TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #14739 · May 23
#c_lang#ctp#ctpapi#futures#options#quant#simnow#stock#tora#trader#tts#xtp openctp is a powerful open-source trading platform compatible with many Chinese securities and futures trading systems, offering both real and simulated trading environments for futures, options, stocks, funds, and bonds across domestic and global markets like A-shares, Hong Kong, and US stocks. It provides easy access to CTPAPI through Python and other programming languages, plus user-friendly trading clients with graphical and command-line interfaces. You can register free simulation accounts instantly via WeChat, enabling you to practice and test trading strategies in real-time or 24/7 environments. It also offers training, development support, and a monitoring platform for multiple trading systems, helping you learn, develop, and trade efficiently with low costs and broad market access. This benefits you by giving a flexible, comprehensive, and cost-effective way to develop, test, and execute trading strategies across many markets with strong community and technical support. https://github.com/openctp/openctp
Search: #runtime
@golang · Post #58 · 04/22/2018, 08:22 PM
Why are goroutines not lightweight threads? Kartik Khare shows us his meaning about goroutines, lightweight threads and their difference in GoLang. There are no code examples inside but good thoughts about parallelism, threads and useful links at the end of the article :) #development#runtime#language https://codeburst.io/why-goroutines-are-not-lightweight-threads-7c460c1f155f
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@golang · Post #64 · 06/21/2018, 04:17 PM
Hi there! Which ways do you use to avoid memory leaks for REST API? In the following article by Iman Tumorang describes an excellent example of memory leaks, his solution, and results. Must have to read for everyone 😉 #development#runtime#architecture https://hackernoon.com/avoiding-memory-leak-in-golang-api-1843ef45fca8
@githubtrending · Post #15382 · 01/01/2026, 12:30 PM
#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples