Python for decision makers and business leaders Transcripts
Chapter: Testing
Lecture: Testing in Python
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0:00
How do you know your software is working
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the way you expect it?
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How do you know that new bugs were not introduced?
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Or that, when you find them
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they don't get reintroduced somewhere along the way?
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Well, you right test for your code.
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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
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and correct them early in the lifecycle.
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When you're planning it, creating architecture
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maybe when you're writing the code
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you found a bug and you fixed it
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before you ever release it.
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Those are relatively cheap.
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We do, maybe in some organizations, have QA
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Quality Assurance steps, where we find bugs there.
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Not all companies have those, but some do.
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Once you've released the software
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depending on how you release it
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it can be a lot more expensive.
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If you need to go and do a deployment to the website
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that's not necessarily huge
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but if it's affected customers;
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if somebody's messed up a credit card purchase
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and then you've got to go back and deal with
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all that in the different systems
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and you've got to do the customer support
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or a package was sent to the wrong place
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or a buy decision was made on stocks
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when it should have been sell
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those all of the sudden have huge implications.
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And, of course, if you're shipping desktop software
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well, it's just a pain to get that sent out again.
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So the idea is that
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testing lowers the overall cost of software systems
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and that you should definitely do it.
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Good news is, Python has two solid options
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more than that actually
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but two of them are really, really good.
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It has a built-in testing framework
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that just comes with it.
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Remember standard library, and the batteries included?
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Well one of those batteries is a testing battery.
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You can go and test your code like that.
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But most professional software these days
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uses this thing called Pytest.
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And Pytest is extremely simple.
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You can see on the screen
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that first gray box shows the entirety of a program
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and it being tested.
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It turns out it's incredibly simple
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but it also is very extensible
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and does a lot of cool things.
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So we're going to talk just very briefly
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for a few minutes about testing code with Python.
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We're not going to write code
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we're not going to spend too much time on this
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but I just do want to address it a little bit
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because it is important in languages like Python.
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Also, you can use Python to test other things.
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Python is simple to write tests in
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maybe you can test other devices, or languages, or so on.
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We'll touch on that, too.
