Operators

Nextflow operators are methods that allow you to connect channels to each other or to transform values emitted by a channel applying some user provided rules.

Operators can be separated in to seven groups:

Note

The operators set and operator-subscribe are terminal operators and therefore need to be the last operator in a chain of combined operators.

Filtering operators

Given a channel, filtering operators allow you to select only the items that comply with a given rule.

The available filter operators are:

filter

The filter operator allows you to get only the items emitted by a channel that satisfy a condition and discarding all the others. The filtering condition can be specified by using either a regular expression, a literal value, a type qualifier (i.e. a Java class) or any boolean predicate.

The following example shows how to filter a channel by using a regular expression that returns only string that begins with a:

Channel
    .from( 'a', 'b', 'aa', 'bc', 3, 4.5 )
    .filter( ~/^a.*/ )
    .view()
a
aa

The following example shows how to filter a channel by specifying the type qualifier Number so that only numbers are returned:

Channel
    .from( 'a', 'b', 'aa', 'bc', 3, 4.5 )
    .filter( Number )
    .view()
3
4.5

Finally, a filtering condition can be defined by using any a boolean predicate. A predicate is expressed by a closure returning a boolean value. For example the following fragment shows how filter a channel emitting numbers so that the odd values are returned:

Channel
    .from( 1, 2, 3, 4, 5 )
    .filter { it % 2 == 1 }
    .view()
1
3
5

Tip

In the above example the filter condition is wrapped in curly brackets, instead of round brackets, since it specifies a closure as the operator’s argument. This just is a language syntax-sugar for filter({ it.toString().size() == 1 })

unique

The unique operator allows you to remove duplicate items from a channel and only emit single items with no repetition.

For example:

Channel
    .from( 1,1,1,5,7,7,7,3,3 )
    .unique()
    .view()
1
5
7
3

You can also specify an optional closure that customizes the way it distinguishes between unique items. For example:

Channel
    .from(1,3,4,5)
    .unique { it % 2 }
    .view()
1
4

distinct

The distinct operator allows you to remove consecutive duplicated items from a channel, so that each emitted item is different from the preceding one. For example:

Channel
    .from( 1,1,2,2,2,3,1,1,2,2,3 )
    .distinct()
    .subscribe onNext: { println it }, onComplete: { println 'Done' }
1
2
3
1
2
3
Done

You can also specify an optional closure that customizes the way it distinguishes between distinct items. For example:

Channel
    .from( 1,1,2,2,2,3,1,1,2,4,6 )
    .distinct { it % 2 }
    .subscribe onNext: { println it }, onComplete: { println 'Done' }
1
2
3
2
Done

first

The first operator creates a channel that returns the first item emitted by the source channel, or eventually the first item that matches an optional condition. The condition can be specified by using a regular expression, a Java class type or any boolean predicate. For example:

// no condition is specified, emits the very first item: 1
Channel
    .from( 1, 2, 3 )
    .first()
    .view()


// emits the first String value: 'a'
Channel
    .from( 1, 2, 'a', 'b', 3 )
    .first( String )
    .view()

// emits the first item matching the regular expression: 'aa'
Channel
    .from( 'a', 'aa', 'aaa' )
    .first( ~/aa.*/ )
    .view()

// emits the first item for which the predicate evaluates to true: 4
Channel
    .from( 1,2,3,4,5 )
    .first { it > 3 }
    .view()

randomSample

The randomSample operator allows you to create a channel emitting the specified number of items randomly taken from the channel to which is applied. For example:

Channel
      .from( 1..100 )
      .randomSample( 10 )
      .view()

The above snippet will print 10 numbers in the range from 1 to 100.

The operator supports a second parameter that allows to set the initial seed for the random number generator. By setting it, the randomSample operator will always return the same pseudo-random sequence. For example:

Channel
      .from( 1..100 )
      .randomSample( 10, 234 )
      .view()

The above example will print 10 random numbers in the range between 1 and 100. At each run of the script, the same sequence will be returned.

take

The take operator allows you to filter only the first n items emitted by a channel. For example:

Channel
    .from( 1,2,3,4,5,6 )
    .take( 3 )
    .subscribe onNext: { println it }, onComplete: { println 'Done' }
1
2
3
Done

Note

By specifying the value -1 the operator takes all values.

See also until.

last

The last operator creates a channel that only returns the last item emitted by the source channel. For example:

Channel
    .from( 1,2,3,4,5,6 )
    .last()
    .view()
6

until

The until operator creates a channel that returns the items emitted by the source channel and stop when the condition specified is verified. For example:

Channel
    .from( 3,2,1,5,1,5 )
    .until{ it==5 }
    .view()
3
2
1

See also take.

Transforming operators

Transforming operators are used to transform the items emitted by a channel to new values.

These operators are:

map

The map operator applies a function of your choosing to every item emitted by a channel, and returns the items so obtained as a new channel. The function applied is called the mapping function and is expressed with a closure as shown in the example below:

Channel
    .from( 1, 2, 3, 4, 5 )
    .map { it * it }
    .subscribe onNext: { println it }, onComplete: { println 'Done' }
1
4
9
16
25
Done

flatMap

The flatMap operator applies a function of your choosing to every item emitted by a channel, and returns the items so obtained as a new channel. Whenever the mapping function returns a list of items, this list is flattened so that each single item is emitted on its own.

For example:

// create a channel of numbers
numbers = Channel.from( 1, 2, 3 )

// map each number to a tuple (array), which items are emitted separately
results = numbers.flatMap { n -> [ n*2, n*3 ] }

// print the final results
results.subscribe onNext: { println it }, onComplete: { println 'Done' }
2
3
4
6
6
9
Done

Associative arrays are handled in the same way, so that each array entry is emitted as a single key-value item. For example:

Channel.from ( 1, 2, 3 )
       .flatMap { it -> [ number: it, square: it*it ] }
       .view { it.key + ': ' + it.value }
number: 1
square: 1
number: 2
square: 4
number: 3
square: 9

reduce

The reduce operator applies a function of your choosing to every item emitted by a channel. Each time this function is invoked it takes two parameters: firstly the i-th emitted item and secondly the result of the previous invocation of the function itself. The result is passed on to the next function call, along with the i+1 th item, until all the items are processed.

Finally, the reduce operator emits the result of the last invocation of your function as the sole output.

