This document lists general directions that core developers are interested to see developed in Pyodide. The fact that an item is listed here is in no way a promise that it will happen, as resources are limited. Rather, it is an indication that help is welcomed on this topic.

Improve documentation#

Our API documentation is fairly detailed, but they need more introductory information like tutorials. We also want to add more information to the FAQ and improve the organization. It would also be good to find some way to include interactive code pens in the documentation.

Reducing download sizes and initialization times#

At present a first load of Pyodide requires a 6.4 MB download, and the environment initialization takes 4 to 5 seconds. Subsequent page loads are faster since assets are cached in the browser. Both of these indicators can likely be improved, by optimizing compilation parameters, minifying the Python standard library and packages, reducing the number of exported symbols. To figure out where to devote the effort, we need a better profiling system for the load process.

See issue #646.

Improve performance of Python code in Pyodide#

Across benchmarks Pyodide is currently around 3x to 5x slower than native Python.

At the same time, C code compiled to WebAssembly typically runs between near native speed and 2x to 2.5x times slower (Jangda et al. 2019 PDF). It is therefore very likely that the performance of Python code in Pyodide can be improved with some focused effort.

In addition, scientific Python code would benefit from packaging a high performance BLAS library such as BLIS.

See issue #1120.

Find a better way to compile Fortran#

Currently, we use f2c to cross compile Fortran to C. This does not work very well because f2c only fully supports Fortran 77 code. LAPACK has used more modern Fortran features since 2008 and Scipy has adopted more recent Fortran as well. f2c still successfully generates code for all but 6 functions in Scipy + LAPACK, but much of the generated code is slightly wrong and requires extensive patching. There are still a large number of fatal errors due to call signature incompatibilities.

If we could use an LLVM-based Fortran compiler as a part of the Emscripten toolchain, most of these problems would be solved. There are several promising projects heading in that direction including flang and lfortran.

See scipy/scipy#15290.

Better project sustainability#

Some of the challenges that Pyodide faces, such as maintaining a collection of build recipes, dependency resolution from PyPI, etc are already solved in either Python or JavaScript ecosystems. We should therefore strive to better re-use existing tooling, and seeking synergies with existing initiatives in this space, such as conda-forge.

See issue #795.

Improve support for WebWorkers#

WebWorkers are necessary in order to run computational tasks in the browser without hanging the user interface. Currently, Pyodide can run in a WebWorker, however the user experience and reliability can be improved.

See issue #1504.

Synchronous IO#

The majority of existing I/O APIs are synchronous. Unless we can support synchronous IO, much of the existing Python ecosystem cannot be ported. There are several different approaches to this, we would like to support at least one method.

See issue #1503.

Write http.client in terms of Web APIs#

Python packages make an extensive use of packages such as requests to synchronously fetch data. We currently can’t use such packages since sockets are not available in Pyodide. We could however try to re-implement some stdlib libraries with Web APIs, potentially making this possible.

Because http.client is a synchronous API, we first need support for synchronous IO.

See issue #140.