Comparing IHaskell and xeus-haskell: Two Approaches to Haskell in Jupyter Notebooks
By
mchav
Pulled from the oven just right. Trustworthy, fact-dense, deeply satisfying.
Summary
This article compares two different approaches to running Haskell in Jupyter notebooks: IHaskell and xeus-haskell. It examines their architectural differences, focusing on how they implement the Jupyter kernel protocol, their engineering trade-offs, and their implications for developers using Haskell in data science workflows and interactive documentation. The analysis covers the Jupyter kernel architecture, how each implementation handles communication between frontend and backend, and the practical considerations for users choosing between these two solutions.
Key quotes
· 5 pulledFor developers integrating Haskell into data science workflows or interactive documentation, the Jupyter notebook is the standard interface.
Currently, there are two primary ways to run Haskell in Jupyter: IHaskell and xeus-haskell.
While both achieve the same end user experience (executing Haskell code in cells) their internal architectures represent fundamentally different engineering trade-offs.
This article explores those architectures side-by-side, with a focus on the Jupyter Kernel Architecture.
Jupyter is essentially a front-end that communicates with a computation server via a well-defined protocol.
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