Web Scraping with Selenium in Python
Selenium is a collection of tools used for browser automation.
These tools are primarily used for automating tests on a web application. For example ensuring the registration form is
correctly storing information in a database, the payment system is secure, clicking a button generates
the right prompt, meausring performance or checking the application is compatible with other browsers.
Selenium's toolkit efficiently helps to test the functionality of web applications and to ensure
everything works as expected.
For this project I utilized Selenium's WebDriver API tool to scrape product information from Amazon. The Webdriver is used
mainly for automating tests on the UI component of an application. So, in this project I wrote a script that
would use this tool to automatically navigate to Amazon, search for a product, extract the brands and store the
information in a Dictionary. For this example I decided to search for Basketball Shoes. In the media the API is going through
the first few pages and obtaining each products name and brand, using their corresponding XPATH, which is then eventually stored in a
Dictionary.
Email Administration Application with Java
For this project I built a employee registration and login system. Idea is that an
employee would first open the application, fill out a registration form with their name
email address and password, then click on the sign up button which would then send
their information to a connected database using SQL queries.
After registering an account an employee can now complete the login form, which authenticates users by finding matching details in the database. As shown in the
media I first attempt to login with the wrong details which doesn't match any entries in the database
and I recieve a prompt that informs me the details are
incorrect. I then retry with the correct details which produces a pop-up message informing me I have now
successfully logged in.
Handling Financial Services with Square APIs in Python
Square is an organization that provides the technological infrastructure and services for a business to
manage all its commercial operations. For example, inventory management, tracking sales,
handling orders and managing business finances. Square also provides a collection of APIs for developers to create
different solutions and applications depending on their businesses needs.
For this project I used Square APIs to simulate handling different tasks for a Square Seller. One example is
using the Merchants API. Every registered Square seller provides information when they create a Square account, such as
the name of their business, which country they are operating in and their language preferences. Using the 'retrive_merchant' endpoint of this API and a Merchant's ID,
I could then be able to retrieve core information about an organization.
Another example using the Locations API. This API helps to manage all the locations a buisness operates in.
So with this API I could create, retrieve and update sellers locations using respective endpoints. In the media I created pseudo locations
a seller might operate in.
Using OpenAIs API for Image Generation and Variation in JavaScript
OpenAI is a AI research company with a mission to create AI technologies that is safe and beneficial
for humanity. The organization works on a range of AI projects, including natural language processing,
robotics and generative models. Some of their most notable work include ChatGPT, DALL-E and the OpenAI Gym, which
serves as an enviroment to create and develop learning agents.
OpenAI provides APIs each with different endpoints to allow developers to use the technology for different tasks
and applications. For this project I used the Image API to create a program that generates a image based on
a provided prompt and then create a new varied image based on that image. The API works in tandem with DALL-E, a generative AI helping to
produce the images.
The first prompt I provided is 'a Dog in the matrix' and the AI generated the corresponding image, then I ran
that image through the variation endpoint twice which produced the next two images after that. The second sequence of images follows the same steps and
was generated from the prompt 'a dinosaur going to work'.