{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/11"}],"enrichment":{"capability":"Amalgam is a Python wrapper that lets you call Amalgam, a tree-structured language designed for safe, sandboxed code generation and information-theoretic inference, directly from Python code.","skillfed_tags":["sandboxed-execution","genetic-programming","agent-modeling"],"use_cases":["Genetic programming: evolve code or data structures in a sandboxed, semantically consistent environment.","Instance-based machine learning: implement algorithms that learn from individual examples using Amalgam's data-code symmetry.","Agent-based modeling: define and execute agent behaviors and interactions with guaranteed semantic safety.","Simulation: build deterministic, reproducible simulations where code and data are interchangeable.","Game AI and content generation: generate game logic and AI behaviors using Amalgam's information-theoretic inference.","Data storage and retrieval: leverage Amalgam's tree structure for efficient, semantically consistent data operations."],"what_it_does":"Amalgam is a Python interface to Amalgam, a specialized language built for safe, sandboxed execution and code generation. Unlike general-purpose languages, Amalgam prioritizes code-data symmetry and semantic consistency, making it suited for domains like genetic programming, instance-based machine learning, simulation, and agent-based modeling. The wrapper handles the underlying compiled binary automatically, so you load Amalgam entity files (.amlg or .caml) and execute labeled functions by passing JSON parameters and receiving JSON results.\n\nThe package ships with precompiled binaries for Windows (x86_64), Linux (x86_64 and arm64), and macOS (arm64). It has no runtime Python dependencies, making installation straightforward. You write Amalgam code natively or through this Python wrapper, and the language's design emphasizes information-theoretic properties and safe execution semantics rather than developer convenience.","worth_installing":"Yes, if you need safe, sandboxed code generation or are exploring genetic programming, instance-based learning, or agent-based modeling. The package is actively maintained, has no external dependencies, and is marked production-stable. However, verify that your OS and CPU architecture are in the supported set (Windows/Linux x86_64, Linux/macOS arm64), and be aware that the GNU Affero v3 license requires source disclosure if you deploy it as a network service. For private or non-network use, it poses no licensing friction."},"id":"amalgam-lang","links":{"html":"https://skillfed.io/packages/amalgam-lang","md":"https://skillfed.io/packages/amalgam-lang.md","pypi":"https://pypi.org/project/amalgam-lang/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-07","license_spdx":null,"license_treatment":"agpl","name":"amalgam-lang","python_support":"supports_current","summary":"A direct interface with Amalgam compiled DLL, dylib, or so."},"popularity":{"monthly_downloads":85334,"position":13930,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"34.2.6"}