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Type compatibility

Type compatibility is the relationship in which values of one type can be used where another type is expected under applicable language rules.

How 3 Manning books explain it

Building User-Friendly DSLs

A relation between types specifying whether values of one type can be used where values of another type are expected.

How it is used
Uses type compatibility to validate expressions, constrain attribute values, and select type-specific rendering.
How deep it goes
Implements equality-based matching and contrasts it with assignability, inheritance, and coercion without implementing those broader relations.
Examples
Demonstrates compatibility with amount, date range, percentage, untyped values, binary subtraction, attribute assignments, and display markers.
What you can do after
Build it from scratch by representing types as objects, comparing stable IDs, and propagating checks into constraints and projections.

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Clojure: The Essential Reference

Type compatibility is the property that two values belong to categories that an operation can compare according to its compatibility rules.

How it is used
Compares Clojure values with diff while preserving compatible collection structure.
How deep it goes
Explains collection predicates, scalar equality, nested outputs, exceptions, and deep-recursion limits.
Examples
Uses vectors, lists, maps, sets, arrays, sorted maps, and deeply nested maps as comparison cases.
What you can do after
Diagnose compatible and incompatible comparisons by interpreting diff's unique and common result positions.

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Functional Programming in JavaScript

The property that one function’s output type matches another function’s accepted input type.

How it is used
Connects stages in functional pipelines by matching returned values with receiving function inputs.
How deep it goes
Defines output-input matching, explains duck typing in JavaScript, and stops short of covering static type systems.
Examples
Uses trim, normalize, and isValid to process a Social Security number through compatible function stages.
What you can do after
Apply it via function signatures to design pipelines whose stages accept one another’s outputs.

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Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.