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A Python library for syncing and managing Pinboard bookmarks

Project description

pinboard-tools

PyPI version Python versions License

A Python library for syncing and managing Pinboard bookmarks.

Features

  • Bidirectional sync with Pinboard.in API
  • SQLite database for local bookmark storage
  • Tag analysis and similarity detection
  • Conflict resolution for sync operations
  • Rate limiting to respect API limits
  • Chunking utilities for LLM processing

Installation

pip install pinboard-tools

Quick Start

from pinboard_tools import (
    init_database,
    get_session,
    PinboardAPI,
    BidirectionalSync,
)

# Initialize database
init_database("bookmarks.db")

# Set up API client
api = PinboardAPI(api_token="your-pinboard-api-token")

# Create sync engine
with get_session() as session:
    sync = BidirectionalSync(session, api)
    
    # Perform full sync
    stats = sync.sync()
    print(f"Added: {stats['added']}, Updated: {stats['updated']}")

Core Components

Database Models

  • Bookmark - Bookmark entity with all Pinboard fields
  • Tag - Tag entity with normalization
  • BookmarkTag - Many-to-many relationship
  • SyncStatus - Track sync state

Sync Engine

  • PinboardAPI - API client with rate limiting
  • BidirectionalSync - Full sync with conflict resolution

Tag Analysis

  • TagSimilarityDetector - Find similar tags
  • TagConsolidator - Merge duplicate tags

Utilities

  • chunk_bookmarks_for_llm - Prepare data for LLM processing
  • DateTime helpers for Pinboard format

Database Schema

The library uses a normalized SQLite schema:

-- See schema.sql for complete structure
bookmarks (url, title, description, tags, time, ...)
tags (name, normalized_name)
bookmark_tags (bookmark_id, tag_id)
sync_status (last_sync, last_update)

API Reference

Initialization

# Initialize database with schema
init_database(db_path: str)

# Get database session
with get_session() as session:
    # Use session for queries

Syncing

# Create API client
api = PinboardAPI(api_token="your-token")

# Sync bookmarks
sync = BidirectionalSync(session, api)
stats = sync.sync(full_sync=False)

Tag Analysis

# Find similar tags
detector = TagSimilarityDetector(session)
similar_groups = detector.find_similar_tags(threshold=0.8)

# Consolidate tags
consolidator = TagConsolidator(session)
consolidator.consolidate_tags(old_tag="python3", new_tag="python")

License

Apache License 2.0 - see LICENSE file for details

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