Turning Data into Insight
The article demonstrates how to build a flexible, modern data lakehouse architecture using open-source tools like MinIO, Apache Iceberg, Airflow, dbt, Spark, Pandera, and Superset. By integrating these technologies with Docker for easy deployment, it shows how to orchestrate robust data pipelines, ensure data quality, and enable scalable analytics from raw ingestion to interactive dashboards.
https://towardsdev.com/turning-data-into-insight-flexible-lakehouse-with-minio-iceberg-airflow-dbt-spark-pandera-409d036e5542
The article demonstrates how to build a flexible, modern data lakehouse architecture using open-source tools like MinIO, Apache Iceberg, Airflow, dbt, Spark, Pandera, and Superset. By integrating these technologies with Docker for easy deployment, it shows how to orchestrate robust data pipelines, ensure data quality, and enable scalable analytics from raw ingestion to interactive dashboards.
https://towardsdev.com/turning-data-into-insight-flexible-lakehouse-with-minio-iceberg-airflow-dbt-spark-pandera-409d036e5542
Medium
Turning Data into Insight: Flexible Lakehouse with MinIO, Iceberg, Airflow, DBT, Spark, Pandera &…
After previously discussing how we transitioned from traditional storage to MinIO object storage in this article:
Machine Learning Prototyping with DuckDB and scikit-learn
In this post, we prototype a machine learning workflow using DuckDB for data handling and scikit-learn for modeling.
https://duckdb.org/2025/05/16/scikit-learn-duckdb.html
In this post, we prototype a machine learning workflow using DuckDB for data handling and scikit-learn for modeling.
https://duckdb.org/2025/05/16/scikit-learn-duckdb.html
DuckDB
Machine Learning Prototyping with DuckDB and scikit-learn
In this post, we prototype a machine learning workflow using DuckDB for data handling and scikit-learn for modeling.
nlweb
Building conversational interfaces for websites is hard. NLWeb seeks to make it easy for websites to do this. And since NLWeb natively speaks MCP, the same natural language APIs can be used both by humans and agents.
https://github.com/microsoft/nlweb
Building conversational interfaces for websites is hard. NLWeb seeks to make it easy for websites to do this. And since NLWeb natively speaks MCP, the same natural language APIs can be used both by humans and agents.
https://github.com/microsoft/nlweb
GitHub
GitHub - microsoft/NLWeb: Natural Language Web
Natural Language Web. Contribute to microsoft/NLWeb development by creating an account on GitHub.
Python Tooling at Scale: LlamaIndex’s Monorepo Overhaul
https://www.llamaindex.ai/blog/python-tooling-at-scale-llamaindex-s-monorepo-overhaul
https://www.llamaindex.ai/blog/python-tooling-at-scale-llamaindex-s-monorepo-overhaul
www.llamaindex.ai
Python Tooling at Scale: LlamaIndex’s Monorepo Overhaul — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
Flowfile
Flowfile is a visual ETL tool combining drag-and-drop workflows with the speed of Polars dataframes. Build and analyze data pipelines without code. Perfect for analysts and engineers needing fast, intuitive data processing. Designed to run locally or deploy to production environments.
https://github.com/Edwardvaneechoud/Flowfile/
Flowfile is a visual ETL tool combining drag-and-drop workflows with the speed of Polars dataframes. Build and analyze data pipelines without code. Perfect for analysts and engineers needing fast, intuitive data processing. Designed to run locally or deploy to production environments.
https://github.com/Edwardvaneechoud/Flowfile/
GitHub
GitHub - Edwardvaneechoud/Flowfile: Flowfile is a visual ETL tool combining drag-and-drop workflows with the speed of Polars dataframes.…
Flowfile is a visual ETL tool combining drag-and-drop workflows with the speed of Polars dataframes. Build and analyze data pipelines without code. Perfect for analysts and engineers needing fast, ...
Datatune
Perform transformations on your data with natural language using LLMs
https://github.com/vitalops/datatune
Perform transformations on your data with natural language using LLMs
https://github.com/vitalops/datatune
GitHub
GitHub - vitalops/datatune: Perform transformations on your data with natural language using LLMs
Perform transformations on your data with natural language using LLMs - vitalops/datatune
Python in LibreOffice (LibrePythonista Extension)
https://extensions.libreoffice.org/en/extensions/show/99231
https://extensions.libreoffice.org/en/extensions/show/99231
Unravelling t-strings
PEP 750 introduced t-strings for Python 3.14. In fact, they are so new that as of Python 3.14.0b1 there still isn't any documentation yet for t-strings. As such, this blog post will hopefully help explain what exactly t-strings are and what you might use them for by unravelling the syntax and briefly talking about potential uses for t-strings.
https://snarky.ca/unravelling-t-strings/
PEP 750 introduced t-strings for Python 3.14. In fact, they are so new that as of Python 3.14.0b1 there still isn't any documentation yet for t-strings. As such, this blog post will hopefully help explain what exactly t-strings are and what you might use them for by unravelling the syntax and briefly talking about potential uses for t-strings.
https://snarky.ca/unravelling-t-strings/
Tall, Snarky Canadian
Unravelling t-strings
PEP 750 introduced t-strings for Python 3.14. In fact, they are so new that as of Python 3.14.0b1 there still isn't any documentation yet for t-strings. 😅 As such, this blog post will hopefully help explain what exactly t-strings are and what you might use…
Ruff - A Fast Linter & Formatter to Replace Multiple Tools and Improve Code Quality
This video is a hands-on tutorial showing how to use Ruff, a super-fast Python linter and formatter written in Rust that consolidates tools like Flake8, Black, and isort into a single, efficient solution. The guide covers installing Ruff, running it from the command line, configuring it for projects, and integrating it with VS Code to improve code quality and developer workflow.
