Repository Index

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

Turns Data and AI algorithms into production-ready web applications in no time.

• automation
• data-engineering
• data-ops
• data-visualization

📚 Parameterize, execute, and analyze notebooks

• jupyter
• notebooks
• notebook-generator
• nteract

Elyra extends JupyterLab with an AI centric approach.

• notebooks
• notebook-jupyter
• jupyterlab
• jupyterlab-extensions

Apache StreamPipes - A self-service (Industrial) IoT toolbox to enable non-technical users to connect, analyze and explore IoT data streams.

• iot
• analytics
• edge
• stream-processing

Easy pipelines for pandas DataFrames.

• pandas
• pandas-dataframe
• pipeline
• data

Move fast from data science prototype to pipeline. Capture, analyze, and transform messy notebooks into data pipelines with just two lines of code.

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

Build, test, deploy, iterate - Dev and prod tool for data science pipelines

• build-tool
• build-automation
• build-system
• data-science

Ordered-concurrently a library for concurrent processing with ordered output in Go. Process work concurrently and returns output in a channel in the order of input. It is useful in concurrently processing items in a queue, and get output in the order provided by the queue.

• concurrent
• golang
• golang-library
• data-science

A coding exercise: let's convert dirty machine learning code into clean code using a Pipeline - which is the Pipe and Filter Design Pattern applied to Machine Learning.

GTFS Data Pipeline for TfNSW Bus Datasets

• gtfs
• gtfs-static
• gtfs-realtime
• tfnsw