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Version: 0.7.0

Expressions

Syntax

In KCL, an expression specifies the computation of a value.

The syntax is the following:

expression: test ("," test)*
test: if_expr | primary_expr | unary_expr | binary_expr

KCL expressions consist of if expression, primary expression, unary expression, and binary expression.

Primary Expressions

Primary expressions are the operands for unary and binary expressions.

Operands are self-delimiting. An operand may be followed by any number of selector dot, a function call, or slice suffixes, to form a primary expression. The grammar uses expression, where a multiple-component expression is allowed, and test where it accepts an expression of only a single component.

Syntax:

primary_expr: operand | primary_expr select_suffix | primary_expr call_suffix | primary_expr subscript_suffix

Operands

Operand denotes the elementary value in an expression. An operand may be an identifier, a literal, or a parenthesized expression.

Syntax:

operand: operand_name | number | string | "True" | "False" | "None" | "Undefined" | list_expr | list_comp | dict_expr | dict_comp | "(" expression ")"
operand_name: identifier | qualified_identifier

Identifiers

In KCL, an identifier is a name, may with selectors, that identifies a value.

Syntax:

identifier: NAME

Examples:

x
a
_b

Use the $ character prefix to define keyword identifiers.

$if = 1
$else = "s"

Please note: whether the non-keyword identifier is prefixed with $ has the same effect.

_a = 1
$_a = 2 # equal to `_a = 2`

To simplify the definition of the qualified identifier, such as 'pkg.type', we additionally define qualified_identifier:

Syntax:

qualified_identifier: identifier "." identifier

Examples:

pkg.a

The package name in qualified_identifier must be imported.

Basic Literals

Basic literals supported in KCL are int, float, string and bool including True and False. Evaluation of basic literal yields a value of the given type with the given value.

Syntax:

operand: number | string | "True" | "False" | "None" | "Undefined"

Examples:

1
2.3
"abc"
True
False
None
Undefined

See more details about data type spec.

Parenthesized Expressions

An expression enclosed in parentheses yields the result of that expression.

Syntax:

operand: '(' expression ')'

Examples:

x = (1 + 2) * (3 + 4)  # 21

Dictionary Expressions

A dictionary expression is a comma-separated immutable list of colon-separated key/value expression pairs, enclosed in curly brackets, and it yields a new dictionary object. An optional comma may follow the final pair.

config_expr: '{' config_entries '}'
config_entries: config_entry [config_entry*]
config_comp: '{' (config_entry comp_clause+) '}'
config_entry: expr (':' | '=' | '+=') expr | double_star_expr | if_entry
double_star_expr: "**" expression
if_entry:
'if' expr ';' if_entry_exec_block
('elif' expr ':' if_entry_exec_block)*
('else' ':' if_entry_exec_block)?
NEWLINE: '/r?/n'

Examples:

{}
{"one": 1}
{"one": 1, "two": 2}

The key and value expressions are evaluated in left-to-right order. Evaluation fails if the same key is used multiple times.

Only hashable values may be used as the keys of a dictionary. This includes all built-in types except dictionaries, and lists.

We can ignore the comma , at the end of the line for writing dict key-value pairs in multiple lines:

data = {
"key1" = "value1" # Ignore the comma ',' at the end of line
"key2" = "value2"
} # {"key1": "value1", "key2": "value2"}

We can ignore the key quotation marks when we writing simple literals on the key.

data = {
key1 = "value1" # Ignore the comma ',' at the end of line
key2 = "value2"
} # {"key1": "value1", "key2": "value2"}

In addition, the config selector expressions can be used to init a schema instance.

person = {
base.count = 2
base.value = "value"
labels.key = "value"
} # {"base": {"count": 2, "value": "value"}, "labels": {"key": "value"}}

We can merge dict using the dict unpacking operator ** like this:

_part1 = {
a = "b"
}

_part2 = {
c = "d"
}

a_dict = {**_part1, **_part2} # {"a: "b", "c": "d"}

We can use if expressions to dynamically add elements to the dict element, elements that meet the conditions are added to the dict, and elements that do not meet the conditions are ignored.

