The Hidden Dangers of Python Decorators
Python decorators look like a great way to add functionality—until they break your type safety, hide function requirements, and turn debugging into a nightmare. This video shows you why decorators can be dangerous, the biggest pitfalls to watch out for, and when you should actually use them.
https://www.youtube.com/watch?v=dVnNc9oEnF8
Python decorators look like a great way to add functionality—until they break your type safety, hide function requirements, and turn debugging into a nightmare. This video shows you why decorators can be dangerous, the biggest pitfalls to watch out for, and when you should actually use them.
https://www.youtube.com/watch?v=dVnNc9oEnF8
YouTube
The Hidden Dangers of Python Decorators
💡 Learn how to design great software in 7 steps: https://arjan.codes/designguide.
Python decorators look like a great way to add functionality—until they break your type safety, hide function requirements, and turn debugging into a nightmare. In this video…
Python decorators look like a great way to add functionality—until they break your type safety, hide function requirements, and turn debugging into a nightmare. In this video…
Debugging Python f-string errors
Brandon Chinn's blog post delves into a perplexing Python bug where using f"{x}" raises a TypeError, while str(x) functions correctly. He uncovers that f-strings internally invoke theformatmethod, which can behave unexpectedly when dealing with proxy objects, such as those introduced by Temporal's sandboxing mechanism.
https://brandonchinn178.github.io/posts/2025/04/26/debugging-python-fstring-errors/
Brandon Chinn's blog post delves into a perplexing Python bug where using f"{x}" raises a TypeError, while str(x) functions correctly. He uncovers that f-strings internally invoke theformatmethod, which can behave unexpectedly when dealing with proxy objects, such as those introduced by Temporal's sandboxing mechanism.
https://brandonchinn178.github.io/posts/2025/04/26/debugging-python-fstring-errors/
brandonchinn178.github.io
Debugging Python f-string errors
Today, I encountered a fun bug where f"{x}" threw a TypeError, but str(x) worked. Join me on my journey unravelling what f-strings do and uncovering the mystery of why an object might not be what it seems.
SQLFlow
SQLFlow is a high-performance stream processing engine that simplifies building data pipelines by enabling you to define them using just SQL. Think of SQLFLow as a lightweight, modern Flink.
https://github.com/turbolytics/sql-flow
SQLFlow is a high-performance stream processing engine that simplifies building data pipelines by enabling you to define them using just SQL. Think of SQLFLow as a lightweight, modern Flink.
https://github.com/turbolytics/sql-flow
GitHub
GitHub - turbolytics/sql-flow: DuckDB for streaming data
DuckDB for streaming data. Contribute to turbolytics/sql-flow development by creating an account on GitHub.
evalstate / fast-agent
Define, Prompt and Test MCP enabled Agents and Workflows
https://github.com/evalstate/fast-agent
Define, Prompt and Test MCP enabled Agents and Workflows
https://github.com/evalstate/fast-agent
GitHub
GitHub - evalstate/fast-agent: Define, Prompt and Test MCP enabled Agents and Workflows
Define, Prompt and Test MCP enabled Agents and Workflows - evalstate/fast-agent
Garmin Grafana
A Python Script to fetch Garmin health data and populate that in a InfluxDB Database, for visualization long term health trends with Grafana.
https://github.com/arpanghosh8453/garmin-grafana
A Python Script to fetch Garmin health data and populate that in a InfluxDB Database, for visualization long term health trends with Grafana.
https://github.com/arpanghosh8453/garmin-grafana
GitHub
GitHub - arpanghosh8453/garmin-grafana: A Dockerized python Script to fetch Garmin health data and populate that in a InfluxDB…
A Dockerized python Script to fetch Garmin health data and populate that in a InfluxDB Database, for visualization long term health trends with Grafana - arpanghosh8453/garmin-grafana
sooperset / mcp-atlassian
MCP server for Atlassian tools (Confluence, Jira)
https://github.com/sooperset/mcp-atlassian
MCP server for Atlassian tools (Confluence, Jira)
https://github.com/sooperset/mcp-atlassian
GitHub
GitHub - sooperset/mcp-atlassian: MCP server for Atlassian tools (Confluence, Jira)
MCP server for Atlassian tools (Confluence, Jira). Contribute to sooperset/mcp-atlassian development by creating an account on GitHub.
