How To Build A Tracker In Python To Monitor Prices
In the fast-paced world of eCommerce, keeping track of prices is essential for both buyers and sellers. Prices can change quickly, making it challenging to keep up with the latest deals and trends. Web scraping, the process of extracting data from websites automatically, is a powerful tool that you can use to monitor prices across multiple websites in real time, giving you an edge over competitors that rely on manual price checking.
Table of Contents
Web scraping eliminates the need for manually entering price changes into a database or spreadsheet and provides better insight into price changes between different retailers and how they may impact your bottom line. Learning how to build your own price tracker can give you an edge in the market.
Let’s explore how to build a tracker with Python, a popular programming language. Whether you are a buyer looking for the best deals or a seller wanting to stay ahead of the competition, mastering eCommerce with a custom price tracker can help you make informed decisions and save money.
Custom-built vs. Outsourced Price Trackers
The decision to custom-build a Python price tracker or outsource the build to a professional depends on an array of factors, including your budget, technical expertise, and the project’s complexity.
Custom-building a Python price tracker can be a cost-effective option for those who have some programming knowledge or are willing to invest the time to learn. By building the price tracker yourself, you have complete control over the features and functionality and can customize it to fit your specific needs.
You can update and modify the price tracker as your business evolves without relying on external contractors or third-party software. When you outsource, you risk not getting the desired results if you choose the wrong partner or third-party solution.
However, building a price tracker from scratch can be time-consuming and requires some technical expertise. If you lack the necessary programming skills, you may need to invest significant time and resources to learn Python and its associated libraries. There may be unforeseen challenges or roadblocks that could slow down development or require outside assistance.
Why Build a Python Price Tracker?
Custom trackers are better than price tracker software because they’re fully customizable and are handy tools for many reasons. Here are some of the benefits of a shopping price tracker:
- Automated price monitoring: A Python price tracker can scan the prices of products sold by competitors. This can save significant time and effort compared to manually checking the prices on different websites.
- Competitive pricing: With a competitor price tracking tool, you can adjust your prices to be more competitive. This can help attract more customers and increase sales.
- Identifying trends: Price trackers can help you identify trends in the market, such as seasonal changes in demand or price fluctuations due to external factors. This information can help you make informed decisions about pricing and inventory management.
- Improved profit margins: You can improve your profit margins by tracking prices and identifying opportunities to lower costs or increase prices. This can be especially important in highly competitive markets where profit margins can be slim.
- Real-time data analysis: Python-based price trackers can provide real-time data on product prices and market trends, allowing businesses to make quick decisions based on the most up-to-date information.
- Data visualization: Python provides powerful data visualization tools to help businesses better understand price trends and make decisions based on visual data analysis. You can use Python to program a target price history tracker that identifies optimal price points for certain products over time.
Now that you see the value in a Python price tracker, let’s review how to create your own.
Getting Started: Setting Up Your Python Environment
Installing Python and the necessary libraries and modules is the first step of building a price tracker in Python, so make sure you have them downloaded and installed on your computer.
Python libraries allow you to collect data, clean and transform it into usable formats, and create visualizations to understand the data better. You’ll be able to quickly analyze large amounts of data, identify patterns and trends, and make informed decisions about pricing strategies.
One library you may find useful is Pandas. This powerful Python library can help you analyze scraped data and identify price trends. It provides an easy-to-use API for manipulating webpages, allowing you to quickly and easily scrape product data from multiple sources in real time.
Matplotlib and Seaborn are also powerful Python libraries that can be used to visualize price trends over time. Matplotlib offers an easy-to-use API for plotting graphs and charts, allowing you to quickly identify how prices have changed between different retailers. Seaborn provides a range of features, such as heat maps, which make it simple to compare how prices vary across multiple websites simultaneously.
You’ll also need to create a virtual environment for your project to keep all of the dependencies used by your project isolated from other projects and their dependencies so they don’t conflict.
To create a virtual environment, you must install Python’s built-in .venv package on your computer. Once installed, you can use the command line to create a new directory to store your project files and activate the virtual environment. This ensures that any packages or libraries installed during development are kept separate from those on your system’s main Python installation. Then you can begin coding the actual price tracking script.
Gathering and Storing Price Data
You will need to select an appropriate data source for the price information. You can either choose from APIs provided by service providers or use web scraping techniques to gather the data from public sources. For instance, you can use Requests to make an HTTP request to the target website and get the HTML page.
From there, you can use a module such as BeautifulSoup to parse the page and extract the information you need, like prices. Once the data is collected, you will need to store it in a database, such as a Pandas DataFrame.
The database you choose will depend on how much data needs to be stored, how quickly it needs to be accessed, and how often it needs to be updated. Choosing the right database system for your price-tracking software will ensure your product remains up-to-date with retail prices worldwide. Some cloud-based storage solutions offer more cost savings, scalability, and security than traditional systems and are worth looking into.
Once you have chosen a suitable system, you must configure the connection properly so that any product data scraped from websites can be safely stored. Designing an appropriate schema will help organize your tracked prices into meaningful categories for easy retrieval later on.
Reviewing Scraped Price Data and Setting Alerts and Notifications
The last step is to create a script that retrieves the values from the database and compares them with predefined thresholds before alerting you about any changes. Don’t forget to set up automated tasks that run regularly to ensure your price tracker is up-to-date.
You can easily create alerts when certain criteria, such as price drops, are met. By analyzing the data scraped from multiple websites, the script can quickly identify how prices have changed between different retailers over time. This allows you to set up notifications if a certain price threshold has been breached or a specific product is on sale.
Automated alerts will ensure you are always aware of how prices are changing so that you can take advantage of any promotional periods or capitalize on sudden price drops. Your Python price-tracking script can even set up email or SMS notifications.
Ready To Discover the Easiest Price Tracking Solution on the Market?
Price tracking is essential for any business looking to stay competitive in a volatile market. They need access to high-quality data sources and must be able to process this data quickly and accurately. Learning how to build a price tracker can come in handy, but it can also be complicated, requiring sophisticated technology and accurate analytics. And if you are on a tight budget, you may want to find a different option — and that doesn’t always mean building it yourself.
Scraping Robot is the perfect solution for anyone looking to quickly and affordably access web scraping services. With 15 prebuilt modules, Scraping Robot makes it easy to extract data from websites with no blocks, captchas, proxy management, or browser scaling. Plus, you can sign up today and claim 5,000 free scrapes today!
The information contained within this article, including information posted by official staff, guest-submitted material, message board postings, or other third-party material is presented solely for the purposes of education and furtherance of the knowledge of the reader. All trademarks used in this publication are hereby acknowledged as the property of their respective owners.
