In any organization, the answers to "who do I work with," "who knows what," and "how can we work together," are often question marks. People data like skills, experience, and even contact info is often locked in an HRMS or scattered across multiple systems, making it hard or even impossible to quickly access. Sift puts your valuable people information from all your systems into a single simple-to-use search bar. Powerful people search, coupled with our dynamic org chart and employee directory, help everyone navigate your org intuitively. Sync to collaboration tools via a dedicated MS Teams app which helps employees find, connect, and collaborate with each other in ways that are more natural. Find folks with subject-matter expertise or similar interests to strengthen your internal network. Give your whole organization a tool that fosters true connections so everyone can work better, together.
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Based on our record, Python seems to be more popular. It has been mentiond 281 times since March 2021. 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.
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 / 30 days 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 / 5 months ago
FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework. - Source: dev.to / 5 months ago
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