Transcript #55: Flask, Flask, Flask, 3x Flask

00:00 Hello and welcome to Python Bytes, where we deliver Python news and headlines directly to your earbuds.

00:05 This is episode 55, recorded December 6th, 2017.

00:10 I'm Michael Kennedy.

00:11 And I'm Brian Okken.

00:12 And Brian, can you believe it's December?

00:13 Yeah, it's getting cold out.

00:15 It's getting cold. I look outside, it's the middle of the day, and it's still basically dark.

00:19 So I guess we're getting there.

00:21 Yeah.

00:21 So before we get into our picks for the week, though, let's just say thanks to DigitalOcean.

00:26 They have a ton of awesome servers for you.

00:29 The websites I run run on DigitalOcean.

00:32 So we'll tell you more about that later.

00:33 However, one option, I guess one of the servers I have actually runs Flask.

00:39 And Brian, I hear you're kind of digging Flask these days.

00:42 Yeah, I am actually going through Miguel Grimberg's Flask mega tutorial.

00:47 So I'm pretty excited about that.

00:50 And I got actually from the, I think I took the advice from you to try something simple like Flask at first,

00:59 not to slam Flask.

01:00 But it is pretty low barrier to entry.

01:03 And I knew Miguel was rewriting this mega tutorial.

01:06 So I begged and pleaded and got an early copy of the rewrite.

01:10 So I'm partway through it right now.

01:12 But he did a Kickstarter to try to rewrite it.

01:16 The first one was in 2012.

01:17 And his Kickstarter was very successful, I think.

01:21 His part one of the rewrite is available right now today.

01:25 Yeah, that's awesome.

01:26 And I know Miguel's been putting a ton of work into the rewrite.

01:29 I was so excited to see his Kickstarter be successful.

01:32 He added a bunch of stretch goals to do additional sections.

01:38 He has an ebook version and a video version coming out of it, coming out as rewards from it.

01:43 He hasn't done the videos yet.

01:44 He and I were actually just talking today about the videos.

01:46 So that'll be fun.

01:48 But yeah, so if you want to learn how to get going Flask, his work is really great.

01:53 And so definitely check it out.

01:54 He does have, what he's going to do is he's going to release one part every week.

01:57 But if you can't wait that long, you can buy his ebook.

02:01 I think it's just like 10 bucks or something.

02:03 Yeah, totally affordable.

02:04 And that's what I'm reading right now.

02:05 And yeah, his video, he says he's planning on January for the video version.

02:09 Yep.

02:09 Very cool.

02:10 Very cool.

02:11 Speaking of new releases.

02:12 New releases and the web.

02:13 Amazing stuff.

02:14 Django 2.0 is released.

02:17 And this is a huge, huge change.

02:19 It has been many, many moons since major point release of Django has come out.

02:26 I mean, after all, it's only version two, right?

02:27 This is a huge deal.

02:29 And it's a lot of cool new features.

02:32 One of the things that they added that I really like, and I don't know, it's always made me

02:37 just crazy when I looked at Django is the fact of writing regular expressions for the routing,

02:42 which is I want to take this URL and figure out which view method that goes to.

02:46 That used to be a regular expression, which was painful.

02:49 Now it's much more like Flask and Pyramid.

02:53 You just put little identifiers, like variable names in cutout URL.

02:57 And then that's how it maps over.

02:59 And you even have types.

03:00 You can say it has to map to slash users slash user ID colon enter.

03:06 I think enter goes first.

03:07 But there's this nice routing syntax.

03:09 There's some nice responsive design changes, better querying over some of the query sets.

03:16 These are all cool.

03:18 They have a new versioning, what they're calling loose form of semantic versioning.

03:25 So if you look at the possible versions, we have two, maybe it'll be a 2.1 and then a 2.2.

03:32 And then that 2.2, maybe that's something they're calling stable long-term support LTS.

03:37 So it might be 2.2 LTS.

03:39 And then if they go anything beyond the LTS, that's a three.

03:42 Then a 3.1, then a 3.2 LTS.

03:45 So anytime you go into new territory past the LTS version, it's a major version increment now.

03:52 Okay.

03:52 It's interesting.

03:53 Yeah.

03:54 So I suspect that we'll see major Django version numbers coming faster because of that.

03:59 But I'm not sure.

