I am the Lord
@Manjusaka
Get back to business
When I watch technical presentations, I look for at least one of three things:
- Interesting.
- Practical.
- It’s very technical.
For example
- Pipenv is a package management tool that is fun and useful. This is something interesting, practical, and refers to the concerns of the speech.
- I’m going to introduce some of the new fancy dependency libraries in the community, some of the optimization classes, algorithms and data structures, async, that kind of technical stuff.
- Like some of the domestic boring, paste small and medium-sized companies can not be the foundation of the technical architecture, is loaded and not interesting and not practical things.
- Not very technical, but meaningful to the community. Educational outreach, for example, and the growing up of engineers, which may be useful for personal growth, are not on my list of concerns.
Python In Depth: section ▼ New Python Feature: section Python Under The Hood: section Async related: Section Module In Depth: Section Optimizing: Section ▼ Web development Section ▼ Data Science: Section ▼ Build/Test/Documentation/Code Quality: SectionCopy the code
Python In Depth
New Python Feature
- Barry Warsaw – Get your resources faster, with importlib.resources – PyCon 2018
After Py3.7, non-code files inside packages can be read using importlib.resources.
- Raymond Hettinger – Dataclasses: The code generator to end all code generators – PyCon 2018
Dataclasses, introduced after PY3.7, can greatly reduce code
Python Under The Hood
Explains some Python postures on compilation.
- David Beazley – Reinventing the Parser Generator – PyCon 2018
- Emily Morehouse-Valcarcel – The AST and Me – PyCon 2018
- James Bennett – A Bit about Bytes: Understanding Python Bytecode – PyCon 2018
Async related
Asynchrony has been the trend in IO intensive applications for several years
- Nathaniel J. Smith – Trio: Async concurrency for mere mortals – PyCon 2018
- John Reese – Thinking Outside the GIL with AsyncIO and Multiprocessing – PyCon 2018
Module In Depth
Delve into some of Python’s features and modules
- Mario Corchero – Effortless Logging: A deep dive into the logging module – PyCon 2018
- Carl Meyer – Type-checked Python in the real world – PyCon 2018
- Hillel Wayne – Beyond Unit Tests: Taking Your Testing to the Next Level – PyCon 2018
- Zekun Li – There and Back Again: Disable and re-enable garbage collector at Instagram – PyCon 2018
Optimizing
Think the application is slow, might as well learn from others to optimize ideas.
- vigneshwer dhinakaran – Pumping up Python modules using Rust – PyCon 2018
- Matt Davis – Python Performance Investigation by Example – PyCon 2018
- Mike Muller-Faster Python Programs – Measure, Don’t Guess – PyCon 2018
- Ned Batchelder – Big-O: How Code Slows as Data Grows – PyCon 2018
Web development related
Django related
Django postures
- Shauna Gordon-McKeon – Beyond Django Basics – PyCon 2018
- Harry Percival – Intermediate testing with Django: Outside-in TDD and Mocking effectively
- Harry Percival – Introduction to TDD with Django – PyCon 2018
- Philip James – API-Driven Django – PyCon 2018
- Andrew Godwin – Taking Django Async – PyCon 2018
Note: Taking Django Async is the one that’s worth checking more than once. Have a chance to write an article to analyze it.
Web Developing
- Moshe Zadka – Web Applications, A to Z – PyCon 2018
- Graham Dumpleton – Secrets of a WSGI master. – PyCon 2018
Data science
- Alex Petralia – Analyzing Data: What pandas and SQL Taught Me About Taking an Average – PyCon 2018
- Aly Sivji, Joe Jasinski, tathagata dasgupta (t) – Docker for Data Science – PyCon 2018
- Anna Nicanorova – Data Visualization in Mixed Reality with Python – PyCon 2018
- Chalmer Lowe – Statistics and probability: your first steps on the road to data science – PyCon 2018
- Christopher Beacham / Lady Red – Visualizing Algorithms with Python and Programmable LEDs
- Christopher Fonnesbeck – Bayesian Non-parametric Models for Data Science using PyMC3 – PyCon 2018
- Kelsey Pedersen – Augmenting Human Decision Making with Data Science – PyCon 2018
- The importance of exploratory data analysis and data visualization in machine learning – PyCon 2018
- Jake VanderPlas – Performance Python: Seven Strategies for Optimizing Your Numerical Code
- Jake VanderPlas – Exploratory Data Visualization with Vega, Vega-Lite, and Altair – PyCon 2018
A very interesting new visualization library
- Christy Heaton – Intro to Spatial Analysis and Maps with Python – PyCon 2018
Some applications of Python for GIS analysis and maps
- Eric Ma, Mridul Seth – Network Analysis Made Simple: Part I – PyCon 2018
- Mridul Seth, Eric Ma – Network Analysis Made Simple: Part II – PyCon 2018
- Nicolle Cysneiros – Graph Databases: Talking about your Data Relationships with Python – PyCon 2018
Python network analysis
Build/test/documentation/code quality
- Kenneth Reitz – Pipenv: The Future of Python Dependency Management – PyCon 2018
The next generation of package management software, written by Kenneth Reitz
- Dustin Ingram – Inside the Cheeseshop: How Python Packaging Works – PyCon 2018
Popularize setup.py/wheels/eggs/setuptools/distutils/twine posture
- Brian Okken, Paul Everitt – Visual Testing with PyCharm and pytest – PyCon 2018
PyCharm and PyTest collections
- Carol Willing – Practical Sphinx – PyCon 2018
Write documents using Sphinx.
- Nina Zakharenko – Elegant Solutions For Everyday Python Problems – PyCon 2018
How to write Python gracefully
www.slideshare.net/nnja/elegan…
- Jack Diederich – HOWTO Write a Function – PyCon 2018
15 years of development veteran driver teach you how to write a Function
- Kyle Knapp – Automating Code Quality – PyCon 2018
High quality code maintenance
- Greg Price – Clearer Code at Scale: Static Types at Zulip and Dropbox – PyCon 2018
Other Technology Stacks
- Julie Qiu – Build a Search Engine with Python + Elasticsearch – PyCon 2018
Write in the last
There are a few of them are worth two or even N brush, so I finished writing a few articles to introduce it in detail.