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About The Project


You can use it for free 👉 Demo

Dashboard that can analyze/monitor the trends of entertainment characteristics occurring in complex situations

Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.


This is an example of how to list things you need to use the software and how to install them.

  • Python
Python >= 3


pip install tremo
  • Homebrew
/usr/bin/ruby -e "$(curl -fsSL"
  • ElasticSearch, Kibana
brew install elasticsearch, kibana


  • Run with/without ElasticSearch
from import run

result = run(elastic_search=False)

The run function collects trends, news data, and keywords from the top 10. The data type of result is list of 10 lengths of the dictionary.

  • Example of result data
from import run

result = run(elastic_search=False)
    "ranking": 1,
    "word": "걸캅스",
    "category": [
    "related_search_word": [
      "영화 걸캅스",
      "걸캅스 주우재",
      "라미란 이성경",
      "이성경 라미란",
      "걸캅스 이레",
      "걸캅스 하정우",
      "정직한 후보"
    "related_keyword": [
    "news_title": "[집에서 볼만한 영화추천] 걸캅스, 검사외전, 스타트렉 다크니스&비욘드",
    "timestamp": "2020-08-17T03:35:28.942994"
  • Repeat with/without ElasticSearch
from import repeat

repeat(elastic_search="localhost:9200", interval_second=600)

The repeat function executes the run function by thread timer every interval_second

elastic_search and interval_second default value is False and 600

If you set elastic_search to {{YOUR_PATH_TO_ES}}, You can use the dashboard visualized in Kibana for the data stored in ElasticSearch.

  • import kibana dash board

You can import our JSON file from Kibana UI under Management > Saved Objects > Import.

1. Click Import.
2. Navigate to the JSON file that represents the objects to import.
3. Import ./kibana_import/{version}.ndjson file
4. Indicate whether to overwrite objects already in Kibana.
5. Click Import.

If you import json file, you can use dash board like this


Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/contribution)
  3. Commit your Changes (git commit -m 'Add some contribution')
  4. Push to the Branch (git push origin feature/contribution)
  5. Open a Pull Request


Distributed under the MIT License. See LICENSE for more information.


Jihoon Kang - [email protected]

Project Link:

Linkedin: LinkedIn

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