#18: Python 3 has some amazing types and you can now constructively insult your shell!

00:00 Hello and welcome to Python Bytes, Python news and headlines delivered directly to your earbuds.

00:05 I'm Michael Kennedy.

00:07 And I'm Brian Okken.

00:08 We're here to share the Python news with you and basically share the cool stuff that Brian and I found for the week.

00:13 Brian, you know what I think is cool?

00:15 That I can open up, I can basically go to any Python object or module or even function or whatever and just say,

00:21 tell me what is in you, dir this thing, and out pops all of its capabilities, mostly anyway.

00:27 Yeah, I love that.

00:27 Do you know what REPL stands for?

00:30 REPL?

00:30 REPL.

00:31 Read Val Print Loop.

00:33 Just what you get when you type Python.

00:35 Yeah.

00:35 Like most of the time now, the only time I open that is to try out something little or to actually to use the dir command.

00:44 You know what?

00:44 I do do that as well.

00:45 I'm like, I'm going to open this up and just do a dir here.

00:47 Okay.

00:48 Back to work.

00:49 Yeah, exactly.

00:50 Just to look at the interface for something.

00:52 So I was excited to see a new project from Leica 9M on GitHub called pdir2.

00:59 And when you use it, so it's pdir2 when you're installing it.

01:04 But when you use it, it's just pdir.

01:06 And it's just a replacement.

01:08 And it's cool because it's all colorized and it splits it out and splits it up into one line per item.

01:17 And it pulls the dock string out of each item so that you can see that.

01:23 And for what I'm using it for, when I pull up the REPL, it does what it should do automatically.

01:29 And I like it.

01:30 Yeah, it's cool.

01:31 I mean, it's kind of like if you typed help a thing, but it gives you meaningful stuff even if there's no real help to be had.

01:38 And it'll categorize things like, here are all the classes.

01:40 Here are all the functions.

01:41 Here's the stuff that I have no idea what it is, but it's also there.

01:43 So we'll put it over here.

01:44 And if there's dock strings, it'll put the dock strings there for like, here's the description of each thing.

01:49 It's really nice.

01:50 Yeah, and it does, it like puts all the dunder functions out of the way so those aren't in the middle of everything too.

01:56 Yeah, yeah, those land in the other.

01:57 Yeah.

01:58 Anyway, it's just, it's part of my repertoire now.

02:02 I'm going to, I'm never going to let it go.

02:03 One of the things I would like to ask somebody to do is to help out with the project and convert the README to whatever that other thing is.

02:12 Restructured?

02:13 Yeah, restructured so that it looks good on PyPI because it's in, the README is in Markdown.

02:20 And PyPI still doesn't like Markdown.

02:22 I wonder, did you look at it on PyPI.org?

02:25 No, I haven't.

02:26 No.

02:27 Versus the older one?

02:29 It's worth looking at that one.

02:30 I have no idea what it'll look like there either, but that's the new one.

02:32 Maybe it understands Markdown.

02:34 Who knows?

02:35 I would also like to recommend that people pair this with PtPython.

02:39 Do you know PtPython?

02:40 I don't.

02:41 Oh my God.

02:41 PtPython is awesome.

02:42 Like I don't use the REPL very much.

02:44 Everyone knows I love PyCharm and I kind of live there.

02:47 But when I do go into the REPL, it really annoys me that I need to completely type everything that is there.

02:54 That it doesn't autocomplete.

02:56 Especially when I'm exploring something new, which is like why we said often we go into the REPL.

03:00 Well, PtPython is basically, I think it's a little bit based on Emacs, but it's like a different version of the REPL that has code completion and a little bit of a UI over the terminal.

03:12 It's really nice.

03:13 So these days, if I want Python, I type PtPython.

03:17 Okay.

03:17 Well, I'll have to check that out.

03:18 And just to let people know, I did.

03:20 Okay.

03:21 So I'll take back that request because I looked it up on PyPI.org and it looks great.

03:26 It even has that animated GIF on there.

03:28 Oh, yeah.

03:29 So there's a little animated GIF that shows you how it works, which is quite cool.

