diff --git a/week1/community-contributions/day-1-Stock-data-analysis.ipynb b/week1/community-contributions/day-1-Stock-data-analysis.ipynb new file mode 100644 index 0000000..1c3a39f --- /dev/null +++ b/week1/community-contributions/day-1-Stock-data-analysis.ipynb @@ -0,0 +1,226 @@ +{ + "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 +}