Expressions 1 2

1.2.3 Precedence of Operations Up: 1.2 Java Mechanics Previous: 1.2.1 Notation and Syntax 1.2.2 Java Expressions In Java, arithmetic, boolean, and String expressions are written in conventional mathematical infix notation, adapted to the standard computer character set (called ASCII). 1-2 Guide Notes TE - Order of Operations and Evaluating Expressions. 1-2 Lesson Plan - Order of Operations and Evaluating Expressions. 1-2 Online Activities - Order of Operations and Evaluating Expressions. 1-2 Slide Show - Order of Operations and Evaluating Expressions.

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2.1.11Expressions

The following are all the expression forms of Pyret:

‹expr›‹paren-expr›‹id-expr›‹prim-expr›‹lam-expr›‹method-expr›‹app-expr›‹obj-expr›‹dot-expr›‹extend-expr›‹tuple-expr›‹tuple-get›‹template-expr›‹get-bang-expr›‹update-expr›‹if-expr›‹ask-expr›‹cases-expr›‹for-expr›‹user-block-expr›‹inst-expr›‹construct-expr›‹multi-let-expr›‹letrec-expr›‹type-let-expr›‹construct-expr›‹table-expr›‹table-select›‹table-sieve›‹table-order›‹table-extract›‹table-transform›‹table-extend›‹load-table-expr›‹reactor-expr›‹paren-expr›(‹binop-expr›)‹id-expr›NAME‹prim-expr›NUMBERRATIONALBOOLEANSTRING

2.1.11.1Lambda Expressions

The grammar for a lambda expression is:

‹lam-expr›lam‹fun-header›block:‹doc-string›‹block›‹where-clause›end

A lambda expression creates a function value that can be applied withapplication expressions. The arguments in argsare bound to their arguments as immutable identifiers as in alet expression.

These identifiers follow the same rules of no shadowing and no assignment.

If the arguments have annotations associated withthem, they are checked before the body of the function starts evaluating, inorder from left to right. If an annotation fails, an exception is thrown. Tower 3 6 0 9.

A lambda expression can have a return annotation as well, which ischecked before evaluating to the final value:

Lambda expressions remember, or close over, the values of other identifiersthat are in scope when they are defined. So, for example:

2.1.11.2Curly-Brace Lambda Shorthand

Lambda expressions can also be written with a curly-brace shorthand:

‹curly-lam-expr›{‹fun-header›block:‹doc-string›‹block›‹where-clause›}

2.1.11.3Anonymous Method Expressions

An anonymous method expression looks much like an anonymous function (definedwith lam):

‹method-expr›method‹fun-header›block:‹doc-string›‹block›‹where-clause›end

All the same rules for bindings, including annotations and shadowing, apply thesame to ‹method-expr›s as they do to ‹lam-expr›s.

It is a well-formedness error for a method to have no arguments.

At runtime, a ‹method-expr› evaluates to a method value. Method valuescannot be applied directly:

Instead, methods must be included as object fields, where they can then bebound and invoked. A method value can be used in multiple objects:

2.1.11.4Application Expressions

Function application expressions have the following grammar:

‹app-expr›‹expr›‹app-args›‹app-args›(‹app-arg-elt›‹binop-expr›)‹app-arg-elt›‹binop-expr›,

An application expression is an expression followed by a comma-separated listof arguments enclosed in parentheses. It first evaluates the arguments inleft-to-right order, then evaluates the function position. If the functionposition is a function value, the number of provided arguments is checkedagainst the number of arguments that the function expects. If they match, thearguments names are bound to the provided values. If they don't, an exceptionis thrown.

Note that there is no space allowed before the opening parenthesis ofthe application. If you make a mistake, Pyret will complain:

2.1.11.5Curried Application Expressions

Suppose a function is defined with multiple arguments:

Sometimes, it is particularly convenient to define a new function thatcalls f with some arguments pre-specified:

Pyret provides syntactic sugar to make writing such helper functionseasier:

Specifically, when Pyret code contains a function application some ofwhose arguments are underscores, it constructs an lambda expressionwith the same number of arguments as there were underscores in theoriginal expression, whose body is simply the original functionapplication, with the underscores replaced by the names of thearguments to the anonymous function.

