169 lines
7.5 KiB
Plaintext
169 lines
7.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "45f026b5",
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"metadata": {},
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"source": [
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"# 02 — Streaming de Datos en Tiempo Real (Binance WebSocket)\n",
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"\n",
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"Binance ofrece WebSocket streams push-based para datos de mercado en tiempo real.\n",
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"\n",
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"**Base URLs:**\n",
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"- Produccion: `wss://stream.binance.com:9443/ws/<stream>`\n",
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"- Testnet: `wss://testnet.binance.vision/ws/<stream>`\n",
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"- Multi-stream: `wss://stream.binance.com:9443/stream?streams=<s1>/<s2>`\n",
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"\n",
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"**Streams principales:**\n",
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"| Stream | Nombre | Frecuencia |\n",
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"|---|---|---|\n",
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"| Trades individuales | `<symbol>@trade` | Cada trade |\n",
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"| Klines en vivo | `<symbol>@kline_<interval>` | Cada cambio en vela |\n",
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"| Mini ticker 24h | `<symbol>@miniTicker` | ~1s |\n",
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"| Book ticker (best bid/ask) | `<symbol>@bookTicker` | Cada cambio |\n",
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"| Todos los tickers | `!miniTicker@arr` | ~1s |\n",
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"\n",
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"**Reglas de conexion:**\n",
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"- Ping cada 3 min desde Binance, pong requerido\n",
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"- Desconexion automatica a las 24h — reconectar periodicamente\n",
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"- Se puede suscribir/desuscribir dinamicamente via JSON"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "6bb48c2e",
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"metadata": {},
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"outputs": [],
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"source": [
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"import asyncio\n",
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"import json\n",
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"import websockets\n",
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"import pandas as pd\n",
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"from datetime import datetime, timezone\n",
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"from collections import deque\n",
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"\n",
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"WS_BASE = \"wss://stream.binance.com:9443/ws\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "2b2d9b2d",
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"metadata": {},
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"source": [
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"## Stream de Trades individuales\n",
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"\n",
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"`<symbol>@trade` — recibe cada trade ejecutado en tiempo real.\n",
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"\n",
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"Campos clave:\n",
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"- `p` = precio, `q` = cantidad\n",
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"- `m` = true si el buyer es maker (es decir, fue un sell market order que impacto un bid)\n",
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"- `t` = trade ID, `T` = timestamp"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aaed9f77",
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"metadata": {},
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"outputs": [],
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"source": [
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"async def stream_trades(symbol: str, max_trades: int = 100) -> list[dict]:\n",
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" \"\"\"Captura N trades en tiempo real y retorna como lista.\"\"\"\n",
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" url = f\"{WS_BASE}/{symbol.lower()}@trade\"\n",
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" trades = []\n",
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"\n",
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" async with websockets.connect(url) as ws:\n",
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" while len(trades) < max_trades:\n",
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" msg = json.loads(await ws.recv())\n",
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" trades.append({\n",
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" \"trade_id\": msg[\"t\"],\n",
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" \"time\": datetime.fromtimestamp(msg[\"T\"] / 1000, tz=timezone.utc),\n",
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" \"price\": float(msg[\"p\"]),\n",
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" \"qty\": float(msg[\"q\"]),\n",
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" \"is_buyer_maker\": msg[\"m\"],\n",
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" \"side\": \"SELL\" if msg[\"m\"] else \"BUY\",\n",