For example:

Channel
    .from( 1, 2, 3, 4, 5 )
    .reduce { a, b -> println "a: $a b: $b"; return a+b }
    .view { "result = $it" }

It prints the following output:

a: 1    b: 2
a: 3    b: 3
a: 6    b: 4
a: 10   b: 5
result = 15

Note

In a common usage scenario the first function parameter is used as an accumulator and the second parameter represents the i-th item to be processed.

Optionally you can specify a seed value in order to initialise the accumulator parameter as shown below:

myChannel.reduce( seedValue ) {  a, b -> ... }

groupBy

Warning

This operator is deprecated. Use the groupTuple operator instead.

The groupBy operator collects the values emitted by the source channel grouping them together using a mapping function that associates each item with a key. When finished, it emits an associative array that maps each key to the set of items identified by that key.

For example:

Channel
    .from('hello','ciao','hola', 'hi', 'bonjour')
    .groupBy { String str -> str[0] }
    .view()
[ b:['bonjour'], c:['ciao'], h:['hello','hola','hi'] ]

The mapping function is an optional parameter. When omitted the values are grouped following these rules:

  • Any value of type Map is associated with the value of its first entry, or null when the map itself is empty.

  • Any value of type Map.Entry is associated with the value of its key attribute.

  • Any value of type Collection or Array is associated with its first entry.

  • For any other value, the value itself is used as a key.

groupTuple

The groupTuple operator collects tuples (or lists) of values emitted by the source channel grouping together the elements that share the same key. Finally it emits a new tuple object for each distinct key collected.

In other words transform a sequence of tuple like (K, V, W, ..) into a new channel emitting a sequence of (K, list(V), list(W), ..)

For example:

Channel
     .from( [1,'A'], [1,'B'], [2,'C'], [3, 'B'], [1,'C'], [2, 'A'], [3, 'D'] )
     .groupTuple()
     .view()

It prints:

[1, [A, B, C]]
[2, [C, A]]
[3, [B, D]]

By default the first entry in the tuple is used a the grouping key. A different key can be chosen by using the by parameter and specifying the index of entry to be used as key (the index is zero-based). For example:

Channel
     .from( [1,'A'], [1,'B'], [2,'C'], [3, 'B'], [1,'C'], [2, 'A'], [3, 'D'] )
     .groupTuple(by: 1)
     .view()

Grouping by the second value in each tuple the result is:

[[1, 2], A]
[[1, 3], B]
[[2, 1], C]
[[3], D]

Available parameters:

Field

Description

by

The index (zero based) of the element to be used as grouping key. A key composed by multiple elements can be defined specifying a list of indices e.g. by: [0,2]

sort

Defines the sorting criteria for the grouped items. See below for available sorting options.

size

The number of items the grouped list(s) has to contain. When the specified size is reached, the tuple is emitted.

remainder

When false incomplete tuples (i.e. with less than size grouped items) are discarded (default). When true incomplete tuples are emitted as the ending emission. Only valid when a size parameter is specified.

Sorting options:

Sort

Description

false

No sorting is applied (default).

true

Order the grouped items by the item natural ordering i.e. numerical for number, lexicographic for string, etc. See http://docs.oracle.com/javase/tutorial/collections/interfaces/order.html

hash

Order the grouped items by the hash number associated to each entry.

deep

Similar to the previous, but the hash number is created on actual entries content e.g. when the item is a file the hash is created on the actual file content.

custom

A custom sorting criteria used to order the tuples element holding list of values. It can be specified by using either a Closure or a Comparator object.

Tip

You should always specify the number of expected element in each tuple using the size attribute to allow the groupTuple operator to stream the collected values as soon as possible. However there are use cases in which each tuple has a different size depending grouping key. In this cases use the built-in function groupKey that allows you to create a special grouping key object to which it’s possible to associate the group size for a given key.

buffer

The buffer operator gathers the items emitted by the source channel into subsets and emits these subsets separately.

There are a number of ways you can regulate how buffer gathers the items from the source channel into subsets:

  • buffer( closingCondition ): starts to collect the items emitted by the channel into a subset until the closing condition is verified. After that the subset is emitted to the resulting channel and new items are gathered into a new subset. The process is repeated until the last value in the source channel is sent. The closingCondition can be specified either as a regular expression, a Java class, a literal value, or a boolean predicate that has to be satisfied. For example:

    Channel
        .from( 1,2,3,1,2,3 )
        .buffer { it == 2 }
        .view()
    
    // emitted values
    [1,2]
    [3,1,2]
    
  • buffer( openingCondition, closingCondition ): starts to gather the items emitted by the channel as soon as one of the them verify the opening condition and it continues until there is one item which verify the closing condition. After that the subset is emitted and it continues applying the described logic until the last channel item is emitted. Both conditions can be defined either as a regular expression, a literal value, a Java class, or a boolean predicate that need to be satisfied. For example:

    Channel
        .from( 1,2,3,4,5,1,2,3,4,5,1,2 )
        .buffer( 2, 4 )
        .view()
    
    // emits bundles starting with '2' and ending with'4'
    [2,3,4]
    [2,3,4]
    
  • buffer( size: n ): transform the source channel in such a way that it emits tuples made up of n elements. An incomplete tuple is discarded. For example:

    Channel
        .from( 1,2,3,1,2,3,1 )
        .buffer( size: 2 )
        .view()
    
    // emitted values
    [1, 2]
    [3, 1]
    [2, 3]
    

If you want to emit the last items in a tuple containing less than n elements, simply add the parameter remainder specifying true, for example:

Channel
    .from( 1,2,3,1,2,3,1 )
    .buffer( size: 2, remainder: true )
    .view()

// emitted values
[1, 2]
[3, 1]
[2, 3]
[1]
  • buffer( size: n, skip: m ): as in the previous example, it emits tuples containing n elements, but skips m values before starting to collect the values for the next tuple (including the first emission). For example:

    Channel
        .from( 1,2,3,4,5,1,2,3,4,5,1,2 )
        .buffer( size:3, skip:2 )
        .view()
    
    // emitted values
    [3, 4, 5]
    [3, 4, 5]
    

If you want to emit the remaining items in a tuple containing less than n elements, simply add the parameter remainder specifying true, as shown in the previous example.

