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<!DOCTYPE html>
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<title>Previous talks - Southampton Python</title>
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<a href="index.html" class="navbar-brand" target="_self">SPUG <small>Southampton Python Users Group</small></a>
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<h1>Previous talks</small></h1>
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<h3 class="list-group-item-heading">
Python testing with pytest: motivation, demonstration, and practices
</h3>
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<div class="list-group-item" style="min-height: 300px; vertical-align: top;">
<img src="images/mark_vousden.png" style="float: right; width: 192px" />
<p>Testing software ensures that simulation or application software remains
functional throughout development, and proves that software operates a
specific way when deployed or frozen. In software engineering, testing is a
necessary practice for reliable software. This talk motivates the use of
pytest to test Python code by outlining common requirements for a testing
framework, and demonstrates the use of pytest.</p>
<p>One common requirement from a testing framework is that a developer must be
able to test aspects of their software under many conditions without
duplicating code, using test parameterisation. Another requirement is the
need to test certain areas of code in isolation to more easily identify the
cause of problems; this can be achieved by mocking areas that are tested
elsewhere. Testing all code in every possible condition is ideal, but time
must be budgeted to run the most essential tests. This limitation motivates
the design of a fast-running test suite; this talk demonstrates running tests
in parallel and across machines. After a summary, this talk concludes with a
brief mention of other useful testing tools.</p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">Who</h4>
<p class="list-group-item-text"><a href="http://mvousden.co.uk/about.html">Mark Vousden</a></p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">When</h4>
<p class="list-group-item-text">6pm–7.30pm, 29th November 2017</p>
</div>
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<h4 class="list-group-item-heading">Where</h4>
<p class="list-group-item-text">
Southampton University, Highfield Campus, Building 6 (Nuffield Theatre), Room 1081
(<a href="http://maps.southampton.ac.uk/#17/50.93540/-1.39640">map</a>)
</p>
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<h3 class="list-group-item-heading">Sustainable Scientific Software Development</h3>
<!--<p class="list-group-item-text"></p>-->
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<div class="list-group-item" style="min-height: 300px; vertical-align: top;">
<img src="images/alice_harpole.jpg" style="float: right" />
<p>In the experimental sciences, new theories are developed by
applying the scientific method to produce results which are accurate,
reproducible and reliable. This involves testing the experimental
setup to show that it is working as designed and thoroughly documenting
the progress of the experiment. Results will not be trusted unless
the experiment has been carried out to a suitable standard.</p>
<p>In computational science, we should aim to apply the same principles.
Results should only be trusted if the code that has produced it has
undergone rigorous testing which demonstrates that it is working
as intended, and any limitations of the code (e.g. numerical errors)
are understood and quantified. The code should be well documented
so that others can understand how it works and run it themselves
to replicate results.
</p>
<p>Unfortunately, this can be quite challenging. By their very
nature, scientific codes are built to investigate systems where
the behaviour is to some extent unknown, so testing them can be
quite difficult. They can be very complex, built over a number of
years (or even decades!) with contributions from many people.
However, even for the most complicated of codes there are a number
of different tools we can use to build robust, reliable code.</p>
<p>In this talk, I shall look at techniques and tools you can use
to build more sustainable scientific code, including testing,
continuous integration and documentation.</p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">Who</h4>
<p class="list-group-item-text"><a href="http://www.southampton.ac.uk/~ah1e14/">Alice Harpole</a></p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">When</h4>
<p class="list-group-item-text">6pm–7.30pm, Thursday 5th October 2017</p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">Where</h4>
<p class="list-group-item-text">
Southampton University, Highfield Campus, Building 7, Room 3023
(<a href="http://maps.southampton.ac.uk/#17/50.93540/-1.39640">map</a>)
</p>
</div>
</div>
</div>
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<h4 class="list-group-item-heading">Title</h4>
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<h4 class="list-group-item-heading">Description</h4>
<p class="list-group-item-text">—</p>
<div id=imagecontainer style="height: 100px; display: flex; justify-content: center;">
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<h4 class="list-group-item-heading">Who</h4>
<p class="list-group-item-text">—</p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">When</h4>
<p class="list-group-item-text">—</p>
</div>
<div class="list-group-item">
<h4 class="list-group-item-heading">Where</h4>
<p class="list-group-item-text">—</p>
</div>
</div>
</div>-->
</div> <!-- End of talks row -->
</div> <!-- End of talks div -->
<div class="main-div">
<h2>Older talks</h2>
<ul>
<li>Oliver Laslett, 3rd May 2017: <em><a href="https://github.com/cytora/clickbait-workshop">Detect clickbait with machine learning</a></em></li>
<li>Ryan Pepper, 2nd March 2017: <em><a href="https://github.com/rpep/2017-03-02-SPUG-Cython-Talk">Cython - how to speed up Python for your research</a></em></li>
<li>Sophia Schillai, 3rd October 2016: <em>Snakes on a Boat: Robotic sailing with Python</em></li>
<li>Ryan Pepper & Alvaro Perez, 4 August 2016: <em><a href="http://computationalmodelling.bitbucket.org/tools/continuous-integration.html">Continuous Integration with CircleCI</a></em></li>
<li>Robin Wilson, 5 July 2016: <em>Writing Python to process millions of row of mobile data - in a weekend</em></li>
<li>Jens Nielsen, 19 May 2016: <em><a href="https://github.com/jenshnielsen/southampton_matplotlib_talk">Matplotlib 2.0: style changes and upcoming features</a></em></li>
<li>Thomas Kluyver, 1 Feb 2016: <em>IPython and Jupyter: Interactive computing in Python (and other languages)</em></li>
</ul>
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