Software and libraries intentionally installed and maintained in the Interactive Notebooks environment are the following:

  • Molecular biology (biopython, blast, clustalw, emboss)
  • Quantum SDK (amazon-braket-sdk, PennyLane, qiskit, qiskit-machine-learning, dwave-ocean-sdk)
  • R language (RStudio, r-gdata, r-plotly)
  • boto3 -- The AWS SDK for Python
  • cartopy -- A Python library for cartographic visualizations with Matplotlib
  • eo-learn -- Earth observation processing framework for machine learning in Python
  • folium -- Maps with Leaflet.js & Python
  • geojson -- Python bindings and utilities for GeoJSON
  • geopandas -- Geographic pandas extensions
  • gnuplot -- Data and function plotting program
  • graphviz -- Graph visualization software
  • h5glance -- Explore HDF5 files in an HTML view
  • ipyleaflet -- A Jupyter widget for dynamic Leaflet maps
  • ipympl -- Matplotlib Jupyter Extension
  • ipywidgets -- Jupyter interactive widgets
  • libsndfile -- C library for reading and writing audio files
  • matplotlib -- Python plotting package
  • nbtop -- resource monitor for IPython Notebook servers
  • octave -- MATLAB compatible language for numerical computations
  • panel -- Data exploration & web app framework for Python
  • plotly -- An open-source, interactive data visualization library for Python
  • prov -- A library for W3C Provenance Data Model supporting PROV-JSON, PROV-XML and PROV-O (RDF)
  • pydap -- An implementation of the Data Access Protocol
  • pytorch -- Library for deep learning and AI
  • rasterstats -- Summarize geospatial raster datasets based on vector geometries
  • rdflib -- Python library for working with RDF, a language for representing information.
  • scipy -- Fundamental algorithms for scientific computing in Python
  • tensorflow -- Machine learning framework
  • tflearn -- Deep Learning Library featuring a higher-level API for TensorFlow
  • torchaudio -- An audio package for PyTorch
  • torchvision -- Image and video datasets and models for torch deep learning
  • tqdm -- Fast, Extensible Progress Meter
  • xarray -- N-D labeled arrays and datasets in Python

Suggestions to install additional libraries are welcome.

  • No labels