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Sources can now wrap a loader function in BatchLoader(loader_fn, batch_size) and share the instance across DatasetResources that should be batched together. Ingestify groups those resources, chunks them into groups of batch_size, wraps each chunk in a BatchTask, and calls the loader_fn once per batch with lists of file_resources / current_files / dataset_resources. load_file() now passes dataset_resource to loaders that accept it (signature introspection with lru_cache, so existing loaders continue to work without changes).
Different BatchTasks sharing the same loader write/read different keys (id(file_resource)); CPython dict operations on distinct keys are atomic under the GIL.
Uses MD5 hash for stable distribution when the value cannot be cast to int. Integer values continue to use direct modulo.
Prevents special characters, spaces, $, unicode etc. from causing issues in GCS/S3 paths. Simple values like integers stay readable.
Transliterates unicode (ü→u, é→e), strips non-alphanumeric chars, takes the first N characters. Falls back to '_' for empty results (e.g. all-special-char or CJK-only strings).
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