DSL variables¶
Miller has the following kinds of variables:
Fields of stream records, accessed using the $ prefix. These refer to fields of the current data-stream record. For example, in echo x=1,y=2 | mlr put '$z = $x + $y', $x and $y refer to input fields, and $z refers to a new, computed output field. In a few contexts, presented below, you can refer to the entire record as $*.
Out-of-stream variables accessed using the @ prefix. These refer to data which persist from one record to the next, including in begin and end blocks (which execute before/after the record stream is consumed, respectively). You use them to remember values across records, such as sums, differences, counters, and so on. In a few contexts, presented below, you can refer to the entire out-of-stream-variables collection as @*.
Local variables are limited in scope and extent to the current statements being executed: these include function arguments, bound variables in for loops, and local variables.
Built-in variables such as NF, NR, FILENAME, M_PI, and M_E. These are all capital letters and are read-only (although some of them change value from one record to another).
Keywords are not variables, but since their names are reserved, you cannot use these names for local variables.
Field names¶
Names of fields within stream records must be specified using a $ in filter and put expressions, even though the dollar signs don't appear in the data stream itself. For integer-indexed data, this looks like awk's $1,$2,$3, except that Miller allows non-numeric names such as $quantity or $hostname. Likewise, enclose string literals in double quotes in filter expressions even though they don't appear in file data. In particular, mlr filter '$x=="abc"' passes through the record x=abc.
If field names have special characters such as . then you can use braces, e.g. '${field.name}'.
You may also use a computed field name in square brackets, e.g.
echo a=3,b=4 | mlr filter '$["x"] < 0.5'
echo s=green,t=blue,a=3,b=4 | mlr put '$[$s."_".$t] = $a * $b'
s=green,t=blue,a=3,b=4,green_blue=12
Notes:
The names of record fields depend on the contents of your input data stream, and their values change from one record to the next as Miller scans through your input data stream.
Their extent is limited to the current record; their scope is the filter or put command in which they appear.
These are read-write: you can do $y=2*$x, $x=$x+1, etc.
Records are Miller's output: field names present in the input stream are passed through to output (written to standard output) unless fields are removed with cut, or records are excluded with filter or put -q, etc. Simply assign a value to a field and it will be output.
Positional field names¶
Even though Miller's main selling point is name-indexing, sometimes you really want to refer to a field name by its positional index (starting from 1).
Use $[[3]] to access the name of field 3. More generally, any expression evaluating to an integer can go between $[[ and ]].
Then using a computed field name, $[ $[[3]] ] is the value in the third field. This has the shorter equivalent notation $[[[3]]].
mlr cat data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802 a=eks,b=pan,i=2,x=0.758679,y=0.522151 a=wye,b=wye,i=3,x=0.204603,y=0.338318 a=eks,b=wye,i=4,x=0.381399,y=0.134188 a=wye,b=pan,i=5,x=0.573288,y=0.863624
mlr put '$[[3]] = "NEW"' data/small
a=pan,b=pan,NEW=1,x=0.346791,y=0.726802 a=eks,b=pan,NEW=2,x=0.758679,y=0.522151 a=wye,b=wye,NEW=3,x=0.204603,y=0.338318 a=eks,b=wye,NEW=4,x=0.381399,y=0.134188 a=wye,b=pan,NEW=5,x=0.573288,y=0.863624
mlr put '$[[[3]]] = "NEW"' data/small
a=pan,b=pan,i=NEW,x=0.346791,y=0.726802 a=eks,b=pan,i=NEW,x=0.758679,y=0.522151 a=wye,b=wye,i=NEW,x=0.204603,y=0.338318 a=eks,b=wye,i=NEW,x=0.381399,y=0.134188 a=wye,b=pan,i=NEW,x=0.573288,y=0.863624
mlr put '$NEW = $[[NR]]' data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802,NEW=a a=eks,b=pan,i=2,x=0.758679,y=0.522151,NEW=b a=wye,b=wye,i=3,x=0.204603,y=0.338318,NEW=i a=eks,b=wye,i=4,x=0.381399,y=0.134188,NEW=x a=wye,b=pan,i=5,x=0.573288,y=0.863624,NEW=y
mlr put '$NEW = $[[[NR]]]' data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802,NEW=pan a=eks,b=pan,i=2,x=0.758679,y=0.522151,NEW=pan a=wye,b=wye,i=3,x=0.204603,y=0.338318,NEW=3 a=eks,b=wye,i=4,x=0.381399,y=0.134188,NEW=0.381399 a=wye,b=pan,i=5,x=0.573288,y=0.863624,NEW=0.863624
mlr put '$[[[NR]]] = "NEW"' data/small
a=NEW,b=pan,i=1,x=0.346791,y=0.726802 a=eks,b=NEW,i=2,x=0.758679,y=0.522151 a=wye,b=wye,i=NEW,x=0.204603,y=0.338318 a=eks,b=wye,i=4,x=NEW,y=0.134188 a=wye,b=pan,i=5,x=0.573288,y=NEW
Right-hand side accesses to non-existent fields -- i.e. with index less than 1 or greater than NF -- return an absent value. Likewise, left-hand side accesses only refer to fields which already exist. For example, if a field has 5 records then assigning the name or value of the 6th (or 600th) field results in a no-op.
