mirror of https://github.com/pyodide/pyodide.git
100 lines
3.8 KiB
Markdown
100 lines
3.8 KiB
Markdown
# Roadmap
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This document lists general directions that core developers are interested to
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see developed in Pyodide. The fact that an item is listed here is in no way a
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promise that it will happen, as resources are limited. Rather, it is an
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indication that help is welcomed on this topic.
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## Reducing download sizes and initialization times
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At present a first load of Pyodide requires a 6.4 MB download, and the
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environment initialization takes 4 to 5 seconds. Subsequent page loads are
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faster since assets are cached in the browser. Both of these indicators can
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likely be improved, by optimizing compilation parameters, minifying the Python
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standard library and packages, reducing the number of exported symbols. To
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figure out where to devote the effort, we need a better profiling system for the
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load process.
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See issue {issue}`646`.
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## Improve performance of Python code in Pyodide
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Across [benchmarks](https://github.com/pyodide/pyodide/tree/main/benchmark)
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Pyodide is currently around 3x to 5x slower than native Python.
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At the same type, C code compiled to WebAssembly typically runs between near
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native speed and 2x to 2.5x times slower (Jangda et al. 2019
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[PDF](https://www.usenix.org/system/files/atc19-jangda.pdf)). It is therefore
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very likely that the performance of Python code in Pyodide can be improved with
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some focused effort.
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In addition, scientific Python code would benefit from packaging a high
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performance BLAS library such as BLIS.
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See issue {issue}`1120`.
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## Simplification of the package loading system
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Currently, Pyodide has two ways of loading packages:
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- `loadPackage` for packages built with Pyodide and
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- `micropip.install` for pure Python packages from PyPI.
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The relationship between these tools is confusing and could be simplified.
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Furthermore, the dependency resolution logic and packaging / build system could
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be improved.
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See issues {issue}`1470` and {issue}`1100`.
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## Update SciPy to a more recent version
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SciPy is a cornerstone of scientific computing in Python. It's a challenging
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package to build for WebAssembly because it is large, includes Fortran code, and
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requires BLAS and LAPACK libraries. Currently, Pyodide includes scipy 0.17.1 from 2016.
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Updating it is a blocker for using more recent versions of packages such
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as scikit-learn, scikit-image, statsmodels, and MNE.
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See issue {issue}`549`.
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## Better project sustainability
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Some of the challenges that Pyodide faces, such as maintaining a collection of
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build recipes, dependency resolution from PyPI, etc are already solved in either
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Python or JavaScript ecosystems. We should therefore strive to better re-use
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existing tooling, and seeking synergies with existing initiatives in this space,
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such as conda-forge.
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See issue {issue}`795`.
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## Improve support for WebWorkers
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WebWorkers are necessary in order to run computational tasks in the browser
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without hanging the user interface. Currently, Pyodide can run in a WebWorker,
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however the user experience and reliability can be improved.
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See issue {issue}`1504`.
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## Synchronous IO
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The majority of existing I/O APIs are synchronous. Unless we can support
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synchronous IO, much of the existing Python ecosystem cannot be ported. Luckily
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{user}`joemarshall` has a solution for this involving rewinding the Python
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stack. He has [a prototype implementation
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here](https://github.com/joemarshall/unthrow). We would like to bring this into
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Pyodide as a core feature.
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See issue {issue}`1503`.
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(http-client-limit)=
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## Write http.client in terms of Web APIs
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Python packages make an extensive use of packages such as `requests` to
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synchronously fetch data. We currently can't use such packages since sockets
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are not available in Pyodide. We could however try to re-implement some
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stdlib libraries with Web APIs, potentially making this possible.
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Because http.client is a synchronous API, we first need support for synchronous
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IO.
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See issue {issue}`140`.
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