See also: collate operator.

collate

The collate operator transforms a channel in such a way that the emitted values are grouped in tuples containing n items. For example:

Channel
    .from(1,2,3,1,2,3,1)
    .collate( 3 )
    .view()
[1, 2, 3]
[1, 2, 3]
[1]

As shown in the above example the last tuple may be incomplete e.g. contain less elements than the specified size. If you want to avoid this, specify false as the second parameter. For example:

Channel
    .from(1,2,3,1,2,3,1)
    .collate( 3, false )
    .view()
[1, 2, 3]
[1, 2, 3]

A second version of the collate operator allows you to specify, after the size, the step by which elements are collected in tuples. For example:

Channel
  .from(1,2,3,4)
  .collate( 3, 1 )
  .view()
[1, 2, 3]
[2, 3, 4]
[3, 4]
[4]

As before, if you don’t want to emit the last items which do not complete a tuple, specify false as the third parameter.

See also: buffer operator.

collect

The collect operator collects all the items emitted by a channel to a List and return the resulting object as a sole emission. For example:

Channel
    .from( 1, 2, 3, 4 )
    .collect()
    .view()

# outputs
[1,2,3,4]

An optional closure can be specified to transform each item before adding it to the resulting list. For example:

Channel
    .from( 'hello', 'ciao', 'bonjour' )
    .collect { it.length() }
    .view()

# outputs
[5,4,7]

See also: toList and toSortedList operator.

flatten

The flatten operator transforms a channel in such a way that every item of type Collection or Array is flattened so that each single entry is emitted separately by the resulting channel. For example:

Channel
    .from( [1,[2,3]], 4, [5,[6]] )
    .flatten()
    .view()
1
2
3
4
5
6

See also: flatMap operator.

toList

The toList operator collects all the items emitted by a channel to a List object and emits the resulting collection as a single item. For example:

Channel
    .from( 1, 2, 3, 4 )
    .toList()
    .subscribe onNext: { println it }, onComplete: 'Done'
[1,2,3,4]
Done

See also: collect operator.

toSortedList

The toSortedList operator collects all the items emitted by a channel to a List object where they are sorted and emits the resulting collection as a single item. For example:

Channel
    .from( 3, 2, 1, 4 )
    .toSortedList()
    .subscribe onNext: { println it }, onComplete: 'Done'
[1,2,3,4]
Done

You may also pass a comparator closure as an argument to the toSortedList operator to customize the sorting criteria. For example, to sort by the second element of a tuple in descending order:

Channel
    .from( ["homer", 5], ["bart", 2], ["lisa", 10], ["marge", 3], ["maggie", 7])
    .toSortedList( { a, b -> b[1] <=> a[1] } )
    .view()
[[lisa, 10], [maggie, 7], [homer, 5], [marge, 3], [bart, 2]]

See also: collect operator.

transpose

The transpose operator transforms a channel in such a way that the emitted items are the result of a transposition of all tuple elements in each item. For example:

Channel.from([
   ['a', ['p', 'q'], ['u','v'] ],
   ['b', ['s', 't'], ['x','y'] ]
   ])
   .transpose()
   .view()

The above snippet prints:

[a, p, u]
[a, q, v]
[b, s, x]
[b, t, y]

Available parameters:

Field

Description

by

The index (zero based) of the element to be transposed. Multiple elements can be defined specifying as list of indices e.g. by: [0,2]

remainder

When false incomplete tuples are discarded (default). When true incomplete tuples are emitted containing a null in place of a missing element.

Splitting operators

These operators are used to split items emitted by channels into chunks that can be processed by downstream operators or processes.

The available splitting operators are:

splitCsv

The splitCsv operator allows you to parse text items emitted by a channel, that are formatted using the CSV format, and split them into records or group them into list of records with a specified length.

In the simplest case just apply the splitCsv operator to a channel emitting a CSV formatted text files or text entries. For example:

Channel
    .from( 'alpha,beta,gamma\n10,20,30\n70,80,90' )
    .splitCsv()
    .view { row -> "${row[0]} - ${row[1]} - ${row[2]}" }

The above example shows hows CSV text is parsed and is split into single rows. Values can be accessed by its column index in the row object.

When the CSV begins with a header line defining the columns names, you can specify the parameter header: true which allows you to reference each value by its name, as shown in the following example:

Channel
    .from( 'alpha,beta,gamma\n10,20,30\n70,80,90' )
    .splitCsv(header: true)
    .view { row -> "${row.alpha} - ${row.beta} - ${row.gamma}" }

It will print

10 - 20 - 30
70 - 80 - 90

Alternatively you can provide custom header names by specifying a the list of strings in the header parameter as shown below:

Channel
    .from( 'alpha,beta,gamma\n10,20,30\n70,80,90' )
    .splitCsv(header: ['col1', 'col2', 'col3'], skip: 1 )
    .view { row -> "${row.col1} - ${row.col2} - ${row.col3}" }

Available parameters:

Field

Description

by

The number of rows in each chunk

sep

The character used to separate the values (default: ,)

quote

Values may be quoted by single or double quote characters.

header

When true the first line is used as columns names. Alternatively it can be used to provide the list of columns names.

charset

Parse the content by using the specified charset e.g. UTF-8

strip

Removes leading and trailing blanks from values (default: false)

skip

Number of lines since the file beginning to ignore when parsing the CSV content.

limit

Limits the number of retrieved records for each file to the specified value.

decompress

When true decompress the content using the GZIP format before processing it (note: files whose name ends with .gz extension are decompressed automatically)

elem

The index of the element to split when the operator is applied to a channel emitting list/tuple objects (default: first file object or first element)

splitFasta

The splitFasta operator allows you to split the entries emitted by a channel, that are formatted using the FASTA format. It returns a channel which emits text item for each sequence in the received FASTA content.

The number of sequences in each text chunk produced by the splitFasta operator can be set by using the by parameter. The following example shows how to read a FASTA file and split it into chunks containing 10 sequences each:

Channel
     .fromPath('misc/sample.fa')
     .splitFasta( by: 10 )
     .view()

Warning

By default chunks are kept in memory. When splitting big files specify the parameter file: true to save the chunks into files in order to not incur in a OutOfMemoryException. See the available parameter table below for details.

A second version of the splitFasta operator allows you to split a FASTA content into record objects, instead of text chunks. A record object contains a set of fields that let you access and manipulate the FASTA sequence information with ease.

In order to split a FASTA content into record objects, simply use the record parameter specifying the map of required the fields, as shown in the example below:

Channel
     .fromPath('misc/sample.fa')
     .splitFasta( record: [id: true, seqString: true ])
     .filter { record -> record.id =~ /^ENST0.*/ }
     .view { record -> record.seqString }

Note

In this example, the file misc/sample.fa is split into records containing the id and the seqString fields (i.e. the sequence id and the sequence data). The following filter operator only keeps the sequences which ID starts with the ENST0 prefix, finally the sequence content is printed by using the subscribe operator.

