resp. y
) is replaced by 3
(resp. 4
), i.e., it will print 3
and return
the evaluation of 2*3+4
, which is 10
.
Anonymous functions
For concision in scripts, it is possible define a function without giving it a name, using the syntax
fun (x) -> ...
This is called an anonymous function, and it is typically used in order to specify short handlers in arguments.
Anonymous function with no arguments
You will see that it is quite common to use anonymous functions with no arguments. For this reason, we have introduced a special convenient syntax for those and allow writing
{...}
instead of
fun () -> ...
Labeled arguments
A function can have an arbitrary number of arguments, and when there are many of them it becomes difficult to keep track of their order and their order matter! For instance, the following function computes the sample rate given a number of samples in a given period of time:
def samplerate(samples, duration) = samples / duration end
which is of type
(float, float) -> float
For instance, if you have 110250 samples over 2.5 seconds the
samplerate will be samplerate(110250., 2.5)
which is 44100.
However, if you mix the order of the arguments and type
samplerate(2.5, 110250.)
, you will get quite a different
result and this will not be detected by the typing system because both
arguments have the same type. Fortunately, we can give labels
to arguments in order to prevent this, which forces explicitly naming
the arguments. This is indicated by prefixing the arguments with a tilde
“~
”:
def samplerate(~samples, ~duration) = samples / duration end
The labels will be indicated as follows in the type:
(samples : float, duration : float) -> float
Namely, in the above type, we read that the argument labeled
samples
is a float and similarly for the one labeled
duration
. For those arguments, we have to give the name of
the argument when calling the function:
samplerate(samples=110250., duration=2.5)
The nice byproduct is that the order of the arguments does not matter anymore, the following will give the same result:
samplerate(duration=2.5, samples=110250.)
Of course, a function can have both labeled and non-labeled arguments.
Optional arguments
Another useful feature is that we can give default values to
arguments, which thus become optional: if, when calling the
function, a value is not specified for such arguments, the default value
will be used. For instance, if for some reason we tend to generally
measure samples over a period of 2.5 seconds, we can make this become
the value for the duration
parameter:
def samplerate(~samples, ~duration=2.5) =
samples / durationend
In this way, if we do not specify a value for the duration, its value will implicitly be assumed to be 2.5, so that the expression:
samplerate(samples=110250.)
will still evaluate to 44100. Of course, if we want to use another value for the duration, we can still specify it, in which case the default value will be ignored:
samplerate(samples=132300., duration=3.)
The presence of an optional argument is indicated in the type by
prefixing the corresponding label with “?
”, so that the
type of the above function is
(samples : float, ?duration : float) -> float
Getters
We often want to be able to dynamically modify some parameters in a
script. For instance, consider the operator amplify
, which
takes a float and an audio source and returns the audio amplified by the
given volume factor: we can expect its type to be
(float, source('a)) -> source('a)
so that we can use it to have a radio consisting of a microphone input amplified by a factor 1.2 by
mic = input.alsa()
radio = amplify(1.2, mic)
In the above example, the volume 1.2 was supposedly chosen because
the sound delivered by the microphone is not loud enough, but this
loudness can vary from time to time, depending on the speaker for
instance, and we would like to be able to dynamically update it. The
problem with the current operator is that the volume is of type
float
and a float cannot change over time: it has a fixed
value.
In order for the volume to have the possibility to vary over time,
instead of having a float
argument for
amplify
, we have decided to have instead an argument of
type
() -> float
This is a function which takes no argument and returns a float (remember that a function can take an arbitrary number of arguments, which includes zero arguments). It is very close to a float excepting that each time it is called the returned value can change: we now have the possibility of having something like a float which varies over time. We like to call such a function a float getter, since it can be seen as some kind of object on which the only operation we can perform is get the value. For instance, we can define a float getter by
n = ref(0.)
def f ()
n() + 1.
n := n()
end
Each time we call f
, by writing f()
in our
script, the resulting float will be increased by one compared to the
previous one: if we try it in an interactive session, we obtain
# f();;
- : float = 1.0
# f();;
- : float = 2.0
# f();;
- : float = 3.0
Since defining such arguments often involves expressions of the form
fun () -> e
which is somewhat heavy, we have introduced the alternative syntax
{e}
for it.
Finally, in order to simplify things a bit, you will see that the type of amplify is actually
({float}, source('a)) -> source('a)
where the type {float}
means that both
float
and () -> float
are accepted, so that
you can still write constant floats where float getters are expected.
What we actually call a getter is generally an element of such
a type, which is either a constant or a function with no argument.