This syntactic sugar also workswith operators. For example, the following are two ways to sum a listof numbers:

Likewise, the following are two ways to compare two lists forequality:

Note that there are some limitations to this syntactic sugar. Youcannot use it with the is or raises expressions incheck blocks, since both test expressions and expectedoutcomes are known when writing tests. Also, note that the sugar isapplied only to one function application at a time. As a result, thefollowing code:

desugars to

which is probably not what was intended. You can still write theintended expression manually:

Pyret just does not provide syntactic sugar to help in this case(or other more complicated ones).

2.1.11.6Chaining Application

‹chain-app-expr›‹binop-expr›^‹binop-expr›

The expression e1 ^ e2 is equivalent to e2(e1). It's justanother way of writing a function application to a single argument.

Sometimes, composing functions doesn't produce readable code. For example, ifsay we have a Tree datatype, and we have an add operation onit, defined via a function. To build up a tree with a series of adds, we'dwrite something like:

Or maybe

If add were a method, we could write:

which would be more readable, but since add is a function, this doesn'twork.

In this case, we can write instead:

This uses curried application to create asingle argument function, and chaining application to apply it. This can bemore readable across several lines of initialization as well, when compared tocomposing 'inside-out' or using several intermediate names:

2.1.11.7Instantiation Expressions

Functions may be defined with parametric signatures. Calling those functionsdoes not require specifying the type parameter, but supplying it might aid inreadability, or may aid the static type checker. You can supply the typearguments just between the function name and the left-paren of the functioncall. Spaces are not permitted before the left-angle bracket or after theright-angle bracket

‹inst-expr›‹expr›<‹ann›,‹ann›>

2.1.11.8Binary Operators

There are a number of binary operators in Pyret. A binary operator expressionis a series of expressions joined by binary operators. An expression itselfis also a binary operator expression.

‹binop-expr›‹expr›BINOP‹expr›

There are additional equality operators in Pyret, which also call methods, but aresomewhat more complex. They are documented in detail in equality.

Logical operators do not have a corresponding method call, since they onlyapply to primitive boolean values.

2.1.11.9Tuple Expressions

Tuples are an immutable, fixed-length collection of expressions indexed by non-negative integers:

Capture one pro 20. ‹tuple-expr›{‹tuple-fields›}‹tuple-fields›‹binop-expr›;‹binop-expr›;

A semicolon-separated sequence of fields enclosed in {} creates a tuple.

2.1.11.10Tuple Access Expressions

‹tuple-get›‹expr›.{NUMBER}

A tuple-get expression evaluates the expr to a value val, and thendoes one of three things:

A static well-formedness error is raised if the index isnegative

• Raises an exception, if expr is not a tuple

• Raises an exception, if NUMBER is equal to or greater than the length of the given tuple

• Evaluates the expression, returning the val at the given index. The first index is 0

For example:

Note that the index is restricted syntactically to being a number. So this program is a parse error:

This restriction ensures that tuple access is typable.

2.1.11.11Object Expressions

Object expressions map field names to values:

‹obj-expr›{‹fields›}{}‹fields›‹list-field›‹field›,‹list-field›‹field›,‹field›‹key›:‹binop-expr›method‹key›‹fun-header›block:‹doc-string›‹block›‹where-clause›end‹key›NAME

A comma-separated sequence of fields enclosed in {} creates an object; werefer to the expression as an object literal. There are two types offields: data fields and method fields. A data field in an objectliteral simply creates a field with that name on the resulting object, with itsvalue equal to the right-hand side of the field. A method field

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is syntactic sugar for:

That is, it's just special syntax for a data field that contains a methodvalue.

The fields are evaluated in the order they appear. If the same field appearsmore than once, it is a compile-time error.

2.1.11.12Dot Expressions

A dot expression is any expression, followed by a dot and name:

‹dot-expr›‹expr›.NAME

A dot expression evaluates the expr to a value val, and then does oneof three things:

• Raises an exception, if NAME is not a field of expr

• Evaluates to the value stored in NAME, if NAME is present andnot a method

• If the NAME field is a method value, evaluates to a function that isthe method binding of the method value to val. For a method

  The method binding of m to a value v is equivalent to:

  What this detail means is that you can look up a method and itautomatically closes over the value on the left-hand side of the dot. Thisbound method can be freely used as a function.