Available parameters:

Field

Description

by

Defines the number of sequences in each chunk (default: 1)

size

Defines the size in memory units of the expected chunks eg. 1.MB.

limit

Limits the number of retrieved sequences for each file to the specified value.

record

Parse each entry in the FASTA file as record objects (see following table for accepted values)

charset

Parse the content by using the specified charset e.g. UTF-8

compress

When true resulting file chunks are GZIP compressed. The .gz suffix is automatically added to chunk file names.

decompress

When true, decompress the content using the GZIP format before processing it (note: files whose name ends with .gz extension are decompressed automatically)

file

When true saves each split to a file. Use a string instead of true value to create split files with a specific name (split index number is automatically added). Finally, set this attribute to an existing directory, in order to save the split files into the specified folder.

elem

The index of the element to split when the operator is applied to a channel emitting list/tuple objects (default: first file object or first element)

The following fields are available when using the record parameter:

Field

Description

id

The FASTA sequence identifier i.e. the word following the > symbol up to the first blank or newline character

header

The first line in a FASTA sequence without the > character

desc

The text in the FASTA header following the ID value

text

The complete FASTA sequence including the header

seqString

The sequence data as a single line string i.e. containing no newline characters

sequence

The sequence data as a multi-line string (always ending with a newline character)

width

Define the length of a single line when the sequence field is used, after that the sequence data continues on a new line.

splitFastq

The splitFastq operator allows you to split the entries emitted by a channel, that are formatted using the FASTQ format. It returns a channel which emits a text chunk for each sequence in the received item.

The number of sequences in each text chunk produced by the splitFastq operator is defined by the parameter by. The following example shows you how to read a FASTQ file and split it into chunks containing 10 sequences each:

Channel
     .fromPath('misc/sample.fastq')
     .splitFastq( by: 10 )
     .view()

Warning

By default chunks are kept in memory. When splitting big files specify the parameter file: true to save the chunks into files in order to not incur in a OutOfMemoryException. See the available parameter table below for details.

A second version of the splitFastq operator allows you to split a FASTQ formatted content into record objects, instead of text chunks. A record object contains a set of fields that let you access and manipulate the FASTQ sequence data with ease.

In order to split FASTQ sequences into record objects simply use the record parameter specifying the map of the required fields, or just specify record: true as in the example shown below:

Channel
     .fromPath('misc/sample.fastq')
     .splitFastq( record: true )
     .view { record -> record.readHeader }

Finally the splitFastq operator is able to split paired-end read pair FASTQ files. It must be applied to a channel which emits tuples containing at least two elements that are the files to be splitted. For example:

Channel
    .fromFilePairs('/my/data/SRR*_{1,2}.fastq', flat:true)
    .splitFastq(by: 100_000, pe:true, file:true)
    .view()

Note

The fromFilePairs requires the flat:true option to have the file pairs as separate elements in the produced tuples.

Warning

This operator assumes that the order of the PE reads correspond with each other and both files contain the same number of reads.

Available parameters:

Field

Description

by

Defines the number of reads in each chunk (default: 1)

pe

When true splits paired-end read files, therefore items emitted by the source channel must be tuples in which at least two elements are the read-pair files to be splitted.

limit

Limits the number of retrieved reads for each file to the specified value.

record

Parse each entry in the FASTQ file as record objects (see following table for accepted values)

charset

Parse the content by using the specified charset e.g. UTF-8

compress

When true resulting file chunks are GZIP compressed. The .gz suffix is automatically added to chunk file names.

decompress

When true decompress the content using the GZIP format before processing it (note: files whose name ends with .gz extension are decompressed automatically)

file

When true saves each split to a file. Use a string instead of true value to create split files with a specific name (split index number is automatically added). Finally, set this attribute to an existing directory, in order to save the split files into the specified folder.

elem

The index of the element to split when the operator is applied to a channel emitting list/tuple objects (default: first file object or first element)

The following fields are available when using the record parameter:

Field

Description

readHeader

Sequence header (without the @ prefix)

readString

The raw sequence data

qualityHeader

Base quality header (it may be empty)

qualityString

Quality values for the sequence

splitText

The splitText operator allows you to split multi-line strings or text file items, emitted by a source channel into chunks containing n lines, which will be emitted by the resulting channel.

For example:

Channel
     .fromPath('/some/path/*.txt')
     .splitText()
     .view()

It splits the content of the files with suffix .txt, and prints it line by line.

By default the splitText operator splits each item into chunks of one line. You can define the number of lines in each chunk by using the parameter by, as shown in the following example:

Channel
     .fromPath('/some/path/*.txt')
     .splitText( by: 10 )
     .subscribe {
         print it;
         print "--- end of the chunk ---\n"
     }

An optional closure can be specified in order to transform the text chunks produced by the operator. The following example shows how to split text files into chunks of 10 lines and transform them to capital letters:

Channel
   .fromPath('/some/path/*.txt')
   .splitText( by: 10 ) { it.toUpperCase() }
   .view()

Note

Text chunks returned by the operator splitText are always terminated by a newline character.

Available parameters:

Field

Description

by

Defines the number of lines in each chunk (default: 1).

limit

Limits the number of retrieved lines for each file to the specified value.

charset

Parse the content by using the specified charset e.g. UTF-8.

compress

When true resulting file chunks are GZIP compressed. The .gz suffix is automatically added to chunk file names.

decompress

When true, decompress the content using the GZIP format before processing it (note: files whose name ends with .gz extension are decompressed automatically).

file

When true saves each split to a file. Use a string instead of true value to create split files with a specific name (split index number is automatically added). Finally, set this attribute to an existing directory, in oder to save the split files into the specified folder.

elem

The index of the element to split when the operator is applied to a channel emitting list/tuple objects (default: first file object or first element).

keepHeader

Parses the first line as header and prepends it to each emitted chunk.

Combining operators

The combining operators are:

join

The join operator creates a channel that joins together the items emitted by two channels for which exits a matching key. The key is defined, by default, as the first element in each item emitted.

For example:

left = Channel.from(['X', 1], ['Y', 2], ['Z', 3], ['P', 7])
right= Channel.from(['Z', 6], ['Y', 5], ['X', 4])
left.join(right).view()

The resulting channel emits:

[Z, 3, 6]
[Y, 2, 5]
[X, 1, 4]

The index of a different matching element can be specified by using the by parameter.

