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OpenBB/openbb_terminal/reports/templates/crypto.ipynb
James Maslek 3dd9fb9567 Fix reports after SDK changes (#3444) 
* Fix sdk changes

* Forex report

* Crypto Report

* etf report

* economy report
2022-11-17 12:43:40 -05:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "70ba2c8a",
"metadata": {},
"source": [
"## Notebook setup"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "driven-billion",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import io\n",
"import warnings\n",
"import datetime\n",
"import numpy as np\n",
"import base64\n",
"import pandas as pd\n",
"\n",
"import matplotlib.pyplot as plt\n",
"import matplotlib_inline.backend_inline\n",
"\n",
"from IPython.display import HTML\n",
"\n",
"# import sys\n",
"# sys.path.append('../../')\n",
"\n",
"from openbb_terminal.reports import widget_helpers as widgets\n",
"from openbb_terminal.sdk import openbb\n",
"from openbb_terminal.helper_classes import TerminalStyle\n",
"from openbb_terminal.core.config.paths import REPOSITORY_DIRECTORY\n",
"\n",
"%matplotlib inline\n",
"matplotlib_inline.backend_inline.set_matplotlib_formats(\"svg\")\n",
"warnings.filterwarnings(\"ignore\")\n",
"\n",
"pd.set_option(\"display.float_format\", lambda x: \"%.5f\" % x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c3fe7db5-ec6a-42cf-9e66-52dc1de22370",
"metadata": {},
"outputs": [],
"source": [
"try:\n",
" theme = TerminalStyle(\"light\", \"light\", \"light\")\n",
"except:\n",
" pass\n",
"stylesheet = widgets.html_report_stylesheet()"
]
},
{
"cell_type": "markdown",
"id": "807fda4e",
"metadata": {},
"source": [
"## Select Ticker"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "intended-sherman",
"metadata": {
"tags": [
"parameters"
]
},
"outputs": [],
"source": [
"# Parameters that will be replaced when calling this notebook\n",
"# Do not leave parameters blank as notebook will not run otherwise\n",
"symbol = \"BTC\"\n",
"report_name = f\"Crypto Report for {symbol}\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2c46efb8",
"metadata": {},
"outputs": [],
"source": [
"ticker = symbol"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d4897334",
"metadata": {},
"outputs": [],
"source": [
"author = \"\"\n",
"report_title = f\"INVESTMENT RESEARCH REPORT ON {ticker.upper()}\"\n",
"report_date = datetime.datetime.now().strftime(\"%d %B, %Y\")\n",
"report_time = datetime.datetime.now().strftime(\"%H:%M\")\n",
"report_timezone = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo\n",
"report_title, report_date, report_time, report_timezone"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "35d9a943",
"metadata": {},
"outputs": [],
"source": [
"# basic info\n",
"\n",
"basic_info = openbb.crypto.dd.basic(ticker)\n",
"if not basic_info.empty:\n",
" basic_info = basic_info.set_index(\"Metric\")\n",
" basic_info"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "091d305e",
"metadata": {},
"outputs": [],
"source": [
"news = openbb.crypto.dd.news(symbol=ticker).head(10)\n",
"news = news.set_index(\"published_at\")\n",
"news.sort_index()\n",
"news[\"link\"] = news[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
"news"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bd281ab8",
"metadata": {},
"outputs": [],
"source": [
"links = openbb.crypto.dd.links(ticker)\n",
"\n",
"if not links.empty:\n",
" links = links.set_index(\"Name\")\n",
"\n",
" links[\"Link\"] = links[\"Link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
"\n",
" links"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9b73e41f",
"metadata": {},
"outputs": [],
"source": [
"# alt index\n",
"\n",
"# fig, ax = plt.subplots(figsize=(11, 5), dpi=150)\n",
"# openbb.crypto.ov.altindex_chart(external_axes=[ax])\n",
"# fig.tight_layout()\n",
"# f = io.BytesIO()\n",
"# fig.savefig(f, format=\"svg\")\n",
"# altindex = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "07d09ce8",