mlr put '$[[6]] = "NEW"' data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802 a=eks,b=pan,i=2,x=0.758679,y=0.522151 a=wye,b=wye,i=3,x=0.204603,y=0.338318 a=eks,b=wye,i=4,x=0.381399,y=0.134188 a=wye,b=pan,i=5,x=0.573288,y=0.863624
mlr put '$[[[6]]] = "NEW"' data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802 a=eks,b=pan,i=2,x=0.758679,y=0.522151 a=wye,b=wye,i=3,x=0.204603,y=0.338318 a=eks,b=wye,i=4,x=0.381399,y=0.134188 a=wye,b=pan,i=5,x=0.573288,y=0.863624
Out-of-stream variables¶
These are prefixed with an at-sign, e.g. @sum. Furthermore, unlike built-in variables and stream-record fields, they are maintained in an arbitrarily nested map: you can do @sum += $quantity, or @sum[$color] += $quantity, or @sum[$color][$shape] += $quantity. The keys for the multi-level map can be any expression which evaluates to string or integer: e.g. @sum[NR] = $a + $b, @sum[$a."-".$b] = $x, etc.
Their names and their values are entirely under your control; they change only when you assign to them.
Just as for field names in stream records, if you want to define out-of-stream variables with special characters such as . then you can use braces, e.g. '@{variable.name}["index"]'.
You may use a computed key in square brackets, e.g.
echo s=green,t=blue,a=3,b=4 | mlr put -q '@[$s."_".$t] = $a * $b; emit all'
green_blue=12
Out-of-stream variables are scoped to the put command in which they appear. In particular, if you have two or more put commands separated by then, each put will have its own set of out-of-stream variables:
cat data/a.dkvp
a=1,b=2,c=3 a=4,b=5,c=6
mlr put '@sum += $a; end {emit @sum}' \
then put 'is_present($a) {$a=10*$a; @sum += $a}; end {emit @sum}' \
data/a.dkvp
a=10,b=2,c=3 a=40,b=5,c=6 sum=5 sum=50
Out-of-stream variables' extent is from the start to the end of the record stream, i.e. every time the put or filter statement referring to them is executed.
Out-of-stream variables are read-write: you can do $sum=@sum, @sum=$sum, etc.
Indexed out-of-stream variables¶
Using an index on the @count and @sum variables, we get the benefit of the -g (group-by) option which mlr stats1 and various other Miller commands have:
mlr put -q '
@x_count[$a] += 1;
@x_sum[$a] += $x;
end {
emit @x_count, "a";
emit @x_sum, "a";
}
' ./data/small
a=pan,x_count=1 a=eks,x_count=2 a=wye,x_count=2 a=pan,x_sum=0.346791 a=eks,x_sum=1.140078 a=wye,x_sum=0.777891
mlr stats1 -a count,sum -f x -g a ./data/small
a=pan,x_count=1,x_sum=0.346791 a=eks,x_count=2,x_sum=1.140078 a=wye,x_count=2,x_sum=0.777891
Indices can be arbitrarily deep -- here there are two or more of them:
mlr --from data/medium put -q '
@x_count[$a][$b] += 1;
@x_sum[$a][$b] += $x;
end {
emit (@x_count, @x_sum), "a", "b";
}
'
a=pan,b=pan,x_count=427,x_sum=219.1851288316854 a=pan,b=wye,x_count=395,x_sum=198.43293070748447 a=pan,b=eks,x_count=429,x_sum=216.07522773165525 a=pan,b=hat,x_count=417,x_sum=205.22277621488686 a=pan,b=zee,x_count=413,x_sum=205.09751802331917 a=eks,b=pan,x_count=371,x_sum=179.96303047250723 a=eks,b=wye,x_count=407,x_sum=196.9452860713734 a=eks,b=zee,x_count=357,x_sum=176.8803651584733 a=eks,b=eks,x_count=413,x_sum=215.91609712937984 a=eks,b=hat,x_count=417,x_sum=208.783170520597 a=wye,b=wye,x_count=377,x_sum=185.29584980261419 a=wye,b=pan,x_count=392,x_sum=195.84790012056564 a=wye,b=hat,x_count=426,x_sum=212.0331829346132 a=wye,b=zee,x_count=385,x_sum=194.77404756708714 a=wye,b=eks,x_count=386,x_sum=204.8129608356315 a=zee,b=pan,x_count=389,x_sum=202.21380378504267 a=zee,b=wye,x_count=455,x_sum=233.9913939194868 a=zee,b=eks,x_count=391,x_sum=190.9617780631925 a=zee,b=zee,x_count=403,x_sum=206.64063510417319 a=zee,b=hat,x_count=409,x_sum=191.30000620900935 a=hat,b=wye,x_count=423,x_sum=208.8830097609959 a=hat,b=zee,x_count=385,x_sum=196.3494502965293 a=hat,b=eks,x_count=389,x_sum=189.0067933716193 a=hat,b=hat,x_count=381,x_sum=182.8535323148762 a=hat,b=pan,x_count=363,x_sum=168.5538067327806
The idea is that stats1, and other Miller verbs, encapsulate frequently-used patterns with a minimum of keystroking (and run a little faster), whereas using out-of-stream variables you have more flexibility and control in what you do.