CocoIndex - Open-source real-time data framework for AI
Open-source real-time data framework for AI, supporting incremental processing and custom logic. SDK in Python.
https://github.com/cocoindex-io/cocoindex
Open-source real-time data framework for AI, supporting incremental processing and custom logic. SDK in Python.
https://github.com/cocoindex-io/cocoindex
GitHub
GitHub - cocoindex-io/cocoindex: Data transformation framework for AI. Ultra performant, with incremental processing.
Data transformation framework for AI. Ultra performant, with incremental processing. - cocoindex-io/cocoindex
Using JWTs in Python Flask REST Framework
This post provides a comprehensive guide to implementing JWT-based authentication in a Flask API. It covers setting up the Flask environment, creating a to-do list API, managing user sessions with token refresh, and adding role-based permissions.
https://blog.appsignal.com/2025/04/30/using-jwts-in-python-flask-rest-framework.html
This post provides a comprehensive guide to implementing JWT-based authentication in a Flask API. It covers setting up the Flask environment, creating a to-do list API, managing user sessions with token refresh, and adding role-based permissions.
https://blog.appsignal.com/2025/04/30/using-jwts-in-python-flask-rest-framework.html
Appsignal
Using JWTs in Python Flask REST Framework | AppSignal Blog
We'll build a JWT-based authentication system by creating a to-do list API using Flask.
GoogleCloudPlatform / agent-starter-pack
A collection of production-ready Generative AI Agent templates built for Google Cloud. It accelerates development by providing a holistic, production-ready solution, addressing common challenges (Deployment & Operations, Evaluation, Customization, Observability) in building and deploying GenAI agents.
https://github.com/GoogleCloudPlatform/agent-starter-pack
A collection of production-ready Generative AI Agent templates built for Google Cloud. It accelerates development by providing a holistic, production-ready solution, addressing common challenges (Deployment & Operations, Evaluation, Customization, Observability) in building and deploying GenAI agents.
https://github.com/GoogleCloudPlatform/agent-starter-pack
GitHub
GitHub - GoogleCloudPlatform/agent-starter-pack: A collection of production-ready Generative AI Agent templates built for Google…
A collection of production-ready Generative AI Agent templates built for Google Cloud. It accelerates development by providing a holistic, production-ready solution, addressing common challenges (D...
SQL-tString
SQL-tString allows for f-string like construction of sql queries.
https://github.com/pgjones/sql-tstring
SQL-tString allows for f-string like construction of sql queries.
https://github.com/pgjones/sql-tstring
GitHub
GitHub - pgjones/sql-tstring: SQL-tString allows for f-string like construction of sql queries
SQL-tString allows for f-string like construction of sql queries - GitHub - pgjones/sql-tstring: SQL-tString allows for f-string like construction of sql queries
Using Python to Automate 3D Workflows with OpenUSD
The post explains how Python’s scripting capabilities can automate and streamline 3D workflows using OpenUSD, making tasks like data transformation, validation, and scene creation more accessible and efficient. It highlights NVIDIA’s tools, SDKs, and learning resources that empower developers to build, validate, and optimize complex 3D scenes with Python in the OpenUSD ecosystem.
https://developer.nvidia.com/blog/using-python-to-automate-3d-workflows-with-openusd/
The post explains how Python’s scripting capabilities can automate and streamline 3D workflows using OpenUSD, making tasks like data transformation, validation, and scene creation more accessible and efficient. It highlights NVIDIA’s tools, SDKs, and learning resources that empower developers to build, validate, and optimize complex 3D scenes with Python in the OpenUSD ecosystem.
https://developer.nvidia.com/blog/using-python-to-automate-3d-workflows-with-openusd/
NVIDIA Technical Blog
Using Python to Automate 3D Workflows with OpenUSD
Universal Scene Description (OpenUSD) offers a powerful, open, and extensible ecosystem for describing, composing, simulating, and collaborating within complex 3D worlds.
LlamaFirewall
The framework to detect and mitigate AI centric security risks.
https://meta-llama.github.io/PurpleLlama/LlamaFirewall/
The framework to detect and mitigate AI centric security risks.
https://meta-llama.github.io/PurpleLlama/LlamaFirewall/
meta-llama.github.io
LlamaFirewall | LlamaFirewall
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