mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-11-02 07:23:25 +00:00
73e59804fc
* include plotly.js in reports html, implement new plotly multi-legends feature * use `ensure_backend` to `check_backend`, improve charts in reports * requirements files * fix files with `CRLF` line endings * Update widget_helpers.py * Update widget_helpers.py * handle unsupported plotly multiple legends version error
500 lines
13 KiB
Plaintext
Vendored
500 lines
13 KiB
Plaintext
Vendored
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "70ba2c8a",
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"metadata": {},
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"source": [
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"## Notebook setup"
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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": "driven-billion",
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"metadata": {},
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"outputs": [],
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"source": [
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"import warnings\n",
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"import numpy as np\n",
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"import datetime\n",
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"\n",
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"from IPython.display import HTML\n",
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"\n",
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"import openbb_terminal.config_terminal as cfg\n",
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"from openbb_terminal import OpenBBFigure, theme\n",
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"from openbb_terminal.helper_classes import TerminalStyle\n",
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"from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA\n",
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"\n",
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"warnings.filterwarnings(\"ignore\")"
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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": "473e83c7",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Suppressing sdk logs\n",
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"from openbb_terminal.core.session.current_system import set_system_variable\n",
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"\n",
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"set_system_variable(\"LOGGING_SUPPRESS\", True)\n",
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"\n",
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"# Import the OpenBB SDK\n",
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"from openbb_terminal.sdk import openbb, widgets"
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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": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
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"metadata": {},
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"outputs": [],
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"source": [
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"from openbb_terminal.core.session.current_user import get_current_user\n",
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"\n",
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"user = get_current_user()\n",
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"\n",
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"cfg.theme = TerminalStyle(\n",
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" user.preferences.MPL_STYLE,\n",
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" user.preferences.PMF_STYLE,\n",
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" user.preferences.RICH_STYLE,\n",
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")\n",
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"theme.apply_style(\"light\")"
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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": "36091f30",
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"metadata": {},
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"outputs": [],
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"source": [
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"stylesheet = widgets.html_report_stylesheet()"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "807fda4e",
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"metadata": {},
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"source": [
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"## Select Ticker"
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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": "intended-sherman",
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"metadata": {
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"tags": [
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"parameters"
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]
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},
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"outputs": [],
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"source": [
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"# Parameters that will be replaced when calling this notebook\n",
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"# Do not leave parameters blank as notebook will not run otherwise\n",
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"symbol = \"GLD\"\n",
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"report_name = \"Equity Report for VTI\""
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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": "e1f87190",
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"metadata": {},
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"outputs": [],
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"source": [
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"ticker = symbol"
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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": "a441ddbc-d75b-4a18-84d4-e01b677674d3",
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"metadata": {},
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"outputs": [],
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"source": [
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"if \".\" in ticker:\n",
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" import sys\n",
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"\n",
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" sys.exit(0)"
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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": "1be26dae-cafe-4a22-80aa-eff296fc1a9b",
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"metadata": {},
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"outputs": [],
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"source": [
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"ticker_data = openbb.stocks.load(\n",
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" symbol=ticker, start_date=datetime.datetime.now() - datetime.timedelta(days=4 * 30)\n",
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")\n",
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"ticker_data = openbb.stocks.process_candle(data=ticker_data)\n",
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"\n",
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"author = \"OpenBB\"\n",
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"report_title = f\"ETF RESEARCH REPORT ON {ticker.upper()}\"\n",
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"report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
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"report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
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"report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
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"report_title, report_date, report_time, report_timezone"
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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": "2ecfcf81",
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"metadata": {},
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"outputs": [],
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"source": [
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"# info = openbb.etf.summary(name=ticker)\n",
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"# info"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "f8a0d747",
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"metadata": {},
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"source": [
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"## Data"
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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": "39b8e77d",
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"metadata": {},
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"outputs": [],
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"source": [
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"data = openbb.stocks.load(ticker)\n",
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"\n",
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"candle_chart = openbb.etf.candle(\n",
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" symbol=ticker,\n",
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" data=data,\n",
