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Python Web Conf 2023 : Day 5 Recap

Python Web Conf 2023 : Day 5 Recap

A heartfelt thank you to the amazing attendees, speakers, ambassadors, and sponsors of the 5th annual Python Web Conf! We hope this week inspired you to use technology for good.

The conference attracted 315 attendees from over 30 countries across 15 timezones — from Australia to Canada. Even though we are thousands of miles apart, we came together to share our knowledge, celebrate our diversity, and have fun! Mission accomplished!  

All 67 presentations are available on LoudSwarm for re-watch. The recordings will be available exclusively on LoudSwarm for 90 days. After 90 days, the videos will be published on Six Feet Up’s YouTube channel.

jj.png KEYNOTE: Taking a step back and leveraging GitOps to wrangle your clusters and projects 
by JJ ASGHAR @ IBM

Key points:
  • Most companies do Continuous Integration. Very few are doing Continuous Delivery.
  • GitOps leverages Git as the single source of truth to define every part of the system.
  • A demo of Argo CD on OpenShift was used to automatically deploy an application and apply changes.
ariana.png KEYNOTE: Crowdsourcing Hope: How a documentary filmmaker is using low code tech solutions to save lives 
by ARIANA VARGAS @ STIGMA

Key points:
  • STIGMA was created to connect people struggling with mental health issues.
  • In less than 90 days, the app went from launch to Google "Best App for Good."
  • We can use our tech skills to give back to others.
  • If you have an idea, run with it and make it happen. It's worth it!
anthony.png Beat the rush! Designing effective load tests for your web application 
by ANTHONY SHAW @ MICROSOFT AUSTRALIA

Key points:
  • Start by analyzing your users (if you have some).
  • Vary your inputs - timing, user requests and data.
  • Remember your goal is to simulate real user traffic.
  • Beware of false performance from caching.
  • Optimize when complete and repeat to get a baseline.
steve.png Debugging Schrödinger's App 
by STEVE COOCHIN @ LUMIGO

Key points:
  • When you have multiple servers and logs, how do you find errors?
  • Using Lumigo with Open Telemetry, learn how to trace errors.
  • Remember to code for potential errors, monitor and trace everything.
nicolas.png Discussing Backend-For-Frontend 
by NICOLAS FRÄNKEL @ APACHE APISIX

Key points:
  • You can filter fetched data for various devices (e.g. a phone, a tablet or a browser).
  • Eventually, microservices were born.
  • Backend-For-Frontend is an architectural design pattern where user experience is also prioritised, aimed at solving one of the (many) issues that come with microservices.
jodie.png Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast 
by JODIE BURCHELL @ JETBRAINS

Key points:
  • A quick change from loops to vector operations can speed up distance calculations over large data sets.
  • Moving away from Python's built-in timsort to numpy's type-optimized sort algorithms — and vectorizing the rest of the final selection for each point — led to a speed-up between 15 and 1150 times.
rob_r.png TUTORIAL: Async Python, Good it is 
by ROB RICHARDSON

Key points:
  • Popen and Threads are more complex.
  • Async: allows developer to think sync but works async. Great for I/O bound workloads.
  • Basic async use demonstrated first.
  • Defines terms to help understanding of units then demonstrates patterns for calling, organizing acting on calls, and preventing blocking.
al_s.png Edit Excel and Google Spreadsheets with Python: An Introduction 
by AL SWEIGART @ INVENT WITH PYTHON

Key points:
  • Start working with Python and Excel superfast: just pip install openpyxl==3.1.2 and ezsheets.
  • Write Python scripts to automate the creation, updating, and verification of spreadsheets.
  • OpenPyXL and EZSheets modules will bring you closer to interact with data.
nagesh.png Push button deployments in minutes not months 
by NAGESH VINNAKOTA @ CAPITAL ONE, GOKUL PRABAGAREN @ CAPITALONE

Key points: 
  • Products without a modern deploy pipeline are prone to having issues.
  • CI/CD setup starts with baby steps, then it develops very fast.
  • Developers are responsible for writing/fixing their own unit tests and integrating with the pipeline.
  • Identify issues before you release your product.
chris_may.png Change without changing: Keep your project healthy by refactoring your code 
by CHRIS MAY @ EVERYDAY SUPERPOWERS

Key points:
  • Taking time to improve your code can reap huge benefits.
  • Refactor your code to make it more understandable and support new features.
  • The Flocking Rules are great for building confidence in your code.
tamara.png Airflow DAGs Made Easy: Introducing the Astro SDK 
by TAMARA FINGERLIN @ ASTRONOMER.IO, DANIEL IMBERMAN @ ASTRONOMER.IO

Key points:
  • Check out the latest features added to Airflow, especially the Astro SDK.
  • The astro sdk now provides abstractions for databases, sql, tables, remote files, and dataframes
  • Dynamic task mapping sets the number and parameters of a task at run-time.
  • Locally test DAGs by adding a test function to attach a debugger to the process.
paul.png Joyful Pyodide with...tests? 
by PAUL EVERITT @ JETBRAINS

Key points:
  • Developers shouldn’t have to rely on the browser or hop around different apps.
  • Pyodide gets Python in the browser with WebAssembly.
  • Vite can check changes as you write.
  • For Javascript folks, there’s also happy-dom, which is a simulated browser for node.js.
pawel.png Observability for Serverless 
by PAWEL PIWOSZ @ EPAM SYSTEMS

Key points:
  • Hardware abstraction is reducing visibility for serverless applications. 
  • Structured logging is the practice of implementing a message format for app logs as data sets.
  • Observability is a framework that contains 3 elements: logs, traces, and metrics.
  • AWS X-Ray and Lambda facilitates tracing in Lambdas and API Gateway.
jordan.png Faster, Smarter Climate Mitigation Using Python 
by JORDAN WARBELOW-FELDSTEIN @ BLOCPOWER

Key points:
  • There are 6 sectors of climate mitigation. 
  • Investors face the question: "Which projects should I invest in?”  
  • Python's capacity for data science can create and defend answers to investors’ questions.
  • We can use Python to build tools that simplify investors' project selection process.
jason.png Protecting Sensitive Data and Models for Machine Learning 
by JASON MANCUSO @ CAPE PRIVACY

Key points:
  • Confidential computing — from key and secrets management to encryption — is complex.
  • AWS Nitro Enclaves lets you deploy verified code that can only be run in locked down containers.
  • The Cape platform provides an AWS Lambda-like authoring and use process.

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