scitex-decorators 0.1.0

Decorator library: numpy_fn/torch_fn/pandas_fn/xarray_fn/signal_fn type converters, caching, batching, deprecation — standalone module from the SciTeX ecosystem

scitex-decorators

Decorator library extracted from the SciTeX ecosystem as a standalone package.

Install

pip install scitex-decorators              # core (numpy only)
pip install "scitex-decorators[caching]"   # + joblib for cache_disk
pip install "scitex-decorators[torch]"     # + torch_fn / batch_torch_fn
pip install "scitex-decorators[all]"       # everything

API

import scitex_decorators as dec

# Type-conversion decorators (cast args before calling, restore after)
@dec.numpy_fn  ; @dec.torch_fn  ; @dec.pandas_fn  ; @dec.xarray_fn
@dec.signal_fn

# Caching (joblib for disk, dict for mem)
@dec.cache_disk        ; @dec.cache_disk_async    ; @dec.cache_mem

# Batching
@dec.batch_fn          ; @dec.batch_numpy_fn / batch_torch_fn / batch_pandas_fn

# Misc
@dec.deprecated(reason="…")
@dec.not_implemented
@dec.preserve_doc
@dec.timeout(seconds=10)
@dec.wrap

# Auto-ordering machinery (advanced)
dec.enable_auto_order() ; dec.disable_auto_order()

# Conversion helpers
dec.to_numpy(x) ; dec.to_torch(x)
dec.is_torch(x) ; dec.is_cuda(x) ; dec.is_nested_decorator(...)

Cache directory resolution

cache_disk / cache_disk_async resolve the cache dir in this order:

1. scitex.config.get_paths().function_cache (only if scitex is installed)
2. ${SCITEX_CACHE_DIR}/function_cache
3. ${XDG_CACHE_HOME}/scitex-decorators/function_cache
4. ~/.cache/scitex-decorators/function_cache

So the package works without the umbrella scitex installed.

Status

Standalone fork of scitex.decorators. Zero scitex.* runtime deps. The umbrella package's scitex.decorators import path is preserved via a sys.modules-alias bridge.

License

AGPL-3.0-only (see LICENSE).