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AWS Lambdas – Python vs Rust. Performance and Cost Savings.

Confessions of a Data Guy

Someone on Linkedin recently brought up the point that companies could save gobs of money by swapping out AWS Python lambdas for Rust ones. While it raised the ire of many a Python Data Engineer, I thought it sounded like a great idea. At least it’s an excuse to […] The post AWS Lambdas – Python vs Rust.

AWS 356
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Isolated Python Environments using Docker

Analytics Vidhya

Introduction While working with multiple projects, there are chances of issues with versions of packages in python; for example, a project needs a new version of a package, and another requires a different version. Sometimes the python version itself changes from project to project.

Python 218
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Building cost effective data pipelines with Python & DuckDB

Start Data Engineering

KISS: DuckDB + Python = easy to debug and quick to develop 4. Cost calculation: DuckDB + Ephemeral VMs = dirt cheap data processing 4.3. Processing data less than 100GB? Use DuckDB 4.4. Distributed systems are scalable, resilient to failures, & designed for high availability 4.5.

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What are Data Access Object and Data Transfer Object in Python?

Analytics Vidhya

This ensures easy […] The post What are Data Access Object and Data Transfer Object in Python? Especially while working with databases, it is often considered a good practice to follow a design pattern. appeared first on Analytics Vidhya.

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Python Essentials for Data Engineers

Start Data Engineering

Introduction Data is stored on disk and processed in memory Running the code Run on Codespaces Run on your laptop Using python REPL Python basics Python is used for extracting data from sources, transforming it, & loading it into a destination [Extract & Load] Read and write data to any system [Transform] Process data in Python or instruct (..)

Python 147
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10 GitHub Repositories to Master Python

KDnuggets

Learn Python through tutorials, blogs, books, project work, and exercises. Access all of it on GitHub for free and join a supportive open-source community.

Python 154
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Tips for Handling Large Datasets in Python

KDnuggets

Here are some tips to make working with such large datasets in Python simpler. Working with large datasets is common but challenging.

Datasets 145