{
    "info": {
        "author": "Ahmet A. Ak\u0131n, Mehmet D. Ak\u0131n",
        "author_email": "ahmetaa@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "License :: OSI Approved :: Apache Software License",
            "Natural Language :: Turkish",
            "Operating System :: OS Independent",
            "Programming Language :: Java",
            "Programming Language :: Python",
            "Topic :: Text Processing"
        ],
        "description": "# Zemberek gRPC\n\n__Latest version 0.16.0__\n\nZemberek-NLP provides some of its functions via a remote procedure call framework called gRPC. gRPC is a high performance, open-source universal RPC framework. Once Zemberek-NLP gRPC server is started, other applications can access remote services natively via automatically generated client libraries.\n\nhttps://github.com/ahmetaa/zemberek-nlp\n\n## Start gRPC server with docker\n\nYou can use it from directly in your computer or run with in docker container.\n\nhttps://hub.docker.com/r/ryts/zemberek-grpc\n\nRun with docker\n```\ndocker run -d --rm -p 6789:6789 --name zemberek-grpc ryts/zemberek-grpc\n```\n\nCheck logs\n```\ndocker logs -f zemberek-grpc\n```\n\n## Install library and example\n\n```shell\npip install zemberek-grpc\n```\n\nPython Client Example\n\n```python\n#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nimport sys\n\nimport grpc\n\nimport zemberek_grpc.language_id_pb2 as z_langid\nimport zemberek_grpc.language_id_pb2_grpc as z_langid_g\nimport zemberek_grpc.normalization_pb2 as z_normalization\nimport zemberek_grpc.normalization_pb2_grpc as z_normalization_g\nimport zemberek_grpc.preprocess_pb2 as z_preprocess\nimport zemberek_grpc.preprocess_pb2_grpc as z_preprocess_g\nimport zemberek_grpc.morphology_pb2 as z_morphology\nimport zemberek_grpc.morphology_pb2_grpc as z_morphology_g\n\nchannel = grpc.insecure_channel('localhost:6789')\n\nlangid_stub = z_langid_g.LanguageIdServiceStub(channel)\nnormalization_stub = z_normalization_g.NormalizationServiceStub(channel)\npreprocess_stub = z_preprocess_g.PreprocessingServiceStub(channel)\nmorphology_stub = z_morphology_g.MorphologyServiceStub(channel)\n\ndef find_lang_id(i):\n    response = langid_stub.Detect(z_langid.LanguageIdRequest(input=i))\n    return response.langId\n\ndef tokenize(i):\n    response = preprocess_stub.Tokenize(z_preprocess.TokenizationRequest(input=i))\n    return response.tokens\n\ndef normalize(i):\n    response = normalization_stub.Normalize(z_normalization.NormalizationRequest(input=i))\n    return response\n\ndef analyze(i):\n    response = morphology_stub.AnalyzeSentence(z_morphology.SentenceAnalysisRequest(input=i))\n    return response;\n\ndef fix_decode(text):\n    \"\"\"Pass decode.\"\"\"\n    if sys.version_info < (3, 0):\n        return text.decode('utf-8')\n    else:\n        return text\n\ndef run():\n    lang_detect_input = 'merhaba d\u00fcnya'\n    lang_id = find_lang_id(lang_detect_input)\n    print(\"Language of [\" + fix_decode(lang_detect_input) + \"] is: \" + lang_id)\n\n    print(\"\")\n    tokenization_input = 'Merhaba d\u00fcnya!'\n    print('Tokens for input : ' + fix_decode(tokenization_input))\n    tokens = tokenize(tokenization_input)\n    for t in tokens:\n        print(t.token + ':' + t.type)\n\n    print(\"\")\n    normalization_input = 'Mrhaba dnya'\n    print('Normalization result for input : ' + fix_decode(normalization_input))\n    n_response = normalize(normalization_input)\n    if n_response.normalized_input:\n        print(n_response.normalized_input)\n    else:\n        print('Problem normalizing input : ' + n_response.error)\n\n    print(\"\")\n    analysis_input = 'Kavanozun kapa\u011f\u0131n\u0131 a\u00e7amad\u0131m.'\n    print('Analysis result for input : ' + fix_decode(analysis_input))\n    analysis_result = analyze(analysis_input)\n    for a in analysis_result.results:\n        best = a.best\n        lemmas = \"\"\n        for l in best.lemmas:\n          lemmas = lemmas + \" \" + l\n        print(\"Word = \" + a.token + \", Lemmas = \" + lemmas + \", POS = [\" + best.pos + \"], Full Analysis = {\" + best.analysis + \"}\")\n\n\nif __name__ == '__main__':\n    run()\n```\n\n",
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        "home_page": "https://github.com/ahmetaa/zemberek-nlp",
        "keywords": "t\u00fcrk\u00e7e turkish language zemberek text",
        "license": "Apache License 2.0",
        "maintainer": "",
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        "name": "zemberek-grpc",
        "package_url": "https://pypi.org/project/zemberek-grpc/",
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