"metadata": {},
"outputs": [],
"source": [
"five_year = datetime.datetime.now() - datetime.timedelta(days=1825)\n",
"three_year = datetime.datetime.now() - datetime.timedelta(days=1095)\n",
"one_year = datetime.datetime.now() - datetime.timedelta(days=365)\n",
"three_months = datetime.datetime.now() - datetime.timedelta(days=90)\n",
"\n",
"dates = {\n",
" \"three_months\": three_months,\n",
" \"one_year\": one_year,\n",
" \"three_year\": three_year,\n",
" \"five_year\": five_year,\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e6d6d43d",
"metadata": {},
"outputs": [],
"source": [
"def get_historical_data(ticker, dict_of_dates, is_plot=True):\n",
"\n",
" list_of_historical_data = []\n",
"\n",
" for date in dict_of_dates:\n",
" data = openbb.crypto.load(\n",
" symbol=ticker,\n",
" start_date=dict_of_dates[date],\n",
" )\n",
"\n",
" # we'll be using the adjusted close price as same as close price\n",
" data[\"Adj Close\"] = data[\"Close\"]\n",
"\n",
" if is_plot:\n",
" fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
" plt.suptitle(\n",
" f\"{date} historical data for {ticker.upper()}\",\n",
" fontsize=14,\n",
" color=\"black\",\n",
" )\n",
" data.plot(y=\"Close\", ax=ax)\n",
" plt.ylabel(\"USDT\")\n",
"\n",
" fig.tight_layout()\n",
" f = io.BytesIO()\n",
" fig.savefig(f, format=\"svg\")\n",
" plot_data = f.getvalue().decode(\"utf-8\")\n",
"\n",
" list_of_historical_data.append(plot_data)\n",
" else:\n",
" list_of_historical_data.append(data)\n",
"\n",
" return list_of_historical_data"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ed19a708",
"metadata": {},
"outputs": [],
"source": [
"try:\n",
" historical_data = get_historical_data(ticker, dates)\n",
"except Exception as e:\n",
" raise KeyboardInterrupt"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8f815dbc",
"metadata": {},
"outputs": [],
"source": [
"historical_data_one_year = get_historical_data(ticker, {\"one_year\": one_year}, False)[0]\n",
"historical_data_one_year"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "081a4bb3",
"metadata": {},
"outputs": [],
"source": [
"from openbb_terminal.cryptocurrency.cryptocurrency_helpers import show_quick_performance\n",
"\n",
"show_quick_performance(\n",
" crypto_df=historical_data_one_year,\n",
" symbol=ticker,\n",
" current_currency=\"USDT\",\n",
" source=\"cctx\",\n",
" exchange=\"binance\",\n",
" interval=\"1440\",\n",
")\n",
"\n",
"fig = plt.figure(figsize=(11, 3), dpi=150)\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"quick_performance = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "88af0fbe",
"metadata": {},
"outputs": [],
"source": [
"fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
"openbb.crypto.dd.headlines_chart(ticker, external_axes=[ax])\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"headlines = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3b23868d",
"metadata": {},
"outputs": [],
"source": [
"# fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)\n",
"# openbb.crypto.chart(\n",
"# historical_data_one_year,\n",
"# symbol=ticker,\n",
"# currency=\"USDT\",\n",
"# source=\"cctx\",\n",
"# exchange=\"binance\",\n",
"# interval=\"1440\",\n",
"# external_axes=[ax1, ax2],\n",
"# )\n",
"# fig.tight_layout()\n",
"# f = io.BytesIO()\n",
"# fig.savefig(f, format=\"svg\")\n",
"# one_year_candle = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e4509c6e",
"metadata": {},
"outputs": [],
"source": [
"fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)\n",
"openbb.crypto.chart(\n",
" historical_data_one_year,\n",
" to_symbol=ticker,\n",
" from_symbol=\"USDT\",\n",
" source=\"cctx\",\n",
" exchange=\"binance\",\n",
" interval=\"1440\",\n",
" external_axes=[ax1, ax2],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"candle_one_year = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "markdown",
"id": "7f83daae",
"metadata": {},
"source": [
