Issue #395 (Nov. 19, 2019) (36)

Threading in Python Learn how to use threading in your Python programs. You’ll see how to create threads, how to coordinate and synchronize them, and how to handle common problems that arise in threading. REAL PYTHON video

Reduce Pandas Memory Usage by Loading Less Data How to reduce the memory your DataFrame uses at the time it is initially loaded: by dropping columns, lower-range numerical dtypes, and categoricals. ITAMAR TURNER-TRAURING

Debug Your Python Applications Fast With Datadog APM and Distributed Tracing Use detailed flame graphs to identify bottlenecks and latency, and correlate log and trace data for individual requests to get the necessary context to debug critical errors. Plus, the Datadog tracing client auto-instruments popular frameworks and libraries like Flask, Tornado, Django, and more → DATADOG sponsor

The Return of Python Dictionary “Addition” An interesting summary of discussions around PEP 584 (“Add + and += operators to the built-in dict class”). JAKE EDGE

Why Is the Migration to Python 3 Taking So Long? Related discussion on Hacker News. VICKI BOYKIS

Don’t Use property() for Computationally Intensive Tasks “To a user, attribute-style access is implicitly assumed to be fast. In contrast, a well-named method can communicate workload: raymondh.family_members vs raymondh.scan_entire_social_graph()“ RAYMOND HETTINGER

I Was About to Learn Django. Should I Wait a Bit for 3.0 to Have Some Tutorials Out? REDDIT

Getting Started With Python IDLE See how to use the development environment included with your Python installation. Python IDLE is a small program that packs a big punch! You’ll learn how to use Python IDLE to interact with Python directly, work with Python files, and improve your development workflow. REAL PYTHON

When Your Data Doesn’t Fit in Memory: The Basic Techniques Python techniques for processing “bigger than RAM” data on a single computer, with minimal setup, and as much as possible using the same libraries you’re already using. ITAMAR TURNER-TRAURING • Shared by ITAMAR TURNER-TRAURING

Unconventional Secure and Asynchronous RESTful APIs Using SSH How to build secure asynchronous APIs in Python using Korv and AsyncSSH that listen on TCP sockets over SSH sessions. TRYEXCEPTPASS.ORG • Shared by Cristian Medina

Pandas GroupBy: Your Guide to Grouping Data in Python Learn how to work adeptly with the Pandas GroupBy facility while mastering ways to manipulate, transform, and summarize data. You’ll work with real-world datasets and chain GroupBy methods together to get data in an output that suits your purpose. REAL PYTHON

Jupyter on Your Phone (Or Anywhere, Really) How to host Jupyter notebooks on your own server so you can access them anywhere, even with your mobile phone. UMAR KHAN

Easily Build Beautiful Video Experiences Into Your Python App Mux Video is an API-first platform, powered by data and designed by video experts. Test it out to build video for your Python app that streams beautifully, everywhere. MUX sponsor

Find a Python Job Through Vettery Vettery specializes in developer roles and is completely free for job seekers. Interested? Submit your profile, and if accepted, you can receive interview requests directly from top companies seeking Python devs. Get started → VETTERY sponsor