{ "cells": [ { "cell_type": "markdown", "id": "306f1a67-4f1c-4aed-8f80-2a8458a1bce5", "metadata": {}, "source": [ "# Stock data analysis" ] }, { "cell_type": "code", "execution_count": null, "id": "4e2a9393-7767-488e-a8bf-27c12dca35bd", "metadata": {}, "outputs": [], "source": [ "import os\n", "import requests\n", "from dotenv import load_dotenv\n", "from bs4 import BeautifulSoup\n", "from IPython.display import Markdown, display\n", "from openai import OpenAI\n", "\n", "# If you get an error running this cell, then please head over to the troubleshooting notebook!" ] }, { "cell_type": "markdown", "id": "6900b2a8-6384-4316-8aaa-5e519fca4254", "metadata": {}, "source": [ "# Connecting to OpenAI" ] }, { "cell_type": "code", "execution_count": null, "id": "7b87cadb-d513-4303-baee-a37b6f938e4d", "metadata": {}, "outputs": [], "source": [ "# Load environment variables in a file called .env\n", "\n", "load_dotenv(override=True)\n", "api_key = os.getenv('OPENAI_API_KEY')\n", "\n", "# Check the key\n", "\n", "if not api_key:\n", " print(\"No API key was found - please head over to the troubleshooting notebook in this folder to identify & fix!\")\n", "elif not api_key.startswith(\"sk-proj-\"):\n", " print(\"An API key was found, but it doesn't start sk-proj-; please check you're using the right key - see troubleshooting notebook\")\n", "elif api_key.strip() != api_key:\n", " print(\"An API key was found, but it looks like it might have space or tab characters at the start or end - please remove them - see troubleshooting notebook\")\n", "else:\n", " print(\"API key found and looks good so far!\")\n" ] }, { "cell_type": "code", "execution_count": null, "id": "019974d9-f3ad-4a8a-b5f9-0a3719aea2d3", "metadata": {}, "outputs": [], "source": [ "openai = OpenAI()" ] }, { "cell_type": "code", "execution_count": null, "id": "51d42a08-188e-4c56-9578-47cd549bd1d8", "metadata": {}, "outputs": [], "source": [ "from urllib.parse import urlencode\n", "import datetime\n", "\n", "headers = {\n", " \"User-Agent\": \"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36\"\n", "}" ] }, { "cell_type": "code", "execution_count": null, "id": "682eff74-55c4-4d4b-b267-703edbc293c7", "metadata": {}, "outputs": [], "source": [ "class YahooFinanceWebsite:\n", " def __init__(self, stock_symbol):\n", " \"\"\"\n", " Create this Website object from the given url using the BeautifulSoup library\n", " \"\"\"\n", " self.stock_symbol = stock_symbol.upper()\n", "\n", " def __build_url(self, params):\n", " base_url = f\"https://finance.yahoo.com/quote/{self.stock_symbol}/history/\"\n", " query_string = urlencode(params)\n", " return f\"{base_url}?{query_string}\"\n", "\n", " def get_stock_data(self):\n", " datetime_now = datetime.datetime.now()\n", " datetime_year_ago = datetime_now - datetime.timedelta(days=365)\n", " params = {\"frequency\": \"1wk\", \"period1\": datetime_year_ago.timestamp(), \"period2\": datetime_now.timestamp()}\n", " url = self.__build_url(params)\n", " response = requests.get(url, headers=headers)\n", "\n", " soup = BeautifulSoup(response.content, 'html.parser')\n", " \n", " title = soup.title.string if soup.title else \"No title found\"\n", " for irrelevant in soup.body([\"script\", \"style\", \"img\", \"input\"]):\n", " irrelevant.decompose()\n", "\n", " html_table_data = soup.find(\"table\")\n", "\n", " return title, html_table_data" ] }, { "cell_type": "code", "execution_count": null, "id": "70b8d7e7-51e7-4392-9b85-9ac9f67a907c", "metadata": {}, "outputs": [], "source": [ "def build_stock_analysis_prompt(stock_symbol, title, stock_table_data):\n", " sys_prompt = r\"\"\"You are an assistant that analyzes the contents of HTML formated table that contains data on a specific stock.\n", " The HTML table contains the date, open price, close price, low and highs aggregated for every week over one year timeframe.\n", " Ignoring text, tags or html attributes that might be navigation related. \n", " Respond in Markdown format\"\"\"\n", " \n", " user_prompt = f\"The data provided below in the HTML table format for {stock_symbol} from the Yahoo Finances.\\\n", " Make the explaination easy enough for a newbie to understand. \\\n", " Analyze and Summarize the trends on this stock:\\n{stock_table_data}\\n\\n\\\n", " Also, calculate the total returns in percentage one could have expected over this period.\"\n", " \n", " return [\n", " {\"role\": \"system\", \"content\": sys_prompt},\n", " {\"role\": \"user\", \"content\": user_prompt}\n", " ]" ] }, { "cell_type": "code", "execution_count": null, "id": "de514421-4cc8-4881-85b4-97f03e94c589", "metadata": {}, "outputs": [], "source": [ "def analyze_stock_trends(stock_symbol):\n", " stock_data_page = YahooFinanceWebsite(stock_symbol)\n", " title, stock_table_data = stock_data_page.get_stock_data()\n", " response = openai.chat.completions.create(\n", " model = \"gpt-4o-mini\",\n", " messages = build_stock_analysis_prompt(stock_symbol, title, stock_table_data)\n", " )\n", " return response.choices[0].message.content\n", "\n", "def display_analysis(stock_symbol):\n", " display(Markdown(analyze_stock_trends(stock_symbol)))" ] }, { "cell_type": "code", "execution_count": null, "id": "41acc36f-484a-4257-a240-cf27520e7396", "metadata": {}, "outputs": [], "source": [ "display_analysis(\"GOOG\")" ] }, { "cell_type": "code", "execution_count": null, "id": "7e09541f-bbc4-4cf3-a1ef-9ed5e1b718e4", "metadata": {}, "outputs": [], "source": [ "display_analysis(\"PFE\")" ] }, { "cell_type": "code", "execution_count": null, "id": "e6af9395-0c5c-4265-a309-baba786bfa71", "metadata": {}, "outputs": [], "source": [ "display_analysis(\"AAPL\")" ] }, { "cell_type": "code", "execution_count": null, "id": "afe4f6d1-a6ea-44b5-81ae-8e756cfc0d84", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.11" } }, "nbformat": 4, "nbformat_minor": 5 }