smc360 1.0.0

Social media data connector for extracting, parsing, and managing social media data at scale.

SMC360 — Social Media Data Connector

SMC360 is a unified toolkit for extracting, parsing, and managing social media data at scale.
It provides both a command-line interface (CLI) and a web interface, enabling flexible integration into automated workflows and user-friendly interactive environments.

---

✨ Features

• Multi-Platform Support

  • YouTube (YouTube Data API)
  • Instagram (Basic Display API)

• Data Persistence

  • Databases: PostgreSQL, Snowflake
  • Object Storage: Amazon S3

• Flexible Interfaces

  • CLI Tool — for automation, scheduling, and scripting
  • Web Interface — for interactive extraction and monitoring

• Dual Storage

  • Parsed Data → relational databases for analytics
  • Raw API Responses → object storage for traceability and reprocessing

---

🚀 Installation

pip install "git+https://github.com/Mdadilfarooq/social_media_connector.git@main"

---

⚡ Quickstart

1. Configure

Prepare a configuration file (config.yaml) with your API keys, database credentials, and storage settings:

platform:
  name: youtube
  api_key: YOUR_YOUTUBE_API_KEY

database:
  type: postgresql
  host: localhost
  port: 5432
  user: postgres
  password: secret
  database: SMC360

storage:
  type: s3
  bucket: SMC360-data
  access_key: YOUR_AWS_KEY
  secret_key: YOUR_AWS_SECRET

---

2. CLI Usage

Extract and store social media data directly from the terminal:

SMC360 extract --config config.yaml --platform youtube

Other commands:

SMC360 extract --platform instagram
SMC360 status
SMC360 config validate

---

3. Web Interface

Launch the web app for interactive control:

SMC360 web

Open http://localhost:8000 to manage configurations, run extractions, and monitor jobs.

---

📂 Workflow

1. Configuration — Connect to the chosen social media platform, database, and storage service.
2. Dynamic Loading — Pull additional configuration from object storage.
3. Extraction & Parsing — Collect raw data via APIs and convert it into structured formats.
4. Storage — Save structured data into databases and archive raw responses in object storage.

---

💡 Use Cases

• Social media analytics and insights
• Data warehousing for BI/reporting
• Marketing and campaign performance tracking
• Archival of raw API responses for compliance and auditing

---

🛠 Development

Clone the repo and install in editable mode:

git clone https://github.com/Mdadilfarooq/social_media_connector.git
cd social_media_connector
pip install -e .

Run tests:

pytest

---

📜 License

This project is licensed under the MIT License.

---