Begin/end blocks can be mixed with pattern/action blocks. For example:
mlr put '
begin {
@num_total = 0;
@num_positive = 0;
};
@num_total += 1;
$x > 0.0 {
@num_positive += 1;
$y = log10($x); $z = sqrt($y)
};
end {
emitf @num_total, @num_positive
}
' data/put-gating-example-1.dkvp
x=-1 x=0 x=1,y=0,z=0 x=2,y=0.3010299956639812,z=0.5486620049392715 x=3,y=0.4771212547196624,z=0.6907396432228734 num_total=5,num_positive=3
Local variables¶
Local variables are similar to out-of-stream variables, except that their extent is limited to the expressions in which they appear (and their basenames can't be computed using square brackets). There are three kinds of local variables: arguments to functions/subroutines, variables bound within for-loops, and locals defined within control blocks. They may be untyped using var, or typed using num, int, float, str, bool, arr, map, and funct.
For example:
# Here I'm using a specified random-number seed so this example always
# produces the same output for this web document: in everyday practice we
# would leave off the --seed 12345 part.
mlr --seed 12345 seqgen --start 1 --stop 10 then put '
func f(a, b) { # function arguments a and b
r = 0.0; # local r scoped to the function
for (int i = 0; i < 6; i += 1) { # local i scoped to the for-loop
num u = urand(); # local u scoped to the for-loop
r += u; # updates r from the enclosing scope
}
r /= 6;
return a + (b - a) * r;
}
num o = f(10, 20); # local to the top-level scope
$o = o;
'
i=1,o=15.952526011537227 i=2,o=12.782237754999116 i=3,o=15.126606630220966 i=4,o=14.794357488895775 i=5,o=15.168665974047421 i=6,o=16.20662783079942 i=7,o=13.966128063060479 i=8,o=13.99248245928659 i=9,o=15.784270485515197 i=10,o=15.37686787628025
Things which are completely unsurprising, resembling many other languages:
-
Parameter names are bound to their arguments but can be reassigned, e.g. if there is a parameter named
athen you can reassign the value ofato be something else within the function if you like. -
However, you cannot redeclare the type of an argument or a local:
var a=1; var a=2is an error butvar a=1; a=2is OK. -
All argument-passing is positional rather than by name; arguments are passed by value, not by reference. (This is also true for map-valued variables: they are not, and cannot be, passed by reference.)
-
You can define locals (using
var,num, etc.) at any scope (if-statements, else-statements, while-loops, for-loops, or the top-level scope), and nested scopes will have access (more details on scope in the next section). If you define a local variable with the same name inside an inner scope, then a new variable is created with the narrower scope. -
If you assign to a local variable for the first time in a scope without declaring it as
var,num, etc. then: if it exists in an outer scope, that outer-scope variable will be updated; if not, it will be defined in the current scope as ifvarhad been used. (See also Type-checking for an example.) I recommend always declaring variables explicitly to make the intended scoping clear. -
Functions and subroutines never have access to locals from their callee (unless passed by value as arguments).
Things which are perhaps surprising compared to other languages:
-
Type declarations using
var, or typed usingnum,int,float,str,bool,arr,map,functare not necessary to declare local variables. Function arguments and variables bound in for-loops over stream records and out-of-stream variables are implicitly declared usingvar. (Some examples are shown below.) -
Type-checking is done at assignment time. For example,
float f = 0is an error (since0is an integer), as isfloat f = 0.0; f = 1. For this reason I prefer to usenumoverfloatin most contexts sincenumencompasses integer and floating-point values. More information is at Type-checking. -
Bound variables in for-loops over stream records and out-of-stream variables are implicitly local to that block. E.g. in
for (k, v in $*) { ... }for ((k1, k2), v in @*) { ... }if there arek,v, etc. in the enclosing scope then those will be masked by the loop-local bound variables in the loop, and moreover the values of the loop-local bound variables are not available after the end of the loop. -
For C-style triple-for loops, if a for-loop variable is defined using
var,int, etc. then it is scoped to that for-loop. E.g.for (i = 0; i < 10; i += 1) { ... }andfor (int i = 0; i < 10; i += 1) { ... }. (This is unsurprising.). If there is no typedecl and an outer-scope variable of that name exists, then it is used. (This is also unsurprising.) But if there is no outer-scope variable of that name, then the variable is scoped to the for-loop only.
The following example demonstrates the scope rules:
cat data/scope-example.mlr
func f(a) { # argument is local to the function
var b = 100; # local to the function
c = 100; # local to the function; does not overwrite outer c
return a + 1;
}
var a = 10; # local at top level
var b = 20; # local at top level
c = 30; # local at top level; there is no more-outer-scope c
if (NR == 3) {
var a = 40; # scoped to the if-statement; doesn't overwrite outer a
b = 50; # not scoped to the if-statement; overwrites outer b
c = 60; # not scoped to the if-statement; overwrites outer c
d = 70; # there is no outer d so a local d is created here
$inner_a = a;
$inner_b = b;
$inner_c = c;
$inner_d = d;
}
$outer_a = a;
$outer_b = b;
$outer_c = c;
$outer_d = d; # there is no outer d defined so no assignment happens
cat data/scope-example.dat
n=1,x=123 n=2,x=456 n=3,x=789
mlr --oxtab --from data/scope-example.dat put -f data/scope-example.mlr
n 1 x 123 outer_a 10 outer_b 20 outer_c 30 n 2 x 456 outer_a 10 outer_b 20 outer_c 30 n 3 x 789 inner_a 40 inner_b 50 inner_c 60 inner_d 70 outer_a 10 outer_b 50 outer_c 60
And this example demonstrates the type-declaration rules:
cat data/type-decl-example.mlr
subr s(a, str b, int c) { # a is implicitly var (untyped).
