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DataGrip PythonBased on our record, Python seems to be a lot more popular than DataGrip. While we know about 282 links to Python, we've tracked only 1 mention of DataGrip. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
DataGrip is a cross-platform integrated development environment (IDE) that supports multiple database environments. The most important thing to note about DataGrip is that it's developed by JetBrains, one of the leading brands for developing IDEs. If you have ever used PhpStorm, IntelliJ IDEA, PyCharm, WebStorm, you won't need an introduction on how good JetBrains IDEs are. - Source: dev.to / over 3 years ago
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 / 7 days ago
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
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
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
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
DBeaver - DBeaver - Universal Database Manager and SQL Client.
Rust - A safe, concurrent, practical language
MySQL Workbench - MySQL Workbench is a unified visual tool for database architects, developers, and DBAs.
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
HeidiSQL - HeidiSQL is a powerful and easy client for MySQL, MariaDB, Microsoft SQL Server and PostgreSQL. Open source and entirely free to use.
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
