Test & Code

I hear and I forget. I see and I remember. I do and I understand. -- Confucius Matt Harrison is an author and instructor of Python and Data Science. This episode focuses on his training company, MetaSnake, and corporate training. Matt's written several books on Python, mostly self published. So of course we talk about that. But the bulk of the conversation is about corporate training, with Brian playing the role of someone considering starting a corporate training role, and asking Matt, an experienced expert in training, how to start and where to go from there. I think you'll learn a lot from this.Special Guest: Matt Harrison.Sponsored By:PyCharm Professional: Try PyCharm Pro for an extended 4 month trial before deciding which version you need. If you value your time, you owe it to yourself to try PyCharm. Promo Code: TESTANDCODE22Links:MetaSnake — Python Consultant and TrainingIllustrated Guide to Python 3 — A Complete Walkthrough of Beginning Python with Unique Illustrations Showing how Python Really WorksLearning the Pandas Library — Python Tools for Data Munging, Analysis, and VisualizationBeginning Python Programming — Learn Python in 7 Days ★ Support this podcast on Patreon ★

There are a lot of learning styles and a lot of ways to learn Python. If you started Python through a class at work, or through an online course, or maybe an email series, it's possibly you may have learned from Reuven Lerner. If your first encounter with pytest was reading an article in Linux Journal recently, that would be the writing of Reuven. Reuven Lerner teaches Python. This interview definitely falls into the category of talking with interesting people doing interesting things with Python. We talk about how incorporating testing into teaching can add a level of clarity to the interaction and help people duirng the learning process. I'm also fascinated by people who teach and train because it's a skill I'm trying to improve.Special Guest: Reuven Lerner.Sponsored By:PyCharm Professional: Try PyCharm Pro for an extended 4 month trial before deciding which version you need. If you value your time, you owe it to yourself to try PyCharm. Promo Code: TESTANDCODE22Links:Reuven's siteReuven's blogReuven's online storeReuven's newsletternewsletter for trainersWeekly Python Exercise: Newbie edition — a 10% discount code for Test & Code listeners for the late January cohort. ★ Support this podcast on Patreon ★

A look back on 3 years of podcasting, and a bit of a look forward to what to expect in 2019. Top 5 episodes: 2: Pytest vs Unittest vs Nose 33: Katharine Jarmul - Testing in Data Science 18: Testing in Startups and Hiring Software Engineers with Joe Stump 45: David Heinemeier Hansson - Software Development and Testing, TDD, and exploratory QA 27: Mahmoud Hashemi : unit, integration, and system testing Honorable mention: 32: David Hussman - Agile vs Agility, Dude's Law, and more This episode also went through lots of: what went well what was lacking what's next Please listen and let me know where I should take this podcast.Sponsored By:DigitalOcean: Get started with a free $100 credit ★ Support this podcast on Patreon ★

Julian Sequeira is Co-Founder of PyBit.es (a blog/platform created to teach and learn Python) and a Python Trainer at Talk Python Training. He's also a survivor of the 100DaysOfCode in Python Challenge. We talk about the 100 days challenge, about learning Python, and about how cool it is to learn within a community.Special Guest: Julian Sequeira.Sponsored By:DigitalOcean: Get started with a free $100 credit Links:PyBites BlogPyBites Code Challenges PlatformTalkPython + PyBites 100 Days of Code in Python CoursePyBites 100 Days of Code RepoPybit.es Slack Community ★ Support this podcast on Patreon ★

Thea Flowers is a Pythonista and open source advocate. She helps empower developers of all backgrounds and experience levels using Python and open source software and hardware. Thea is the creator of Nox, the co-chair of PyCascades 2019, the lead maintainer of urllib3, and a member of the Python Packaging Authority and Packaging Working Group. Thea works on Google Cloud Platform's wonderful Developer Relations team where she works on API client libraries and community outreach. All of that is definitely cool enough. But she is also building a synthesiser based on Sega Genesis chips. So of course, that's where we'll start the conversation.Special Guest: Thea Flowers.Sponsored By:DigitalOcean: Get started with a free $100 credit Links:Genesynth part 1: idea and researchGenesynth part 2: basic communicationGenesynth part 3: proper audio amplificationnoxurllib3PyCascades 2019thea.codes ★ Support this podcast on Patreon ★