The join operator can emit all the pairs that are incomplete, i.e. the items for which a matching element is missing, by specifying the optional parameter remainder as shown below:

left = Channel.from(['X', 1], ['Y', 2], ['Z', 3], ['P', 7])
right= Channel.from(['Z', 6], ['Y', 5], ['X', 4])
left.join(right, remainder: true).view()

The above example prints:

[Y, 2, 5]
[Z, 3, 6]
[X, 1, 4]
[P, 7, null]

The following parameters can be used with the join operator:

Name

Description

by

The index (zero based) of the element to be used as grouping key. A key composed by multiple elements can be defined specifying a list of indices e.g. by: [0,2]

remainder

When false incomplete tuples (i.e. with less than size grouped items) are discarded (default). When true incomplete tuples are emitted as the ending emission.

failOnDuplicate

An error is reported when the same key is found more than once.

failOnMismatch

An error is reported when a channel emits a value for which there isn’t a corresponding element in the joining channel. This option cannot be used with remainder.

merge

Warning

This operator is deprecated and it will be removed in upcoming release.

The merge operator lets you join items emitted by two (or more) channels into a new channel.

For example the following code merges two channels together, one which emits a series of odd integers and the other which emits a series of even integers:

odds  = Channel.from([1, 3, 5, 7, 9]);
evens = Channel.from([2, 4, 6]);

odds
    .merge( evens )
    .view()
[1, 2]
[3, 4]
[5, 6]

An option closure can be provide to customise the items emitted by the resulting merged channel. For example:

odds  = Channel.from([1, 3, 5, 7, 9]);
evens = Channel.from([2, 4, 6]);

odds
    .merge( evens ) { a, b -> tuple(b*b, a) }
    .view()

mix

The mix operator combines the items emitted by two (or more) channels into a single channel.

For example:

c1 = Channel.from( 1,2,3 )
c2 = Channel.from( 'a','b' )
c3 = Channel.from( 'z' )

c1 .mix(c2,c3)
   .subscribe onNext: { println it }, onComplete: { println 'Done' }
1
2
3
'a'
'b'
'z'

Note

The items emitted by the resulting mixed channel may appear in any order, regardless of which source channel they came from. Thus, the following example it could be a possible result of the above example as well.

'z'
1
'a'
2
'b'
3

phase

Warning

This operator is deprecated. Use the join operator instead.

The phase operator creates a channel that synchronizes the values emitted by two other channels, in such a way that it emits pairs of items that have a matching key.

The key is defined, by default, as the first entry in an array, a list or map object, or the value itself for any other data type.

For example:

ch1 = Channel.from( 1,2,3 )
ch2 = Channel.from( 1,0,0,2,7,8,9,3 )
ch1 .phase(ch2) .view()

It prints:

[1,1]
[2,2]
[3,3]

Optionally, a mapping function can be specified in order to provide a custom rule to associate an item to a key, as shown in the following example:

ch1 = Channel.from( [sequence: 'aaaaaa', id: 1], [sequence: 'bbbbbb', id: 2] )
ch2 = Channel.from( [val: 'zzzz', id: 3], [val: 'xxxxx', id: 1], [val: 'yyyyy', id: 2])
ch1 .phase(ch2) { it -> it.id } .view()

It prints:

[[sequence:aaaaaa, id:1], [val:xxxxx, id:1]]
[[sequence:bbbbbb, id:2], [val:yyyyy, id:2]]

Finally, the phase operator can emit all the pairs that are incomplete, i.e. the items for which a matching element is missing, by specifying the optional parameter remainder as shown below:

ch1 = Channel.from( 1,0,0,2,5,3 )
ch2 = Channel.from( 1,2,3,4 )
ch1 .phase(ch2, remainder: true) .view()

It prints:

[1, 1]
[2, 2]
[3, 3]
[0, null]
[0, null]
[5, null]
[null, 4]

See also join operator.

cross

The cross operators allows you to combine the items of two channels in such a way that the items of the source channel are emitted along with the items emitted by the target channel for which they have a matching key.

The key is defined, by default, as the first entry in an array, a list or map object, or the value itself for any other data type. For example:

source = Channel.from( [1, 'alpha'], [2, 'beta'] )
target = Channel.from( [1, 'x'], [1, 'y'], [1, 'z'], [2,'p'], [2,'q'], [2,'t'] )

source.cross(target).view()

It will output:

[ [1, alpha], [1, x] ]
[ [1, alpha], [1, y] ]
[ [1, alpha], [1, z] ]
[ [2, beta],  [2, p] ]
[ [2, beta],  [2, q] ]
[ [2, beta],  [2, t] ]

The above example shows how the items emitted by the source channels are associated to the ones emitted by the target channel (on the right) having the same key.

There are two important caveats when using the cross operator:

  1. The operator is not reflexive, i.e. the result of a.cross(b) is different from b.cross(a)

  2. The source channel should emits items for which there’s no key repetition i.e. the emitted items have an unique key identifier.

Optionally, a mapping function can be specified in order to provide a custom rule to associate an item to a key, in a similar manner as shown for the phase operator.

collectFile

The collectFile operator allows you to gather the items emitted by a channel and save them to one or more files. The operator returns a new channel that emits the collected file(s).

In the simplest case, just specify the name of a file where the entries have to be stored. For example:

Channel
    .from('alpha', 'beta', 'gamma')
    .collectFile(name: 'sample.txt', newLine: true)
    .subscribe {
        println "Entries are saved to file: $it"
        println "File content is: ${it.text}"
    }

A second version of the collectFile operator allows you to gather the items emitted by a channel and group them together into files whose name can be defined by a dynamic criteria. The grouping criteria is specified by a closure that must return a pair in which the first element defines the file name for the group and the second element the actual value to be appended to that file. For example:

Channel
   .from('Hola', 'Ciao', 'Hello', 'Bonjour', 'Halo')
   .collectFile() { item ->
       [ "${item[0]}.txt", item + '\n' ]
   }
   .subscribe {
       println "File ${it.name} contains:"
       println it.text
   }

It will print:

File 'B.txt' contains:
Bonjour

File 'C.txt' contains:
Ciao

File 'H.txt' contains:
Halo
Hola
Hello

Tip

When the items emitted by the source channel are files, the grouping criteria can be omitted. In this case the items content will be grouped in file(s) having the same name as the source items.