"## Due Diligence"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "93d66cf1",
"metadata": {},
"outputs": [],
"source": [
"# market cap dominance\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 5), dpi=150)\n",
"openbb.crypto.dd.mcapdom_chart(symbol=ticker, external_axes=[ax])\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"mcapdom = f.getvalue().decode(\"utf-8\")\n",
"mcapdom_df = openbb.crypto.dd.mcapdom(symbol=ticker)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "284b0586",
"metadata": {},
"outputs": [],
"source": [
"# roadmap\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 5), dpi=150)\n",
"openbb.crypto.dd.rm_chart(symbol=ticker, external_axes=[ax])\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"roadmap_view = f.getvalue().decode(\"utf-8\")\n",
"\n",
"roadmap_model = openbb.crypto.dd.rm(symbol=ticker)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f496d047",
"metadata": {},
"outputs": [],
"source": [
"if not roadmap_model.empty:\n",
" roadmap_model = roadmap_model.set_index(\"Date\")\n",
" roadmap_model.sort_index()\n",
" roadmap_model"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9ddbc654",
"metadata": {},
"outputs": [],
"source": [
"fig, ax1 = plt.subplots(figsize=(11, 5), dpi=150)\n",
"ax2 = ax1.twinx()\n",
"openbb.crypto.dd.tk_chart(symbol=ticker, external_axes=[ax1, ax2])\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"tokenomics_view = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "aecd816f",
"metadata": {},
"outputs": [],
"source": [
"tokenomics_model = openbb.crypto.dd.rm(symbol=ticker)\n",
"if not tokenomics_model.empty:\n",
" tokenomics_model = tokenomics_model.set_index(\"Date\")\n",
" tokenomics_model.sort_index()\n",
" tokenomics_model"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7d02fcc4",
"metadata": {},
"outputs": [],
"source": [
"# fundraise\n",
"\n",
"fundraise = openbb.crypto.dd.fr(symbol=ticker)\n",
"fundraise_info = fundraise[0]\n",
"fundraise_df = fundraise[1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5e625a2e",
"metadata": {},
"outputs": [],
"source": [
"trading_pair_info = openbb.crypto.dd.trading_pair_info(f\"{ticker}-USDT\")\n",
"if not trading_pair_info.empty:\n",
" trading_pair_info = trading_pair_info.set_index(\"Metric\")\n",
" trading_pair_info"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8f33b4d8",
"metadata": {},
"outputs": [],
"source": [
"import openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model as gecko\n",
"from openbb_terminal.cryptocurrency.cryptocurrency_helpers import get_coingecko_id\n",
"\n",
"ath = pd.DataFrame()\n",
"try:\n",
" cg_id = get_coingecko_id(symbol=ticker)\n",
" coin = gecko.Coin(ticker)\n",
" ath = coin.get_all_time_high(currency=cg_id)\n",
"\n",
"except Exception as e:\n",
" # ath = str(\"Reached coingecko API limit\")\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2a82e990",
"metadata": {},
"outputs": [],
"source": [
"import openbb_terminal.cryptocurrency.due_diligence.pycoingecko_model as gecko\n",
"from openbb_terminal.cryptocurrency.cryptocurrency_helpers import get_coingecko_id\n",
"\n",
"atl = pd.DataFrame()\n",
"try:\n",
" cg_id = get_coingecko_id(symbol=ticker)\n",
" coin = gecko.Coin(ticker)\n",
" atl = coin.get_all_time_low(currency=cg_id)\n",
"\n",
"except Exception as e:\n",
" # atl = str(\"Reached coingecko API limit\")\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e9e512e9",
"metadata": {},
"outputs": [],
"source": [
"# market stats about loaded coin\n",
"\n",
"market = openbb.crypto.dd.mkt(ticker)\n",
"\n",
"if not market.empty:\n",
" market = market.set_index(\"exchange\")\n",
"\n",
" market[\"market_url\"] = market[\"market_url\"].apply(\n",
" lambda x: f'<a href=\"{x}\">{x}</a>'\n",
" )\n",
"\n",
" market"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1d6e76cb",
"metadata": {},
"outputs": [],
"source": [
"# all exchanges where loaded coin is listed\n",
