In your working directory, you can create the following file structure (Kindly ignore LICENSE and README.md since these files might be required if you host the project files on GitHub).

• app.py will be our main file.
• requirements.txt is created so that other developers can install the correct versions of the required Python packages to run your Python code.
• The runtime.txt contains the version of python we need , when deploying to Heroku.
• The Procfile is created for deployment using Heroku. It is not needed to run the app locally.
• setup.sh will contain commands which will be executed on the Heroku platform.

Install necessary libraries using pip package installer. It is recommended to use the following packages/libraries for this project.

streamlit==0.63.1
matplotlib==3.2.2
DateTime==4.3
pyowm==3.0.0

pip install lib1 lib2 lib3

• Import relevant libraries as shown below:

  import os
  import pytz
  import pyowm
  import streamlit as st
  from matplotlib import dates
  from datetime import datetime
  from matplotlib import pyplot as plt
  

• Get the api key from the OpenWeatherMap website and use it as follows:

  owm=pyowm.OWM('your-api-key')
  mgr=owm.weather_manager()
  

• For the streamlit frontend we will need a title and a placeholder text:

  st.title("5 Day Weather Forecast")
  st.write("### Write the name of a City and select the Temperature Unit and Graph Type from the sidebar")
  

• Now we will input the city name and using store it in a variable called place

  place=st.text_input("NAME OF THE CITY :", "")
  
  if place == None:
      st.write("Input a CITY!")
  

• Now we will create two selection forms as follows :

  unit=st.selectbox("Select Temperature Unit",("Celsius","Fahrenheit"))
  
  g_type=st.selectbox("Select Graph Type",("Line Graph","Bar Graph"))
  

• To run the code use the following command :

  streamlit run <filename>
  

• The OpenWeatherMap free tier gives you access to 5 day forecasts. The forecasts contain the weather data in three-hour intervals.

• The methods for retrieving the forecast are:

  • forecast_at_place('Los Angeles, US', '3h')
  • forecast_at_id(5391959, '3h')
  • forecast_at_coords(lat=37.774929, lon=-122.419418, interval='3h')

• Create an OWM object.

• Next we get a WeatherManager instance.

• Retrieve a 5 day forecast data with intervals of 3 hours.

• Create 2 functions one for bar chart and the other for line chart.
• Pass the days , minimum temperature and maximum temperature as parameters.
• Use the plt.bar(days,temp_min) and plt.bar(days,temp_max) for plotting minimum and maximum temperatures on the bar graph respectively.
• Similarly use the plt.plot for the line chart.
• At this point the plot should showing the forecast for the next five days.

• Python Open Weather Map provides methods to check for certain weather conditions in a forecast. The following methods are available:

  will_have_rain()
  will_have_clear()
  will_have_fog()
  will_have_clouds()
  will_have_snow()
  will_have_storm()
  will_have_tornado()
  will_have_hurricane()
  

• For example, the following snippet checks if there is rain in this week's forecast for LA:

  forecaster = mgr.forecast_at_place('Los Angeles, US', '3h')
  print(forecaster.will_have_rain())
  

• Knowing what time the sun rises and sets is great information to have when planning your day! Let's see how we can get these times using PyOWM.
  
  

  sunrise_time(): Returns the GMT time of sunrise
  
  sunset_time(): Returns the GMT time of sunset
  
  

  For example :

  print(weather.sunrise_time())
  

• PyOWM gives you access to other weather information in addition to the temperature. Some of the information you can get about is:

  • wind

  • clouds

  • humidity
    

    The values in the clouds and humidity properties are of type int. The values represents the percentage of cloud cover and the humidity percentage respectively. For example, to print the humidity after obtaining a Weather object, you could write:

    humidity = weather.humidity
    print(f'The current humidity is {humidity}%')
    

• All we have to do is to integrate all these functions into the main file.

• Create a Heroku account.

• Run pip freeze > requirements.txt in the terminal. This creates a text file containing all our dependencies.

• Create a Procfile in the working directory. This file will contain commands to be run on the Heroku cloud.

• Run sudo snap install --classic heroku on terminal to install the Heroku CLI.

• In the Heroku terminal, run the commands below:

  heroku create unique-name-here
  git add .
  git commit -m 'Initial app template'
  git push heroku master