# b is explicitly str.
# c is explicitly int.
# The type-checking is done at the callsite
# when arguments are bound to parameters.
#
var b = 100; # error # Re-declaration in the same scope is disallowed.
int n = 10; # Declaration of variable local to the subroutine.
n = 20; # Assignment is OK.
int n = 30; # error # Re-declaration in the same scope is disallowed.
str n = "abc"; # error # Re-declaration in the same scope is disallowed.
#
float f1 = 1; # error # 1 is an int, not a float.
float f2 = 2.0; # 2.0 is a float.
num f3 = 3; # 3 is a num.
num f4 = 4.0; # 4.0 is a num.
} #
#
call s(1, 2, 3); # Type-assertion '3 is int' is done here at the callsite.
#
k = "def"; # Top-level variable k.
#
for (str k, v in $*) { # k and v are bound here, masking outer k.
print k . ":" . v; # k is explicitly str; v is implicitly var.
} #
#
print "k is".k; # k at this scope level is still "def".
print "v is".v; # v is undefined in this scope.
#
i = -1; #
for (i = 1, int j = 2; i <= 10; i += 1, j *= 2) {
# C-style triple-for variables use enclosing scope,
# unless declared local: i is outer, j is local to the loop.
print "inner i =", i; #
print "inner j =", j; #
} #
print "outer i =", i; # i has been modified by the loop.
print "outer j =", j; # j is undefined in this scope.
Map literals¶
Miller's put/filter DSL has four kinds of maps. Stream records are (single-level) maps from name to value. Out-of-stream variables and local variables can also be maps, although they can be multi-level maps (e.g. @sum[$x][$y]). The fourth kind is map literals. These cannot be on the left-hand side of assignment expressions. Syntactically they look like JSON, although Miller allows string and integer keys in its map literals while JSON allows only string keys (e.g. "3" rather than 3). Note though that integer keys become stringified in Miller: @mymap[3]=4 results in @mymap being {"3":4}.
For example, the following swaps the input stream's a and i fields, modifies y, and drops the rest:
mlr --opprint put '
$* = {
"a": $i,
"i": $a,
"y": $y * 10,
}
' data/small
a i y 1 pan 7.26802 2 eks 5.22151 3 wye 3.3831800000000003 4 eks 1.34188 5 wye 8.636239999999999
Likewise, you can assign map literals to out-of-stream variables or local variables; pass them as arguments to user-defined functions, return them from functions, and so on:
mlr --from data/small put '
func f(map m): map {
m["x"] *= 200;
return m;
}
$* = f({"a": $a, "x": $x});
'
a=pan,x=69.3582 a=eks,x=151.7358 a=wye,x=40.9206 a=eks,x=76.2798 a=wye,x=114.6576
Like out-of-stream and local variables, map literals can be multi-level:
mlr --from data/small put -q '
begin {
@o = {
"nrec": 0,
"nkey": {"numeric":0, "non-numeric":0},
};
}
@o["nrec"] += 1;
for (k, v in $*) {
if (is_numeric(v)) {
@o["nkey"]["numeric"] += 1;
} else {
@o["nkey"]["non-numeric"] += 1;
}
}
end {
dump @o;
}
'
{
"nrec": 5,
"nkey": {
"numeric": 15,
"non-numeric": 10
}
}
See also the Maps page.
Built-in variables¶
These are written all in capital letters, and only a small, specific set of them is defined by Miller.
Namely, Miller supports the following five built-in variables for filter and
put, all awk-inspired: NF, NR, FNR, FILENUM, and
FILENAME, as well as the mathematical constants M_PI and M_E. As well,
there are the read-only separator variables IRS, ORS, IFS, OFS, IPS,
and OPS as discussed on the separators page,
and the flatten/unflatten separator FLATSEP discussed on the
flatten/unflatten page. Lastly, the ENV map allows
read/write access to environment variables, e.g. ENV["HOME"] or
ENV["foo_".$hostname] or ENV["VERSION"]="1.2.3".
mlr filter 'FNR == 2' data/small*
a=eks,b=pan,i=2,x=0.758679,y=0.522151 1=pan,2=pan,3=1,4=0.3467901443380824,5=0.7268028627434533 a=wye,b=eks,i=10000,x=0.734806020620654365,y=0.884788571337605134
mlr put '$fnr = FNR' data/small*
a=pan,b=pan,i=1,x=0.346791,y=0.726802,fnr=1 a=eks,b=pan,i=2,x=0.758679,y=0.522151,fnr=2 a=wye,b=wye,i=3,x=0.204603,y=0.338318,fnr=3 a=eks,b=wye,i=4,x=0.381399,y=0.134188,fnr=4 a=wye,b=pan,i=5,x=0.573288,y=0.863624,fnr=5 1=a,2=b,3=i,4=x,5=y,fnr=1 1=pan,2=pan,3=1,4=0.3467901443380824,5=0.7268028627434533,fnr=2 1=eks,2=pan,3=2,4=0.7586799647899636,5=0.5221511083334797,fnr=3 1=wye,2=wye,3=3,4=0.20460330576630303,5=0.33831852551664776,fnr=4 1=eks,2=wye,3=4,4=0.38139939387114097,5=0.13418874328430463,fnr=5 1=wye,2=pan,3=5,4=0.5732889198020006,5=0.8636244699032729,fnr=6 a=pan,b=eks,i=9999,x=0.267481232652199086,y=0.557077185510228001,fnr=1 a=wye,b=eks,i=10000,x=0.734806020620654365,y=0.884788571337605134,fnr=2 a=pan,b=wye,i=10001,x=0.870530722602517626,y=0.009854780514656930,fnr=3 a=hat,b=wye,i=10002,x=0.321507044286237609,y=0.568893318795083758,fnr=4 a=pan,b=zee,i=10003,x=0.272054845593895200,y=0.425789896597056627,fnr=5
Their values of NF, NR, FNR, FILENUM, and FILENAME change from one
record to the next as Miller scans through your input data stream. The
mathematical constants, of course, do not change; ENV is populated from the
system environment variables at the time Miller starts. Any changes made to
ENV by assigning to it will affect any subprocesses, such as using
piped tee.
