10-26, 15:45–16:15 (Asia/Jakarta), CLASS #5
Language: English
It is possible to use functionalities (modules, classes, functions) implemented with languages other than Python as Python libraries.
Well-known examples, Numpy and Pandas are primarily implemented in C/C++ for poweful performance.
Recently, the use of the Rust language has gained attention in addition to C/C++.
In this talk, I will explain the advantages and procedures for developing Python libraries using Rust.
I will also introduce examples of libraries where Rust is being used.
Functionalities (modules, classes, functions) implemented in languages other than Python can be used as Python libraries. Well-known examples like Numpy and Pandas are primarily implemented in C for speed optimization.
Of course, since PyCon is a conference for Python developers, I will ensure the content does not lean too heavily towards Rust.
- Introduction: Introduce the benefits and internal mechanisms of developing Python libraries with compiled languages like C/C++ and Rust.
- Development Methods
- Testing and Debugging
- Deployment and Distribution
- Practical Use Cases: Touch on the internals of pydantic v2 (pydantic-core), which recently became a hot topic because its core implementation in Rust, and introduce how major libraries are being developed.
Software Engineer @RevComm, Inc. from Japan.