03:31 So, yeah, check out this project.

03:33 It's easy to use.

03:34 The one thing to notice is you've got a pip install peter2 versus peter, but then the module's just pdir, right?

03:43 So there's a little bit of a nomenclature funkiness, but it is cool.

03:47 You know what else?

03:48 Go ahead.

03:49 I just want people to remember that.

03:52 And speaking of memory.

03:53 Speaking of memory, absolutely.

03:56 So this has happened to me once in my life.

04:00 I have not used these tools to solve it.

04:03 But here's the deal.

04:04 Like, suppose that you somehow, through probably your fault, but it could have been like a hard drive failure or something, somehow you've lost your source code.

04:16 So there's a guy who was using a source control wrong and wiped away all of his files off of his directory.

04:22 But he still had the program running in memory.

04:25 It was a Python program.

04:27 So he used two really interesting packages that I'd never heard of.

04:32 Had you heard of these?

04:33 No, I haven't.

04:33 One of them is Pyrocyte, like parasite, but for Python, P-Y-R-A-C-E.

04:38 And the other one is un-compile 6.

04:42 Because apparently it's one of the few that supports both Python 2 and Python 3, and multiplication is awesome.

04:48 So un-compile 6.

04:50 So the idea is with Pyrocyte, you can attach to any running Python process.

04:56 And you basically get this REPL, like we were talking about, to just explore its memory, to see what its values are.

05:02 You can even, like, force it to load other scripts and run them.

05:05 You can go to, like, an in-memory, like, singleton object and, like, work with its data.

05:10 All sorts of stuff you can do in real time while it's still running around.

05:16 That's pretty cool.

05:17 So basically what he did is he said, all right, I'm going to hook up to it with Pyrocyte.

05:21 I'm going to force the thing to load un-compile, and I'm going to call un-compile on itself and get my code back.

05:26 Wow.

05:26 But mostly the core.

05:29 It worked.

05:30 Yes, it worked.

05:31 There are people, there's, like, a whole bunch of people.

05:33 It's a, I get a gist.

05:34 At the bottom of the gist, they're like, oh, my God, I just had to try this because I couldn't believe it would work.

05:39 Oh, that's so awesome.

05:39 Yeah, it works.

05:40 I think there's either a video or a little GIF that is just, like, that basically shows you how it works if you go to Pyrocyte.

05:46 Pyrocyte.com, which that's the coolest takeaway for me on this whole one.

05:50 That's awesome.

05:51 Good job.

05:51 Cool.

05:52 Yeah.

05:52 All right.

05:54 You know what I think?

05:55 You and I were on a mission, right, to make sure that Python is modern Python, not legacy Python, right?

06:00 Yes, definitely.

06:00 And I was really surprised.

06:02 They're still adding quite interesting and new data types to Python 3.

06:07 Even stuff that's been around for a little while that I just haven't, like, heard of.

06:11 Because of this show, I've learned about the simple namespace as a, wait, no, that's not it.

06:18 The name tuple class, the capitals.

06:20 But let's get into this.

06:21 There's an article called New Interesting Data Types in Python 3.

06:26 And it just goes through three that I really like.

06:29 And the three types are types.mappingproxytype, types.simple namespace, and typing.namedtuple.

06:38 And the mapping proxy type is, like, really cool.

06:42 It takes, like, something like a dictionary.

06:45 Or it says, I can't think of anything other than dictionary.

06:48 It says it only takes mapping types.

06:50 Yeah, it's really cool.

06:51 But it's, like, a read-only dictionary, basically, right?

06:54 Yeah.

06:54 So you take a normal, like, maybe a normal dictionary.

06:56 And, like, if you had an API or something, you wanted to expose that dictionary through the API,

07:02 you could wrap it in this mapping proxy type and return that.

07:05 And I tried it out.

07:07 And so, for instance, one part of your project could use the mapping proxy type version and read everything.

07:14 And the part of your system that can have, that still has write access, that is synchronized.

07:20 So it isn't a copy.

07:20 You can, when one part writes to it, it gets updated in the other place, too.

07:25 Oh, it's like a view into an existing dictionary, huh?