Their scope is global: you can refer to them in any filter or put statement. Their values are assigned by the input-record reader:
mlr --csv put '$nr = NR' data/a.csv
a,b,c,nr 1,2,3,1 4,5,6,2
mlr --csv repeat -n 3 then put '$nr = NR' data/a.csv
a,b,c,nr 1,2,3,1 1,2,3,1 1,2,3,1 4,5,6,2 4,5,6,2 4,5,6,2
The extent is for the duration of the put/filter: in a begin statement (which executes before the first input record is consumed) you will find NR=1 and in an end statement (which is executed after the last input record is consumed) you will find NR to be the total number of records ingested.
These are all read-only for the mlr put and mlr filter DSL: they may be assigned from, e.g. $nr=NR, but they may not be assigned to: NR=100 is a syntax error.
Type-checking¶
Miller's put/filter DSL supports two optional kinds of type-checking. One is inline type-tests and type-assertions within expressions. The other is type declarations for assignments to local variables, binding of arguments to user-defined functions, and return values from user-defined functions, These are discussed in the following subsections.
Use of type-checking is entirely up to you: omit it if you want flexibility with heterogeneous data; use it if you want to help catch misspellings in your DSL code or unexpected irregularities in your input data.
Type-test and type-assertion expressions¶
The following is_... functions take a value and return a boolean indicating whether the argument is of the indicated type. The assert_... functions return their argument if it is of the specified type, and cause a fatal error otherwise:
mlr -f | grep ^is
is_absent is_array is_bool is_boolean is_empty is_empty_map is_error is_float is_int is_map is_nan is_nonempty_map is_not_array is_not_empty is_not_map is_not_null is_null is_numeric is_present is_string
mlr -f | grep ^assert
asserting_absent asserting_array asserting_bool asserting_boolean asserting_empty asserting_empty_map asserting_error asserting_float asserting_int asserting_map asserting_nonempty_map asserting_not_array asserting_not_empty asserting_not_map asserting_not_null asserting_null asserting_numeric asserting_present asserting_string
See Data-cleaning Examples for examples of how to use these.
Type-declarations for local variables, function parameter, and function return values¶
Local variables can be defined either untyped as in x = 1, or typed as in int x = 1. Types include var (explicitly untyped), int, float, num (int or float), str, bool, arr, map, and funct. These optional type declarations are enforced at the time values are assigned to variables: whether at the initial value assignment as in int x = 1 or in any subsequent assignments to the same variable farther down in the scope.
The reason for num is that int and float typedecls are very precise:
float a = 0; # Runtime error since 0 is int not float int b = 1.0; # Runtime error since 1.0 is float not int num c = 0; # OK num d = 1.0; # OK
A suggestion is to use num for general use when you want numeric content, and use int when you genuinely want integer-only values, e.g. in loop indices or map keys (since Miller map keys can only be strings or ints).
The var type declaration indicates no type restrictions, e.g. var x = 1 has the same type restrictions on x as x = 1. The difference is in intentional shadowing: if you have x = 1 in outer scope and x = 2 in inner scope (e.g. within a for-loop or an if-statement) then outer-scope x has value 2 after the second assignment. But if you have var x = 2 in the inner scope, then you are declaring a variable scoped to the inner block.) For example:
x = 1;
if (NR == 4) {
x = 2; # Refers to outer-scope x: value changes from 1 to 2.
}
print x; # Value of x is now two
x = 1;
if (NR == 4) {
var x = 2; # Defines a new inner-scope x with value 2
}
print x; # Value of this x is still 1
Likewise function arguments can optionally be typed, with type enforced when the function is called:
func f(map m, int i) {
...
}
$a = f({1:2, 3:4}, 5); # OK
$b = f({1:2, 3:4}, "abc"); # Runtime error
$c = f({1:2, 3:4}, $x); # Runtime error for records with non-integer field named x
if (NR == 4) {
var x = 2; # Defines a new inner-scope x with value 2
}
print x; # Value of this x is still 1
Thirdly, function return values can be type-checked at the point of return using : and a typedecl after the parameter list:
func f(map m, int i): bool {
...
...
if (...) {
return "false"; # Runtime error if this branch is taken
}
...
...
if (...) {
return retval; # Runtime error if this function doesn't have an in-scope
# boolean-valued variable named retval
}
...
...
# In Miller if your functions don't explicitly return a value, they return absent-null.
# So it would also be a runtime error on reaching the end of this function without
# an explicit return statement.
}
The funct keyword, for function type, indicates that a variable, argument, or return value is a function -- either a function literal or a (named) user-defined function.
$ cat funct-example.mlr
func makefunc(): funct {
return func(x,y) {
return 10*x + y
}
}
func callfunc(funct f, num x, num y): num {
return f(x, y)
}
$ rlwrap mlr repl Miller 6.0.0-dev REPL for darwin/amd64/go1.17 Docs: https://miller.readthedocs.io Type ':h' or ':help' for online help; ':q' or ':quit' to quit. [mlr] :load funct-example.mlr [mlr] f = makefunc() [mlr] f function-literal-000001 [mlr] f(2,3) 23 [mlr] callfunc(f, 3, 5) 35
Aggregate variable assignments¶
There are three remaining kinds of variable assignment using out-of-stream variables, the last two of which use the $* syntax:
- Recursive copy of out-of-stream variables
- Out-of-stream variable assigned to full stream record
- Full stream record assigned to an out-of-stream variable
Example recursive copy of out-of-stream variables:
mlr --opprint --from data/small put -q '
@v["sum"] += $x;
@v["count"] += 1;
end{
dump;
@w = @v;
dump
}
'
{
"v": {
"sum": 2.26476,
"count": 5
}
}
{
"v": {
"sum": 2.26476,
"count": 5
},
"w": {
"sum": 2.26476,
"count": 5
}
}
Example of out-of-stream variable assigned to full stream record, where the 2nd record is stashed, and the 4th record is overwritten with that:
mlr put 'NR == 2 {@keep = $*}; NR == 4 {$* = @keep}' data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802 a=eks,b=pan,i=2,x=0.758679,y=0.522151 a=wye,b=wye,i=3,x=0.204603,y=0.338318 a=eks,b=pan,i=2,x=0.758679,y=0.522151 a=wye,b=pan,i=5,x=0.573288,y=0.863624
Example of full stream record assigned to an out-of-stream variable, finding the record for which the x field has the largest value in the input stream:
cat data/small
a=pan,b=pan,i=1,x=0.346791,y=0.726802 a=eks,b=pan,i=2,x=0.758679,y=0.522151 a=wye,b=wye,i=3,x=0.204603,y=0.338318 a=eks,b=wye,i=4,x=0.381399,y=0.134188 a=wye,b=pan,i=5,x=0.573288,y=0.863624
mlr --opprint put -q '
is_null(@xmax) || $x > @xmax {@xmax = $x; @recmax = $*};
end {emit @recmax}
' data/small
a b i x y eks pan 2 0.758679 0.522151
Keywords for filter and put¶
mlr help list-keywords # you can also use mlr -k
all begin bool break call continue do dump edump elif else emit1 emit emitf emitp end eprint eprintn false filter float for func funct if in int map num print printn return stderr stdout str subr tee true unset var while ENV FILENAME FILENUM FNR IFS IPS IRS M_E M_PI NF NR OFS OPS ORS
mlr help usage-keywords # you can also use mlr -K
all: used in "emit1", "emit", "emitp", and "unset" as a synonym for @*
begin: defines a block of statements to be executed before input records
are ingested. The body statements must be wrapped in curly braces.
Example: 'begin { @count = 0 }'
bool: declares a boolean local variable in the current curly-braced scope.
Type-checking happens at assignment: 'bool b = 1' is an error.
break: causes execution to continue after the body of the current for/while/do-while loop.
call: used for invoking a user-defined subroutine.
Example: 'subr s(k,v) { print k . " is " . v} call s("a", $a)'
continue: causes execution to skip the remaining statements in the body of
the current for/while/do-while loop. For-loop increments are still applied.
do: with "while", introduces a do-while loop. The body statements must be wrapped
in curly braces.
dump: prints all currently defined out-of-stream variables immediately
to stdout as JSON.
With >, >>, or |, the data do not go directly to stdout but are instead
redirected.
The > and >> are for write and append, as in the shell, but (as with awk) the
file-overwrite for > is on first write, not per record. The | is for piping to
a process which will process the data. There will be one open file for each
distinct file name (for > and >>) or one subordinate process for each distinct
value of the piped-to command (for |). Output-formatting flags are taken from
the main command line.
Example: mlr --from f.dat put -q '@v[NR]=$*; end { dump }'
Example: mlr --from f.dat put -q '@v[NR]=$*; end { dump > "mytap.dat"}'
Example: mlr --from f.dat put -q '@v[NR]=$*; end { dump >> "mytap.dat"}'
Example: mlr --from f.dat put -q '@v[NR]=$*; end { dump | "jq .[]"}'
edump: prints all currently defined out-of-stream variables immediately
to stderr as JSON.
Example: mlr --from f.dat put -q '@v[NR]=$*; end { edump }'
elif: the way Miller spells "else if". The body statements must be wrapped
in curly braces.
else: terminates an if/elif/elif chain. The body statements must be wrapped
in curly braces.
emit1: inserts an out-of-stream variable into the output record stream. Unlike
the other map variants, side-by-sides, indexing, and redirection are not supported,
but you can emit any map-valued expression.
