starfix 0.4.0

Pure-Python implementation of starfix Arrow logical hasher

starfix-python

Pure-Python implementation of the starfix Arrow logical hasher.

Produces stable SHA-256 hashes of Arrow tables, record batches, and arrays that are:

• Column-order independent — reordering columns does not change the hash
• Batch-split independent — splitting data across batches does not change the hash
• Cross-language compatible — identical hashes to the Rust implementation

Installation

pip install starfix

Usage

import pyarrow as pa
from starfix import ArrowDigester

schema = pa.schema([
    pa.field("id", pa.int32(), nullable=False),
    pa.field("value", pa.float64(), nullable=True),
])

# Hash a full table
table = pa.table({"id": [1, 2, 3], "value": [1.1, 2.2, 3.3]}, schema=schema)
digest = ArrowDigester.hash_table(table)

# Streaming: feed record batches incrementally
digester = ArrowDigester(schema)
for batch in batches:
    digester.update(batch)
digest = digester.finalize()

Metadata hashing

By default, Arrow schema- and field-level metadata are excluded from the hash, preserving hash format 0.0.1 stability. Pass include_metadata=True to any entry point to include them:

# One-shot
digest = ArrowDigester.hash_table(table, include_metadata=True)

# Streaming
digester = ArrowDigester(schema, include_metadata=True)
for batch in batches:
    digester.update(batch)
digest = digester.finalize()

When include_metadata=True, adding or changing any metadata key or value on any field (including nested struct children and list element fields) produces a different hash. Metadata key ordering is deterministic — the hash is stable regardless of insertion order.

A schema with no metadata produces the same hash regardless of include_metadata (empty-metadata invariant).

License

MIT OR Apache-2.0