"\n",
"ex = openbb.crypto.dd.ex(ticker)\n",
"if not ex.empty:\n",
" ex = ex.set_index(\"id\")\n",
" ex"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1fcdbc67",
"metadata": {},
"outputs": [],
"source": [
"# last trades\n",
"trades = openbb.crypto.dd.trades(symbol=ticker, exchange_id=\"binance\", to_symbol=\"USDT\")\n",
"if not trades.empty:\n",
" trades = trades.set_index(\"Date\")\n",
" trades"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "262d190a",
"metadata": {},
"outputs": [],
"source": [
"# order book\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 5), dpi=150)\n",
"openbb.crypto.dd.ob_chart(\n",
" symbol=ticker, exchange=\"binance\", to_symbol=\"USDT\", external_axes=[ax]\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"order_book = f.getvalue().decode(\"utf-8\")\n",
"order_book_raw = openbb.crypto.dd.ob(\n",
" symbol=ticker, exchange=\"binance\", to_symbol=\"USDT\"\n",
")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "95cdc32e",
"metadata": {},
"outputs": [],
"source": [
"order_book_raw"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "679d0d79",
"metadata": {},
"outputs": [],
"source": [
"# price and supply related metrics for loaded coin\n",
"\n",
"ps = openbb.crypto.dd.ps(ticker)\n",
"if not ps.empty:\n",
" ps = ps.set_index(\"Metric\")\n",
" ps"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "92e76d79",
"metadata": {},
"outputs": [],
"source": [
"# events\n",
"\n",
"events = openbb.crypto.dd.events(ticker)\n",
"\n",
"if not events.empty:\n",
" events = events.set_index(\"date\")\n",
"\n",
" events[\"link\"] = events[\"link\"].apply(lambda x: f'<a href=\"{x}\">{x}</a>')\n",
"\n",
"events"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a14130db",
"metadata": {},
"outputs": [],
"source": [
"# social media\n",
"\n",
"from openbb_terminal.cryptocurrency.due_diligence.pycoingecko_view import display_social\n",
"\n",
"display_social(ticker)\n",
"fig = plt.figure()\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"social = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8f89627f",
"metadata": {},
"outputs": [],
"source": [
"# tweets for loaded coin\n",
"\n",
"tweets = openbb.crypto.dd.twitter(ticker)\n",
"tweets"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9bb75443",
"metadata": {},
"outputs": [],
"source": [
"# github activity over time\n",
"\n",
"gh_data = openbb.crypto.dd.gh(symbol=ticker)\n",
"\n",
"if not gh_data.empty:\n",
" fig, ax = plt.subplots(figsize=(11, 5), dpi=150)\n",
" openbb.crypto.dd.gh_chart(symbol=ticker, external_axes=[ax])\n",
" fig.tight_layout()\n",
" f = io.BytesIO()\n",
" fig.savefig(f, format=\"svg\")\n",
" gh = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "markdown",
"id": "fcaa973d",
"metadata": {},
"source": [
"## TA\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "477317b4",
"metadata": {},
"outputs": [],
"source": [
"ticker_data = historical_data_one_year.copy()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7af3695c",
"metadata": {},
"outputs": [],
"source": [
"# simple moving average\n",
"ticker_data.index.names = [\"date\"]\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
"openbb.ta.ma_chart(\n",
" data=ticker_data[\"Close\"],\n",
" ma_type=\"SMA\",\n",
" symbol=ticker,\n",
" external_axes=[ax],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"sma = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5d5089fa",
"metadata": {},
"outputs": [],
"source": [
"# exponential moving average\n",
"fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
"openbb.ta.ma_chart(\n",
" data=ticker_data[\"Close\"],\n",
" ma_type=\"EMA\",\n",
" symbol=ticker,\n",
" external_axes=[ax],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"ema = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5facfbf4",
"metadata": {},
"outputs": [],
"source": [
"# zero lag exponential moving average\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
