| 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.
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 →
The Return of Python Dictionary “Addition”
An interesting summary of discussions around PEP 584 (“Add + and += operators to the built-in dict class”).
Why Is the Migration to Python 3 Taking So Long?
Related discussion on Hacker News.
Django 3.0 RC 1 Now Available
PyCon 2020 Tutorial Proposal Deadline Approaching
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:
I Was About to Learn Django. Should I Wait a Bit for 3.0 to Have Some Tutorials Out?
Automated Tasks at Work… Boss Found Out
Senior Python Engineer
STYLIGHT GMBH 📍 MUNICH, GERMANY
Senior Python/Django Developer
SENDCLOUD 📍 EINDHOVEN, NETHERLANDS
Django Full Stack Web Developer
ZEITCODE 📍 AUSTIN, TX, USA
Full Stack Developer
BEANFIELD METROCONNECT 📍 TORONTO, ON, CANADA
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Articles & Tutorials
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.
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
Python Developers Are in Demand on Vettery
Vettery is an online hiring marketplace that’s changing the way people hire and get hired. Ready for a bold career move? Make a free profile, name your salary, and connect with hiring managers from top employers today →
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.
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.
How to Port an
awk Script to Python
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.
Profiling Django With DTrace and cProfile
PyCon Africa 2019 (Recap)
“int” Strips Strings of Whitespace
Projects & Code
modin: Speed Up Your Pandas Workflows
viewflow: Reusable Workflow Library for Django
django-fsm: Friendly Finite State Machines for Django
django-river: Django Workflow Library
BrachioGraph: The Cheapest, Simplest Possible Pen-Plotter
adtk: Unsupervised Anomaly Detection in Time Series
slim4py: Ruby Slim as a Template Engine for Python
Makefile.venv: Manage Python Virtual Environments With a Makefile
jenkinsapi: Python API for Jenkins CI
pythonji: Write Python With Emojis