  For example:

2.1.11.13Extend Expressions

The extend expression consists of an base expression and a list of fields toextend it with:

‹extend-expr›‹expr›.{‹fields›}

The extend expression first evaluates expr to a value val, and thencreates a new object with all the fields of val and fields. If afield is present in both, the new field is used.

Examples:

2.1.11.14If Expressions

An if expression has a number of test conditions and an optional else case.

‹if-expr›if‹binop-expr›block:‹block›‹else-if›else:‹block›end‹else-if›else if‹binop-expr›:‹block›

For example, this if expression has an 'else:'

This one does not:

Both are valid. The conditions are tried in order, and the block correspondingto the first one to return true is evaluated. If no condition matches,the else branch is evaluated if present. If no condition matches and no elsebranch is present, an error is thrown. If a condition evaluates to a valueother than true or false, a runtime error is thrown.

2.1.11.15Ask Expressions

An ask expression is a different way of writing an ifexpression that can be easier to read in some cases.

‹ask-expr›ASKblock:‹ask-branch›|otherwise:‹block›end‹ask-branch›|‹binop-expr›then:‹block›

This ask expression:

is equivalent to

Similar to if, if an otherwise: branch isn't specified and nobranch matches, a runtime error results.

2.1.11.16Cases Expressions

A cases expression consists of a datatype (in parentheses), an expression toinspect (before the colon), and a number of branches. It is intended to beused in a structure parallel to a data definition.

‹cases-expr›cases(‹ann›)‹expr›block:‹cases-branch›|else=>‹block›end‹cases-branch›|NAME‹args›=>‹block›

The check-ann must be a type, like List. Thenexpr is evaluated and checked against the given annotation. Ifit has the right type, the cases are then checked.

Cases should use the names of the variants of the given data type as theNAMEs of each branch. In the branch that matches, the fields of thevariant are bound, in order, to the provided args, and the right-hand sideof the => is evaluated in that extended environment. An exception resultsif the wrong number of arguments are given.

An optional else clause can be provided, which is evaluated if no casesmatch. If no else clause is provided, a runtime error results.

For example, some cases expression on lists looks like:

If a field of the variant is a tuple, it can also be bound using a tuple binding.

For example, a cases expression on a list with tuples looks like:

2.1.11.17For Expressions

For expressions consist of the for keyword, followed by a list ofbinding from expr clauses in parentheses, followed by a block:

‹for-expr›for‹expr›(‹for-bind-elt›‹for-bind›)‹return-ann›block:‹block›end‹for-bind-elt›‹for-bind›,‹for-bind›‹binding›from‹binop-expr›

The for expression is just syntactic sugar for alam-expr and a app-expr. An expression

is equivalent to:

Using a for-expr can be a more natural way to call, for example, listiteration functions because it puts the identifier of the function and thevalue it draws from closer to one another. Use of for-expr is a matter ofstyle; here is an example that compares fold with and without for:

2.1.11.18Template (..) Expressions

A template expression is three dots in a row:

‹template-expr›..

It is useful for a placeholder for other expressions in code-in-progress. Whenit is evaluated, it raises a runtime exception that indicates the expression itis standing in for isn't yet implemented:

This is handy for starting a function (especially one with many cases) withsome tests written and others to be completed.

These other positions for .. may be included in the future.

Because templates are by definition unfinished, the presence of atemplate expression in a block exempts that block fromexplicit-blockiness checking.

2.1.11.19Tables

Tables precise syntax is documented here. For helper functions and datastructures, see Creating Tables.

Table expressions consist of a list of column names followed by one or morerows of data:

‹table-expr›table:‹table-headers›‹table-rows›end‹table-headers›‹table-header›,‹table-header›‹table-header›NAME::‹ann›‹table-rows›‹table-row›‹table-row›‹table-row›row:‹binop-expr›,‹binop-expr›

‹table-select›selectNAME,NAMEfrom‹expr›end

‹table-sieve›sieve‹expr›using‹binding›,‹binding›:‹binop-expr›end

2.1.11.19.1Sorting Table Rows

‹table-order›order‹expr›:‹column-order›end‹column-order›NAMEascendingdescending

2.1.11.19.2Transforming Table Rows

‹table-transform›transform‹expr›using‹binding›,‹binding›:‹transform-fields›end‹transform-fields›‹transform-field›,‹transform-field›,‹transform-field›‹key›:‹binop-expr›