"openbb.ta.ma_chart(\n",
" data=ticker_data[\"Close\"],\n",
" ma_type=\"ZLMA\",\n",
" symbol=ticker,\n",
" external_axes=[ax],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"zlma = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "df54f7ad",
"metadata": {},
"outputs": [],
"source": [
"# commodity channel index\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)\n",
"openbb.ta.cci_chart(\n",
" data=ticker_data,\n",
" symbol=ticker,\n",
" external_axes=[ax1, ax2],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"cci = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f53469eb",
"metadata": {},
"outputs": [],
"source": [
"# moving average convergence/divergence\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)\n",
"openbb.ta.macd_chart(\n",
" data=ticker_data[\"Adj Close\"],\n",
" symbol=ticker,\n",
" external_axes=[ax1, ax2],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"macd = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "dd79e6b6",
"metadata": {},
"outputs": [],
"source": [
"# fisher transform\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 11), dpi=150)\n",
"ax3 = ax2.twinx()\n",
"openbb.ta.fisher_chart(\n",
" data=ticker_data,\n",
" symbol=ticker,\n",
" external_axes=[ax1, ax2, ax3],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"fisher = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b699e61f",
"metadata": {},
"outputs": [],
"source": [
"# aroon indicator\n",
"\n",
"fig, (ax1, ax2, ax3) = plt.subplots(nrows=3, ncols=1, figsize=(11, 11), dpi=150)\n",
"openbb.ta.aroon_chart(\n",
" data=ticker_data,\n",
" symbol=ticker,\n",
" external_axes=[ax1, ax2, ax3],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"aroon = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "79401027",
"metadata": {},
"outputs": [],
"source": [
"# bollinger bands\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
"openbb.ta.bbands_chart(\n",
" data=ticker_data,\n",
" symbol=ticker,\n",
" external_axes=[ax],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"bbands = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0b5e2949",
"metadata": {},
"outputs": [],
"source": [
"# fibonacci retracement\n",
"\n",
"fig, ax1 = plt.subplots(figsize=(11, 5), dpi=150)\n",
"ax2 = ax1.twinx()\n",
"openbb.ta.fib_chart(\n",
" data=ticker_data,\n",
" symbol=ticker,\n",
" external_axes=[ax1, ax2],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"fib = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "markdown",
"id": "48847a7f",
"metadata": {},
"source": [
"## QA"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e77b373b",
"metadata": {},
"outputs": [],
"source": [
"# summary\n",
"\n",
"summary = openbb.qa.summary(data=ticker_data)\n",
"summary"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3ecfc93e",
"metadata": {},
"outputs": [],
"source": [
"# normality statistics and tests\n",
"\n",
"# fig, _ = plt.subplots(figsize=(11, 3), dpi=150)\n",
"# openbb.qa.normality_chart(\n",
"# data=ticker_data,\n",
"# target=\"Close\",\n",
"# )\n",
"# fig.tight_layout()\n",
"# f = io.BytesIO()\n",
"# fig.savefig(f, format=\"svg\")\n",
"\n",
"normality = openbb.qa.normality(\n",
" data=ticker_data[\"Close\"],\n",
")\n",
"normality"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8abe96b0",
"metadata": {},
"outputs": [],
"source": [
"# box and whisker plot\n",
"\n",
"fig, ax = plt.subplots(figsize=(11, 3), dpi=150)\n",
"openbb.qa.bw(\n",
" symbol=ticker,\n",
" data=ticker_data,\n",
" target=\"Close\",\n",
" yearly=False,\n",
" external_axes=[ax],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"bw = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "66a7dccc",
"metadata": {},
"outputs": [],
"source": [
"# rolling mean and std deviation of prices\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)\n",
"openbb.qa.rolling(\n",
" symbol=ticker,\n",
" data=ticker_data,\n",
