List of videos

Presented by: Hank Preston How do you test that your network is healthy? You probably ping a few things, run some show commands, and watch for open trouble tickets. I don’t think I’ll stir up a ton of controversy by saying that’s a really bad method. With the move towards network automation, NetDevOps, and Network Reliability Engineering (NRE), we need to have robust, repeatable tests to check the state of the network from Layer 1 to 7. pyATS is an open source network test framework that was built by software developers for network developers. It provides all the tools automation engineers need to describe test cases, run jobs, gather reports, and make the entire process part of your network automation pipeline. In this talk, we’ll look at everything you need to write your first few test cases, and discuss strategies for what you should test, and when. Talk slides: https://www.slideshare.net/HankPreston1/introduction-to-writing-network-tests-with-pyats Talk resources: - Code and Demo: https://github.com/hpreston/intro-network-tests - Twitter: https://twitter.com/hfpreston

Presented by: Dr. Cristián Maureira-Fredes Extending Python with C is a technique that many popular modules use for OS-level operations, serialization, performance, and more, but dealing with C code is not simple: you need to take care of memory, understand pointers, and write many lines of code for simple tasks. Luckily for you, there is C++. Wait! Don’t be scared! I know maybe you heard bad stories and saw complicated pieces of C code, but: are you aware of how C has been evolving? The latest C++ standards include many goodies that smell a bit of Python, and I will show them to you. During this talk, you will learn how to include C features into CPython modules, how to create hybrid applications**, and even to extend existent C applications with Python, making them scriptable**. This talk is intended for developers who are familiar with Python and know basic C, but you don’t need to know any C++ to take the most out of it. Talk resources: - Github repository: https://github.com/cmaureir/pycon2020_cpp_python

Presented by: Flávio Juvenal da Silva Junior How to find duplicate records in a dataset without unique identifiers, like the SSN for US citizens? The answer is to use Record Deduplication techniques: look for matches by cleaning and comparing attributes in a fuzzy way. In this talk, you’ll learn with Python examples how to do this without needing any expert Data Science knowledge. There are several critical applications of Record Deduplication in government and business. For example, by deduping records from Census data, the Australian government was able to find there were 250,000 fewer people in the country than they previously thought. This reduction impacted the estimations of government agencies and even caused the revision of economic projections. Similarly, businesses can use record deduplication techniques to clean up customers’ data. In this talk, you’ll learn with Python examples the main concepts of Record Deduplication: what kinds of problems can be solved, what’s the most common workflow for the process, what algorithms are involved, and which tools and libraries you can use. Although some of the discussed concepts are related to data mining, any intermediate-level Python developer will be able to learn the basics of how to dedupe data using Python. Talk slides: https://github.com/vintasoftware/deduplication-slides/tree/pycon-2020

Presented by: Hannah Stepanek What’s an ORM? Is there a way to write database queries so that they are compatible with multiple types of databases? How do you make database changes (such as adding a new table or a new column) safely? What is a connection pool and why is it useful? What are some things that can go wrong when operating at scale? Is lazy loading slowing you down? In this talk we’ll take a deep dive into how the Python libraries SQLAlchemy and Alembic make managing production databases simple, efficient, and painless so you can get back to feature development. Talk slides: http://bit.ly/lets-talk-databases-python

Presented by: Wendi Dreesen I am proposing a talk that describes how to get started using a Raspberry Pi with Python. My child wanted to do a science fair project this year using the Raspberry Pi to collect the data. The project was to measure how long marbles would take to travel down different types of tracks: linear and curvy. In the talk I present a few tips that should help to make a successful project. Then I proceed to describe the project in detail and how we broke it down into steps to get it completed. Talk resources: https://github.com/wdreesen/rasp_pi_photogate_tracks

Presented by: Rebeca Sarai Customers’ data is important. The number of privacy laws in recent years has grown from 20 to 100, to name a few: PCI compliance in the payment industry, the European GDPR regulation, and the Brazilian LGPD. All these new regulations attempt to bridge an old gap: data anonymity. How to handle data and protect the individuals comprised in it? Companies often face lawsuits to compensate for personal information breaches in their database. Many times production data is copied onto test, QA or staging environments, only to be followed by exposure to the eyes of testers, receivers, or unauthorized developers on machines less protected than production environments. It is not seldom for files also to be shared with external partners, who often require but a small part of the data transferred, and granting access to user’s data might be a breach. If in one hand sharing data is both necessary and inevitable, on the other technologies that assure the privacy of individuals details are no longer only desirable, but essential. In this talk, we will approach two important topics: how to manage data whilst securing users’ personal information and how to do it in machine learning models. Exposing different techniques of anonymization and pseudonymization (k-anonymity, differential privacy, and others), showing that solving the anonymity problem is much more complex than replacing names, last names, and social security numbers. Talk slides: https://drive.google.com/open?id=1cx8zDJsHh6PfQJw5RheIdho3xA37TTi-mP9975VnWHY Talk resources: https://github.com/rsarai/security-and-privacy/blob/master/Security%20and%20Privacy.ipynb

Presented by: Terri Oda Detecting known software vulnerabilities is hard to do perfectly, but it’s easy to get part way there. The CVE Binary Tool is a tool that detects issues in a few components but has grand ambitions. Learn how it works, how to use it & how to improve it so together we can help everyone be more secure. Talk slides: https://docs.google.com/presentation/d/1ceHAXQ3qeTowpoCyOWAtDvhmLbxVddbCEllac4EJIkY/edit?usp=sharing Github: https://github.com/intel/cve-bin-tool

Presented by: Reuven M. Lerner When you invoke a function, how does it know how many arguments to expect? How does it distinguish between local and global (and enclosing) variables? How does it know that you defined the function with args and/or *kwargs? And where does it store such things as docstrings, annotations, and defaults? The short answer is that Python functions are objects – no different from integers, strings, and dicts. And like all other bjects, functions have attributes. It turns out that those attributes are the source of functions’ power. In this talk, we’ll peek into function attributes, gaining an understanding of (and appreciation for) the way in which functions are built. We’ll also see the relationship between attributes, functions, and Python bytecodes. And while we’ll be dissecting many functions, I can assure you that none of them will be harmed in our quest for deeper understanding. Talk resources: http://FunctionDissectionLab.com

Presented by: Neeraj Pandey Art is everywhere and it’s beautiful. Unleash the creative artist inside you with the beauty of Generative Art. Learn how algorithms are used to create these aesthetic art forms, how motion and structures emit sounds and what toolkits are required to do so. The talk will take the audience to a small history of Generative Art and how autonomously these art forms are created using algorithms with various examples using Processing, PyCario and more. Talk slides: bit.ly/350H8rF Twitter: twitter.com/neerajp99/