Chapter
Building and Managing Python Packages Across Different Platforms
1:59:30 - 2:05:46 (06:16)
Building and managing Python packages is a tedious task for most data scientists, especially when the packages need to be configured to work on different platforms and operating systems. This is due to the numerous low-level libraries requiring compilation with a C, C++, or Fortran compiler, leading to complicated dependencies that hinder efficient numerical computing.
Clips
Anaconda believes that a marketplace can be created for people to create notebooks, models, datasets, and curation of these different kinds of things, in order to have a long tail marketplace dynamic, which could potentially make a bigger impact in the industry.
1:59:30 - 2:01:00 (01:29)
Summary
Anaconda believes that a marketplace can be created for people to create notebooks, models, datasets, and curation of these different kinds of things, in order to have a long tail marketplace dynamic, which could potentially make a bigger impact in the industry.
ChapterBuilding and Managing Python Packages Across Different Platforms
Episode#250 – Peter Wang: Python and the Source Code of Humans, Computers, and Reality
PodcastLex Fridman Podcast
The package problem in Python is that there are several low-level libraries that need to be compiled, making it difficult to install the correct package for a given set of packages you need.
2:01:02 - 2:03:45 (02:43)
Summary
The package problem in Python is that there are several low-level libraries that need to be compiled, making it difficult to install the correct package for a given set of packages you need. To address this issue, a new set of technologies like build recipe system, build system and installer system has been introduced.
ChapterBuilding and Managing Python Packages Across Different Platforms
Episode#250 – Peter Wang: Python and the Source Code of Humans, Computers, and Reality
PodcastLex Fridman Podcast
The Python community built their own packaging technologies, but they may not have contemplated the complexity of dependencies, particularly when it comes to GPU acceleration and supporting other packages using different versions of libraries like NumPy or OpenCV.
2:03:46 - 2:05:46 (02:00)
Summary
The Python community built their own packaging technologies, but they may not have contemplated the complexity of dependencies, particularly when it comes to GPU acceleration and supporting other packages using different versions of libraries like NumPy or OpenCV.