a = 1  # 1
data = {
key1 = "value1"
if a == 1: key2 = "value2"
if a > 0: key3 = "value3"
if a < 0: key4 = "value4"
} # {"key1": "value1", "key2": "value2", "key3": "value3"}
a = 1  # 1
data1 = {
key1 = "value1"
if a == 1:
key2 = "value2"
elif a > 0:
key3 = "value3"
else:
key4 = "value4"
} # {"key1": "value1", "key2": "value2"}
data2 = {
key1 = "value1"
if a == 1: key2 = "value2"
elif a > 0: key3 = "value3"
else: key4 = "value4"
} # {"key1": "value1", "key2": "value2"}

List Expressions

A list expression is a comma-separated immutable list of element expressions, enclosed in square brackets, and it yields a new list. An optional comma may follow the last element expression.

list_expr: '[' [list_item [',']] ']'
list_item: test | "*" primary_expr | if_expr

Element expressions are evaluated in left-to-right order.

Examples:

[]                      # [], empty list
[1] # [1], a 1-element list
[1, 2, 3] # [1, 2, 3], a 3-element list

We can use if expressions to dynamically add elements to the list element, elements that meet the conditions are added to the list, and elements that do not meet the conditions are ignored.

a = 1  # 1
data = [
1
if a == 1: 2
if a > 0: 3
if a < 0: 4
] # [1, 2, 3]
a = 1  # 1
data1 = [
1
if a == 1:
2
elif a == 2:
3
else:
3
] # [1, 2]
data2 = [
1
if a == 1: 2
elif a == 2: 2
else: 3
] # [1, 2]

Comprehensions

A comprehension constructs a new list or dictionary value by looping over one or more iterables and evaluating a body expression that produces successive elements of the result.

Syntax:

list_comp: '[' list_item comp_clause+ ']' .
dict_comp: '{' entry comp_clause+ '}' .

comp_clause: 'for' loop_variables [","] 'in' test ['if' test]
loop_variables: primary_expr (',' primary_expr)*

A list comprehension consists of a single expression followed by one or more clauses, the first of which must be a for clause. Each for clause resembles a for statement, and specifies an iterable operand and a set of variables to be assigned by successive values of the iterable. An if cause resembles an if statement, and specifies a condition that must be met for the body expression to be evaluated. A sequence of for and if clauses acts like a nested sequence of for and if statements.

Examples:

[x * x for x in range(5)]                 # [0, 1, 4, 9, 16]
[x * x for x in range(5) if x % 2 == 0] # [0, 4, 16]
[[x, y] for x in range(5) \
if x % 2 == 0 \
for y in range(5) \
if y > x] # [[0, 1], [0, 2], [0, 3], [0, 4], [2, 3], [2, 4]]

Besides, we can use two variables in the list comprehension, the first variable denotes the list index and the second variable denotes the list item.

data = [1000, 2000, 3000]
# Single variable loop
dataLoop1 = [i * 2 for i in data] # [2000, 4000, 6000]
dataLoop2 = [i for i in data if i == 2000] # [2000]
dataLoop3 = [i if i > 2 else i + 1 for i in data] # [1000, 2000, 3000]
# Double variable loop
dataLoop4 = [i + v for i, v in data] # [1000, 2001, 3002]
dataLoop5 = [v for i, v in data if v == 2000] # [2000]
# Use `_` to ignore loop variables
dataLoop6 = [v if v > 2000 else v + i for i, v in data] # [1000, 2001, 3000]
dataLoop7 = [i for i, _ in data] # [0, 1, 2]
dataLoop8 = [v for _, v in data if v == 2000] # [2000]

A dict comprehension resembles a list comprehension, but its body is a pair of expressions, key: value, separated by a colon, and its result is a dictionary containing the key/value pairs for which the body expression was evaluated. Evaluation fails if the value of any key is un-hashable.