Example: mlr --from f.dat put 'emit1 $*'
Example: mlr --from f.dat put 'emit1 mapsum({"id": NR}, $*)'
Please see https://miller.readthedocs.io://johnkerl.org/miller/doc for more information.
emit: inserts an out-of-stream variable into the output record stream. Hashmap
indices present in the data but not slotted by emit arguments are not output.
With >, >>, or |, the data do not become part of the output record stream but
are instead redirected.
The > and >> are for write and append, as in the shell, but (as with awk) the
file-overwrite for > is on first write, not per record. The | is for piping to
a process which will process the data. There will be one open file for each
distinct file name (for > and >>) or one subordinate process for each distinct
value of the piped-to command (for |). Output-formatting flags are taken from
the main command line.
You can use any of the output-format command-line flags, e.g. --ocsv, --ofs,
etc., to control the format of the output if the output is redirected. See also mlr -h.
Example: mlr --from f.dat put 'emit > "/tmp/data-".$a, $*'
Example: mlr --from f.dat put 'emit > "/tmp/data-".$a, mapexcept($*, "a")'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit @sums'
Example: mlr --from f.dat put --ojson '@sums[$a][$b]+=$x; emit > "tap-".$a.$b.".dat", @sums'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit @sums, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit > "mytap.dat", @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit >> "mytap.dat", @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit | "gzip > mytap.dat.gz", @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit > stderr, @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emit | "grep somepattern", @*, "index1", "index2"'
Please see https://miller.readthedocs.io://johnkerl.org/miller/doc for more information.
emitf: inserts non-indexed out-of-stream variable(s) side-by-side into the
output record stream.
With >, >>, or |, the data do not become part of the output record stream but
are instead redirected.
The > and >> are for write and append, as in the shell, but (as with awk) the
file-overwrite for > is on first write, not per record. The | is for piping to
a process which will process the data. There will be one open file for each
distinct file name (for > and >>) or one subordinate process for each distinct
value of the piped-to command (for |). Output-formatting flags are taken from
the main command line.
You can use any of the output-format command-line flags, e.g. --ocsv, --ofs,
etc., to control the format of the output if the output is redirected. See also mlr -h.
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf @a'
Example: mlr --from f.dat put --oxtab '@a=$i;@b+=$x;@c+=$y; emitf > "tap-".$i.".dat", @a'
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf @a, @b, @c'
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf > "mytap.dat", @a, @b, @c'
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf >> "mytap.dat", @a, @b, @c'
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf > stderr, @a, @b, @c'
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf | "grep somepattern", @a, @b, @c'
Example: mlr --from f.dat put '@a=$i;@b+=$x;@c+=$y; emitf | "grep somepattern > mytap.dat", @a, @b, @c'
Please see https://miller.readthedocs.io://johnkerl.org/miller/doc for more information.
emitp: inserts an out-of-stream variable into the output record stream.
Hashmap indices present in the data but not slotted by emitp arguments are
output concatenated with ":".
With >, >>, or |, the data do not become part of the output record stream but
are instead redirected.
The > and >> are for write and append, as in the shell, but (as with awk) the
file-overwrite for > is on first write, not per record. The | is for piping to
a process which will process the data. There will be one open file for each
distinct file name (for > and >>) or one subordinate process for each distinct
value of the piped-to command (for |). Output-formatting flags are taken from
the main command line.
You can use any of the output-format command-line flags, e.g. --ocsv, --ofs,
etc., to control the format of the output if the output is redirected. See also mlr -h.
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp @sums'
Example: mlr --from f.dat put --opprint '@sums[$a][$b]+=$x; emitp > "tap-".$a.$b.".dat", @sums'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp @sums, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp > "mytap.dat", @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp >> "mytap.dat", @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp | "gzip > mytap.dat.gz", @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp > stderr, @*, "index1", "index2"'
Example: mlr --from f.dat put '@sums[$a][$b]+=$x; emitp | "grep somepattern", @*, "index1", "index2"'
Please see https://miller.readthedocs.io://johnkerl.org/miller/doc for more information.
end: defines a block of statements to be executed after input records
are ingested. The body statements must be wrapped in curly braces.
Example: 'end { emit @count }'
Example: 'end { eprint "Final count is " . @count }'
eprint: prints expression immediately to stderr.
Example: mlr --from f.dat put -q 'eprint "The sum of x and y is ".($x+$y)'
Example: mlr --from f.dat put -q 'for (k, v in $*) { eprint k . " => " . v }'
Example: mlr --from f.dat put '(NR % 1000 == 0) { eprint "Checkpoint ".NR}'
eprintn: prints expression immediately to stderr, without trailing newline.
Example: mlr --from f.dat put -q 'eprintn "The sum of x and y is ".($x+$y); eprint ""'
false: the boolean literal value.
filter: includes/excludes the record in the output record stream.
Example: mlr --from f.dat put 'filter (NR == 2 || $x > 5.4)'
Instead of put with 'filter false' you can simply use put -q. The following
uses the input record to accumulate data but only prints the running sum
without printing the input record:
Example: mlr --from f.dat put -q '@running_sum += $x * $y; emit @running_sum'
float: declares a floating-point local variable in the current curly-braced scope.
Type-checking happens at assignment: 'float x = 0' is an error.
for: defines a for-loop using one of three styles. The body statements must
be wrapped in curly braces.
