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Blogs

I regularly publish in some of Medium’s top engineering publications, reaching a global audience of hundreds of thousands of developers every month. My work appears in:

  • Level Up Coding — One of the most-read dev publications, home to tutorials, engineering deep-dives, and practical coding guides.
  • Python in Plain English — New Python content daily, read by over 3.5M+ monthly readers.
  • Stackademic — A major learning hub focused on democratizing high-quality programming education.
  • CodeToDeploy — A unique publication blending technical insights with real-world engineering job opportunities.

My articles consistently attract strong engagement — thousands of reads, likes, and shares - thanks to a focus on clear, hands-on engineering content that developers can apply immediately.

Old Blogs

Memory Topics

  1. Understanding Python Memory and Garbage Collection Through Hands-on Experiments - Published on LevelUp. This article provides a practical, hands-on approach to understanding Python’s memory management and garbage collection mechanisms. By conducting experiments and observing the memory behavior, you’ll gain insights into how Python handles memory allocation and deallocation. The post also covers common memory pitfalls and tips for optimizing memory usage in Python applications.

  2. The Three Generations in Python’s Garbage Collector– published on the Python-focused Medium publication Plain English, breaks down the generational model used by Python’s garbage collector, offering a clear explanation of how objects are tracked and collected across different generations to optimize memory performance.

  3. Memory Allocation in Python: Understanding Arenas, Pools, and Blocks– published on the educational platform Plain English, dives into the internal memory management of Python, breaking down the layered structure of arenas, pools, and blocks to help developers gain a deeper understanding of how Python allocates and organizes memory for optimal performance.

Quick Dives into FastAPI Series’ Articles

  1. Unleash the Power of FastAPI: Async vs Blocking I/O - Published on Python in Plain English Medium publication. This article delves into the crucial differences between asynchronous and blocking I/O in FastAPI, explaining their impact on application performance and scalability. Through practical examples, it demonstrates how to leverage asynchronous programming to handle high-concurrency scenarios efficiently, making it a must-read for developers optimizing FastAPI projects.

  2. Understanding FastAPI’s UploadFile: The Starlette Connection - Published on Python in Plain English Medium publication. This article explores FastAPI’s UploadFile functionality and its seamless integration with Starlette, the foundational ASGI toolkit. It provides insights into handling file uploads efficiently and demonstrates how to work with streaming and large files in web applications, making it an essential guide for developers managing file operations in FastAPI projects.

  3. Building Robust Components with FastAPI and Pydantic - Published on Python in Plain English Medium publication. This article highlights the synergy between FastAPI and Pydantic in constructing reliable and maintainable application components. It covers creating reusable models and enforcing validation rules, ensuring data consistency and integrity across APIs. A practical guide for developers seeking to improve their application’s robustness and clarity.

  4. Understanding FastAPI Fundamentals: A Guide to FastAPI, Uvicorn, Starlette, Swagger UI, and Pydantic - Published on Python in Plain English Medium publication. This foundational article introduces FastAPI’s core building blocks, including Uvicorn for serving, Starlette for routing, and Pydantic for data validation. It also explores the built-in features for auto-generating API documentation with Swagger UI and ReDoc, making it an essential resource for developers new to FastAPI.

  5. Why You Should Use a Single FastAPI App and TestClient Instance - Published on Python in Plain English Medium publication. This article explains the advantages of using a single FastAPI app instance and a single TestClient instance throughout your application. By doing so, you simplify the testing setup, improve performance, and ensure consistent configurations across your tests. The post dives into best practices for structuring your FastAPI application and offers practical tips to enhance testability and maintainability.

  6. Do You Really Know About FastAPI and ASGI? - Published on Python in Plain English Medium publication. This article dives into the relationship between FastAPI and ASGI (Asynchronous Server Gateway Interface). It explores how FastAPI utilizes ASGI to handle asynchronous operations, and why it’s crucial for developers to understand ASGI for building scalable, high-performance applications. The post also highlights the difference between ASGI and WSGI and provides insights into when and how to use ASGI effectively.

Enhance Your Code Delivery Skills as a Software Engineer Series’ Articles

  1. Solving Logs Woes: A Small Dive into Singleton Design Pattern- Published in Python in Plain English. Describes my experience incorporating logging into a Python software project, initially encountering difficulties with writing logs from files but overcoming the issue by implementing the Singleton Design Pattern, ensuring a single instance of the Logger class exists throughout the program’s execution. They explain the Singleton pattern’s concept, implementation in Python, benefits, considerations, and its role in resolving their logging issue, emphasizing streamlined and centralized logging.

  2. Enhancing Software Architecture through Comprehensive Testing in Backend Development - Published in Python in Plain English.Discusses the importance of incorporating comprehensive testing into backend development to ensure code quality and resilience. He explains a three-layered architectural approach (Controller, Service, Data Access) and outlines different types of tests (True Positive, False Positive, Error Handling) to cover a wide range of use cases and scenarios.

  3. How to Write an Effective README File — A Guide for Software Engineers- Published in Stackademic. This blog emphasizes the importance of creating clear and comprehensive README files for software projects, highlighting their role in enhancing collaboration, communication, and long-term project sustainability.

  4. Mastering Error Handling: A Comprehensive Guide - Published on Stackademic Medium publication. This article offers an in-depth exploration of error handling in FastAPI. It discusses how to implement custom exception handlers, leverage middleware for centralized error logging, and provide meaningful responses to clients. With practical examples, it serves as a valuable resource for building resilient and user-friendly APIs.

  5. Raising the Difference: Between Raise and Raise e -Published on Stackademic Medium publication. This article dives into the nuanced differences between Python’s raise and raise e syntax in exception handling. It explains how each impacts stack traces and debugging, offering practical examples to clarify their appropriate use cases. A must-read for Python developers aiming to write cleaner and more informative error-handling code.

Security Topics

  • Shell injection in GitHub Actions CI/CD- The article describes the security risks of using pull_request_target event in GitHub Actions, and how an attacker can exploit shell injection to run malicious commands or scripts in the workflow.

  • Why IMDSv1 is a Security Risk for Cloud Infrastructure- The article discusses the security risks of using IMDsv1, a metadata service for cloud infrastructure, and how an attacker can exploit it to gain access to sensitive information or execute commands on the cloud instances.

  • Why You Should Disable Cloud Storage Bucket Versioning- The article explains why cloud storage bucket versioning can be a security risk and a performance bottleneck, and suggests some alternatives to achieve data durability and availability.

📰 Archive of Blogs
- [Spotify Genres Network Analysis](https://medium.com/@kfir_g/spotify-genres-network-analysis-3047c5b9b777) I built a genre network and found that the number of artists playing a genre correlated with its centrality in the network. - [Spotify- Genres Network Analysis by Through Decades](https://medium.com/@kfir_g/spotify-genres-network-analysis-by-through-decades-b7d325f9677a) Analysis the Pop and Rock through 1960-2020 by their popularity and the importance.
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