Python Tutorial Shows How to Build a Qualified YouTube Creator Prospecting Tool

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A new tutorial published on DEV Community demonstrates how to build a YouTube channel finder in Python that goes beyond basic name or topic lookups. The tool is designed for use cases such as sponsor outreach, educator recruitment, or selling services to creators, by filtering candidates based on niche, upload frequency, subscriber count, and recent viewership. Using the Apify client library, the workflow discovers channel candidates, analyzes recent performance metrics, and returns structured data rows per channel without requiring a manual review of each profile. Key output fields include recent median views, estimated videos per month, content format ratios, inferred country data, and publicly available business contact information. The tutorial argues that qualifying active channel state — rather than relying solely on lifetime subscriber totals — is what separates a basic scraper from a practical creator-prospecting dataset.

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