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diff --git a/REAMDE.md b/REAMDE.md
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+Stock Analyzer
+Project Overview
+This is a Flask-based stock analysis website that offers user registration, login, stock price querying, and visualization. It leverages Flask, SQLite, Bootstrap, Matplotlib, and the Alpha Vantage API.
+Directory Structure
+Copy
+StockAnalyzer/
+├── app.py
+├── templates/
+│ ├── base.html
+│ ├── index.html
+│ ├── login.html
+│ ├── predict_future.html
+│ └── register.html
+├── static/
+│ └── (images, CSS, JS files)
+└── README.md
+Installation and Launch
+1. Install Dependencies
+Ensure you have Python and pip installed. Then, install the required packages:
+bashCopy
+pip install flask pandas matplotlib requests sqlite3
+2. Get Alpha Vantage API Key
+Sign up at Alpha Vantage to get a free API key. Replace 'YOUR_API_KEY' in the get_stock_data_alpha_vantage function in app.py with your key.
+3. Start the Flask App
+Run the following command in the project root directory to start the Flask app:
+bashCopy
+python app.py
+The app will run locally, accessible at http://127.0.0.1:50582.
+4. Access the Website
+Open your browser and navigate to http://127.0.0.1:50582 to see the homepage. You can register, log in, query stock prices, and view visualizations.
+Features
+User registration and login.
+Stock price querying and visualization.
+Responsive design using Bootstrap.
+Immediate user feedback with Flask's flash function.
diff --git a/app.py b/app.py
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+import requests
+import pandas as pd
+import base64
+from flask import Flask, render_template, request, redirect, url_for, flash, session, send_file
+import matplotlib
+import matplotlib.pyplot as plt
+from io import BytesIO
+import sqlite3
+matplotlib.use("Agg")
+
+app = Flask(__name__)
+app.secret_key = 'secret_key'
+
+# init database
+def init_db():
+ conn = sqlite3.connect('users.db')
+ c = conn.cursor()
+ c.execute('''CREATE TABLE IF NOT EXISTS users (username TEXT PRIMARY KEY, password TEXT)''')
+ conn.commit()
+ conn.close()
+
+init_db()
+
+# connect database
+def get_db_connection():
+ conn = sqlite3.connect('users.db')
+ conn.row_factory = sqlite3.Row
+ return conn
+
+# sign up
+@app.route('/register', methods=['GET', 'POST'])
+def register():
+ if request.method == 'POST':
+ username = request.form['username']
+ password = request.form['password']
+
+ conn = get_db_connection()
+ c = conn.cursor()
+
+ # check whether the user exist
+ c.execute('SELECT * FROM users WHERE username = ?', (username,))
+ user = c.fetchone()
+
+ if user:
+ flash('Username already exists. Please choose a different one.', 'danger')
+ conn.close()
+ return redirect(url_for('register'))
+
+ # save into database
+ c.execute('INSERT INTO users (username, password) VALUES (?, ?)', (username, password))
+ conn.commit()
+ conn.close()
+
+ flash('Registration successful! You can now log in.', 'success')
+ return redirect(url_for('login'))
+
+ return render_template('register.html')
+
+# log in
+@app.route('/login', methods=['GET', 'POST'])
+def login():
+ if request.method == 'POST':
+ username = request.form['username']
+ password = request.form['password']
+
+ conn = get_db_connection()
+ c = conn.cursor()
+
+ # check user and password
+ c.execute('SELECT * FROM users WHERE username = ? AND password = ?', (username, password))
+ user = c.fetchone()
+
+ conn.close()
+
+ if user:
+ session['username'] = username
+ flash('Login successful!', 'success')
+ return redirect(url_for('index'))
+ else:
+ flash('Invalid username or password. Please try again.', 'danger')
+
+ return render_template('login.html')
+
+# log out
+@app.route('/logout')
+def logout():
+ session.pop('username', None)
+ flash('You have been logged out.', 'info')
+ return redirect(url_for('login'))
+
+# main page
+@app.route('/')
+def index():
+ if 'username' not in session:
+ flash('Please log in to access the dashboard.', 'warning')
+ return redirect(url_for('login'))
+ return render_template('index.html', username=session['username'])
+
+# plot stock
+@app.route('/predict_future', methods=['GET', 'POST'])
+def predict_future():
+ if 'username' not in session:
+ flash('Please log in to access this feature.', 'warning')
+ return redirect(url_for('login'))
+
+ img_base64 = None
+ stock_symbol = None
+ start_date = None
+ end_date = None
+
+ if request.method == 'POST':
+ stock_symbol = request.form['stock_symbol']
+ start_date = request.form['start_date']
+ end_date = request.form['end_date']
+
+ # get stock price data
+ try:
+ stock_data = get_stock_data_alpha_vantage(stock_symbol, start_date, end_date, 'VLP8G4UP0NW3RFAA')
+ print(f"Stock data for {stock_symbol} from {start_date} to {end_date}:")
+ print(stock_data)
+ except Exception as e:
+ flash(f'Error fetching stock data: {e}', 'danger')
+ return render_template('predict_future.html', stock_symbol=stock_symbol, start_date=start_date, end_date=end_date)
+
+ if stock_data.empty:
+ flash(f'No data available for {stock_symbol} from {start_date} to {end_date}.', 'warning')
+ return render_template('predict_future.html', stock_symbol=stock_symbol, start_date=start_date, end_date=end_date)
+
+ # plot
+ plt.figure(figsize=(10, 5))
+ plt.plot(stock_data.index.to_numpy(), stock_data['4. close'].to_numpy(), label='Close Price')
+ plt.title(f'Stock Price for {stock_symbol}')
+ plt.xlabel('Date')
+ plt.ylabel('Price')
+ plt.legend()
+ plt.grid(True)
+
+ img = BytesIO()
+ plt.savefig(img, format='png')
+ img.seek(0)
+ img_base64 = base64.b64encode(img.getvalue()).decode('utf8')
+ plt.close()
+
+ return render_template('predict_future.html', img_base64=img_base64, stock_symbol=stock_symbol, start_date=start_date, end_date=end_date)
+
+
+def get_stock_data_alpha_vantage(symbol, start_date, end_date, api_key):
+ url = f'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol={symbol}&apikey={api_key}&outputsize=full'
+ r = requests.get(url)
+ data = r.json()
+
+ # decode data
+ time_series = data.get('Time Series (Daily)', {})
+ df = pd.DataFrame.from_dict(time_series, orient='index', dtype=float)
+ df.index = pd.to_datetime(df.index)
+ df = df.sort_index()
+
+ # set date
+ df = df[(df.index >= start_date) & (df.index <= end_date)]
+
+ return df
+
+if __name__ == '__main__':
+ app.run(debug=True, port=50582)
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