The following parameters can be used with the collectFile operator:

Name

Description

keepHeader

Prepend the resulting file with the header fetched in the first collected file. The header size (ie. lines) can be specified by using the skip parameter (default: false), to determine how many lines to remove from all collected files except for the first (where no lines will be removed).

name

Name of the file where all received values are stored.

newLine

Appends a newline character automatically after each entry (default: false).

seed

A value or a map of values used to initialise the files content.

skip

Skip the first n lines eg. skip: 1.

sort

Defines sorting criteria of content in resulting file(s). See below for sorting options.

storeDir

Folder where the resulting file(s) are be stored.

tempDir

Folder where temporary files, used by the collecting process, are stored.

Note

The file content is sorted in such a way that it does not depend on the order on which entries have been added to it, this guarantees that it is consistent (i.e. do not change) across different executions with the same data.

The ordering of file’s content can be defined by using the sort parameter. The following criteria can be specified:

Sort

Description

false

Disable content sorting. Entries are appended as they are produced.

true

Order the content by the entries natural ordering i.e. numerical for number, lexicographic for string, etc. See http://docs.oracle.com/javase/tutorial/collections/interfaces/order.html

'index'

Order the content by the incremental index number assigned to each entry while they are collected.

'hash'

Order the content by the hash number associated to each entry (default)

'deep'

Similar to the previous, but the hash number is created on actual entries content e.g. when the entry is a file the hash is created on the actual file content.

custom

A custom sorting criteria can be specified by using either a Closure or a Comparator object.

For example the following snippet shows how sort the content of the result file alphabetically:

Channel
   .from('Z'..'A')
   .collectFile(name:'result', sort: true, newLine: true)
   .view { it.text }

It will print:

A
B
C
:
Z

The following example shows how use a closure to collect and sort all sequences in a FASTA file from shortest to longest:

Channel
     .fromPath('/data/sequences.fa')
     .splitFasta( record: [id: true, sequence: true] )
     .collectFile( name:'result.fa', sort: { it.size() } )  {
        it.sequence
      }
     .view { it.text }

Warning

The collectFile operator to carry out its function need to store in a temporary folder that is automatically deleted on job completion. For performance reason this folder is allocated in the machine local storage, and it will require as much free space as are the data you are collecting. Optionally, an alternative temporary data folder can be specified by using the tempDir parameter.

combine

The combine operator combines (cartesian product) the items emitted by two channels or by a channel and a Collection object (as right operand). For example:

numbers = Channel.from(1,2,3)
words = Channel.from('hello', 'ciao')
numbers
    .combine(words)
    .view()

# outputs
[1, hello]
[2, hello]
[3, hello]
[1, ciao]
[2, ciao]
[3, ciao]

A second version of the combine operator allows you to combine between them those items that share a common matching key. The index of the key element is specified by using the by parameter (the index is zero-based, multiple indexes can be specified with list a integers). For example:

left = Channel.from(['A',1], ['B',2], ['A',3])
right = Channel.from(['B','x'], ['B','y'], ['A','z'], ['A', 'w'])

left
    .combine(right, by: 0)
    .view()

# outputs
[A, 1, z]
[A, 3, z]
[A, 1, w]
[A, 3, w]
[B, 2, x]
[B, 2, y]

See also join, cross, spread and phase.

concat

The concat operator allows you to concatenate the items emitted by two or more channels to a new channel, in such a way that the items emitted by the resulting channel are in same order as they were when specified as operator arguments.

In other words it guarantees that given any n channels, the concatenation channel emits the items proceeding from the channel i+1 th only after all the items proceeding from the channel i th were emitted.

For example:

a = Channel.from('a','b','c')
b = Channel.from(1,2,3)
c = Channel.from('p','q')

c.concat( b, a ).view()

It will output:

p
q
1
2
3
a
b
c

spread

Warning

This operator is deprecated. See combine instead.

The spread operator combines the items emitted by the source channel with all the values in an array or a Collection object specified as the operator argument. For example:

Channel
    .from(1,2,3)
    .spread(['a','b'])
    .subscribe onNext: { println it }, onComplete: { println 'Done' }
[1, 'a']
[1, 'b']
[2, 'a']
[2, 'b']
[3, 'a']
[3, 'b']
Done

Forking operators

The forking operators are:

branch

Note

Requires Nextflow version 19.08.0-edge or later.

The branch operator allows you to forward the items emitted by a source channel to one or more output channels, choosing one out of them at a time.

The selection criteria is defined by specifying a closure that provides one or more boolean expression, each of which is identified by a unique label. On the first expression that evaluates to a true value, the current item is bound to a named channel as the label identifier. For example:

Channel
    .from(1,2,3,40,50)
    .branch {
        small: it < 10
        large: it > 10
    }
    .set { result }

 result.small.view { "$it is small" }
 result.large.view { "$it is large" }

It shows:

1 is small
2 is small
3 is small
40 is large
50 is large

Note

The above small and large strings maybe be printed interleaving each other due to the asynchronous execution of the view operator.

Tip

A default fallback condition can be specified using true as last branch condition. See the example below.

Channel
    .from(1,2,3,40,50)
    .branch {
        small: it < 10
        large: it < 50
        other: true
    }

The value returned by each branch condition can be customised by specifying an optional expression statement(s) just after the condition expression. For example:

Channel
 .from(1,2,3,40,50)
 .branch {
     foo: it < 10
         return it+2

     bar: it < 50
         return it-2

     other: true
         return 0
 }

Tip

When the return keyword is omitted the value of the last expression statement is implicitly returned.

Warning

The branch evaluation closure must be specified inline, ie. it cannot be assigned to a variable and passed as argument to the operator, how it can be done with other operators.

To create a branch criteria as variable that can be passed as an argument to more than one branch operator use the branchCriteria built-in method as shown below:

def criteria = branchCriteria {
                small: it < 10
                large: it > 10
                }

Channel.from(1,2,30).branch(criteria).set { ch1 }
Channel.from(10,20,1).branch(criteria).set { ch2 }

choice

Warning

The choice operator has been deprecated. Use branch instead.

The choice operator allows you to forward the items emitted by a source channel to two (or more) output channels, choosing one out of them at a time.

The destination channel is selected by using a closure that must return the index number of the channel where the item has to be sent. The first channel is identified by the index 0, the second as 1 and so on.

The following example sends all string items beginning with Hello into queue1, the others into queue2

source = Channel.from 'Hello world', 'Hola', 'Hello John'
queue1 = Channel.create()
queue2 = Channel.create()

source.choice( queue1, queue2 ) { a -> a =~ /^Hello.*/ ? 0 : 1 }

queue1.view()

See also branch operator.

multiMap

Note

Requires Nextflow version 19.11.0-edge or later.