Let's say you've got a web application you need to test. It has a REST API that you want to use for testing. Can you use Python for this testing even if the application is written in some other language? Of course. Can you use pytest? duh. yes. what else? What if you want to spin up docker instances, get your app running in that, and run your tests against that environment? How would you use pytest to do that? Well, there, I'm not exactly sure. But I know someone who does. Dima Spivak is the Director of Engineering at StreamSets, and he and his team are doing just that. He's also got some great advice on utilizing code reviews across teams for test code, and a whole lot more.Special Guest: Dima Spivak.Sponsored By:DigitalOcean: Get started with a free $100 credit Links:Introducing the StreamSets Test Frameworkpytest-benchmark · PyPIStreamSets Test Framework-based tests for StreamSets Data CollectorStreamSets: Where DevOps Meets Data Integrationslack channel for Test & Code ★ Support this podcast on Patreon ★

Data science, data engineering, data analysis, and machine learning are part of the recent massive growth of Python. But really what is data science? Vicki Boykis helps me understand questions like: No really, what is data science? What does a data pipeline look like? What is it like to do data science, data analysis, data engineering? Can you do analysis on a laptop? How big does data have to be to be considered big? What are the challenges in data science? Does it make sense for software engineers to learn data engineering, data science, pipelines, etc? How could someone start learning data science? Also covered: A type work (analysis) vs B type work (building) data lakes and data swamps predictive models data cleaning development vs experimentation Jupyter Notebooks Kaggle ETL pipelines I learned a lot about the broad field of data science from talking with Vicki.Special Guest: Vicki Boykis.Sponsored By:DigitalOcean: Get started with a free $100 credit Links:How to Lie with Statistics : Darrell HuffShould you replace Hadoop with your laptop?KaggleProject JupyterSoviet Art Bot — A bot that finds socialist realism paintings and tweets them out ★ Support this podcast on Patreon ★

Michael Kennedy of Talk Python and Python Bytes fame joins Brian to talk about being a great guest and what to expect. Even if you have never wanted to be on a podcast, you might learn some great tips. A few of the things we talk about will be helpful for other endeavors, like public speaking, guest blog posts, look for unsolicited job opportunities. Some people have never been on a podcast before, and are possibly freaked out about some of the unknowns of being on a podcast. That's why we did this episode. Michael and I discuss a bunch of the niggly details so that you can be relaxed and know what to expect. Topics include: If you want to be on a podcast How to stand out and be someone a podcast would want to have on a show. How to suggest yourself as a guest and the topic you want to discuss. Picking a topic for a podcast What to do before the show to prepare Helping the host out with some information Some hardware (not much) Some software (all free) Sending info like bio, headshot, links, etc. What to expect the host or show to do before the recording. Where to record Sketching out some show topics with the host, maybe on a shared document. What to expect and do Right before the show During the conversation After the recording When it goes live (help promote it) Special Guest: Michael Kennedy.Sponsored By:DigitalOcean: Get started with a free $100 credit ★ Support this podcast on Patreon ★

What happens when 100% test code coverage just isn't enough. In this episode, we talk with Mahmoud Hashemi about glom, a very cool project in itself, but a project that needs more coverage than 100%. This problem affects lots of projects that use higher level programming constructs, like domain specific languages (DSLs), sub languages mini languages, compilers, and db query languages. Also covered: awesome Python applications versioning: 0-ver vs calver vs semver Special Guest: Mahmoud Hashemi.Sponsored By:DigitalOcean: Get started with a free $100 credit Links:Announcing glom — Restructured Data for PythonDomain-specific language - Wikipediaawesome-python-applications — Free software that works great, and also happens to be open-source Python.Meld — a visual diff and merge tool targeted at developers.ZeroVer: 0-based Versioning SemVer: Semantic Versioning CalVer: Calendar Versioningepisode 27: unit, integration, and system testing - Mahmoud Hashemi ★ Support this podcast on Patreon ★

Paul talks about the beginning years of Python. Talking about Python's beginnings is also talking about the Python community beginnings. Yes, it's reminiscing, but it's fun.Special Guest: Paul Everitt.Sponsored By:DigitalOcean: Get started with a free $100 credit Links:Python 1994 Panel Discussion PyCon 2017"Python 1994", PyBay2017Spam, Spam, Spam, ... ★ Support this podcast on Patreon ★