Mailman 3 October 2020 - python-uk

London Dojo next Thursday
by Tom Viner March 15, 2024

March 15, 2024

Hi all, For February's London code dojo, we'll be at Sohonet <https://www.sohonet.com/>. We'll have pizza, drinks and some fun group coding. All abilities welcome! There'll also be the prize draw for a random O'Reilly Python book as usual. *6:30pm Thursday 1st Feb 2018* Get your tickets while they're hot: https://www.eventbrite.co.uk/e/london-python-code-dojo-season-9-episode-6-t… If you need any more information, contact the team via Twitter: @ldnpydojo <https://twitter.com/ldnpydojo> or via e-mails to team(a)ldnpydojo.org.uk We're always looking for venues to host the Dojo and volunteers to be cat herders, i.e. writing an email like this and coordinating the voting etc. Look forward to seeing you next Thursday! Tom @tomviner <https://twitter.com/tomviner>

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Vacancy Notice
by Steve Holden Oct. 27, 2020

Oct. 27, 2020

My employer's Platform group has vacancies, including one for a full-stack Python developer. The position is fully remote (I was hired without meeting anyone in the company face to face). The only downside is you might end up working in my team. See https://careers.labster.com/departments/platform Hope you are all doing well in these troubling times. Kind regards, Steve

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Austin -- CPython frame stack sampler v2.0.0 is now available
by Gabriele Oct. 18, 2020

Oct. 18, 2020

I am delighted to announce the release 2.0.0 of Austin. If you haven't heard of Austin before, it is an open source frame stack sampler for CPython, distributed under the GPLv3 license. It can be used to obtain statistical profiling data out of a running Python application without a single line of instrumentation. This means that you can start profiling a Python application straight away, even while it's running on a production environment, with minimal impact on performance. The simplest way of using Austin is by piping its output to FlameGraph for a quick and detailed representation of the collected samples. Austin is a pure C application that has no other dependencies other than the C standard library. Its source code is hosted on GitHub at https://github.com/P403n1x87/austin The README contains installation and usage details, as well as some examples of Austin in action. Details on how to contribute to Austin's development can be found at the bottom of the page. Austin can be installed easily on the following platforms and from the following sources: Linux: - Snap Store - Debian repositories macOS: - Homebrew Windows: - Chocolatey - Scoop Austin is also simple to compile from sources as it only depends on the standard C library, if you don't have access to the above-listed sources. Besides support for Python 3.9, this new release of Austin brings a considerable performance enhancement that allows it to sample up to 8 times faster than previous versions. But please do read on until the end to find out about some new tools that take advantage of all the key features of Austin. Due to increasing popularity, the sample Python applications that were included in the main repository have been moved to dedicated projects on GitHub. The TUI can now be found at https://github.com/P403n1x87/austin-tui while Austin Web is now available from https://github.com/P403n1x87/austin-web They can both be installed easily from PyPI, but to use them the Austin binary needs to be on the PATH environment variable. These projects now rely on the austin-python Python package that provides a Python wrapper around Austin. If you are considering making your own profiling tool based on Austin, this package can spare you from writing boilerplate code, so it's worth having a look at it at https://github.com/P403n1x87/austin-python The documentation is hosted on RTD at https://austin-python.readthedocs.io/en/latest/ Finally, I am happy to announce the release of pytest-austin, a plugin for pytest that allows you to set up performance regression testing by simply decorating your existing pytest test suite. The plugin launches Austin to profile your test runs, meaning that no further instrumentation is required. For more details, check out the project on GitHub https://github.com/P403n1x87/pytest-austin Like the other Austin tools, pytest-austin can be installed easily from PyPI. You can stay up-to-date with the project's development by following Austin on Twitter (https://twitter.com/AustinSampler). All the best, Gabriele

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Contract opportunity for a Big Data engineer
by Harry Robinson Oct. 8, 2020

Oct. 8, 2020

Hello all, My client is looking for a Python developer to join them for an initial 3 month contract, FULLY REMOTE, working on a breakthrough AI regulation platform. We are looking for a developer with the following: Experience with distributed computing/large distributed systems (P2P systems); Big Data experience (Hadoop, ElasticSearch); Understanding of security protocols (TLS/SSL); DevOps experience would be beneficial (Docker, microservices, CI/CD). The project length will be up to 12 months and we are assured that it's fully remote. If this would be of interest to you or someone you know, then please contact me by any of the methods listed below. Regards, Harry -- *Harry Robinson* *Associate* *RJC Group LTD* <http://www.rjcgroup.co.uk/> 27 Clements Lane London EC4N 7AE DL: 020 3983 2647 Mob: 07512685741 Email: harry.robinson(a)rjcgroup.co.uk <edward.campbell(a)rjcgroup.co.uk> Web: www.rjcgroup.co.uk

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