The multiMap operator allows you to forward the items emitted by a source channel to two or more output channels mapping each input value as a separate element.

The mapping criteria is defined by specifying a closure that specify the target channels labelled by a unique identifier followed by an expression statement that evaluates the value to be assigned to such channel.

For example:

Channel
    .from(1,2,3,4)
    .multiMap { it ->
        foo: it + 1
        bar: it * it
        }
    .set { result }

 result.foo.view { "foo $it" }
 result.bar.view { "bar $it" }

It prints:

foo 2
foo 3
foo 4
bar 1
bar 4
bar 9

Tip

The statement expression can be omitted when the value to be emitted is the same as the following one. If you need just need to forward the same value to multiple channel you can use the following the shorthand notation showed below.

Channel
     .from(1,2,3)
     .multiMap { it -> foo: bar: it }
     .set { result }

As before creates two channels, however both of them receive the same source items.

Warning

The multi-map evaluation closure must be specified inline, ie. it cannot be assigned to a variable and passed as argument to the operator, how it can be done with other operators.

To create a multi-map criteria as variable that can be passed as an argument to more than one multiMap operator use the multiMapCriteria built-in method as shown below:

def criteria = multiMapCriteria {
                  small: it < 10
                  large: it > 10
                }

Channel.from(1,2,30).multiMap(criteria).set { ch1 }
Channel.from(10,20,1).multiMap(criteria).set { ch2 }

into

Warning

The into operator is not available when using Nextflow DSL2 syntax.

The into operator connects a source channel to two or more target channels in such a way the values emitted by the source channel are copied to the target channels. For example:

Channel
     .from( 'a', 'b', 'c' )
     .into{ foo; bar }

 foo.view{ "Foo emit: " + it }
 bar.view{ "Bar emit: " + it }
Foo emit: a
Foo emit: b
Foo emit: c
Bar emit: a
Bar emit: b
Bar emit: c

Note

Note the use in this example of curly brackets and the ; as channel names separator. This is needed because the actual parameter of into is a closure which defines the target channels to which the source one is connected.

A second version of the into operator takes an integer n as an argument and returns a list of n channels, each of which emits a copy of the items that were emitted by the source channel. For example:

(foo, bar) = Channel.from( 'a','b','c').into(2)
foo.view{ "Foo emit: " + it }
bar.view{ "Bar emit: " + it }

Note

The above example takes advantage of the multiple assignment syntax in order to assign two variables at once using the list of channels returned by the into operator.

See also tap and separate operators.

tap

The tap operator combines the functions of into and separate operators in such a way that it connects two channels, copying the values from the source into the tapped channel. At the same time it splits the source channel into a newly created channel that is returned by the operator itself.

The tap can be useful in certain scenarios where you may be required to concatenate multiple operations, as in the following example:

log1 = Channel.create()
log2 = Channel.create()

Channel
    .of ( 'a', 'b', 'c' )
    .tap ( log1 )
    .map { it * 2 }
    .tap ( log2 )
    .map { it.toUpperCase() }
    .view { "Result: $it" }

log1.view { "Log 1: $it" }
log2.view { "Log 2: $it" }
Result: AA
Result: BB
Result: CC

Log 1: a
Log 1: b
Log 1: c

Log 2: aa
Log 2: bb
Log 2: cc

The tap operator also allows the target channel to be specified by using a closure. The advantage of this syntax is that you won’t need to previously create the target channel, because it is created implicitly by the operator itself.

Using the closure syntax the above example can be rewritten as shown below:

Channel
    .of ( 'a', 'b', 'c' )
    .tap { log1 }
    .map { it * 2 }
    .tap { log2 }
    .map { it.toUpperCase() }
    .view { "Result: $it" }

log1.view { "Log 1: $it" }
log2.view { "Log 2: $it" }

See also into and separate operators.

separate

Warning

The separate operator has been deprecated. Use multiMap instead.

The separate operator lets you copy the items emitted by the source channel into multiple channels, which each of these can receive a separate version of the same item.

The operator applies a mapping function of your choosing to every item emitted by the source channel. This function must return a list of as many values as there are output channels. Each entry in the result list will be assigned to the output channel with the corresponding position index. For example:

queue1 = Channel.create()
queue2 = Channel.create()

Channel
    .from ( 2,4,8 )
    .separate( queue1, queue2 ) { a -> [a+1, a*a] }

queue1.view { "Channel 1: $it" }
queue2.view { "Channel 2: $it" }
Channel 1: 3
Channel 2: 4
Channel 1: 5
Channel 2: 16
Channel 2: 64
Channel 1: 9

When the mapping function is omitted, the source channel must emit tuples of values. In this case the operator separate splits the tuple in such a way that the value i-th in a tuple is assigned to the target channel with the corresponding position index. For example:

alpha = Channel.create()
delta = Channel.create()

Channel
   .from([1,2], ['a','b'], ['p','q'])
   .separate( alpha, delta )

alpha.view { "first : $it" }
delta.view { "second: $it" }

It will output:

first : 1
first : a
first : p
second: 2
second: b
second: q

A second version of the separate operator takes an integer n as an argument and returns a list of n channels, each of which gets a value from the corresponding element in the list returned by the closure as explained above. For example:

source = Channel.from(1,2,3)
(queue1, queue2, queue3) = source.separate(3) { a -> [a, a+1, a*a] }

queue1.view { "Queue 1 > $it" }
queue2.view { "Queue 2 > $it" }
queue3.view { "Queue 3 > $it" }

The output will look like the following fragment:

Queue 1 > 1
Queue 1 > 2
Queue 1 > 3
Queue 2 > 2
Queue 2 > 3
Queue 2 > 4
Queue 3 > 1
Queue 3 > 4
Queue 3 > 9

Warning

In the above example, please note that since the subscribe operator is asynchronous, the output of channel2 and channel3 can be printed before the content of channel1.

Note

The above example takes advantage of the multiple assignment syntax in order to assign two variables at once using the list of channels returned by the separate operator.

See also: multiMap, into, choice and map operators.

Maths operators

This section talks about operators that performs maths operations on channels.

