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HOW TO CREATE A TRADING BOT WITH CLAUDE Step-by-step tutorial, free and 23 minutes long. → Build it from scratch → Use Claude as the base → Buy and sell orders 🔖 Bookmark this.

Python Quiz: What is the Output? A) 5 B) 7 C) 8 D) 4

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卧槽！有人把 50 套量化交易策略全部公开了，连源码、回测收益和最大回撤都能直接查看！ quants.md + QuantJourney Backtester，Apache-2.0 开源，覆盖股票、ETF、期货、外汇等市场。 以前找量化策略，GitHub 上虽然代码不少，但很多只有交易逻辑，没有完整回测结果，想验证还得自己搭环境。 这套资源有点东西，直接把策略源码、历史表现和 Python 回测引擎整合起来，最长回测跨度达到 26 年。 核心能力： 1️⃣ 50 套量化策略：25 套组合权重策略、20 套订单策略、5 套滚动验证和优化案例 2️⃣ 策略类型丰富：均线趋势、RSI 反转、动量轮动、配对交易、风险平价等 3️⃣ 交易模拟：支持市价、限价、止损、追踪止损、OCO 订单，还能计算手续费和滑点 4️⃣ 参数优化：支持网格搜索、Optuna、Walk-Forward 样本外验证，检查过拟合风险 5️⃣ 可视化回测：网站展示 45 份结果看板，包含收益、Sharpe、最大回撤等指标 6️⃣ AI 辅助开发：内置 5 个 AI Skills，辅助编写策略、检查未来函数和分析回测报告 更实用的是，比如你想研究 SPY 均线策略，可以直接查看历史收益、最大回撤和 Python 源码，再修改参数重新回测。 网站还能按策略类型、市场和交易周期筛选，不用自己到处找代码。 不过部分历史数据回测需要 QuantJourney 账户及相应权限，开源引擎也不代表云端服务全部免费。 做股票量化、策略回测或者 AI 交易系统开发的，这套资源值得收藏！ 策略库： GitHub：

我去！有人拿 10 个历史股票案例，做了一套 A 股自动选股系统，连相似 K 线形态都能匹配出来！ A-Share Quant Selector，481 Stars，基于 Python + AKShare，专门研究 A 股碗口反弹和趋势买点。 以前找这类股票，得一只只看 K 线、找放量信号、判断趋势，再筛掉风险股，光复盘就很费时间。 这套工具直接把选股、形态匹配、K 线分析和钉钉提醒串起来，还能根据历史案例给股票相似度排名。 核心能力： 1️⃣ 碗口反弹选股：结合 KDJ、趋势线、成交量，寻找回踩后的潜在反弹机会 2️⃣ B1 图形匹配：对比 10 个历史案例，从趋势、量能、K 线形态和 KDJ 四个维度评分 3️⃣ 自动过滤风险股：排除 ST、退市风险股、异常数据和明显放量阴线 4️⃣ 智能信号分类：自动区分回落碗中、靠近多空线、靠近短期趋势线的股票 5️⃣ K 线可视化：自动生成走势图、趋势线和成交量图表，方便检查选股信号 6️⃣ 自动选股推送：支持每日更新行情、定时运行，结果和 K 线图直接发送钉钉 比较有意思的是，B1 匹配还能给每只股票计算相似度，并告诉你最接近哪个历史案例。 比如一只股票出现缩量整理、KDJ 低位、价格靠近趋势线，系统就能把它筛出来，再和历史形态比较。 项目还提供 Web 管理界面，可以查看股票数据、修改策略参数，不用每次都在终端操作。 做 A 股短线、趋势选股或者 Python 量化研究的，这套值得拿来研究。

Python Quiz: 90% of the beginners will answer this wrongly🤯🤯 Comment your answer 👇 A) 6 B) 9 C) 10 D) 5

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Python Quiz Challenge! Comment your answer: A, B, C, or D before running the code.

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Mika 正式开源：真正的 Phone Agent，就跑在你的安卓手机上。 一句话交给它，它就能在你手机上把事干完。 复用你现有的登录态，不用额外授权，也不用 Root，更不用电脑。 你继续玩手机，它在后台干活，互不干扰。干完了通知你，你也可以随时随地再丢任务给它。 他能干什么？ 1、操作你手机上的任何 App：发微信、总结群聊、小红书总结博主内容，在 BOSS 直聘批量打招呼、订闹钟、改设置，手机上的 App 都能操作，不用事先适配 2、内置浏览器：强大的 Browser use，搜索、筛选、读网页、批量操作，帮你把事干好的同时，节奏像真人一样，不容易被风控 3、悬浮胶囊：在任何 App 里都能随时呼起，和它对话，叫它干活，或者把这一屏发给它，问这个怎么回、帮我记下来 4、本地 Linux 沙箱：跑 Python、处理你发来的文件、Agent 写的脚本 不要 root，无需电脑，就跑在你的安卓手机上，真正的 phone Agent，替你在手机上把事都干了。 更多功能正在赶来的路上。 欢迎 star，下载使用，感兴趣也可以一起开发。 Github 地址：

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THIS IS F*CKING DANGEROUS MY GROK BOT RAN A TRADING TERMINAL BY ITSELF OVERNIGHT AND TURNED $69.67 INTO $13,370 BY 7AM I never touched a trade. I funded it, put the phone on charge and went to bed. it found setups, sized entries and closed every position by the rules I gave it 10 GitHub repos to build your own overnight system with Grok Bot: 01 / Cryptofeed pipes live trades, prices and order books from crypto exchanges straight into your scanner 02 / CCXT one API for balances, market data and orders across exchanges, so your executor talks to all of them the same way 03 / Freqtrade runs your strategies with backtests, dry-run mode, position tracking and a web dashboard 04 / VectorBT throws thousands of entry and exit combos at historical data and shows the trades and drawdowns behind every result 05 / TA-Lib Python gives you RSI, MACD, moving averages and 150+ indicators computed right from market data 06 / skfolio balances allocations across positions with limits on weights, turnover and trading costs 07 / QuantStats turns your returns into a full report: drawdowns, win rate, volatility and benchmark comparison 08 / DuckDB keeps every market snapshot and trade record queryable, so the morning review can replay the whole night 09 / APScheduler runs your Python jobs on schedule: data refreshes, balance checks and the morning report 10 / Lightweight Charts draws your price feed and trade markers in a live terminal you can watch while the system works these are building blocks you connect through scripts, APIs or MCP tools. let only one service place orders, hard-code spend and loss limits there, and always check an order's status before retrying it run a full session in dry-run first. the morning report should split closed profit, open positions, fees and failed orders, so the headline balance has a record behind it

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Python Quiz: What is the Output?

HACKERS DON’T WANT YOU TO SEE THIS. Someone built a cross platform Wi-Fi hacking tool that works without the usual Linux toolchain. Meet WIFIT3. A standalone Wi-Fi auditing tool built entirely in Python. → Works on Linux, Windows and macOS → Scans 2.4GHz and 5GHz networks → Detects encryption types, including WPA3 → Supports WPA/WPA2 security testing → Includes WPS and legacy WEP attack capabilities → Exports captured handshake data in HC22000 format No aircrack-ng. No reaver. No complicated runtime dependencies. Just a supported USB Wi-Fi adapter and the tool. A powerful collection of wireless hacking and auditing features in one project. Only test networks you own or have permission to assess. REPO BELOW

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30 Must Know Terms in Claude

Top 10 Python Built-in Functions Every Beginner Must Know 💥