Besides, we can use two variables in the dict comprehension, the first variable denotes the dict key and the second variable denotes the dict value of the key.

data = {"key1" = "value1", "key2" = "value2"}
# Single variable loop
dataKeys1 = {k: k for k in data} # {"key1": "key1", "key2": "key2"}
dataValues1 = {k: data[k] for k in data} # {"key1": "value1", "key2": "value2"}
# Double variable loop
dataKeys2 = {k: k for k, v in data} # {"key1": "key1", "key2": "key2"}
dataValues2 = {v: v for k, v in data} # {"value1": "value1", "value2": "value2"}
dataFilter = {k: v for k, v in data if k == "key1" and v == "value1"} # {"key1": "value1"}
# Use `_` to ignore loop variables
dataKeys3 = {k: k for k, _ in data} # {"key1": "key1", "key2": "key2"}
dataValues3 = {v: v for _, v in data} # {"value1": "value1", "value2": "value2"}

As with a for loop, the loop variables may exploit compound assignment:

[x * y + z for [x, y], z in [[[2, 3], 5], [["o", 2], "!"]]]      # [11, 'oo!']

KCL does not accept an un-parenthesized list as the operand of a for clause:

[x * x for x in 1, 2, 3]  # parse error: unexpected comma

Comprehensions defines a new lexical block, so assignments to loop variables have no effect on variables of the same name in an enclosing block:

x = 1
_ = [x for x in [2]] # new variable x is local to the comprehension
print(x) # 1

The operand of a comprehension's first clause (always a for) is resolved in the lexical block enclosing the comprehension. In the examples below, identifiers referring to the outer variable named x have been distinguished by subscript.

x0 = [1, 2, 3]
[x * x for x in x0] # [1, 4, 9]
[x * x for x in x0 if x % 2 == 0] # [4]

All subsequent for and if expressions are resolved within the comprehension's lexical block, as in this rather obscure example:

x0 = [[1, 2], [3, 4], [5, 6]]
[x * x for x in x0 for x in x if x % 2 == 0] # [4, 16, 36]

which would be more clearly rewritten as:

x = [[1, 2], [3, 4], [5, 6]]
[z * z for y in x for z in y if z % 2 == 0] # [4, 16, 36]

Conditional Expressions

A conditional expression has the form a if cond else b. It first evaluates the condition cond. If it's true, it evaluates a and yields its value; otherwise it yields the value of b.

Syntax:

if_expr: test "if" test "else" test

Examples:

x = True if enabled else False  # if enabled is

Unary Expressions

In KCL, supported unary operators are +, -, ~, and not.

Syntax:

unary_expr: ("+" | "-" | "~") primary_expr
| "not" test

Usage:

+ number        unary positive          (int, float)
- number unary negation (int, float)
~ number unary bitwise inversion (int)
not x logical negation (any type)

The + and - operators may be applied to any number (int or float) and return the number. The not operator returns the negation of the truth value of its operand.

Examples:

~1   # -2
~-1 # 0
~0 # -1
not True # False
not 0 # True

Binary Expressions

In KCL, binary expressions consist of comparisons, logical operations, arithmetic operations and membership tests.

Syntax:

binary_expr: test bin_op test
bin_op: 'or'
| 'and'
| '==' | '!=' | '<' | '>' | '<=' | '>='
| 'in' | 'not' 'in'
| '|'
| '^'
| '&'
| '-' | '+'
| '*' | '%' | '/' | '//'
| '<<' | '>>'

Logical Operations

The or and and operators yield the logical disjunction and conjunction of their arguments, which need not be Booleans.

The expression x or y yields the value of x if its truth value is True, or the value of y otherwise.

False or False   # False
False or True # True
True or True # True
1 or "hello" # 1

Similarly, x and y yields the value of x if its truth value is False, or the value of y otherwise.

False and False   # False
False and True # False
True and True # True
1 and "hello" # "hello"

These operators use "short circuit" evaluation, so the second expression is not evaluated if the value of the first expression has already determined the result, allowing constructions like these:

x and x[0] == 1   # x[0] is not evaluated if x is empty
len(x) == 0 or x[0] == ""
not x or not x[0]

Comparisons

The == operator reports whether its operands are equal; the != operator is its negation.

