Python client for Vektonn

Related tags

Third-party APIs Wrappersvektonn-client-python
Overview

Python client for Vektonn

CI version Supported Python Versions license

Installation

Install the latest version:

$ pip install vektonn

Install specific version:

$ pip install vektonn==1.2.3

Upgrade to the latest version:

$ pip install --upgrade vektonn

Usage

Having Vektonn running on localhost:8081 and configured for QuickStart examples one can access it with synchronous Python client:

from vektonn import Vektonn

vektonn_client = Vektonn('http://localhost:8081')

or asynchronous one:

from vektonn import VektonnAsync

vektonn_client_async = VektonnAsync('http://localhost:8081')

To upload data to Vektonn use upload() method:

from vektonn.dtos import AttributeDto, AttributeValueDto, InputDataPointDto, VectorDto

vektonn_client.upload(
    data_source_name='QuickStart.Source',
    data_source_version='1.0',
    input_data_points=[
        InputDataPointDto(
            attributes=[
                AttributeDto(key='id', value=AttributeValueDto(int64=1)),
                AttributeDto(key='payload', value=AttributeValueDto(string='sample data point')),
            ],
            vector=VectorDto(is_sparse=False, coordinates=[3.14, 2.71]))
    ])

To query Vektonn for k nearest data points to the given query_vector use search() method:

from vektonn.dtos import VectorDto, SearchQueryDto

k = 10
query_vector = VectorDto(is_sparse=False, coordinates=[1.2, 3.4])

search_results = vektonn_client.search(
    index_name='QuickStart.Index',
    index_version='1.0',
    search_query=SearchQueryDto(k=k, query_vectors=[query_vector]))

print(f'For query vector {query_vector.coordinates} {k} nearest data points are:')
for fdp in search_results[0].nearest_data_points:
    attrs = {x.key : x.value for x in fdp.attributes}
    distance, vector, dp_id, payload = fdp.distance, fdp.vector, attrs['id'].int64, attrs['payload'].string
    print(f' - "{payload}" with id = {dp_id}, vector = {vector.coordinates}, distance = {distance}')
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Comments
  • Optimize DTOs json serialization

    Optimize DTOs json serialization

    test_perf_serialize run shows that VektonnBaseModel.json() is a huge bottleneck:

    ----------------------------- Captured stdout call -----------------------------
         28285893 function calls in 25.275 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
   118351   15.430    0.000   21.607    0.000 dtos.py:17(json)
   118351    3.108    0.000    3.522    0.000 test_dtos_perf.py:55(to_idp_fast)
 12781908    2.509    0.000    2.509    0.000 {built-in method _abc._abc_instancecheck}
 12781908    2.122    0.000    4.630    0.000 abc.py:96(__instancecheck__)
   118351    0.691    0.000    0.691    0.000 {orjson.dumps}
   118351    0.414    0.000    0.414    0.000 {method 'tolist' of 'numpy.ndarray' objects}
   118351    0.189    0.000    0.552    0.000 typing.py:802(__getitem__)
   118351    0.130    0.000    0.317    0.000 typing.py:255(inner)
   236702    0.113    0.000    0.1[65](https://github.com/vektonn/vektonn-client-python/runs/5082861448?check_suite_focus=true#step:6:65)    0.000 <frozen importlib._bootstrap>:389(parent)
   118351    0.076    0.000    0.815    0.000 utils.py:13(orjson_dumps)
   23[67](https://github.com/vektonn/vektonn-client-python/runs/5082861448?check_suite_focus=true#step:6:67)02    0.075    0.000    0.104    0.000 typing.py:329(__hash__)
        1    0.071    0.071    3.605    3.605 test_dtos_perf.py:42(construct)
        1    0.063    0.063   21.671   21.671 test_dtos_perf.py:37(serialize)
   118351    0.059    0.000    0.083    0.000 typing.py:720(__hash__)
   355053    0.052    0.000    0.052    0.000 {built-in method builtins.hash}
   236[70](https://github.com/vektonn/vektonn-client-python/runs/5082861448?check_suite_focus=true#step:6:70)2    0.051    0.000    0.051    0.000 {method 'rpartition' of 'str' objects}
   11[83](https://github.com/vektonn/vektonn-client-python/runs/5082861448?check_suite_focus=true#step:6:83)51    0.047    0.000    0.047    0.000 {method 'decode' of 'bytes' objects}
   236702    0.027    0.000    0.027    0.000 {built-in method builtins.isinstance}
   118351    0.019    0.000    0.019    0.000 {built-in method builtins.len}
   118351    0.016    0.000    0.016    0.000 typing.py:1149(cast)
   118351    0.012    0.000    0.012    0.000 {method 'append' of 'list' objects}
        1    0.000    0.000    0.000    0.000 cProfile.py:133(__exit__)
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
    help wanted 
    opened by AndrewKostousov 2
Releases(v0.7.1)

  • v0.7.1(Feb 25, 2022)

    • Speed up VektonnBaseModel.json() for Vector model (see #3)

    Full Changelog: https://github.com/vektonn/vektonn-client-python/compare/v0.7.0...v0.7.1

    Source code(tar.gz)
    Source code(zip)

  • v0.7.0(Feb 25, 2022)

    • Allow to specify request timeouts
    • Introduce retrieveVectors parameter to speed things up when there is no need in nearest vectors themselves

    Full Changelog: https://github.com/vektonn/vektonn-client-python/compare/v0.6.0...v0.7.0

    Source code(tar.gz)
    Source code(zip)

  • v0.6.0(Jan 19, 2022)

    What's Changed

    • Remove 'Dto' suffix form DTOs' names by @streamoverflow in https://github.com/vektonn/vektonn-client-python/pull/2

    New Contributors

    • @streamoverflow made their first contribution in https://github.com/vektonn/vektonn-client-python/pull/2

    Full Changelog: https://github.com/vektonn/vektonn-client-python/compare/v0.5.4...v0.6.0

    Source code(tar.gz)
    Source code(zip)

  • v0.5.4(Nov 23, 2021)

  • v0.5.3(Nov 23, 2021)

  • v0.5.2(Nov 23, 2021)

  • v0.5.1(Nov 23, 2021)

    • Support attribute values with floating-point numeric data type

    Full Changelog: https://github.com/vektonn/vektonn-client-python/compare/v0.5.0...v0.5.1

    Source code(tar.gz)
    Source code(zip)

  • v0.5.0(Nov 23, 2021)

Owner
Vektonn
An open source vector search solution
Vektonn
GitHub Repository
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