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" external_axes=True,\n",
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")\n",
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"\n",
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"if candle_chart:\n",
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" candle_chart = candle_chart.to_html()"
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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": "f751f57c",
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"metadata": {},
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"outputs": [],
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"source": [
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"import pandas as pd\n",
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"\n",
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"sectors = openbb.etf.weights(ticker)\n",
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"sector_weights_formatted = {}\n",
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"for sector_weight in sectors:\n",
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" sector_weights_formatted[sector_weight[\"sector\"]] = (\n",
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" float(sector_weight[\"weightPercentage\"].strip(\"%\")) / 100\n",
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" )\n",
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"sector_weights_formatted = dict(sorted(sector_weights_formatted.items()))\n",
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"weights_df = pd.DataFrame.from_dict(sector_weights_formatted, orient=\"index\")"
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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": "324e2d4b-b2f6-4da3-bac4-ef785ad4e436",
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"metadata": {},
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"outputs": [],
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"source": [
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"weights_chart = \"\"\n",
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"\n",
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"if \"Percentage\" in weights_df.columns:\n",
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" weights_df.columns = [\"Percentage\"]\n",
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"\n",
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"if (\n",
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" \"Percentage\" in weights_df.columns\n",
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" and len(weights_df[weights_df[\"Percentage\"] > 10].index) > 1\n",
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"):\n",
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" colors = theme.get_colors()\n",
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" fig = OpenBBFigure.create_subplots(\n",
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" 1,\n",
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" 3,\n",
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" specs=[[{\"type\": \"domain\"}, {\"type\": \"pie\", \"colspan\": 2}, None]],\n",
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" row_heights=[1],\n",
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" column_widths=[0.1, 0.8, 0.1],\n",
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" )\n",
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"\n",
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" fig.add_pie(\n",
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" labels=weights_df[weights_df[\"Percentage\"] > 10].index,\n",
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" values=weights_df[weights_df[\"Percentage\"] > 10][\"Percentage\"],\n",
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" textinfo=\"label+percent\",\n",
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" hoverinfo=\"label+percent\",\n",
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" automargin=True,\n",
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" rotation=45,\n",
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" row=1,\n",
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" col=2,\n",
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" )\n",
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" fig.update_traces(\n",
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" textposition=\"outside\",\n",
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" textfont_size=15,\n",
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" marker=dict(\n",
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" colors=colors,\n",
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" line=dict(color=\"#F5EFF3\", width=0.8),\n",
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" ),\n",
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" )\n",
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"\n",
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" fig.update_layout(\n",
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" margin=dict(t=40, b=20),\n",
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" title=dict(\n",
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" text=f\"Sector holdings of {ticker}\",\n",
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" y=0.98,\n",
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" x=0.5,\n",
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" xanchor=\"center\",\n",
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" yanchor=\"top\",\n",
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" ),\n",
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" colorway=colors,\n",
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" showlegend=False,\n",
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" )\n",
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"\n",
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" weights_chart = fig.to_html()"
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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": "d8bb53c1-147e-4342-af61-0d0a9cc56e59",
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"metadata": {},
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"outputs": [],
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"source": [
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"holdings = openbb.etf.holdings(ticker)\n",
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"holdings"
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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": "b60ebf25",
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"metadata": {},
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"outputs": [],
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"source": [
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"indicators = dict(\n",
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" ema=dict(length=[50]),\n",
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" sma=dict(length=[50]),\n",
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" wma=dict(length=[50]),\n",
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")\n",
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"\n",
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"ma_chart = PlotlyTA.plot(ticker_data, indicators, symbol, candles=False, volume=False)\n",
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"\n",
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"if ma_chart:\n",
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" ma_chart = ma_chart.show(external=True)\n",
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" ma_chart = ma_chart.to_html()"
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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": "fa02a874",
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"metadata": {},
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"outputs": [],
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"source": [
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"macd_chart = openbb.ta.macd_chart(\n",
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" ticker_data[\"Close\"], symbol=symbol, external_axes=True\n",
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")\n",
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"\n",
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"if macd_chart:\n",
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" macd_chart = macd_chart.to_html()"
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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": "de3d59c7",
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"metadata": {},
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"outputs": [],
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"source": [
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"cci_chart = openbb.ta.cci_chart(ticker_data, symbol=symbol, external_axes=True)\n",
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"\n",
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"if cci_chart:\n",
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" cci_chart = cci_chart.to_html()"
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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": "44326981",
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"metadata": {},
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"outputs": [],
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"source": [
