Building Data-Driven Web Apps with Flask and SQLAlchemy Transcripts
Chapter: Using SQLAlchemy
Lecture: Creating the basic insert script
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In this chapter, we're going to look at actually using SQLAlchemy. Previously we had modeled all of our data but we didn't do anything with it.
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We didn't do any insert queries, updates none of that. That's what we're going to do now. And to get started
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we're just going to jump right into writing some code. And so I just want to point out we are now in Chapter 10
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Using SQLAlchemy, working on the final bits here. So let's switch over to PyCharm grab our new chapter and get going.
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This is the code from before, just carrying on. And what we're going to do is we're going to actually have over here a new directory called bin.
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Now, this is just a convention that I use. I've seen it in other places as well and this bin folder comes along with our website
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for little admin tasks and scripts that we need to run and so on. It's not directly involved in running the site but more like maintaining the site.
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So, for example we're going to do some importing of data. And to do so, we're just going to write some scripts here. They don't actually run normally
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but they're going to run here. Let's go over and add a Python file called basic_inserts.py.
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We're going to take two passes at showing how to insert data. First, we're going to write some example data just standard make-up stuff.
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And then I'm going to show you I've actually got a hold of the real PyPI data for the top 100 packages using their API and we're going to insert that.
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Turned out that's super, super tricky. There's lots of little nuances and typecasting and all that kind of stuff we have to do
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to make it work just right. We're not going to do that first we're going to do like a simple example and then I'll show you the program
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that'll actually generate our real database. So, here it is. We already have our database right here and if we look at it
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we'll see that we have our packages and releases put together. And, of course, there are the interesting ones.
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Actually, I'll go over here and show you a little more. Show you a visualization pop-up. It's kind of a cool feature of PyCharm.
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So we have our packages and this relationship between the releases. That's probably the most interesting part of our database.
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We didn't actually set up save, like the maintainers and what not here. This should maybe have, like some relationships and so on
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but we didn't set up all the relationships for our data model, just the really important ones. So, we're going to focus on just those two tables.