Compute MinHashes in bulk. This method avoids unnecessary overhead when initializing many minhashes by reusing the initialized state. Args: b (Iterable): An Iterable of lists of bytes, each list is hashed in to one MinHash in the output.
(cls, b, **minhash_kwargs)
| 291 | |
| 292 | @classmethod |
| 293 | def bulk(cls, b, **minhash_kwargs): |
| 294 | '''Compute MinHashes in bulk. This method avoids unnecessary |
| 295 | overhead when initializing many minhashes by reusing the initialized |
| 296 | state. |
| 297 | |
| 298 | Args: |
| 299 | b (Iterable): An Iterable of lists of bytes, each list is |
| 300 | hashed in to one MinHash in the output. |
| 301 | minhash_kwargs: Keyword arguments used to initialize MinHash, |
| 302 | will be used for all minhashes. |
| 303 | |
| 304 | Returns: |
| 305 | List[datasketch.MinHash]: A list of computed MinHashes. |
| 306 | |
| 307 | Example: |
| 308 | |
| 309 | .. code-block:: python |
| 310 | |
| 311 | from datasketch import MinHash |
| 312 | data = [[b'token1', b'token2', b'token3'], |
| 313 | [b'token4', b'token5', b'token6']] |
| 314 | minhashes = MinHash.bulk(data, num_perm=64) |
| 315 | |
| 316 | ''' |
| 317 | return list(cls.generator(b, **minhash_kwargs)) |
| 318 | |
| 319 | @classmethod |
| 320 | def generator(cls, b, **minhash_kwargs): |