From 164caa833d0ebed7aaf9cf7f10f0e402b5305518 Mon Sep 17 00:00:00 2001 From: Kunal Brahma Date: Fri, 1 Aug 2025 17:38:58 +0530 Subject: [PATCH] Add Bitcoin market prediction notebook to community contributions --- .../day1-BitcoinMarketPrediction.ipynb | 230 ++++++++++++++++++ 1 file changed, 230 insertions(+) create mode 100644 week1/community-contributions/day1-BitcoinMarketPrediction.ipynb diff --git a/week1/community-contributions/day1-BitcoinMarketPrediction.ipynb b/week1/community-contributions/day1-BitcoinMarketPrediction.ipynb new file mode 100644 index 0000000..dd5265d --- /dev/null +++ b/week1/community-contributions/day1-BitcoinMarketPrediction.ipynb @@ -0,0 +1,230 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "7db973a2-c95e-4939-a0d7-b54edec4d2cf", + "metadata": {}, + "source": [ + "# Bitcoin Market Prediction uisng CoinmarketCap\n", + "An AI-powered project using historical CoinMarketCap data to predict Bitcoin price trends and offer actionable insights for traders." + ] + }, + { + "cell_type": "markdown", + "id": "b792b517-bbc8-4e2c-bff2-45fad1a784dc", + "metadata": {}, + "source": [ + "## Imports" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "51523d62-825a-4a15-aec2-7c910beb5fda", + "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" + ] + }, + { + "cell_type": "markdown", + "id": "2e3816b0-4557-4225-bfb9-9933d813548a", + "metadata": {}, + "source": [ + "## .env configuration" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "02be59e7-01cc-41b5-88c3-a47860570078", + "metadata": {}, + "outputs": [], + "source": [ + "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!\")" + ] + }, + { + "cell_type": "markdown", + "id": "3fc32555-ea4e-45fe-ad44-9dbf4441afd1", + "metadata": {}, + "source": [ + "### This line creates an authenticated OpenAI client instance, used to make API requests in your code." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0845c687-6610-4f83-89e8-fb94bc47ddd2", + "metadata": {}, + "outputs": [], + "source": [ + "from openai import OpenAI\n", + "openai = OpenAI(api_key=api_key)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d140db1a-dd72-4986-8f38-09f8d8f97b00", + "metadata": {}, + "outputs": [], + "source": [ + "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", + "}\n", + "\n", + "class Website:\n", + "\n", + " def __init__(self, url):\n", + " \"\"\"\n", + " Create this Website object from the given url using the BeautifulSoup library\n", + " \"\"\"\n", + " self.url = url\n", + " response = requests.get(url, headers=headers)\n", + " soup = BeautifulSoup(response.content, 'html.parser')\n", + " self.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", + " self.text = soup.body.get_text(separator=\"\\n\", strip=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fdc96768-94a8-4a08-acf1-32a62b699b94", + "metadata": {}, + "outputs": [], + "source": [ + "system_prompt = \"\"\"\n", + "You are an intelligent assistant specialized in Bitcoin market prediction. Your tasks are:\n", + "\n", + "- Collect, preprocess, and analyze historical Bitcoin price and volume data sourced from CoinMarketCap historical data tables or API.\n", + "- Extract relevant time series and technical features from OHLC (open, high, low, close) and volume data.\n", + "- Use machine learning or statistical models to forecast future Bitcoin price trends.\n", + "- Output clear, concise, and actionable insights, focusing on predicted price direction and potential trading signals.\n", + "- Ensure all data collection respects CoinMarketCap’s terms of service.\n", + "- Present findings in user-friendly language, explaining prediction confidence and market risks.\n", + "- Continuously improve prediction accuracy through back-testing on updated datasets.\n", + "\n", + "\"\"\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7d39e983-5b65-4de1-bdf0-e4239c3eb03f", + "metadata": {}, + "outputs": [], + "source": [ + "def user_prompt_for(website):\n", + " user_prompt = f\"You are analyzing historical Bitcoin market data from the webpage titled '{website.title}'.\\n\"\n", + " user_prompt += (\n", + " \"The data includes daily open, high, low, close prices, trading volume, \"\n", + " \"and market capitalization presented in a table format.\\n\"\n", + " \"Please provide a clear and concise analysis in Markdown format, focusing on recent trends, \"\n", + " \"price movements, volatility, and any insights that could help forecast Bitcoin price directions.\\n\"\n", + " \"If possible, include technical indicators, significant patterns, or notable market events mentioned in the data.\\n\\n\"\n", + " )\n", + " user_prompt += website.text\n", + " return user_prompt\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d3d41ed3-4753-49f2-b51f-37e8be43102c", + "metadata": {}, + "outputs": [], + "source": [ + "def messages_for(website):\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_prompt},\n", + " {\"role\": \"user\", \"content\": user_prompt_for(website)}\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0eb99fcf-75a2-41b8-bf53-568f94264438", + "metadata": {}, + "outputs": [], + "source": [ + "# And now: call the OpenAI API. You will get very familiar with this!\n", + "\n", + "def summarize(url):\n", + " website = Website(url)\n", + " response = openai.chat.completions.create(\n", + " model = \"gpt-4o-mini\",\n", + " messages = messages_for(website)\n", + " )\n", + " return response.choices[0].message.content\n", + "\n", + "# A function to display this nicely in the Jupyter output, using markdown\n", + "\n", + "def display_summary(summary): \n", + " display(Markdown(summary))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a0e57921-5132-40c6-834b-03a11a96425c", + "metadata": {}, + "outputs": [], + "source": [ + "url = \"https://coinmarketcap.com/currencies/bitcoin/historical-data/3\"\n", + "summary = summarize(url)\n", + "display_summary(summary)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "19d9b69a-6493-402d-a0b4-a486c322c816", + "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": "3.11.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}