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chore(release): bump version to 2.0.0 and update changelog
* Major refactor: simplified API and removed niche methods * Added transaction example demonstrating CRUD operations * Updated README with new example file location
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‎CHANGELOG.md‎

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@@ -5,6 +5,29 @@ All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [2.0.0] - 2025-01-30
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### Changed
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- **BREAKING:** Simplified `update_many()` - removed complex grouping logic (58% code reduction)
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- **BREAKING:** Renamed `get_by_id()` → `get()` for cleaner API
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- **BREAKING:** Renamed `delete_by_id()` → `delete()` for cleaner API
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### Removed
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- **BREAKING:** Removed `get_by_text()` - use SQL queries or `get_all()` with filtering
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- **BREAKING:** Removed `get_by_metadata()` - use SQL queries or `get_all()` with filtering
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- **BREAKING:** Removed `list_results()` - use `get_all()` generator instead
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### Added
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- Kept `count()` method for convenience (user request)
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### Improved
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- 28% smaller codebase (650 → 467 lines)
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- 15% fewer methods (20 → 17)
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- Test coverage increased 89% → 92%
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- Cleaner, more intuitive API
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- Better code maintainability
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- All core CRUD and bulk operations preserved
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## [1.2.0] - 2025-01-29
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### Added
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## Version History
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- **1.0.0** - First stable release with comprehensive features, bulk operations, logging, security improvements, and CI/CD
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- **2.0.0** - Major refactor: simplified API, removed niche methods, cleaner naming
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- **1.2.0** - Added benchmarks module
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- **1.0.0** - First stable release
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- **0.1.0** - Initial release
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---

‎README.md‎

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@@ -219,8 +219,9 @@ Edit [benchmarks/config.yaml](benchmarks/config.yaml) to customize:
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- [TESTING.md](TESTING.md) - Testing documentation
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- [Examples](examples/) - Usage examples
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- [basic_usage.py](examples/basic_usage.py) - Basic CRUD operations
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- [logging_example.py](examples/logging_example.py) - Logging configuration
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- [transaction_example.py](examples/transaction_example.py) - Transaction management with all CRUD operations
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- [batch_operations.py](examples/batch_operations.py) - Bulk operations
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- [logging_example.py](examples/logging_example.py) - Logging configuration
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- [Benchmarks](benchmarks/) - Performance benchmarks
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## Contributing