" target=\"Close\",\n",
" external_axes=[ax1, ax2],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"rolling = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d6b43dd7",
"metadata": {},
"outputs": [],
"source": [
"# rolling kurtosis of distribution of prices\n",
"\n",
"fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, figsize=(11, 5), dpi=150)\n",
"openbb.qa.kurtosis(\n",
" symbol=ticker,\n",
" data=ticker_data,\n",
" target=\"Close\",\n",
" external_axes=[ax1, ax2],\n",
")\n",
"fig.tight_layout()\n",
"f = io.BytesIO()\n",
"fig.savefig(f, format=\"svg\")\n",
"kurtosis = f.getvalue().decode(\"utf-8\")"
]
},
{
"cell_type": "markdown",
"id": "ac501a32-124d-4d21-aae1-a8d147bb1071",
"metadata": {},
"source": [
"## Render the report template to a file"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "abfe37e4-ea38-42c3-8fb5-7cceb233fb12",
"metadata": {},
"outputs": [],
"source": [
"body = \"\"\n",
"\n",
"img = (\n",
" str(REPOSITORY_DIRECTORY)\n",
" + \"/openbb_terminal/reports/templates/OpenBB_reports_logo.png\"\n",
")\n",
"floppy_disk_img = (\n",
" str(REPOSITORY_DIRECTORY) + \"/openbb_terminal/reports/templates/floppy-disc.png\"\n",
")\n",
"body += widgets.header(\n",
" img,\n",
" floppy_disk_img,\n",
" author,\n",
" report_date,\n",
" report_time,\n",
" report_timezone,\n",
" f\"<b>INVESTMENT RESEARCH REPORT:</b> {ticker}\",\n",
")\n",
"\n",
"body += widgets.tablinks(\n",
" [\n",
" \"SUMMARY\",\n",
" \"Due Diligence\",\n",
" \"Technical Analysis\",\n",
" \"Quantitative Analysis\",\n",
" ]\n",
")\n",
"\n",
"comment = \"\"\n",
"\n",
"# Summary tab\n",
"htmlcode = \"\"\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, \"Basic information about loaded coin\") + basic_info.to_html()]\n",
")\n",
"if not links.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Links\") + links.to_html(escape=False)])\n",
"\n",
"htmlcode += widgets.row([widgets.h(3, \"Published news\") + news.to_html(escape=False)])\n",
"# htmlcode += widgets.row([widgets.h(3, \"Altindex\")])\n",
"# htmlcode += widgets.row([altindex])\n",
"\n",
"htmlcode += widgets.row([widgets.h(3, \"Historical data\")])\n",
"for data in historical_data:\n",
" htmlcode += widgets.row([data])\n",
"\n",
"htmlcode += widgets.row([widgets.h(3, \"1-year historical data candlestick chart\")])\n",
"htmlcode += widgets.row([candle_one_year])\n",
"htmlcode += widgets.row([widgets.h(3, \"Sentiment analysis\")])\n",
"htmlcode += widgets.row([headlines])\n",
"# TODO: print rich table\n",
"# htmlcode += widgets.row([widgets.h(3, \"Quick performance\")])\n",
"# htmlcode += widgets.row([quick_performance])\n",
"body += widgets.add_tab(\"SUMMARY\", htmlcode)\n",
"\n",
"# # Due diligence tab\n",
"htmlcode = \"\"\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, f\"Trading pair info {ticker}/USDT\") + trading_pair_info.to_html()]\n",
")\n",
"if not mcapdom_df.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Market cap dominance\")])\n",
" htmlcode += widgets.row([mcapdom])\n",
"\n",
"if not roadmap_model.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Roadmap\") + roadmap_model.to_html()])\n",
" htmlcode += widgets.row([roadmap_view])\n",
"\n",
"if not tokenomics_model.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Tokenomics\") + tokenomics_model.to_html()])\n",
" htmlcode += widgets.row([tokenomics_view])\n",
"\n",
"if not fundraise_df.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Fundraising Details\")])\n",
" htmlcode += widgets.row([widgets.p(fundraise_info)])\n",
" htmlcode += widgets.row([fundraise_df.to_html()])\n",
"\n",
"if not ath.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"All time high\")])\n",
" htmlcode += widgets.row([ath.to_html()])\n",
"\n",
"if not atl.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"All time low\")])\n",
" htmlcode += widgets.row([atl.to_html()])\n",
"\n",
"htmlcode += widgets.row([widgets.h(3, \"All markets\")])\n",
