Install & Compatibility
Where this runs
tested against v0.0.2 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
Transform
✓ from fasttransform import Transform
✗ from fasttransform import Transform
This quickstart demonstrates how to define a simple transform using the `@Transform` decorator, create a reversible transform by passing encode and decode functions, and compose multiple transforms into a `Pipeline`.
from fasttransform import Transform, Pipeline
# Create a simple transform using a decorator
@Transform
def add_one(x: int) -> int:
return x + 1
# Create a reversible transform
def multiply_by_two_encodes(x: int) -> int:
return x * 2
def multiply_by_two_decodes(x: int) -> int:
return x // 2
MultiplyByTwo = Transform(multiply_by_two_encodes, multiply_by_two_decodes)
# Use a Pipeline to chain transforms
my_pipeline = Pipeline([add_one, MultiplyByTwo])
# Demonstrate usage
result_encoded = my_pipeline(5)
print(f"Encoded result: {result_encoded}") # Expected: (5 + 1) * 2 = 12
result_decoded = MultiplyByTwo.decode(result_encoded)
print(f"Decoded result (MultiplyByTwo): {result_decoded}") # Expected: 12 // 2 = 6
Debug
Known issues
breakingMigration from `fastcore.dispatch`'s `typedispatch` to `plum-dispatch` may introduce `AmbiguousLookupError` where `fastcore` would silently pick a function. `plum` is stricter to prevent unexpected behavior.fixReview type dispatch definitions to ensure unique matches for argument types, or explicitly specify the desired function.
affects: All versions (due to underlying dependency change)
breakingThe `Pipeline` class has moved from `fastcore` to `fasttransform`. Older `fastai` versions (specifically 2.7.x) might expect `Pipeline` in `fastcore`, leading to `ModuleNotFoundError` when loading models or using certain functionalities.fixEnsure `fasttransform` is installed and `Pipeline` is imported directly from `fasttransform`. If using `fastai` with older saved models, consider retraining or upgrading `fastai` and `fasttransform` to compatible versions. Downgrading `fastai` to v2.7.x was a workaround for some users, but generally updating is recommended.
affects: Potentially `fastai` versions 2.8.0 and higher when interacting with older saved models or explicit imports.
gotchaWhen implementing custom reversible transforms, remember to define both `encodes` and `decodes` methods for the `Transform` class or pass both functions to the `Transform` constructor. Forgetting the `decodes` method will prevent reversibility.fixAlways implement or provide the inverse function(s) (`decodes`) for any transform intended to be reversible.
affects: All versions
gotchaFasttransform's type-based multiple dispatch, powered by `plum-dispatch`, will return the original input if no matching type annotation is found for an argument. This can lead to unexpected no-op behavior if types are not correctly annotated or handled.fixCarefully annotate types in `encodes`/`decodes` methods or decorator arguments. Provide a default implementation without type hints if a fallback behavior is desired for unhandled types.
affects: All versions
gotchaThere is another unrelated library named `fastflowtransform` on PyPI. Ensure you are installing and importing the correct library (`fasttransform`) for data pipeline transformations described here to avoid confusion.fixDouble-check the package name during installation (`pip install fasttransform`) and imports (`from fasttransform import ...`).
affects: All versions
Upgrade
Version history
0.0.2latest on PyPI · released Apr 18, 2025
Audit
Dependencies
plum-dispatchrequiredProvides the multiple dispatch functionality used internally for type-based specialization.