Metadata-Version: 2.4 Name: preshed Version: 3.0.13 Summary: Cython hash table that trusts the keys are pre-hashed Home-page: https://github.com/explosion/preshed Author: Explosion Author-email: contact@explosion.ai License: MIT Classifier: Environment :: Console Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Science/Research Classifier: License :: OSI Approved :: MIT License Classifier: Operating System :: POSIX :: Linux Classifier: Operating System :: MacOS :: MacOS X Classifier: Operating System :: Microsoft :: Windows Classifier: Programming Language :: Cython Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3.10 Classifier: Programming Language :: Python :: 3.11 Classifier: Programming Language :: Python :: 3.12 Classifier: Programming Language :: Python :: 3.13 Classifier: Programming Language :: Python :: 3.14 Classifier: Programming Language :: Python :: Free Threading :: 2 - Beta Classifier: Topic :: Scientific/Engineering Requires-Python: >=3.9,<3.15 Description-Content-Type: text/markdown License-File: LICENSE Requires-Dist: cymem<2.1.0,>=2.0.2 Requires-Dist: murmurhash<1.1.0,>=0.28.0 Dynamic: author Dynamic: author-email Dynamic: classifier Dynamic: description Dynamic: description-content-type Dynamic: home-page Dynamic: license Dynamic: license-file Dynamic: requires-dist Dynamic: requires-python Dynamic: summary # preshed: Cython Hash Table for Pre-Hashed Keys Simple but high performance Cython hash table mapping pre-randomized keys to `void*` values. Inspired by [Jeff Preshing](http://preshing.com/20130107/this-hash-table-is-faster-than-a-judy-array/). All Python APIs provded by the `BloomFilter` and `PreshMap` classes are thread-safe on both the GIL-enabled build and the free-threaded build of Python 3.14 and newer. If you use the C API or the `PreshCounter` class, you must provide external synchronization if you use the data structures by this library in a multithreaded environment. [![tests](https://github.com/explosion/preshed/actions/workflows/tests.yml/badge.svg)](https://github.com/explosion/preshed/actions/workflows/tests.yml) [![pypi Version](https://img.shields.io/pypi/v/preshed.svg?style=flat-square&logo=pypi&logoColor=white)](https://pypi.python.org/pypi/preshed) [![conda Version](https://img.shields.io/conda/vn/conda-forge/preshed.svg?style=flat-square&logo=conda-forge&logoColor=white)](https://anaconda.org/conda-forge/preshed) [![Python wheels](https://img.shields.io/badge/wheels-%E2%9C%93-4c1.svg?longCache=true&style=flat-square&logo=python&logoColor=white)](https://github.com/explosion/wheelwright/releases) ## Installation ```bash pip install preshed --only-binary preshed ``` Or with conda: ```bash conda install -c conda-forge preshed ``` ## Usage ### PreshMap A hash map for pre-hashed keys, mapping `uint64` to `uint64` values. ```python from preshed.maps import PreshMap map = PreshMap() # create with default size map = PreshMap(initial_size=1024) # create with initial capacity (must be power of 2) map[key] = value # set a value value = map[key] # get a value (returns None if missing) value = map.pop(key) # remove and return a value del map[key] # delete a key key in map # membership test len(map) # number of entries for key in map: # iterate over keys pass for key, value in map.items(): # iterate over key-value pairs pass for value in map.values(): # iterate over values pass ``` ### BloomFilter A probabilistic set for fast membership testing of integer keys. ```python from preshed.bloom import BloomFilter bloom = BloomFilter(size=1024, hash_funcs=23) # explicit parameters bloom = BloomFilter.from_error_rate(10000, error_rate=1e-4) # auto-sized bloom.add(42) # add a key 42 in bloom # membership test (may have false positives) data = bloom.to_bytes() # serialize bloom.from_bytes(data) # deserialize in-place ``` ### PreshCounter A counter backed by a hash map, for counting occurrences of `uint64` keys. ```python from preshed.counter import PreshCounter counter = PreshCounter() counter.inc(key, 1) # increment key by 1 count = counter[key] # get current count len(counter) # number of buckets for key, count in counter: # iterate over entries pass counter.smooth() # apply Good-Turing smoothing prob = counter.prob(key) # get smoothed probability ``` ### Cython API All classes expose a C-level API via `.pxd` files for use in Cython extensions. The low-level `MapStruct` and `BloomStruct` functions operate on raw structs and can be called without the GIL: ```cython from preshed.maps cimport PreshMap, map_get, map_set, map_iter, key_t from preshed.bloom cimport BloomFilter, bloom_add, bloom_contains cdef PreshMap table = PreshMap() # Low-level nogil access (requires external synchronization) cdef void* value with nogil: value = map_get(table.c_map, some_key) ```