Elastic Search + Mongo in Python

db_utils.py

from pymongo import MongoClient
from elasticsearch import Elasticsearch

class MongoElasticCache:
    def __init__(self, mongo_uri, mongo_db, mongo_collection, es_host, es_index):
        self.mongo_client = MongoClient(mongo_uri)
        self.mongo_db = self.mongo_client[mongo_db]
        self.mongo_collection = self.mongo_db[mongo_collection]
        
        self.es_client = Elasticsearch([es_host])
        self.es_index = es_index

    def save_and_cache(self, data):
        # Save data to MongoDB
        mongo_id = self.mongo_collection.insert_one(data).inserted_id
        data["_id"] = mongo_id

        # Cache data in Elasticsearch
        self.es_client.index(index=self.es_index, id=str(mongo_id), body=data)

    def search(self, query):
        # Search Elasticsearch
        res = self.es_client.search(index=self.es_index, body=query)
        return res['hits']['hits']

test.py

mongo_uri = "mongodb://username:password@localhost:27017"
mongo_db = "test_db"
mongo_collection = "test_collection"

es_host = "localhost:9200"
es_index = "test_index"

cache = MongoElasticCache(mongo_uri, mongo_db, mongo_collection, es_host, es_index)

# Save and cache data
data = {
    "title": "Example",
    "description": "This is an example document."
}
cache.save_and_cache(data)

# Search cached data
query = {
    "query": {
        "match": {
            "title": "Example"
        }
    }
}
results = cache.search(query)
print(results)