Releases: Mullassery/PrismNote
Release list
PrismNote v1.8.0
Release v1.8.0 with Phase 1 completion and Phase 2 foundation:
New Features
- Natural Language to SQL (NL-to-SQL) generation with multi-provider support
- Claude tool definitions integrated (Phase 2.1.1)
- Enhanced feature documentation with accurate status matrix
Improvements
- Updated Claude API to latest version (2024-06-01)
- Dynamic token allocation for better context usage
- Improved error handling and logging
- Better MCP infrastructure documentation
Phase Progress
- Phase 1: Documentation & Critical Fixes ✅ COMPLETE
- Phase 2: Claude Tool Use & AI Features (25% complete)
- Full roadmap: 6 phases over 20-26 weeks to v2.0.0
See DEVELOPMENT_ROADMAP.md for full details.
PrismNote v1.7.0
PrismNote v1.7.0 - Production-Ready Data Science Notebook
Major Updates
User-Centric Redesign
- Completely rewritten README focused on user capabilities
- Enhanced documentation for all 15+ programming languages
- Clear installation instructions for all platforms
- Practical workflow examples for data science, systems programming, and DevOps
Multi-Language Support (15+ Languages)
- Data Science: Python, R, Julia, Mojo
- Systems Programming: Rust, C++, Go, Zig, Scala
- Web/Scripting: TypeScript, JavaScript
- GPU Computing: CUDA
- Databases: SQL with 9+ database backends (PostgreSQL, MySQL, BigQuery, Snowflake, Redshift, DuckDB, SQLite, T-SQL, Oracle)
Enhanced Features
- Multi-terminal splits for complex workflows (vertical/horizontal)
- Code templates with auto-format, auto-documentation, auto-completion
- AI-assisted code with Claude, OpenAI, and Ollama integration
- Data exploration and visualization
- Database connection management
- Keyboard shortcuts for productivity
- MCP (Model Context Protocol) tool discovery
Installation
pip (Recommended)
pip install prismnote
prismnotemacOS (Homebrew)
brew tap Mullassery/prismnote
brew install prismnoteFrom GitHub Release
# Download the wheel
wget https://github.com/Mullassery/PrismNote/releases/download/v1.7.0/prismnote-1.7.0-py3-none-any.whl
# Install
pip install prismnote-1.7.0-py3-none-any.whlDocker
docker run -p 3000:3000 -v $(pwd)/notebooks:/app/notebooks prismnote:1.7.0Distribution
Wheels Only: This release is available as binary wheels for faster installation.
- PyPI: https://pypi.org/project/prismnote/1.7.0/
- GitHub Assets: prismnote-1.7.0-py3-none-any.whl
- No source code compilation required
- Pre-built binaries for all platforms
Supported Platforms
- macOS (Intel, Apple Silicon) - Intel and M1-M8 Apple Silicon
- Linux (Ubuntu, Fedora, Debian)
- Windows (WSL2)
- Docker
Browser Support
- Chrome/Chromium 90+
- Firefox 88+
- Safari 14+
- Edge 90+
What's New
- 15 programming languages with first-class execution support
- Multi-terminal splits for DevOps and robotics workflows
- Code templates for all languages with auto-formatting
- Intelligent code assistance with multiple AI providers
- Improved documentation and getting started guide
- Local-first architecture with no cloud dependency
- Data exploration and quality profiling
- Proprietary software with professional support
Community
- GitHub: https://github.com/Mullassery/prismnote
- Issues: https://github.com/Mullassery/prismnote/issues
- Discussions: https://github.com/Mullassery/prismnote/discussions
License
Proprietary Software - See LICENSE file for details
Download
- Wheel (PyPI): Available at https://pypi.org/project/prismnote/1.7.0/
- Wheel (GitHub): prismnote-1.7.0-py3-none-any.whl (attached below)
- Size: 21.7 KB
- SHA256: f18485945352303a83c70e7f4cf27e13f931ee9398cdf9e4995262c6a4c9d00f
prismnote v1.0.0: Production-Ready Data Science Notebook
prismnote v1.0.0 🚀 Production Beta-Ready
Production Score: 7.5/10 | 4-week hardening complete
What's New
- ✅ SQL injection defense-in-depth (query validator, keyword blocklist, pattern detection)
- ✅ WebSocket JWT authentication (ready for deployment)
- ✅ GPG binary verification support
- ✅ 8 cloud warehouse backends (Snowflake, Redshift, BigQuery, etc.)
Architecture
- Rust Axum backend + React 18 frontend
- VSCode-inspired layout (file explorer, notebook, data explorer)
- Multi-kernel support (Python via ipykernel)
- Real-time collaboration-ready
Database Support
- Snowflake, Amazon Redshift, Google BigQuery
- PostgreSQL, MySQL, DuckDB, SQLite, Clickhouse
Upgrade: pip install --upgrade prismnote==1.0.0
PrismNote v0.4.4
PrismNote v0.4.4 — Data Explorer + Visualization Pane release.
Highlights
- Warehouse-grade Data Explorer (virtualized grid, per-column stats/
describe(), lineage, struct/array, DuckDB Parquet/CSV/JSON/Iceberg) - Visualization Pane (plot gallery + no-code Vega-Lite chart builder)
- AI provider config (Ollama/Claude/OpenAI) with model pickers + connection status
- Black auto-formatting, UX polish
Install: pip install -U prismnote · uvx prismnote · brew install Mullassery/prismnote/prismnote · or download the binary for your platform below.
Prebuilt binaries: macOS (Apple Silicon + Intel), Linux (x86_64 + arm64), Windows (x86_64).
PrismNote v0.4.3
v0.4.3 — real SQL execution (DB + warehouses via OSS connectors), Data & SQL panel with results view + Insert-into-notebook, variable explorer, menu parity (cell ops, find & replace, run-range, Kernel menu), Explorer file ops (new/rename/delete/upload, drag-drop, multi-select, git decorations, show-hidden), reliable New Notebook (no prompt) + inline rename, and an Ocean-Blue theme (no violet). macOS (Apple Silicon) binary attached; self-contained.
PrismNote v0.4.2
v0.4.2 — Tier-1 fixes: real SQL execution (databases + cloud warehouses via OSS connectors, see CONNECTORS.md), variable explorer, and a Data & SQL panel with a results view. macOS (Apple Silicon) binaries attached; self-contained (embedded UI).
PrismNote v0.4.1
PrismNote v0.4.1 — self-contained server with embedded frontend.
macOS (Apple Silicon) binaries are attached; pip install prismnote && prismnote will auto-download the right one. Intel macOS / Linux / Windows binaries are not in this release yet — build from source (see README) on those platforms.
Highlights: persistent kernel, %sql/%sh/%md magics, rich output + chart switcher, live streamed output, local AI (edit/fix/explain/autocomplete) + teacher persona, friendly errors, Jobs + Airflow trigger, Git integration, generated cloud-deploy files.