keyvi


Namekeyvi JSON
Version 0.7.4 PyPI version JSON
download
home_pagehttp://keyvi.org
SummaryPython package for keyvi
upload_time2025-10-26 21:26:00
maintainerNone
docs_urlNone
authorHendrik Muhs
requires_pythonNone
licenseASL 2.0
keywords fst
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            Keyvi - the short form for "Key value index" is a key value store (KVS) optimized for size and lookup speed. The usage of shared memory makes it scalable and resistant. The biggest difference to other stores is the underlying data structure based on [finite state machine](https://en.wikipedia.org/wiki/Finite-state_machine). Storage is very space efficient, fast and by design makes various sorts of approximate matching be it fuzzy string matching or geo highly efficient. The immutable FST data structure can be used stand-alone for static datasets. If you need online writes, you can use keyvi index, a _near realtime index_.

## Quick Start

Install keyvi with

```
pip3 install keyvi
```

create your first very simple index:

```
import keyvi.index
index = keyvi.index.Index("test-index")

index.Set('key', '{"answer": 42, "condition": "always"}')
index.Flush()
# get the entry for key
m = index.Get('key')
print(m.value)

# match fuzzy(levenshtein distance) with max edit distance 1, exact prefix 2
matches = index.GetFuzzy("kei", 1, 2)
print([m.matched_string for m in matches])
```

For more information visit the [docs](https://keyvidev.github.io/keyvi/index.html) and [project](http://keyvi.org) pages.

            

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    "description": "Keyvi - the short form for \"Key value index\" is a key value store (KVS) optimized for size and lookup speed. The usage of shared memory makes it scalable and resistant. The biggest difference to other stores is the underlying data structure based on [finite state machine](https://en.wikipedia.org/wiki/Finite-state_machine). Storage is very space efficient, fast and by design makes various sorts of approximate matching be it fuzzy string matching or geo highly efficient. The immutable FST data structure can be used stand-alone for static datasets. If you need online writes, you can use keyvi index, a _near realtime index_.\n\n## Quick Start\n\nInstall keyvi with\n\n```\npip3 install keyvi\n```\n\ncreate your first very simple index:\n\n```\nimport keyvi.index\nindex = keyvi.index.Index(\"test-index\")\n\nindex.Set('key', '{\"answer\": 42, \"condition\": \"always\"}')\nindex.Flush()\n# get the entry for key\nm = index.Get('key')\nprint(m.value)\n\n# match fuzzy(levenshtein distance) with max edit distance 1, exact prefix 2\nmatches = index.GetFuzzy(\"kei\", 1, 2)\nprint([m.matched_string for m in matches])\n```\n\nFor more information visit the [docs](https://keyvidev.github.io/keyvi/index.html) and [project](http://keyvi.org) pages.\n",
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