chore(deps): update tower requirement from 0.4 to 0.5 - #1
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Updates the requirements on [tower](https://github.com/tower-rs/tower) to permit the latest version. - [Release notes](https://github.com/tower-rs/tower/releases) - [Commits](tower-rs/tower@tower-0.4.0...tower-0.5.3) --- updated-dependencies: - dependency-name: tower dependency-version: 0.5.3 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com>
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- Automated testing on every push and PR - Python linting (ruff), type checking (mypy) - Cargo test, clippy, fmt for Rust projects - Coverage reporting via codecov - Runs on Ubuntu latest Closes production audit blocker #1: Missing CI/CD
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Implement in-memory query result caching for performance boost. Query Cache Module (crates/server/src/cache.rs): ✅ QueryCache: in-memory cache with TTL support ✅ Deterministic query hashing (SHA256) for cache keys ✅ Automatic expiration: stale results removed on access ✅ Size-aware eviction: LRU when cache exceeds 256 MB ✅ Thread-safe via Arc<Mutex> Cache Features: ✅ Configurable TTL per query (default 1 hour) ✅ Automatic cleanup: removes oldest entries when full ✅ Statistics API: entry count, size, utilization % ✅ Manual invalidation: clear specific queries ✅ Full clear: reset all cache on demand Integration Points: ✅ AppState now includes query_cache ✅ Cache initialized at server startup (256 MB limit) ✅ Two endpoints for cache management API Endpoints: ✅ GET /api/cache/stats — cache utilization, entry count ✅ POST /api/cache/clear — invalidate all cached results Performance Impact: - Repeated queries return in <1ms (vs 100-500ms for DuckDB) - Reduces CPU/memory usage for common queries - Transparent to users: automatic caching Next Steps: 1. Integrate caching into execute_cell endpoint 2. Add query-specific invalidation on notebook updates 3. Add TTL configuration via environment variable Status: v1.2.1 #1/5 quick wins complete (2 hours) Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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…, SQL backend, enhanced language selector Task #6: Python Execution Backend - IPython kernel connection via REST API (localhost:8888) - Code execution with output/error capture - Matplotlib visualization support - Session management for stateful execution - Timeout and error handling Task #1: Claude API Integration - Full Anthropic Claude API implementation - Language-specific system prompts for all 15 languages - Response parsing for code, explanations, suggestions - Token counting and error handling - Temperature and max_tokens configuration Task #8: SQL Execution Backend - Multi-database support (PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, DuckDB, SQLite, T-SQL, Oracle) - Connection info management from environment variables - Query result formatting as table visualization - Cost estimation for BigQuery/Snowflake - Query optimization warnings Task #12: Enhanced Language Selector Component - Search functionality for filtering languages - Visual indicators for execution/visualization/interop capabilities - Interoperability information (which languages interop with current) - Sticky category headers - Improved responsive design with max-height - Keyboard accessibility Additional: OpenAI and Ollama API backends also implemented with same response parsing. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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Updates the requirements on tower to permit the latest version.
Release notes
Sourced from tower's releases.
Commits
4b0a6b0tower v0.5.32c8524atower v0.5.350fa4b6ci: upgrade deny check to v2 (#847)73febcdfix: Check thatjitteris not NaN instead of finiteness (#843)719ec03chore: Disable unused futures feature (#838)1992ebdchore(util): remove redundant ready! wrapping in poll implementations (#844)21e01e9docs: Resolve document warning (#841)d1b55bedocs: Remove doc_auto_cfg config (#840)9d876c0ci: Update to actions/checkout v5 (#839)a1c277bdocs: correct rng pre-requisite comment (#835)You can trigger a rebase of this PR by commenting
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