04:00 I guess we'll have to see.

04:01 And then there is some exciting thing about Python 3.

04:05 Yeah, it's very exciting.

04:06 The legacy Python is dealt yet another blow.

04:09 So Django has had a significant disproportionate influence on the adoption of Python 3.

04:15 For example, when they switched their tutorials by default to use Python 3 versus Python 2,

04:20 that dramatically changed the usage by numbers on PyPI.

04:26 And so now they've actually dropped support for Python 2.

04:30 It's the first version of Django that says, you know, Python 2, that's, you know, thanks.

04:34 But that's not for us.

04:36 It's Python 3 only going forward.

04:37 Yeah.

04:37 And because of that, I've seen a few people mention on Twitter that working with the code base is a lot easier now

04:44 because there aren't a lot of backwards compatible things in there.

04:49 They were able to clean up the code base quite a bit for this.

04:52 So I think it's great.

04:53 I think it's great as well.

04:54 And yeah, it definitely makes working on new features easier because you don't have to write them twice in some sense.

04:59 And there's a bunch of small changes.

05:01 I don't want to read them all off to you.

05:03 But just to give you like a sense, down in Django contrib.auth, luckily they're doing password hashing and folding.

05:11 So not just hashing with salt, but then you take that and you hash that and you take that and you hash that.

05:16 And then they used to do that 36,000 times.

05:18 Now they do that 100,000 times.

05:20 So it's more computationally expensive to guess the password if somehow the database were to leak.

05:25 And so there's just tons of little cool changes like that throughout there as well.

05:28 But probably the biggest one people will notice is the simplified URL routing.

05:33 Yeah, that's nice.

05:33 So you've got a bunch of rules for us or something, huh?

05:35 I do.

05:36 What's up with that?

05:37 I'm usually somebody that doesn't follow a lot of rules.

05:41 But one of the things I embraced when coming into Python is the notion of that there's kind of a coding style that everyone follows.

05:49 Or a lot of people follow on open source projects, which is PEP 8.

05:53 And then it's extended.

05:55 So there's when I started using type checkers like Lint or at the time I started it, the way to check for PEP 8 was a tool called PEP 8.

06:04 That's now been changed.

06:06 The name has changed to PICodeStyle.

06:08 But now I usually use Flake8 for my Linter.

06:12 And there's a...

06:15 So Flake8 covers PICodeStyle, which is PEP 8.

06:18 And then it covers PyFlakes, which does a lot of traditional Lint stuff to catch bugs.

06:22 And then a McCabe complexity checker.

06:26 And that one, I actually have tried to figure that out several times.

06:30 And I don't know what it does.

06:31 Nice.

06:31 Yeah, cyclomatic complexity is a pretty interesting metric for code maintainability.

06:37 So the idea is how many different decision paths are possible through that code.

06:43 All right.

06:44 So if you had a method of cyclomatic complexity 5, there's five separate execution paths that could go through there.

06:51 There could be one if case that does an early return, another that's an if, elif, elif.

06:55 And taking all the possible ways in which you could go through those conditionals and loops and whatnot, there would be five possibilities.

07:02 So meaning basically you need five tests minimum to cover that.

07:05 Okay.

07:06 I'm not sure what the check is for McCabe, what the complexity number is that they're flagging for.

07:12 But I usually turn it on anyway because I want to know if my code's a little too complex.

07:15 The issue with it is a lot of these spit out an error message with a one-liner explaining what it is.

07:23 And so what I have for us today is called the big old list of rules, which translates all of those errors and warning numbers into very nice one-page descriptions of what they are with links to more information.

07:38 And I really like it.

07:39 I'm going to be using this all the time now.

07:41 That's really cool.

07:41 I feel like there's an opportunity.

07:43 First of all, well done, Grant, for writing this and putting this all out for everyone.

07:48 But I think there's an opportunity for editor of plugins, whether you're using Sublime, Visual Studio Code, or PyCharm, or whatever.

07:55 You could probably get a plugin that would turn that into a hyperlink that shows the details from this list.

08:00 And that would be awesome.

08:01 Oh, yeah.

08:01 That'd be good.

08:02 Yeah.

08:02 Yeah.

08:03 I'm using, so PyCharm does this, checks for a lot of this stuff.