The operators <, >, <=, and >= perform an ordered comparison of their operands. It is an error to apply these operators to operands of unequal type, unless one of the operands is an int and the other is a float. Of the built-in types, only the following support ordered comparison, using the ordering relation shown:

NoneType        # None <= None
bool # False < True
int # mathematical
float # as defined by IEEE 754
string # lexicographical
list # lexicographical

Comparison of floating-point values follows the IEEE 754 standard, which breaks several mathematical identities. For example, if x is a NaN value, the comparisons x < y, x == y, and x > y all yield false for all values of y.

The remaining built-in types support only equality comparisons. Values of type dict and schema compare equal if their elements compare equal, and values of type function or builtin_function_or_method are equal only to themselves.

dict                            # equal contents
schema # equal exported-attributes
function # identity
builtin_function_or_method # identity

Arithmetic Operations

The following table summarizes the binary arithmetic operations available for built-in types:

Arithmetic (int or float; result has type float unless both operands have type int)
number + number # addition
number - number # subtraction
number * number # multiplication
number / number # real division (result is always a float)
number // number # floored division
number % number # remainder of floored division
number ^ number # bitwise XOR
number << number # bitwise left shift
number >> number # bitwise right shift

Concatenation
string + string
list + list

Repetition (string/list)
int * sequence
sequence * int

Union
int | int
list | list
dict | dict
schema | schema
schema | dict
basictype | basictype

The operands of the arithmetic operators +, -, *, //, and % must both be numbers (int or float) but need not have the same type. The type of the result has type int only if both operands have that type. The result of real division / always has type float.

The + operator may be applied to non-numeric operands of the same type, such as two lists, or two strings, in which case it computes the concatenation of the two operands and yields a new value of the same type.

"Hello, " + "world"           # "Hello, world"
[1, 2] + [3, 4] # [1, 2, 3, 4]

The * operator may be applied to an integer n and a value of type string, list, in which case it yields a new value of the same sequence type consisting of n repetitions of the original sequence. The order of the operands is immaterial. Negative values of n behave like zero.

'mur' * 2               # 'murmur'
3 * range(3) # [0, 1, 2, 0, 1, 2, 0, 1, 2]

The & operator requires two operands of the same type, such as int. For integers, it yields the bitwise intersection (AND) of its operands.

The | operator likewise computes bitwise, unions basic types and unions collection and schema data, such as list, dict and schema.

Computing bitwise examples:

0x12345678 | 0xFF  # 0x123456FF

Unioning basic types examples:

schema x:
a: int | str # attribute a could be a int or string

A union type is used to define a schema attribute type. See more details in schema spec. Supported types in a union type are int, str, float, bool, list and dict.

Unioning collection and schema data:

  • Unioning List. Overwrite the list expression on the right side of the operator | to the list variable on the left side of the operator one by one according to the index.
_a = [1, 2, 3]
_b = [4, 5, 6, 7]
x = _a | _b # [4, 5, 6, 7] 4 -> 1; 5 -> 2; 6 -> 3; 7 -> None

Unioning to the specific index or all elements is still under discussion.

  • Unioning Dict. Union the dict expression on the right side of the operator | one by one to the dict variable on the left side of the operator according to the key
_a = {key1 = "value1"}
_b = {key1 = "overwrite", key2 = "value2"}
_c = _a | _b # {"key1": "overwrite", "key2": "value2"}

The union of collection and schema is a new one whose attributes are unioning b to a, preserving the order of the attributes of the operands, left before right.

Unioning to the specific key or all keys is still under discussion.

  • Unioning Schema.

The union operation for schema is similar to dict.

Schema union could be done as:

schema Person:
firstName: str
lastName: str

_a = Person {
firstName = "John"
}
_b = {lastName = "Doe"}
_a = _a | _b # {"firstName": "John", "lastName": "Doe"}

Unioning to a specific attribute is still under discussion. Unioning to all attributes is not applicable to schema instances.

See selector expression in expression spec for more details.

The ^ operator accepts operands of int. For integers, it yields the bitwise XOR (exclusive OR) of its operands.

The << and >> operators require operands of int type both. They shift the first operand to the left or right by the number of bits given by the second operand. It is a dynamic error if the second operand is negative. Implementations may impose a limit on the second operand of a left shift.

