Building a Web App with ChatGPT: A Python Coding Journey

Table of Contents

1. Introduction
2. Building the Web App
   • Setting up Flask and Python
   • Defining Routes and Functions
   • Scraping and Wrangling Data
   • Creating HTML Templates
   • Adding CSS Styling
3. Improving the User Interface
   • Centering Content and Adding Line Breaks
   • Adding a Logo
   • Modifying Logo Size
4. Data Extraction and CSV Generation
   • Extracting Data from Amazon
   • Storing Data in CSV Files
   • Comparing Prices from Previous Data
5. Filtering and Displaying Products
   • Implementing Filters by Price and Name
   • Displaying the List of Products

Building an Amazon Price Tracker Web App with Python and Flask

In this article, we will walk through the process of building a web app that tracks the prices of Amazon products using Python and Flask. This app allows users to enter the name of a product and the number of pages they want to scrape. The app then retrieves the data, compares the prices with previous data sets, and displays the products with their respective price changes.

1. Introduction

Tracking the prices of products on Amazon can be a useful way to find the best deals and make informed purchasing decisions. With the help of Python and Flask, we can automate this process and Create a web app that simplifies the task.

2. Building the Web App

Setting up Flask and Python

To start, we need to set up Flask and Python on our development environment. Flask is a micro web framework that allows us to build web applications easily. Python is the programming language we will use for this project.

Defining Routes and Functions

Once Flask and Python are set up, we can define the routes and functions that will handle the requests. This includes defining the search and results functions, which will render the HTML pages for searching and displaying the products.

Scraping and Wrangling Data

To retrieve the data from Amazon, we will use web scraping techniques. We will write a function that extracts the necessary data, such as the product name, image, and price. We will also use the pandas library to wrangle the data and prepare it for display.

Creating HTML Templates

The web app will require two HTML templates: one for the search page and another for the results page. The search page will include inputs for the product name and number of pages, while the results page will display the list of products with their price changes.

Adding CSS Styling

To enhance the user interface of our web app, we will add some CSS styling. This includes centering the content, adding line breaks, and incorporating a logo. We will modify the HTML code generated by Flask and add CSS code to achieve the desired styling.

3. Improving the User Interface

Centering Content and Adding Line Breaks

To improve the layout of the search page, we will center the content using CSS. This will make the inputs more visually appealing. Additionally, we will add line breaks between the inputs to improve readability.

Adding a Logo

To give the web app a professional look, we will add a logo to the top of the page. We will download the logo image and place it in the static folder. Then, we will update the HTML code to display the logo using the appropriate HTML tags and attributes.

Modifying Logo Size

After adding the logo, we might need to adjust its size to ensure it fits nicely within the page. We will use CSS to customize the size of the logo image and make it visually pleasing.

4. Data Extraction and CSV Generation

Extracting Data from Amazon

To extract data from Amazon, we will revisit our web scraping techniques. We will create a function that takes the product name, number of pages, and Current date as inputs. This function will scrape the data from Amazon and return the necessary information.

Storing Data in CSV Files

To compare the prices of products with previous data sets, we need to store the data in CSV files. We will use the current date as part of the CSV file name to keep track of the data over time. Each time we scrape Amazon, we will update the CSV file with the new data.

Comparing Prices from Previous Data

To calculate the price change for each product, we need to compare the current prices with the prices from previous data sets. We will use pandas to Read the CSV files, clean the data, and perform the necessary calculations. The resulting price changes will be displayed alongside the product information.

5. Filtering and Displaying Products

Implementing Filters by Price and Name

To enhance the user experience, we can add filters to the web app. Users can specify a price range or filter products by name. We will modify the code to handle these filters and display the filtered products accordingly.

Displaying the List of Products

The final step is to display the list of products on the results page. We will modify the HTML code to include the product list and update the app.py file to retrieve and pass the necessary data. This will ensure that users can easily view and analyze the scraped products.

Throughout this article, we have covered the entire process of building an Amazon price tracker web app using Python and Flask. From setting up the development environment to implementing filters and displaying the data, we have provided a comprehensive guide. By following these steps, You can create your own price tracking web app and make informed purchasing decisions on Amazon.

FAQ

Q: Can I scrape any product on Amazon using this web app? A: Yes, this web app allows you to scrape any product on Amazon by entering the name of the product and the number of pages to scrape.

Q: Are the filters case-sensitive? A: No, the filters for product names are not case-sensitive. You can enter lowercase or uppercase letters without affecting the filter results.

Q: How often should I scrape Amazon to get accurate price changes? A: The frequency of scraping depends on your needs. If you want up-to-date price changes, you can scrape Amazon daily or as frequently as desired. However, keep in mind that excessive scraping may violate Amazon's terms of service.