Python for Decision Makers and Business Leaders Transcripts
Chapter: Testing
Lecture: Testing in Python
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How do you know your software is working the way you expect it? How do you know that new bugs were not introduced? Or that, when you find them
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they don't get reintroduced somewhere along the way? Well, you right test for your code. Maybe you've seen a graph that looks like this.
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The general idea is that it is much cheaper to find bugs and correct them early in the lifecycle. When you're planning it, creating architecture
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maybe when you're writing the code you found a bug and you fixed it before you ever release it. Those are relatively cheap.
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We do, maybe in some organizations, have QA Quality Assurance steps, where we find bugs there. Not all companies have those, but some do.
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Once you've released the software depending on how you release it it can be a lot more expensive. If you need to go and do a deployment to the website
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that's not necessarily huge but if it's affected customers; if somebody's messed up a credit card purchase and then you've got to go back and deal with
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all that in the different systems and you've got to do the customer support or a package was sent to the wrong place
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or a buy decision was made on stocks when it should have been sell those all of the sudden have huge implications.
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And, of course, if you're shipping desktop software well, it's just a pain to get that sent out again. So the idea is that
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testing lowers the overall cost of software systems and that you should definitely do it. Good news is, Python has two solid options
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more than that actually but two of them are really, really good. It has a built-in testing framework that just comes with it.
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Remember standard library, and the batteries included? Well one of those batteries is a testing battery. You can go and test your code like that.
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But most professional software these days uses this thing called Pytest. And Pytest is extremely simple. You can see on the screen
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that first gray box shows the entirety of a program and it being tested. It turns out it's incredibly simple but it also is very extensible
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and does a lot of cool things. So we're going to talk just very briefly for a few minutes about testing code with Python. We're not going to write code
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we're not going to spend too much time on this but I just do want to address it a little bit because it is important in languages like Python.
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Also, you can use Python to test other things. Python is simple to write tests in maybe you can test other devices, or languages, or so on.
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We'll touch on that, too.