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"stoch_chart = openbb.ta.stoch_chart(ticker_data, symbol=symbol, external_axes=True)\n",
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"\n",
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"if stoch_chart:\n",
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" stoch_chart = stoch_chart.to_html()"
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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": "3e171fe5",
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"metadata": {},
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"outputs": [],
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"source": [
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"adx_chart = openbb.ta.adx_chart(ticker_data, symbol=symbol, external_axes=True)\n",
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"\n",
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"if adx_chart:\n",
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" adx_chart = adx_chart.to_html()"
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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": "fc1a5418",
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"metadata": {},
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"outputs": [],
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"source": [
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"bbands_chart = openbb.ta.bbands_chart(ticker_data, symbol=symbol, external_axes=True)\n",
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"\n",
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"if bbands_chart:\n",
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" bbands_chart = bbands_chart.to_html()"
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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": "d4be9f55",
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"metadata": {},
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"outputs": [],
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"source": [
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"ad_chart = openbb.ta.ad_chart(ticker_data, symbol=symbol, external_axes=True)\n",
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"\n",
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"if ad_chart:\n",
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" ad_chart = ad_chart.to_html()"
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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": "4d29aafa",
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"metadata": {},
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"outputs": [],
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"source": [
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"ta_rsi = openbb.ta.rsi_chart(ticker_data[\"Close\"], external_axes=True)\n",
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"\n",
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"if ta_rsi:\n",
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" ta_rsi = ta_rsi.to_html()"
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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": "e539e995",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = openbb.ta.rsi(ticker_data[\"Close\"])\n",
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"rsi_value = round(df.values[-1][0], 2)\n",
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"rsi_value"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
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"metadata": {},
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"source": [
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"## Render the report template to a file"
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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": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
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"metadata": {},
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"outputs": [],
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"source": [
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"body = \"\"\n",
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"\n",
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"\n",
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"body += widgets.header(\n",
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" author,\n",
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" report_date,\n",
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" report_time,\n",
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" report_timezone,\n",
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" f\"<b>ETF RESEARCH REPORT:</b> {ticker.upper()}\",\n",
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" plotly_js=True,\n",
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")\n",
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"\n",
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"body += widgets.tablinks(\n",
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" [\n",
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" \"SUMMARY\",\n",
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" \"Technical Analysis\",\n",
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" ]\n",
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")\n",
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"\n",
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"htmlcode = widgets.h(3, \"Summary\")\n",
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"# htmlcode += widgets.p(info)\n",
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"htmlcode += widgets.row([candle_chart])\n",
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"\n",
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"htmlcode += widgets.p(\"The ETF has the following weights distribution:\")\n",
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"\n",
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"htmlcode += widgets.row([weights_df.to_html()])\n",
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"htmlcode += widgets.row([weights_chart])\n",
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"\n",
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"htmlcode += widgets.p(\"And has funds in the following assets:\")\n",
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"htmlcode += widgets.row([holdings.to_html()])\n",
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"\n",
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"body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
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"\n",
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"htmlcode = widgets.row([widgets.h(3, f\"Moving Averages for {symbol}\") + ma_chart])\n",
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"htmlcode += widgets.row([macd_chart or \"\"])\n",
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"htmlcode += widgets.row([ta_rsi or \"\"])\n",
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"htmlcode += widgets.row([stoch_chart or \"\"])\n",
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"htmlcode += widgets.row([cci_chart or \"\"])\n",
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"htmlcode += widgets.row([ad_chart or \"\"])\n",
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"htmlcode += widgets.row([bbands_chart or \"\"])\n",
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"htmlcode += widgets.row([adx_chart or \"\"])\n",
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"body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
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"\n",
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"\n",
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"body += widgets.tab_clickable_and_save_evt()\n",
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"\n",
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"report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
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"\n",
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"\n",
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"# to save the results\n",
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"with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
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" fh.write(report)"
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]
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}
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],
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"metadata": {
|
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"celltoolbar": "Tags",
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"kernelspec": {
|
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"display_name": "venv",
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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": "3.10.5"
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},
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"vscode": {
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|
"interpreter": {
|
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"hash": "381a209f752e9104bff95ec5e80679ea2e476866b80e4326f1ee6b7658af6049"
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|
}
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|
}
|
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},
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"nbformat_minor": 5
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}
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