[Python] Cannot Connect from Python to Docker Containers Elastic Search and MongoDB [closed]

I have this code that sends user query to Kafka along with documents returned from elastic search container and business rules from MongoDb container , but the issue is documents are not getting retrieved from Mongo and elastic search connection that test fails , so If anyone can help with this , I think I probably have an issue in docker connectivity or something ...

import json
from flask import Flask, jsonify, request
from kafka_producer import send_user_query_to_kafka, send_business_rules_to_kafka,
send_elasticsearch_results_to_kafka
from kafka_consumer import consume_and_process
from pymongo import MongoClient
import pymongo
from elasticsearch import Elasticsearch
from bson.json_util import dumps

app = Flask(__name__)

MongoDB connection setup
def get_mongo_client():
# MongoDB is running in a Docker container
client = pymongo.MongoClient('mongodb://localhost:27017')
#testing mongodb connection
server_info = client.server_info() # This will raise an exception if unable to connect
print("Connected to MongoDB:", server_info)
return client


def get_business_rules():
"""
Retrieves business rules from MongoDB.

Returns:
- dict: The business rules retrieved from MongoDB.
"""

client = get_mongo_client()
db = client['businessrules']
collection = db['rules']

business_rules = list(collection.find()) # Retrieve all documents

# Print the extracted business rules
for rule in business_rules:
print(f"Rule ID: {rule['_id']}")
print(f"Name: {rule['name']}")
print(f"Description: {rule['description']}")
print(f"Conditions: {rule['conditions']}")
print(f"Action: {rule['mapping']['action']}")
print('---')

# If rules are found, return them, otherwise return a default message or empty dictionary
if business_rules:
return business_rules # Return the business rules as a dictionary
#return json.loads(dumps(business_rules))
#return [rule['data'] for rule in business_rules] # Return the business rules
else:
#return "no business rules found " # Empty dictionary if no business rules found
return []


def get_search_results(user_query):
#connecting to elastic search
es = Elasticsearch(
"http://elasticsearch-docker:9200",
basic_auth=("elastic", "elasticpfe25") # The credentials for the Elasticsearch
instance
)

# Check if Elasticsearch is connected
if es.ping():
print("Successfully connected to Elasticsearch!")
else:
print("Could not connect to Elasticsearch.")

es = Elasticsearch()
documents = es.search(index="university_index", body={"query": {"match": {"content":
user_query}}})
return documents

Sending


@app.route('/send_query', methods=['POST'])
def send_query():
user_query = request.json['query']

# Retrieve search results from Elasticsearch
documents = get_search_results(user_query)
print(f"Fetched {len(documents['hits']['hits'])} documents from Elasticsearch")
# Retrieve business rules from MongoDB
business_rules = get_business_rules()
print(f"Fetched {len(business_rules)} business rules from MongoDB")

# Send user query and business rules to Kafka
send_user_query_to_kafka(user_query)
send_business_rules_to_kafka(business_rules)
send_elasticsearch_results_to_kafka(documents)


if user_query:
processed_result = consume_and_process()

# Print the response data to the terminal/console
print("Response Data:", processed_result)

return jsonify({
"status": "success",
"message": "Query and Business rules sent to Kafka",
"query": user_query,
"business_rules": business_rules,
"processed_result": processed_result # Include the processed result from LLM
}), 200
else:
return jsonify({
"status": "error",
"message": "No query received"
}), 400


if __name__ == '__main__':
app.run(debug=True, port=5000)

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