6 GAN Architectures You Really Should Know

Generative Adversarial Networks (GANs) were first introduced in 2014 by Ian Goodfellow et. al. and since then this topic itself opened up a new area of research. Within a few years, the research community came up with plenty of papers on this topic some of which have very interesting names :). You have CycleGAN, followed […]

The post 6 GAN Architectures You Really Should Know appeared first on neptune.ai.

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EuroPython: EuroPython 2020: CFP for the Online Event

Since we had started the CFP under the assumption of running an in-person conference and are now switching EuroPython 2020 to an online event, we will extend the CFP for another two weeks until April 12, to give everyone who would like to participate in this new format, a chance to submit a session proposal.

EuroPython 2020 Online - Call for Proposal

The online event will have this layout:

• July 23 - 24 (Thursday, Friday): conference days
• July 25 - 26 (Saturday, Sunday): sprint days
  

Presenting at EuroPython

For the conference days, we are looking for the following session types:

• Talks of 35- or 45-minute duration (including 3-5 minutes for Q&A)
• Posters
• Help desks / Panels / Interactive sessions

We will give out free tickets to the event for all selected speakers.

For posters, we are planning to collect them on a gallery page, together with PDF versions to read during the event. The speaker will then be available during the poster session to answer questions and present more details using screen sharing.

Help desks, panels and interactive sessions will be run using virtual rooms we’ll make available during the conference days.

We will also have lightning talks for the online event, but those will be collected closer to the event using a separate form or Google sheet - similar to how we run this at the in-person conference.

For submitting sprints, please check our sprints page. Note that unlike the conference days, the sprints day won’t require buying a ticket.

Let’s make this an engaging event for everyone

Even though we’re running an online event, our aim is to make the online event as engaging as possible, so we will provide ways for direct interaction with the speakers after their talk in separate virtual rooms and additionally a chat system for asynchronous interaction.

The conference system will also allow live polls and text or audio/video based Q&A sessions, so please consider this when preparing your sessions and add any polls you’d like to run in the submission notes section (“Additional information for talk reviewers”).

The conference will be held between 09:00 CEST and 20:00 CEST on the two conference days. We will try to schedule talks based on location and timezone of the speaker. Please indicate your timezone in submission notes.

Thanks,
–
EuroPython 2020 Team
https://ep2020.europython.eu/
https://www.europython-society.org/

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Matt Layman: Onboarding Continuity - Building SaaS #50

In this episode, we stepped from the welcome onboarding page to the first interactive page in the flow. I extracted the common banner for each of the templates and customized it for each of the steps in the process. The first thing we did was create a button on the starting page. The button connects the welcome page to the second step in the flow where the app will ask for information about the user’s school year.

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Python Bytes: #175 Python string theory with superstring.py

