Pipeline programming

Programming paradigms
Agent-oriented Automata-based Component-based Flow-based Pipelined Concatenative Concurrent computing Relativistic programming Data-driven Declarative (contrast: Imperative) Constraint Dataflow Cell-oriented (spreadsheets) Reactive Intensional Functional Logic Abductive logic Answer set Constraint logic Functional logic Inductive logic End-user programming Event-driven Service-oriented Time-driven Expression-oriented Feature-oriented Function-level (contrast: Value-level) Generic Imperative (contrast: Declarative) Procedural Language-oriented Discipline-specific Domain-specific Grammar-oriented Dialecting Intentional Metaprogramming Automatic Reflective Attribute-oriented Template Policy-based Non-structured (contrast: Structured) Array Nondeterministic Parallel computing Process-oriented Programming in the large and small Semantic Structured (contrast: Non-structured) Modular (contrast: Monolithic) Object-oriented By separation of concerns: Aspect-oriented Role-oriented Subject-oriented Class-based Prototype-based Recursive Value-level (contrast: Function-level)

When a programming language is originally designed without any syntax to nest function calls, pipeline programming is a simple syntax change to add it. The programmer connects notional program modules into a flow structure, by analogy to a physical pipeline carrying reaction products through a chemical or other plant. The best-known example is the Unix pipe system, but many high level software design tools (such as the openDX display suite) provide a GUI pipeline programming tool that helps visualize data flow through a program. A data flow diagram (DFD) maps well to pipeline programming. However, exception handling can be one of the weaknesses.

Examples

• Windows PowerShell
• Hartmann pipeline
• Bash

See also

• Pipeline (software)
• Hartmann pipeline
• Function composition (computer science)
• Architecture description language
• Scripting language