Open Source Projects
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We help you coordinate with the communities around open-source to save you money by synchronizing your software plans with the direction open-source communities are heading. Don't be caught relying on yesterday's technology or fighting against the momentum of successful open-source projects. Quansight helps you collaborate with open-source communities with our
Open Source Partnerships.
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If you maintain or manage an open-source project you would like us to feature below, let us know.
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Spyder bridges the gap between the world of machine learning and data analysis, and that of production code, allowing you to easily transform cutting edge science into powerful applications.
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Language Server Protocol Integration
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New, Powerful Debugging Kernel and UI
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Major Enhancements to Projects
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Bokeh is an interactive visualization library that targets modern web browsers for presentation. It provides an elegant and concise way to construct versatile graphics.
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Integrate with VegaLite / Altair
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Visual Design Improvements
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​Develop BokehJS as a First-Class JavaScript Library
SymPy
SymPy is a Python library for symbolic mathematics. It's intended to become a full-featured computer algebra system while keeping the code as simple as possible.
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The Assumptions System
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Code Generation
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Performance
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XND is an extensible framework of C libraries and Python modules for handling typed memory blocks. XND recreates the foundations of NumPy as a number of smaller libraries.
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GPU Support
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Lapack/MKL Kernels and Kernel Generators
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Numba Integration
Datashader is a graphics pipeline system for creating meaningful representations of large datasets quickly and flexibly.
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Improving and Tracking Performance
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Better Integration with External Plotting Libraries
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More Consistent and Powerful Shading and Aggregation
GeoViews is a Python library that makes it easy to explore and
visualize geographical, meteorological, and oceanographic datasets,
such as those used in weather, climate, and remote sensing research.
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Integrating 3D Earth Rendering into GeoViews
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Better Support for Remote Datasets and Remote Computation
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Integration with External Tools
PyViz is an initiative to coordinate scientific Python libraries so that they can work well together and jointly solve a wide range of problems in data science, visualization, and analysis.
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Better integration with other tools
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More extensive documentation about deployment
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Toolbox for GIS primitives
SciPy is open-source software for mathematics, science, and engineering. It includes modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, ODE solvers, and more.
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Evolve BLAS and LAPACK support​
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Implement sparse arrays in addition to sparse matrices
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Fourier transform enhancements
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The aim of PyData/Sparse is to create sparse containers that implement the
ndarray interface. PyData/Sparse is well on its way to replacing scipy.sparse as the de-facto sparse array implementation in the PyData ecosystem.
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More storage formats
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Better performance/algorithms
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Covering more of the NumPy API
Numba gives you the power to speed up your applications with high performance functions written directly in Python. Numba generates optimized machine code using LLVM.
Sparse
Vega & Vega-Lite
Vega and Vega-Lite are intended to become the standard languages for data visualization practice and research, regardless of the underlying programming language used (e.g., JavaScript, Python, etc.). A core principle of Vega-Lite is compiling a declarative specification of visual encodings and interactions to low-level Vega for maximum flexibility.​​
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JupyterLab enables you to work with documents and activities such as Jupyter notebooks, text editors, terminals, and custom components in a flexible, integrated, and extensible manner.
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Odo
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Odo shapeshifts your data using two arguments, a source and a target for a data transfer. It efficiently migrates data from the source to the target through a network of conversions.
Chainer is a powerful, flexible, and intuitive deep learning framework. Chainer supports CUDA computation, and requires only a few lines of code to leverage GPU and runs on multiple GPUs with little effort.
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Dask ML has two goals. Scale machine learning to more computation; and scale machine learning to big data. Dask’s architecture can scale to many machines using parallelism for optimization.
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Big Data Algorithms
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Optimization Framework
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Existing Libraries ​
Ibis
Ibis is a toolbox to bridge the gap between local Python environments, remote storage execution systems like Hadoop components, and SQL databases.
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HoloViews helps you understand your data better, by letting you work seamlessly with both the data and its graphical representation; providing immediate, automatic visualization.
Altair
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Altair is a declarative statistical visualization library for Python, based on Vega and Vega-Lite, and the source is available on GitHub. Altair’s API is simple, friendly and consistent.