D2B Data Framework 🚀

A robust Python framework designed for managing and integrating data operations across multiple marketing and analytics platforms. D2B Data Framework provides modular, reusable classes to streamline ETL processes and data handling.

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🛠 Installation

1. Clone the Repository

git clone [https://github.com/D2b-Innovation/d2b_dataframework.git](https://github.com/D2b-Innovation/d2b_dataframework.git)
cd d2b_dataframework
pip install -r requirements.txt

2. Install via pip (Directly from GitHub)

pip install git+[https://github.com/D2b-Innovation/d2b_dataframework.git](https://github.com/D2b-Innovation/d2b_dataframework.git)

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📦 Modules and Capabilities

Module	Main Class	Description
🔵 Facebook	Facebook_Marketing	Manage Ads Insights and campaign data.
📊 GA4	Google_GA4	Fetch reports and real-time analytics data.
☁️ BigQuery	Google_Bigquery	Streamline SQL queries and data uploads.
📈 Google Analytics	Google_Analytics	Legacy Universal Analytics support.
📝 Sheets	Google_Spreadsheet	Read/Write operations on Google Sheets.
🔑 Auth	Google_Token_MNG	Manage OAuth2 tokens and credentials.
💼 LinkedIn	Linkedin_Marketing	Extract B2B marketing performance metrics.
🎵 TikTok	Tiktok	Integration with TikTok Ads API.
🐦 X (Twitter)	X_ads	Handle X Ads data reporting.

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🚀 Quick Start (Usage)

from d2b_data.Google_GA4 import Google_GA4

# 1. Initialize the client
ga4_client = Google_GA4('client_secret.json', 'token.json')

# 2. Fetch data
property_id = 'properties/YOUR_PROPERTY_ID'
query = { "dimensions": [{"name": "city"}], "metrics": [{"name": "activeUsers"}] }

df = ga4_client.get_report_df(property_id, query, realtime=True)
print(df.head())

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📄 License

This project is licensed under the MIT License.

🤝 Contributing

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

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