The maths operators are:

count

The count operator creates a channel that emits a single item: a number that represents the total number of items emitted by the source channel. For example:

Channel
    .from(9,1,7,5)
    .count()
    .view()
// -> 4

An optional parameter can be provided in order to select which items are to be counted. The selection criteria can be specified either as a regular expression, a literal value, a Java class, or a boolean predicate that needs to be satisfied. For example:

Channel
    .from(4,1,7,1,1)
    .count(1)
    .view()
 // -> 3

Channel
    .from('a','c','c','q','b')
    .count ( ~/c/ )
    .view()
// -> 2

Channel
    .from('a','c','c','q','b')
    .count { it <= 'c' }
    .view()
// -> 4

countBy

The countBy operator creates a channel which emits an associative array (i.e. Map object) that counts the occurrences of the emitted items in the source channel having the same key. For example:

Channel
    .from( 'x', 'y', 'x', 'x', 'z', 'y' )
    .countBy()
    .view()
[x:3, y:2, z:1]

An optional grouping criteria can be specified by using a closure that associates each item with the grouping key. For example:

Channel
    .from( 'hola', 'hello', 'ciao', 'bonjour', 'halo' )
    .countBy { it[0] }
    .view()
[h:3, c:1, b:1]

min

The min operator waits until the source channel completes, and then emits the item that has the lowest value. For example:

Channel
    .from( 8, 6, 2, 5 )
    .min()
    .view { "Min value is $it" }
Min value is 2

An optional closure parameter can be specified in order to provide a function that returns the value to be compared. The example below shows how to find the string item that has the minimum length:

Channel
    .from("hello","hi","hey")
    .min { it.size() }
    .view()
"hi"

Alternatively it is possible to specify a comparator function i.e. a closure taking two parameters that represent two emitted items to be compared. For example:

Channel
    .from("hello","hi","hey")
    .min { a,b -> a.size() <=> b.size() }
    .view()

max

The max operator waits until the source channel completes, and then emits the item that has the greatest value. For example:

Channel
    .from( 8, 6, 2, 5 )
    .min()
    .view { "Max value is $it" }
Max value is 8

An optional closure parameter can be specified in order to provide a function that returns the value to be compared. The example below shows how to find the string item that has the maximum length:

Channel
    .from("hello","hi","hey")
    .max { it.size() }
    .view()
"hello"

Alternatively it is possible to specify a comparator function i.e. a closure taking two parameters that represent two emitted items to be compared. For example:

Channel
    .from("hello","hi","hey")
    .max { a,b -> a.size() <=> b.size() }
    .view()

sum

The sum operator creates a channel that emits the sum of all the items emitted by the channel itself. For example:

Channel
    .from( 8, 6, 2, 5 )
    .sum()
    .view { "The sum is $it" }
The sum is 21

An optional closure parameter can be specified in order to provide a function that, given an item, returns the value to be summed. For example:

Channel
        .from( 4, 1, 7, 5 )
        .sum { it * it }
        .view { "Square: $it" }
Square: 91

toInteger

The toInteger operator allows you to convert the string values emitted by a channel to Integer values. For example:

Channel
    .from( '1', '7', '12' )
    .toInteger()
    .sum()
    .view()

Other operators

dump

The dump operator prints the items emitted by the channel to which is applied only when the option -dump-channels is specified on the run command line, otherwise it is ignored.

This is useful to enable the debugging of one or more channel content on-demand by using a command line option instead of modifying your script code.

An optional tag parameter allows you to select which channel to dump. For example:

Channel
    .from(1,2,3)
    .map { it+1 }
    .dump(tag:'foo')

Channel
    .from(1,2,3)
    .map { it^2 }
    .dump(tag: 'bar')

Then you will be able to specify the tag foo or bar as an argument of the -dump-channels option to print either the content of the first or the second channel. Multiple tag names can be specified separating them with a , character.

set

The set operator assigns the channel to a variable whose name is specified as a closure parameter. For example:

Channel.from(10,20,30).set { my_channel }

This is semantically equivalent to the following assignment:

my_channel = Channel.from(10,20,30)

However the set operator is more idiomatic in Nextflow scripting, since it can be used at the end of a chain of operator transformations, thus resulting in a more fluent and readable operation.

ifEmpty

The ifEmpty operator creates a channel which emits a default value, specified as the operator parameter, when the channel to which is applied is empty i.e. doesn’t emit any value. Otherwise it will emit the same sequence of entries as the original channel.

Thus, the following example prints:

Channel .from(1,2,3) .ifEmpty('Hello') .view()

1
2
3

Instead, this one prints:

Channel.empty().ifEmpty('Hello') .view()

Hello

The ifEmpty value parameter can be defined with a closure. In this case the result value of the closure evaluation will be emitted when the empty condition is satisfied.

See also: empty method.

print

Warning

The print operator is deprecated and not supported any more when using DSL2 syntax. Use view instead.

The print operator prints the items emitted by a channel to the standard output. An optional closure parameter can be specified to customise how items are printed. For example:

Channel
      .from('foo', 'bar', 'baz', 'qux')
      .print { it.toUpperCase() + ' ' }

It prints:

FOO BAR BAZ QUX

See also: println and view.

println

Warning

The println operator is deprecated and not supported any more when using DSL2 syntax. Use view instead.

The println operator prints the items emitted by a channel to the console standard output appending a new line character to each of them. For example:

Channel
      .from('foo', 'bar', 'baz', 'qux')
      .println()

It prints:

foo
bar
baz
qux

An optional closure parameter can be specified to customise how items are printed. For example:

Channel
      .from('foo', 'bar', 'baz', 'qux')
      .view { "~ $it" }

It prints:

~ foo
~ bar
~ baz
~ qux

See also: print and view.

view

The view operator prints the items emitted by a channel to the console standard output. For example:

Channel.from(1,2,3).view()

1
2
3

Each item is printed on a separate line unless otherwise specified by using the newLine: false optional parameter.

How the channel items are printed can be controlled by using an optional closure parameter. The closure it must return the actual value of the item being to be printed:

Channel.from(1,2,3)
        .map { it -> [it, it*it] }
        .view { num, sqr -> "Square of: $num is $sqr" }

It prints:

Square of: 1 is 1
Square of: 2 is 4
Square of: 3 is 9

Note

Both the view and print (or println) operators consume them items emitted by the source channel to which they are applied. However, the main difference between them is that the former returns a newly create channel whose content is identical to the source one. This allows the view operator to be chained like other operators.

close

The close operator sends a termination signal over the channel, causing downstream processes or operators to stop. In a common usage scenario channels are closed automatically by Nextflow, so you won’t need to use this operator explicitly.

See also: empty factory method.