eBPF has become the key technology for infrastructure software. This session tells you everything you need to know about eBPF in 5 minutes. Why eBPF matters and why it exists. What it can do. What it can’t do. Who uses it for what. And finally, what the future holds. PUBLICATION PERMISSIONS:
Original video was published with the Creative Commons Attribution license (reuse allowed), Link: https://www.youtube.com/watch?v=KhPrMW5Rbbc https://www.youtube.com/watch?v=45h6iqtorZQ
Manning's authors Reuven Lerner and Dane Hillard discuss the past, present, and future of the Python programming language, privacy engineering, Big Data, and ethics. Their passionate and dynamic conversation in this Code Call Session is geared toward becoming a Pythonista pro. This video is an excerpt from a Code Calls session by Reuven Lerner and Dane Hillard. To watch the full video go to http://mng.bz/v154 📚📚📚
Reuven Lerner 📖 Python Workout | http://mng.bz/4M0B
Discount Code: WATCHPYTHON40
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Dane Hillard 📖 Practices of the Python Pro | http://mng.bz/Q2Am Discount Code: WATCHPYTHON40
📚📚📚 About the books: Reuven Lerner – Python Workout
Python Workout presents 50 exercises that focus on key Python 3 features. In it, expert Python coach Reuven Lerner guides you through a series of small projects, practicing the skills you need to tackle everyday tasks. You'll appreciate the clear explanations of each technique, and you can watch Reuven solve each exercise in the accompanying videos. Dane Hillard – Practices of the Python Pro
Practices of the Python Pro teaches you to design and write professional-quality software that’s understandable, maintainable, and extensible. Dane Hillard is a Python pro who has helped many dozens of developers make this step, and he knows what it takes. With helpful examples and exercises, he teaches you when, why, and how to modularize your code, how to improve quality by reducing complexity, and much more. Embrace these core principles, and your code will become easier for you and others to read, maintain, and reuse. https://www.youtube.com/watch?v=qRXPcANY-Is
It's common for data scientists to narrowly focus on the APIs of the tools they use every day—pandas, matplotlib, pymc, dask, &c.—to the detriment of any focus on the surrounding programming language. In the case of tools like matplotlib, the total amount of Python we need to know is limited to what existed when matplotlib was first developed. (Did you know that matplotlib predates @property? That explains a lot…) In the case of newer tools like dask or pymc or even pandas, we may encounter some newer parts of Python—e.g., context managers or descriptors—as part of these tools' API design, but it's very easy to accept these as mere “syntax.” In this talk, we will discuss where a deeper understanding of pure Python has direct and immediate consequences to your work as a data scientist. We will discuss where these parts of Python you may have skimmed over show up in analytical code, outside of the mere “syntax” of an API. This talk will be organised around answering the following questions:
– why do generators even matter (and who cares about coroutines)?
– the itertools module is great… if I were writing scripts, but where does it show up in data analysis?
– object orientation seems like a bunch of bureaucracy—can it really simplify my analytical code?
– why should I bother with data types in builtins and collections; is the pandas.DataFrame not enough?
– knowledge of Python internals would probably be useful, if I were a programmer writing scripts, but why do they matter for a data scientist? Bio:
James Powell
James Powell is the founder and lead instructor at Don’t Use This Code. A professional Python programmer and enthusiast, James got his start with the language by building reporting and analysis systems for proprietary trading offices; now, he uses his experience as a consultant for those building data engineering and scientific computing platforms for a wide range of clients using cutting-edge open source tools like Python and React. He also currently serves as a Board Director, Chair, and Vice President at NumFOCUS, the 501©3 non-profit that supports all the major tools in the Python data analysis ecosystem (i.e., pandas, numpy, jupyter, matplotlib). At NumFOCUS, he helps build global open source communities for data scientists, data engineers, and business analysts. He helps NumFOCUS run the PyData conference series and has sat on speaker selection and organizing committees for 18 conferences. James is also a prolific speaker: since 2013, he has given over seventy (70) conference talks at over fifty (50) Python events worldwide. PUBLICATION PERMISSIONS:
PyData Organizer provided Coding Tech with the permission to republish PyData tech talks. CREDITS:
PyData YouTube channel: https://www.youtube.com/@PyDataTV https://www.youtube.com/watch?v=-Y0eTPoMjVk