Python Mania: Technology Corps Targeting the Open Source Community
Blog|by Leanne Bevan|1 October 2018
Python*, as stated in one of our previous blogs, is fast becoming one of the world’s most popular programming languages. So, it’s no wonder that some of the biggest technology corporations like Microsoft and Intel® Software are coming on board by tailoring their software to reach these avid coders.
Microsoft has recently launched their August 2018 Python* Extension for Visual Studio Code. In the release Microsoft has updated all users to the latest ptvsd (4.1.1) version of their Python* debugger, with better performance and stability. The new debug engine is built on top of the open source pydevd, which brings greater performance and support for third party libraries. Furthermore, remote debugging is now much easier as you can install any 4.x version of ptvsd and can even attach from the command line. The debugger now supports the logpoints feature that was added in the March version of VS Code. This feature enables you to add print statements without the need to stop execution. There are also some improvements to the Language Server Preview too.
Intel® Software has just released the latest version of their developer tools suite, Intel® Parallel Studio XE 2019. In this release Python* developers are now able to speed up machine learning through enabling new high-performance Python* optimisations with the Intel® Distribution for Python* and Intel® Data Analytics Acceleration Library (Intel® DAAL). Accelerated data analysis and scientific computing with the Intel® Distribution for Python* now integrate into the latest version of Intel® Parallel Studio XE.
Grey Matter is a Gold Microsoft Partner and an Intel Software Elite Reseller. If you have any questions about how the software above is licensed, the editions available or would like any additional information, please call +44 (0) 1364 654100 or email firstname.lastname@example.org.
We are hosting a webinar on 30 April about how you can use parallelism and profiling to improve the performance of Python code. Find out more here.
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