https://github.com/saransh-cpp/memetastic-backend

Created for Elasticsearch X Code for Cause Hackathon. This is the backend for my MemeTastic Application. (Winner for the hackathon)
https://github.com/saransh-cpp/memetastic-backend

axios backend backend-api cicd elasticsearch express github-actions hackathon kibana ngrams nodejs

Last synced: about 14 hours ago
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Created for Elasticsearch X Code for Cause Hackathon. This is the backend for my MemeTastic Application. (Winner for the hackathon)

• Host: GitHub
• URL: https://github.com/saransh-cpp/memetastic-backend
• Owner: Saransh-cpp
• Created: 2021-05-23T10:27:27.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2021-06-11T10:47:58.000Z (over 3 years ago)
• Last Synced: 2024-12-30T22:15:02.660Z (13 days ago)
• Topics: axios, backend, backend-api, cicd, elasticsearch, express, github-actions, hackathon, kibana, ngrams, nodejs
• Language: JavaScript
• Homepage:
• Size: 26.4 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# MemeTastic-backend

Created for Elasticsearch X Code for Cause Hackathon. (Winner for the hackthon - [devpost project](https://devpost.com/software/memetastic))

This is the backend for my MemeTastic Application.

## How it works

- Scrapes top 100 memes from subreddit `memes` using reddit's public API.

- Adds the `link` and the `title` of those 100 memes in `elasticsearch` which can then be visualised using `kibana`.

- `Elasticsearch` has been hosted on `Google Cloud`.

- The first two steps are repeated after every 30 minutes using a CI/CD pipeline created using `GitHub Actions` to make sure that the Application stays up-to-date.

## Ngrams

- This also uses ngrams, implemetation is given below (implemeted using `kibana`)

```JSON

PUT dankmemes

{

  "settings": {

    "analysis": {

      "analyzer": {

        "autocomplete": {

          "tokenizer": "autocomplete",

          "filter": [

            "lowercase"

          ]

        },

        "autocomplete_search": {

          "tokenizer": "lowercase"

        }

      },

      "tokenizer": {

        "autocomplete": {

          "type": "edge_ngram",

          "min_gram": 1,

          "max_gram": 10,

          "token_chars": [

            "letter"

          ]

        }

      }

    }

  },

  "mappings": {

    "properties": {

      "title": {

        "type": "text",

        "analyzer": "autocomplete",

        "search_analyzer": "autocomplete_search"

      }

    }

  }

}

```