2.1.11.19.3Extracting Table Columns

‹table-extract›extractNAMEfrom‹expr›end

2.1.11.19.4Adding Table Columns

‹table-extend›extend‹expr›using‹binding›,‹binding›:‹table-extend-field›,‹table-extend-field›end‹table-extend-field›‹key›::‹ann›:‹binop-expr›‹key›::‹ann›:‹expr›ofNAME

2.1.11.20Table Loading Expressions

‹load-table-expr›load-table:‹table-headers›‹load-table-specs›end‹load-table-specs›‹load-table-spec›‹load-table-spec›‹load-table-spec›source:‹expr›sanitizeNAMEusing‹expr›

2.1.11.21Reactor Expressions

‹reactor-expr›reactor:init:‹expr›,‹option-name›:‹expr›end‹option-name›on-tickon-mouseon-keyto-drawstop-whentitleclose-when-stopseconds-per-tick

Reactors are described in detail in Creating Reactors.

2.1.11.22Mutable fields

‹get-bang-expr›‹expr›!NAME‹update-expr›‹expr›!{‹fields›}

By analogy with how ‹dot-expr› accesses normal fields,‹get-bang-expr› accesses mutable fields — but more emphatically so,because mutable fields, by their nature, might change. Dot-access to mutablefields also works, but does not return the field's value: it returns thereference itself, which is a Pyret value that's mostly inert and difficult towork with outside the context of its host object.

To update a reference value, we use syntax similar to ‹extend-expr›,likewise made more emphatic:

2.1.11.23Construction expressions

‹construct-expr›[‹binop-expr›:‹construct-args›]‹construct-args›‹binop-expr›,‹binop-expr›

Pyret defines several of these constructors for you: lists, sets, arrays, andstring-dictionaries all have the same syntax.

2.1.11.24Expression forms of bindings

Every definition in Pyret is visible until the end of its scope, which isusually the nearest enclosing block. To limit that scope, you can wrapdefinitions in explicit ‹user-block-expr›s, but this is sometimes awkward toread. Pyret allows for three additional forms that combine bindings withexpression blocks in a manner that is sometimes more legible:

‹multi-let-expr›let‹let-or-var›,‹let-or-var›block:‹block›end‹let-or-var›‹let-decl›‹var-decl›‹letrec-expr›letrec‹let-decl›,‹let-decl›block:‹block›end‹type-let-expr›type-let‹type-let-or-newtype›,‹type-let-or-newtype›block:end‹type-let-or-newtype›‹type-decl›‹newtype-decl›

These define their bindings only for the scope of the following block. A‹multi-let-expr› defines a sequence of either let- orvariable-bindings, each of which are in scope for subsequent ones. A‹letrec-expr› defines a set of mutually-recursive let-bindings that mayrefer to each other in a well-formed way (i.e., no definition may rely on otherdefinitions before they've been fully evaluated). These are akin to the‹let-decl› and ‹var-decl› forms seen earlier, but with moreexplicitly-visible scoping rules.

Finally, ‹type-let-expr› defines local type aliases or new types, akinto ‹type-stmt›.

Azure Pipelines | TFS 2018 | TFS 2017.3

Note

In Microsoft Team Foundation Server (TFS) 2018 and previous versions,build and release pipelines are called definitions,runs are called builds,service connections are called service endpoints,stages are called environments,and jobs are called phases.

Expressions can be used in many places where you need to specify a string, boolean, or number value when authoring a pipeline.The most common use of expressions is in conditions to determine whether a job or step should run.

Another common use of expressions is in defining variables.Expressions can be evaluated at compile time or at run time.Compile time expressions can be used anywhere; runtime expressions can be used in variables and conditions. Runtime expressions are intended as a way to compute the contents of variables and state (example: condition).

The difference between runtime and compile time expression syntaxes is primarily what context is available.In a compile-time expression (${{ }}), you have access to parameters and statically defined variables.In a runtime expression ($[ ]), you have access to more variables but no parameters.

In this example, a runtime expression sets the value of $(isMain). A static variable in a compile expression sets the value of $(compileVar).

