Category:Tailspin: Difference between revisions

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Tailspin simplifies data transfer and the processing of data according to rules and conditions.
⚫
A programming language with extreme pattern matching and declarative syntax, hopefully different enough to be interesting. The inspiration comes mostly from xslt, but data structures are json-like. The main idea is to let your data flow through a series of transforms so it should be easy to specify that flow. Transform steps can be specified as a set of templates with pattern-matching determining which template to apply. Output is generally specified as literals with interpolation of values.
Thanks to its declarative data structures and corresponding condition matching syntax,
many algorithms look exactly like the specification, for example, compare the
[https://rosettacode.org/wiki/JSON#Tailspin json parser]
and the [https://www.json.org/json-en.html json specification].

Despite the grounding in business data processing, Tailspin turns out to be fun to use and has been
used for the [https://adventofcode.com/ adventofcode] events of [https://github.com/tobega/aoc2018 2018]
and [https://github.com/tobega/aoc2019 2019]

⚫
The inspiration comes mostly from xslt, but data structures are json-like. The main idea is to let your data flow through a series of transforms so it should be easy to specify that flow. Transform steps can be specified as a set of templates with pattern-matching determining which template to apply. Output is generally specified as literals with interpolation of values.


[http://tobega.blogspot.com/2020/05/a-little-tailspin.html Quick intro]
[http://tobega.blogspot.com/2020/05/a-little-tailspin.html Quick intro]

Revision as of 14:06, 23 August 2020

Language
Tailspin
This programming language may be used to instruct a computer to perform a task.
Official website
Lang tag(s): tailspin
See Also:


Listed below are all of the tasks on Rosetta Code which have been solved using Tailspin.

Tailspin simplifies data transfer and the processing of data according to rules and conditions. Thanks to its declarative data structures and corresponding condition matching syntax, many algorithms look exactly like the specification, for example, compare the json parser and the json specification.

Despite the grounding in business data processing, Tailspin turns out to be fun to use and has been used for the adventofcode events of 2018 and 2019

The inspiration comes mostly from xslt, but data structures are json-like. The main idea is to let your data flow through a series of transforms so it should be easy to specify that flow. Transform steps can be specified as a set of templates with pattern-matching determining which template to apply. Output is generally specified as literals with interpolation of values.

Quick intro

Syntax reference

Development page, also how to run Tailspin programs on github

Pages in category "Tailspin"

The following 94 pages are in this category, out of 94 total.

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P

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