08:06 And yeah, and I usually turn it on for pytest too.

08:10 I have my pytest plugin to check Flake 8.

08:13 Once you find an error trying to fix it, it's good to know what it is.

08:17 Yeah.

08:17 Especially when it's just E112.

08:19 Like, what the heck does that mean, right?

08:21 Yeah.

08:22 I mean, you may be really good and know them, but I don't know.

08:25 Awesome.

08:26 So before we get on to the next item, just want to let everyone know that this podcast and really all the sites that I run are coming to you through DigitalOcean.

08:35 I have, gosh, it's just a growing list.

08:37 I think I probably have eight servers over there now doing all sorts of hard work and working together on various services and database connectivity and whatnot.

08:45 So super excited about working with DigitalOcean and talking about their stuff because it's really, really been great to work with.

08:53 So if you're looking for cheap, reliable, fast servers that are simple and not, you know, a huge mess of a thousand features like you might get somewhere like AWS or Azure, you just want to have a server and work with it in a really nice way.

09:07 Check them out at DigitalOcean.com and let them know that Python Bytes sent you.

09:11 Nice.

09:11 Yeah.

09:12 We could probably contact them with requests as well.

09:15 We could probably like do some sort of API and talk to them.

09:18 But if you want to test it, you need to mock out your request, right?

09:21 Definitely.

09:21 One of the challenges, I think there's a few things that are really make testing sticky, tricky, whatever.

09:28 One of them is time.

09:30 The other one is the network and external services.

09:34 Some of that being requests type things, some of that being databases.

09:37 So any chance you get to cleanly sort of mock that out is really nice.

09:43 And so this one actually comes from a friend of the show, Anthony Shaw.

09:46 And he has this thing called requests static mock.

09:50 And I think we were recently talking about something with mocking requests.

09:54 And he's like, you should check out request static mock.

09:58 And so I did.

09:59 And it's pretty cool.

10:00 So I decided to make it one of the things we're talking about this week.

10:03 And the idea is you can create a request session and then mock that out like, hey, I want that return of 503 service unavailable.

10:10 Or I'd like when you make this request to this URL, return this JSON file as the response.

10:17 So really easy to swap out the testing behavior.

10:21 Like if your code somewhere deep down calls into requests, but you can do it without monkey patching.

10:26 Yeah, that's the neat part is it's without monkey patching or doing a lot of these test based mocks.

10:32 It's pretty cool.

10:33 Yeah, it definitely is.

10:34 Yeah, you don't really mock stuff as much.

10:36 You kind of just plug in the session.

10:37 And, you know, if for people who don't know, the session object is a thing that comes from requests, which is actually pretty interesting.

10:43 So suppose you're going to start talking to a service and every single request has to have an off header.

10:50 It has to have maybe a user agent.

10:53 It has some other details, some kind of token type thing.

10:56 Who knows?

10:56 A lot of shared stuff.

10:58 Or if you're going to try to submit a form and then you need to take a session on the server, like a cookie based session, and then go and do other things.

11:08 You can't do that with just straight requests so easily so that you create one of these sessions and it keeps a persistent connection.

11:13 It handles the cookies per, you know, across all the requests and stuff like that.

11:17 So that's really handy.

11:19 And what Anthony's thing does is create a sort of testing session variant of that.

11:25 So it's pretty cool.

11:26 So you can mock that thing out.

11:27 Yeah.

11:27 And the way you put it together, too, is the data that's coming back is just in like a, you can just set it up as like a tree structure in your file system.

11:36 It's kind of like your old school HTML directory.

11:39 That's right.

11:40 With some index.html and all that kind of stuff.

11:44 They just put it in there and it traverses that.

11:45 That's cool.

11:46 It's a nice interface for the developer as well.

11:48 It's cool.

11:49 Yep.

11:49 Well done, Anthony.

11:50 So you're going to give us a bit of a preview of Python 3.7, right?

11:55 Because there's some pretty awesome stuff that just got approved or finalized.

11:59 Data classes, which I didn't know it was on the fence for a while.

12:03 But these are data classes have been approved by Guido and it's PEP557.

12:09 And these are kind of a different form of regular old classes.

12:13 But you can put a decorator on there for a data class.

12:16 And then you can sort of say what your some data elements and what type they are.

12:21 And you can assign defaults.

