


Guide to developing weather forecast applications based on Django Prophet
Weather prediction application development guide based on Django Prophet
Introduction:
Weather prediction is a very important part of people's daily life. Accurate weather prediction can Help people make decisions such as travel planning, crop planting, and energy dispatch. This article will introduce how to use Django Prophet to develop a weather forecast application that can predict future weather based on historical weather data.
1. Preparation work
Before starting development, we need to prepare the following environment and tools:
- Python 3.x
- Django
- Prophet
- Pandas
- Database (such as MySQL, SQLite, etc.)
2. Create a Django project
-
In Run the following command on the command line to create a new Django project:
django-admin startproject weather_forecast
-
Enter the project directory:
cd weather_forecast
-
Create a new Django application Program:
python manage.py startapp forecast
-
Add the application in the settings.py file of the project:
INSTALLED_APPS = [ ... 'forecast', ... ]
3. Define the data model
-
Define a Weather model in the models.py file of the forecast application, which contains fields such as date, minimum temperature, maximum temperature:
from django.db import models class Weather(models.Model): date = models.DateTimeField() min_temperature = models.FloatField() max_temperature = models.FloatField() humidity = models.FloatField() def __str__(self): return str(self.date)
-
In the command line Run the following command to create a database table:
python manage.py makemigrations python manage.py migrate
4. Import historical weather data
- Create a weather.csv file in the root directory of the project, Used to store historical weather data. The data should contain fields such as date, minimum temperature, maximum temperature, humidity, etc.
-
Write a view function that imports data in the views.py file of the forecast application:
from django.shortcuts import render import pandas as pd from .models import Weather def import_data(request): data = pd.read_csv('weather.csv') for index, row in data.iterrows(): weather = Weather( date=row['date'], min_temperature=row['min_temperature'], max_temperature=row['max_temperature'], humidity=row['humidity'] ) weather.save() return render(request, 'forecast/import_data.html')
-
Add a view function in the urls.py file of the project URL mapping of imported data:
from django.urls import path from forecast import views urlpatterns = [ ... path('import/', views.import_data, name='import_data'), ... ]
5. Use Prophet for weather forecast
-
Write a view in the views.py file of the forecast application View function to predict weather:
from django.shortcuts import render from .models import Weather from fbprophet import Prophet import pandas as pd def predict_weather(request): data = Weather.objects.all() df = pd.DataFrame(list(data.values())) df = df.rename(columns={'date': 'ds', 'max_temperature': 'y'}) model = Prophet() model.fit(df) future = model.make_future_dataframe(periods=365) forecast = model.predict(future) return render(request, 'forecast/predict_weather.html', {'forecast': forecast})
-
Add a URL mapping to predict weather in the project’s urls.py file:
from django.urls import path from forecast import views urlpatterns = [ ... path('predict/', views.predict_weather, name='predict_weather'), ... ]
6. Create a template file
-
Create an import_data.html file in the templates directory of the forecast application, a page for importing historical weather data:
<!DOCTYPE html> <html> <head> <title>Import Data</title> </head> <body> <h1 id="Import-Data">Import Data</h1> <form action="{% url 'import_data' %}" method="POST"> {% csrf_token %} <input type="submit" value="Import"> </form> </body> </html>
-
Create a predict_weather.html file in the templates directory of the forecast application to display the predicted weather results:
<!DOCTYPE html> <html> <head> <title>Predict Weather</title> </head> <body> <h1 id="Predicted-Weather">Predicted Weather</h1> <table> <thead> <tr> <th>Date</th> <th>Max Temperature (°C)</th> <th>Humidity</th> </tr> </thead> <tbody> {% for index, row in forecast.iterrows %} <tr> <td>{{ row['ds'] }}</td> <td>{{ row['yhat'] }}</td> <td>{{ row['humidity'] }}</td> </tr> {% endfor %} </tbody> </table> </body> </html>
7. Run the application
-
Run the following command in the command line to start the Django development server:
python manage.py runserver
- Visit http://localhost:8000/import/ in the browser to import historical weather data.
- Visit http://localhost:8000/predict/ for weather prediction, and the prediction results will be displayed on the page.
Conclusion:
This article introduces how to use Django Prophet to develop a weather forecast application. By importing historical weather data and using the Prophet model for prediction, we can predict future weather based on past weather conditions. I hope this article was helpful and gave you a deeper understanding of developing weather prediction applications.
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