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#howtos
How to Protect Your Web Applications From XSS, by @torgo (@w3c):
https://www.w3.org/blog/2025/how-to-protect-your-web-applications-from-xss/
How to Get Deep Traces in Your Node.js Backend With OTel and Deno, by @andyjiang@x.com (@deno_land):
How to Create Quality Content (Follow Our 5-Level Framework), by @siquanong@x.com and @timsoulo@x.com (@ahrefs):
How to Prevent WordPress SQL Injection Attacks, by @smashingmag:
https://www.smashingmagazine.com/2025/03/how-prevent-wordpress-sql-injection-attacks/
How to Fix Largest Contentful Paint Issues With Subpart Analysis, by @mattzeunert@x.com (@smashingmag):
https://www.smashingmagazine.com/2025/03/how-to-fix-largest-contentful-issues-with-subpart-analysis/
How to Troubleshoot Node.js Images in OpenShift, by @rhdevelopers@x.com:
https://developers.redhat.com/articles/2025/03/05/how-troubleshoot-nodejs-images-openshift
How to Do Visual Regression Testing in Vue With Vitest?, by @alexanderopalic@x.com:
https://alexop.dev/posts/visual-regression-testing-with-vue-and-vitest-browser/
Published an article on LinkedIn to help folx considering joining or new people who don't know how to navigate here.
I applaud you kind, welcoming Fedi folx!
Thanks for making this a wonderful place to be in online :)
The Ultimate Guide to Django Templates
#Python #Pycharm #Howtos #Webdevelopment #Django
https://blog.jetbrains.com/pycharm/2025/02/the-ultimate-guide-to-django-templates/
Anomaly Detection in Time Series
#Python #Pycharm #Datascience #Howtos #Anomalydetection
https://blog.jetbrains.com/pycharm/2025/01/anomaly-detection-in-time-series/
Anomaly Detection in Machine Learning Using Python
#Python #Pycharm #Datascience #Howtos #Anomalydetection
https://blog.jetbrains.com/pycharm/2025/01/anomaly-detection-in-machine-learning/
在 PyCharm 中使用 Jupyter Notebook 的 7 种方式
#Python #Pycharm #Datascience #Howtos #Jupyter #Jupyternotebooks
https://blog.jetbrains.com/pycharm/2024/12/7-ways-to-use-jupyter-notebooks-inside-pycharm
7 Reasons You Should Use dbt Core in PyCharm
#Python #Pycharm #Datascience #Howtos #Dbt
♬ 
A Quick Way To Evaluate Software Frameworks
One of the most impressive bits of #software I’ve used is #Python. When I started to learn Python, it was version 1.5, a long time ago. I was immediately impressed with the tutorial. It was the first port of call. Here it is now:
<https://docs.python.org/3/tutorial/index.html>
Read the tutorial basics and you could start exploring the language library
<https://docs.python.org/3/library/index.html>
knowing you could master enough to move to more advanced concepts. Want to do something more complicated? Say build a web server?
First you might try the #HOWTO pages trying #sockets:
<https://docs.python.org/3/howto/index.html>
After reading about the limitations you might try the #PEPS (Python Enhancement Proposal) What is a PEP? Try reading this page:
<https://peps.python.org/pep-0001/)
Finally you might decide #WSGI is what you want and read the specification at
<https://peps.python.org/pep-0333/>. I travelled this path in 2007/8 to build a version of my blog engine. 
<https://seldomlogical.com/redux.html>
So I go the latest build on #Deno, install it and try a simple blog engine to see how it works
<https://deno.com/blog/build-a-blog-with-fresh>.
The example code fails, the source code fails. I see the basic documentation for it (yet to try, but skimming through, it appears okay.) The tutorial only a couple of years old has rusted, the source is unmaintained. The issue is with JS / #React / #Preact where plain old #HTML5 and #CSS will do. 
A quick example how the basics have to documented, correct in bite sized pieces. The #HOWTOS maintained and blog #examples periodically revised.
How to Do Sentiment Analysis With Large Language Models
#Pycharm #Datascience #Howtos #Ai #Llms #Machinelearning #Python
https://blog.jetbrains.com/pycharm/2024/12/how-to-do-sentiment-analysis-with-large-language-models/
Where To Get Data for Your Data Science Projects
#Pycharm #Data #Datascience #Education #Howtos #Python #Dataset #Datasets