A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.
- notebooks
- python
- data-science
- machine-learning
Repository Index
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Turns Data and AI algorithms into production-ready web applications in no time.
📚 Parameterize, execute, and analyze notebooks
- jupyter
- notebooks
- notebook-generator
- nteract
🦀 event stream processing for developers to collect and transform data in motion to power responsive data intensive applications.
- cloud-native
- streaming
- rust
- real-time
AI Infra / AI Orchestration / AI Control Plane
High-performance time-series aggregation for PostgreSQL
- realtime
- stream-processing
- analytics
- sql
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
- data-science
- python
- dag
- data-engineering
CLI task management & automation tool
- python
- build-tool
- build-automation
- task-runner
Elyra extends JupyterLab with an AI centric approach.
- notebooks
- notebook-jupyter
- jupyterlab
- jupyterlab-extensions
Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.
- analytics
- bigquery
- data-modeling
- data-pipelines
Python Streaming DataFrames for Kafka
MLBox is a powerful Automated Machine Learning python library.
- machine-learning
- auto-ml
- kaggle
- deep-learning
visual data prep powered by python
- data
- data-pipelines
- etl
- structured-data
Improve the readability of R code with the pipe
- r
- pipe
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
- hpc
- workflow
- workflow-automation
- workflow-management
Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.
Easy pipelines for pandas DataFrames.
Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code.
An extensible Java framework for building event-driven applications that break up XML and non-XML data into chunks for data integration
- java
- smooks
- enterprise-integration
- etl
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
- python3
- data-science
- machine-learning
- python
Multi-Paradigm Pipeline Implementation
Python histogram library - histograms as updateable, fully semantic objects with visualization tools. [P]ython [HYST]ograms.
- histogram
- plotting
- python
- visualization
Integrated pipeline for multiplexed image analysis
- multiplexed-imaging
- python
Realistic synthetic events for testing, demos, and pipelines — streamed live or generated in bulk
- clickhouse
- data-engineering
- data-generation
- devops