https://github.com/asmrcodez-yt/posthunter
https://github.com/asmrcodez-yt/posthunter
elastic gui posthunter python search telegram
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/asmrcodez-yt/posthunter
- Owner: AsmrCodeZ-YT
- Created: 2025-04-29T16:06:55.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-29T17:03:43.000Z (about 1 year ago)
- Last Synced: 2025-04-29T18:22:27.002Z (about 1 year ago)
- Topics: elastic, gui, posthunter, python, search, telegram
- Language: Python
- Homepage:
- Size: 113 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🕵️♂️ PostHunter
**PostHunter** is a simple yet powerful tool for searching, displaying, and analyzing Telegram export messages. It uses a GUI built with `customtkinter` and integrates with Elasticsearch to index and search Telegram message data efficiently.
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## ⚙️ INSTALLATION
### 1. Install Python 3.11+
```bash
git clone https://github.com/AsmrCodeZ-YT/PostHunter.git
cd PostHunter
pip install -r requirements.txt
```
### 2.Install Docker and Run Elasticsearch
Make sure Docker is installed on your system, then start the Elasticsearch container:
docker compose up -d
### 3. Copy Telegram Export File to the data Folder
Export your Telegram data using the official Telegram export tool and copy the file into the data/ directory:
### 4. Run the Config App First
Before running the main application, configure settings using:
python ConfigApp.py
### 5. Run the Main Application
python MainApp.py
## 🧠 About PostHunter
PostHunter is designed for users who want to explore and search their Telegram data exports (including messages, chats, and groups) with advanced filters and a user-friendly interface. Powered by Elasticsearch, it enables fast searching through large datasets. It's ideal for researchers, analysts, and power users who want insight into Telegram communication patterns.
## ✨ Features
- Clean and modern GUI with customtkinter
- Processes and transforms Telegram JSON export files
- Indexes data into Elasticsearch for high-performance querying
- Simple initial setup via ConfigApp
- Docker integration for automated environment setup
## 📌 TODOs
- Run locally without Docker containers
- Add .sh script for installing Elasticsearch and pip dependencies
- Add export path to environment variables
- Enable auto-insertion of Telegram export data
- Implement TRANSFORM_REQUEST for request transformation before indexing
## 📜 License
This project is licensed under the MIT License. See the LICENSE file for more details.
## 👨💻 Developer
Made with ❤️ by AsmrCodeZ-YT