Building FastAPI with Python for High-Performance APIs

My past self just saved my afternoon. Months ago, I wrote a Python package called gherkins to skip the headache of a full CI/CD setup. I almost didn't share it because I figured it was 'too simple' and less useful compared to massive tools like Jenkins. That changed today. I was making a POC and needed a deployment pipeline now, not in an hour. Instead of breaking my flow to wait on Jenkins provisioning or digging through boilerplate Groovy files, I imported my own package. The result? ⚡ 10 minutes to a functional deployment script. ⏳ 0 minutes waiting for compute to provision. 🐍 Entirely Pythonic logic instead of Bash or Groovy. It’s a reminder that the best tools are often the ones we build to solve our own headaches. If you need to run sequential deployment pipelines locally or over SSH without burning time on CI/CD, check it out. Github repo: https://lnkd.in/gvXKhDiD P.S. CI/CD (Jenkins) is great for production stability. It just wasn't the best tool for deploying a quick POC :) #OpenSource #Python #DevOps #BuildInPublic

🚀 Excited to share a small milestone! Last week I open-sourced a Python tool I’ve been working on: AsyncAPI Payload Validator. It helps validate message payloads against AsyncAPI specifications, making it easier to ensure that event-driven systems publish and consume messages that match their contracts. 🔧 Built for teams working with event-driven architectures who want stronger schema validation and better reliability in their messaging systems. In just one week, the package has already reached 900+ downloads, which is incredibly encouraging! 🙌 Open source is all about sharing, learning, and improving together — and I’m excited to see how others might use or contribute to it. If you're working with AsyncAPI, event-driven systems, or message validation in Python, feel free to check it out: https://lnkd.in/eUQKr3RU Feedback and contributions are very welcome! #opensource #python #asyncapi #eventdriven #softwareengineering

Want every TODO in your Python code without clicking around? One grep does it all. ⚡ Command: grep -r 'TODO' ./src --include='*.py' -l - -r: recursive search - 'TODO': literal pattern - ./src: start here - --include='*.py': Python files only - -l: list files Real world: you're auditing a growing Python repo at 2AM. TODOs are scattered everywhere. This prints exactly which files contain TODOs, so you open them in your editor and triage in minutes. Why it matters: tiny one-liners save hours and keep work aligned. The terminal is a superpower; you control the pace. Run it right now. Tell me what you find. 🐧 #linux #terminal #bash #commandline #devops #sysadmin #programming #softwareengineering #developer #coding #opensource #productivity #automation #cloudcomputing #learntocode

We are encountering challenges with validating STAC JSON schemas in Python. Given that concurrency can be costly in Python, organizations ingesting and validating thousands of STAC items daily must seek more efficient solutions for the geospatial community that can reduce costs and energy consumption. To tackle this issue, we are developing a STAC validator in Golang. For more information, please visit gostac-validator hosted at StacLabs. https://lnkd.in/g2X3wC-P

Day-10 of Python for Devops Today’s session was a bit challenging but also very interesting. I learned how to combine multiple concepts to build something closer to a real-world use case. Concepts Covered: Functions -> Used to organize code into reusable blocks Lists -> To store multiple values (like server names) Exception Handling (try-except) -> To handle errors gracefully and prevent program crashes To understand these concepts better, I built a small DevOps-style project called "Server Deployment Checker". What the program does: -Displays a list of available servers -Takes user input to select a server -Handles invalid input using exception handling -Simulates a deployment process on the selected server -Shows success or failure message based on conditions This helped me understand how real-world scripts: -Take user input -Work with infrastructure data -Handle unexpected errors -Perform automated tasks Github Repository:- https://lnkd.in/dk2pnszH

A python automation project using Django. # python # django # ldap3 # netmiko # smtplib # zipfile In this project, try to automate the active directory user operations. Thanks Anup Kumar Malakar to help me in this project.

Day 544 of Learning – Exploring Python Backend Frameworks 🌐🐍 Explored different Python backend frameworks used to build web applications and APIs, each designed for specific use cases and performance needs. Frameworks like Django provide a full-stack solution with built-in features such as authentication, ORM, and admin panels, making it ideal for large-scale applications. Flask is a lightweight and flexible framework that allows developers to build applications with minimal setup and more control. Modern frameworks like FastAPI and Starlette focus on high performance and asynchronous processing, making them perfect for APIs and real-time applications. Frameworks such as Falcon and Sanic are optimized for speed and are commonly used in high-performance systems. Bottle and CherryPy are simple and beginner-friendly options for smaller applications, while Pyramid offers flexibility by allowing developers to scale from simple to complex applications. Understanding these frameworks helps in choosing the right tool based on project requirements, scalability, and performance needs. Each framework plays an important role in modern backend development and API design. 🚀 #BackendDevelopment #Python #Django #Flask #FastAPI #WebDevelopment #APIs #LearningJourney #Day644

🚀 Today I went deeper into building backend APIs using Python, FastAPI, and Async SQLAlchemy. Instead of just learning theory, I implemented a mini backend system that includes: 🔹 REST API endpoints with FastAPI 🔹 Request & response validation using Pydantic 🔹 Async database integration with SQLAlchemy 🔹 SQLite async engine configuration 🔹 UUID-based primary keys for scalable data models 🔹 Automatic database table creation at startup 🔹 Error handling using HTTPException Example endpoints implemented: • GET /posts/{id} → Retrieve a post • POST /post → Create a new post Tech stack used today: Python 🐍 FastAPI ⚡ Pydantic 📦 Async SQLAlchemy 🗄️ SQLite (async driver) Key learning today: Modern Python backend development is moving toward asynchronous architectures, which significantly improve scalability and performance for real-world applications. Next steps in this project: ✔ File upload API ✔ Authentication system (JWT) ✔ Cloud deployment ✔ Production-grade database integration Building every day. Improving every day. #Python #FastAPI #BackendDevelopment #AsyncPython #SQLAlchemy #SoftwareEngineering #BuildInPublic

Python has become the go-to language for developers across industries, powering everything from data science and machine learning to web development and automation. With its popularity comes a critical challenge: maintaining a secure and reliable supply chain for Python packages while ensuring they stay up-to-date. Tools like Anaconda make this process easier, but organizations can also take control by hosting their own internal Python package server, giving full oversight of dependencies, security, and version management. https://lnkd.in/guZAVxgy

Day 13/100: Leveling Up APIs with Validation, Error Handling & Authentication 🚀 This week has been all about making my APIs smarter, safer, and more robust. Here’s a quick recap of what I accomplished: Python (FastAPI) – Input Validation & Error Handling Added request validation using Pydantic Implemented global error handling Result: Python API now validates inputs and handles errors gracefully. Node.js (Express) – Input Validation & Error Handling Used Joi for request validation Built global error-handling middleware Result: Node.js API now validates requests consistently and reports errors reliably. Python JWT Authentication Created register/login endpoints with password hashing via Passlib Generated and verified JWT tokens to secure endpoints Result: Python API endpoints are now secured with authentication. Every day, my APIs are becoming stronger. Excited to keep building and stacking these skills! Chris Nyeche #100DaysOfCode #Python #NodeJS #FastAPI #ExpressJS #JWT #BackendDevelopment #APIDevelopment #BuildInPublic