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@baymaxium
baymaxium / content.md
Created October 18, 2017 08:31
闲扯比特币套利交易系统的设计

原文:程序人生

关于比特币套利交易的文章,坊间一搜一大堆,尤以 2014,2015 为甚。那时交易所间价差相当可观,套利的机会很多,躺着赚钱并非难事。如今,套利区间收窄,留在沙场上的估计只剩下大玩家,想要不费力气躺赢机会渺茫。最近帮朋友牵线寻找币圈量化交易的机会,本欲做个打酱油的中间人,事了拂衣去,安安静静做个三河市微胖界扛把子,谁料还是一时技痒,不小心昨夜搭进去六七个小时。

关于如何做套利交易,我就不赘述,大家可以看这篇文章,有内容有故事:https://daily.zhihu.com/story/4831821。

本文没有故事,只有技术和产品上的分析。

既然要做可行性分析,那么第一步就是观察交易数据。国内的交易市场虽然在政策要求下清场出局,国外的交易市场还算红火。从 bitfinex,kraken 一路到 bithumb,korbit 等,都提供 rest API,少量提供 websocket 接口。虽然文档欠缺,但这些接口都很简单,上手并不困难。

LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@xthezealot
xthezealot / lyra.txt
Last active May 20, 2026 08:02
Lyra - AI Prompt Optimization Specialist
You are Lyra, a master-level AI prompt optimization specialist. Your mission: transform any user input into
precision-crafted prompts that unlock AI's full potential across all platforms.
## THE 4-D METHODOLOGY
### 1. DECONSTRUCT
- Extract core intent, key entities, and context
- Identify output requirements and constraints
- Map what's provided vs. what's missing
# Claude Code CLI Environment Variables
# This file lists all environment variables used in v2.1.118 with explanations
## Anthropic API & Authentication
ANTHROPIC_API_KEY - Primary API key for Anthropic's Claude API. Used as fallback when no OAuth token is configured
ANTHROPIC_AUTH_TOKEN - Alternative bearer token for Anthropic services. Takes priority over ANTHROPIC_API_KEY for authorization headers
ANTHROPIC_BASE_URL - Custom base URL for Anthropic API endpoints. Overrides the default api.anthropic.com endpoint
ANTHROPIC_BETAS - Comma-separated list of beta feature headers to include in API requests. Appended to internal beta flags
ANTHROPIC_CONFIG_DIR - Override Anthropic config directory. Falls back to XDG_CONFIG_HOME/anthropic, then HOME/.config/anthropic
@skyline75489
skyline75489 / 1000.txt
Created September 17, 2018 10:30
常用 1000 汉字
的一是了我不人在他有这个上们来到时大地为子中你说生国年着就那和要她出也得里后自以会家可下而过天去能对小多然于心学么之都好看起发当没成只如事把还用第样道想作种开美总从无情己面最女但现前些所同日手又行意动方期它头经长儿回位分爱老因很给名法间斯知世什两次使身者被高已亲其进此话常与活正感见明问力理尔点文几定本公特做外孩相西果走将月十实向声车全信重三机工物气每并别真打太新比才便夫再书部水像眼等体却加电主界门利海受听表德少克代员许稜先口由死安写性马光白或住难望教命花结乐色更拉东神记处让母父应直字场平报友关放至张认接告入笑内英军候民岁往何度山觉路带万男边风解叫任金快原吃妈变通师立象数四失满战远格士音轻目条呢病始达深完今提求清王化空业思切怎非找片罗钱紶吗语元喜曾离飞科言干流欢约各即指合反题必该论交终林请医晚制球决窢传画保读运及则房早院量苦火布品近坐产答星精视五连司巴奇管类未朋且婚台夜青北队久乎越观落尽形影红爸百令周吧识步希亚术留市半热送兴造谈容极随演收首根讲整式取照办强石古华諣拿计您装似足双妻尼转诉米称丽客南领节衣站黑刻统断福城故历惊脸选包紧争另建维绝树系伤示愿持千史谁准联妇纪基买志静阿诗独复痛消社算义竟确酒需单治卡幸兰念举仅钟怕共毛句息功官待究跟穿室易游程号居考突皮哪费倒价图具刚脑永歌响商礼细专黄块脚味灵改据般破引食仍存众注笔甚某沉血备习校默务土微娘须试怀料调广蜖苏显赛查密议底列富梦错座参八除跑亮假印设线温虽掉京初养香停际致阳纸李纳验助激够严证帝饭忘趣支春集丈木研班普导顿睡展跳获艺六波察群皇段急庭创区奥器谢弟店否害草排背止组州朝封睛板角况曲馆育忙质河续哥呼若推境遇雨标姐充围案伦护冷警贝著雪索剧啊船险烟依斗值帮汉慢佛肯闻唱沙局伯族低玩资屋击速顾泪洲团圣旁堂兵七露园牛哭旅街劳型烈姑陈莫鱼异抱宝权鲁简态级票怪寻杀律胜份汽右洋范床舞秘午登楼贵吸责例追较职属渐左录丝牙党继托赶章智冲叶胡吉卖坚喝肉遗救修松临藏担戏善卫药悲敢靠伊村戴词森耳差短祖云规窗散迷油旧适乡架恩投弹铁博雷府压超负勒杂醒洗采毫嘴毕九冰既状乱景席珍童顶派素脱农疑练野按犯拍征坏骨余承置臓彩灯巨琴免环姆暗换技翻束增忍餐洛塞缺忆判欧层付阵玛批岛项狗休懂武革良恶恋委拥娜妙探呀营退摇弄桌熟诺宣银势奖宫忽套康供优课鸟喊降夏困刘罪亡鞋健模败伴守挥鲜财孤枪禁恐伙杰迹妹藸遍盖副坦牌江顺秋萨菜划授归浪听凡预奶雄升碃编典袋莱含盛济蒙棋端腿招释介烧误
@carefree-ladka
carefree-ladka / Backend for Frontend (BFF) Pattern.mdx
Created March 4, 2026 03:49
Backend for Frontend (BFF) Pattern

Backend for Frontend (BFF) Pattern

A comprehensive guide to the BFF architectural pattern — what it is, why it exists, and how companies like Netflix use it to power multi-device experiences at scale.


Table of Contents

  1. What is the BFF Pattern?
  2. The Problem BFF Solves
@carefree-ladka
carefree-ladka / React Rendering Strategies.mdx
Last active May 20, 2026 07:25
React Rendering Strategies

React Rendering Strategies

In React and frontend system design interviews, rendering strategy means how HTML is generated and delivered to the browser. Choosing the right strategy directly impacts SEO, performance, interactivity, and cost.


Table of Contents

  1. Quick Reference
  2. Client Side Rendering (CSR)