In order to work with such types, the standard library often uses the following functions:
getter
, of type({'a}) -> {'a}
, creates a getter,getter.get
, of type({'a}) -> 'a
, retrieves the current value of a getter,getter.function
, of type({'a}) -> () -> 'a
, creates a function from a getter.
Recursive functions
Liquidsoap supports functions which are recursive, i.e., that can call themselves. For instance, in mathematics, the factorial function on natural numbers is defined as fact(n)=1×2×3×…×n, but it can also be defined recursively as the function such that fact(0)=1 and fact(n)=n×fact(n-1) when n>0: you can easily check by hand that the two functions agree on small values of n (and prove that they agree on all values of n). This last formulation has the advantage of immediately translating to the following implementation of factorial:
def rec fact(n) =
if n == 0 then 1
else n * fact(n-1) end
end
for which you can check that fact(5)
gives 120, the
expected result. As another example, the list.length
function, which computes the length of a list, can be programmed in the
following way in Liquidsoap:
def rec length(l)
if l == [] then 0
else 1 + length(list.tl(l)) end
end
We do not detail much further this trait since it is unlikely to be used for radios, but you can see a few occurrences of it in the standard library.
Records and modules
Records
Suppose that we want to store and manipulate structured data. For
instance, a list of songs together with their duration and tempo. One
way to store each song is as a tuple of type
string * float * float
, but there is a risk of confusion
between the duration and the length which are both floats, and the
situation would of course be worse if there were more fields. In order
to overcome this, one can use a record which is basically the
same as a tuple, excepting that fields are named. In our case, we can
store a song as
song = { filename = "song.mp3", duration = 257., bpm = 132. }
which is a record with three fields respectively named
filename
, duration
and bpm
. The
type of such a record is
{filename : string, duration : float, bpm : float}
which indicates the fields and their respective type. In order to
access a field of a record, we can use the syntax
record.field
. For instance, we can print the duration
with
print("The duration of the song is #{song.duration} seconds")
Records can be re-used using spreads:
song = { filename = "song.mp3", duration = 257., bpm = 132. }
# This is a fresh value with all the fields from `song` and
# a new `id` field:
song_with_id = { id = 1234, ...song }
Alternatively, you can also extend a record using the explicit
v.{...}
syntax:
song = { filename = "song.mp3", duration = 257., bpm = 132. }
# This is a fresh value with all the fields from `song` and
# a new `id` field:
song_with_id = song.{id = 1234}
Modules
Records are heavily used in Liquidsoap in order to structure the
functions of the standard library. We tend to call module a
record with only functions, but this is really the same as a record. For
instance, all the functions related to lists are in the
list
module and functions such as list.hd
are
fields of this record. For this reason, the def
construction allows adding fields in record. For instance, the
definition
def list.last(l)
list.nth(l, list.length(l)-1)
end
adds, in the module list
, a new field named
last
, which is a function which computes the last element
of a list. Another shorter syntax to perform definitions consists in
using the let
keyword which allows assigning a value to a
field, so that the previous example can be rewritten as
let list.last = fun(l) -> list.nth(l, list.length(l)-1)
If you often use the functions of a specific module, the
open
keyword allows using its fields without having to
prefix them by the module name. For instance, in the following
example
l = [1,2,3]
open list
x = nth(l, length(l)-1)
the open list
directive allows directly using the
functions in this module: we can simply write nth
and
length
instead of list.nth
and
list.length
.
Values with fields
A unique feature of the Liquidsoap language is that it allows adding fields to any value. We also call them methods by analogy with object-oriented programming. For instance, we can write
song = "test.mp3".{duration = 123., bpm = 120.}
which defines a string ("test.mp3"
) with two methods
(duration
and bpm
). This value has type
string.{duration : float, bpm : float}
and behaves like a string, e.g. we can concatenate it with other strings:
print("the song is " ^ song)
but we can also invoke its methods like a record or a module:
print("the duration is #{song.duration}")
The construction def replaces
allows changing the main
value while keeping the methods unchanged, so that
def replaces song = "newfile.mp3" end
print(song)
will print
"newfile.mp3".{duration = 123., bpm = 120.}
(note that the string is modified but not the fields
duration
and bpm
).
Optional fields
During the execution of your script, it can be useful to allow functions to receive records that may or may not have a specific field. This can be used, for instance, to model optional arguments.
This can be achieved in two ways:
- Using the
x.foo ?? default
syntax
Here’s an example:
# This functions adds 1 to x unless options has a
# add field in which case it adds this value
def f(x, options) =
1)
x + (options.add ?? end
The type of this function is:
int = <fun> f : (int, 'a.{add? : int}) ->
which denotes that the options
argument can be any value
that may or may not have a add
field. However, if this
field is present, it must be of type int
.
- Using the
x?.foo
syntax
Given a variable x
, x?.foo
returns the
field value foo
, if present, or null
otherwise.
The ?.
syntax can be chained and works with functions,
which make it a very convenient way to drill deep inside nested
records:
fn(123, "aabb")?.field x?.
Patterns
As explained earlier, you can use several constructions to extract
data from structured values such as let [x, y] = l
and etc.
These constructions are called patterns.
Patterns allows to quickly access values nested deeply inside structured data in a way that remains pretty intuitive when reading the code.
Patterns are constructed using variable placeholders, which
are either a variable name such as: x
, foo
,
etc. or the special symbol _
for any ignored value.
Tuple patterns
Tuple patterns are pretty straight forward and consist of any sequence of variable captures:
let (x, y, _, z) = (123, "aabbcc", true, 3.14)
# x = 1, y = "aabbcc", z = 3.14
List patterns
List patterns are composed of variable placeholders, etc. and spreads
of the form: ...<variable placeholder>
such as:
...z
. The spread ..._
can be simply written
...
. See below for an example.
You can use any combination of:
- Forward variable names: these capture the first elements of the list.
- One spread: this captures any remaining element as a list.
- Backward variable names: these capture the last elements of a the list.
Here are some examples:
# Forward capture:
let [x, y, z] = [1, 2, 3]
# x = 1, y = 2, z = 3
# Forward capture with spread:
let [x, y, ...z] = [1, 2, 3, 4]
# x = 1, y = 2, z = [3, 4]
# Forward capture with ignored values:
let [_, x, ...z] = [1, 2, 3, 4]
# x = 2, z = [3, 4]
# Full capture:
let [x, y, ...z, t, u, v] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
# x = 1, y = 2, z = [3, 4, 5, 6, 7], t = 7, u = 8, v = 9
# Backward capture only.
let [..., t, u, v] = [1, 2, 3, 4, 5]
# t = 3, u = 4, v = 5
Record and module patterns
Record and module patterns consist of either variable names (not variable capture!), which capture method values or variable names with an associated pattern.
Record patterns are of the form:
{<captured methods>}
while module patterns are of the
form:
<variable capture>.{<captured methods>}
Here are some examples:
# Record capture
let {foo, bar} = {foo = 123, bar = "baz", gni = true}
# foo = 123, bar = "baz"
# Record capture with spread
let {foo, bar, ...x} = {foo = 123, bar = "baz", gni = true}
# foo = 123, bar = "baz", x = {gni = true}
# Module capture
let v.{foo, bar} = "aabbcc".{foo = 123, bar = "baz", gni = true}
# v = "aabbcc", foo = 123, bar = "baz"
# Module capture with ignored value
let _.{foo, bar} = "aabbcc".{foo = 123, bar = "baz", gni = true}
# foo = 123, bar = "baz"
# Record capture with sub-patterns. Same works for module!
let {foo = [x, y, z], gni} = {foo = [1, 2, 3], gni = "baz"}
# foo = [1, 2, 3], x = 1, y = 2, z = 3, gni = "baz"
# Record capture with optional methods:
let { foo? } = ()
# foo = null()
let { foo? } = { foo = 123 }
# foo = 123
Combining patterns
As seen with record and modules, patterns can be combined at will, for instance, these are all valid patterns:
let [{foo}, {gni}, ..., {baz}] = l
let (_.{ bla = [..., z] }, t, _, u) = x
Advanced values
In this section, we detail some more advanced values than the ones presented in. You are not expected to be understanding those in details for basic uses of Liquidsoap.
Errors
In the case where a function does not have a sensible result to
return, it can raise an error. Typically, if we try to take the
head of the empty list without specifying a default value (with the
optional parameter default
), an error will be raised. By
default, this error will stop the script, which is usually not a
desirable behavior. For instance, if you try to run a script
containing
list.hd([])
the program will exit printing
Error 14: Uncaught runtime error:
type: not_found, message: "no default value for list.hd"
This means that the error named “not_found
” was raised,
with a message explaining that the function did not have a reasonable
default value of the head to provide.
In order to avoid this, one can catch exceptions with the syntax
try
codecatch err do
handlerend
This will execute the instructions code
: if an error is
raised at some point during this, the code handler
is
executed, with err
being the error. For instance, instead
of writing
l = []
x = list.hd(default=0, l)
we could equivalently write
l = []
x =
try
list.hd(l)
catch err do
0
end
The name and message associated to an error can respectively be
retrieved using the error kind
and message
attributes, e.g. we can write
try
...catch err do
print("the error #{err.kind} was raised")
print("the error message is #{err.message}")
end
Typically, when reading from or writing to a file, errors will be raised when a problem occurs (such as reading from a non-existent file or writing a file in a non-existent directory) and one should always check for those and log the corresponding message:
data = "bla"
try
file.write(data=data, "/non/existent/path")
catch err do
log.important("Could not write to file: #{error.message(err)}")
end
Specific errors can be caught with the syntax
try
...catch err : l do
...end
where l
is a list of error names that we want to handle
here.