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" })\n",
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"\n",
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" return trades"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5dc19bb4",
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"source": "### Ejemplo: Capturar 100 trades de BTCUSDT",
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"metadata": {}
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},
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{
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"cell_type": "code",
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"id": "2ad6bc1c",
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"source": "trades = await stream_trades(\"BTCUSDT\", max_trades=100)\ndf_trades = pd.DataFrame(trades)\nprint(f\"Capturados {len(df_trades)} trades\")\nprint(f\"Rango de tiempo: {df_trades['time'].min()} -> {df_trades['time'].max()}\")\nprint(f\"Precio: {df_trades['price'].min():.2f} - {df_trades['price'].max():.2f}\")\nprint(f\"BUY: {(df_trades['side'] == 'BUY').sum()}, SELL: {(df_trades['side'] == 'SELL').sum()}\")\ndf_trades.head(10)",
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"metadata": {},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"id": "65a65f5b",
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"source": "## Stream de Klines en vivo\n\n`<symbol>@kline_<interval>` — recibe actualizaciones de la vela actual y velas cerradas.\n\nCampo clave: `k.x` = true cuando la vela esta cerrada (final). Mientras `x=false`, los valores OHLCV son parciales.",
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"metadata": {}
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},
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{
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"cell_type": "code",
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"id": "99c11390",
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"source": "async def stream_klines(symbol: str, interval: str = \"1m\", max_closed: int = 5) -> list[dict]:\n \"\"\"Captura N velas CERRADAS en tiempo real (espera a que x=true).\"\"\"\n url = f\"{WS_BASE}/{symbol.lower()}@kline_{interval}\"\n closed_candles = []\n current = None\n\n async with websockets.connect(url) as ws:\n while len(closed_candles) < max_closed:\n msg = json.loads(await ws.recv())\n k = msg[\"k\"]\n current = {\n \"open_time\": pd.Timestamp(k[\"t\"], unit=\"ms\", tz=\"UTC\"),\n \"open\": float(k[\"o\"]),\n \"high\": float(k[\"h\"]),\n \"low\": float(k[\"l\"]),\n \"close\": float(k[\"c\"]),\n \"volume\": float(k[\"v\"]),\n \"trades\": k[\"n\"],\n \"is_closed\": k[\"x\"],\n }\n if k[\"x\"]: # vela cerrada\n closed_candles.append(current)\n print(f\"Vela cerrada #{len(closed_candles)}: {current['close']:.2f} | vol={current['volume']:.4f} | trades={current['trades']}\")\n\n return closed_candles",
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"metadata": {},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"id": "ddab999b",
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"source": "### Ejemplo: Capturar 3 velas cerradas de 1m de BTCUSDT\n\n**Nota:** Esto tarda hasta 3 minutos esperando que se cierren las velas.",
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"metadata": {}
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},
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{
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"cell_type": "code",
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"id": "5e4b017f",
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"source": "candles = await stream_klines(\"BTCUSDT\", interval=\"1m\", max_closed=3)\ndf_candles = pd.DataFrame(candles)\ndf_candles",
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"metadata": {},
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"execution_count": null,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"id": "b067572a",
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"source": "## Multi-stream: multiples feeds en una conexion\n\nCombinar trades + klines + book ticker de varios pares en un solo WebSocket.",
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"metadata": {}
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},
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{
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"cell_type": "code",
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"id": "b4763056",
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"source": "async def stream_multiple(streams: list[str], max_messages: int = 100) -> list[dict]:\n \"\"\"Captura N mensajes de multiples streams combinados.\"\"\"\n combined = \"/\".join(streams)\n url = f\"wss://stream.binance.com:9443/stream?streams={combined}\"\n messages = []\n\n async with websockets.connect(url) as ws:\n while len(messages) < max_messages:\n raw = json.loads(await ws.recv())\n messages.append({\n \"stream\": raw[\"stream\"],\n \"data\": raw[\"data\"],\n })\n\n return messages\n\n\n# Ejemplo: trades de BTC + ETH + book ticker de BTC\nmulti = await stream_multiple([\n \"btcusdt@trade\",\n \"ethusdt@trade\",\n \"btcusdt@bookTicker\",\n], max_messages=50)\n\n# Contar mensajes por stream\nfrom collections import Counter\ncounts = Counter(m[\"stream\"] for m in multi)\nprint(\"Mensajes por stream:\")\nfor stream, count in counts.most_common():\n print(f\" {stream}: {count}\")",
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"metadata": {},
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"execution_count": null,
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"outputs": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.7"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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} |