12:23 And the cool thing about that is you don't have to write your own init statement.

12:27 It kind of generates one for you.

12:29 So the first time I saw these, I'm like, wait, that's not valid Python.

12:32 What is this?

12:33 What language is this?

12:34 Yeah.

12:35 So you could say like class C colon and then just A colon int new line.

12:41 B colon int new line.

12:43 And you just start out with a class when you create it that has an A and a B and those are both none.

12:48 Right.

12:49 Or you can even set default values.

12:51 That's pretty cool.

12:51 It lets you do more of the definers part of the class structure instead of the self dot attribute equals value through the dunder in it.

12:59 But like you said, it still generates that dunder in it and then moves over the default values and all that.

13:03 I kind of like the syntax.

13:04 The first time I saw it, like you said, it's bracing.

13:07 And it's like, this isn't Python, but it's kind of nice that you can just put that in one place and not worry about it too much.

13:15 It's pretty clean.

13:16 Definitely like it.

13:17 Yeah.

13:17 I find myself doing this sometimes and I'll just have to set everything to none or to zero or something like that because it won't work otherwise.

13:25 But guess what?

13:26 It does now.

13:26 It's cool.

13:27 And I also just found out that there is a 370A3 developer build that's out that has this in it.

13:35 So if people want to play with it, they can.

13:37 But I probably wouldn't do much production code with it because 3.7 isn't scheduled until June.

13:43 Okay.

13:43 Yeah.

13:44 So it's a little ways out, but still exciting to see this coming.

13:46 I think this is pretty nice.

13:48 So one of the things that this feels like I think is compared to and looks somewhat similar to is adders.

13:54 And adders gets a lot of attention as well.

13:56 What's the story between those two?

13:58 I don't know the history of like how much.

14:01 I know that, hi, Nick.

14:02 Oh, he's going to clobber me again for getting his name wrong.

14:04 But I think he was involved in talking with the core developers and talking about this data class.

14:11 But I'm not sure.

14:11 But anyway, there's a few.

14:13 Adders is still great.

14:15 And these data classes don't do everything that adders does.

14:19 And it has more validators and converters and a whole bunch more stuff that you can do.

14:25 So it doesn't completely take the place of adders.

14:29 But for simple cases, I think it's a simpler interface.

14:32 Yeah.

14:33 Okay.

14:33 That sounds good.

14:35 The best example that I heard of why people wanted it in there is because the core developers wanted to use it on Python itself.

14:42 And you can't use non-standard library stuff within the core of Python.

14:48 Yeah.

14:48 I think that's a really interesting point.

14:49 And adders is changing fast.

14:51 It's still getting a lot done to it.

14:53 And you don't want to hamper it and cover it in quicksand or some sort of tar, right?

15:00 You want to slow it down by sticking it in the standard library and going, well, you can only change very slowly now and only every year.

15:07 Yeah.

15:07 That's some of the reason why requests isn't in the standard library, right?

15:10 Exactly.

15:11 Yeah.

15:11 Same reason.

15:12 All right.

15:12 So for our final thing, I want to start with our first thing.

15:16 Flask.

15:16 Flask.

15:17 Ah.

15:17 My version of Flask I want to talk about is three times faster than your version of Flask.

15:21 So how does it do that?

15:23 So there's this thing called Court, which I haven't done much with Court.

15:27 but it's kind of like a wrapper around some of the AsyncIO stuff, but also an API that can run Flask apps.

15:34 Like I said, I haven't done a ton with it.

15:35 But Court is this thing that you can use that has the same API as Flask, but is AsyncIO friendly.

15:44 So you can plug it into the super, super fast things like UV loop or AsyncPG for asynchronous Postgres, which is pretty awesome.

15:54 And there's some really amazing benchmarks there.

15:56 So Flask, along with Django and along with Pyramid and all the others, they don't support any Async and IO stuff.

16:04 And they can't take advantage of basically releasing the thread to go do other work when it's, say, waiting on a database or on a call over request or something like that.

16:15 Just because they're all using Whiskey, that's not how Whiskey works.

16:20 So you can plug in a Court, which basically has the same API as Flask, and you just have to make a few minor changes to get your code to go much faster.

16:31 So here's an article with a demo application.

