Skip to main content

An experimental programming language combining formal and informal computation.

Project description

An experimental programming language combining formal and informal computation.

© 2024, 2025 Daios Technologies Limited

preview

Read the Docs: https://mindscript.daios.ai
Try in Browser: https://www.daios.ai/playground
Source code: https://github.com/DAIOS-AI/mindscript

Description

MindScript is a programming language that seamlessly integrates both formal and informal computation.

MindScript lets programmers code directly when the method for accomplishing a task is clear. Conversely, when they know what they want but not how to achieve it, developers can simply describe their intent. Indeed, for certain functions, such as analyzing the sentiment of a sentence, there might not exist a concrete implementation at all. The syntax is designed to make such specifications straightforward.

A distinctive feature of MindScript is its dual support for both formal and informal types. The formal types are as in other programming languages, which allow expressing hard constraints. The informal types (unique to MindScript) on the other hand offer flexible inductive constraints, similar to how our observations guide our own thought processes.

In practice, formal computation within MindScript is realized through a Turing-complete language (λ), while informal computations are handled by an oracle, realized through a language model (Ψ) which interprets and processes less structured inputs (hence λΨ).

Features

  • Implements an oracle machine.

  • Minimal C-like/JavaScript/Lua syntax on top of JSON data types.

  • Everything is an expression.

  • The formal type system is:

    • dynamic (runtime-checked),
    • structural (based on the properties, not on names or object hierarchies),
    • and strong (type rules are strictly enforced).
  • Code comments are informal type annotations.

  • (Current version) interpreter implemented in Python.

Applications

  • Applications that use large language models
  • Processing of unstructured information
  • Language model agents
  • Semantic web
  • and much more.

Requirements

Disclaimer

This is a strictly experimental programming language. The Python implementation does not aim to be efficient and most likely contains bugs.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mindscript-0.2.17.tar.gz (44.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mindscript-0.2.17-py3-none-any.whl (47.9 kB view details)

Uploaded Python 3

File details

Details for the file mindscript-0.2.17.tar.gz.

File metadata

  • Download URL: mindscript-0.2.17.tar.gz
  • Upload date:
  • Size: 44.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mindscript-0.2.17.tar.gz
Algorithm Hash digest
SHA256 f4a19815f461b44378765c1d28fe108bf43852ac29063bc1c22b056b5ac83b94
MD5 5073a61a0937283f9b5399b4050d5c5a
BLAKE2b-256 11822801f72ed14714ad3a12590cd5f2244ea0d6327416216a2ecab55658e7f4

See more details on using hashes here.

Provenance

The following attestation bundles were made for mindscript-0.2.17.tar.gz:

Publisher: publish.yml on DAIOS-AI/mindscript

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mindscript-0.2.17-py3-none-any.whl.

File metadata

  • Download URL: mindscript-0.2.17-py3-none-any.whl
  • Upload date:
  • Size: 47.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for mindscript-0.2.17-py3-none-any.whl
Algorithm Hash digest
SHA256 96a28f9135b29b549e6d57d0845650ed46adcaa77c429862e2973f1010706dc2
MD5 f04734e7f0e2a2afff306d31955db8cd
BLAKE2b-256 50d65325d59fe4c3c1d7d5d702beb689dcfc2cf5d707033391f0889785c5c3be

See more details on using hashes here.

Provenance

The following attestation bundles were made for mindscript-0.2.17-py3-none-any.whl:

Publisher: publish.yml on DAIOS-AI/mindscript

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page