0x12345678 & 0xFF               # 0x00000078
0b01011101 ^ 0b110101101 # 0b111110000
0b01011101 >> 2 # 0b010111
0b01011101 << 2 # 0b0101110100

Membership Tests

Usage:

      any in     sequence       (list, dict, schema, string)
any not in sequence

The in operator reports whether its first operand is a member of its second operand, which must be a list, dict, schema, or string. The not in operator is its negation. Both return a Boolean.

The meaning of membership varies by the type of the second operand: the members of a list are its elements; the members of a dict are its keys; the members of a string are all its substrings.

1 in [1, 2, 3]                  # True

d = {"one" = 1, "two" = 2}
"one" in d # True
"three" in d # False
1 in d # False
[] in d # False

"nasty" in "dynasty" # True
"a" in "banana" # True
"f" not in "way" # True

d = data {one = 1, two = 2} # data is a schema with attributes one and two
"one" in d # True
"three" in d # False

Function Invocations

KCL allows calling built-in functions and functions from built-in and system modules. Whether KCL allows defining new functions is under discussion.

Syntax:

call_suffix: "(" [arguments [","]] ")"
arguments: argument ("," argument)*
argument: test | identifier "=" test | "*" test | "**" test

To call a function, the basic way is shown as the following code excerpt:

print("An argument")

import math
# 2 powers 3 is 8.
a = math.pow(2, 3)

As you can see, arguments are separated with ,. Arguments can only be passed in this way. KCL supports positional arguments and key-value arguments.

Note that:

  • Some functions have parameters with default values.
  • Some functions accept variadic arguments.

When an argument is not supplied for a parameter without a default value, an error will be reported.

Selector Expressions

A selector expression selects the attribute or method of the value.

Select Attributes

Syntax:

select_suffix: ["?"] "." identifier

KCL provides a wealth of ways to identify or filter attributes.

x.y

  • schema: it denotes the attribute value of a schema x identified by y
  • package: it denotes the identifier of a package x identified by y

Examples:

schema Person:
name: str
age: int

person = Person {
name = "Alice"
age = 18
}
name = person.name # "Alice"
age = person.age # 18

x?.y

If the x if None/Undefined or empty(empty list or dict), just return None, otherwise behave as x.y.

Examples

noneData = None
data?.name # None

emptyDict = {}
emptyDict?.name # None

emptyList = []
emptyList?[0] # None

As a supplementary of the selector expression in KCL code, the KCL compiler needs to provide corresponding identifying and filtering features through the command line and api form.

Select Methods

Syntax:

select_suffix: "." identifier

A identifier identifies method belongs to the built-in types string, list, dict, and schema.

  • A selector expression fails if the value does not have an attribute of the specified name.
  • A selector expression that selects a method typically appears within a call expression, as in these examples:

Examples:

["able", "baker", "charlie"].index("baker")     # 1
"banana".count("a") # 3
"banana".reverse() # error: string has no .reverse field or method
Person.instances() # all instances of schema Person

But when not called immediately, the selector expression evaluates to a bound method, that is, a method coupled to a specific receiver value. A bound method can be called like an ordinary function, without a receiver argument:

f = "banana".count
f # <built-in method count of string value>
f("a") # 3
f("n") # 2

Index Expressions

An index expression a[i] yields the i th element of an indexable type such as a string or list. The index i must be an int value in the range -ni < n, where n is len(a); any other index results in an error.

Syntax:

subscript_suffix: "[" [test] "]"

A valid negative index i behaves like the non-negative index n+i, allowing for convenient indexing relative to the end of the sequence.

"abc"[0]                        # "a"
"abc"[1] # "b"
"abc"[-1] # "c"

["zero", "one", "two"][0] # "zero"
["zero", "one", "two"][1] # "one"
["zero", "one", "two"][-1] # "two"

An index expression d[key] may also be applied to a dictionary d, to obtain the value associated with the specified key. It returns Undefined if the dictionary contains no such key.

An index expression appearing on the left side of an assignment causes the specified list or dictionary element to be updated:

a = range(3)            # a == [0, 1, 2]
b = a[2] # 2

It is a dynamic error to attempt to update an element of an immutable type, such as a list or string, or a frozen value of a mutable type.

