Getting Started with Data Extraction Automation
Prerequisites
- Python 3
- Apollo.io API key
- Access to the private repo
Installation
git clone https://github.com/TeamFleetStudio/data-extraction-automation.git
cd data-extraction-automation
pip install pandas requests python-dotenv
Create .env:
APOLLO_API_KEY=your_apollo_api_key_here
Prepare input CSV with a COMPANYDOMAIN column (see repo defaults / input.csv).
Run
python apollo_extractor.py --input "input.csv" --output "apollo_enriched_contacts.csv" --start-row 1 --num-rows 10
| Argument | Default | Description |
|---|---|---|
--input | apollo_extraction - prem_split.csv | Source CSV with COMPANYDOMAIN |
--output | apollo_enriched_contacts.csv | Enriched output |
--start-row | 1 | 1-indexed start (skips header) |
--num-rows | 1 | Companies to process |
Verification
- Output CSV gains exec name/email/LinkedIn columns
- Domains normalized (e.g.
https://www.google.com/->google.com) - No Apollo rate-limit failures for small batches