07:27 Yeah, it's a read-only view.

07:28 Sweet.

07:29 So that's nice.

07:30 And then not too long ago, I started using where I really wanted classes or something.

07:36 And I was using things like tuples or lists where there really should have been something more structured.

07:41 I've been using the lowercase named tuple.

07:45 Right, out of the collections names, out of the collections module, right?

07:47 Yeah, out of collections.

07:49 And there is this thing in types called types.simple namespace that uses a similar sort of functionality.

07:57 You can just, if you define a type to be that type, you can just, the parameters when you instantiate it,

08:05 those just become elements inside the object.

08:07 It's pretty convenient.

08:09 Yeah, that's cool.

08:09 So you can do a little more organization.

08:11 And then, of course, the typing.name tuple class is really nice.

08:15 I hadn't been using it.

08:15 I've always just used collections.name tuple.

08:17 But I think I'm going to be switching.

08:19 Now, one word of caution, I suppose, is a lot of these are, they require pretty modern Python.

08:25 Some of the techniques they show require 3.6.1.

08:29 Like, 3.6.0 is not enough.

08:31 So just be aware that some of these require pretty new versions.

08:35 Yeah, and that's, I guess, it's hard for me to remember because I'm usually trying to stay.

08:40 I don't go into the in-development Python, but I try to use the latest released one.

08:45 I do as well.

08:46 You know where that bites me, though?

08:47 Is on my DigitalOcean servers.

08:49 It's running the version of Ubuntu that only has 3.5.2 or something like that.

08:55 So if it's literally a 3.6 feature, I'll put it in my app and I'll ship it like, oh, it doesn't work.

09:00 What was I thinking?

09:00 Yeah, and I forget that.

09:02 That 3.5 is really, for version 3.x, 3.5 is being used more than 3.6 right now.

09:09 Yeah, just because of the distributions, I think.

09:11 In my mind, that's like the minimum bar for 3.5 stuff is 3.5.

09:15 Yeah, okay.

09:16 But I think these are great things to start adding to your repertoire.

09:20 If you have control over where it's going to run, those are good things.

09:24 Yeah, and some of them come from like Python 3.3 or 3.4.

09:26 They're fine.

09:27 There's just a few techniques there that are brand new.

09:29 And what I like about this, one of the things I like about this article is it's pretty short

09:33 and it gives examples of how to use these pretty concisely.

09:37 So that's good.

09:38 Yeah, very nice, very nice.

09:39 Speaking of how do I use things, wouldn't it be awesome if I could just go to my Bash shell

09:45 and just type, how do I and type a thing?

09:47 Like I'd like to say, maybe I want to know how to print a stack trace or trace back in Python.

09:52 I could say, how do I print stack trace Python and just type that?

09:56 Yeah, that'd be cool.

09:57 It'd be cool if my computer knew that, right?

09:59 Well, it turns out we ran across a project called How Do I?

10:03 And if you install How Do I, if you pip install it, it will give you instant coding and shell answers on the command line.

10:11 So I can say, how do I connect SQLAlchemy?

10:14 And it'll give me the Python code to connect for SQLAlchemy.

10:17 I can say, how do I Python save dictionary?

10:20 That's three words.

10:21 And it'll show me how to use the JSON load s dump functionality right there in the command line.

10:28 Now, sometimes it gives me like a stupid answer.

10:30 Like if you type that, how do I Python save?

10:32 How do I Python load JSON?

10:35 It just shows you JSON, which is stupid.

10:37 But you can do a dash A and it'll give you all the answers it's found on the internet related to that.

10:43 Usually somewhere in that list is something decent.

10:45 It has some sources like Stack Overflow and I don't know where they all come from, but they're all over the place.

10:50 It's cool.

10:51 I can say, how do I debug Python?

10:53 It'll show me the PDB commands.

10:54 I can say, how do I change my path in macOS?

10:57 And it'll show me how to do that, assuming I'm running Bash.

11:00 Things like that.

11:00 Okay.

11:01 I'm going to try that.

11:02 Yeah.

11:02 How do I put a worm on a hook?