Errors can be raised from Liquidsoap with the function
error.raise
, which takes as arguments the error to raise
and the error message. For instance:
error.raise(error.not_found, "we could not find your result")
We should also mention that all the errors should be declared in
advance with the function error.register
, which takes as
argument the name of the new error to register:
myerr = error.register("my_error")
error.raise(myerr, "testing my own error")
Lastly, if you need to make sure that a certain piece of code is executed whether or not there is an exception raised, you can use finally:
# Without a catch block
try
...
finally
...end
# With a catch block
try
...catch ... do
...
finally
...end
This is roughly equivalent to:
finally_called = ref(false)
def finally() = ... end
try
let ret = ...
true
finally_called := finally()
ret# If specified:
catch ... do
let ret = ...
if not finally_called() then finally() end
retend
The biggest different is that finally
is called on all
errors, including internal errors that cannot be caught by the runtime
code.
Errors raised in a finally
block do override any
previously raised errors.
Nullable values
It is sometimes useful to have a default value for a type. In
Liquidsoap, there is a special value for this, which is called
null
. Given a type t
, we write t?
for the type of values which can be either of type t
or be
null
: such a value is said to be nullable. For
instance, we could redefine the list.hd
function in order
to return null (instead of raising an error) when the list is empty:
def list.hd(l)
if l == [] then null() else list.hd(l) end
end
whose type would be
(['a]) -> 'a?
since it takes as argument a list whose elements are of type
'a
and returns a list whose elements are 'a
or
null
. As it can be observed above, the null value is
created with null()
.
In order to use a nullable value, one typically uses the construction
x ?? d
which is the value x
excepting when it
is null, in which case it is the default value d
. For
instance, with the above head function:
x = list.hd(l)
print("the head is " ^ (x ?? "not defined"))
Some other useful functions include
null.defined
: test whether a value is null or not,null.get
: obtain the value of a nullable value supposed to be distinct fromnull
,null.case
: execute a function or another, depending on whether a value is null or not.
Runtime evaluation of scripting values
Similarly to how JSON is parsed, you can
evaluate string into values at runtime using the eval
decorator. As with JSON, too, the recommended way to use it is by adding
an explicit type annotation:
let eval (x: {foo: int, bla: string}) = "{foo = 123, bla = \"gni\"}"
print("x.foo = #{x.foo}, x.bla = #{x.bla}")
Including other files
It is often useful to split your script over multiple files, either
because it has become quite large, or because you want to be able to
reuse common functions between different scripts. You can include a file
file.liq
in a script by writing
%include "file.liq"
which will be evaluated as if you had pasted the contents of the file in place of the command.
For instance, this is useful in order to store passwords out of the
main file, in order to avoid risking leaking those when handing the
script to some other people. Typically, one would have a file
passwords.liq
defining the passwords in variables, e.g.
radio_pass = "secretpassword"
and would then use it by including it:
%include "passwords.liq"
radio = ...
output.icecast(%mp3, host="localhost", port=8000,
password=radio_pass, mount="my-radio.mp3", radio)
so that passwords are not shown in the main script.
Code comments
Comments can be added to your code in two ways:
Multi-line comments are comments that can span multiple
lines. They are delimitated by the sequence of characters
#<
at the beginning and >#
at the end.
Anything in between those two sequences is considered code comment.
Here are some examples:
Simple multiline comments:
#< This is a comment >#
Multiline comments can be nested:
#<
This is a top-level comment
# This is also a comment
#<
This is a nested code comment#
># >
Fancy looking multiline comment
#<------- BEGIN CODE COMMENT ----#
Comments can also look like this#--------- END CODE COMMENT ----->#
Single-line comments are comments that are limited to the
current line. Such comments are started with the character
#
without a following <
. Anything after the
initial #
character and until the end of the line is
considered code comment:
def f(x) = # This is a single line comment.
123
end
Caching
Type-checking scripts can take a lot of time and consume memory. To optimize things, this step can be cached.
During the first execution, the script is parsed, type checked and
evaluated. On second and any following execution, a cache of the script
is used, reducing the typechecking phase, sometimes by a
100x
factor!
