elasticsearchquerygenerator 2.0.0

Create Complex Elastic Search Query in Seconds Please see documentation for more details

---

[]

Elastic Search Query Generator

what is Elastic Search Query Generator ?

• While i was working with Elastic Search i found it very difficult to write complex queries as most of query are deep Nested

• Thats the reason i decided to make a helper class that can generate complex Elastic Search query in Seconds

• Library can be used to generate complex aggregation Query , Geo location Query (AND | OR | NOT ) any set of combination is possible

• in addition to all mentioned above you can also generate auto complete query in matter of seconds

• please see examples below on how to use this module.

• if you have any questions or suggestion please drop me an email at [e-mail]

• Learn More : https://www.youtube.com/watch?v=C-JKcMM6IXE&t=2548s

documentation :

• UML Diagram

• Constructor:

  • Size: How Many Documents should the Query Return
  • BucketName: is optional pass a name for Aggregation
  • Source: Basically what fields you want to return takes a List Argument source= [“f1”, “f2”, …..]
  • Min_score: used for filtering large documents average threshold is set to 0.5

• Field:

  • This is column or field you would like to search

• Boost:

  • If you want to Boost certain field pass a integer value

• Operation

  • There are four main operation you can pass * Should ( OR Operation) * Must (AND operation) * Filter (FILTER Result ) * Must_not (NOT Operation )

• Analyzer:

  • you can specify various analyzer such as stop etc

Installation

pip install elasticsearchquerygenerator

Usage

from elasticsearchquerygenerator.elasticsearchquerygenerator import ElasticSearchQuery
import json

def main():
    helper = ElasticSearchQuery(size=100, BucketName="MyBuckets")

    # match phrase
    query=helper.match_phrase(field="myfeild", value="myvalue", operation='must')

    # terms
    query=helper.terms(field="myfeild", value="myvalue", operation='must')

    # Feild Exists
    query = helper.exists(field='comp feild', operation="must")

    #Match
    query=helper.match(field="MMMMM", value="myvalue", operation='must')

    # Geo Queires
    query = helper.add_geoqueries(radius="100", lat="22", lon="33")

    # Aggreation
    helper.add_aggreation(aggregate_name="FirstName", field="field1",type='terms',sort='desc', size=3)
    helper.add_aggreation(aggregate_name="SecondName", field="field2",type='terms',sort='desc', size=3)
    helper.add_aggreation(aggregate_name="ThirdName", field="field3",type='terms',sort='desc', size=3)
    query = helper.complete_aggreation()
    query = helper.query_string(default_field="DEFAULT",query="X OR  Y",operation='must')

    query = helper.add_geo_aggreation(field="AAAA", lat="22", lon="43",aggregate_name="my_distance")

    print(json.dumps(query, indent=3))


if __name__ == "__main__":
    main()

{
   "_source": [],
   "size": 100,
   "min_score": 0.5,
   "query": {
      "bool": {
         "must": [
            {
               "match_phrase": {
                  "myfeild": {
                     "query": "myvalue"
                  }
               }
            },
            {
               "match_phrase": {
                  "myfeild": {
                     "query": "myvalue"
                  }
               }
            },
            {
               "term": {
                  "myfeild": "myvalue"
               }
            },
            {
               "exists": {
                  "field": "comp feild"
               }
            },
            {
               "match": {
                  "MMMMM": {
                     "query": "myvalue"
                  }
               }
            },
            {
               "match": {
                  "MMMMM": {
                     "query": "myvalue"
                  }
               }
            },
            {
               "query_string": {
                  "default_field": "DEFAULT",
                  "query": "X OR  Y"
               }
            }
         ],
         "filter": [
            {
               "geo_distance": {
                  "distance": "100mi",
                  "null": {
                     "lat": "22",
                     "lon": "33"
                  }
               }
            }
         ],
         "should": [],
         "must_not": []
      }
   },
   "aggs": {
      "FirstName": {
         "terms": {
            "field": "field1",
            "order": {
               "_count": "desc"
            },
            "size": 3
         }
      },
      "SecondName": {
         "terms": {
            "field": "field2",
            "order": {
               "_count": "desc"
            },
            "size": 3
         }
      },
      "ThirdName": {
         "terms": {
            "field": "field3",
            "order": {
               "_count": "desc"
            },
            "size": 3
         }
      },
      "my_distance": {
         "geo_distance": {
            "field": "AAAA",
            "origin": "22,43",
            "unit": "mi",
            "ranges": [
               {
                  "to": 0
               },
               {
                  "from": 0,
                  "to": 25
               },
               {
                  "from": 25,
                  "to": 50
               },
               {
                  "from": 50,
                  "to": 75
               },
               {
                  "from": 75,
                  "to": 100
               },
               {
                  "from": 100
               }
            ]
         }
      }
   }
}

Example 2

from elasticsearchquerygenerator.elasticsearchquerygenerator import ElasticSearchQuery
import json

def autocomplete():
    helper = ElasticSearchQuery(size=0, BucketName="MyBuckets")
    query  = helper.autocomplete_1(field="title",value="n", size=25,sort='desc')
    print(json.dumps(query, indent=3))


if __name__ == "__main__":
    main(autocomplete

{
   "_source": [],
   "size": 0,
   "min_score": 0.5,
   "query": {
      "bool": {
         "must": [
            {
               "match_phrase_prefix": {
                  "title": {
                     "query": "n"
                  }
               }
            }
         ],
         "filter": [],
         "should": [],
         "must_not": []
      }
   },
   "aggs": {
      "auto_complete": {
         "terms": {
            "field": "title",
            "order": {
               "_count": "desc"
            },
            "size": 25
         }
      }
   }
}

i would be adding more examples and making it better and better

Authors

Soumil Nitin Shah

• Excellent experience of building scalable and high-performance Software Applications combining distinctive skill sets in Internet of Things (IoT), Machine Learning and Full Stack Web Development in Python.

Bachelor in Electronic Engineering | Masters in Electrical Engineering | Master in Computer Engineering |

• Website : https://soumilshah.herokuapp.com
• Github: https://github.com/soumilshah1995
• Linkedin: https://www.linkedin.com/in/shah-soumil/
• Blog: https://soumilshah1995.blogspot.com/
• Youtube : https://www.youtube.com/channel/UC_eOodxvwS_H7x2uLQa-svw?view_as=subscriber
• Facebook Page : https://www.facebook.com/soumilshah1995/
• Email : [e-mail]

License

This project is licensed under the MIT License - see the LICENSE.md file for details