11:05 Exactly.

11:06 Yeah, it doesn't work.

11:08 Yeah, it's got to be something technical, I think.

11:10 There's another one that I want to point out that I thought was really funny,

11:14 but actually it's kind of useful.

11:16 Oh, what's that?

11:16 It starts with a command.

11:17 It actually starts with a cartoon.

11:20 And basically the idea is if you type in a command that you think you know on the shell,

11:24 but you get it wrong, you can curse at your shell and it will potentially fix it for you.

11:30 Yeah, I love this.

11:30 So this thing is called the F.

11:32 I'm not going to complete it so we can keep our clean rating in iTunes, but the link is in the show notes.

11:38 And basically you type that after you've made a mistake on the shell and it goes,

11:41 oh, you probably meant this.

11:43 Are you trying to do this get checkout branch thing?

11:45 You did a little bit wrong.

11:46 The F.

11:47 Oh, here's the command.

11:48 Enter.

11:48 And it'll just automatically fix it for you.

11:50 It's beautiful.

11:50 Yeah, nice.

11:51 So plus you get a little, yeah, you get to let some frustration out on the thing, right?

11:55 Yeah.

11:56 All right.

11:57 What you got for us?

11:58 What's next?

11:58 Oh, yeah.

11:59 I got to go back to that tab.

12:00 We have a, yeah, we're at a listener.

12:04 So, you know, it just seems like we just did the last episode.

12:08 Just a few days ago.

12:09 How did that work?

12:09 That we had a listener commented on the last episode.

12:14 Last episode, we did mention some feedback from a listener about async speeding up their

12:20 some work.

12:21 And we have another one from a comment this time.

12:24 And this is a project that a listener shared with us.

12:28 And we've got a link in the show notes.

12:30 But it's a project called PyMarsis.

12:33 And I wasn't familiar with eMarsis.

12:37 It doesn't really matter.

12:38 But it's a cloud-based CRM.

12:41 And it's a Python interface.

12:42 But I'll just read this.

12:44 The gist of it is it sped it up.

12:45 And this is from Diego.

12:47 Thanks, Diego.

12:47 Another awesome episode.

12:49 Thanks, Michael and Brian.

12:51 And if you say that we do something awesome, we'll totally put you on the show.

12:54 Okay.

12:55 About async.io being awesome.

12:57 I had my own experience.

12:58 I had to send information to about 100 information about hundreds of thousands of users to a CRM

13:05 through their public API daily.

13:07 And with the synchronous stuff, it would have taken 50 hours a day, which you can't do that.

13:14 And they added async.

13:16 And it went down to 20 minutes.

13:18 So that's 150 times faster, which is awesome.

13:21 Yeah.

13:22 They were using requests before.

13:23 And in order to update their CRM, it took 50 hours per day problem.

13:28 So they switched to the AIo HTTP client stuff that has async and await in 20 minutes.

13:35 In fact, he told us an interesting story.

13:37 He said, the first time I ran it, it opened so many connections that it crashed his Mac.

13:42 And so he actually had to implement a semaphore limiting system, which is pretty cool.

13:47 Yeah.

13:47 And I did like that he added that, that he added the semaphores.

13:49 But the GitHub link that he had put up, I didn't see any semaphore usage in there.

13:54 So I've also, in our show notes, linked another article that talks about using asynchronous I.O.

14:00 with semaphores to limit how many connections you're making.

14:03 Yeah.

14:03 No, thanks, Diego, for putting that up there.

14:05 Anybody who wants to have a comment on the show, you know, you can contact us on Twitter where we're at, Python Bytes.

14:10 But also, every episode has a discuss section at the end.

14:15 So if you want to talk about an episode, share a link or whatever, drop in there.

14:18 So what's the link for this episode?

14:19 Pythonbytes.fm slash 18.

14:21 Yeah, yeah.

14:22 There you go.

14:22 Cool.

14:23 Yeah, it's super, I made it super easy to find.

14:25 And do you know what would be super easy is if somebody would make an easy way for me to do a pyramid installation.

14:31 That's right.

