Notion API

Intermediate2+ years experienceTools & Platforms

Solid understanding with practical experience in multiple projects

My Experience

Official API for integrating with Notion workspace data. Experienced in fetching, processing, and managing Notion content for AI applications and data pipelines.

Technical Deep Dive

Core Concepts I'm Proficient In:
Content Extraction: Fetching and processing all Notion block types including text, headings, lists, code blocks, tables, and embedded content
Authentication: Implementing secure API key management with environment variables and keyring-based credential storage
Block Type Processing: Converting diverse Notion block types into normalized text representations for AI processing
Recursive Fetching: Implementing async pipeline-based page traversal to collect main pages and all child pages efficiently
Metadata Management: Preserving page IDs, URLs, titles, and hierarchical relationships for context-aware retrieval
Async Operations: Using asynchronous patterns to parallelize page fetching for improved performance (~0.8s for 9 pages)
Advanced Implementation Patterns:
Async Pipeline Architecture: Building concurrent fetching systems that process multiple pages in parallel using asyncio
Complete Block Coverage: Handling all Notion block types comprehensively without missing content from unsupported block types
Efficient Text Extraction: Converting Notion's rich text format into clean, structured text suitable for embedding and RAG
Minimal Conversion Overhead: Leveraging Notion's block type structure to directly extract text without complex transformation logic
Performance Optimization: Achieving ~0.8s fetch times for 9 pages through parallelized API calls and efficient content aggregation
Error Handling: Implementing robust error handling for API rate limits, missing pages, and malformed content
Complex Problem-Solving Examples:
High-Performance Recursive Fetcher:
Built a comprehensive Notion content fetcher for the RAG CLI that recursively traverses entire Notion page hierarchies using async pipelines to maximize throughput. The system fetches a home page and all its child pages in parallel, processing approximately 9 pages in ~0.8 seconds through concurrent API calls. Implemented complete coverage of all Notion block types, ensuring no content is lost during extraction - from basic paragraphs and headings to complex tables, code blocks, and embedded content. The fetcher preserves critical metadata including page IDs, URLs, titles, and parent-child relationships, enabling the RAG system to provide source attribution and context in its responses.
Block Type Normalization System: Designed an efficient text extraction pipeline that converts Notion's diverse block types into uniform text representations without losing semantic meaning. Unlike systems that struggle with markdown conversion or unsupported block types, this approach leverages Notion's structured block format to directly extract text content while maintaining logical document structure. The system handles nested blocks, maintains list hierarchies, preserves code block formatting, and converts tables into readable text formats, ensuring the RAG system receives clean, well-structured content for embedding and retrieval.
Areas for Continued Growth:
Write Operations: Learning Notion API's write capabilities to build automation tools that can create, update, and organize Notion content programmatically
Database Operations: Exploring Notion database APIs for querying, filtering, and manipulating structured data within Notion
Advanced Automation: Building custom Notion automations for personal productivity and team workflows
Real-Time Sync: Implementing webhook-based systems for real-time content synchronization and change detection
2+ years
Experience
1
Projects
Intermediate
Proficiency