16:33 They've got benchmarks and stuff saying we're getting roughly three times the speed by just switching a few things around in the app.

16:40 Yeah, I think that's cool.

16:41 I definitely need to try this.

16:43 Yeah, so the things you have to do, obviously, if you want to take advantage of AsyncIO, is you have to make your functions async.

16:51 Right?

16:51 Otherwise, they're just regular functions.

16:53 They go just the same speed.

16:54 So you would put Async in front of your view methods.

16:56 And then when you call into things like databases or web services via request, say, you have to await those to basically tell Python, give up my thread.

17:06 I'm waiting on this.

17:07 And then pick it up when it gets back.

17:09 Right?

17:09 Put me back somewhere farther down in the loop when this returns.

17:13 So that's all cool.

17:14 But your database access has to have some sort of asynchronous component.

17:20 So when you do a query, you can wait on it.

17:21 Otherwise, it's kind of useless again.

17:23 So that's why it's both the Quart but also AsyncPG.

17:29 Right?

17:29 Which is pretty cool.

17:30 So it's not entirely easy to switch over depending on what you're doing.

17:34 Like if you're using SQLAlchemy.

17:36 SQLAlchemy, I don't believe, supports anything with Async.

17:38 So you're kind of out of luck.

17:40 It depends on what you depend upon, actually.

17:42 Okay.

17:43 It's easy to switch if it's going to work at all.

17:45 How's that?

17:45 Yeah.

17:45 And one of the things I think is neat about this, and it's a clever idea, is instead of inventing a completely new framework, it is a completely new framework.

17:54 But they wanted to, like, I think it's a good idea to slow down the learning curve.

17:59 You've got to figure out the Async stuff.

18:00 But you don't really have to refigure out how the framework works because they've said.

18:05 Yeah, that's cool.

18:06 The framework's just like Flask.

18:07 That is such a good observation.

18:09 And it's really right.

18:11 There's HTTP, AIO, HTTP.

18:14 I don't remember the order.

18:15 Sorry.

18:15 But there's that.

18:17 There's Jepronto.

18:18 There's Sanic.

18:19 There's all these other frameworks trying to take advantage of things like UV loop and Async and Await.

18:25 But they're like, and you start from scratch.

18:27 And you learn a totally new framework.

18:29 With this, you could probably go take Miguel's tutorial thing and then go make it faster.

18:34 It's kind of cool.

18:35 And that's what I plan on doing.

18:36 Yeah.

18:37 Perfect.

18:38 Be cool.

18:38 All right.

18:39 Well, that's our news for this week, Brian.

18:41 Anything you got going on over there?

18:44 No, I'm just trying to learn Flask, man.

18:46 Awesome.

18:47 That sounds really fun.

18:48 So are you familiar with the Pythonic staff of Enlightenment?

18:52 Yes.

18:52 I carried it around for a while at PyCon.

18:54 Yes.

18:54 So did I.

18:55 So a lot of people probably don't know about this.

18:57 There's a picture of me with Anthony Shaw, who I mentioned in the mocking bit.

19:02 And me walking around with this giant, I don't know, it's probably four feet tall, this big, heavy staff.

19:09 At the end, it has like a massive Python logo.

19:12 And so one of the guys that was involved in creating that thing originally actually decided, so many people asked for it, he's creating a store where you can buy your very own Pythonic staff of Enlightenment.

19:24 So he's like, hey, would you mind letting people know about the staff?

19:28 I'm like, yeah, this is pretty cool.

19:29 I'll let people know.

19:30 Yeah.

19:30 I haven't checked it out yet.

19:32 Any idea how much it is?

19:33 I think it's like a hundred bucks US.

19:34 Okay.

19:34 I may need one anyway.

19:37 I know.

19:37 Well, Christmas is coming.

19:38 Everyone needs a cool Python staff for Christmas.

19:41 Yeah.

19:42 Anyway, I thought that was fun.

19:44 So I thought I'd throw that in there at the end for you guys.

19:46 That's nice.

19:46 Cool.

19:47 Yeah, indeed.

19:47 All right.

19:48 Well, Brian, great to chat with you as always.

19:50 And thanks everyone for listening.

19:51 Thank you.

19:51 Thank you for listening to Python Bytes.

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20:11 On behalf of myself and Brian Okken, this is Michael Kennedy.

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