14:32 Because, so the way I made that slash 18 work, and you can still go to like slash episode slash list or whatever, is I use constraints in the routing infrastructure.

14:42 And so one of the things that I've been doing a lot of work with lately is with building pyramid web apps and trying to really help people jumpstart what they're up to, right?

14:52 Like I can go to pyramid and create a web app, and I get basically a web app that runs, and here's the view function, and here's a template.

15:00 Go.

15:00 Go write the web app from scratch.

15:02 And I kind of wanted to help the world not start from scratch, but start from near the end.

15:08 So I've been doing a lot with cookie cutter.

15:10 More on that later.

15:11 But I decided to create a cookie cutter template that is an opinionated cookie cutter template for creating pyramid web apps that have most of what you need pre-built and pre-configured.

15:22 And factored the way you would for a large professional app, not for like a one-file starter thing.

15:28 Yeah, that's great.

15:28 So I created a cookie cutter thing called cookie cutter dash pyramids --talk Python starter.

15:33 And so this came out of my Python for Entrepreneurs course, but you don't have to have anything to do with that to play with this template.

15:38 So what you do is it comes out with like when you just say create the website, it'll create like a shared layout.

15:44 So there's one place where all your general navigation and look and feel goes.

15:47 It has handlers for class management.

15:52 It has like secure user management using things like pass lib and other techniques, bootstrap, logbook, rollbar integration, MailChimp integration, outbound, email integration, power for static file management.

16:04 All just the list goes on and on.

16:06 But it's very much closer to where you need to be for a professional pyramid app to get started, in my opinion, rather than like basically here's one file.

16:16 Now create the whole thing from scratch.

16:18 So if people want to check that out, that's on GitHub.

16:20 You can just cookie cutter space the GitHub URL and you're off to the races.

16:23 It needs a little bit more documentation.

16:25 I'm going to work on that this week, but it's really close.

16:27 But it's a good start and I'm actually pretty excited about it.

16:31 And you've got one, your course is one of the very few that I've seen that really teaches people how to do pyramid as well.

16:38 Yeah, thanks.

16:38 Yeah, it's definitely one of the few ones on pyramid, which is great.

16:41 So here's like one more resource.

16:42 Basically, this is going to be part of the end of that course.

16:46 And, you know, the first time I heard about cookie cutter, I really kind of thought it was a little silly.

16:51 But it's actually turning out to be quite a useful tool for a lot of spaces.

16:56 Yeah, I definitely.

16:57 Yeah, the more I use it, the more I like it.

16:59 So I've definitely been putting some effort into it.

17:02 It's great.

17:02 Well, that's the end of our six.

17:04 So do you have anything to share with us, Michael?

17:07 No, nothing.

17:08 Nothing other than this template thing.

17:10 That's really all I have to share.

17:11 I've been just cranking on my classes.

17:12 I hear that you're probably still writing on your book.

17:16 That's getting close, though, isn't it?

17:17 Yeah, it is.

17:18 It's getting a lot closer.

17:19 And I wish it was closer than it is.

17:21 But I've got a whole bunch of...

17:24 Actually, I'm kind of overwhelmed with both work and with gratitude.

17:28 That I've had a lot of great people, incredible programmers and good writers help me out with

17:34 technical reviews on the first four chapters and a lot of great feedback.

17:38 And now I've got to go rewrite everything.

17:39 Thanks a lot, guys.

17:40 Thanks a lot.

17:42 No, that's awesome.

17:42 Yeah, I'm looking forward to the day where we can announce your book on here.

17:45 That'd be great.

17:45 Any day now with that book, huh?

17:47 No, any...

17:48 Hopefully, the goal still is to have something to sell by PyCon.

17:52 Beautiful.

17:53 All right, well, thanks, Brian, for sharing your news.

17:57 And thank you, everyone, for listening.

17:58 We'll catch you next week.

17:59 All right, thank you.

18:00 Thank you for listening to Python Bytes.

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18:16 We're always on the lookout for sharing something cool.

18:19 On behalf of myself and Brian Okken, this is Michael Kennedy.

18:23 Thank you for listening and sharing this podcast with your friends and colleagues.