| Using a Build System & Continuous Integration in Python |
What advantages can a build system provide for a Python developer? What new skills are required when working with a team of developers? This week on the show, Benjy Weinberger from Toolchain is here to discuss the Pants build system and getting started with continuous integration (CI).
REAL PYTHON podcast
PEP 701: Syntactic Formalization of F-Strings
This Python Enhancement Proposal describes the formalization of a grammar for f-strings, allowing a reduction in the underlying parser code complexity and providing future features like comments in multi-line f-strings.
TelemetryHub by Scout APM, A One-Step Solution for Open-Telemetry
Imagine a world where you could see all of your logs, metrics, and tracing data in one place. We’ve built TelemetryHub to be the simplest observability tool on the market. We supply peace of mind by providing an intuitive user experience that allows you to easily monitor your application →
Running Python Inside ChatGPT
Did you know that ChatGPT knows Python? It knows Python so well, you can even run a Python REPL inside ChatGPT and it supports non-trivial features like decorators, properties, and asynchronous programming.
RODRIGO GIRÃO SERRÃO • Shared by Rodrigo Girão Serrão
PyTexas 2023 Call for Proposals
PyCon US 2023 Registration Launch
PyPI Upgraded to Python 3.11 and Halved Their CPU
Articles & Tutorials
Python Magic Methods You Might Not Have Heard About
Python classes support operations through the definition of magic methods, also known as dunder-methods. To enable to support for
len(), you define
__len__() on your class. There are many Python magic methods, read on to learn about some of the less common ones.
MARTIN HEINZ • Shared by Martin Heinz
Finding JIT Optimizer Bugs Using SMT Solvers and Fuzzing
Finding bugs can be a challenging exercise, but when your code is a Just-In-Time compiler, your bugs create bugs for other people. PyPy has recently added new techniques to find errors in the JIT optimizer. Dive deep into Z3 theory and using fuzzing to find errors.
Connect, Integrate & Automate Your Data - From Python or Any Other Application
At CData, we simplify connectivity between the application and data sources that power business, making it easier to unlock the value of data. Our SQL-based connectors streamline data access making it easy to access real-time data from on-premise or cloud databases, SaaS, APIs, NoSQL and Big Data →
Testing AWS Chalice Applications
“AWS Chalice is a Python-based web micro-framework that leverages on the AWS Lambda and API Gateway services. It is used to create serverless applications.” Learn how to write unit and integration tests in the AWS Chalice space.
AUTH0.COM • Shared by Robertino
8 Levels of Using Type Hints in Python
This article introduces the reader to eight separate levels of type-hint use in Python, starting with annotating basic data types and going all the way up to compound and types for classes.
Concurrency in Python With FastAPI
FastAPI is an
asyncio friendly library, which means you can dive deep into your concurrency needs. This article shows you how to get high performance out of FastAPI using co-routines.
Django Domain-Driven Design Guide
“This style guide combines domain-driven design principles and Django’s apps pattern to provide a pragmatic guide for developing scalable API services with the Django web framework.”
Summary of Guido van Rossum Interview
In case you missed the three hour interview by Lex Fridman, or decided that it was a bit too long, this article summarizes key points.
Context Managers and Python’s
In this video course, you’ll learn what the Python
with statement is and how to use it with existing context managers. You’ll also learn how to create your own context managers.
REAL PYTHON course
What I Learned From Pairing by Default
Eve recently worked on a client site where pair programming was the default. She outlines the pros and cons of her experience and what she learned.
How to Use Async Python Correctly
See some common mistakes when writing Python Async and learn how to avoid them to increase your code’s performance.
GUI LATROVA • Shared by Gui Latrova
Projects & Code
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Nuitka Optimizing Python Compiler
import-linter: Define and Enforce Rules for Imports
codon: High-Performance, Extensible Python Compiler
num2words: Convert Numbers to Words. 42 –> Forty-Two
faqtory: Generate GitHub Flavored FAQ.md Documents