{
    "info": {
        "author": "ruifengyun",
        "author_email": "rfyiamcool@163.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.0",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "#elasticsearch_parse\n=================\n\n\u9996\u5148\u6ce8\u660e\u4e0b\u672c\u9879\u76ee\u662f\u7531\u6765,\u5b66\u4e60Elasticsearch\u672c\u8eab\u662f\u6709\u4e9b\u75db\u82e6\u7684, \u6211\u4eec\u53ef\u4ee5\u719f\u7ec3\u7684\u7f16\u5199SQL \u3001 Mongodb\u8bed\u53e5\uff0c\u4f46\u5bf9\u4e8eElasticsearch Dsl\u8bed\u6cd5\u603b\u662f\u8499\u5934\uff0c\u4e00\u4e2a\u52b2\u7684\u7ffb\u627e\u7b14\u8bb0...  \n\u7b80\u5355\u8bf4 Elasticsearch Parse\u53ef\u4ee5\u8ba9\u4f60\u66f4\u5bb9\u6613\u7684\u4e0a\u624bES, \u4ed6\u7684\u529f\u80fd\u4e3b\u8981\u662f\u8bed\u53e5\u6620\u5c04, \u6709\u70b9ORM\u7684\u610f\u601d... \n\n\u6b64\u9879\u76ee\u7ee7\u627f\u4e8e`elasticsearch-dsl-py`,\u672c\u6765\u662f\u60f3fork\u5b50\u9879\u76ee,\u5f00\u53d1\u597d\u540e\u63d0\u4ea4pull request, \u4f46\u662f\u60f3\u5230\u6211\u8fd9\u8bed\u6cd5\u6620\u5c04\u7684\u529f\u80fd, \u5bf9\u4e8e\u5b98\u65b9\u6765\u8bf4\u4e0d\u662f\u5f88\u7a00\u7f55,\u7d22\u6027\u76f4\u63a5\u780d\u6389\u4e86 70% \u4ee3\u7801,\u7136\u540e\u4e2d\u95f4\u53c8\u52a0\u4e86\u4e00\u4e9b\u4f50\u6599, \u6700\u7ec8\u53ea\u662f\u4e3a\u4e86DSL\u8bed\u53e5\u6620\u5c04\u529f\u80fd ! \n\n\u6a21\u5757\u5b89\u88c5\u65b9\u6cd5:\n```\npip install elasticsearch_parse\n```\n\n\u4e0b\u9762\u6211\u4eec\u6765\u4f53\u9a8c\u4e0b\u5c01\u88c5\u540e\u7684es\u8bed\u6cd5\u89e3\u91ca\u5668.\n\n\u9996\u5148\u7528\u539f\u59cb\u7684DSL\u8bed\u6cd5\u64cd\u4f5c,\u4e00\u773c\u671b\u53bb\u4f1a\u6709\u4e9b\u9ebb\u70e6, \u624b\u5199\u8d77\u6765\u4f1a\u66f4\u9ebb\u70e6.  \n```\nfrom elasticsearch import Elasticsearch\nclient = Elasticsearch()\n\nresponse = client.search(\n    index=\"my-index\",\n    body={\n      \"query\": {\n        \"filtered\": {\n          \"query\": {\n            \"bool\": {\n              \"must\": [{\"match\": {\"title\": \"python\"}}],\n              \"must_not\": [{\"match\": {\"description\": \"beta\"}}]\n            }\n          },\n          \"filter\": {\"term\": {\"category\": \"search\"}}\n        }\n      },\n      \"aggs\" : {\n        \"per_tag\": {\n          \"terms\": {\"field\": \"tags\"},\n          \"aggs\": {\n            \"max_lines\": {\"max\": {\"field\": \"lines\"}}\n          }\n        }\n      }\n    }\n)\n\n```\n\n\u4e0b\u9762\u662f\u4f7f\u7528Elasticsearch_parse\u7684\u7528\u6cd5,\u8981\u591a\u7b80\u5355\u5c31\u591a\u7b80\u5355\n\n```\nfrom elasticsearch_parse import Search, Q\n\ns = Search(index=\"my-index\") \\\n    .filter(\"term\", blog=\"xiaorui.cc\") \\\n    .query(\"match\", author=\"ruifengyun\")   \\\n    .query(~Q(\"match\", face=\"good\"))\n\ns.aggs.bucket('per_tag', 'terms', field='tags')\n\nresponse = s.execute()\n```\n\u6211\u4eec\u5f97\u5230\u7684\u7ed3\u679c\u662f:\n```\n{\n    \"query\": {\n        \"filtered\": {\n            \"filter\": {\n                \"term\": {\n                    \"blog\": \"xiaorui.cc\"\n                }\n            },\n            \"query\": {\n                \"bool\": {\n                    \"must_not\": [\n                        {\n                            \"match\": {\n                                \"face\": \"good\"\n                            }\n                        }\n                    ],\n                    \"must\": [\n                        {\n                            \"match\": {\n                                \"author\": \"ruifengyun\"\n                            }\n                        }\n                    ]\n                }\n            }\n        }\n    },\n    \"aggs\": {\n        \"per_tag\": {\n            \"terms\": {\n                \"field\": \"tags\"\n            }\n        }\n    }\n}\n```\n\n\u6211\u4eec\u628a\u8bed\u6cd5\u7684\u7528\u6cd5\u7ed9\u8fc7\u4e00\u904d.\n```\ns = search.Search()\n```\n\n\u901a\u8fc7match\u67e5\u8be2,f\u5b57\u6bb5\u503c\u4e3a55\u7684\u6570\u636e\n```\ns.query('match', f=55)\n```\n\n\u65f6\u95f4\u8303\u56f4\n```\ns.query('range', ** {'@timestamp': {'lt': 'now'}})\n```\n\n\u5916\u56f4\u7684size\u7684\u63a7\u5236  \n```\ns = s.query('match', f=42)\ns[3].to_dict() {'query': {'match_all': {}}, 'from': 3, 'size': 1}\n```\n\n```\nassert s.to_dict(size=10) == {\"query\": {\"match\": {'f': 42}}, \"size\": 10}\n```\n\n\u5d4c\u5165\u5185\u90e8size\u63a7\u5236\n```\ns = search.Search.from_dict({\"size\": 5})\nassert {\n     \"query\": {\"match_all\": {}},\n     \"size\": 5\n} == s.to_dict()\n```\n\n\u5bf9\u4e8eaggs\u7684\u805a\u5408\u7684\u4f7f\u7528\n```\ns = s.query('match', f=42)\nassert {\"query\": {\"match\": {'f': 42}}} == s.to_dict()\nassert {\"query\": {\"match\": {'f': 42}}, \"size\": 10} == s.to_dict(size=10)\ns.aggs.bucket('per_tag', 'terms', field='f').metric('max_score', 'max', field='score')\nd = {\n    'aggs': {\n        'per_tag': {\n            'terms': {'field': 'f'},\n            'aggs': {'max_score': {'max': {'field': 'score'}}}\n         }\n    }\n```\n\n\n...",
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