Here’s a log without caching on a M3 macbook pro:
2024/07/03 14:31:41 [startup:3] main script hash computation: 0.03s
2024/07/03 14:31:41 [startup:3] main script cache retrieval: 0.03s
2024/07/03 14:31:41 [startup:3] stdlib hash computation: 0.03s
2024/07/03 14:31:41 [startup:3] stdlib cache retrieval: 0.03s
2024/07/03 14:31:41 [startup:3] Typechecking stdlib: 3.37s
2024/07/03 14:31:41 [startup:3] Typechecking main script: 0.00s
And the same log after caching:
2024/07/03 14:32:59 [startup:3] main script hash computation: 0.02s
2024/07/03 14:32:59 [startup:3] Loading main script from cache!
2024/07/03 14:32:59 [startup:3] main script cache retrieval: 0.05s
Scripts can be cached ahead of time without executing them, for
instance while compiling a docker image, using
--cache-only
. Caching can also be disabled using
--no-cache
.
Caching happens at two different time:
- First the standard library is cached
- Then the script itself is cached
Caching the standard library makes it possible to run the type-checker faster on new scripts. Here’s an example of a log from running a new script with a cached standard library:
2024/07/03 14:33:27 [startup:3] main script hash computation: 0.02s
2024/07/03 14:33:27 [startup:3] main script cache retrieval: 0.02s
2024/07/03 14:33:27 [startup:3] stdlib hash computation: 0.03s
2024/07/03 14:33:27 [startup:3] Loading stdlib from cache!
2024/07/03 14:33:27 [startup:3] stdlib cache retrieval: 0.10s
2024/07/03 14:33:27 [startup:3] Typechecking main script: 0.00s
Caching can be disabled by setting LIQ_CACHE
to anything
else than "true"
.
Cache locations
Cache files can accumulate and also take up disk space so it is important to know where they are located!
There are two type of cache locations:
- System cache for cached files that should be shared with all
liquidsoap scripts. This is where the standard library cache is located.
This location is a system-wide path on unix system such as
/var/cache/liquidsoap
. - User cache for cached files that are specific to the user running
liquidsoap scripts. On unix systems, this location is at
$HOME/.cache/liquidsoap
.
On windows, the default cache directory for both type of cache locations is in the same directory as the binary.
At runtime, liquidsoap.cache(mode=<mode>)
returns
the cache directory. mode
should be one of:
"user"
or "system"
.
Cache maintenance
There is a cache maintenance routine which deletes unused cache files
after 10
days and keeps the cache to a maximum of
200
files.
You can run the cache maintenance routing by calling
liquidsoap.cache.maintenance(mode=<mode>)
manually.
Here, too, mode
should be one of: "user"
or
"system"
.
Cache security
Please be aware that the cache does not encrypt its values. As such, user cache files should be considered sensitive as they may contain password and other runtime secrets that are available through your scripts. We recommend to:
- Use environment variables as much as possible when passing secrets
- Secure your user script and cache files.
The default creation permissions for user cache files is:
0o600
so only the user creating them should be able to read
them. You should make sure that your script permissions are also
similarly restricted.
Cache and memory usage
One side-benefit from loading a script from cache is that the entire typechecking process is skipped.
This can result is significant reduction in the initial memory
consumption, typically down from about 375MB
to about
80MB
!
If memory consumption is a concern but you are not sure you can cache
your script, you can also set the environment variable
settings.init.compact_before_start
to
true
:
true settings.init.compact_before_start :=
This will run the OCaml memory compaction algorithm after typechecking your script but before running it. This will result in a similar memory footprint when running the script but will delay its initial startup time.
Cache environment variables
The following environment variables control the cache behavior:
LIQ_CACHE
: disable the cache when set to anything else than1
ortrue
LIQ_CACHE_SYSTEM_DIR
: set the cache system directoryLIQ_CACHE_SYSTEM_DIR_PERMS
: set the permission used when creating cache system directory (and its parents when needed). Default:0o755
LIQ_CACHE_SYSTEM_FILE_PERMS
: set the permissions used when creating a system cache file. Default:0o644
LIQ_CACHE_USER_DIR
: set the cache user directoryLIQ_CACHE_USER_DIR_PERMS
: set the permission used when creating cache user directory (and its parents when needed). Default:0o700
.LIQ_CACHE_USER_FILE_PERMS
: set the permissions used when creating a user cache file. Default:0o600
LIQ_CACHE_MAX_DAYS
: set the maximum days a cache file can be stored before it is eligible to be deleted during the next cache maintenance pass.LIQ_CACHE_MAX_FILES
: set the maximum number of files in each cache directory. Older files are removed first.