An expression can be a literal, a reference to a variable, a reference to a dependency, a function, or a valid nested combination of these.

Literals

As part of an expression, you can use boolean, null, number, string, or version literals.

Boolean

True and False are boolean literal expressions.

Null

Null is a special literal expression that's returned from a dictionary miss, e.g. (variables['noSuch']). Null can be the output of an expression but cannot be called directly within an expression.

Number

Starts with '-', '.', or '0' through '9'.

String

Must be single-quoted. For example: 'this is a string'.

To express a literal single-quote, escape it with a single quote.For example: 'It's OK if they're using contractions.'.

You can use a pipe character (|) for multiline strings.

Version

A version number with up to four segments.Must start with a number and contain two or three period (.) characters.For example: 1.2.3.4.

Variables

As part of an expression, you may access variables using one of two syntaxes:

• Index syntax: variables['MyVar']
• Property dereference syntax: variables.MyVar

In order to use property dereference syntax, the property name must:

• Start with a-Z or _
• Be followed by a-Z0-9 or _

Depending on the execution context, different variables are available.

• If you create pipelines using YAML, then pipeline variables are available.
• If you create build pipelines using classic editor, then build variables are available.
• If you create release pipelines using classic editor, then release variables are available.

Variables are always strings. If you want to use typed values, then you should use parameters instead.

Note

There is a limitation for using variables with expressions for both Classical and YAML pipelines when setting up such variables via variables tab UI. Variables that are defined as expressions shouldn't depend on another variable with expression in value since it isn't guaranteed that both expressions will be evaluated properly. For example we have variable a whose value $[ ] is used as a part for the value of variable b. Since the order of processing variables isn't guaranteed variable b could have an incorrect value of variable a after evaluation.

Described constructions are only allowed while setup variables through variables keyword in YAML pipeline. It is required to place the variables in the order they should be processed to get the correct values after processing.

Functions

The following built-in functions can be used in expressions.

and

• Evaluates to True if all parameters are True
• Min parameters: 2. Max parameters: N
• Casts parameters to Boolean for evaluation
• Short-circuits after first False
• Example: and(eq(variables.letters, 'ABC'), eq(variables.numbers, 123))

coalesce

• Evaluates the parameters in order, and returns the value that does not equal null or empty-string.
• Min parameters: 2. Max parameters: N
• Example: coalesce(variables.couldBeNull, variables.couldAlsoBeNull, 'literal so it always works')

contains

• Evaluates True if left parameter String contains right parameter
• Min parameters: 2. Max parameters: 2
• Casts parameters to String for evaluation
• Performs ordinal ignore-case comparison
• Example: contains('ABCDE', 'BCD') (returns True)

containsValue

• Evaluates True if the left parameter is an array, and any item equals the right parameter. Also evaluates True if the left parameter is an object, and the value of any property equals the right parameter.
• Min parameters: 2. Max parameters: 2
• If the left parameter is an array, convert each item to match the type of the right parameter. If the left parameter is an object, convert the value of each property to match the type of the right parameter. The equality comparison for each specific item evaluates False if the conversion fails.
• Ordinal ignore-case comparison for Strings
• Short-circuits after the first match

Note

There is no literal syntax in a YAML pipeline for specifying an array.This function is of limited use in general pipelines.It's intended for use in the pipeline decorator context with system-provided arrays such as the list of steps.

convertToJson

• Take a complex object and outputs it as JSON.
• Min parameters: 1. Max parameters: 1.

counter

• This function can only be used in an expression that defines a variable. It cannot be used as part of a condition for a step, job, or stage.
• Evaluates a number that is incremented with each run of a pipeline.
• Parameters: 2. prefix and seed.
• Prefix is a string expression. A separate value of counter is tracked for each unique value of prefix
• Seed is the starting value of the counter

You can create a counter that is automatically incremented by one in each execution of your pipeline. When you define a counter, you provide a prefix and a seed. Here is an example that demonstrates this. The prefix value cannot contain some special characters, including ..

The value of minor in the above example in the first run of the pipeline will be 100. In the second run it will be 101, provided the value of major is still 1.

If you edit the YAML file, and update the value of the variable major to be 2, then in the next run of the pipeline, the value of minor will be 100. Subsequent runs will increment the counter to 101, 102, 103, ..

Later, if you edit the YAML file, and set the value of major back to 1, then the value of the counter resumes where it left off for that prefix. In this example, it resumes at 102.

Here is another example of setting a variable to act as a counter that starts at 100, gets incremented by 1 for every run, and gets reset to 100 every day.

Note

pipeline.startTime is not available outside of expressions. pipeline.startTimeformats system.pipelineStartTime into a date and time object so that it is available to work with expressions.The default time zone for pipeline.startTime is UTC. You can change the time zone for your organization.

Here is an example of having a counter that maintains a separate value for PRs and CI runs.

Counters are scoped to a pipeline. In other words, its value is incremented for each run of that pipeline. There are no project-scoped counters.

endsWith

• Evaluates True if left parameter String ends with right parameter
• Min parameters: 2. Max parameters: 2
• Casts parameters to String for evaluation
• Performs ordinal ignore-case comparison
• Example: endsWith('ABCDE', 'DE') (returns True)

eq

• Evaluates True if parameters are equal
• Min parameters: 2. Max parameters: 2
• Converts right parameter to match type of left parameter. Returns False if conversion fails.
• Ordinal ignore-case comparison for Strings
• Example: eq(variables.letters, 'ABC')

format

• Evaluates the trailing parameters and inserts them into the leading parameter string
• Min parameters: 1. Max parameters: N
• Example: format('Hello {0} {1}', 'John', 'Doe')
• Uses .NET custom date and time format specifiers for date formatting (yyyy, yy, MM, M, dd, d, HH, H, m, mm, ss, s, f, ff, ffff, K)
• Example: format('{0:yyyyMMdd}', pipeline.startTime). In this case pipeline.startTime is a special date time object variable.
• Escape by doubling braces. For example: format('literal left brace {{ and literal right brace }}')

ge

• Evaluates True if left parameter is greater than or equal to the right parameter
• Min parameters: 2. Max parameters: 2
• Converts right parameter to match type of left parameter. Errors if conversion fails.
• Ordinal ignore-case comparison for Strings
• Example: ge(5, 5) (returns True)

gt

• Evaluates True if left parameter is greater than the right parameter
• Min parameters: 2. Max parameters: 2
• Converts right parameter to match type of left parameter. Errors if conversion fails.
• Ordinal ignore-case comparison for Strings
• Example: gt(5, 2) (returns True)

in

• Evaluates True if left parameter is equal to any right parameter
• Min parameters: 1. Max parameters: N
• Converts right parameters to match type of left parameter. Equality comparison evaluates False if conversion fails.
• Ordinal ignore-case comparison for Strings
• Short-circuits after first match
• Example: in('B', 'A', 'B', 'C') (returns True)

join

• Concatenates all elements in the right parameter array, separated by the left parameter string.
• Min parameters: 2. Max parameters: 2
• Each element in the array is converted to a string. Complex objects are converted to empty string.
• If the right parameter is not an array, the result is the right parameter converted to a string.

In this example, a semicolon gets added between each item in the array. The parameter type is an object.

le

• Evaluates True if left parameter is less than or equal to the right parameter
• Min parameters: 2. Max parameters: 2
• Converts right parameter to match type of left parameter. Errors if conversion fails.
• Ordinal ignore-case comparison for Strings
• Example: le(2, 2) (returns True)

length

• Returns the length of a string or an array, either one that comes from the system or that comes from a parameter
• Min parameters: 1. Max parameters 1
• Example: length('fabrikam') returns 8

lower

• Converts a string or variable value to all lowercase characters
• Min parameters: 1. Max parameters 1
• Returns the lowercase equivalent of a string
• Example: lower('FOO') returns foo

lt

• Evaluates True if left parameter is less than the right parameter
• Min parameters: 2. Max parameters: 2
• Converts right parameter to match type of left parameter. Errors if conversion fails.
• Ordinal ignore-case comparison for Strings
• Example: lt(2, 5) (returns True)

ne

• Evaluates True if parameters are not equal
• Min parameters: 2. Max parameters: 2
• Converts right parameter to match type of left parameter. Returns True if conversion fails.
• Ordinal ignore-case comparison for Strings
• Example: ne(1, 2) (returns True)

