taskferry
A portable execution layer for Python.
Taskferry models units of work, chooses the right kind of execution, and routes them to engines that already exist. It is not a task queue, not a worker system, not a scheduler and not a workflow engine.
pip install taskferry
That installs nothing else. No Django, no PostgreSQL driver, no Redis client, no cloud SDK. The distribution declares zero dependencies and CI proves it in a bare virtualenv on every commit.
from taskferry import Taskferry
runtime = Taskferry.local()
def add(a: int, b: int) -> int:
return a + b
execution = runtime.inline.submit(add, 20, 22)
assert execution.result().value == 42
Three primitives
runtime.inline.submit(add, 20, 22) # now, in this process
runtime.tasks.submit("myapp.tasks:send_email", 42) # later, on an engine
runtime.jobs.submit("build-cog", image="gdal:latest") # a container, to completion
A Job is not "a Task that takes longer": it has its own image, its own resource envelope and its own lifecycle, and it returns an exit code rather than a Python value.
Built-in backends
| Backend | Kind | Use |
|---|---|---|
inline |
inline | tests, notebooks, CLIs, small tools |
thread |
task | development, single-process applications |
process |
task | rehearsing what a real worker does to your code |
subprocess |
job | local batch workloads |
None of them is a queue. They are not durable, not visible across processes, and they lose pending work on restart — which is stated plainly in their docstrings and in their capability sets. For production, route at a real engine; that is a configuration change.
Adapters
Install the engine you use. Each registers itself through the taskferry.backends
entry-point group, so naming it in configuration is all it takes.
pip install taskferry-procrastinate # PostgreSQL-backed tasks
pip install taskferry-cloudtasks # push-based serverless tasks
pip install taskferry-cloudrun # serverless container jobs
pip install taskferry-jobs # AWS Batch, Kubernetes, Azure Container Apps
pip install taskferry-django # django.tasks integration
CLI
taskferry backends
taskferry capabilities pg
taskferry route --kind job --profile gpu
taskferry doctor
Documentation
Full documentation, ADRs and the migration guide live in the repository.
License
Apache-2.0.
Release files for taskferry 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| taskferry-0.2.0.tar.gz | 82.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| taskferry-0.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 189.8 kB
Release files / taskferry-0.2.0.tar.gz
| Download URL | taskferry-0.2.0.tar.gz |
|---|---|
| Size | 82.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / taskferry-0.2.0-py3-none-any.whl
| Download URL | taskferry-0.2.0-py3-none-any.whl |
|---|---|
| Size | 107.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 18, 2026.
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