Skip to content
Send Slack messages with Python (template)
  • AI Chat
  • Code
  • Report
  • Send Slack messages with Python

    Business Logic

    Let's write some Python code that tracks the total value of an imaginary portfolio of tech stocks. Feel free to swap this out with Python code for your project!

    # package imports
    import pandas as pd
    import yfinance as yf
    from datetime import datetime, timedelta
    import plotly.graph_objs as go
    import plotly.express as px
    my_portfolio = {
        'AAPL': 18,
        'AMZN': 15,
        'MSFT': 7,
        'META': 10,
    }
    end_date = datetime.today().strftime('%Y-%m-%d')
    start_date = (datetime.today() - timedelta(days=180)).strftime('%Y-%m-%d')
    
    def get_historical_data(ticker, start_date, end_date, quantity):
        historical_data = yf.download(ticker, start=start_date, end=end_date, progress=False)*quantity
        historical_data.rename(columns={'Close': ticker}, inplace=True)  # Corrected line
        return historical_data[ticker]  # Corrected line
    
    series = [ get_historical_data(stock, start_date, end_date, quantity) for stock, quantity in my_portfolio.items() ]
    
    # Combine all data in one data frame
    portfolio_df = pd.concat(series, axis=1)
    portfolio_df
    traces = [ go.Scatter(x=portfolio_df.index, y=portfolio_df[stock], mode='lines', name=stock) for stock in portfolio_df.columns]
    layout = go.Layout(title='My stock portfolio over time', xaxis=dict(title='Date'), yaxis=dict(title='Stock Value'))
    go.Figure(data=traces, layout=layout)
    portfolio_df['Total'] = portfolio_df.sum(axis=1)
    px.line(portfolio_df, x=portfolio_df.index, y='Total', title='Total Portfolio Value Over Time')
    # Calculate the latest total value of the portfolio
    latest_total = portfolio_df['Total'].iloc[-1]
    
    # Calculate the percentage change compared to last week
    last_week_total = portfolio_df['Total'].iloc[-8]
    percentage_change_week = ((latest_total - last_week_total) / last_week_total) * 100
    
    # Calculate the percentage change compared to last month
    last_month_total = portfolio_df['Total'].iloc[-30]
    percentage_change_month = ((latest_total - last_month_total) / last_month_total) * 100
    
    # Print the f-string with the information
    message = "\n".join([
        f"Total value of my portfolio on {portfolio_df.index[-1]:%B %d, %Y} is ${latest_total:,.2f}.",
        f"It's {'up' if percentage_change_week >= 0 else 'down'} {percentage_change_week:.2f}% compared to last week.",
        f"It's {'up' if percentage_change_month >= 0 else 'down'} {percentage_change_month:.2f}% compared to last month.",
    ])
    
    print(message)

    Sending the Slack message

    import os
    from slack_sdk import WebClient
    
    # Append a link to the workbook
    message += f"\nFor the full analysis, check <https://www.datacamp.com/datalab/w/{os.environ.get('DL_WORKBOOK_ID', 'invalid')}/edit|this workbook> (updates daily)"
    
    # Send the Slack message
    client = WebClient(token=os.environ["SLACK_TOKEN"])
    client.chat_postMessage(channel="bot-updates", 
                            text=message, 
                            username="Bot User")