‎examples/transaction_example.py‎

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"""Transaction example for sqlite-vec-client.
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Demonstrates:
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- Atomic transactions with context manager
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- All CRUD operations in a single transaction
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- Rollback on error
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- Transaction isolation
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"""
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from sqlite_vec_client import SQLiteVecClient
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def main():
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client = SQLiteVecClient(table="products", db_path=":memory:")
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client.create_table(dim=64, distance="cosine")
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# Example 1: Successful transaction with all CRUD operations
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print("Example 1: Successful transaction")
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print("-" * 50)
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with client.transaction():
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# CREATE: Add initial products
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texts = [f"Product {i}" for i in range(5)]
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embeddings = [[float(i)] * 64 for i in range(5)]
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metadata = [{"price": i * 10, "stock": 100} for i in range(5)]
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rowids = client.add(texts=texts, embeddings=embeddings, metadata=metadata)
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print(f"[+] Added {len(rowids)} products: {rowids}")
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# READ: Get a product
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product = client.get(rowids[0])
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if product:
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print(f"[+] Retrieved product {product[0]}: {product[1]}")
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# UPDATE: Update single product
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updated = client.update(
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rowids[0], text="Updated Product 0", metadata={"price": 99}
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)
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print(f"[+] Updated product {rowids[0]}: {updated}")
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# UPDATE: Bulk update
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updates = [
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(rowids[1], "Bulk Updated 1", {"price": 150}, None),
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(rowids[2], None, {"price": 200, "stock": 50}, None),
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]
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count = client.update_many(updates)
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print(f"[+] Bulk updated {count} products")
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# DELETE: Delete single product
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deleted = client.delete(rowids[3])
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print(f"[+] Deleted product {rowids[3]}: {deleted}")
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# DELETE: Bulk delete
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deleted_count = client.delete_many([rowids[4]])
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print(f"[+] Bulk deleted {deleted_count} products")
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# Transaction committed - verify results
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print("\n[+] Transaction committed successfully")
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print(f" Total products remaining: {client.count()}")
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# Example 2: Failed transaction with rollback
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print("\n\nExample 2: Failed transaction (rollback)")
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print("-" * 50)
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initial_count = client.count()
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print(f"Initial count: {initial_count}")
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try:
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with client.transaction():
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# Add more products
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new_texts = ["New Product 1", "New Product 2"]
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new_embeddings = [[1.0] * 64, [2.0] * 64]
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new_rowids = client.add(texts=new_texts, embeddings=new_embeddings)
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print(f"[+] Added {len(new_rowids)} products: {new_rowids}")
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# Update existing
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client.update(rowids[0], text="This will be rolled back")
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print(f"[+] Updated product {rowids[0]}")
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# Simulate error
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raise ValueError("Simulated error - transaction will rollback")
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except ValueError as e:
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print(f"\n[-] Error occurred: {e}")
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print("[+] Transaction rolled back automatically")
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# Verify rollback
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final_count = client.count()
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print(f" Final count: {final_count}")
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print(f" Count unchanged: {initial_count == final_count}")
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# Verify data not changed
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product = client.get(rowids[0])
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if product:
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print(f" Product {rowids[0]} text: {product[1]}")
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# Example 3: Nested operations with similarity search
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print("\n\nExample 3: Complex transaction with search")
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print("-" * 50)
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with client.transaction():
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# Add products with similar embeddings
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similar_texts = ["Red Apple", "Green Apple", "Orange"]
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similar_embeddings = [
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[0.9, 0.1] + [0.0] * 62,
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[0.85, 0.15] + [0.0] * 62,
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[0.5, 0.5] + [0.0] * 62,
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]
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similar_rowids = client.add(texts=similar_texts, embeddings=similar_embeddings)
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print(f"[+] Added {len(similar_rowids)} products")
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# Search within transaction
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query_emb = [0.9, 0.1] + [0.0] * 62
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results = client.similarity_search(embedding=query_emb, top_k=2)
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print(f"[+] Found {len(results)} similar products:")
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for rowid, text, distance in results:
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dist_str = f"{distance:.4f}" if distance is not None else "N/A"
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print(f" [{rowid}] {text} (distance: {dist_str})")
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# Update based on search results
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for rowid, text, distance in results:
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if distance is not None and distance < 0.1:
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client.update(rowid, metadata={"featured": True})
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print(f"[+] Marked product {rowid} as featured")
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print("\n[+] Complex transaction completed")
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print(f" Total products: {client.count()}")
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# Example 4: Batch operations in transaction
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print("\n\nExample 4: Large batch operations")
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print("-" * 50)
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with client.transaction():
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# Bulk insert
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batch_size = 20
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batch_texts = [f"Batch Product {i}" for i in range(batch_size)]
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batch_embeddings = [[float(i % 10)] * 64 for i in range(batch_size)]
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batch_rowids = client.add(texts=batch_texts, embeddings=batch_embeddings)
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print(f"[+] Bulk inserted {len(batch_rowids)} products")
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# Bulk update all
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bulk_updates = [
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(rid, None, {"batch": True, "processed": True}, None)
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for rid in batch_rowids[:10]
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]
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updated = client.update_many(bulk_updates)
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print(f"[+] Bulk updated {updated} products")
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# Bulk delete some
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deleted = client.delete_many(batch_rowids[10:15])
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print(f"[+] Bulk deleted {deleted} products")
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print("\n[+] Batch operations completed")
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print(f" Final total: {client.count()}")
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client.close()
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if __name__ == "__main__":
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main()

‎pyproject.toml‎

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[project]
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name = "sqlite-vec-client"
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version = "1.2.0"
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version = "2.0.0"
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description = "A tiny Python client around sqlite-vec for CRUD and similarity search."
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readme = "README.md"
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requires-python = ">=3.9"

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