diastatic-malt
A library for Python operator overloading
Decision gist · record as of 2026-08-14
Yes, if you need source-to-source code transformation or operator overloading in Python. Low install friction, active maintenance, no known vulnerabilities, and permissive licensing make it a safe choice. The main consideration is whether your use case actually requires the transformation capabilities it provides—it is a specialized tool, not a general utility.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.9 or later (supports 3.9, 3.10, 3.11).
- Low friction: pure Python wheel with a single runtime dependency (termcolor).
- Active maintenance with last commit 2026-03-18 and classified as Production/Stable.
License · maintenance · safety
Apache License 2.0 (permissive) — Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions. You must include a copy of the license and state significant changes, but can use the code freely.
last release 2026-03-09 (158 days) · last repo commit 2026-03-18 · 9 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 329,952 downloads/mo, #7,541 on PyPI
Alternatives
Verify before relying
pip install diastatic-malt
import diastatic_malt
# Use the library's transformation capabilities on your Python code- What specific transformation capabilities are available beyond operator overloading and keyword overloading.
- Whether the AutoGraph functionality ported from TensorFlow is feature-complete or has limitations.
- Real-world performance characteristics and overhead of the transformations.
What it is and what it does
DiastaticMalt is a Python metaprogramming library that performs source-to-source code transformations and operator overloading, including the ability to overload built-in Python keywords. It is derived from TensorFlow's AutoGraph module (under Apache 2.0 license) but operates as a standalone library without requiring TensorFlow as a dependency. The library transforms regular Python code into alternative forms optimized for specific use cases, such as program capture or specialized execution contexts.
The package is lightweight, depending only on termcolor for output formatting, and targets modern Python versions (3.9+). It is maintained by the PennyLane team and classified as Production/Stable, making it suitable for use in projects that need fine-grained control over how Python code is executed or analyzed at runtime.
Use it for
- Transform Python code for specialized execution contexts without depending on the full TensorFlow library.
- Implement custom operator overloading to intercept and modify how Python expressions are evaluated.
- Build program capture or tracing systems that need to intercept keyword behavior.
- Create domain-specific languages or embedded DSLs that require fine-grained control over Python semantics.
- Develop debugging or profiling tools that need to instrument Python code at the source level.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need source-to-source code transformation or operator overloading in Python.
Low install friction, active maintenance, no known vulnerabilities, and permissive licensing make it a safe choice. The main consideration is whether your use case actually requires the transformation capabilities it provides—it is a specialized tool, not a general utility.
Install
diastatic-malt on PyPI
Before you install
Low friction: pure Python wheel with a single runtime dependency (termcolor). Active maintenance with last commit 2026-03-18 and classified as Production/Stable.
Requires Python 3.9 or later (supports 3.9, 3.10, 3.11).
License in practice
Apache License 2.0 is permissive, allowing commercial and private use with minimal restrictions. You must include a copy of the license and state significant changes, but can use the code freely.
Quickstart
pip install diastatic-malt
import diastatic_malt
# Use the library's transformation capabilities on your Python codeVerify before relying
- What specific transformation capabilities are available beyond operator overloading and keyword overloading.
- Whether the AutoGraph functionality ported from TensorFlow is feature-complete or has limitations.
- Real-world performance characteristics and overhead of the transformations.
Package facts
| License | Apache License 2.0 permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagetermcolor |
| Maintenance | Actively maintained 158 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 329,952 / month, #7,541 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.9 |
Evidence: diastatic_malt-2.15.3-py3-none-any.whl
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See also overloading · tensorflow-estimator · tensorflow-transform · tensorflow-probability · pyccolo · multipledispatch · imgaug · einshape · dbt-core · dbt