Mohammad Aghdam
212 lines
5.9 KiB
Python
212 lines
5.9 KiB
Python
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "53c28be9",
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"metadata": {},
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"source": [
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"# 1) Data — Collect & Save OHLC (MT5)\n",
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"\n",
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"This notebook fetches OHLCV data from MT5 via a tiny adapter and saves it to CSV.\n",
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"- Keep your credentials in `.env` and **do not commit** `.env`.\n",
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"- If MT5 is not available, you can skip this and drop in a CSV manually."
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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": 1,
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"id": "dcb5ac32",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Connecting to MT5...\n",
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"MT5 connected: True\n"
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]
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}
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],
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"source": [
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"import sys, os; sys.path.append(os.path.abspath('..')) # Path fix\n",
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"\n",
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"# Prereqs: `pip install -r requirements.txt` (locally)\n",
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"import os\n",
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"from pathlib import Path\n",
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"import pandas as pd\n",
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"from dotenv import load_dotenv\n",
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"\n",
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"from adapters import broker\n",
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"\n",
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"# Load settings from env\n",
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"load_dotenv()\n",
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"SYMBOL = os.getenv(\"TRAINING_SYMBOL\", \"EURUSD\")\n",
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"TIMEFRAME = os.getenv(\"TIMEFRAME\", \"M15\")\n",
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"START = os.getenv(\"DATA_START\", \"2023-01-01\")\n",
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"END = os.getenv(\"DATA_END\", \"2025-01-01\")\n",
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"\n",
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"print(\"Connecting to MT5...\")\n",
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"ok = broker.open_session(\n",
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" login=int(os.getenv(\"MT5_LOGIN\", \"0\")) or None,\n",
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" password=os.getenv(\"MT5_PASSWORD\"),\n",
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" server=os.getenv(\"MT5_SERVER\")\n",
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")\n",
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"print(\"MT5 connected:\", ok)"
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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": 2,
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"id": "3b690e97",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Saved: G:\\My Drive\\Bots DRL\\DRL\\DRL-MT5-Lab\\notebooks\\data\\ohlc_EURUSD_M15.csv\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>open</th>\n",
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" <th>high</th>\n",
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" <th>low</th>\n",
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" <th>close</th>\n",
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" <th>volume</th>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>time</th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" <th></th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>2024-12-31 20:45:00+00:00</th>\n",
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" <td>1.03568</td>\n",
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" <td>1.03568</td>\n",
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" <td>1.03528</td>\n",
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" <td>1.03531</td>\n",
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" <td>529</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2024-12-31 21:00:00+00:00</th>\n",
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" <td>1.03528</td>\n",
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" <td>1.03625</td>\n",
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" <td>1.03518</td>\n",
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" <td>1.03619</td>\n",
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" <td>425</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2024-12-31 21:15:00+00:00</th>\n",
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" <td>1.03618</td>\n",
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" <td>1.03647</td>\n",
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" <td>1.03575</td>\n",
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" <td>1.03590</td>\n",
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" <td>465</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2024-12-31 21:30:00+00:00</th>\n",
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" <td>1.03590</td>\n",
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" <td>1.03590</td>\n",
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" <td>1.03543</td>\n",
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" <td>1.03560</td>\n",
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" <td>545</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2024-12-31 21:45:00+00:00</th>\n",
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" <td>1.03560</td>\n",
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" <td>1.03571</td>\n",
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" <td>1.03539</td>\n",
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" <td>1.03542</td>\n",
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" <td>306</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" open high low close volume\n",
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"time \n",
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"2024-12-31 20:45:00+00:00 1.03568 1.03568 1.03528 1.03531 529\n",
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"2024-12-31 21:00:00+00:00 1.03528 1.03625 1.03518 1.03619 425\n",
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"2024-12-31 21:15:00+00:00 1.03618 1.03647 1.03575 1.03590 465\n",
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"2024-12-31 21:30:00+00:00 1.03590 1.03590 1.03543 1.03560 545\n",
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"2024-12-31 21:45:00+00:00 1.03560 1.03571 1.03539 1.03542 306"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"\n",
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"# Fetch OHLC and save\n",
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"DATA_DIR = Path(\"data\"); DATA_DIR.mkdir(exist_ok=True)\n",
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"df = broker.fetch_ohlc(SYMBOL, TIMEFRAME, START, END)\n",
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"out_csv = DATA_DIR / f\"ohlc_{SYMBOL}_{TIMEFRAME}.csv\"\n",
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"df.to_csv(out_csv)\n",
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"print(\"Saved:\", out_csv.resolve())\n",
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"df.tail()"
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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": "5e151d9a",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"# Clean shutdown\n",
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"broker.close_session()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "drl",
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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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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.18"
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"nbformat_minor": 5
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}
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