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Source channel @githubtrending · Post #15409 · Jan 12

#javascript#agentic_ai#agentic_engineering#agentic_framework#agentic_rag#agentic_workflow#ai_assistant#ai_tools#anthropic_claude#autonomous_agents#claude_code#codex#huggingface#jules#mcp_server#model_context_protocol#multi_agent#multi_agent_systems#npx#swarm#swarm_intelligence Claude-Flow v2.7 is an enterprise AI platform with hive-mind swarms, 25 natural language skills, 100+ tools, and AgentDB integration for 96x-164x faster semantic search and 4-32x less memory use. Install via `npx claude-flow@alpha init` after Claude Code, then use commands like `swarm "build API"` for quick tasks or hive-mind for projects. It boosts your coding speed with 84.8% problem-solving rate, automation, GitHub tools, and persistent memory—saving you hours on complex development. https://github.com/ruvnet/claude-flow

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djangoproject

@djangoproject · Post #153 · 09/03/2016, 08:20 PM

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http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.

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