Slice Expressions

A slice expression a[start:stop:stride] yields a new value containing a sub-sequence of a, which must be a string, or list.

subscript_suffix: "[" [test] [":" [test] [":" [test]]] "]"

Each of the start, stop, and stride operands is optional; if present, and not None, each must be an integer. The stride value defaults to 1. If the stride is not specified, the colon preceding it may be omitted too. It is an error to specify a stride of zero.

Conceptually, these operands specify a sequence of values i starting at start and successively adding stride until i reaches or passes stop. The result consists of the concatenation of values of a[i] for which i is valid.`

The effective start and stop indices are computed from the three operands as follows. Let n be the length of the sequence.

If the stride is positive: If the start operand was omitted, it defaults to -infinity. If the end operand was omitted, it defaults to +infinity. For either operand, if a negative value was supplied, n is added to it. The start and end values are then "clamped" to the nearest value in the range 0 to n, inclusive.

If the stride is negative: If the start operand was omitted, it defaults to +infinity. If the end operand was omitted, it defaults to -infinity. For either operand, if a negative value was supplied, n is added to it. The start and end values are then "clamped" to the nearest value in the range -1 to n-1, inclusive.

"abc"[1:]               # "bc"  (remove first element)
"abc"[:-1] # "ab" (remove last element)
"abc"[1:-1] # "b" (remove first and last element)
"banana"[1::2] # "aaa" (select alternate elements starting at index 1)
"banana"[4::-2] # "nnb" (select alternate elements in reverse, starting at index 4)

It's not allowed to define a slice expression as a left value in KCL. Cause list and string are immutable, re-slicing can directly operate to operand to ensure better performance.

Quantifier Expressions

Quantifier expressions act on collection: list or dict, generally used to obtain a certain result after processing the collection, mainly in the following four forms:

quant_expr: quant_op [ identifier ',' ] identifier 'in' quant_target '{' expr ['if' expr] '}'
quant_target: string | identifier | list_expr |list_comp | dict_expr | dict_comp
quant_op: 'all' | 'any' | 'filter' | 'map'
  • all
    • Used to detect that all elements in the collection satisfy the given logical expression, and return a boolean value as the result.
    • Only when all elements in the collection satisfy the expression true, the all expression is true, otherwise it is false.
    • If the original collection is empty, return true.
    • Supports short-circuiting of logical expressions during expression execution.
  • any
    • Used to detect that at least one element in the collection satisfies the given logical expression, and returns a boolean value as the result.
    • When at least one element in the collection satisfies the expression true, the any expression is true, otherwise it is false.
    • If the original collection is empty, return false.
    • Supports short-circuiting of logical expressions during expression execution.
  • map
    • Generate a new list by mapping the elements in the original collection.
    • The length of the new list is exactly the same as the original collection.
  • filter
    • By logically judging and filtering the elements in the original collection, and returning the filtered sub-collection.
    • Only when the element judges the expression to be true, it is added to the sub-collection.
    • The type (list, dict and schema) of the new collection is exactly the same as the original collection, and the length range is [0, len(original-collection)].

all and any expression sample codes:

schema Config:
volumes: [{str:}]
services: [{str:}]

check:
all service in services {
service.clusterIP == "NONE" if service.type == "ClusterIP"
}, "invalid cluster ip"

any volume in volumes {
volume.mountPath in ["/home/admin", "/home/myapp"]
}

map and filter expression sample codes:

a = map e in [{name = "1", value = 1}, {name = "2", value = 2}] {
{name = e.name, value = int(e.value) ** 2}
} # [{"name": "1", value: 1}, {"name": "2", "value": 4}]

b = map k, v in {a = "foo", b = "bar"} { v } # ["foo", "bar"]

c = filter e in [{name = "1", value = 1}, {name = "2", value = 2}] {
int(e.value) > 1
} # [{"name": "2", "value": 2}]

d = filter _, v in {a = "foo", b = "bar"} {
v == "foo"
} # {"a": "foo"}

Please pay attention to distinguish the difference between any expression and any type. When any is used in type annotations, it means that the value of the variable is arbitrary, while the any expression means that one of the elements in a set satisfies the condition.