ConfDB Query Language

ConfDB offers flexible query language based on predicate logic. ConfDB queries may be used for config processing, including fetching, classification and validation.

Common Concepts

Contexts

Query context is the couple of variables and their values. It is a simple key-value structure implemented over python’s dict. Context represents a possible state of pipeline. Contexts are grouped together representing possibilities on each stage of pipeline. Within the possibilities, each context is independent on each other.

Variables can be either bound (known values) or unbound (superposition of possible values).

Predicates

Predicate is the logic function, defined by its arguments and accepting possibilities on input, evaluating them and passing outcomes as output. Predicates evaluate input context independently. Each input context may be evaluated to one or more output context.

graph LR Possibilities --> Predicate Predicate -> Outcomes

Pipelining

Predicates may be combined together into sequential (and) and parallel (or) chains. Chains can be grouped together by bracket operator. Resulting chains build pipeline which is valid predicate too.

Query

Query is the pipeline, which can be applied to exact ConfDB state and input context to produce output contexts with possible outcomes

Syntax

Query is the Python expression

Variable

Variable is coded as plain python variables

Predicate

Predicate is coded as python function call

Match('interface', X, 'description', Y)

See Built-in predicates for possible predicates and examples

Sequential chain

Sequential chain is the combination of two predicates when output of first predicate serves as input to the second one

graph LR Input --> P1 P1 --> P2 P2 --> Output

Sequential chain is coded by boolean and operator

P1() and P2()

Sequential chain can contain more than two operators like

P1() and P2() and P3() and P4()

Parallel chain

Parallel chain consists of two or more predicates independently accepting same input and combining and deduplicating resulting outputs

graph LR Input --> P1 Input --> P2 P1 --> Output P2 --> Output

Parallel chains are coded by or operator

P1() or P2()

Chain Grouping

Chains can be grouped using brackets

(P1() and P2()) or P3() or (P4() and P5())

Built-in predicates

Simple Logic

True()

Always True, pass context unmodified

False()

Always False, breaks predicate chain

Context Manipulation

Set(**kwargs)

Add or modify variables of context. If variable value is a list, expand the list and apply production

Set(X=2)
Set(X=[1, 2, 3])

Del(*args)

Delete variables from context. Deduplicate contexts when necessary

Del(X)

ConfDB Matching

Match(*args)

Match *args against ConfDB. Bind unbound variables on match

Parameters:*args –

ConfDB path

Match('interface', X, 'description', Y)

NotMatch(self, _input, *args)

Pass only if *args is not matched against ConfDB. Bind unbound variables when possible

Parameters:*args –

ConfDB path

NotMatch('interface', X, 'description')

ConfDB Manipulation

Fact(*args)

Set Fact to database

Parameters:*args –

ConfDB path of fact, eigther constants or bound variables

Fact('interface', X, 'hints', 'test')

Filtering and Checking

Filter(expr)

Pass context only if expr is evaluated as True

Parameters:expr – Python expression

Filter(X % 2 == 0)

Re(pattern, name, ignore_case=None):

Match variable name against regular expression pattern. Pass context further if matched. If regular expression contains named groups, i.e. (?P<group_name>….), apply them as context variables

Parameters:

• pattern – Regular expression pattern
• name – Variable name
• ignore_case – Ignore case during match

Re("a+", X)
Re("a+", X, ignore_case=True)
Re("-(?P<abs>\d+)", X)

HasVLAN(vlan_filter, vlan_id):

Check vlan_id is within vlan_filter expression

Parameters:

• vlan_filter – VC Filter expression
• vlan_id – Vlan Id or bound variable

HasVlan("1-99,200-299", X)

Aggregation

Group(stack=None, *args, **kwargs):

Group input context on given variables

(
    Match("interfaces", name)
    or Match("interfaces", name, "type", type)
    or Match("interfaces", name, "description", description)
    or Match("interfaces", name, "admin-status", admin_status)
) and Group("name")

Collapse(*args, **kwargs):

Collapse multiple keys to a single one following rules

Parameters:kwargs – One of collapse operation should be specified * join=<sep> – join lines with separator sep * joinrange=<sep> – join lines with separator sep and apply range optimization

Collapse("interfaces", X, "tagged-vlans", join=",")
Collapse("interfaces", X, "tagged-vlans", joinrange=",")

Debugging

Dump(message=None):

Dump current context to stdout and pass unmodified

Parameters:message – Optional message

Dump()
Dump("Point1")

Sprintf(name, fmt, *args):

Perform string formatting and apply result to context variable

Parameters:

• name – Target variable name
• fmt – String format
• args – Values or bound variables

Sprintf(y, 'x = %s, y = %s', x, '2')

Examples

Fetch all interfaces descriptions

Match("interfaces", name, "description", descr)