Unlock the potential of Python data scraping, a powerful technique to programmatically access data directly from websites. Gain insights into the unique challenges, ethical considerations, and practical applications of scraping website content.
Key Insights
- Data scraping involves programmatically retrieving data directly from the HTML and text of third-party websites, differing significantly from accessing data through structured API servers.
- Unique challenges in data scraping include parsing HTML-formatted data, exploring data structures, and ensuring compliance with ethical standards and legal licenses.
- While typically permissible, it is essential to verify a website's licensing policies and consult legal counsel as necessary before performing data scraping to avoid potential liabilities.
Note: These materials offer prospective students a preview of how our classes are structured. Students enrolled in this course will receive access to the full set of materials, including video lectures, project-based assignments, and instructor feedback.
Let's talk about our second way to access data with Python that we'll be discussing in this course. Data scraping. Data scraping is a strange term for sure, if you're not familiar.
It's the process of programmatically accessing data from a third-party website. So what does that mean? It means we're accessing data by pulling it down from a third-party website. So it's not from a server.
There's no API server the way there is with this API, which just, you know, exposed this data. And we could say, hey, make a request to that server, and we make the right format request, and we get the right data back. Instead, we're going to this website.
In this case, we're going to start with this one, but we'll look at some other ones as well. And we're pulling it straight from the page itself, straight from the HTML, straight from the text that just happens to be on that page. So this is a very different way to access data.
It's a little similar, for sure, to getting data from an API. But there are unique challenges. Data exploration.
We have to figure out what formats the data is going to be in. Parsing the data. And ethics and legality.
Now, I am not a lawyer, and this is not legal advice. But this data was not purpose-built to be programmatically accessed, right? If they built an API, great, we'd be using the API. They didn't.
And we need to respect the reason they did it. Sometimes, most of the time, it's because, you know, nobody, they didn't see a vested interest in putting their data out there on a server for anyone to access publicly, which is fine. It's a fine decision to make.
Sometimes, they didn't put that data on an API because they don't want it out there. So every website should have their legal opinion on whether their site should be accessed or not, whether it should be scraped or not, who does this data belong to, and what license do you have to use that data. And as long as you are following that license, you are usually doing a great job.
If you are breaking that license, if you are using data in a way that the creator of that data or the distributor of that data doesn't approve of, then you are breaking your agreement with that company and there may be legal liability. Again, this is not a legal course. This is not a course in the law.
Even if you are following the license, you should speak to a lawyer if you're using this data in a way that you're not sure is correct, ethically or legally. Okay, that's the lawyer part of this. And again, not a lawyer, made that pretty clear.
So feel free to do some research, talk to a lawyer if you're not sure if you should be accessing that data. Data scraping, though, as a tool, is a very powerful tool. And most of the time, you are fully in the clear to use that data.
You just had to go through some extra effort because the producers of that data did not put in the resources to create a full API for it. We're going to assume that for the rest of this course, data scraping is, when used wisely, a very powerful tool and we will be exploring how to use that tool. All right, let's start in the very next video.