For-loop over stream record:
Example: 'for (k, v in $*) { ... }'
For-loop over out-of-stream variables:
Example: 'for (k, v in @counts) { ... }'
Example: 'for ((k1, k2), v in @counts) { ... }'
Example: 'for ((k1, k2, k3), v in @*) { ... }'
C-style for-loop:
Example: 'for (var i = 0, var b = 1; i < 10; i += 1, b *= 2) { ... }'
func: used for defining a user-defined function.
Example: 'func f(a,b) { return sqrt(a**2+b**2)} $d = f($x, $y)'
funct: used for saying that a function argument is a user-defined function.
Example: 'func g(num a, num b, funct f) :num { return f(a**2+b**2) }'
if: starts an if/elif/elif chain. The body statements must be wrapped
in curly braces.
in: used in for-loops over stream records or out-of-stream variables.
int: declares an integer local variable in the current curly-braced scope.
Type-checking happens at assignment: 'int x = 0.0' is an error.
map: declares an map-valued local variable in the current curly-braced scope.
Type-checking happens at assignment: 'map b = 0' is an error. map b = {} is
always OK. map b = a is OK or not depending on whether a is a map.
num: declares an int/float local variable in the current curly-braced scope.
Type-checking happens at assignment: 'num b = true' is an error.
print: prints expression immediately to stdout.
Example: mlr --from f.dat put -q 'print "The sum of x and y is ".($x+$y)'
Example: mlr --from f.dat put -q 'for (k, v in $*) { print k . " => " . v }'
Example: mlr --from f.dat put '(NR % 1000 == 0) { print > stderr, "Checkpoint ".NR}'
printn: prints expression immediately to stdout, without trailing newline.
Example: mlr --from f.dat put -q 'printn "."; end { print "" }'
return: specifies the return value from a user-defined function.
Omitted return statements (including via if-branches) result in an absent-null
return value, which in turns results in a skipped assignment to an LHS.
stderr: Used for tee, emit, emitf, emitp, print, and dump in place of filename
to print to standard error.
stdout: Used for tee, emit, emitf, emitp, print, and dump in place of filename
to print to standard output.
str: declares a string local variable in the current curly-braced scope.
Type-checking happens at assignment.
subr: used for defining a subroutine.
Example: 'subr s(k,v) { print k . " is " . v} call s("a", $a)'
tee: prints the current record to specified file.
This is an immediate print to the specified file (except for pprint format
which of course waits until the end of the input stream to format all output).
The > and >> are for write and append, as in the shell, but (as with awk) the
file-overwrite for > is on first write, not per record. The | is for piping to
a process which will process the data. There will be one open file for each
distinct file name (for > and >>) or one subordinate process for each distinct
value of the piped-to command (for |). Output-formatting flags are taken from
the main command line.
You can use any of the output-format command-line flags, e.g. --ocsv, --ofs,
etc., to control the format of the output. See also mlr -h.
emit with redirect and tee with redirect are identical, except tee can only
output $*.
Example: mlr --from f.dat put 'tee > "/tmp/data-".$a, $*'
Example: mlr --from f.dat put 'tee >> "/tmp/data-".$a.$b, $*'
Example: mlr --from f.dat put 'tee > stderr, $*'
Example: mlr --from f.dat put -q 'tee | "tr \[a-z\\] \[A-Z\\]", $*'
Example: mlr --from f.dat put -q 'tee | "tr \[a-z\\] \[A-Z\\] > /tmp/data-".$a, $*'
Example: mlr --from f.dat put -q 'tee | "gzip > /tmp/data-".$a.".gz", $*'
Example: mlr --from f.dat put -q --ojson 'tee | "gzip > /tmp/data-".$a.".gz", $*'
true: the boolean literal value.
unset: clears field(s) from the current record, or an out-of-stream or local variable.
Example: mlr --from f.dat put 'unset $x'
Example: mlr --from f.dat put 'unset $*'
Example: mlr --from f.dat put 'for (k, v in $*) { if (k =~ "a.*") { unset $[k] } }'
Example: mlr --from f.dat put '...; unset @sums'
Example: mlr --from f.dat put '...; unset @sums["green"]'
Example: mlr --from f.dat put '...; unset @*'
var: declares an untyped local variable in the current curly-braced scope.
Examples: 'var a=1', 'var xyz=""'
while: introduces a while loop, or with "do", introduces a do-while loop.
The body statements must be wrapped in curly braces.
ENV: access to environment variables by name, e.g. '$home = ENV["HOME"]'
FILENAME: evaluates to the name of the current file being processed.
FILENUM: evaluates to the number of the current file being processed,
starting with 1.
FNR: evaluates to the number of the current record within the current file
being processed, starting with 1. Resets at the start of each file.
IFS: evaluates to the input field separator from the command line.
IPS: evaluates to the input pair separator from the command line.
IRS: evaluates to the input record separator from the command line,
or to LF or CRLF from the input data if in autodetect mode (which is
the default).
M_E: the mathematical constant e.
M_PI: the mathematical constant pi.
NF: evaluates to the number of fields in the current record.
NR: evaluates to the number of the current record over all files
being processed, starting with 1. Does not reset at the start of each file.
OFS: evaluates to the output field separator from the command line.
OPS: evaluates to the output pair separator from the command line.
ORS: evaluates to the output record separator from the command line,
or to LF or CRLF from the input data if in autodetect mode (which is
the default).