<p>Sponsored by Datadog: <a href="http://pythonbytes.fm/datadog"><strong>pythonbytes.fm/datadog</strong></a></p> <p>Special Guest: <a href="https://twitter.com/__mharrison__"><strong>Matt Harrison</strong></a></p> <p><strong>Topic #0: Quick chat about COVID 19.</strong></p> <ul> <li>What does your world look like?</li> <li>Amusing to see news channels, daily shows, etc, learning what we podcasters have figured out years ago</li> </ul> <p><strong>Brian #1:</strong> <a href="https://medium.com/better-programming/dictionary-merging-and-updating-in-python-3-9-4ac67c667ce"><strong>Dictionary Merging and Updating in Python 3.9</strong></a></p> <ul> <li>Yong Cui, Ph.D.</li> <li>Python 3.9, scheduled for Oct release, will introduce new merge <code>(|)</code> and update <code>(|=)</code> operators, a.k.a. union operators</li> <li>Available in <a href="https://www.python.org/downloads/release/python-390a5/">alpha 4 and later</a></li> <li>see also <a href="https://www.python.org/dev/peps/pep-0584/">pep 584</a></li> </ul> <pre><code> # merge d1 = {'a': 1, 'b': 2} d2 = {'c': 3, 'd': 4} d3 = d1 | d2 # d3 is now {'a': 1, 'b': 2, 'c': 3, 'd': 4} # update d1 = {'a': 1, 'b': 2} d1 |= {'c': 3, 'd': 4} # d1 is now {'a': 1, 'b': 2, 'c': 3, 'd': 4} # last one wins if contention for both | and |= d1 = {'a': 1, 'b': 2} d1 |= {'a': 10, 'c': 3, 'd': 4} # d1 is now {'a': 10, 'b': 2, 'c': 3, 'd': 4} </code></pre> <p><strong>Matt #2:</strong> <a href="https://github.com/btwael/superstring.py"><strong>superstring</strong></a></p> <ul> <li>An efficient library for heavy-text manipulation in Python, that achieves a remarkable memory and CPU optimization.</li> <li>Uses Rope (data structure) and optimization techniques.</li> <li>Performance comparisons for 50,000 char text <ul> <li>memory: 1/20th</li> <li>speed: 1/5th</li> </ul></li> <li>Features <ul> <li>Fast and Memory-optimized</li> <li>Rich API <ul> <li>concatenation (a + b)</li> <li>len() and .length()</li> <li>indexing</li> <li>slicing</li> <li>strip</li> <li>lower</li> <li>upper</li> </ul></li> </ul></li> <li>Similar functionalities to python built-in string</li> <li>Easy to embed and use.</li> <li>I wonder if any of these optimizations could be brought into CPython</li> <li>Beware, it’s lacking tests</li> </ul> <p><strong>Michael #3:</strong> <a href="https://pyfound.blogspot.com/2020/03/new-pip-resolver-to-roll-out-this-year.html"><strong>New pip resolver to roll out this year</strong></a></p> <ul> <li>via PyCoders</li> <li>The developers of pip are in the process of developing a new resolver for pip (as <a href="https://pyfound.blogspot.com/2019/12/moss-czi-support-pip.html">announced on the PSF blog</a> last year).</li> <li>As part of that work, there will be some major changes to how pip determines what to install, based on package requirements.</li> <li>What will change: <ul> <li>It will <strong>reduce inconsistency</strong>: it will <em>no longer install a combination of packages that is mutually inconsistent</em>.</li> <li>It will be <strong>stricter</strong> - if you ask pip to install two packages with incompatible requirements, it will refuse (rather than installing a broken combination, like it does now).</li> </ul></li> <li>What you can do to help <ul> <li>First and most fundamentally, <a href="https://bit.ly/pip-ux-studies">please help us understand how you use pip by</a> <a href="https://bit.ly/pip-ux-studies"><strong>talking with our user experience researchers</strong></a>.</li> <li>Even before we release the new resolver as a beta, you can help by <strong>running</strong> <code>**pip check**</code> <strong>on your current environment</strong>.</li> <li>Please make time to <strong><em>test</em></strong> <strong>the new version of pip, probably in May.</strong></li> <li><strong>Spread the word!</strong></li> <li>And if you develop or support a tool that wraps pip or uses it to deliver part of your functionality, please make time to <strong>test your integration with our beta in May</strong></li> </ul></li> </ul> <p><strong>Matt</strong> <strong>#4:</strong> <a href="https://www.kaggle.com/saga21/covid-global-forecast-sir-model-ml-regressions"><strong>Covid-19 Data</strong></a></p> <ul> <li>Think global act local</li> <li>Problem - No local data</li> <li>Made my own plots - current status no predictions</li> <li>ML works ok for basic model</li> <li>Implementing SIR Model with ordinary differential equations <strong>scipy odeint function</strong> </li> </ul> <p><strong>Brian #5:</strong> <a href="https://blog.carlmjohnson.net/post/2020/python-square-of-opposition/"><strong>Why does all() return True if the iterable is empty?</strong></a></p> <ul> <li>Carl Johnson</li> <li>Q: “Why does <code>all()</code> return <code>True</code> if the iterable is empty? Shouldn’t it return <code>False</code> just like <code>if my_list:</code>would evaluate to <code>False</code> if the list is empty? What’s the thinking behind it returning <code>True</code>?”</li> <li>Lesson 1: "… basically doesn’t matter. The Python core team chose to make <code>all([])</code>return <code>True</code>, and whatever their reasons, you can program your way around by adding wrapper functions or <code>if</code> tests. ”</li> <li>Lesson 2: “all unicorns are blue”</li> <li>Lesson 3: “This is literally a 2,500 year old debate in philosophy. The ancients thought “all unicorns are blue” should be false because there are no unicorns, but modern logic says it is true because there are no unicorns that aren’t blue. Python is just siding with modern predicate logic, but your intuition is also quite common and was the orthodox position until the last few hundred years.”</li> <li>Blog post goes into teaching about predicate logic, Socrates, Aristotelean syllogisms, and such.</li> <li>And, really, no answer to why. But now, I’ll never forget that <code>all([]) == True</code>.</li> </ul> <p><strong>Michael #6:</strong> <a href="https://github.com/CFMTech/pytest-monitor"><strong>pytest-monitor</strong></a></p> <ul> <li>written by Jean-Sébastien Dieu</li> <li>pytest plugin for analyzing resource usage during test sessions</li> <li>Analyze your resources consumption through test functions: <ul> <li>memory consumption</li> <li>time duration</li> <li>CPU usage</li> </ul></li> <li>Keep a history of your resource consumption measurements.</li> <li>Compare how your code behaves between different environments.</li> <li>Usage: Simply run <em>pytest</em> as usual: <em>pytest-monitor</em> is active by default as soon as it is installed. </li> <li>After running your first session, a .pymon sqlite database will be accessible in the directory where pytest was run.</li> <li>You will need a valid Python 3.5+ interpreter. To get measures, we rely on: <ul> <li><em>psutil</em> to extract CPU usage</li> <li><em>memory_profiler</em> to collect memory usage</li> <li>and <em>pytest</em> (obviously!)</li> </ul></li> </ul> <p>Extras:</p> <p>Michael:</p> <ul> <li><code>switchlang</code> is now <a href="https://pypi.org/project/switchlang/"><strong>on pypi</strong></a> <strong>:</strong> <code>pip install switchlang</code></li> <li><code>markdown-subtemplate</code> is now <a href="https://pypi.org/project/markdown-subtemplate/"><strong>on pypi</strong></a>: <code>pip install markdown-subtemplate</code></li> </ul> <p>Joke:</p> <p>Light timer fix: <a href="https://twitter.com/Sarcastic_Pharm/status/1238060786658009089">https://twitter.com/Sarcastic_Pharm/status/1238060786658009089</a></p>

