Metadata-Version: 2.4
Name: thds.mops
Version: 3.10.20251106231221
Summary: ML Ops tools for Trilliant Health
Author-email: Trilliant Health <info@trillianthealth.com>
Project-URL: Repository, https://github.com/TrilliantHealth/ds-monorepo
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: azure-core
Requires-Dist: azure-identity
Requires-Dist: azure-storage-file-datalake
Requires-Dist: cachetools
Requires-Dist: importlib_metadata>=3.6; python_version < "3.10"
Requires-Dist: tblib~=2.0
Requires-Dist: thds-adls
Requires-Dist: thds-core
Requires-Dist: thds-humenc
Requires-Dist: thds-termtool
Requires-Dist: tomli
Provides-Extra: k8s
Requires-Dist: kubernetes!=32.0.0,>=18.20; extra == "k8s"

`mops` is a Python library for ML Operations.

Jump to
[Quickstart](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/docs/quickstart.adoc)
if you ~~are impatient~~ prefer examples, like me!

`mops` solves for four core design goals:

- [Efficient](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/docs/optimizations.adoc)
  transfer of
  [pure](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/docs/pure_functions.adoc)
  function execution to
  [remote](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/docs/remote.adoc)
  execution environments with more &| different compute resources

- Everything is written in standard Python with basic Python primitives; no frameworks, YAML, DSLs...

- [Memoization](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/docs/memoization.adoc)
  — i.e. _reproducibility and fault tolerance_ — for individual functions.

- Droppability: `mops` shouldn't entangle itself with your code, and you should always be able to run
  your code with or without `mops` in the loop.

It is used by
[decorating or wrapping your pure function and then calling it](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/docs/magic.adoc)
like a normal function.

### read the docs

[Browse our full documentation here.](https://github.com/TrilliantHealth/trilliant-data-science/blob/main/libs/mops/README.adoc)