"htmlcode += widgets.row([market.sample(n=20).sort_index().to_html(escape=False)])\n",
"htmlcode += widgets.row([widgets.h(3, \"Exchanges where loaded coin is listed\")])\n",
"htmlcode += widgets.row([ex.sample(n=20).sort_index().to_html()])\n",
"htmlcode += widgets.row([widgets.h(3, \"Last trades\")])\n",
"htmlcode += widgets.row([trades.tail(20).to_html()])\n",
"\n",
"if order_book_raw:\n",
" htmlcode += widgets.row([widgets.h(3, \"Order book\")])\n",
" htmlcode += widgets.row([order_book])\n",
"\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, \"Price and supply related metrics for loaded coin\")]\n",
")\n",
"htmlcode += widgets.row([ps.to_html()])\n",
"if not events.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Events\")])\n",
" htmlcode += widgets.row([events.to_html(escape=False)])\n",
"# TODO: print rich table\n",
"# htmlcode += widgets.row([widgets.h(3, \"Tweets for loaded coin\")])\n",
"# htmlcode += widgets.row([tweets])\n",
"# htmlcode += widgets.row([widgets.h(3, \"Social media\")])\n",
"# htmlcode += widgets.row([social.to_html()])\n",
"if not gh_data.empty:\n",
" htmlcode += widgets.row([widgets.h(3, \"Github activity over time\")])\n",
" htmlcode += widgets.row([gh])\n",
"else:\n",
" htmlcode += widgets.row([widgets.h(3, \"Github activity over time\")])\n",
" htmlcode += widgets.row([widgets.p(\"No data available.\")])\n",
"\n",
"body += widgets.add_tab(\"Due Diligence\", htmlcode)\n",
"\n",
"# Technical Analysis tab\n",
"htmlcode = \"\"\n",
"htmlcode = widgets.row([widgets.h(3, \"Simple moving average\")])\n",
"htmlcode += widgets.row([sma])\n",
"htmlcode += widgets.row([widgets.h(3, \"Exponential moving average\")])\n",
"htmlcode += widgets.row([ema])\n",
"htmlcode += widgets.row([widgets.h(3, \"Zero lag exponential moving average\")])\n",
"htmlcode += widgets.row([zlma])\n",
"htmlcode += widgets.row([widgets.h(3, \"Commodity channel index\")])\n",
"htmlcode += widgets.row([cci])\n",
"htmlcode += widgets.row([widgets.h(3, \"Moving average convergence/divergence\")])\n",
"htmlcode += widgets.row([macd])\n",
"htmlcode += widgets.row([widgets.h(3, \"Fisher transform\")])\n",
"htmlcode += widgets.row([fisher])\n",
"htmlcode += widgets.row([widgets.h(3, \"Aroon indicator\")])\n",
"htmlcode += widgets.row([aroon])\n",
"htmlcode += widgets.row([widgets.h(3, \"Bollinger bands\")])\n",
"htmlcode += widgets.row([bbands])\n",
"htmlcode += widgets.row([widgets.h(3, \"Fibonacci retracement\")])\n",
"htmlcode += widgets.row([fib])\n",
"body += widgets.add_tab(\"Technical Analysis\", htmlcode)\n",
"\n",
"# Quantitative Analysis tab\n",
"htmlcode = \"\"\n",
"htmlcode = widgets.row([widgets.h(3, \"Summary\") + summary.to_html()])\n",
"htmlcode += widgets.row(\n",
" [widgets.h(3, \"Normality statistics and tests\") + normality.to_html()]\n",
")\n",
"htmlcode += widgets.row([widgets.h(3, \"Box and whisker plot\")])\n",
"htmlcode += widgets.row([bw])\n",
"htmlcode += widgets.row([widgets.h(3, \"Rolling mean and std deviation of prices\")])\n",
"htmlcode += widgets.row([rolling])\n",
"htmlcode += widgets.row([widgets.h(3, \"Rolling kurtosis of distribution of prices\")])\n",
"htmlcode += widgets.row([kurtosis])\n",
"body += widgets.add_tab(\"Quantitative Analysis\", htmlcode)\n",
"\n",
"body += widgets.tab_clickable_and_save_evt()\n",
"report = widgets.html_report(title=report_name, stylesheet=stylesheet, body=body)\n",
"\n",
"# # to save the results\n",
"with open(report_name + \".html\", \"w\", encoding=\"utf-8\") as fh:\n",
" fh.write(report)"
]
}
],
"metadata": {
"celltoolbar": "Tags",
"kernelspec": {
"display_name": "Python 3.9.6 ('obb')",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.6"
},
"vscode": {
"interpreter": {
"hash": "cb66ba39c97f15743fbb79e204a841ea03600987d49579cfb0ffc8e8dd934c69"
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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