facebook-ads-reports 2.0.0

ETL module for Facebook Ads API v23 with lightweight native Python data processing

Facebook Ads Reports Helper

A Python ETL driver for Facebook Marketing API v23 data extraction and transformation. Simplifies the process of extracting Facebook Ads data and converting it to structured data formats with comprehensive utility functions.

Features

• Facebook Marketing API v23: Latest API version support with full compatibility
• Robust Error Handling: Comprehensive error handling with retry logic and specific exceptions
• Multiple Report Types: Pre-configured report models for common use cases
• Custom Reports: Create custom report configurations
• Flexible Data Export: Built-in CSV and JSON export utilities
• Lightweight Architecture: No pandas dependency for faster installations and smaller footprint
• Type Hints: Full type hint support with strict mypy compliance for better IDE experience
• Data Processing Utilities: Helper functions for data transformation and export

Installation

pip install facebook-ads-reports

Quick Start

1. Set up credentials

Option A: Configuration file

Create a secrets/fb_business_config.json file with your Facebook Ads API credentials:

{
  "app_id": "YOUR_APP_ID",
  "app_secret": "YOUR_APP_SECRET",
  "access_token": "YOUR_ACCESS_TOKEN",
  "ad_account_id": "act_1234567890",
  "base_url": "https://graph.facebook.com/v23.0"
}

Option B: Environment variable

Set the FACEBOOK_ADS_CONFIG_JSON environment variable with your credentials as JSON:

export FACEBOOK_ADS_CONFIG_JSON='{"app_id": "YOUR_APP_ID", "app_secret": "YOUR_APP_SECRET", "access_token": "YOUR_ACCESS_TOKEN", "ad_account_id": "act_1234567890", "base_url": "https://graph.facebook.com/v23.0"}'

2. Basic usage

from datetime import date, timedelta
from facebook_ads_reports import MetaAdsReport, MetaAdsReportModel
from facebook_ads_reports.utils import load_credentials, save_report_to_csv, save_report_to_json

# Load credentials
credentials = load_credentials()
client = MetaAdsReport(credentials_dict=credentials)

# Configure report parameters
ad_account_id = "act_1234567890"
start_date = date.today() - timedelta(days=7)
end_date = date.today() - timedelta(days=1)

# Extract report data
data = client.get_insights_report(
        ad_account_id=ad_account_id,
        report_model=MetaAdsReportModel.ad_performance_report,
        start_date=start_date,
        end_date=end_date
)

# Save to CSV using utility function
save_report_to_csv(data, "ad_performance_report.csv")

# Save to JSON using utility function
save_report_to_json(data, "ad_performance_report.json")

Available Report Models

• MetaAdsReportModel.ad_dimensions_report - Ad dimensions and metadata
• MetaAdsReportModel.ad_performance_report - Ad performance and actions metrics

Custom Reports

Create custom report configurations:

from facebook_ads_reports import create_custom_report

custom_report = create_custom_report(
    report_name="my_custom_report",
    select=["ad_id", "impressions", "spend"],
    from_table="ad_insights"
)

# Usage:
# data = client.get_insights_report(ad_account_id, custom_report, start_date, end_date)

Examples

Check the examples/ directory for comprehensive usage examples:

• basic_usage.py - Simple report extraction

Requirements

• Python 3.10-3.12
• requests >= 2.32.4

License

GPL License. See LICENSE file for details.

Support

• Documentation
• Issues
• Examples

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.