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PyCharm: PyCharm 2020.1 Release Candidate

We’ve passed the final approach fix, and we’re now established on the glideslope for the PyCharm 2020.1 release. This week’s build brings a couple of bug fixes as we hope to take the release in for a smooth landing. Let us know how we’re doing by getting this version, if you run into any issues please leave us a ticket on YouTrack.

Improvements in this version

• Creating a scientific project (pro only) would fail as a tool window was giving us trouble. This has been resolved.
• Developing with pleasure means that keyboard navigation of forms should work as expected, we had an issue in the new SSH configuration screen (pro only), and this is now resolved.
• PyCharm Professional Edition bundles all database features from JetBrains DataGrip, and they’ve made a couple of improvements that are available in this build: Microsoft SQL Server sparse columns are now supported, and AWS Redshift stored procedures should now have working introspection.

Read the release notes to learn more.

Interested?

Download the RC from our website. Alternatively, you can use the JetBrains Toolbox App to stay up to date.

If you’re on Ubuntu 16.04 or later, you can use snap to get PyCharm RC versions, and stay up to date. You can find the installation instructions on our website.

The release candidate (RC) is not an early access program (EAP) build, and does not bundle an EAP license. If you get PyCharm Professional Edition RC, you will either need a currently active PyCharm subscription, or you will receive a 30-day free trial.

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PyCharm 2020.1 Release Candidate

We’ve passed the final approach fix, and we’re now established on the glideslope for the PyCharm 2020.1 release. This week’s build brings a couple of bug fixes as we hope to take the release in for a smooth landing. Let us know how we’re doing by getting this version, if you run into any issues please leave us a ticket on YouTrack.

Improvements in this version

• Creating a scientific project (pro only) would fail as a tool window was giving us trouble. This has been resolved.
• Developing with pleasure means that keyboard navigation of forms should work as expected, we had an issue in the new SSH configuration screen (pro only), and this is now resolved.
• PyCharm Professional Edition bundles all database features from JetBrains DataGrip, and they’ve made a couple of improvements that are available in this build: Microsoft SQL Server sparse columns are now supported, and AWS Redshift stored procedures should now have working introspection.

Read the release notes to learn more.

Interested?

Download the RC from our website. Alternatively, you can use the JetBrains Toolbox App to stay up to date.

If you’re on Ubuntu 16.04 or later, you can use snap to get PyCharm RC versions, and stay up to date. You can find the installation instructions on our website.

The release candidate (RC) is not an early access program (EAP) build, and does not bundle an EAP license. If you get PyCharm Professional Edition RC, you will either need a currently active PyCharm subscription, or you will receive a 30-day free trial.

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Reuven Lerner: Reminder: My free “Python for non-programmers” course continues tomorrow!

If you’ve never programmed a computer before — or if you tried, and found it frustrating and difficult — then you’re welcome to join my “Python for non-programmers” course, which takes place on Thursdays at 10 a.m. Eastern.

The class is 100% free of charge, and open to anyone who wants. Just register at https://PythonForNonProgrammers.com/. Registering gets you weekly reminders, recordings of previous sessions, and invites to the private forum, where you can chat about the lessons with other students.

And it’s a live class, so you can ask questions during the session, and get an immediate answer from me.

(So yes, this means that if you’re only joining now, you can catch up. And if you miss this or any other lesson, you can access the recording down the line.)

Stay home and stay safe — but while you’re home, take advantage of the opportunity to learn Python! I guarantee that you’ll enjoy it. (And at this price, why not give it a whirl?)

Once again, you can register at https://PythonForNonProgrammers.com/.

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