Gin Gonic Reviews

Python Reviews

Gin Gonic mentions (85)

• Even more Opentelemetry!

  Let me be blunt: I dislike (hate?) Go for its error handling approach. However, with close to zero knowledge of the language, I was able to build a basic HTTP API that reads from the database in a couple of hours. I chose Gin Gonic for the web library and Gorm for the ORM. OpenTelemetry provides an integration with a couple of libraries, including Gin and Gorm. On the Dockerfile side, it's also pretty... - Source: dev.to / 24 days ago

• Ask HN: Good examples of Go back ends?

  Most golang backends I've seen meanwhile use or switched to using the "gin" framework to build their APIs. A lot of them also have conventions for the frontend, where the assets usually are stored in /public, so they can be go:embed later as an embed.FS instance into the binary. Having said that, there's plenty of examples on github. I'd recommend to take a look at bigger projects or templates and understand how... - Source: Hacker News / 5 months ago

• From Laravel to Sponge: How to Easily Develop Web Services with Golang

  Excellent Performance: Sponge is built on the gin framework, providing outstanding performance for web service development. - Source: dev.to / 6 months ago

• Uploading and Serving Images from MongoDB in Golang

  In this blog, we will delve into the fascinating realm of handling images in a Golang application, leveraging the power of the Gin framework for RESTful API development, MongoDB as a robust NoSQL database, and the mongo-driver library for seamless interaction with MongoDB. To store images efficiently, we'll explore the intricacies of GridFS, a specification within MongoDB for storing large files as separate chunks. - Source: dev.to / 6 months ago

• Building RESTful API with Hexagonal Architecture in Go

  For building the RESTful Point of Sale service API, I've considered and selected a combination of technologies that would work seamlessly together. For handling HTTP requests and responses, using the Gin HTTP web framework would make sense because I think it seems complete and popular among Go community too. To ensure data integrity and persistence, I'm using PostgreSQL database with pgx as the database driver,... - Source: dev.to / 9 months ago

Python mentions (282)

• Choosing Between AIOHTTP and Requests: A Python HTTP Libraries Comparison

  Import aiohttp Import asyncio Async def fetch(session, url): async with session.get(url) as response: return await response.text() Async def main(): async with aiohttp.ClientSession() as session: html = await fetch(session, 'https://python.org') print(html) Asyncio.run(main()). - Source: dev.to / 11 days ago

• Marking macOS component packages available based on hardware platform type

  Flat packages are the most common used packages, but distribution packages are more robust and can contain multiple flat packages. That's enough detail for this article but if you want to know more Armin Briegel of ScriptingOSX has a great book covering a lot of the details of these package types. I highly recommend picking up a copy for reference. One of the benefits of Distribution packages is that you can... - Source: dev.to / about 1 month ago

• Python String Formatting: A Comprehensive Guide to F-strings

  F-strings, introduced in Python 3.6 and later versions, provide a concise and readable way to embed expressions inside string literals. They are created by prefixing a string with the letter ‘f’ or ‘F’. Unlike traditional formatting methods like %-formatting or str.format(), F-strings offer a more straightforward and Pythonic syntax. - Source: dev.to / 4 months ago

• Don’t Block entire Python Thread: Use Asynchronous Programming Instead

  Import aiohttp, asyncio Async def fetch_data(i, url): print('Starting', i, url) async with aiohttp.ClientSession() as session: async with session.get(url): print('Finished', i, url) Async def main(): urls = ["https://dev.to", "https://medium.com", "https://python.org"] async_tasks = [fetch_data(i+1, url) for i, url in enumerate(urls)] await... - Source: dev.to / 5 months ago

• A Comprehensive Guide to Python Threading: Advanced Concepts and Best Practices

  Threading involves the execution of multiple threads (smaller units of a process) concurrently, enabling better resource utilization and improved responsiveness. Python‘s threading module facilitates the creation, synchronization, and communication between threads, offering a robust foundation for building concurrent applications. - Source: dev.to / 6 months ago