not

• Evaluates True if parameter is False
• Min parameters: 1. Max parameters: 1
• Converts value to Boolean for evaluation
• Example: not(eq(1, 2)) (returns True)

notIn

• Evaluates True if left parameter is not equal to any right parameter
• Min parameters: 1. Max parameters: N
• Converts right parameters to match type of left parameter. Equality comparison evaluates False if conversion fails.
• Ordinal ignore-case comparison for Strings
• Short-circuits after first match
• Example: notIn('D', 'A', 'B', 'C') (returns True)

or

• Evaluates True if any parameter is True
• Min parameters: 2. Max parameters: N
• Casts parameters to Boolean for evaluation
• Short-circuits after first True
• Example: or(eq(1, 1), eq(2, 3)) (returns True, short-circuits)

replace

• Returns a new string in which all instances of a string in the current instance are replaced with another string
• Min parameters: 3. Max parameters: 3
• replace(a, b, c): returns a, with all instances of b replaced by c
• Example: replace('https://www.tinfoilsecurity.com/saml/consume','https://www.tinfoilsecurity.com','http://server') (returns http://server/saml/consume)

startsWith

• Evaluates True if left parameter string starts with right parameter
• Min parameters: 2. Max parameters: 2
• Casts parameters to String for evaluation
• Performs ordinal ignore-case comparison
• Example: startsWith('ABCDE', 'AB') (returns True)

upper

• Converts a string or variable value to all uppercase characters
• Min parameters: 1. Max parameters 1
• Returns the uppercase equivalent of a string
• Example: upper('bah') returns BAH

xor

• Evaluates True if exactly one parameter is True
• Min parameters: 2. Max parameters: 2
• Casts parameters to Boolean for evaluation
• Example: xor(True, False) (returns True)

Job status check functions

You can use the following status check functions as expressions in conditions, but not in variable definitions.

always

• Always evaluates to True (even when canceled). Note: A critical failure may still prevent a task from running. For example, if getting sources failed.

canceled

• Evaluates to True if the pipeline was canceled.

failed

• For a step, equivalent to eq(variables['Agent.JobStatus'], 'Failed').
• For a job:
  • With no arguments, evaluates to True only if any previous job in the dependency graph failed.
  • With job names as arguments, evaluates to True only if any of those jobs failed.

succeeded

• For a step, equivalent to in(variables['Agent.JobStatus'], 'Succeeded', 'SucceededWithIssues')
• For a job:
  • With no arguments, evaluates to True only if all previous jobs in the dependency graph succeeded or partially succeeded.
  • If the previous job succeeded but a dependency further upstream failed, succeeded('previousJobName') will return true. When you just use dependsOn: previousJobName, it will fail because all of the upstream dependencies were not successful. To only evaluate the previous job, use succeeded('previousJobName') in a condition.
  • With job names as arguments, evaluates to True if all of those jobs succeeded or partially succeeded.
  • Evaluates to False if the pipeline is canceled.

Expression 12000xl-ga

succeededOrFailed

• For a step, equivalent to in(variables['Agent.JobStatus'], 'Succeeded', 'SucceededWithIssues', 'Failed')

• For a job:

  • With no arguments, evaluates to True regardless of whether any jobs in the dependency graph succeeded or failed.
  • With job names as arguments, evaluates to True whether any of those jobs succeeded or failed.

  This is like always(), except it will evaluate False when the pipeline is canceled.

Conditional insertion

You can use an if clause to conditionally assign the value or a variable or set inputs for tasks. Conditionals only work when using template syntax. Learn more about variable syntax.

For templates, you can use conditional insertion when adding a sequence or mapping. Learn more about conditional insertion in templates.

Conditionally assign a variable

Conditionally set a task input

Each keyword

You can use the each keyword to loop through parameters with the object type.

Dependencies

Expressions can use the dependencies context to reference previous jobs or stages. You can use dependencies to: Vmware fusion pro 11 5 14.

• Reference the job status of a previous job
• Reference the stage status of a previous stage
• Reference output variables in the previous job in the same stage
• Reference output variables in the previous stage in a stage
• Reference output variables in a job in a previous stage in the following stage

The context is called dependencies for jobs and stages and works much like variables.Inside a job, if you refer to an output variable from a job in another stage, the context is called stageDependencies.

