|   |  |   |  |   |   |   |    |    | 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.
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 Reduce Pandas Memory Usage by Loading Less Data
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 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 → DATADOGsponsor
 
 The Return of Python Dictionary “Addition”
 An interesting summary of discussions around PEP 584 (“Add + and += operators to the built-in dict class”).
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 Why Is the Migration to Python 3 Taking So Long?
 Related discussion on Hacker News.
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 Django 3.0 RC 1 Now Available
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 PyCon 2020 Tutorial Proposal Deadline Approaching
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 DiscussionsDon’t Use
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 I Was About to Learn Django. Should I Wait a Bit for 3.0 to Have Some Tutorials Out?
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 Python JobsSenior Python Engineer
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 Articles & TutorialsGetting 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.
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 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.
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 Python Developers Are in Demand on Vettery
 
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 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.
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 How to Port an
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 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.
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 Profiling Django With DTrace and cProfile
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 PyCon Africa 2019 (Recap)
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 “int” Strips Strings of Whitespace
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 Projects & Codemodin: Speed Up Your Pandas Workflows
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 viewflow: Reusable Workflow Library for Django
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 django-fsm: Friendly Finite State Machines for Django
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 django-river: Django Workflow Library
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 BrachioGraph: The Cheapest, Simplest Possible Pen-Plotter
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 slim4py: Ruby Slim as a Template Engine for Python
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 jenkinsapi: Python API for Jenkins CI
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 pythonji: Write Python With Emojis
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