https://www.youtube.com/watch?v=828S-DMQog8
This video is a hands-on tutorial showing how to use Ruff, a super-fast Python linter and formatter written in Rust that consolidates tools like Flake8, Black, and isort into a single, efficient solution. The guide covers installing Ruff, running it from the command line, configuring it for projects, and integrating it with VS Code to improve code quality and developer workflow.
https://www.youtube.com/watch?v=828S-DMQog8
YouTube
Python Tutorial: Ruff - A Fast Linter & Formatter to Replace Multiple Tools and Improve Code Quality
In this Python tutorial, we'll be learning how to use Ruff, a super-fast Python linter and formatter written in Rust. We'll cover how to install Ruff, how to use Ruff from the command line to check and fix your code, and how to configure Ruff both for individual…
ii-agent
A new open-source framework to build and deploy intelligent agents.
https://github.com/Intelligent-Internet/ii-agent
A new open-source framework to build and deploy intelligent agents.
https://github.com/Intelligent-Internet/ii-agent
GitHub
GitHub - Intelligent-Internet/ii-agent: II-Agent: a new open-source framework to build and deploy intelligent agents
II-Agent: a new open-source framework to build and deploy intelligent agents - Intelligent-Internet/ii-agent
Ruff users, what rules are using and what are you ignoring?
https://www.reddit.com/r/Python/comments/1kttfst/ruff_users_what_rules_are_using_and_what_are_you/
https://www.reddit.com/r/Python/comments/1kttfst/ruff_users_what_rules_are_using_and_what_are_you/
Reddit
From the Python community on Reddit
Explore this post and more from the Python community
Beyond Query Optimization
Lyft engineers detail how they improved the scalability and reliability of their Aurora Postgres databases by implementing connection pooling with SQLAlchemy and Amazon RDS Proxy. The article explains the challenges of managing database connections in high-traffic environments and describes how these solutions reduced connection limits, improved application stability, and optimized resou...
https://eng.lyft.com/beyond-query-optimization-aurora-postgres-connection-pooling-with-sqlalchemy-rdsproxy-200db7f562d7
Lyft engineers detail how they improved the scalability and reliability of their Aurora Postgres databases by implementing connection pooling with SQLAlchemy and Amazon RDS Proxy. The article explains the challenges of managing database connections in high-traffic environments and describes how these solutions reduced connection limits, improved application stability, and optimized resou...
https://eng.lyft.com/beyond-query-optimization-aurora-postgres-connection-pooling-with-sqlalchemy-rdsproxy-200db7f562d7
Medium
Beyond Query Optimization: Aurora Postgres Connection Pooling with SQLAlchemy & RDSProxy
Written by Jay Patel and Creston Jamison
A leap year check in three instructions
The article explores how to check if a year is a leap year using just three CPU instructions, leveraging clever bit manipulation and "magic numbers" to optimize the standard algorithm. By reverse-engineering and brute-forcing constants, the author demonstrates a branchless, highly efficient leap year check for years up to 102,499, illustrating both the mathematical tricks and practical l...
https://hueffner.de/falk/blog/a-leap-year-check-in-three-instructions.html
The article explores how to check if a year is a leap year using just three CPU instructions, leveraging clever bit manipulation and "magic numbers" to optimize the standard algorithm. By reverse-engineering and brute-forcing constants, the author demonstrates a branchless, highly efficient leap year check for years up to 102,499, illustrating both the mathematical tricks and practical l...
https://hueffner.de/falk/blog/a-leap-year-check-in-three-instructions.html
hueffner.de
A leap year check in three instructions
How to test for leap years (until year 102499) in the proleptic Gregorian calendar with just three 32-bit instructions, with detailed explanation of the bit-level tricks.
AlphaEvolve: A coding agent for scientific and algorithmic discovery
AlphaEvolve is an autonomous coding agent that uses evolutionary strategies to improve algorithms by iteratively modifying code and learning from evaluator feedback. It has achieved breakthroughs in data center scheduling, hardware design, and mathematical discovery—including surpassing Strassen’s 4×4 matrix multiplication algorithm for the first time in 56 years.
https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/AlphaEvolve.pdf
AlphaEvolve is an autonomous coding agent that uses evolutionary strategies to improve algorithms by iteratively modifying code and learning from evaluator feedback. It has achieved breakthroughs in data center scheduling, hardware design, and mathematical discovery—including surpassing Strassen’s 4×4 matrix multiplication algorithm for the first time in 56 years.
https://storage.googleapis.com/deepmind-media/DeepMind.com/Blog/alphaevolve-a-gemini-powered-coding-agent-for-designing-advanced-algorithms/AlphaEvolve.pdf
A Python frozenset interpretation of Dependent Type Theory
The post explores modeling dependent type theory (DTT) concepts using Python’s frozenset data structure, treating types as finite sets to clarify complex type-theoretic ideas. By implementing type constructors like dependent sums (Σ), dependent products (Π), and identity types in Python, the author demonstrates how key DTT judgments and structures can be represented and reasoned about in...
https://www.philipzucker.com/frozenset_dtt/
The post explores modeling dependent type theory (DTT) concepts using Python’s frozenset data structure, treating types as finite sets to clarify complex type-theoretic ideas. By implementing type constructors like dependent sums (Σ), dependent products (Π), and identity types in Python, the author demonstrates how key DTT judgments and structures can be represented and reasoned about in...
https://www.philipzucker.com/frozenset_dtt/
Hey There Buddo!
A Python frozenset interpretation of Dependent Type Theory
TLDR. Types are basically sets. Why not python sets?