If you experience issues with output variables having quote characters (' or ') in them, see this troubleshooting guide.

Stage to stage dependencies

Structurally, the dependencies object is a map of job and stage names to results and outputs.Expressed as JSON, it would look like:

Use this form of dependencies to map in variables or check conditions at a stage level.In this example, Stage B runs whether Stage A is successful or skipped.

Note

The following examples use standard pipeline syntax. If you're using deployment pipelines, both variable and conditional variable syntax will differ. For information about the specific syntax to use, see Deployment jobs.

Stages can also use output variables from another stage.In this example, Stage B depends on a variable in Stage A.

Note

Math Expressions 1-20 Board

By default, each stage in a pipeline depends on the one just before it in the YAML file.If you need to refer to a stage that isn't immediately prior to the current one, you can override this automatic default by adding a dependsOn section to the stage.

Job to job dependencies within one stage

At the job level within a single stage, the dependencies data doesn't contain stage-level information.

In this example, Job A will always be skipped and Job B will run.Job C will run, since all of its dependencies either succeed or are skipped.

In this example, Job B depends on an output variable from Job A.

Job to job dependencies across stages

At the job level, you can also reference outputs from a job in a previous stage.This requires using the stageDependencies context.

In this example, job B1 will run whether job A1 is successful or skipped.Job B2 will check the value of the output variable from job A1 to determine whether it should run.

Stage depending on job output

If no changes are required after a build, you might want to skip a stage in a pipeline under certain conditions. An example is when you're using Terraform Plan, and you want to trigger approval and apply only when the plan contains changes.

When you use this condition on a stage, you must use the dependencies variable, not stageDependencies.

The following example is a simple script that sets a variable (use your actual information from Terraform Plan) in a step in a stage, and then invokes the second stage only if the variable has a specific value.

Filtered arrays

When operating on a collection of items, you can use the * syntax to apply a filtered array. A filtered array returns all objects/elements regardless their names.

As an example, consider an array of objects named foo. We want to get an array of the values of the id property in each object in our array.

We could do the following:

foo.*.id

This tells the system to operate on foo as a filtered array and then select the id property.

This would return:

Type casting

Values in an expression may be converted from one type to another as the expression gets evaluated.When an expression is evaluated, the parameters are coalesced to the relevant data type and then turned back into strings.

For example, in this YAML, the values True and False are converted to 1 and 0 when the expression is evaluated.The function lt() returns True when the left parameter is less than the right parameter.

In this example, the values variables.emptyString and the empty string both evaluate as empty strings.The function coalesce() evaluates the parameters in order, and returns the first value that does not equal null or empty-string.

Detailed conversion rules are listed further below.

Boolean

To number:

• False → 0
• True → 1

To string:

• False → 'False'
• True → 'True'

Null

• To Boolean: False
• To number: 0
• To string: ' (the empty string)

Number

• To Boolean: 0 → False, any other number → True
• To version: Must be greater than zero and must contain a non-zero decimal. Must be less than Int32.MaxValue (decimal component also).
• To string:Converts the number to a string with no thousands separator and no decimal separator.

String

Cached

• To Boolean: ' (the empty string) → False, any other string → True
• To null: ' (the empty string) → Null, any other string not convertible
• To number: ' (the empty string) → 0, otherwise, runs C#'s Int32.TryParse using InvariantCulture and the following rules: AllowDecimalPoint | AllowLeadingSign | AllowLeadingWhite | AllowThousands | AllowTrailingWhite. If TryParse fails, then it's not convertible.
• To version:runs C#'s Version.TryParse. Must contain Major and Minor component at minimum. If TryParse fails, then it's not convertible.

Version

• To Boolean: True
• To string: Major.Minor or Major.Minor.Build or Major.Minor.Build.Revision.

FAQ

I want to do something that is not supported by expressions. What options do I have for extending Pipelines functionality?

You can customize your Pipeline with a script that includes an expression. For example, this snippet takes the BUILD_BUILDNUMBER variable and splits it with Bash. This script outputs two new variables, $MAJOR_RUN and $MINOR_RUN, for the major and minor run numbers.The two variables are then used to create two pipeline variables, $major and $minor with task.setvariable. These variables are available to downstream steps. To share variables across pipelines see Variable groups.